bluuebunny/crossref_metadata_2025 huggingface dataset:
Stable High-Capacity Elemental Sulfur Cathodes with Simple Process for Lithium Sulfur Batteries
Authors: Sawada Shunsuke , Yoshida Hideki , Luski Shalom , Markevich Elena , Salitra Gregory , Elias Yuval , Aurbach Doron
Published: June 2023

Lithium sulfur batteries are suitable for drones due to their high gravimetric energy density (2600 Wh/kg of sulfur). However, on the cathode side, high specific capacity with high sulfur loading (high areal capacity) is challenging due to the poor conductivity of sulfur. Shuttling of Li-sulfide species between the sulfur cathode and lithium anode also limits specific capacity. Sulfur-carbon composite active materials with encapsulated sulfur address both issues but require expensive processing and have low sulfur content with limited areal capacity. Proper encapsulation of sulfur in carbonaceous structures along with active additives in solution may largely mitigate shuttling, resulting in cells with improved energy density at relatively low cost. Here, composite current collectors, selected binders, and carbonaceous matrices impregnated with an active mass were used to award stable sulfur cathodes with high areal specific capacity. All three components are necessary to reach a high sulfur loading of 3.8 mg/cm2 with a specific/areal capacity of 805 mAh/g/2.2 mAh/cm2. Good adhesion between the carbon-coated Al foil current collectors and the composite sulfur impregnated carbon matrices is mandatory for stable electrodes. Swelling of the binders influenced cycling retention as electroconductivity dominated the cycling performance of the Li-S cells comprising cathodes with high sulfur loading. Composite electrodes based on carbonaceous matrices in which sulfur is impregnated at high specific loading and non-swelling binders that maintain the integrated structure of the composite electrodes are important for strong performance. This basic design can be mass produced and optimized to yield practical devices.
Core–Shell Structured Carbon Nanofiber-Based Electrodes for High-Performance Supercapacitors
Authors: Fan Peizhi , Wang Jie , Ding Wenfei , Xu Lan
Published: June 2023

The combination of multiple electrode materials and their reasonable structural design are conducive to the preparation of composite electrodes with excellent performance. In this study, based on carbon nanofibers grown with Ni(OH)2 and NiO (CHO) prepared by electrospinning, hydrothermal growth, and low-temperature carbonization, five transition metal sulfides (MnS, CoS, FeS, CuS, and NiS) were hydrothermally grown on their surfaces, exhibiting that CHO/NiS had the optimal electrochemical properties. Subsequently, the effect of hydrothermal growth time on CHO/NiS revealed that the electrochemical performance of CHO/NiS-3h was optimal, with a specific capacitance of up to 1717 F g−1 (1 A g−1), due to its multistage core–shell structure. Moreover, the diffusion-controlled process of CHO/NiS-3h dominated its charge energy storage mechanism. Finally, the asymmetric supercapacitor assembled with CHO/NiS-3h as the positive electrode demonstrated an energy density of 27.76 Wh kg−1 at a maximum power density of 4000 W kg−1, and it still maintained a power density of 800 W kg−1 at a maximum energy density of 37.97 Wh kg−1, exhibiting the potential application of multistage core–shell composite materials in high-performance supercapacitors.
Magnetic Nanozyme Based on Loading Nitrogen-Doped Carbon Dots on Mesoporous Fe3O4 Nanoparticles for the Colorimetric Detection of Glucose
Authors: Huang Yunxi , Ding Zhanling , Li Yutong , Xi Fengna , Liu Junjie
Published: June 2023

The simple and accurate monitoring of blood glucose level is of great significance for the prevention and control of diabetes. In this work, a magnetic nanozyme was fabricated based on loading nitrogen-doped carbon dots (N-CDs) on mesoporous Fe3O4 nanoparticles for the colorimetric detection of glucose in human serum. Mesoporous Fe3O4 nanoparticles were easily synthesized using a solvothermal method, and N-CDs were then prepared in situ and loaded on the Fe3O4 nanoparticles, leading to a magnetic N-CDs/Fe3O4 nanocomposite. The N-CDs/Fe3O4 nanocomposite exhibited good peroxidase-like activity and could catalyze the oxidation of the colorless enzyme substrate 3,3′,5,5′-tetramethylbenzidine (TMB) to blue TMB oxide (ox-TMB) in the presence of hydrogen peroxide (H2O2). When the N-CDs/Fe3O4 nanozyme was combined with glucose oxidase (Gox), Gox catalyzed the oxidization of glucose, producing H2O2 and leading to the oxidation of TMB under the catalysis of the N-CDs/Fe3O4 nanozyme. Based on this mechanism, a colorimetric sensor was constructed for the sensitive detection of glucose. The linear range for glucose detection was from 1 to 180 μM, and the limit of detection (LOD) was 0.56 μM. The recovered nanozyme through magnetic separation showed good reusability. The visual detection of glucose was also realized by preparing an integrated agarose hydrogel containing the N-CDs/Fe3O4 nanozyme, glucose oxidase, and TMB. The colorimetric detection platform has an enormous potential for the convenient detection of metabolites.
In-Depth Study on the Effects of Impurity Ions in Saline Wastewater Electrolysis
Authors: Pan Qicheng , Zhao Peixuan , Gao Linxia , Liu Huimin , Hu Hongyun , Dong Lu
Published: June 2023

