bluuebunny/crossref_metadata_2025 huggingface dataset:
BD-AcAc2 Mitigates Chronic Colitis in Rats: A Promising Multi-Pronged Approach Modulating Inflammasome Activity, Autophagy, and Pyroptosis
Authors: Saber Sameh , Alamri Mohannad , Alfaifi Jaber , Saleh Lobna , Abdel-Ghany Sameh , Aboregela Adel , Farrag Alshaimaa , Almaeen Abdulrahman , Adam Masoud , AlQahtani AbdulElah , Eleragi Ali , Abdel-Reheim Mustafa , Ramadan Heba , Mohammed Osama
Published: July 2023

Ulcerative colitis is a chronic and incurable form of inflammatory bowel disease that can increase the risk of colitis-associated cancer and mortality. Limited treatment options are available for this condition, and the existing ones often come with non-tolerable adverse effects. This study is the first to examine the potential benefits of consuming BD-AcAc2, a type of ketone ester (KE), and intermittent fasting in treating chronic colitis induced by dextran sodium sulfate (DSS) in rats. We selected both protocols to enhance the levels of β-hydroxybutyrate, mimicking a state of nutritional ketosis and early ketosis, respectively. Our findings revealed that only the former protocol, consuming the KE, improved disease activity and the macroscopic and microscopic features of the colon while reducing inflammation scores. Additionally, the KE counteracted the DSS-induced decrease in the percentage of weight change, reduced the colonic weight-to-length ratio, and increased the survival rate of DSS-insulted rats. KE also showed potential antioxidant activities and improved the gut microbiome composition. Moreover, consuming KE increased the levels of tight junction proteins that protect against leaky gut and exhibited anti-inflammatory properties by reducing proinflammatory cytokine production. These effects were attributed to inhibiting NFκB and NLRP3 inflammasome activation and restraining pyroptosis and apoptosis while enhancing autophagy as revealed by reduced p62 and increased BECN1. Furthermore, the KE may have a positive impact on maintaining a healthy microbiome. To conclude, the potential clinical implications of our findings are promising, as BD-AcAc2 has a greater safety profile and can be easily translated to human subjects.
Incretins-Based Therapies and Their Cardiovascular Effects: New Game-Changers for the Management of Patients with Diabetes and Cardiovascular Disease
Authors: Bernardini Federico , Nusca Annunziata , Coletti Federica , La Porta Ylenia , Piscione Mariagrazia , Vespasiano Francesca , Mangiacapra Fabio , Ricottini Elisabetta , Melfi Rosetta , Cavallari Ilaria , Ussia Gian Paolo , Grigioni Francesco
Published: July 2023

Atherosclerosis is the leading cause of death worldwide, especially in patients with type 2 diabetes mellitus (T2D). GLP-1 receptor agonists and DPP-4 inhibitors were demonstrated to play a markedly protective role for the cardiovascular system beyond their glycemic control. Several cardiovascular outcome trials (CVOT) reported the association between using these agents and a significant reduction in cardiovascular events in patients with T2D and a high cardiovascular risk profile. Moreover, recent evidence highlights a favorable benefit/risk profile in myocardial infarction and percutaneous coronary revascularization settings. These clinical effects result from their actions on multiple molecular mechanisms involving the immune system, platelets, and endothelial and vascular smooth muscle cells. This comprehensive review specifically concentrates on these cellular and molecular processes mediating the cardiovascular effects of incretins-like molecules, aiming to improve clinicians’ knowledge and stimulate a more extensive use of these drugs in clinical practice as helpful cardiovascular preventive strategies.
Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review
Authors: Del Valle-Moreno Paula , Suarez-Casillas Paloma , Mejías-Trueba Marta , Ciudad-Gutiérrez Pablo , Guisado-Gil Ana , Gil-Navarro María , Herrera-Hidalgo Laura
Published: July 2023

Background: Pharmacokinetic nomograms, equations, and software are considered the main tools available for Therapeutic Drug Monitoring (TDM). Model-informed precision dosing (MIPD) is an advanced discipline of TDM that allows dose individualization, and requires a software for knowledge integration and statistical calculations. Due to its precision and extensive applicability, the use of these software is widespread in clinical practice. However, the currently available evidence on these tools remains scarce. Objectives: To review and summarize the available evidence on MIPD software tools to facilitate its identification, evaluation, and selection by users. Methods: An electronic literature search was conducted in MEDLINE, EMBASE, OpenAIRE, and BASE before July 2022. The PRISMA-ScR was applied. The main inclusion criteria were studies focused on developing software for use in clinical practice, research, or modelling. Results: Twenty-eight software were classified as MIPD software. Nine are currently unavailable. The remaining 19 software were described in depth. It is noteworthy that all MIPD software used Bayesian statistical methods to estimate drug exposure and all provided a population model by default, except NONMEN. Conclusions: Pharmacokinetic software have become relevant tools for TDM. MIPD software have been compared, facilitating its selection for use in clinical practice. However, it would be interesting to standardize the quality and validate the software tools.
The Peptide Salamandrin-I Modulates Components Involved in Pyroptosis and Induces Cell Death in Human Leukemia Cell Line HL-60
Authors: Silva-Carvalho Amandda Évelin , Oliveira Nakaly Natiely de , Machado Julia Viana Lafetá , Moreira Daniel Carneiro , Brand Guilherme Dotto , Leite José Roberto S. A. , Plácido Alexandra , Eaton Peter , Saldanha-Araujo Felipe
Published: July 2023

