bluuebunny/crossref_metadata_2025 huggingface dataset:
Eco-Friendly Hybrid PLLA/Chitosan/Trichoderma asperellum Nanomaterials as Biocontrol Dressings against Esca Disease in Grapevines
Authors: Spasova Mariya , Manolova Nevena , Rashkov Iliya , Naydenov Mladen
Published: June 2022

Fungi constitute the largest number of plant pathogens and are responsible for a range of serious plant diseases. Phaeomoniella chlamydospora (P. chlamydospora) and Phaeoacremonium aleophilum (P. aleophilum) are the main fungal pathogens causing esca disease in grapevines. On the other hand, there are beneficial microorganisms such as Trichoderma spp., which are able to control the growth of many phytopathogens. In the present study, innovative, eco-friendly hybrid nanomaterials were created by electrospinning PLLA, followed by the formation of a film of chitosan/Trichoderma asperellum (T. asperellum) spores on the fibers. The polymer carrier used in this study plays an active role in ensuring the viability of the biological agent during storage and, when placed in contact with moisture, ensures the agent’s normal development. Oligochitosan, as well as low molecular weight and high molecular weight chitosan, were used. The effects of chitosan molecular weight on the dynamic viscosity of chitosan solutions, film formation, mechanical properties, spore incorporation and growth were studied. The morphology of the prepared nanomaterials, and the presence of a film based on the formation of chitosan/T. asperellum spores on the PLLA fibers, were examined using scanning electron microscopy (SEM). The surface chemical compositions of the fibrous materials were studied using attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR). The mechanical properties of the obtained materials were also tested. The microbiological screening that was performed revealed that the eco-friendly hybrid nanomaterials incorporated with the beneficial microorganism, T. asperellum, to hamper the growth of the pathogenic P. chlamydospora and P. aleophilum fungi. The suppression rate depended on the viscosity of the chitosan solution used for the film formation. The use of oligochitosan resulted in the most effective infection of the material with T. asperellum spores. The environmentally friendly hybrid nanomaterials obtained in this study—in which the bioagent was embedded—are promising bioactive dressings for protecting grapevines against esca disease.
On the Use of Oxidation Induction Time as a Kinetic Parameter for Condition Monitoring and Lifetime Evaluation under Ionizing Radiation Environments
Authors: Lungulescu Eduard-Marius , Setnescu Radu , Ilie Sorin , Taborelli Mauro
Published: June 2022

The durability of polymeric materials is closely linked to their degradation under specific operating conditions when different stressors—general or specific, such as high temperature, sunlight or ionizing radiation, solvents, or mechanical stresses—act simultaneously, causing degradation. In the case of electrical cables, the durability of the electrically insulating materials used in their construction is an important parameter to ensure their operational security. In this work, we studied the degradation state of various types of electrical insulating materials from cables used in particle acceleration systems under European Organization for Nuclear Research (CERN) conditions (e.g., Super Proton Synchrotron, SPS) as a function of time and irradiation dose. A simple kinetic model was proposed based on the exponential decrease in the antioxidant amount in polymeric insulations. The onset oxidation time (OIT) values, used as an indicator of antioxidant concentration, were obtained from isothermal differential scanning calorimetry (DSC) and chemiluminescence (CL) measurements. Fourier transform infrared (FTIR) measurements were used to assess the degradation state and identify polymeric materials. The practical applicability of such a model in diagnosing degradation and in the subsequent evaluation of the remaining service life is of interest, as it can be adapted to a broad range of operating conditions and materials.
Intravitreal Injectable Hydrogels for Sustained Drug Delivery in Glaucoma Treatment and Therapy
Authors: Akulo Kassahun Alula , Adali Terin , Moyo Mthabisi Talent George , Bodamyali Tulin
Published: June 2022

Glaucoma is extensively treated with topical eye drops containing drugs. However, the retention time of the loaded drugs and the in vivo bioavailability of the drugs are highly influenced before reaching the targeted area sufficiently, due to physiological and anatomical barriers of the eye, such as rapid nasolacrimal drainage. Poor intraocular penetration and frequent administration may also cause ocular cytotoxicity. A novel approach to overcome these drawbacks is the use of injectable hydrogels administered intravitreously for sustained drug delivery to the target site. These injectable hydrogels are used as nanocarriers to intimately interact with specific diseased ocular tissues to increase the therapeutic efficacy and drug bioavailability of the anti-glaucomic drugs. The human eye is very delicate, and is sensitive to contact with any foreign body material. However, natural biopolymers are non-reactive, biocompatible, biodegradable, and lack immunogenic and inflammatory responses to the host whenever they are incorporated in drug delivery systems. These favorable biomaterial properties have made them widely applicable in biomedical applications, with minimal adversity. This review highlights the importance of using natural biopolymer-based intravitreal hydrogel drug delivery systems for glaucoma treatment over conventional methods.
Recent Advances in Production of Ecofriendly Polylactide (PLA)–Calcium Sulfate (Anhydrite II) Composites: From the Evidence of Filler Stability to the Effects of PLA Matrix and Filling on Key Properties
Authors: Murariu Marius , Paint Yoann , Murariu Oltea , Laoutid Fouad , Dubois Philippe
Published: June 2022

