bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Pt-Doped TiO2 Nanoparticles and Thickness of Semiconducting Layers at Photoanode in the Improved Performance of Dye-Sensitized Solar Cells
Authors: Mujahid M. , Al-Hartomy Omar A.
Published: November 2022

This work synthesized Pt-doped dye-sensitized solar cells (DSSC) with different molar ratios and thicknesses. The materials were revealed fully through X-ray diffraction (XRD), energy-dispersive spectroscopy (EDS), and transmission electron microscopy (TEM). The photovoltaic properties of the sample were studied by UV-visible spectroscopy, electrochemical impedance spectroscopy (EIS), and IPEC (incident photon-to-current conversion efficiency) techniques. EIS analysis established the decrease in series resistance at the electrolyte interface. It could be one of the reasons for the increase in electron transfer rate and decrease in the recombination process at the interface. Statistical data obtained from optical and electrical investigations revealed that the electrical power-output efficiency of DSSC was 14.25%. It was found that a high ratio of Pt doping and thinner thickness can promote cell performance, owing to the reduction of series resistance, lower bandgap, and high dye adsorption. Doping TiO2 with Pt reduced its energy bandgap and introduces intermediate energy levels inside TiO2 to facilitate the transition of electrons at low excitation energies. The absorbance of the samples 0.15 M Pt and 0.25 M Pt showed improvement in the wavelength ranging from 200 to 800 nm by Pt doping.
Atmospheric Pressure Plasma-Treated Polyurethane Foam as Reusable Absorbent for Removal of Oils and Organic Solvents from Water
Authors: Uricchio Antonella , Lasalandra Teresa , Tamborra Eliana R. G. , Caputo Gianvito , Mota Rogério P. , Fanelli Fiorenza
Published: November 2022

This paper reports the optimization of a two-step atmospheric pressure plasma process to modify the surface properties of a polyurethane (PU) foam and, specifically, to prepare a superhydrophobic/superoleophilic absorbent for the removal of oils and nonpolar organic solvents from water. In particular, in the first step, an oxygen-containing dielectric barrier discharge (DBD) is used to induce the etching/nanotexturing of the foam surfaces; in the second step, an ethylene-containing DBD enables uniform overcoating with a low-surface-energy hydrocarbon polymer film. The combination of surface nanostructuring and low surface energy ultimately leads to simultaneous superhydrophobic and superoleophilic wetting properties. X-ray photoelectron spectroscopy, scanning electron microscopy and water contact angle measurements are used for the characterization of the samples. The plasma-treated PU foam selectively absorbs various kinds of hydrocarbon-based liquids (i.e., hydrocarbon solvents, mineral oils, motor oil, diesel and gasoline) up to 23 times its own weight, while it completely repels water. These absorption performances are maintained even after 50 absorption/desorption cycles and after immersion in hot water as well as acidic, basic and salt aqueous solutions. The plasma-treated foam can remove mineral oil while floating on the surface of mineral oil/water mixtures with a separation efficiency greater than 99%, which remains unaltered after 20 separation cycles.
Influence of Thermal Modification in Nitrogen Atmosphere on the Selected Mechanical Properties of Black Poplar Wood (Populus nigra L.)
Authors: Bytner Olga , Drożdżek Michał , Laskowska Agnieszka , Zawadzki Janusz
Published: November 2022

The thermal modification of wood in a nitrogen atmosphere shapes the functional properties of wood. The aim of this research was to determine the influence of different levels of temperature and the duration of thermal modification on the mechanical properties of the black poplar (Populus nigra L.). Black poplar was thermally modified in nitrogen atmosphere in the temperature range from 160 °C to 220 °C (6 levels) for 2 h to 8 h (4 levels), resulting in a total of 24 treatments. The effect of these treatments on compressive strength parallel to the grain (CS), modulus of rupture (MOR), and modulus of elasticity during bending (MOE) were analyzed. Thermal modification influenced the mechanical properties of black poplar wood. After thermal modification occurred in a nitrogen atmosphere, an increase in compressive strength was noticeable for all variants of black poplar wood modification. The highest 16% increase in CS was obtained for the modification carried out at the temperature of 160 °C and for 2 h. An increase was also found for MOE when modified under mild conditions, while a decrease occurred for variants at higher temperatures, i.e., for 200 °C and 220 °C. The study showed that for all modification variants, there was a decrease in MOR alongside the increase in modification temperature and time.
New Insights into the Mechanism of Nucleation of ZrO2 Inclusions at High Temperature
Authors: Li Yutang , Wang Linzhu , Chen Chaoyi , Yang Shufeng , Li Xiang
Published: November 2022