Amphibian secretions have been extensively investigated for the production of bioactive molecules. Salamandrin-I is an antioxidant peptide, isolated from the skin secretion of the fire salamander, that has induced no toxicity in microglia or erythrocytes. Importantly, the administration of antioxidants may constitute an adequate therapeutic approach to cancer treatment. Here, with the purpose of better characterizing the therapeutic potential of salamandrin-I, we investigated whether this antioxidant peptide also exerts anticancer activity, using the human leukemia cell line HL-60 as a cancer model. Salamandrin-I treatment induced a significant reduction in HL-60 proliferation, which was accompanied by cell cycle arrest. Furthermore, the peptide-induced cell death showed a significant increase in the LDH release in HL-60 cells. The cellular toxicity exerted by salamandrin-I is possibly related to pyroptosis, since the HL-60 cells showed loss of mitochondrial membrane potential and hyperexpression of inflammasome components following the peptide treatment. This is the first demonstration of the anticancer potential of the salamandrin-I peptide. Such results are important, as they offer relevant insights into the field of cancer therapy and allow the design of future bioactive molecules using salamandrin-I as a template.
Gold Nanoparticles: Construction for Drug Delivery and Application in Cancer Immunotherapy
Authors: Huang Huiqun , Liu Ronghui , Yang Jie , Dai Jing , Fan Shuhao , Pi Jiang , Wei Yubo , Guo Xinrong
Published: July 2023

Cancer immunotherapy is an innovative treatment strategy to enhance the ability of the immune system to recognize and eliminate cancer cells. However, dose limitations, low response rates, and adverse immune events pose significant challenges. To address these limitations, gold nanoparticles (AuNPs) have been explored as immunotherapeutic drug carriers owing to their stability, surface versatility, and excellent optical properties. This review provides an overview of the advanced synthesis routes for AuNPs and their utilization as drug carriers to improve precision therapies. The review also emphasises various aspects of AuNP-based immunotherapy, including drug loading, targeting strategies, and drug release mechanisms. The application of AuNPs combined with cancer immunotherapy and their therapeutic efficacy are briefly discussed. Overall, we aimed to provide a recent understanding of the advances, challenges, and prospects of AuNPs for anticancer applications.
Manganese-Doped Carbon Dots as a Promising Nanoprobe for Luminescent and Magnetic Resonance Imaging
Authors: Stepanidenko Evgeniia A. , Vedernikova Anna A. , Badrieva Zilya F. , Brui Ekaterina A. , Ondar Saikho O. , Miruschenko Mikhail D. , Volina Olga V. , Koroleva Aleksandra V. , Zhizhin Evgeniy V. , Ushakova Elena V.
Published: July 2023

Luminescent carbon nanodots (CDs) are a low-toxic nanomaterial with a tunable emission in a wide spectral range and with various functional groups on the surface. Therefore, CDs can prospectively serve as luminescent nanoprobes for biomedical applications, such as drug-delivery, visualization, sensing, etc. The doping of CDs with paramagnetic or transition metals allows the expansion of the range of applications of CDs and the fabrication of a multimodal nanoprobe for bioimaging. Here, we developed CDs doped with manganese (Mn) based on commonly used precursors—o-phenylenediamine or citric acid and formamide. The chemical structure, morphology, optical properties, and magnetic resonance responses have been carefully studied. The obtained CDs are up to 10 nm, with emissions observed in the 400–650 nm spectral region. CDs exhibit an ability to reduce both T1 and T2 relaxation times by up to 6.4% and 42.3%, respectively. The high relaxivity values suggest the use of CDs as promising dual-mode contrast agents for T1 and T2 MRI. Therefore, our developed CDs can be utilized as a new multifunctional nanoscale probe for photoluminescent and magnetic resonance bioimaging.
Tunable Multiple Surface Plasmonic Bending Beams into Single One by Changing Incident Light Wavelength
Authors: Zhang Hang , Wang Liang , Li Xueli , Li Xiaoming , Li Hui
Published: July 2023

Controllable surface plasmonic bending beams (SPBs) with propagating along bending curves have a wide range of applications in the fields of fiber sensors, optical trapping, and micro-nano manipulations. In terms of designing and optimizing controllable SPB generators, there is great significance in realizing conversion between multiple SPBs and single SPB without rebuilding metasurface structures. In this study, a SPB generator, composed of an X-shaped nanohole array, is proposed to realize conversion between multiple SPBs and a single one by changing the incident light wavelength. The Fabry–Pérot (F–P) resonance effect of SPPs in nanoholes and localized surface plasmonic (LSP) resonance of the nanohole are utilized to explain this conversion. It turns out that the relationship between the electric field intensities of SPBs and the polarization angle of incident light satisfies the sine distribution, which is consistent with dipole radiation theory. In addition, we also find that the electric field intensities of SPBs rely on the width, length, and angle of the X-shaped nanohole. These findings could help in designing and optimizing controllable and multi-functions SPBs converters.
The Effect of Sample Preparation Techniques on Lignin Fourier Transform Infrared Spectroscopy
Authors: Blindheim Fredrik Heen , Ruwoldt Jost
Published: July 2023