The melt–mixing of polylactide (PLA) with micro- and/or nanofillers is a key method used to obtain specific end-use characteristics and improvements of properties. So-called “insoluble” CaSO4 (CS) β-anhydrite II (AII) is a mineral filler recently considered for the industry of polymer composites. First, the study proves that AII made from natural gypsum by a specifically thermal treatment is highly stable compared to other CS forms. Then, PLAs of different isomer purity and molecular weights (for injection molding (IM) and extrusion), have been used to produce “green” composites filled with 20–40 wt.% AII. The composites show good thermal and mechanical properties, accounting for the excellent filler dispersion and stability. The stiffness of composites increases with the amount of filler, whereas their tensile strength is found to be dependent on PLA molecular weights. Interestingly, the impact resistance is improved by adding 20% AII into all investigated PLAs. Due to advanced kinetics of crystallization ascribed to the effects of AII and use of a PLA grade of high L-lactic acid isomer purity, the composites show after IM an impressive degree of crystallinity (DC), i.e., as high as 50%, while their Vicat softening temperature is remarkably increased to 160 °C, which are thermal properties of great interest for applications requiring elevated rigidity and heat resistance.
Starch as a Matrix for Incorporation and Release of Bioactive Compounds: Fundamentals and Applications
Authors: Falcão Lucas de Souza , Coelho Deborah Bento , Veggi Priscilla Carvalho , Campelo Pedro Henrique , Albuquerque Patrícia Melchionna , de Moraes Mariana Agostini
Published: June 2022

Due to its abundance in nature and low cost, starch is one of the most relevant raw materials for replacing synthetic polymers in a number of applications. It is generally regarded as non-toxic, biocompatible, and biodegradable and, therefore, a safe option for biomedical, food, and packaging applications. In this review, we focused on studies that report the use of starch as a matrix for stabilization, incorporation, or release of bioactive compounds, and explore a wide range of applications of starch-based materials. One of the key application areas for bioactive compounds incorporated in starch matrices is the pharmaceutical industry, especially in orally disintegrating films. The packaging industry has also shown great interest in using starch films, especially those with antioxidant activity. Regarding food technology, starch can be used as a stabilizer in nanoemulsions, thus allowing the incorporation of bioactive compounds in a variety of food types. Starch also presents potential in the cosmetic industry as a delivery system. However, there are still several types of industry that could benefit from the incorporation of starch matrices with bioactive compounds, which are described in this review. In addition, the use of microbial bioactive compounds in starch matrices represents an almost unexplored field still to be investigated.
One-Step Lignin Refining Process: The Influence of the Solvent Nature on the Properties and Quality of Fractions
Authors: Gordobil Oihana , Diaz René Herrera , Sandak Jakub , Sandak Anna
Published: June 2022

Heterogeneity of kraft lignin is one of the main limitations for the development of high-performance applications. Therefore, refining lignin using organic solvents is a promising strategy to obtain homogenous fractions with controlled quality in terms of structure and properties. In this work, one-step refining processes for hardwood kraft lignin using nine organic solvents of different chemical nature and polarity were carried out with the aim of investigating and understanding the effect of the type of organic solvent on the quality of resulting fractions. Structural features of both soluble and insoluble lignin fractions were assessed by GPC, Py-GC-MS, and FTIR linked to PCA analysis. Moreover, functional properties such as physical appearance, hygroscopicity, antioxidant capacity, and thermal properties were evaluated. The results evidenced the relationship between the nature and polarity of the solvents and the properties of the obtained soluble and insoluble fractions.
Development of Statistically Optimized Chemically Cross-Linked Hydrogel for the Sustained-Release Delivery of Favipiravir
Authors: Salawi Ahmad , Khan Arooj , Zaman Muhammad , Riaz Tehseen , Ihsan Hafsa , Butt Muhammad Hammad , Aman Waqar , Khan Rahima , Majeed Imtiaz , Almoshari Yosif , Alshamrani Meshal
Published: June 2022

Nowadays, the use of statistical approaches, i.e., Box–Bhenken designs, are becoming very effective for developing and optimizing pharmaceutical drug formulations. In the current work, a Box–Bhenken design was employed using Design Expert version 11 to develop, evaluate, and optimize a hydrogel-based formulation for sustained release of an antiviral drug, i.e., favipiravir. The hydrogels were prepared using the free radical polymerization technique. β-Cyclodextrin (β-CD), N,N′-methylenebisacrylamide (MBA), acrylic acid (AA), and potassium per sulfate (KPS) were used as oligomer, crosslinker, monomer, and initiator, respectively. Three variables, including β-CD (X1), MBA (X2), and AA (X3) were used at various concentrations for the preparation of hydrogels, followed by evaluation of a sol–gel fraction, swelling, porosity, chemical compatibilities, in vitro drug release, and entrapment efficiency. The results of the studies revealed that the degree of swelling was pH dependent, the best swelling being at pH 7.2 (1976%). On the other hand, for the low sol fraction of 0.2%, the reasonable porosity made the hydrogel capable of loading 99% favipiravir, despite its hydrophobic nature. The maximum entrapment efficiency (99%) was observed in optimized hydrogel formulation (F15). Similarly, in vitro drug release studies showed that the prepared hydrogels exhibited a good, sustained release effect till the 24th hour. The kinetic modelling of drug release data revealed that the Korsmeyer–Peppas model was best fit model, describing a diffusion type of drug release from the prepared hydrogels. Conclusively, the outcomes predict that the hydrogel-based system could be a good choice for developing a sustained-release, once-daily dosage form of favipiravir for improved patient compliance.
Biodegradable Nonwovens with Poultry Feather Addition as a Method for Recycling and Waste Management
Authors: Jóźwik-Pruska Jagoda , Wrześniewska-Tosik Krystyna , Mik Tomasz , Wesołowska Ewa , Kowalewski Tomasz , Pałczyńska Michalina , Walisiak Damian , Szalczyńska Magdalena
Published: June 2022