Concentration followed by electrolysis is one of the most promising ways for saline wastewater treatment, since it could produce H2, Cl2, and an alkaline solution with deacidification potential. However, due to the diversity and difference of wastewater, knowledge on the suitable salt concentration for wastewater electrolysis and the effects of mixed ions are still lacking. In this work, electrolysis experiments of mixed saline water were conducted. The salt concentration for stable dechlorination was explored, with in-depth discussions on the effects of typical ions such as K+, Ca2+, Mg2+, and SO42−. Results showed that K+ had a positive effect on the H2/Cl2 production of saline wastewater through accelerating the mass transfer efficiency in the electrolyte. However, the existence of Ca2+ and Mg2+ had negative effects on the electrolysis performance by forming precipitates, which would adhere to the membrane, reduce the membrane permeability, occupy the active sites on the cathode surface, and also increase the transport resistance of the electrons in the electrolyte. Compared to Mg2+, the damaging effect of Ca2+ on the membrane was even worse. Additionally, the existence of SO42− reduced the current density of the salt solution by affecting the anodic reaction while having less of an effect on the membrane. Overall, Ca2+ ≤ 0.01 mol/L, Mg2+ ≤ 0.1 mol/L and SO42− ≤ 0.01 mol/L were allowable to ensure the continuous and stable dechlorination electrolysis of saline wastewater.
Reduction of Nitroaromatics by Gold Nanoparticles on Porous Silicon Fabricated Using Metal-Assisted Chemical Etching
Authors: Liang Ling-Yi , Kung Yu-Han , Hsiao Vincent K. S. , Chu Chih-Chien
Published: June 2023

In this study, we investigated the use of porous silicon (PSi) fabricated using metal-assisted chemical etching (MACE) as a substrate for the deposition of Au nanoparticles (NPs) for the reduction of nitroaromatic compounds. PSi provides a high surface area for the deposition of Au NPs, and MACE allows for the fabrication of a well-defined porous structure in a single step. We used the reduction of p-nitroaniline as a model reaction to evaluate the catalytic activity of Au NPs on PSi. The results indicate that the Au NPs on the PSi exhibited excellent catalytic activity, which was affected by the etching time. Overall, our results highlighted the potential of PSi fabricated using MACE as a substrate for the deposition of metal NPs for catalytic applications.
Nonlinear Dynamic Response of Nanocomposite Microbeams Array for Multiple Mass Sensing
Authors: Formica Giovanni , Lacarbonara Walter , Yabuno Hiroshi
Published: June 2023

A nonlinear MEMS multimass sensor is numerically investigated, designed as a single input-single output (SISO) system consisting of an array of nonlinear microcantilevers clamped to a shuttle mass which, in turn, is constrained by a linear spring and a dashpot. The microcantilevers are made of a nanostructured material, a polymeric hosting matrix reinforced by aligned carbon nanotubes (CNT). The linear as well as the nonlinear detection capabilities of the device are explored by computing the shifts of the frequency response peaks caused by the mass deposition onto one or more microcantilever tips. The frequency response curves of the device are obtained by a pathfollowing algorithm applied to the reduced-order model of the system. The microcantilevers are described by a nonlinear Euler-Bernoulli inextensible beam theory, which is enriched by a meso-scale constitutive law of the nanocomposite. In particular, the microcantilever constitutive law depends on the CNT volume fraction suitably used for each cantilever to tune the frequency bandwidth of the whole device. Through an extensive numerical campaign, the mass sensor sensitivity estimated in the linear and nonlinear dynamic range shows that, for relatively large displacements, the accuracy of the added mass detectability can be improved due to the larger nonlinear frequency shifts at resonance (up to 12%).
Characterisation of Fasting and Postprandial NMR Metabolites: Insights from the ZOE PREDICT 1 Study
Authors: Bermingham Kate M. , Mazidi Mohsen , Franks Paul W. , Maher Tyler , Valdes Ana M. , Linenberg Inbar , Wolf Jonathan , Hadjigeorgiou George , Spector Tim D. , Menni Cristina , Ordovas Jose M. , Berry Sarah E. , Hall Wendy L.
Published: June 2023

Background: Postprandial metabolomic profiles and their inter-individual variability are not well characterised. Here, we describe postprandial metabolite changes, their correlations with fasting values and their inter- and intra-individual variability, following a standardised meal in the ZOE PREDICT 1 cohort. Methods: In the ZOE PREDICT 1 study (n = 1002 (NCT03479866)), 250 metabolites, mainly lipids, were measured by a Nightingale NMR panel in fasting and postprandial (4 and 6 h after a 3.7 MJ mixed nutrient meal, with a second 2.2 MJ mixed nutrient meal at 4 h) serum samples. For each metabolite, inter- and intra-individual variability over time was evaluated using linear mixed modelling and intraclass correlation coefficients (ICC) were calculated. Results: Postprandially, 85% (of 250 metabolites) significantly changed from fasting at 6 h (47% increased, 53% decreased; Kruskal–Wallis), with 37 measures increasing by >25% and 14 increasing by >50%. The largest changes were observed in very large lipoprotein particles and ketone bodies. Seventy-one percent of circulating metabolites were strongly correlated (Spearman’s rho >0.80) between fasting and postprandial timepoints, and 5% were weakly correlated (rho <0.50). The median ICC of the 250 metabolites was 0.91 (range 0.08–0.99). The lowest ICCs (ICC <0.40, 4% of measures) were found for glucose, pyruvate, ketone bodies (β-hydroxybutyrate, acetoacetate, acetate) and lactate. Conclusions: In this large-scale postprandial metabolomic study, circulating metabolites were highly variable between individuals following sequential mixed meals. Findings suggest that a meal challenge may yield postprandial responses divergent from fasting measures, specifically for glycolysis, essential amino acid, ketone body and lipoprotein size metabolites.
Polysaccharides Extracted from Dendrobium officinale Grown in Different Environments Elicit Varying Health Benefits in Caenorhabditis elegans
Authors: Okoro Nkwachukwu Oziamara , Odiba Arome Solomon , Yu Qi , He Bin , Liao Guiyan , Jin Cheng , Fang Wenxia , Wang Bin
Published: June 2023