It is difficult to observe the nucleation mechanism of inclusions in real-time. In this study, the nucleation process of zirconium oxide inclusions was systematically studied by classical nucleation theory and first principles. Zr deoxidized steel with 100 ppm Zr addition was processed into metallographic samples for scanning electron microscopy energy-dispersive spectroscopy observation. The electrolytic sample was analyzed by micro X-ray diffraction and transmission electron microscopy, and the zirconium oxide in the sample was determined to be ZrO2. The nucleation rate and radius of the ZrO2 inclusions were calculated by classical nucleation theory, and they were compared with the experimental values. There was a considerable difference between the experimental and theoretical values of the nucleation rate. The effect of the nucleation size was analyzed by first-principles calculation, and the thermodynamic properties of ZrO2 clusters and nanoparticles were analyzed by constructing (ZrO2)n (n = 1–6) clusters. The thermodynamic properties of ZrO2 calculated by first principles were consistent with the values in the literature. Based on two-step nucleation theory, the nucleation pathway of ZrO2 is as follows: Zratom + Oatom → (ZrO2)n → (ZrO2)2 → core (ZrO2 particle)–shell ((ZrO2)2 cluster) nanoparticle → (ZrO2)bulk.
On the Impact of Condensation and Liquid Water on the Radial Turbine of a Fuel Cell Turbocharger
Authors: Wittmann Tim , Lück Sebastian , Bode Christoph , Friedrichs Jens
Published: November 2022

The air-management system of a proton exchange membrane fuel cell (PEMFC) is responsible for supplying the fuel cell stack with ambient air at appropriate conditions. The compressor of the air-management system can be partly driven by utilizing the fuel cell exhaust gas in a turbine. The fuel cell exhaust is partially or fully saturated with water vapor. When the exhaust gas is expanded in the turbine, supersaturation occurs. This leads to the nucleation of droplets and their subsequent growth by condensation. This study provides an overview and understanding of the various phenomena caused by condensation and liquid water in the turbine of a PEMFC air-management system. The basis for this work is previously published numerical simulations that focused on individual aspects of the above phenomena. The present work revisits these results and puts them in context to provide a comprehensive understanding. Important phenomena are the effects of condensation on turbine performance through phase change losses, release of latent heat and thermal throttling. In addition, the released latent heat offers a power potential for downstream turbine stages. Through these effects, condensation can also impact the entire air-management system. However, condensation may occur unevenly, causing a circumferential asymmetry of the turbine outflow. Liquid water in the turbine can lead to droplet erosion, corrosion, and water-induced damage. In summary, it is essential to consider condensation and liquid water when developing turbines for PEMFC air-management systems.
Development and Experimental Verification of a High-Temperature and In-Plane Biaxial Testing Apparatus
Authors: Chen Junxian , Zhang Jianhai , Zhao Hongwei
Published: November 2022

Given the lack of primary data on heat-resistant composites under high-temperature conditions, the focus of this paper is the development of an in-plane biaxial apparatus under high temperatures and complex loads. Besides loading complex loads up to 80 kN, the apparatus can load under high-temperatures up to 2500 °C. A C/C tensile/compression test at 1700 °C illustrates the successful use of high-temperature digital speckle pattern technology to evaluate the in-plane mechanical properties of heat-resistant composites at 1700 °C under biaxial stress. A high-temperature impact test of a graphite specimen at 2500 °C shows that this apparatus can load at a high temperature in a vacuum and inert gas atmosphere. The yield characteristics of the Q235 steel sheet under in-plane stress show that the apparatus can conduct various mechanical loads, including tension–tension, tension–compression, and compression–compression loads. The proposed equipment can measure the in-plane mechanical properties of composite materials, particularly heat-resistant composites. The obtained results can be applied to structural design, life prediction, and reliability evaluation, as well as for the development, research, and design of aerospace instruments and critical materials.
Development of an Earthworm-Based Intestinal Soft Robot Equipped with a Gripper
Authors: Li Gongxin , Qiu Wei , Wen Hao , Wang Mindong , Liu Fei
Published: November 2022

An endoscopy is a tool that is used to examine the interior of a hollow organ or cavity of the body by inserting directly into the organ. However, intestinal endoscopy is not friendly to patients due to discomfort, and it can easily cause intestinal damage or even perforation due to the use of the rigid materials of the endoscopy. Here, we provide an earthworm-based intestinal soft robot equipped with a gripper for application on intestinal exams or surgery. The intestinal soft robot is composed of a frontal radial actuator, a central axial actuator, a rear radial actuator and a gripper. The first three actuators drive the robot to move freely in some specific pipes by altering its own deformation, and the gripper, fixed at the end of the frontal radial actuator, is used to pick up “foreign bodies” into and out of the pipes for the purpose of intestinal applications. The different experiments validated that the intestinal soft robot could move forward and backward autonomously in a rigid pipe, a flexible pipe, and a mucus-containing pipe and could extract objects from these pipes. The ultimate weight that the intestinal soft robot extracts is up to 220 g, and the maximum moving speed is 12.0 cm/min in the rigid pipe. This intestinal soft robot is non-destructive to the operating environment, providing a friendly and novel method for the application of intestinal diseases.
Designing Computer Games to Teach Finance and Technical Concepts in an Online Learning Context: Potential and Effectiveness
Authors: Imam Tasadduq , Cowling Michael , Das Narottam
Published: November 2022