Geotextiles are used for separation, drainage, filtration and anti-erosion protection sealing, as well as to improve plant vegetation conditions. The research objective of this study was to verify the influence of the addition of poultry feathers on accelerating the biodegradation of nonwovens in cultivated soil. The tests were carried out in laboratory conditions and were based on the assessment of weight loss. The experiments confirmed the positive effects of the presence of waste that was rich in keratin on the time required for the biodegradation of the tested materials (the period of biodegradation was 8–24 weeks). Additionally, the influence of the biodegradation of the tested materials on the ecotoxicity was investigated and showed no negative effects on the microbiological activity (106 cfu). The research also included the determination of the carbon to nitrogen ratio of the test medium (blank, 12–14:1; with feather addition, 19–20:1). A statistical analysis revealed a correlation between the mechanical properties and the period of biological decomposition. This research was an important step for the management of poultry feather waste in agricultural applications. The tested materials could be seen an alternative that meets all ecological criteria, which seems to be a golden solution that not only allows the delivery of important nutrients to the soil, but also manages waste in an environmentally safe manner.
Investigating Potential Effects of Ultra-Short Laser-Textured Porous Poly-ε-Caprolactone Scaffolds on Bacterial Adhesion and Bone Cell Metabolism
Authors: Filipov Emil , Angelova Liliya , Vig Sanjana , Fernandes Maria Helena , Moreau Gerard , Lasgorceix Marie , Buchvarov Ivan , Daskalova Albena
Published: June 2022

Developing antimicrobial surfaces that combat implant-associated infections while promoting host cell response is a key strategy for improving current therapies for orthopaedic injuries. In this paper, we present the application of ultra-short laser irradiation for patterning the surface of a 3D biodegradable synthetic polymer in order to affect the adhesion and proliferation of bone cells and reject bacterial cells. The surfaces of 3D-printed polycaprolactone (PCL) scaffolds were processed with a femtosecond laser (λ = 800 nm; τ = 130 fs) for the production of patterns resembling microchannels or microprotrusions. MG63 osteoblastic cells, as well as S. aureus and E. coli, were cultured on fs-laser-treated samples. Their attachment, proliferation, and metabolic activity were monitored via colorimetric assays and scanning electron microscopy. The microchannels improved the wettability, stimulating the attachment, spreading, and proliferation of osteoblastic cells. The same topography induced cell-pattern orientation and promoted the expression of alkaline phosphatase in cells growing in an osteogenic medium. The microchannels exerted an inhibitory effect on S. aureus as after 48 h cells appeared shrunk and disrupted. In comparison, E. coli formed an abundant biofilm over both the laser-treated and control samples; however, the film was dense and adhesive on the control PCL but unattached over the microchannels.
Water-Soluble and -Insoluble Polymers and Biopolymers for Biomedical, Environmental, and Biological Applications
Authors: Stadler Florian J. , García-Peñas Alberto
Published: June 2022

In this Special Issue, several papers dedicated to biomedical, environmental, and biological applications have been assembled, representing different aspects of the field [...]
Frequency Domain Analysis of Fluid–Structure Interaction in Aircraft Hydraulic Pipe with Complex Constraints
Authors: Gao Haihai , Guo Changhong , Quan Lingxiao , Wang Shuai
Published: June 2022

This paper focuses on the frequency domain fluid–structure interaction (FSI) vibration characteristics of aircraft hydraulic pipe with complex constraints. The linear partial differential fourteen-equation model is applied to describe the nonlinear FSI dynamics of pipes conveying fluid with high-speed, high-pressure, a wide Reynolds number, and the vibration frequency range. The excitation, complex boundary, and middle constraint models of liquid-filled pipes are analytically established and added into the global model of the pipe system. These resulting models are solved by the improved Laplace transform transfer matrix method (LTTMM) in the frequency domain. Then, the dynamic response characteristics of an aircraft hydraulic pipe containing diverse constraints are investigated numerically and experimentally under four types of working conditions, and the improvement conditions for the numerical instabilities are presented. In general, the present method is highly efficient and convenient for rapid model parameter modifications, in order to be fully applicable to different pipe systems and analysis cases. The results reveal the complex resonant laws regarding aircraft hydraulic pipes with complex constraints in the broad frequency band, which can also provide theoretical reference and technical support for FSI vibration analysis and the control of aircraft hydraulic pipes.
Modelling Method and Application of Anti-Corrosion Pill Particles in Oil and Gas Field Wellbore Casing Annulus Based on the Discrete Element Method
Authors: Liu Dongtao , Qiao Chunshang , Wan Jun , Lu Yuliang , Song Jiming , Yao Zhenhe , Wei Xinjie , Yu Yajun
Published: June 2022

