bluuebunny/crossref_metadata_2025 huggingface dataset:
Nutrition, Immune Function, and Infectious Disease in Military Personnel: A Narrative Review
Authors: Hatch-McChesney Adrienne , Smith Tracey J.
Published: December 2023

Consuming a diet that meets energy demands and provides essential nutrients promotes a healthy immune system, while both under- and over-nutrition have been associated with immune dysfunction. Military personnel comprise a unique population who frequently endure multi-stressor environments, predisposing them to immune decrements. Additionally, 49% and 22% of active duty U.S. military personnel are classified as overweight and obese, respectively. A literature search on PubMed was conducted to identify studies, reports, review papers, and references within those sources relevant to the topic area. Military personnel experiencing either under- or over-nutrition can suffer from degraded health, readiness, and performance. Insufficient intake of nutrients during military operations increases infection risk and negatively impacts infection recovery. Energy, protein, iron, zinc, and vitamins C and D are nutritional areas of concern that may impact immune competence in a multi-stressor environment. Over-nutrition can promote accretion of excess body fat and obesity, which contributes to a chronic inflammatory state that coincides with immune impairments. Prioritizing efforts to optimize nutrient intake is one approach for reducing disease burden and improving readiness. This review discusses nutritional concerns concomitant to multi-stressor environments that impact immune function, and the relevance of obesity to infectious disease risk in the military population.
The Effect of Iron-Fortified Lentils on Blood and Cognitive Status among Adolescent Girls in Bangladesh
Authors: Barnett Amy L. , Wenger Michael J. , Yunus Fakir M. , Jalal Chowdhury , DellaValle Diane M.
Published: December 2023

Background: Iron deficiency is highly prevalent in South Asia, especially among women and children in Bangladesh. Declines in cognitive performance are among the many functional consequences of iron deficiency. Objective: We tested the hypothesis that, over the course of a 4-month iron fortification trial, cognitive performance would improve, and that improvement would be related to improvements in iron status. Methods: Participants included 359 adolescent girls attending Bangladesh Rural Advancement Committee (BRAC) clubs as a subsample of a larger double-blind, cluster-randomized community trial in which participants were assigned to one of three conditions: a condition in which no lentils were supplied (NL, n = 118, but which had the usual intake of lentils), a control (non-fortified) lentil condition (CL, n = 124), and an iron-fortified lentil condition (FL, n = 117). In the FL and CL conditions, approximately 200 g of cooked lentils were served five days per week for a total of 85 feeding days. In addition to biomarkers of iron status, five cognitive tasks were measured at baseline (BL) and endline (EL): simple reaction time task (SRT), go/no-go task (GNG), attentional network task (ANT), the Sternberg memory search Task (SMS), and a cued recognition task (CRT). Results: Cognitive performance at EL was significantly better for those in the FL relative to the CL and NL conditions, with this being true for at least one variable in each task, except for the GNG. In addition, there were consistent improvements in cognitive performance for those participants whose iron status improved. Although there were overall declines in iron status from BL to EL, the declines were smallest for those in the FL condition, and iron status was significantly better for those in FL condition at EL, relative to those in the CL and NL conditions. Conclusions: the provision of iron-fortified lentils provided a protective effect on iron status in the context of declines in iron status and supported higher levels of cognitive performance for adolescent girls at-risk of developing iron deficiency.
Impact of Sclerotinia sclerotiorum Infection on Lettuce (Lactuca sativa L.) Survival and Phenolics Content—A Case Study in a Horticulture Farm in Poland
Authors: Macioszek Violetta Katarzyna , Marciniak Paulina , Kononowicz Andrzej Kiejstut
Published: December 2023

Sclerotinia sclerotiorum is a cause of a prevalent and destructive disease that attacks many horticultural food crops, such as lettuce. This soil-borne necrotrophic fungal pathogen causes significant economic losses in worldwide lettuce production annually. Furthermore, current methods utilized for management and combatting the disease, such as biocontrol, are insufficient. In this study, three cultivars of lettuce (one Crispy and two Leafy cultivars of red and green lettuce) were grown in central Poland (Lodz Voivodeship), a widely known Polish horticultural region. In the summer and early autumn, lettuce cultivars were grown in control and S. sclerotiorum-infected fields. The lettuce cultivars (Templin, Lollo Rossa, and Lollo Bionda) differed phenotypically and in terms of the survival of the fungal infection. The Crispy iceberg Templin was the most susceptible to S. sclerotiorum infection compared to the other cultivars during both vegetation seasons. The total content of phenolic compounds, flavonoids, and anthocyanins varied among cultivars and fluctuated during infection. Moreover, phenolic content was affected by vegetation season with alterable environmental factors such as air temperature, humidity, soil temperature, and pH. The most increased levels of phenolics, both flavonoids and anthocyanins in infected plants, were observed in the Leafy red Lollo Rossa cultivar in both crops. However, the highest survival/resistance to the fungus was noticed for Lollo Rossa in the summer crop and Lollo Bionda in the autumn crop.
Computational and Experimental Drug Repurposing of FDA-Approved Compounds Targeting the Cannabinoid Receptor CB1
Authors: Criscuolo Emanuele , De Sciscio Maria Laura , De Cristofaro Angela , Nicoara Catalin , Maccarrone Mauro , Fezza Filomena
Published: December 2023