Designing computer games to educate students is not a new technique. Not all disciplines, however, embed the same degree of cognitive load, and not all game design approaches are appropriate across contexts. Teaching technical business disciplines, such as finance, using a game imposes specific challenges, especially when the subject is offered online and to students who may not be from relevant technical backgrounds. However, there has only been limited attention concerning the use of game-based learning (GBL) for teaching finance at the higher education level, especially when delivered online. This article explores the potential of GBL to teach finance at an Australian university. We further present the outcomes of a survey of students’ experiences concerning the unique business simulation tool. The results reveal that while a game-based intervention can positively affect students’ learning in a technical discipline, such as finance, the design also needs to be such that the players can relate the experience to learning goals and practical needs for satisfactory outcomes. A defining aspect of this research is using Bayesian analysis, capable of gaining insights irrespective of sample size, yet not widely used in the higher education research area in favour of the frequentist analysis. Bayesian analysis shows a high probability of the educational game achieving positive or satisfactory ratings. Further, two aspects of a game—functionalities and usability and perception of impact—are particularly noted to influence the game’s overall rating. Overall, the outcomes from this research call for careful consideration of the learners’ requirements and capability towards ensuring an enjoyable outcome rather than just focusing on a game’s content or context.
Stochastic Capital–Labor Lévy Jump Model with the Precariat Labor Force
Authors: Danane Jaouad
Published: November 2022

In this work, we study a capital–labor model by considering the interaction between the new proposed and the confirmed free jobs, the precariat labor force, and the mature labor force by introducing Brownian motion and Lévy noise. Moreover, we illustrate the well-posedness of the solution. In addition, we establish the conditions of the extinction of both the free jobs and labor force; subsequently, we prove the persistence of only the free jobs, and we also show the conditions of the persistence of both the free jobs and labor force. Finally, we validate our theoretical finding by numerical simulation by building a new stochastic Runge–Kutta method.
Application of Gene Knockout and Heterologous Expression Strategy in Fungal Secondary Metabolites Biosynthesis
Authors: Ning Yaodong , Xu Yao , Jiao Binghua , Lu Xiaoling
Published: November 2022

The in-depth study of fungal secondary metabolites (SMs) over the past few years has led to the discovery of a vast number of novel fungal SMs, some of which possess good biological activity. However, because of the limitations of the traditional natural product mining methods, the discovery of new SMs has become increasingly difficult. In recent years, with the rapid development of gene sequencing technology and bioinformatics, new breakthroughs have been made in the study of fungal SMs, and more fungal biosynthetic gene clusters of SMs have been discovered, which shows that the fungi still have a considerable potential to produce SMs. How to study these gene clusters to obtain a large number of unknown SMs has been a research hotspot. With the continuous breakthrough of molecular biology technology, gene manipulation has reached a mature stage. Methods such as gene knockout and heterologous expression techniques have been widely used in the study of fungal SM biosynthesis and have achieved good effects. In this review, the representative studies on the biosynthesis of fungal SMs by gene knockout and heterologous expression under the fungal genome mining in the last three years were summarized. The techniques and methods used in these studies were also briefly discussed. In addition, the prospect of synthetic biology in the future under this research background was proposed.
Nutrient-Limited Operational Strategies for the Microbial Production of Biochemicals
Authors: Rajpurohit Hemshikha , Eiteman Mark A.
Published: November 2022

Limiting an essential nutrient has a profound impact on microbial growth. The notion of growth under limited conditions was first described using simple Monod kinetics proposed in the 1940s. Different operational modes (chemostat, fed-batch processes) were soon developed to address questions related to microbial physiology and cell maintenance and to enhance product formation. With more recent developments of metabolic engineering and systems biology, as well as high-throughput approaches, the focus of current engineers and applied microbiologists has shifted from these fundamental biochemical processes. This review draws attention again to nutrient-limited processes. Indeed, the sophisticated gene editing tools not available to pioneers offer the prospect of metabolic engineering strategies which leverage nutrient limited processes. Thus, nutrient- limited processes continue to be very relevant to generate microbially derived biochemicals.
Emerging Direct Targeting β-Catenin Agents
Authors: Nalli Marianna , Masci Domiziana , Urbani Andrea , La Regina Giuseppe , Silvestri Romano
Published: November 2022

Aberrant accumulation of β-catenin in the cell nucleus as a result of deregulation of the Wnt/β-catenin pathway is found in various types of cancer. Direct β-catenin targeting agents are being researched despite obstacles; however, specific β-catenin drugs for clinical treatments have not been approved so far. We focused on direct β-catenin targeting of potential therapeutic value as anticancer agents. This review provides recent advances on small molecule β-catenin agents. Structure-activity relationships and biological activities of reported inhibitors are discussed. This work provides useful knowledge in the discovery of β-catenin agents.
Lycopene Improves Metabolic Disorders and Liver Injury Induced by a Hight-Fat Diet in Obese Rats
Authors: Baz Lina , Algarni Salha , Al-thepyani Mona , Aldairi Abdullah , Gashlan Hana
Published: November 2022