This study uses a self-developed anti-corrosion pill particle as the research object and develops the pill particle population modelling method in order to optimize the anti-corrosion process of oil and gas wellbore casing annuli. The shape of the pill particle is similar to a cylinder, according to the test and analysis of geometrical characteristics, and can be simplified into three types based on height, namely pill particles A (5.4 mm), B (5.8 mm), and C (6.2 mm). The multi-sphere approach is then used to create models of three different types of pill particles with varying degrees of precision. The feasibility and effectiveness of the modelling method for pill particle populations are proven by comparing the simulation results of the bulk density test and the angle of repose test. The results show that the 12-sphere models of pill particles A, B, and C are accurate representations of genuine pill particle morphologies and are adequate for simulating particle mechanics and flow processes. The applicability and practical use of the modelling method are then demonstrated using an example of a self-designed pill particle discharging mechanism. The results show that the modelling method can accurately simulate the pill discharging process and provide an accurate simulation model and theoretical basis for the optimization of the structural parameters, dimension parameters, and operating parameters of the discharging device.
Physicochemical Study of Albumin Nanoparticles with Chlorambucil
Authors: Kulig Karolina , Ziąbka Magdalena , Pilarczyk Kacper , Owczarzy Aleksandra , Rogóż Wojciech , Maciążek-Jurczyk Małgorzata
Published: June 2022

Currently, nanotechnology is considered a promising strategy to enhance drug solubility and other physicochemical properties. Albumin is a biopolymer that can be used in drug delivery systems due to its biodegradability and biocompatibility. The aim of this study was to prepare and characterize albumin nanoparticles with chlorambucil as a controlled drug delivery system. Different concentrations of chlorambucil were incubated with bovine serum albumin (BSA) in order to prepare nanoparticles using the desolvation method. As a result, nanoparticles in sizes ranging from 199.6 to 382.6 nm exhibiting high encapsulation efficiency of chlorambucil were obtained. A spectroscopic study revealed concentration-dependent changes in secondary structure of the albumin chain and in the hydrophobicity of chlorambucil. Based on the results obtained, it was concluded that the investigated structures may be used in the development of a drug delivery system.
Untargeted Metabolomics of Streptomyces Species Isolated from Soils of Nepal
Authors: Bhattarai Bibek Raj , Khadayat Karan , Aryal Niraj , Aryal Babita , Lamichhane Uttam , Bhattarai Keshab , Rana Nabin , Regmi Bishnu P. , Adhikari Achyut , Thapa Sandeep , Parajuli Niranjan
Published: June 2022

Actinomycetes are natural architects of numerous secondary metabolites including antibiotics. With increased multidrug-resistant (MDR) pathogens, antibiotics that can combat such pathogens are urgently required to improve the health care system globally. The characterization of actinomycetes available in Nepal is still very much untouched which is the reason why this paper showcases the characterization of actinomycetes from Nepal based on their morphology, 16S rRNA gene sequencing, and metabolic profiling. Additionally, antimicrobial assays and liquid chromatography-high resolution mass spectrometry (LC-HRMS) of ethyl acetate extracts were performed. In this study, we employed a computational-based dereplication strategy for annotating molecules which is also time-efficient. Molecular annotation was performed through the GNPS server, the SIRIUS platform, and the available databases to predict the secondary metabolites. The sequencing of the 16S rRNA gene revealed that the isolates BN6 and BN14 are closely related to Streptomyces species. BN14 showed broad-spectrum antibacterial activity with the zone of inhibition up to 30 mm against Staphylococcus aureus (MIC: 0.3051 µg/mL and MBC: 9.7656 µg/mL) and Shigella sonnei (MIC: 0.3051 µg/mL and MBC: 4.882 µg/mL). Likewise, BN14 also displayed significant inhibition to Acinetobacter baumannii, Klebsiella pneumoniae, and Salmonella typhi. GNPS approach suggested that the extracts of BN6 and BN14 consisted of diketopiperazines ((cyclo(D-Trp-L-Pro), cyclo(L-Leu-L-4-hydroxy-Pro), cyclo(L-Phe-D-Pro), cyclo(L-Trp-L-Pro), cyclo(L-Val-L-Pro)), and polypeptide antibiotics (actinomycin D and X2). Additional chemical scaffolds such as bacterial alkaloids (bohemamine, venezueline B, and G), anthramycin-type antibiotics (abbeymycin), lipase inhibitor (ebelactone B), cytocidal (oxopropaline D), antifungal and antitumor antibiotics (reductiomycin, streptimidone, deoxynybomycin), alaremycin, fumaramidmycin, anisomycin, and others were also annotated, which were further confirmed by using the SIRIUS platform, and literature survey. Thus, the bioprospecting of natural products from Streptomyces species from Nepal could be a potential source for the discovery of clinically significant and new antimicrobial agents in the future.
Process Analytical Technology for the Production of Parenteral Lipid Emulsions According to Good Manufacturing Practices
Authors: Grumbach Carsten , Czermak Peter
Published: June 2022