The cannabinoid receptor 1 (CB1R) plays a pivotal role in regulating various physiopathological processes, thus positioning itself as a promising and sought-after therapeutic target. However, the search for specific and effective CB1R ligands has been challenging, prompting the exploration of drug repurposing (DR) strategies. In this study, we present an innovative DR approach that combines computational screening and experimental validation to identify potential Food and Drug Administration (FDA)-approved compounds that can interact with the CB1R. Initially, a large-scale virtual screening was conducted using molecular docking simulations, where a library of FDA-approved drugs was screened against the CB1R’s three-dimensional structures. This in silico analysis allowed us to prioritize compounds based on their binding affinity through two different filters. Subsequently, the shortlisted compounds were subjected to in vitro assays using cellular and biochemical models to validate their interaction with the CB1R and determine their functional impact. Our results reveal FDA-approved compounds that exhibit promising interactions with the CB1R. These findings open up exciting opportunities for DR in various disorders where CB1R signaling is implicated. In conclusion, our integrated computational and experimental approach demonstrates the feasibility of DR for discovering CB1R modulators from existing FDA-approved compounds. By leveraging the wealth of existing pharmacological data, this strategy accelerates the identification of potential therapeutics while reducing development costs and timelines. The findings from this study hold the potential to advance novel treatments for a range of CB1R -associated diseases, presenting a significant step forward in drug discovery research.
Span 60/Cholesterol Niosomal Formulation as a Suitable Vehicle for Gallic Acid Delivery with Potent In Vitro Antibacterial, Antimelanoma, and Anti-Tyrosinase Activity
Authors: Zolghadri Sara , Asad Ali Ghanbari , Farzi Fatemeh , Ghajarzadeh Fatemeh , Habibi Zeinab , Rahban Mahdie , Zolghadri Samaneh , Stanek Agata
Published: December 2023

Natural compounds such as gallic acid (GA) have attracted more attention in cosmetic and pharmaceutical skin care products. However, the low solubility and poor stability of GA have limited its application. This study aimed to synthesize and characterize the GA niosomal dispersion (GAN) and investigate the potential of an optimal formulation as a skin drug delivery system for GA. For this purpose, GAN formulations were synthesized using the thin layer evaporation method with different molar ratios of Tween 60/Span 60, along with a constant molar ratio of polyethylene glycol 4000 (PEG-4000) and cholesterol in a methanol and chloroform solvent (1:4 v/v). The physicochemical properties of nanosystems in terms of size, zeta potential, drug entrapment, drug release, morphology, and system–drug interaction were characterized using different methods. In addition, in vitro cytotoxicity, anti-tyrosinase activity, and antibacterial activity were evaluated by MTT assay, the spectrophotometric method, and micro-well dilution assay. All formulations revealed a size of 80–276 nm, polydispersity index (PDI) values below 0.35, and zeta potential values below—9.7 mV. F2 was selected as the optimal formulation due to its smaller size and high stability. The optimal formulation of GAN (F2) was as follows: a 1:1 molar ratio of Span 60 to cholesterol and 1.5 mM GA. The release of the F2 drug showed a biphasic pattern, which was fast in the first 12 h until 58% was released. Our results showed the high antibacterial activity of GAN against Escherichia coli and Pseudomonas aeruginosa. The MTT assay showed that GA encapsulation increased its effect on B6F10 cancer cells. The F2 formulation exhibited potent anti-tyrosinase activity and inhibited melanin synthesis. These findings suggest that it can be used in dermatological skin care products in the cosmetic and pharmaceutical industries due to its significant antibacterial, anti-melanoma, and anti-tyrosinase activity.
Natural Chalcones and Derivatives in Colon Cancer: Pre-Clinical Challenges and the Promise of Chalcone-Based Nanoparticles
Authors: Hba Soufyane , Ghaddar Suzan , Wahnou Hicham , Pinon Aline , El Kebbaj Riad , Pouget Christelle , Sol Vincent , Liagre Bertrand , Oudghiri Mounia , Limami Youness
Published: December 2023