Epidemiological studies have shown that the consumption of a high-fat diet (HFD) is positively related to the development of obesity. Lycopene (LYC) can potentially combat HFD-induced obesity and metabolic disorders in rats. This study aimed to investigate the effect of LYC on metabolic syndrome and assess its anti-inflammatory and antioxidant effects on the liver and adipose tissue in rats fed an HFD. Thirty-six male Wistar albino rats were divided into three groups. Group Ι (the control group) was fed a normal diet, group ΙΙ (HFD) received an HFD for 16 weeks, and group ΙΙΙ (HFD + LYC) received an HFD for 12 weeks and then LYC (25 mg/kg b.wt) was administered for four weeks. Lipid peroxidation, antioxidants, lipid profile, liver function biomarkers, and inflammatory markers were determined. The results showed that long-term consumption of an HFD significantly increased weight gain, liver weight, and cholesterol and triglyceride levels. Rats on an HFD displayed higher levels of lipid peroxidation and inflammatory markers. Moreover, liver and white adipose tissue histopathological investigations showed that LYC treatment mended the damaged tissue. Overall, LYC supplementation successfully reversed HFD-induced changes and shifts through its antioxidant and anti-inflammatory activity. Therefore, LYC displayed a therapeutic potential to manage obesity and its associated pathologies.
Comparative Study of Useful Compounds Extracted from Lophanthus anisatus by Green Extraction
Authors: Stefan Daniela-Simina , Popescu Mariana , Luntraru Cristina-Mihaela , Suciu Alexandru , Belcu Mihai , Ionescu Lucia-Elena , Popescu Mihaela , Iancu Petrica , Stefan Mircea
Published: November 2022

Essential oils were obtained from different parts of Agastache foeniculum (Lophanthus anisatus) plants by means of extraction: green extraction using hydro-distillation (HD) and bio-solvent distillation, BiAD, discontinuous distillation, and supercritical fluid extraction, in two stages: (1) with CO2, and (2) with CO2 and ethanol co-solvent. The extraction yields were determined. The yield values varied for different parts of the plant, as well as the method of extraction. Thus, they had the values of 0.62 ± 0.020 and 0.92 ± 0.015 g/100 g for the samples from the whole aerial plant, 0.75 ± 0.008 and 1.06 ± 0.005 g/100 g for the samples of leaves, and 1.22 ± 0.011 and 1.60 ± 0.049 g/100 g for the samples of flowers for HD and BiAD, respectively. The yield values for supercritical fluid extraction were of 0.94 ± 0.010 and 0.32 ± 0.007 g/100 g for the samples of whole aerial plant, 0.9 ± 0.010 and 1.14 ± 0.008 g/100 g for the samples of leaves, and 1.94 ± 0.030 and 0.57 ± 0.003 g/100 g for the samples of flowers, in the first and second stages, respectively. The main components of Lophanthus anisatus were identified as: estragon, limonene, eugenol, chavicol, benzaldehyde, and pentanol. The essential oil from Agatache foeniculum has antimicrobial effects against Staphylococcus aureus, the Escherichia coli and Pseudomonas aeruginosa. Acclimatization of Lophantus anisatus in Romania gives it special qualities by concentrating components such as: estragole over 93%, limonene over 8%, especially in flowers; and chavicol over 14%, estragole over 30%, eugenol and derivatives (methoxy eugenol, methyl eugenol, etc.) over 30% and phenyl ether alcohol over 20% in leaves. As a result of the research carried out, it was proven that Lophanthus anisatus can be used as a medicinal plant for many diseases, it can be used as a spice and preservative for various foods, etc.
A Novel Method for the Background Signal Correction in SP-ICP-MS Analysis of the Sizes of Titanium Dioxide Nanoparticles in Cosmetic Samples
Authors: Temerdashev Zaual A. , Galitskaya Olga A. , Bolshov Mikhail A.
Published: November 2022

We discuss the features involved in determining the titanium dioxide nanoparticle (TiO2NP) sizes in cosmetic samples via single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) in the millisecond-time resolution mode, and methods for considering the background signal. In the SP-ICP-MS determination of TiO2NPs in cosmetics, the background signal was recorded in each dwell time interval due to the signal of the Ti dissolved form in deionized water, and the background signal of the cosmetic matrix was compensated by dilution. A correction procedure for the frequency and intensity of the background signal is proposed, which differs from the known procedures due to its correction by the standard deviation above the background signal. Background signals were removed from the sample signal distribution using the deionized water signal distribution. Data processing was carried out using Microsoft Office Excel and SPCal software. The distributions of NP signals in cosmetic product samples were studied in the dwell time range of 4–20 ms. The limit of detection of the NP size (LODsize) with the proposed background signal correction procedure was 71 nm. For the studied samples, the LODsize did not depend on the threshold of the background signal and was determined by the sensitivity of the mass spectrometer.
The Synergic Effect of a Nutraceutical Supplementation Associated to a Mediterranean Hypocaloric Diet in a Population of Overweight/Obese Adults with NAFLD
Authors: Chiurazzi Martina , Cacciapuoti Nunzia , Di Lauro Mariastella , Nasti Gilda , Ceparano Margherita , Salomone Elisabetta , Guida Bruna , Lonardo Maria Serena
Published: November 2022