The good manufacturing practices (GMP) and process analytical technology (PAT) initiatives of the US Food and Drug Administration, in conjunction with International Council for Harmonisation (ICH) quality guidelines Q8, Q9, and Q10, ensure that manufacturing processes for parenteral formulations meet the requirements of increasingly strict regulations. This involves the selection of suitable process analytics for process integration and aseptic processing. In this article, we discuss the PAT requirements for the GMP-compliant manufacturing of parenteral lipid emulsions, which can be used for clinical nutrition or for the delivery of lipophilic active ingredients. There are risks associated with the manufacturing processes, including the potential for unstable emulsions and the formation of large droplets that can induce embolisms in the patient. Parenteral emulsions are currently monitored offline using a statistical approach. Inline analytics, supplemented by measurements of zeta potential, could minimize the above risks. Laser scanning technology, ultrasound attenuation spectroscopy, and photo-optical sensors combined with image analysis may prove to be useful PAT methods. In the future, these technologies could lead to better process understanding and control, thus improving production efficiency.
Thermal Stability Determination of Propylene Glycol Sodium Alginate and Ammonium Sulfate with Calorimetry Technology
Authors: Yao Chen , Liu Ye-Cheng , Wu Jie , Tang Yan , Zhai Juan , Shu Chi-Min , Jiang Jun-Cheng , Xing Zhi-Xiang , Huang Chung-Fu , Huang An-Chi
Published: June 2022

Propylene Glycol Alginate Sodium Sulfate (PSS) is widely produced and used in medicine as a marine drug for treating hyperlipidemia. During the sulfonation synthesis of PSS, the sulfonation of chlorosulfonic acid is exothermic. At high temperatures, the process can easily produce a large amount of ammonium sulfate. Ammonium sulfate adheres to PSS in crystal and participates in the sulfonation reaction. In this study, the sulfonation process of commercial PSS was reproduced in the laboratory using chlorosulfonic acid and formamide. We used differential scanning calorimetry and thermogravimetric analyzer to examine the thermal stability of PSS, and we used both differential and integral conversional methods to determine the appropriate thermokinetic models for this substance. We also established an autocatalytic model to study the conversion limit time and the maximum rate time of this substance. After calculation, the activation energy of this substance is no more than 60 kJ/mol, and it has other exothermic performances at different heating rates. The results help to optimize the sulfonation process of PSS and analyze the thermal risk of PSS with ammonium sulfate.
Does Policy on Plastic Waste Support Higher Waste Management Hierarchy Options?
Authors: Olatayo Kunle Ibukun , Mativenga Paul T. , Marnewick Annlizé L.
Published: June 2022

There is an urgent and growing need to further advance the plastic waste management system globally and in South Africa, due to the increasing impact of plastic waste. This study focused on the adequacy of plastic policies to sustainably manage plastic waste. Policies need to address the plastic material supply systems and the options up the waste hierarchy for them to be effective and support material circularity. The study used qualitative content analysis to assess how the evolution of plastic policies for plastic waste management in South Africa aligned with national plastic material flows and promoted options higher up the waste hierarchy. This was benchmarked with Norway and Germany, which have some of the highest plastic recycling rates. The results showed that the evolution of existing plastic policies for South Africa addresses stages of production, trade and consumption, and recycling. There is no focus on waste generation, collection and sorting. None aligned with the waste hierarchy options of rethink, reduce, reuse, repair, refurbish, remanufacture and repurpose. This policy gap supports the need for broader national plastic policy frameworks that embed a policy drive in the value chain points and promote the priority higher value measures of the waste hierarchy.
Belonging to the World through Body, Trust, and Trinity: Climate Change and Pastoral Care with University Students
Authors: Johannessen Christine Tind
Published: June 2022

This article explores how pastoral care is performed in an age of climate change. University students suffer from a wide range of stresses, reducing their well-being. Climate change compounds these stress reactions, even where students are not directly affected. As climate change affects concrete, material matters, human reactions to it may no longer be viewed and treated as purely inner psychic states. Thus, climate change disrupts usual divisions of material, social, and mental features as separate categories, underscoring instead the close-knit relations between them. Given the far-reaching ways climate change affects mental health, the article presents an ethnographical-theologically-driven model for basic conversation in pastoral care with students in the midst of escalating climate events. Making use of theories from anthropology, psychology, and theology, this article builds on in-depth interviews with Danish university chaplains about their pastoral care with students. The model extrapolates from these theories how pastoral care may support students in the era of climate change through a triad of organizing themes that come to the fore in the interviews: “Mothering the Content”, “Loving Vital Force”, and “Befriending the Environment”.
Communicating Transcendent Love: Interpersonal Encounter and Church–State Transitions in Fratelli tutti
Authors: Radwan Jon P. , Alfani Roger B.
Published: June 2022