The characterization and quantification of functional groups in technical lignins are among the chief obstacles of the utilization of this highly abundant biopolymer. Although several techniques were developed for this purpose, there is still a need for quick, cost-efficient, and reliable quantification methods for lignin. In this paper, three sampling techniques for fourier transform infrared (FTIR) spectroscopy were assessed both qualitatively and quantitatively, delineating how these affected the resultant spectra. The attenuated total reflectance (ATR) of neat powders and DMSO-d6 solutions, as well as transmission FTIR using the KBr pelleting method (0.5 wt%), were investigated and compared for eight lignin samples. The ATR of neat lignins provided a quick and easy method, but the signal-to-noise ratios in the afforded spectra were limited. The ATR of the DMSO-d6 solutions was highly concentration dependent, but at a 30 wt%, acceptable signal-to-noise ratios were obtained, allowing for the lignins to be studied in the dissolved state. The KBr pelleting method gave a significant improvement in the smoothness and resolution of the resultant spectra compared to the ATR techniques. Subsequently, the content of phenolic OH groups was calculated from each FTIR mode, and the best correlation was seen between the transmission mode using KBr pellets and the ATR of the neat samples (R2 = 0.9995). Using the titration measurements, the total OH and the phenolic OH group content of the lignin samples were determined as well. These results were then compared to the FTIR results, which revealed an under-estimation of the phenolic OH groups from the non-aqueous potentiometric titration, which was likely due to the differences in the pKa between the lignin and the calibration standard 4-hydroxybenzoic acid. Further, a clear correlation was found between the lower Mn and the increased phenolic OH group content via SEC analyses. The work outlined in this paper give complementary views on the characterization and quantification of technical lignin samples via FTIR.
Electrically and Thermally Triggered Three-Dimensional Graphene-Foam-Reinforced Shape Memory Epoxy Composites
Authors: Idowu Adeyinka , Thomas Tony , Bustillos Jenniffer , Boesl Benjamin , Agarwal Arvind
Published: July 2023

Shape memory polymer (SMP) epoxy composites have attracted significant attention due to their easy processing, lightweight nature, and ability to recover strain. However, their limited recovery rate and inferior mechanical properties have hindered their functional applications. This research explores the potential of three-dimensional (3D) graphene foam (GrF) as a highly efficient reinforcement for SMP epoxy composites. We demonstrated that the incorporation of a mere 0.13 wt.% GrF into mold-cast SMP epoxy leads to a 19% increase in the glass transition temperature (Tg). To elucidate the reinforcing mechanism, we fabricated and extensively analyzed composites with varying weight percentages of GrF. The GrF-based SMP epoxy composite exhibits a 57% increase in thermal conductivity, measuring 0.296 W mK−1 at 70 °C, due to the interconnected 3D graphene network within the matrix. Notably, this composite also demonstrates remarkable electrical conductivity, making it suitable for dual-triggering applications. The GrF-SMP epoxy composite achieves a maximum shape recovery ratio and a significant 23% improvement in the recovery rate, effectively addressing the issue of slow recovery associated with SMPs. We investigated the effect of switching temperatures on the shape recovery rate. We identified the optimal triggering temperature to initiate shape recovery for epoxy SMP and GrF-epoxy SMP as thermal energy equivalent to Tg + 20 °C. Additionally, we fabricated a bird-shaped composite using GrF reinforcement, which showcases self-healing capabilities through the crack opening and closure and serves as a tangible demonstration of the transformative potential of the composite. These GrF-epoxy SMP composites, responsive to stimuli, hold immense promise for diverse applications, such as mechanical systems, wearable sensors, morphing wings, foldable robots, and antennas.
Microfluidic-Based Continuous Fabrication of Ultrathin Hydrogel Films with Controllable Thickness
Authors: Ouyang Xiaozhi , Huang Cheng , Cheng Sha , Zhang Pengchao , Chen Wen
Published: July 2023

Ultrathin hydrogel films composed of cross-linked polymer networks swollen by water, with soft and moisturized features similar to biological tissue, play a vital role in flexible biosensors and wearable electronics. However, achieving efficient and continuous fabrication of such films remains a challenge. Here, we present a microfluidic-based strategy for the continuous fabrication of free-standing ultrathin hydrogel films by using laminar flow, which can be precisely controlled in the micrometer scale. Compared with conventional methods, the microfluidic-based method shows advantages in producing hydrogel films with a high homogeneity as well as maintaining the structural integrity, without the need of supporting substrates and sophisticated equipment. This strategy allows the precise control over the thickness of the hydrogel films ranging from 15 ± 0.2 to 39 ± 0.5 μm, by adjusting the height of the microfluidic channels, with predictable opportunities for scaling up. Therefore, our strategy provides a facile route to produce advanced thin polymer films in a universal, steerable, and scalable manner and will promote the applications of thin polymer films in biosensors and wearable electronics.
Films of Poly(Hydroxybutyrate) (PHB) and Copper with Antibacterial Activity
Authors: Quispe Mayte M. , Villanueva María E. , Copello Guillermo J. , López Olivia V. , Villar Marcelo A.
Published: July 2023