Overweight/obesity is often associated with a non-alcoholic fatty liver disease (NAFLD). The study aim was to investigate the effects of a nutraceutical supplementation associated to a Mediterranean-hypocaloric-diet (MHD) on ultrasound-liver-steatosis (ULS) grade improvement in overweight/obese patients with NAFLD. A total of 68 subjects (BMI ≥ 25 kg/m2) with NAFLD were recruited, randomized into 2 groups and treated for 3 months: the Nutraceutical group was treated with MHD plus nutraceutical supplementation (Vitamin E, L-glutathione, silymarin and hepato-active compounds); the Control-group only with a MHD. Anthropometric measurements, body composition, biochemical parameters and Hepatic steatosis index (HSI) were evaluated at baseline and after 3 months; patients with HSI >36 underwent a liver ultrasound to determine liver steatosis grade (3 severe, 2 moderate, 1 mild). In all patients, a significant improvement in nutritional and biochemical parameters was observed after treatment. After treatment, the nutraceutical group showed a significant improvement in hepatic steatosis, either according to ULS-grade (11.1% and 5.6% of patients with mild and moderate liver steatosis, respectively, showed a complete NAFLD regression; 33.3% and 22.2% of patients with moderate and severe liver steatosis, respectively showed a regression to mild liver steatosis), or according to HSI (49.3 ± 10.1 vs. 43.3 ± 9.0, p = 0.01), suggesting that a healthy diet is still the best choice, although the use of specific supplements can enhance the efficacy of dietary intervention in overweight/obese patients with NAFLD.
Isoflavone-Enriched Soybean Leaves (Glycine Max) Alleviate Cognitive Impairment Induced by Ovariectomy and Modulate PI3K/Akt Signaling in the Hippocampus of C57BL6 Mice
Authors: Yoo Dae Young , Jung Soonwoong , Kang Jae Soon , Baek Ji Hyeong , Park Ki Hun , Lee Dong Hoon , Kang Sang Soo , Kim Hyun Joon
Published: November 2022

(1) Background: The estrogen decline during perimenopause can induce various disorders, including cognitive impairment. Phytoestrogens, such as isoflavones, lignans, and coumestans, have been tried as a popular alternative to avoid the side effects of conventional hormone replacement therapy, but their exact mechanisms and risk are not fully elucidated. In this study, we investigated the effects of isoflavone-enriched soybean leaves (IESLs) on the cognitive impairment induced by ovariectomy in female mice. (2) Methods: Ovariectomy was performed at 9 weeks of age to mimic menopausal women, and the behavior tests for cognition were conducted 15 weeks after the first administration. IESLs were administered for 18 weeks. (3) Results: The present study showed the effects of IESLs on the cognitive function in the OVX (ovariectomized) mice. Ovariectomy markedly increased the body weight and fat accumulation in the liver and perirenal fat, but IESL treatment significantly inhibited them. In the behavioral tests, ovariectomy impaired cognitive functions, but administration of IESLs restored it. In addition, in the OVX mice, administration of IESLs restored decreased estrogen receptor (ER) β and PI3K/Akt expression in the hippocampus. (4) Conclusions: The positive effects of IESLs on cognitive functions may be closely related to the ER-mediated PI3/Akt signaling pathway in the hippocampus.
Spatial Differences of Nutrient Adequacy in Coastal Areas of China
Authors: Yin Wei , Yu Huijuan , Wang Yecheng , Qiu Rongshan , Han Limin
Published: November 2022

Ensuring nutrient adequacy for all is a common goal of the international community, but spatial difference is one of the barriers to its development. Exploring nutrient adequacy in coastal areas of China can help regions where food production systems and economic development systems are under mutual stress to reduce nutritional disparities and improve nutrition levels. This paper used the transformation food-to-nutrient model to calculate nutrient production and nutrient consumption in 11 coastal provinces of China and analyzed their spatial patterns, after which spatial differences in nutrient adequacy (including energy, protein and fat) were analyzed. The results showed that nutrient production and nutrient consumption in coastal areas of China showed significant spatial differences, in which nutrient production was mainly concentrated in land food, and the three provinces of Shandong, Jiangsu and Hebei contributed more. Guangdong had the highest nutrient consumption; in contrast, Shanghai, Tianjin, and Hainan had the lowest consumption. Nutrient adequacy was not optimistic, with fat being particularly significant, and nutrient surplus quantity was mainly concentrated in Shandong and Jiangsu and nutrient deficiency quantity was mainly concentrated in Guangdong. Overall, the study area had adequate levels of protein and was deficient in energy and fat levels, with surplus or shortage of 2.41 million tonnes, 2620 billion kcal and 9.97 million tonnes, respectively.
Physical Exercise-Induced FGF-21 to Fight Obesity: An Update Review
Authors: Vecchiatto Bruno , de Castro Thiago Lucas , Muller Cynthia R. , Azevedo-Martins Anna Karenina , Evangelista Fabiana S.
Published: November 2022

Fibroblast growth factor 21 (FGF-21) is a protein that is involved in the regulation of glucose, lipids, and energy metabolism. To act on target tissues, endocrine FGF-21 binds preferably to FGF receptor 1 (FGFR1) in the presence of the coreceptor named β-klotho (KLB). Some of the effects of FGF-21 include increased fatty acid oxidation, glucose uptake, insulin sensitivity, and thermogenesis, which can regulate body weight and glycemia control. By exerting such metabolic effects, the therapeutic potential of FGF-21 for the treatment of obesity and diabetes has been investigated. Physical exercise has been widely used for the prevention and treatment of obesity. Several mechanisms mediate the effects of physical exercise, including the FGF-21 pathway. Studies have shown that physical exercise increases the concentration of circulating and tissue FGF-21 in animals, while contradictory results are still observed in humans. Considering the metabolic role of FGF-21 and the chance of physical exercise to induce FGF-21 secretion, in this review we explore the potential of physical exercise-induced FGF-21 modulation as a strategy for prevention and treatment of obesity.
Drug Resistance to Integrase Strand-Transfer Inhibitors among HIV-1-Infected Adults in Guangdong, China
Authors: Lan Yun , Li Linghua , Xin Ruolei , Ling Xuemei , Deng Xizi , Li Junbin , Li Liya , Cai Weiping , Li Feng , Hu Fengyu
Published: November 2022