This essay analyzes Pope Francis’ social teaching on relationality within his 2020 encyclical letter Fratelli tutti [Brothers all]. The relationship between the Church and modern nation-states is an important macro-level social dynamic, and Francis explains it by placing Church–State relations into a broader spiritual context of human communication and interaction. He articulates norms of fraternal contact growing from the bottom-up, that is, from interpersonal encounters through groups and movements on to countries and the United Nations. After a focused research question and discussion of critical method, this article offers a rhetorical critique of Fratelli tutti. To provide context, it explains the genres of Judeo-Christian and papal communication, Francis’ biography, and the immediate global context of his encyclical. Working within the text, this study details the Biblical foundations of his argument for “fraternity and social friendship” and shows how they are applied to global social media dystopia and accelerating migration/border crises. Conclusions include the utility of Francis’ contact terms in analyzing complex religio-political dynamics and their value in advancing peace.
Neomythology: A New Religious Mythology
Authors: Xidakis Ioannis
Published: June 2022

The purpose of this paper was to present the link between the myths in the plots of modern entertainment products, such as science fiction novels, movies, comic books and video games, with the motifs of New Religiosity. The plots employed in these products are of a mythical nature. This re-emergence of myth is once more taking centre stage today. The social sciences and humanities concerned with this phenomenon call it “neomythology”. Neomythology, in whatever form, as a comic book, video game, etc., shows gods and supernatural heroes or villains interacting with one another in certain ways. The ways these mythical elements are combined and displayed confirm that neomythology belongs to New Religiosity and repeats motifs of New Religions and New Age myths, such as the secularization of the absolute, that is to say, the placing of the transcendental element in the material and explainable world, the absolutisation not only of the acquisition of power but also those who bear it, the correlation of magic and technology, and the reuse and utilization of the mythology of the past and of traditional religious teachings, in order to produce a new myth.
Re-Imagining the Religious Beliefs and Cultural Practices of Indigenous Christian Youth
Authors: Del Castillo Fides A.
Published: June 2022

This paper aims to understand better the religious beliefs and cultural practices of Cordilleran Christian youth in the Philippines. By zooming in on the notions of God and practices of select Cordilleran Christian youth, this study endeavors to make the voices of indigenous Christian youth heard. Using the framework of Laylayan theology, this study explores the perspectives of the indigenous Christian youth on God, traditional practices, and lived experience, particularly during the COVID-19 pandemic. The results show the interconnectedness of faith and culture among select indigenous youth during this contemporary period. Their lived religious context informs society on the dialogue of life and experience.
Neuronal and Non-Neuronal GABA in COVID-19: Relevance for Psychiatry
Authors: Sfera Adonis , Thomas Karina G. , Sasannia Sarvin , Anton Jonathan J. , Andronescu Christina V. , Garcia Michael , Sfera Dan O. , Cummings Michael A. , Kozlakidis Zisis
Published: June 2022

Infection with SARS-CoV-2, the causative agent of the COVID-19 pandemic, originated in China and quickly spread across the globe. Despite tremendous economic and healthcare devastation, research on this virus has contributed to a better understanding of numerous molecular pathways, including those involving γ-aminobutyric acid (GABA), that will positively impact medical science, including neuropsychiatry, in the post-pandemic era. SARS-CoV-2 primarily enters the host cells through the renin–angiotensin system’s component named angiotensin-converting enzyme-2 (ACE-2). Among its many functions, this protein upregulates GABA, protecting not only the central nervous system but also the endothelia, the pancreas, and the gut microbiota. SARS-CoV-2 binding to ACE-2 usurps the neuronal and non-neuronal GABAergic systems, contributing to the high comorbidity of neuropsychiatric illness with gut dysbiosis and endothelial and metabolic dysfunctions. In this perspective article, we take a closer look at the pathology emerging from the viral hijacking of non-neuronal GABA and summarize potential interventions for restoring these systems.
A Standardized Protocol for Post-Partum Salpingectomy with Suture Ligation: A Prospective Feasibility Study
Authors: Hsieh Gillian L. , Wagar Matthew K. , Antony Kathleen M. , Masand Ramya , Anderson Matthew L.
Published: June 2022

Our objective is to define a standard protocol for post-partum salpingectomy and provide a prospective assessment of safety and feasibility of such a procedure. Thus, a protocol for performing post-partum salpingectomy in limited-resource environments was created based on contemporary practices for tubal ligation. Gravidae presenting for post-partum tubal ligation following vaginal delivery or at time of cesarean were prospectively approached and, if consent was obtained, enrolled. Outcomes were compared to a historical cohort of gravidae who underwent standard post-partum tubal ligation following vaginal birth or at the time of cesarean as per institutional standard of care. The primary outcome was operative time. One hundred and fifty-seven subjects underwent post-partum salpingectomy following cesarean or vaginal delivery (on post-partum days 0–2). Post-partum salpingectomy performed after vaginal delivery (n = 97) resulted in slightly longer operative times (39.1 ± 11.8 vs. 34.3 ± 13.1 min, p = 0.003) and slightly greater blood loss (21.0 ± 22.0 vs. 13.4 ± 17.3 mL, p = 0.001) than modified Pomeroy tubal ligation (n = 200). Post-partum salpingectomy at cesarean resulted in no difference in estimated blood loss, but slightly longer operative times compared to Parkland tubal ligations (99.5 ± 47.3 vs. 86.5 ± 33.9 min, p = 0.048). Surgical complications for post-partum salpingectomy were similar to controls, regardless of when the procedure was performed. In conclusion, a standardized protocol created for post-partum salpingectomy using suture ligation is feasible and safe.
Analyzing How the Social Security Reserve Fund in Spain Affects the Sustainability of the Pension System
Authors: Gómez-Déniz Emilio , Pérez-Rodríguez Jorge V. , Sosvilla-Rivero Simón
Published: June 2022