Dendrobium officinale is one of the most widely used medicinal herbs, especially in Asia. In recent times, the polysaccharide content of D. officinale has garnered attention due to the numerous reports of its medicinal properties, such as anticancer, antioxidant, anti-diabetic, hepatoprotective, neuroprotective, and anti-aging activities. However, few reports of its anti-aging potential are available. Due to high demand, the wild D. officinale is scarce; hence, alternative cultivation methods are being employed. In this study, we used the Caenorhabditis elegans model to investigate the anti-aging potential of polysaccharides extracted from D. officinale (DOP) grown in three different environments; tree (TR), greenhouse (GH), and rock (RK). Our findings showed that at 1000 µg/mL, GH-DOP optimally extended the mean lifespan by 14% and the maximum lifespan by 25% (p < 0.0001). TR-DOP and RK-DOP did not extend their lifespan at any of the concentrations tested. We further showed that 2000 µg/mL TR-DOP, GH-DOP, or RK-DOP all enhanced resistance to H2O2-induced stress (p > 0.05, p < 0.01, and p < 0.01, respectively). In contrast, only RK-DOP exhibited resistance (p < 0.01) to thermal stress. Overall, DOP from the three sources all increased HSP-4::GFP levels, indicating a boost in the ability of the worms to respond to ER-related stress. Similarly, DOP from all three sources decreased α-synuclein aggregation; however, only GH-DOP delayed β-amyloid-induced paralysis (p < 0.0001). Our findings provide useful information on the health benefits of DOP and also provide clues on the best practices for cultivating D. officinale for maximum medicinal applications.
Development of Conjugated Kefiran-Chondroitin Sulphate Cryogels with Enhanced Properties for Biomedical Applications
Authors: Radhouani Hajer , Gonçalves Cristiana , Maia F. Raquel , Oliveira Eduarda P. , Reis Rui L. , Oliveira Joaquim M.
Published: June 2023

Hydrogels based on natural polysaccharides can have unique properties and be tailored for several applications, which may be mainly limited by the fragile structure and weak mechanical properties of this type of system. We successfully prepared cryogels made of newly synthesized kefiran exopolysaccharide-chondroitin sulfate (CS) conjugate via carbodiimide-mediated coupling to overcome these drawbacks. The freeze-thawing procedure of cryogel preparation followed by lyophilization is a promising route to fabricate polymer-based scaffolds with countless and valuable biomedical applications. The novel graft macromolecular compound (kefiran-CS conjugate) was characterized through 1H-NMR and FTIR spectroscopy—which confirmed the structure of the conjugate, differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA)—which mirrored good thermal stability (degradation temperature of about 215 °C) and, finally, gel permeation chromatography–size exclusion chromatography (GPC-SEC)—which proved an increased molecular weight due to chemical coupling of kefiran with CS. At the same time, the corresponding cryogels physically crosslinked after the freeze-thawing procedure were investigated by scanning electron microscopy (SEM), Micro-CT, and dynamic rheology. The results revealed a prevalent contribution of elastic/storage component to the viscoelastic behavior of cryogels in swollen state, a micromorphology with micrometer-sized open pores fully interconnected, and high porosity (ca. 90%) observed for freeze-dried cryogels. Furthermore, the metabolic activity and proliferation of human adipose stem cells (hASCs), when cultured onto the developed kefiran-CS cryogel, was maintained at a satisfactory level over 72 h. Based on the results obtained, it can be inferred that the newly freeze-dried kefiran-CS cryogels possess a host of unique properties that render them highly suitable for use in tissue engineering, regenerative medicine, drug delivery, and other biomedical applications where robust mechanical properties and biocompatibility are crucial.
Development of a Gene and Nucleic Acid Delivery System for Skeletal Muscle Administration via Limb Perfusion Using Nanobubbles and Ultrasound
Authors: Sekine Shohko , Mayama Sayaka , Nishijima Nobuaki , Kojima Takuo , Endo-Takahashi Yoko , Ishii Yuko , Shiono Hitomi , Akiyama Saki , Sakurai Akane , Sashida Sanae , Hamano Nobuhito , Tada Rui , Suzuki Ryo , Maruyama Kazuo , Negishi Yoichi
Published: June 2023