Background: Integrase strand-transfer inhibitor (INSTI)-containing regimens have gradually been administered in Guangdong Province, China beginning in 2016, and INSTI-related drug resistance (DR) may occur and should be monitored among HIV-1-infected patients. Objective: To investigate the prevalence of INSTI-related resistance among HIV-1-infected individuals in Guangdong and provide evidence for the optimal administration of INSTIs. Methods: This study recruited 1208 HIV-1-infected patients (including 404 ART-naive and 804 ART-experienced patients) between June 2021 and April 2022. The entire integrase gene was amplified from blood plasma. Demographic and epidemiological information were collected. INSTI mutations and susceptibility were interpreted using the Stanford HIV Drug Resistance Database HIVdb program. Results: Of the 1208 enrolled individuals, 2.65% (32/1208) carried at least one INSTI major or accessory drug resistance mutation (DRM), with 1.49% (6/404) being from ART-naive individuals and 3.23% (26/804) from ART-experienced individuals. Among them, seven polymorphic major mutations were detected. Although no INSTI drug resistance was found among treatment-naive patients, seven ART-experienced patients (0.87%, 7/804) carried mutations conferring resistance to INSTIs. Conclusion: The overall prevalence of INSTI DRMs and DR was comparatively low among ART-naive and ART-treated populations in Guangdong; however, INSTI-related polymorphic mutations were observed. Surveillance should be reinforced before transfer to INSTI-containing regimens.
Can Essential Oils Provide an Alternative Adjuvant Therapy for COVID-19 Infections and Pain Management at the Same Time?
Authors: Damiescu Roxana , Lee David Y. W. , Efferth Thomas
Published: November 2022

The active compounds from essential oils have been an important asset in treating different diseases for many centuries. Nowadays, there are various available formulations used as food supplements to stimulate the immune system. In light of the current pandemic and the large amount of fake news circulating the internet, it is important to analyze which of the active compounds from essential oils can be successfully used in the treatment of COVID-19 infections. We analyzed the current literature on the effects of essential oils against the new SARS-CoV-2 virus to gain a better understanding of the underlying mechanisms of these compounds and establish their possible antiviral efficacy. The available studies have highlighted the antiviral potential of active compounds from essential oils, indicating that they could be used as adjuvants in treating various viral infections, including COVID-19, leading to a milder course of the disease, and improving patients’ outcomes. At the same time, these compounds relieve pain and lift the mood in comorbid patients suffering from opioid addiction. Essential oils might be useful as adjuvant tools, not only against SARS-CoV-2 but also for a subset of especially vulnerable patients affected with both COVID-19 and opioid addiction. However, randomized clinical trials are needed to determine their efficacy and develop standardized high-quality preparations that can be safely administered to the general population.
Enhancing the Terahertz Absorption Spectrum Based on the Low Refractive Index All-Dielectric Metasurface
Authors: Liu Pingan , Li Wenping , Chen Naichang , Ma Chan , Li Xiangjun , Yan Dexian
Published: November 2022

We presented an angle-multiplexing low refractive index dielectric metasurface for terahertz absorption spectrum enhancement of lactose with high Q resonance properties. The unit cell structure of the acrylonitrile butadiene styrene (ABS) square structure is designed and optimized. The resonant peak shifts of the dielectric metasurface are analyzed by changing the incident angle of the terahertz wave. Then the α-lactose films with different thicknesses are added to investigate the enhancement effect. The resonant peak amplitude of the angle-multiplexing low refractive index dielectric metasurface absorption spectrum changes greatly with the absorption spectrum of the samples. The results illustrate that the enhanced absorption spectrum formed by the linked envelope can be up to 45 times stronger than that without the unit cell structures and also exhibits a high-quality factor. The proposed dielectric metasurface provides great potential in enhancing the terahertz absorption spectrum.
Insecticidal Activities and GC-MS Analysis of the Selected Family Members of Meliaceae Used Traditionally as Insecticides
Authors: Shilaluke Kolwane Calphonia , Moteetee Annah Ntsamaeeng
Published: November 2022