Faced with the need to adjust public pension systems to meet changing demographic, economic and social conditions, most developed countries have created government reserve funds to ensure macroeconomic sustainability. This paper aims to study the importance that this reserve fund plays in the sustainability of the Spanish public pension system. Using data for the 2000 to 2019 period (20 observations) on the main variables impacting on the system, we calculate probabilities and other indicators of its unsustainability in relation to the reserve fund. Our model accurately reflects certain aspects of the data, and suggests that the probability of unsustainability is inversely associated with the size of the reserve fund, but that this relation is moderated by the heterogeneity of the members of the pension system. Moreover, the probability of unsustainability increases in line with the pension system deficit, the time elapsed until unsustainability is reached is shorter when the Reserve Fund balance falls, and the size of this fund at which the system becomes unsustainable diminishes with the probability of unsustainability.
Meta-Learning Approaches for Recovery Rate Prediction
Authors: Gambetti Paolo , Roccazzella Francesco , Vrins Frédéric
Published: June 2022

While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine the predictions from 20 candidates of linear, nonlinear and rule-based algorithms, and we exploit a data set of predictors including security-specific factors, macro-financial indicators and measures of economic uncertainty. We find that the most promising approach consists of model combinations trained on security-specific characteristics and a limited number of well-identified, theoretically sound recovery rate determinants, including uncertainty measures. Our research provides useful indications for practitioners and regulators targeting more reliable risk measures in designing micro- and macro-prudential policies.
Satellite On-Board Change Detection via Auto-Associative Neural Networks
Authors: Guerrisi Giorgia , Del Frate Fabio , Schiavon Giovanni
Published: June 2022

The increase in remote sensing satellite imagery with high spatial and temporal resolutions has enabled the development of a wide variety of applications for Earth observation and monitoring. At the same time, it requires new techniques that are able to manage the amount of data stored and transmitted to the ground. Advanced techniques for on-board data processing answer this problem, offering the possibility to select only the data of interest for a specific application or to extract specific information from data. However, the computational resources that exist on-board are limited compared to the ground segment availability. Alternatively, in applications such as change detection, only images containing changes are useful and worth being stored and sent to the ground. In this paper, we propose a change detection scheme that could be run on-board. It relies on a feature-based representation of the acquired images which is obtained by means of an auto-associative neural network (AANN). Once the AANN is trained, the dissimilarity between two images is evaluated in terms of the extracted features. This information can be subsequently turned into a change detection result. This study, which presents one of the first techniques for on-board change detection, yielded encouraging results on a set of Sentinel-2 images, even in light of comparison with a benchmark technique.
Self-Supervised Pre-Training with Bridge Neural Network for SAR-Optical Matching
Authors: Qian Lixin , Liu Xiaochun , Huang Meiyu , Xiang Xueshuang
Published: June 2022

Due to the vast geometric and radiometric differences between SAR and optical images, SAR-optical image matching remains an intractable challenge. Despite the fact that the deep learning-based matching model has achieved great success, SAR feature embedding ability is not fully explored yet because of the lack of well-designed pre-training techniques. In this paper, we propose to employ the self-supervised learning method in the SAR-optical matching framework, in order to serve as a pre-training strategy for improving the representation learning ability of SAR images as well as optical images. We first use a state-of-the-art self-supervised learning method, Momentum Contrast (MoCo), to pre-train an optical feature encoder and an SAR feature encoder separately. Then, the pre-trained encoders are transferred to an advanced common representation learning model, Bridge Neural Network (BNN), to project the SAR and optical images into a more distinguishable common feature representation subspace, which leads to a high multi-modal image matching result. Experimental results on three SAR-optical matching benchmark datasets show that our proposed MoCo pre-training method achieves a high matching accuracy up to 0.873 even for the complex QXS-SAROPT SAR-optical matching dataset. BNN pre-trained with MoCo outperforms BNN with the most commonly used ImageNet pre-training, and achieves at most 4.4% gains in matching accuracy.
Graph-Represented Broad Learning System for Landslide Susceptibility Mapping in Alpine-Canyon Region
Authors: Xu Lili , Chen C. L. Philip , Qing Feng , Meng Xingmin , Zhao Yan , Qi Tianjun , Miao Tianyao
Published: June 2022