Strategies for gene and nucleic acid delivery to skeletal muscles have been extensively explored to treat Duchenne muscular dystrophy (DMD) and other neuromuscular diseases. Of these, effective intravascular delivery of naked plasmid DNA (pDNA) and nucleic acids into muscles is an attractive approach, given the high capillary density in close contact with myofibers. We developed lipid-based nanobubbles (NBs) using polyethylene-glycol-modified liposomes and an echo-contrast gas and found that these NBs could improve tissue permeability by ultrasound (US)-induced cavitation. Herein, we delivered naked pDNA or antisense phosphorodiamidate morpholino oligomers (PMOs) into the regional hindlimb muscle via limb perfusion using NBs and US exposure. pDNA encoding the luciferase gene was injected with NBs via limb perfusion into normal mice with application of US. High luciferase activity was achieved in a wide area of the limb muscle. DMD model mice were administered PMOs, designed to skip the mutated exon 23 of the dystrophin gene, with NBs via intravenous limb perfusion, followed by US exposure. The number of dystrophin-positive fibers increased in the muscles of mdx mice. Combining NBs and US exposure, which can be widely delivered to the hind limb muscles via the limb vein, could be an effective therapeutic approach for DMD and other neuromuscular disorders.
Er-Doped Mg4Ta2O9 Single-Crystal Scintillators Emitting Near-Infrared Photons for High-Dose Field Monitoring
Authors: Hayashi Taisei , Ichiba Kensei , Nakauchi Daisuke , Okazaki Kai , Kato Takumi , Kawaguchi Noriaki , Yanagida Takayuki
Published: June 2023

Mg4Ta2O9 single crystals doped with 0.01, 0.1, and 1% Er were grown using the floating zone method, and their photoluminescence and scintillation properties were studied. X-ray diffraction analysis confirmed that all samples had a hexagonal structure of Mg4Ta2O9. The samples showed that the emission peak at 1550 nm was due to 4f−4f transitions of Er3+ ions, with quantum yields of 32.9, 46.6, and 18.0% for 0.01, 0.1, and 1% doping concentrations, respectively. All samples showed scintillation with a broad emission band at 350 nm due to charge transfer from Ta5+ to O2− ions and emission peak at 1550 nm due to 4f−4f transition of Er3+ ions. The dose rate response functions showed that the detection limit for all samples was 0.06 Gy/h for scintillation detector applications.
Orchidaceae in Puglia (Italy): Consistency, Distribution, and Conservation
Authors: Turco Alessio , Albano Antonella , Medagli Pietro , D’Emerico Saverio , Wagensommer Robert Philipp
Published: June 2023

A study of the distribution of orchid species in Puglia, based on an analysis of 2084 bibliographic reports from 2000 to 2022, was carried out with the aim of revising and updating the information on the consistency of the Orchidaceae family in Puglia, with a special focus on assessing threatened species occurring inside and outside protected areas. The work presents a checklist of the Orchidaceae taxa (genera, species, and subspecies) found in the region, including observations on genera and species that present taxonomic challenges. A total of 113 taxa (i.e., species and subspecies), distributed across 16 genera, are listed in alphabetical order. The most representative genera were Ophrys (51 taxa), Serapias (15 taxa), and Epipactis (11 taxa). Additionally, 49 taxa (43.4%) were found to be endemic to Italy, with 21 of these, mostly belonging to the Ophrys genus, being exclusive to Puglia. Our study notes two different trends of distribution: a predominantly coastal distribution for orchid records located in southern Puglia (the Salento peninsula) and a more widespread distribution for the other provinces. Our study also shows that the greatest number of records locate orchids in protected areas with a positive correlation between their presence and habitats cited in Directive 92/43/EEC.
Pathogenesis-Related Proteins (PRs) with Enzyme Activity Activating Plant Defense Responses
Authors: dos Santos Cristiane , Franco Octávio Luiz
Published: June 2023

Throughout evolution, plants have developed a highly complex defense system against different threats, including phytopathogens. Plant defense depends on constitutive and induced factors combined as defense mechanisms. These mechanisms involve a complex signaling network linking structural and biochemical defense. Antimicrobial and pathogenesis-related (PR) proteins are examples of this mechanism, which can accumulate extra- and intracellular space after infection. However, despite their name, some PR proteins are present at low levels even in healthy plant tissues. When they face a pathogen, these PRs can increase in abundance, acting as the first line of plant defense. Thus, PRs play a key role in early defense events, which can reduce the damage and mortality caused by pathogens. In this context, the present review will discuss defense response proteins, which have been identified as PRs, with enzymatic action, including constitutive enzymes, β-1,3 glucanase, chitinase, peroxidase and ribonucleases. From the technological perspective, we discuss the advances of the last decade applied to the study of these enzymes, which are important in the early events of higher plant defense against phytopathogens.
Electrical and Mechanical Characterisation of Poly(ethylene)oxide-Polysulfone Blend for Composite Structural Lithium Batteries
Authors: Gucci Francesco , Grasso Marzio , Russo Stefano , Leighton Glenn J. T. , Shaw Christopher , Brighton James
Published: June 2023

In this work, a blend of PEO, polysulfone (PSF), and lithium bis(trifluoromethanesulfonyl)imide (LiTFSi) was prepared at different PEO–PSf weight ratios (70-30, 80-20, and 90-10) and ethylene oxide to lithium (EO/Li) ratios (16/1, 20/1, 30/1, and 50/1). The samples were characterised using FT-IR, DSC, and XRD. Young’s modulus and tensile strength were evaluated at room temperature with micro-tensile testing. The ionic conductivity was measured between 5 °C and 45 °C through electrochemical impedance spectroscopy (EIS). The samples with a ratio of PEO and PSf equal to 70-30 and EO/Li ratio equal to 16/1 have the highest conductivity (1.91 × 10−4 S/cm) at 25 °C, while the PEO–PSf 80-20 EO/Li = 50/1 have the highest averaged Young’s modulus of about 1.5 GPa at 25 °C. The configuration with a good balance between electrical and mechanical properties is the PEO–PSf 70-30 EO/Li = 30/1, which has a conductivity of 1.17 × 10−4 S/cm and a Young’s modulus of 800 MPa, both measured at 25 °C. It was also found that increasing the EO/Li ratio to 16/1 dramatically affects the mechanical properties of the samples with them showing extreme embrittlement.
Production of Kojic Acid by Aspergillus niger M4 with Different Concentrations of Yeast Extract as a Nitrogen Source
Authors: Quiterio-Gutiérrez Tomasa , González-Morales Susana , González-Fuentes José Antonio , Benavides-Mendoza Adalberto , Fernández-Luqueño Fabián , Medrano-Macías Julia , Robledo-Olivo Armando
Published: June 2023