The environmental and health risks associated with synthetic pesticides have increased the demand for botanical insecticides as safer and biodegradable alternatives to control insect pests in agriculture. Hence in this study, five Meliaceae species were evaluated for their insecticidal activities against the Spodoptera frugiperda and the Plutella xylostella larvae, as well as their chemical constituents. Repellence, feeding deterrence, and topical application bioassays were employed to evaluate their insecticidal activities. GC-MS analysis was performed to identify chemical compounds present in each plant. The repellence bioassay indicated that Melia azedarach extracts exhibited the highest repellence percentage against S. frugiperda (95%) and P. xylostella (90%). The feeding deterrence bioassay showed that M. azedarach and Trichilia dregeana extracts displayed excellent antifeeding activity against the S. frugiperda (deterrent coefficient, 83.95) and P. xylostella (deterrent coefficient, 112.25), respectively. The topical application bioassay demonstrated that Ekebergia capensis extracts had the highest larval mortality against S. frugiperda (LD50 0.14 mg/kg). Conversely, M. azedarach extracts showed the highest larval mortality against P. xylostella (LD50 0.14 mg/kg). GC-MS analysis revealed that all plant extracts had compounds belonging to the two noteworthy groups (phenols and terpenes), which possess insecticidal properties. Overall, this study lends scientific credence to the folkloric use of Meliaceae species as potential biocontrol agents against insect pests.
Comparison of High-Resolution 14C and Luminescence-Based Chronologies of the MIS 2 Madaras Loess/Paleosol Sequence, Hungary: Implications for Chronological Studies
Authors: Sümegi Pál , Molnár Dávid , Gulyás Sándor , Stevens Thomas , Makó László , Cseh Péter , Molnár Mihály , Fitzsimmons Kathryn , Nett Janina J. , Hlavatskyi Dmytro , Lehmkuhl Frank
Published: November 2022

Numerous loess/paleosol sequences (LPS) in the Carpathian Basin span the period of Marine Isotope Stage (MIS) 2 and the last glacial maximum (LGM). Nevertheless, only two known records—Madaras and Dunaszekcső—preserve highly resolved records with absolute chronologies with minimal uncertainties, which enable the meaningful assessment of feedbacks and short-term climatic fluctuations over this period. The Madaras profile is located at the northern margin fringe of the Bácska loess plateau; Dunaszekcső, located on the Danube to its west, yields a chronology built on over 100 14C dates yet spans only part of MIS 2, missing half of the LGM including its peak. Here, we add to the previously published 14C chronology for Madaras (15 dates) with an additional 17 14C and luminescence ages. Resulting age models built solely on quartz OSL and feldspar pIRIRSL data underestimate the 14C based chronology, which is likely based on inaccuracies related to luminescence signal behavior; we observe age underestimations associated with unusual quartz behavior and significant signal loss, a phenomenon also observed in Serbian and Romanian loess, which may relate to non-sensitized grains from proximal sources. Our new chronology provides higher resolution than hitherto possible, yielding consistent 2 sigma uncertainties of ~150–200 years throughout the entire sequence. Our study indicates that the addition of further dates may not increase the chronological precision significantly. Additionally, the new age model is suitable for tackling centennial-scale changes. The mean sedimentation rate based on our new age-depth model (10.78 ± 2.34 years/cm) is the highest yet recorded in the Carpathian Basin for MIS 2. The resolution of our age model is higher than that for the Greenland NGRIP ice core record. The referred horizons in our profile are all characterized by a drop in accumulation and a higher sand input, the latter most likely deriving from nearby re-exposed sand dunes.
Consecutive Pre-Training: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domain
Authors: Zhang Tong , Gao Peng , Dong Hao , Zhuang Yin , Wang Guanqun , Zhang Wei , Chen He
Published: November 2022

Currently, under supervised learning, a model pre-trained by a large-scale nature scene dataset and then fine-tuned on a few specific task labeling data is the paradigm that has dominated knowledge transfer learning. Unfortunately, due to different categories of imaging data and stiff challenges of data annotation, there is not a large enough and uniform remote sensing dataset to support large-scale pre-training in the remote sensing domain (RSD). Moreover, pre-training models on large-scale nature scene datasets by supervised learning and then directly fine-tuning on diverse downstream tasks seems to be a crude method, which is easily affected by inevitable incorrect labeling, severe domain gaps and task-aware discrepancies. Thus, in this paper, considering the self-supervised pre-training and powerful vision transformer (ViT) architecture, a concise and effective knowledge transfer learning strategy called ConSecutive Pre-Training (CSPT) is proposed based on the idea of not stopping pre-training in natural language processing (NLP), which can gradually bridge the domain gap and transfer large-scale data knowledge to any specific domain (e.g., from nature scene domain to RSD) In addition, the proposed CSPT also can release the huge potential of unlabeled data for task-aware model training. Finally, extensive experiments were carried out on twelve remote sensing datasets involving three types of downstream tasks (e.g., scene classification, object detection and land cover classification) and two types of imaging data (e.g., optical and synthetic aperture radar (SAR)). The results show that by utilizing the proposed CSPT for task-aware model training, almost all downstream tasks in the RSD can outperform the previous knowledge transfer learning strategies based on model pre-training without any expensive manually labeling and even surpass the state-of-the-art (SOTA) performance without any careful network architecture designing.
Landsat-8 and Sentinel-2 Based Prediction of Forest Plantation C Stock Using Spatially Varying Coefficient Bayesian Hierarchical Models
Authors: Chinembiri Tsikai Solomon , Mutanga Onisimo , Dube Timothy
Published: November 2022