Poly(3-hydroxybutyrate), PHB, is a hydrophobic biopolymer with good mechanical and barrier properties. However, neat PHB is a semicrystalline polymer with a relative high degree of crystallinity and poor film properties. In this work, this biopolymer was plasticized with glycerol tributyrate and functionalized with copper (II) sulfate, allowing us to obtain biodegradable antimicrobial flexible films. Films with the minimum inhibitory concentration (MIC) of copper (II) sulfate presented a higher roughness than neat PHB films. The presence of plasticizer significantly improved the copper sulfate diffusion process, which was evidenced by a greater inhibition halo for plasticized materials compared to unplasticized ones, at the same salt concentration. Plasticized PHB with 2.5% copper (II) sulfate inhibited both Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomona aeruginosa) bacteria, as determined by the bacterial inhibition halo. In addition, neat PHB films and PHB containing copper (II) sulfate did not show in vitro cytotoxicity in the L-929 cell line. Thus, plasticized PHB functionalized with copper (II) sulfate can be used as biodegradable antimicrobial flexible films for different applications.
Multi-Geometry Parameters Optimization of Large-Area Roll-to-Roll Nanoimprint Module Using Grey Relational Analysis and Artificial Neural Network
Authors: Nguyen Truong Sinh , Gafurov Anton Nailevich , Jo Jeongdai , Lee Taik-Min , Lee Seung-Hyun , Kim Kyunghoon
Published: July 2023

Micro- and nanofabrication on polymer substrate is integral to the development of flexible electronic devices, including touch screens, transparent conductive electrodes, organic photovoltaics, batteries, and wearable devices. The demand for flexible and wearable devices has spurred interest in large-area, high-throughput production methods. Roll-to-roll (R2R) nanoimprint lithography (NIL) is a promising technique for producing nano-scale patterns rapidly and continuously. However, bending in a large-scale R2R system can result in non-uniform force distribution during the imprinting process, which reduces pattern quality. This study investigates the effects of R2R imprinting module geometry parameters on force distribution via simulation, using grey relational analysis to identify optimal parameter levels and ANOVA to determine the percentage of each parameter contribution. The study also investigates the length and force ratio on a backup roller used for bending compensation. The simulation results and the artificial neural network (ANN) model enable the prediction of nip pressure and force distribution non-uniformity along the roller, allowing the selection of the optimal roller geometry and force ratio for minimal non-uniformity on a specific R2R system. An experiment was conducted to validate the simulation results and ANN model.
Evaluation of the Effects of Different Polishing Protocols on the Surface Characterizations of 3D-Printed Acrylic Denture Base Resins: An In Vitro Study
Authors: Al-Dulaijan Yousif A.
Published: July 2023

Chairside polishing kits are an alternative to laboratory polishing techniques. The effects of using a chairside polishing kit on a three-dimensional (3D)-printed acrylic denture base (ADB) have not been reported previously. Thus, this study aimed to evaluate the effects of different chairside polishing techniques on the surface characterizations of ABD, including surface roughness average (Ra), average maximum profile height (Rz), and scanning electron microscopy (SEM) representations. One hundred and twenty disc-shaped specimens were fabricated from one conventional heat-polymerized (HP) ADB resin and two 3D-printed (Asiga (AS) and NextDent (ND)) ADB resins (n = 40 per material). Each group was further divided based on the polishing protocol (n = 10) as follows: conventional polishing protocol (C), microdont chairside polishing kit (M), shofu chairside polishing kit (S), and an unpolished group (U). The Ra and Rz values were measured using an optical profilometer. Two-way ANOVA and post hoc tests were used for data analysis (α = 0.05) at significant levels. In unpolished groups, there was a statistically significant difference between HP-U vs. AS-U and ND-U groups (p < 0.0001). For Ra, the lowest values were observed in HP-C, AS-S, and ND-C. While the highest values were shown in all unpolished groups. Within the material, there were statistically significant differences between the three polishing protocols (C, M, and S) vs. unpolished (p < 0.0001), while there was no significant between C, M, and S groups (p = 0.05). The Rz values had the same pattern as the Ra values. The two chairside polishing kits were comparable to conventional polishing techniques, and they can be recommended for clinical application.
Vegetable Cellulose Fibers in Natural Rubber Composites
Authors: R. Lozada Elizabeth , Gutiérrez Aguilar Carlos M. , Jaramillo Carvalho Jaime A. , Sánchez Juan C. , Barrera Torres Giovanni
Published: July 2023

In the last decade, natural fibers have had a significant impact on the research and development of innovative composites made with natural rubber, improving their properties over those of their counterparts that incorporate polluting synthetic fibers. In recent years, this fact has stimulated the research into several modified natural rubber composites reinforced with vegetable fibers. This paper reviews the scientific literature published in the last decade about the properties and characteristics of natural vegetable fibers and natural rubber used in composites. Nowadays the use of alternative materials has become necessary, considering that synthetic materials have caused irreversible damage to the environment, being associated with global warming, for this reason research and development with materials that print a lower carbon footprint during the manufacturing process and subsequent product manufacturing. This review is an invitation to the use of vegetable fibers, as well as vegetable-type matrices, in this case natural rubber as a binder system, it is fantastic to know the different works carried out by other scientists and engineers, in this way to project new compounds linked to innovation in processes that reduce the carbon footprint and its negative impact on our planet.
Phosphonium-Based Polyelectrolytes: Preparation, Properties, and Usage in Lithium-Ion Batteries
Authors: Misenan Muhammad Syukri Mohamad , Hempelmann Rolf , Gallei Markus , Eren Tarik
Published: July 2023