In agro-industrial processes, microorganisms that are not pathogenic and that generate molecules are generally recognized as safe (GRAS). The Aspergillus niger fungus has different industrial applications, being used to produce citric acid and 166 other secondary metabolites. The objective of this research was to optimize a culture medium to induce the production of kojic acid (KA) by the Aspergillus niger M4 strain in a liquid fermentation process. Four fermentative kinetics were developed in flasks, using different levels of yeast extract in (1) 0.05 g/L, (2) 0.10 g/L, (3) 2.5 g/L, and (4) 2.5 g/L + Zinc sulfate. The culture medium conditions influenced the formation and speed of biomass and the synthesis and yield of KA. The optimum production points were from 72 h and 96 h with 0.552 g/L and 0.510 g/L of KA using 2.5 g/L of yeast extract and with a pH of 5.5. The Aspergillus niger M4 strain had the ability to produce kojic acid, which was induced by the concentration of the nitrogen source.
Performance of a Nanofluid-Cooled Segmented Thermoelectric Generator: Hollow/Filled Leg Structures and Segmentation Effects
Authors: Ramos-Castañeda Cristian Francisco , Olivares-Robles Miguel Angel , Olivares-Hernandez Ana Elisabeth , Hernandez-Gonzalez Leobardo
Published: June 2023

A thermoelectric generator (TEG) is studied by considering different leg structures of hollow/filled legs, using new cooling nanofluids, and analyzing the segmentation effect. TEG performance is characterized by power output, conversion efficiency, and exergy efficiency. This study shows the impact of different cooling nanofluids (TiO2, graphene, and Al2O3) on the performance of the thermoelectric generator. Furthermore, in the comparative analysis of nanofluid cooling enhancement for TEG, different hollow/filled thermoelectric legs recently proposed in the literature are considered. Likewise, three segmentation types are used, 2n-2p, 1n-2p, and 2n-1p, thus will be compared with the results of the unsegmented legs. This study calculates the performance of thermoelectric leg structures through a validated numerical simulation on the ANSYS Workbench (modeling, design, and simulation). In addition, the optimal working conditions are evaluated. This study found that quenching of nanofluids can improve TEG performance by up to 17% compared to distilled water. However, the performance improvement of the TEG for each nanofluid is small between them. Furthermore, segmentation of n-type thermocouples improves efficiency and exergy, whereas segmentation of p-type thermocouples improves output power. The segmentation enhances performance by up to twice that of non-segmented leg structures; hollow structures are better performers. In the results, it is reported that the 2n-1p segmentation is the one with the best performance, reaching a maximum energy efficiency of 38%. The triangular leg structure improves performance by up to 75% compared to the rectangular and square leg structures. Likewise, using TiO2 is the best cooling option with nanofluids since it improves performance by 17% compared to distilled water. Furthermore, the results of cooling nanofluids for TEG performance are useful for the design of thermoelectric leg structures and stimulate further research.
Natural Deep Eutectic Solvent Optimization to Obtain an Extract Rich in Polyphenols from Capsicum chinense Leaves Using an Ultrasonic Probe
Authors: Avilés-Betanzos Kevin Alejandro , Cauich-Rodríguez Juan Valerio , González-Ávila Marisela , Scampicchio Matteo , Morozova Ksenia , Ramírez-Sucre Manuel Octavio , Rodríguez-Buenfil Ingrid Mayanin
Published: June 2023

Capsicum chinense Jacq., from the Yucatan peninsula, is recognized worldwide for its pungency, flavor, and secondary metabolites content. This has resulted in an increase in its production, which has led to an increase in the number of byproducts considered waste, mainly its leaves. Capsicum chinense leaves have been demonstrated to contain polyphenols with bioactive properties (antioxidant, anti-inflammatory, antiobesogenic capacity, etc.); hence, the extraction of polyphenols through the use of natural deep eutectic solvents (NADES) with a green technology, such as an ultrasonic probe, could help to revalue these leaves by maximizing the extraction efficiency and preserving their bioactive properties. The objective of this study was to optimize the composition of a eutectic solvent for obtaining an extract rich in polyphenols from the Capsicum chinense leaf using a sonic probe. The optimum conditions of the composition of NADES for obtaining the highest Antioxidant capacity (Ax, 79.71% inhibition) were a 0.8 mol glucose to 1 mol of choline chloride ratio, and 12% water. In addition, with this composition, the Total Polyphenol Content (TPC) obtained was 165.39 mg GAE/100 g dry leaf, and the individual polyphenols, such as vanillin (19.15 mg/100 g dry leaf) and ferulic acid (1.35 mg/100 g dry leaf), were optimized. The habanero pepper leaf extract obtained using a eutectic solvent and a sonic probe demonstrated a high potential for use as an ingredient in the development of nutraceuticals (i.e., functional foods).
The Nexus of Digital Authoritarianism and Religious Populism
Authors: Yilmaz Ihsan
Published: June 2023