Zhouqu County is located at the intersection of two active structural belts in the east of the Qinghai-Tibet Plateau, which is a rare, high-incidence area of landslides, debris flow, and earthquakes on a global scale. The complex regional geological background, the fragile ecological environment, and the significant tectonic activities have caused great difficulties for the dynamic susceptibility assessment and prediction of landslides in the study area. Specifically, Zhouqu is a typical alpine-canyon region in geomorphology; currently there is still a lack of a landslide susceptibility assessment study for this particular type of area. Therefore, the development of landslide susceptibility mapping (LSM) in this area is of great significance for quickly grasping the regional landslide situation and formulating disaster reduction strategies. In this article, we propose a graph-represented learning algorithm named GBLS within a broad framework in order to better extract the spatially relevant characteristics of the geographical data and to quickly obtain the change pattern of landslide susceptibility according to the frequent variation (increase or decrease) of the data. Based on the broad structure, we construct a group of graph feature nodes through graph-represented learning to make better use of geometric correlation of data to upgrade the precision. The proposed method maintains the efficiency and effectiveness due to its broad structure, and even better, it is able to take advantage of incremental data to complete fast learning methodology without repeated calculation, thus avoiding time waste and massive computation consumption. Empirical results verify the excellent performance with high efficiency and generalization of GBLS on the 407 landslides in the study area inventoried by remote sensing interpretation and field investigation. Then, the landslide susceptibility map is drawn to visualize the landslide susceptibility assessment according to the result of GBLS with the highest AUC (0.982). The four most influential factors were ranked out as rainfall, NDVI, aspect, and Terrain Ruggedness Index. Our research provides a selection criterion that can be referenced for future research where GBLS is of great significance in LSM of the alpine-canyon region. It plays an important role in demonstrating and popularizing the research in the same type of landform environment. The LSM would help the government better prevent and confine the risk of landslide hazards in the alpine-canyon region of Zhouqu.
Water Multi-Parameter Sampling Design Method Based on Adaptive Sample Points Fusion in Weighted Space
Authors: Zhai Mingjian , Tao Zui , Zhou Xiang , Lv Tingting , Wang Jin , Li Ruoxi
Published: June 2022

The spatial representativeness of the in-situ data is an important prerequisite for ensuring the reliability and accuracy of remote sensing product retrieval and verification. Limited by the collection cost and time window, it is essential to simultaneously collect multiple water parameter data in water tests. In the shipboard measurements, sampling design faces problems, such as heterogeneity of water quality multi-parameter spatial distribution and variability of sampling plan under multiple constraints. Aiming at these problems, a water multi-parameter sampling design method is proposed. This method constructs a regional multi-parameter weighted space based on the single-parameter sampling design and performs adaptive weighted fusion according to the spatial variation trend of each water parameter within it to obtain multi-parameter optimal sampling points. The in-situ datasets of three water parameters (chlorophyll a, total suspended matter, and Secchi-disk Depth) were used to test the spatial representativeness of the sampling method. The results showed that the sampling method could give the sampling points an excellent spatial representation in each water parameter. This method can provide a fast and efficient sampling design for in-situ data for water parameters, thereby reducing the uncertainty of inversion and the validation of water remote sensing products.
Hyperspectral Reflectance Proxies to Diagnose In-Field Fusarium Head Blight in Wheat with Machine Learning
Authors: Mustafa Ghulam , Zheng Hengbiao , Khan Imran Haider , Tian Long , Jia Haiyan , Li Guoqiang , Cheng Tao , Tian Yongchao , Cao Weixing , Zhu Yan , Yao Xia
Published: June 2022

Hyperspectral reflectance (HR) technology as proxy approach to diagnose fusarium head blight (FHB) in wheat crop could be a real-time and non-invasive approach for its in-field management to reduce grain damage. In-field canopy’s non-imaging HR (400–2400 nm using ground-based spectrometer system), photosynthesis rate (Pn) and disease severity (DS) data were simultaneously acquired from artificially inoculated wheat plots over a period of two years (2020 and 2021) in the field. Subsequently, continuous wavelet transform (CWT) was employed to select the consistent spectral bands (CSBs) and to develop the canopy-based difference indices with criterion of variable importance score using random forest—recursive feature elimination. Thereby, different machine learning algorithms were employed for FHB classification and multivariate estimation, and linear regression models to evaluate the newly developed indices against conventional vegetation indices. The results showed that inoculation reduced the Pn rate of spikes, elevated reflectance in visible and short-wave infrared regions and decreased in near infrared region at different days after inoculation (DAI). CWT analysis selected five CSBs (401, 460, 570, 786 and 840 nm) employing datasets from 2020 and 2021. These spectral bands were employed to develop wheat fusarium canopy indices (WFCI1 and WFCI2). Considering the average classification accuracy (ACA) in both years of experiments, WFCI1 manifested a maximum ACA of 75% at 5 DAI with DS of 9.73% which raised to 100% at 10 DAI with a DS of 18%. ACA mentions the averaged results of all machine learning classifiers (MLC). While in the perspective of MLC, random forest (RF) outperformed the rest of the MLC, individually, it revealed 100% classification accuracy through WFCI1 at DS 10.78% on the eight DAI. The univariate estimation of disease based on WFCI1 and WFCI2 with independent data produced R2 and root mean square error (RMSE) values of 0.80 and 14.7, and 0.81 and13.50, respectively. However, Knn regression analysis with both canopy indices (WFCI1 and WFCI2) manifested the maximum accuracy for disease estimation with RMSE of 11.61 and R2 = 0.83. Conclusively, the newly proposed HR indices show great potential as proxy approach for detecting FHB at early stage and understanding the physical state of crops in field conditions for the better management and control of plant diseases.