Phosphorous is an essential element for the life of organisms, and phosphorus-based compounds have many uses in industry, such as flame retardancy reagents, ingredients in fertilizers, pyrotechnics, etc. Ionic liquids are salts with melting points lower than the boiling point of water. The term “polymerized ionic liquids” (PILs) refers to a class of polyelectrolytes that contain an ionic liquid (IL) species in each monomer repeating unit and are connected by a polymeric backbone to form macromolecular structures. PILs provide a new class of polymeric materials by combining some of the distinctive qualities of ILs in the polymer chain. Ionic liquids have been identified as attractive prospects for a variety of applications due to the high stability (thermal, chemical, and electrochemical) and high mobility of their ions, but their practical applicability is constrained because they lack the benefits of both liquids and solids, suffering from both leakage issues and excessive viscosity. PILs are garnering for developing non-volatile and non-flammable solid electrolytes. In this paper, we provide a brief review of phosphonium-based PILs, including their synthesis route, properties, advantages and drawbacks, and the comparison between nitrogen-based and phosphonium-based PILs. As phosphonium PILs can be used as polymer electrolytes in lithium-ion battery (LIB) applications, the conductivity and the thermo-mechanical properties are the most important features for this polymer electrolyte system. The chemical structure of phosphonium-based PILs that was reported in previous literature has been reviewed and summarized in this article. Generally, the phosphonium PILs that have more flexible backbones exhibit better conductivity values compared to the PILs that consist of a rigid backbone. At the end of this section, future directions for research regarding PILs are discussed, including the use of recyclable phosphorus from waste.
Removal of Calcareous Concretions from Marine Archaeological Ceramics by Means of a Stimuli-Responsive Hydrogel
Authors: Zha Jianrui , Huang Qijun , Liu Xinyi , Han Xiangna , Guo Hong
Published: July 2023

The presence of calcareous concretions on the surface of marine archaeological ceramics is a frequently observed phenomenon. It is necessary to remove these materials when the deposits obscure the feature of ceramics. Unfortunately, calcareous concretions provide distinctive documentation of the burning history of ceramics. The interaction of acid solution or detachment of the deposit layers in physical ways leads to the loss of archeological information. To prevent the loss of archeological information and to achieve precise and gentle concretion removal, responsive hydrogel cleaning systems have been developed. The hydrogels synthesized are composed of networks of poly(vinyl acetate)/sodium alginate that exhibit desirable water retention properties, are responsive to Ca2+ ions, and do not leave any residues after undergoing cleaning treatment. Four distinct compositions were selected. The study of water retention properties involved quantifying the weight changes. The composition was obtained from Fourier transform infrared spectra. The microstructure was obtained from scanning electron microscopy. The mechanical properties were obtained from rheological measurements. To demonstrate both the efficiency and working mechanism of the selected hydrogels, a representative study of mocked samples is presented first. After selecting the most appropriate hydrogel composite, a cleaning process was implemented on the marine archaeological ceramics. This article demonstrates the advantages of stimuli-responsive hydrogels in controlling the release of acid solution release, thereby surpassing the limitations of traditional cleaning methods.
Influence of Ultrasound on the Properties of Polysaccharide Complexes and Materials Based on Them
Authors: Mokhova Elizaveta , Gordienko Mariia , Menshutina Natalia , Kalenov Sergei , Avetissov Igor , Eremeev Artyom
Published: July 2023

Freeze-drying is often used as a final stage to produce three-dimensional porous matrices for medicine. Because a pure solvent crystallizes first during freezing, it acts as a pore-forming agent. The size of the solvent crystals primarily depends on the cooling rate and the composition of the material to be frozen. Ultrasonic treatment also affects the size of crystals and can be used to control the structure of a porous matrix. This article describes the effect of ultrasound (40 kHz, 50 W) applied at the preliminary freezing stage of polysaccharide solutions (alginate, chitosan, alginate–chitosan and alginate–gelatin) on the finished matrix properties. The most attention was paid to the effect of ultrasound on the size and shape of crystals formed during freezing, which leads to a change in the porous structure of the matrices after solvent sublimation. As a result of changes in the microstructure, a number of differences in the vibrational spectra of the molecules and the values of pore volume, sorption capacity, permeability and degradation of matrices were identified. Such changes in the structure of materials, as well as the emerging directionality of pores, together can affect the process of cell cultivation in these polysaccharide matrices, which can be useful in solving problems of tissue engineering.
Islamic Caricature Controversy from Jyllands-Posten to Charlie Hebdo from the Perspective of Arab Opinion Leaders
Authors: Kazkaz Lana , Bosch Míriam Díez
Published: July 2023