This study sought to establish the performance of Spatially Varying Coefficient (SVC) Bayesian Hierarchical models using Landsat-8, and Sentinel-2 derived auxiliary information in predicting plantation forest carbon (C) stock in the eastern highlands of Zimbabwe. The development and implementation of Zimbabwe’s land reform program undertaken in the year 2000 and the subsequent redistribution and resizing of large-scale land holdings are hypothesized to have created heterogeneity in aboveground forest biomass in plantation ecosystems. The Bayesian hierarchical framework, accommodating residual spatial dependence and non-stationarity of model predictors, was evaluated. Firstly, SVC models utilizing Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Enhanced Vegetation Index (EVI), derived from Landsat-8 and Sentinel-2 data and 191 sampled C stock observations were constructed. The SVC models built for each of the two multispectral remote sensing data sets were assessed based on the goodness of fit criterion as well as the predictive performance using a 10-fold cross-validation technique. The introduction of spatial random effects in the form of Landsat-8 and Sentinel-2 derived covariates to the model intercept improved the model fit and predictive performance where residual spatial dependence was dominant. For the Landsat-8 C stock predictive model, the RMSPE for the non-spatial, Spatially Varying Intercept (SVI) and SVC models were 8 MgCha−1, 7.77 MgCha−1, and 6.42 MgCha−1 whilst it was 7.85 MgCha−1, 7.69 MgCha−1 and 6.23 MgCha−1 for the Sentinel-2 C stock predictive models, respectively. Overall, the Sentinel-2-based SVC model was preferred for predicting C stock in plantation forest ecosystems as its model provided marginally tighter credible intervals, [1.17–1.60] MgCha−1 when compared to the Landsat-8 based SVC model with 95% credible intervals of [1.13–1.62] Mg Cha−1. The built SVC models provided an understanding of the performance of the multispectral remote sensing derived predictors for modeling C stock and thus provided an essential foundation required for updating the current carbon forest plantation databases.
Global Terrestrial Water Storage Reconstruction Using Cyclostationary Empirical Orthogonal Functions (1979–2020)
Authors: Chandanpurkar Hrishikesh A. , Hamlington Benjamin D. , Reager John T.
Published: November 2022

Terrestrial water storage (TWS) anomalies derived from the Gravity Recovery and Climate Experiment (GRACE) mission have been useful for several earth science applications, ranging from global earth system science studies to regional water management. However, the relatively short record of GRACE has limited its use in understanding the climate-driven interannual-to-decadal variability in TWS. Targeting these timescales, we used the novel method of cyclostationary empirical orthogonal functions (CSEOFs) and the common modes of variability of TWS with precipitation and temperature to reconstruct the TWS record of 1979–2020. Using the same common modes of variability, we also provide a realistic, time-varying uncertainty estimate of the reconstructed TWS. The interannual variability in the resulting TWS record is consistent in space and time, and links the global variations in TWS to the regional ones. In particular, we highlight improvements in the representation of ENSO variability when compared to other available TWS reconstructions.
Recognition of Ballistic Targets by Fusing Micro-Motion Features with Networks
Authors: Yang Lei , Zhang Wenpeng , Jiang Weidong
Published: November 2022

Ballistic target recognition is of great significance for space attack and defense. The micro-motion features, which contain spatial and motion information, can be regarded as the foundation of the recognition of ballistic targets. To take full advantage of the micro-motion information of ballistic targets, this paper proposes a method based on feature fusion to recognize ballistic targets. The proposed method takes two types of data as input: the time–range (TR) map and the time–frequency (TF) spectrum. An improved feature extraction module based on 1D convolution and time self-attention is applied first to extract the multi-level features at each time instant and the global temporal information. Then, to efficiently fuse the features extracted from the TR map and TF spectrum, deep generalized canonical correlation analysis with center loss (DGCCA-CL) is proposed to transform the extracted features into a hidden space. The proposed DGCCA-CL possesses better performance in two aspects: small intra-class distance and compact representation, which is crucial to the fusion of multi-modality data. At last, the attention mechanism-based classifier which can adaptively focus on the important features is employed to give the target types. Experiment results show that the proposed method outperforms other network-based recognition methods.
Multiple Band Prioritization Criteria-Based Band Selection for Hyperspectral Imagery
Authors: Sun Xudong , Shen Xin , Pang Huijuan , Fu Xianping
Published: November 2022

Band selection (BS) is an effective pre-processing way to reduce the redundancy of hyperspectral data. Specifically, the band prioritization (BP) criterion plays an essential role since it can judge the importance of bands from a particular perspective. However, most of the existing methods select bands according to a single criterion, leading to incomplete band evaluation and insufficient generalization against different data sets. To address this problem, this work proposes a multi-criteria-based band selection (MCBS) framework, which innovatively treats BS as a multi-criteria decision-making (MCDM) problem. First, a decision matrix is constructed based on several typical BPs, so as to evaluate the bands from different focuses. Then, MCBS defines the global positive and negative idea solutions and selects bands according to their relative closeness to these solutions. Since each BP has a different capability to discriminate the bands, two weight estimation approaches are developed to adaptively balance the contributions of various criteria. Finally, this work also provides an extended version of MCBS, which incorporates the subspace partition strategy to reduce the correlation of the selected bands. In this paper, the classification task is used to evaluate the performance of the selected band subsets. Extensive experiments on three public data sets verify that the proposed method outperforms other state-of-the-art methods.