This paper delves into the intricate relationship between religious populism and the legitimization of digital authoritarianism in Turkey. Specifically, it investigates how the ruling party, AKP, has strategically linked Islamist values to state policies as a means of justifying its repressive control over digital technology. Through an examination of internet governance at multiple levels—full network-level governance, sub-network or website-level governance, proxy or corporation-level governance, and network–node or individual-level governance—the study reveals the instrumentalization of religious populism to consolidate support and validate the government’s autocratic agenda. Furthermore, it sheds light on the role of state-controlled religious institutions, traditional media, social media outlets, as well as religious leaders and organizations in shaping public opinion, enabling the government to exert greater control over the dissemination of information. By dissecting the religious populist justification of digital authoritarianism in Turkey, this research provides valuable insights into the complex dynamics at play in the realm of online governance.
Comparing Contemporary Evangelical Models Regarding Human Origins
Authors: Luskin Casey
Published: June 2023

Multiple viewpoints exist among Protestant Evangelical Christians regarding human origins, with each offering different answers to questions regarding the existence of Adam and Eve and their relationship to humanity, common human–ape ancestry, evolution and intelligent design, humanity’s relationship to other members of the genus Homo (e.g., Neanderthals and Denisovans), and the timing of human origins. This article will review eight models for human origins which have recently received attention: (1) the Classical Theistic Evolution/Evolutionary Creationism model, (2) the Homo divinus model, (3) the Genealogical Adam and Eve model, (4) the Homo heidelbergensis model, (5) the Unique Origins Design model, (6) the Classical Old Earth Creationist model, (7) the Classical Young Earth Creationist model, and (8) an Old Earth/Recent Humans Hybrid model. Key features of each model will be described, and critical responses will be discussed in light of agreement or disagreement with traditional Judeo-Christian theological views and the scientific evidence. Most of these models maintain that science does not force one to abandon belief in core tenets of a traditional Adam and Eve, though they resolve the relevant scientific and theological questions in different ways and with varying degrees of success.
A Machine Learning Algorithm Predicting Infant Psychomotor Developmental Delay Using Medical and Social Determinants
Authors: Waynforth David
Published: June 2023

Psychomotor developmental delay in infants includes failure to acquire abilities such as sitting, walking, grasping objects and communication at the ages when most infants have acquired these abilities. Known risk factors include a large number of aspects of family environment, socioeconomic position, problems in pregnancy and birth and maternal health. It is clinically useful to be able to screen for developmental delay so that healthcare interventions can be considered. The present research used machine learning (random forest) to create an algorithm predicting psychomotor delay in 9-month-old infants using information ascertainable at birth and in early infancy. The dataset was the UK longitudinal Millennium Cohort study. In total, 53 predictors measuring socioeconomic indicators, paternal, family and social support for the mother, beliefs about good parenting, maternal health, pregnancy and birth were included in the initial algorithm. Feature reduction showed that of the 53 variables, birthweight, gestational age at birth, pre-pregnancy BMI, family income and parents’ ages had the highest feature importance scores and could alone correctly predict developmental delay with over 99% sensitivity and 100% specificity. No features measuring aspects of early infant care or environment meaningfully added to algorithm performance. The relationships between delay and some of the predictors, particularly income, were nonlinear and complex. The results suggest that the risk of psychomotor developmental delay can be identified in early infancy using machine learning, and that the best predictors are factors present prior to and at birth.
A Guaranteed-Return Structured Product as an Investment Risk-Hedging Instrument in Pension Savings Plans
Authors: Afik Zvika , Hadad Elroi , Yosef Rami
Published: June 2023

This study proposes a structured product (SP) for hedging defined contribution pension fund members against capital market risk. Using Monte Carlo simulations on three different guaranteed returns to test the investment strategy of the SP against a balanced investment portfolio, we measure their performance across a wide variety of capital market returns and risk scenarios. The results show that the SP guarantees a minimal return on the pension savings portfolio and offers a higher portfolio return at a lower investment risk, compared with the balanced investment portfolio. We conclude that the SP may become popular among pension fund members, potentially leading to improved risk management, greater competition, and investment strategy innovations for defined contribution pension schemes.
The Explanatory Factors of Risk Disclosure in the Integrated Reports of Listed Entities in Brazil
Authors: Albuquerque Fabio , Monteiro Eveline , Rodrigues Maria Albertina Barreiro
Published: June 2023

The gaps observed in entities’ traditional reports and accounts led to the emergence of the integrated report (IR), which includes several content elements, namely the component relating to risks and opportunities. Within this scope, the specific risks that may affect an organization’s capacity to create value are disclosed, among others, which is information of interest to the different stakeholders. This paper aims to identify the explanatory factors that influence the disclosure of risks in IRs. For this purpose, the IRs of entities listed on the Brazilian stock exchange for the year 2020 were assessed. The study was based on the explanatory theories of risk disclosure usually found in the literature, namely, the legitimacy, the agency, the signaling, and the upper echelon theories. Linear regression models were used with the disclosure rates of different types of risk as dependent variables. The size, profitability, indebtedness, independence, and gender diversity in the board of directors (BD), audit, and activity sector comprised the selected explanatory factors. Associations were found between some of the types of risks disclosed and the size of the entity, the existence of an audit, the independence of the BD, and the activity sector. The paper contributes to the literature about the explanatory factors of risk disclosure by exploring its analysis with different typologies and attributes, having the IR as a source of information, which is still little explored. The scientific contribution encompasses proposing a new risk analysis model in the IR. The innovative elements also comprise the classification of risks related to sustainable development (SD), including environmental, social, and governance (ESG) factors.
Do Behavioral Biases Affect Investors’ Investment Decision Making? Evidence from the Pakistani Equity Market
Authors: Abideen Zain UI , Ahmed Zeeshan , Qiu Huan , Zhao Yiwei
Published: June 2023