The Jyllands-Posten Muhammad cartoons controversy began after the Danish newspaper Jyllands-Posten published 12 editorial cartoons in September 2005. Cultural and political relations between the West and the Arabic and Islamic worlds have witnessed multiple events that revealed the nature and understanding of historical relations between the worlds, and the role of contemporary media in formulating them. After this incident, the phenomenon of Western media handling of Islamic religious symbols began to arouse interest, where they faced angry responses in the Arabic and Islamic worlds, which denounced Denmark, while Denmark, as a country, refused to apologize to Muslims for what they considered a major abuse, which led some Arab countries to suspend relations with the latter. Additionally, in January 2015, the French magazine Charlie Hebdo was targeted in a deadly attack on its headquarters in Paris, killing 12 people for its “red-line cartoons” on Islam. This study seeks to understand the positions of a group of opinion leaders comprised of intellectuals and influencers who represent cultural and political currents in a number of Arab countries from the phenomenon of cartoons in Western media. This study aimed to evaluate them on the intense reactions of rage witnessed in multiple Islamic countries that occurred after the release of these drawings, and ask them basic questions: Did the Arab media, opinion leaders, and intellectuals have an inciting role that provoked the Western media’s handling of Islamic religious symbols or did this practice coincide with the Arab-Islamic cultural context and its limits? Answering the above questions helped to reveal the features of continuity and change in the perception of opinion leaders in the Arab world on the role of Western media in the dialogue and cultural conflict between the Arab-Islamic and Western worlds.
Why Can’t We Be Friends? The Synod on Synodality and the Eucharistic Revival
Authors: Briola Lucas
Published: July 2023

This article considers how two ongoing major ecclesial events—the Synod on Synodality and the Eucharistic Revival—might shed light on each other. While both events have garnered much attention, few have read them together. Nevertheless, the Eucharist and synodality belong together. This article argues that reading the Synod through the Revival and the Revival through the Synod—a Eucharistically-revived synodality and a synodally-shaped Eucharist—can strengthen the aims of each, thus resolving various critiques of both initiatives while also charting a bracing vision of U.S. Catholicism in the twenty-first century.
Chronic Plantar Fasciitis Treatment: A Randomized Trial Comparing Corticosteroid Injections Followed by Therapeutic Ultrasound with Extracorporeal Shock Wave Therapy
Authors: Moneim Nermeen Hassan A. , Hemed Mennatullah A. , Klooster Peter M. ten , Rasker Johannes J. , El Shaarawy Nashwa K.
Published: July 2023

This study aims to compare the effect of corticosteroid injection (CSI) followed by therapeutic ultrasound (TUS) with that of extracorporeal shock wave therapy (ESWT) in patients with chronic plantar fasciitis (PF) and to explore the impact of a sedentary lifestyle and obesity on treatment outcomes. Female patients with PF were randomly allocated to receive ESWT (group A, n = 25) or CSI + TUS (group B, n = 25). Interventions: Group A received four once-weekly sessions of ESWT (2000 shocks, 2.5 bar pressure, 10.0 Hz frequency). Group B received a local injection of 40 mg triamcinolone acetonide with 2 mL 1% xylocaine, followed by three sessions of TUS per week for two weeks. Pain visual analog scale (VAS pain), plantar fasciitis pain and disability scale (PFPDS), and fascia thickness using musculoskeletal ultrasound were all measured at baseline, 4 weeks, and 12 weeks after the end of treatment. VAS pain and PFPDS improved significantly in both groups after 4 and 12 weeks. In the ESWT group, the pain improved significantly more at 12 weeks (p = 0.004). In obese patients (BMI > 29.9 kg/m2), ESWT gave more long-term pain relief at 12 weeks follow-up. In both the ESWT and CSI + TUS groups, after 12 weeks, the VAS pain improved more in patients with a sedentary daily life than in those with active life (p = 0.021 and p = 0.014, resp.), as well as the PFPDS (p = 0.014 and p = 0.019, resp.). Plantar fascia thickness decreased in both groups at 12 weeks. In both groups, improvements in function (PFPDS) correlated significantly with decreased plantar fascia thickness at 4 and 12 weeks. In the CSI + TUS group only, the decrease in plantar fascia thickness was correlated with pain improvement at both follow-up visits. Echogenicity changed from hypoechoic to iso- or hyperechoic and improved significantly in both groups at 12 weeks follow-up, but changes were not different between the groups (p = 0.208). Both CSI + TUS and ESWT are effective treatments for female patients with chronic plantar fasciitis resulting in pain relief and improved function and fascia thickness. ESWT gave more pain relief at 12 weeks follow-up. CSI + TUS is effective as a rapid and short-term modality for relieving PF pain. According to previous studies, the addition of TUS does not appear to make CSI much more effective.
Combining Images and Trajectories Data to Automatically Generate Road Networks
Authors: Bai Xiangdong , Feng Xuyu , Yin Yuanyuan , Yang Mingchun , Wang Xingyao , Yang Xue
Published: July 2023