Using a unique sample constructed by 600 investors’ responses to a structured questionnaire, we investigate the impact of behavioral biases on the investors’ investment decision making in the Pakistani equity market, as well as the roles that market anomalies and financial literacy play in the decision making process. We first document the empirical evidence to support that the behavioral biases and market anomalies are closely associated and that these two factors significantly influence the investors’ investment decision making. The additional analyses confirm the mediating roles of certain market anomalies in the association between the investors’ behavioral biases and their investment decision making. Furthermore, empirical evidence reveals that financial literacy moderates the association between behavioral biases and market anomalies, and eventually influences the investors’ investment decision making. Overall, although the results are inconclusive for the relationships between certain variables, our results highlight the importance of financial literacy in terms of optimal investment decision making of individuals and the stability of the overall stock market.
Improving APT Systems’ Performance in Air via Impedance Matching and 3D-Printed Clamp
Authors: Liu Liu , Abdulla Waleed
Published: June 2023

This paper presents a study on improving the performance of the acoustic piezoelectric transducer system in air, as the low acoustic impedance of air leads to suboptimal system performance. Impedance matching techniques can enhance the acoustic power transfer (APT) system’s performance in air. This study integrates an impedance matching circuit into the Mason circuit and investigates the impact of fixed constraints on the piezoelectric transducer’s sound pressure and output voltage. Additionally, this paper proposes a novel equilateral triangular peripheral clamp that is entirely 3D-printable and cost-effective. This study analyses the peripheral clamp’s impedance and distance characteristics and confirms its effectiveness through consistent experimental and simulation results. The findings of this study can aid researchers and practitioners in various fields that employ APT systems to improve their performance in air.
Buildings’ Biaxial Tilt Assessment Using Inertial Wireless Sensors and a Parallel Training Model
Authors: Sánchez-Fernández Luis Pastor , Sánchez-Pérez Luis Alejandro , Carbajal-Hernández José Juan , Hernández-Guerrero Mario Alberto , Pérez-Echazabal Lucrecia
Published: June 2023

Applications of MEMS-based sensing technology are beneficial and versatile. If these electronic sensors integrate efficient processing methods, and if supervisory control and data acquisition (SCADA) software is also required, then mass networked real-time monitoring will be limited by cost, revealing a research gap related to the specific processing of signals. Static and dynamic accelerations are very noisy, and small variations of correctly processed static accelerations can be used as measurements and patterns of the biaxial inclination of many structures. This paper presents a biaxial tilt assessment for buildings based on a parallel training model and real-time measurements using inertial sensors, Wi-Fi Xbee, and Internet connectivity. The specific structural inclinations of the four exterior walls and their severity of rectangular buildings in urban areas with differential soil settlements can be supervised simultaneously in a control center. Two algorithms, combined with a new procedure using successive numeric repetitions designed especially for this work, process the gravitational acceleration signals, improving the final result remarkably. Subsequently, the inclination patterns based on biaxial angles are generated computationally, considering differential settlements and seismic events. The two neural models recognize 18 inclination patterns and their severity using an approach in cascade with a parallel training model for the severity classification. Lastly, the algorithms are integrated into monitoring software with 0.1° resolution, and their performance is verified on a small-scale physical model for laboratory tests. The classifiers had a precision, recall, F1-score, and accuracy greater than 95%.
Characterizing Periodic Variations of Atomic Frequency Standards via Their Frequency Stability Estimates
Authors: Cheng Weiwei , Nie Guigen , Zhu Jian
Published: June 2023

The onboard atomic frequency standard (AFS) is a crucial element of Global Navigation Satellite System (GNSS) satellites. However, it is widely accepted that periodic variations can influence the onboard AFS. The presence of non-stationary random processes in AFS signals can lead to inaccurate separation of the periodic and stochastic components of satellite AFS clock data when using least squares and Fourier transform methods. In this paper, we characterize the periodic variations of AFS using Allan and Hadamard variances and demonstrate that the Allan and Hadamard variances of the periodics are independent of the variances of the stochastic component. The proposed model is tested against simulated and real clock data, revealing that our approach provides more precise characterization of periodic variations compared to the least squares method. Additionally, we observe that overfitting periodic variations can improve the precision of GPS clock bias prediction, as indicated by a comparison of fitting and prediction errors of satellite clock bias.
3D Road Lane Classification with Improved Texture Patterns and Optimized Deep Classifier
Authors: Janakiraman Bhavithra , Shanmugam Sathiyapriya , Pérez de Prado Rocío , Wozniak Marcin
Published: June 2023