Road network data are an important part of many applications, e.g., intelligent transportation and urban planning. At present, most of the approaches to road network generation are dominated by single data sources including images, point cloud data, trajectories, etc., which may cause the fragmentation of information. This study proposes a novel strategy to obtain the vector data of road networks by combining images and trajectory data with a postprocessing method named RNITP. The designed RNITP includes two parts: an initial generation layer of road network detection and a postprocessing layer of vector map acquirement. At the first layer, there are three steps of road network detection including road information interpretation from images based on a new deep learning model (denoted as SPBAM-LinkNet), road detection from trajectories data by rasterizing, and road information fusion by using OR operation. The last layer is used to generate a vector map based on a postprocessing method that is focused on error identification and removal. Experiments were conducted using two kinds of datasets: CHN6-CUG road datasets and HB road datasets. The results show that the accuracy, F1 score, and MIoU of SPBAM-LinkNet on CHN6-CUG and HB were (0.9695, 0.7369, 0.7760) and (0.9387, 0.7257, 0.7514), respectively, which are better than other typical models (e.g., Unet, DeepLabv3+, D-Linknet, NL-Linknet). In addition, the F1 score, IoU, and recall of the vector map obtained from RNITP are 0.8883, 0.7991, and 0.9065, respectively.
Forecasting PM10 Levels Using Machine Learning Models in the Arctic: A Comparative Study
Authors: Fazzini Paolo , Montuori Marco , Pasini Antonello , Cuzzucoli Alice , Crotti Ilaria , Campana Emilio Fortunato , Petracchini Francesco , Dobricic Srdjan
Published: July 2023

In this study, we present a statistical forecasting framework and assess its efficacy using a range of established machine learning algorithms for predicting Particulate Matter (PM) concentrations in the Arctic, specifically in Pallas (FI), Reykjavik (IS), and Tromso (NO). Our framework leverages historical ground measurements and 24 h predictions from nine models by the Copernicus Atmosphere Monitoring Service (CAMS) to provide PM10 predictions for the following 24 h. Furthermore, we compare the performance of various memory cells based on artificial neural networks (ANN), including recurrent neural networks (RNNs), gated recurrent units (GRUs), long short-term memory networks (LSTMs), echo state networks (ESNs), and windowed multilayer perceptrons (MLPs). Regardless of the type of memory cell chosen, our results consistently show that the proposed framework outperforms the CAMS models in terms of mean squared error (MSE), with average improvements ranging from 25% to 40%. Furthermore, we examine the impact of outliers on the overall performance of the model.
Landslide Hazard Assessment in Highway Areas of Guangxi Using Remote Sensing Data and a Pre-Trained XGBoost Model
Authors: Zhang Yuze , Deng Lei , Han Ying , Sun Yunhua , Zang Yu , Zhou Minlu
Published: July 2023

This study presents a novel method for assessing landslide hazards along highways using remote sensing and machine learning. We extract geospatial features such as slope, aspect, and rainfall over Guangxi, China, and apply an extreme gradient boosting model pre-trained on contiguous United States datasets. The model produces susceptibility maps that indicate landslide probability at different scales. However, the lack of accurate data on historical landslides in Guangxi challenges the model evaluation and comparison between regions. To overcome this, we calibrate the model to fit the local conditions in Guangxi. The calibrated model agrees with the observed landslide locations, implying its capability to capture regional variations in landslide mechanisms. We apply the model at a 30 m resolution along the Heba Expressway and validate it against reports from July 2021 to March 2022. The model correctly predicts five of seven landslide events in this period with a reasonable alarm rate. This framework has the potential for large-scale landslide risk management by informing transportation planning and infrastructure maintenance decisions. More data on landslide timing and human disturbance events may improve the model’s accuracy across diverse geographical areas and terrains.
Study on Electron Density Anomalies Possibly Related to Earthquakes Based on CSES Observations
Authors: Han Chengcheng , Yan Rui , Marchetti Dedalo , Pu Weixing , Zhima Zeren , Liu Dapeng , Xu Song , Lu Hengxin , Zhou Na
Published: July 2023

This research examines the correlation between seismic activity and variations in ionospheric electron density (Ne) using the data from the Langmuir probe (LAP) onboard the China Seismo-Electromagnetic Satellite (CSES) during nighttime. Statistical analysis of Ms ≥ 6.8 earthquakes that occurred globally between August 2018 and March 2023 is conducted, as well as Ms ≥ 6.0 earthquakes in China during the same period, using the quartile analysis method for fixed revisiting orbits. The main conclusions are that: (1) the larger the magnitude of the earthquake, the more anomalous the phenomena that appear; (2) the anomalies on the east side of the epicenter are significantly higher than those on the west side, and the anomalies in the Northern Hemisphere are mostly distributed southward from the epicenter, while those in the Southern Hemisphere are mostly distributed northward from the epicenter; (3) anomalies appear with a higher frequency on several specific time intervals, including the day of the earthquake (likely co-seismic effect) and 2, 7, and 11 days before the earthquake (possible precursor candidates); and (4) for the 15 earthquakes of Ms ≥ 6.0 in China over the past five years, anomalous Ne mainly occurred southwest of the epicenter, with the highest frequency observed 5 days before the earthquake, and there were continuous anomalous phenomena between 9 days and 5 days before the earthquake. This study concludes that Ne, measured by CSES, can play a fundamental role in studying earthquake-related ionospheric disturbances.
Exploring the Best-Matching Precipitation Traits in Four Long-Term Mainstream Products over China from 1981 to 2020
Authors: Li Xuejiao , Zhang Jutao , Feng Qi , Liu Wei , Ao Yong , Zhu Meng , Yang Linshan , Yin Xinwei , Li Yongge , Han Tuo
Published: July 2023

As a major component of water cycle, the accuracy quantification of different precipitation products is critical for evaluating climate change and ecosystem functions. However, a lack of evidence is available to choose a precise precipitation product in relative applications. Here, to solve this limit, we analyze the spatiotemporal pattern and accuracy of four precipitation products, including CHIRPS V2.0, PERSIANN-CDR, ECMWF ERA5-Land, and GLDAS_NOAH025_3H, over China during the period of 1981–2020, based on the five precipitation traits (i.e., spatial pattern of multi-year average, annual trend, seasonality, frequency, and intensity), and meteorological gauge observations are taken as the benchmark. Our results show that, compared to other products, CHIRPS data has the strongest ability to present spatial pattern of multi-year average precipitation, especially in most parts of northeastern and southern China, and ERA5 has the weakest ability to simulate the multi-year average precipitation. All four precipitation products can accurately depict the spatial pattern of seasonality, among which CHIRPS and ERA5 have the highest and lowest fitting ability, respectively, but four products poorly describe the spatial pattern of precipitation intensity and frequency at a daily scale. These products only correctly predict the interannual precipitation trend in some local areas. Our findings provide evidences to select high-quality precipitation data, and could help to improve the accuracy of relative geophysical models.
Multi-Scale Analysis of PM2.5 Concentrations in the Yangtze River Economic Belt: Investigating the Combined Impact of Natural and Human Factors
Authors: Li Shuoshuo , Wei Guoen , Liu Yaobin , Bai Ling
Published: July 2023

Air pollutants, primarily PM2.5, have inflicted significant harm on public health and sustainable urban development in the Yangtze River Economic Belt (YREB). Previous studies often neglected the coordinated measurement of PM2.5 human and natural factors in this area. Therefore, this paper focuses on the YREB. Using a geographic information system (GIS) platform, along with remote sensing and statistical data spanning from 2000 to 2020, this study employs spatial analysis to uncover the spatial-temporal characteristics of PM2.5 and its spatial agglomeration patterns. Furthermore, this study further employs the spatial panel Durbin model to investigate the natural and anthropogenic factors driving PM2.5 concentrations across multiple scales. The analysis of the results reveals an “M”-shaped change trend in PM2.5 concentrations within the YREB. PM2.5 concentrations exhibit significant spatial agglomeration characteristics, whereby most urban agglomerations are high-pollution areas. Moreover, the changes in PM2.5 concentrations are jointly influenced by several factors, including the secondary industry, urban built-up area, population density, annual precipitation, and NDVI. Furthermore, the dominant factors influencing PM2.5 concentrations in the three major urban agglomerations exhibit both similarities and differences. In addition, for effective governance coordination across regions, policymakers should diligently consider both the shared predominant factors and the varying factors specific to each region in the future. This study expands the research content of watershed PM2.5 collaborative governance, and further provides practical support for other watershed environmental governance and urban sustainable management.
Distributed Coordination of Space–Ground Multiresources for Remote Sensing Missions
Authors: Liu Runzi , Ding Xu , Wu Weihua , Guo Wei
Published: July 2023

As data relay satellites (DRSs) play an increasingly important supporting role in remote sensing missions, efficient coordination across space–ground multiresources becomes a significant problem. Owing to the implementation problem of the centralized coordinate methods, this paper studies a distributed coordinate resource scheduling method which is realizable in the current space network structure. To be specific, we first formulate the multiple resource coordination problem into an MILP problem based on a modified time-expanded graph. Then, the problem is transferred and decomposed into subproblems for remote sensing satellite (RSS) systems and DRS systems to solve distributedly. Afterwards, we propose a distributed iterative scheme for the RSS systems and DRS systems based on alternating direction method of multipliers (ADMM), in which only the schedule information of the inter-satellite links are required to exchange between RSS systems and DRS systems. Simulation results are provided to validate the effectiveness of our distributed coordinated resource scheduling algorithm.
Shallow-Guided Transformer for Semantic Segmentation of Hyperspectral Remote Sensing Imagery
Authors: Chen Yuhan , Liu Pengyuan , Zhao Jiechen , Huang Kaijian , Yan Qingyun
Published: July 2023

Convolutional neural networks (CNNs) have achieved great progress in the classification of surface objects with hyperspectral data, but due to the limitations of convolutional operations, CNNs cannot effectively interact with contextual information. Transformer succeeds in solving this problem, and thus has been widely used to classify hyperspectral surface objects in recent years. However, the huge computational load of Transformer poses a challenge in hyperspectral semantic segmentation tasks. In addition, the use of single Transformer discards the local correlation, making it ineffective for remote sensing tasks with small datasets. Therefore, we propose a new Transformer layered architecture that combines Transformer with CNN, adopts a feature dimensionality reduction module and a Transformer-style CNN module to extract shallow features and construct texture constraints, and employs the original Transformer Encoder to extract deep features. Furthermore, we also designed a simple Decoder to process shallow spatial detail information and deep semantic features separately. Experimental results based on three publicly available hyperspectral datasets show that our proposed method has significant advantages compared with other traditional CNN, Transformer-type models.