The understanding of roads and lanes incorporates identifying the level of the road, the position and count of lanes, and ending, splitting, and merging roads and lanes in highway, rural, and urban scenarios. Even though a large amount of progress has been made recently, this kind of understanding is ahead of the accomplishments of the present perceptual methods. Nowadays, 3D lane detection has become the trending research in autonomous vehicles, which shows an exact estimation of the 3D position of the drivable lanes. This work mainly aims at proposing a new technique with Phase I (road or non-road classification) and Phase II (lane or non-lane classification) with 3D images. Phase I: Initially, the features, such as the proposed local texton XOR pattern (LTXOR), local Gabor binary pattern histogram sequence (LGBPHS), and median ternary pattern (MTP), are derived. These features are subjected to the bidirectional gated recurrent unit (BI-GRU) that detects whether the object is road or non-road. Phase II: Similar features in Phase I are further classified using the optimized BI-GRU, where the weights are chosen optimally via self-improved honey badger optimization (SI-HBO). As a result, the system can be identified, and whether it is lane-related or not. Particularly, the proposed BI-GRU + SI-HBO obtained a higher precision of 0.946 for db 1. Furthermore, the best-case accuracy for the BI-GRU + SI-HBO was 0.928, which was better compared with honey badger optimization. Finally, the development of SI-HBO was proven to be better than the others.
A Novel Steganography Method for Infrared Image Based on Smooth Wavelet Transform and Convolutional Neural Network
Authors: Bai Yu , Li Li , Lu Jianfeng , Zhang Shanqing , Chu Ning
Published: June 2023

Infrared images have been widely used in many research areas, such as target detection and scene monitoring. Therefore, the copyright protection of infrared images is very important. In order to accomplish the goal of image-copyright protection, a large number of image-steganography algorithms have been studied in the last two decades. Most of the existing image-steganography algorithms hide information based on the prediction error of pixels. Consequently, reducing the prediction error of pixels is very important for steganography algorithms. In this paper, we propose a novel framework SSCNNP: a Convolutional Neural-Network Predictor (CNNP) based on Smooth-Wavelet Transform (SWT) and Squeeze-Excitation (SE) attention for infrared image prediction, which combines Convolutional Neural Network (CNN) with SWT. Firstly, the Super-Resolution Convolutional Neural Network (SRCNN) and SWT are used for preprocessing half of the input infrared image. Then, CNNP is applied to predict the other half of the infrared image. To improve the prediction accuracy of CNNP, an attention mechanism is added to the proposed model. The experimental results demonstrate that the proposed algorithm reduces the prediction error of the pixels due to full utilization of the features around the pixel in both the spatial and the frequency domain. Moreover, the proposed model does not require either expensive equipment or a large amount of storage space during the training process. Experimental results show that the proposed algorithm had good performances in terms of imperceptibility and watermarking capacity compared with advanced steganography algorithms. The proposed algorithm improved the PSNR by 0.17 on average with the same watermark capacity.
Particle Cut Diameter Prediction of Uniflow Cyclone Systems with Fuzzy System Analysis
Authors: Klapper Vinzenz , Luzi Giovanni , Prah Benedict , Delgado Antonio
Published: June 2023

Cyclones are devices used in various industries to remove particulate matter from gases and liquids. Commonly used in the power generation, cement, and mining industries, cyclones improve the efficiency and longevity of equipment by removing dust and other small particles that can cause wear and damage. Among centrifugal separation, reverse-flow cyclones are primarily used for particle separation, which can reach heights of several meters on an industrial scale and therefore, are difficult to access for maintenance. A uniflow centrifugal segregation system avoids these drawbacks of reverse-flow cyclones since their accessibility is good and their height usually does not exceed their diameter. The efficiency is a critical aspect of separating systems. This study systematically examines the collection efficiency for particles ranging from 1 µm to 29 µm in diameter based on varying vane angles of the swirl inducer at flow rates ranging from 130 L/s−1 to 236 L/s−1.
Exploring the Role of Foreign Direct Investment and Environmental Regulation in Regional Ecological Efficiency in the Context of Sustainable Development
Authors: Wu Yumei , Wang Rong , Wang Fayuan
Published: June 2023

Eco-efficiency (EE) is an important indicator of regional sustainable development, which reflects the efficiency of regional economic development in using resources effectively to reduce environmental pressures, and foreign direct investment and environmental regulation are very important in promoting regional economic growth and enhancing eco-efficiency. In this paper, we chose China’s panel data from 2009 to 2021, measured China’s regional eco-efficiency using the super-efficient SBM model, and explored environmental regulation and the impact of FDI on EE in different regions using the Tobit model, with conclusions as follows: (1) The average value of national EE in China during 2009–2021 was about 0.631, which was at a low level, and there were significant differences between regions, with the highest EE in the eastern region, and the central and western regions being lower than the national average. (2) FDI at the national level had a significant promoting effect on regional EE, with an elasticity coefficient of 0.0213, which verifies that the “pollution paradise” effect does not exist at national level. FDI promoted EE in the eastern region, while not being significant in the other two regions. The impact of the environmental regulation act on EE at the national level did not pass the significance test, but the impact passed the significance test with positive coefficients for both the eastern and central regions, while in the western region it was not significant. (3) Financial investment in science and technology promoted EE in the national, east, and central regions significantly, while not being significant in the western region. The economic development level of all regions was positively correlated with EE; the impact of urbanization on EE was significantly positive in national, central, and western regions, but was not significant in the eastern region. The industrial structure of all regions was not conducive to the improvement of EE, with the western region having the most negative impact on EE. The study in this paper represents an important addition and refinement to research in related fields.