Colon cancer poses a complex and substantial global health challenge, necessitating innovative therapeutic approaches. Chalcones, a versatile class of compounds with diverse pharmacological properties, have emerged as promising candidates for addressing colon cancer. Their ability to modulate pivotal signaling pathways in the development and progression of colon cancer makes them invaluable as targeted therapeutics. Nevertheless, it is crucial to recognize that although chalcones exhibit promise, further pre-clinical studies are required to validate their efficacy and safety. The journey toward effective colon cancer treatment is multifaceted, involving considerations such as optimizing the sequencing of therapeutic agents, comprehending the resistance mechanisms, and exploring combination therapies incorporating chalcones. Furthermore, the integration of nanoparticle-based drug delivery systems presents a novel avenue for enhancing the effectiveness of chalcones in colon cancer treatment. This review delves into the mechanisms of action of natural chalcones and some derivatives. It highlights the challenges associated with their use in pre-clinical studies, while also underscoring the advantages of employing chalcone-based nanoparticles for the treatment of colon cancer.
The Specific Copper(II) Chelator TDMQ20 Is Efficient for the Treatment of Wilson’s Disease in Mice
Authors: Zhu Yingshan , Tang Ying , Huang Lan , Nguyen Michel , Liu Yan , Robert Anne , Meunier Bernard
Published: December 2023

(1) Background: In patients with Wilson’s disease, the deficiency of the copper carrier ATP7B causes the accumulation of copper in the liver, brain and various other organs. Lifelong treatment is therefore mandatory, using copper chelators to increase the excretion of copper and to avoid life-threatening damage. The clinically used reference drug, D-penicillamine, exhibit numerous adverse effects, especially a frequent severe and irreversible neurological worsening, mainly due to its lack of metal selectivity; (2) Methods: A new tetradentate ligand based on an 8-aminoquinoline entity, named TDMQ20, which is highly selective for copper compared with other metal ions, is evaluated in “toxic milk” TX mice as an oral treatment of this Wilson’s disease murine model; (3) Results: The concentration of copper in the liver of “toxic milk” TX mice decreased and the fecal excretion of copper increased upon oral treatment with TDMQ20. Both effects are dose-dependent, and more pronounced than those of D-penicillamine; (4) Conclusions: The TDMQ20 copper chelator is more efficient than the reference drug D-penicillamine for the treatment of a Wilson’s disease murine model. Pharmacological data obtained with TDMQ20 on the TX mouse model strongly support the selection of this ligand as a drug candidate for this genetic disease.
Improved Therapeutic Efficacy of MT102, a New Anti-Inflammatory Agent, via a Self-Microemulsifying Drug Delivery System, in Ulcerative Colitis Mice
Authors: Baral Kshitis Chandra , Lee Sang Hoon , Song Jae Geun , Jeong Seong Hoon , Han Hyo-Kyung
Published: December 2023

MT-102 is a new anti-inflammatory agent derived from Juglans mandshurica and Isatis indigotica. Its therapeutic potential is hindered by low aqueous solubility, impacting its in vivo efficacy. Therefore, this study aimed to develop a self-microemulsifying drug delivery system (SMEDDS) for MT-102 to enhance its oral efficacy in treating ulcerative colitis. Solubility assessment in different oils, surfactants, and cosurfactants led to a SMEDDS formulation of MT-102 using Capmul MCM, Tween 80, and propylene glycol. Based on a pseudoternary phase diagram, the optimal SMEDDS composition was selected, which consisted of 15% Capmul MCM, 42.5% Tween 80, and 42.5% propylene glycol. The resulting optimized SMEDDS (SMEDDS-F1) exhibited a narrow size distribution (177.5 ± 2.80 nm) and high indirubin content (275 ± 5.58 µg/g, a biomarker). Across an acidic to neutral pH range, SMEDDS-F1 showed rapid and extensive indirubin release, with dissolution rates approximately 15-fold higher than pure MT-102. Furthermore, oral administration of SMEDDS-F1 effectively mitigated inflammatory progression and symptoms in a mouse model of ulcerative colitis, whereas pure MT-102 was ineffective. SMEDDS-F1 minimized body weight loss (less than 5%) without any significant change in colon length and the morphology of colonic tissues, compared to those of the healthy control group. In addition, oral administration of SMEDDS-F1 significantly inhibited the secretion of pro-inflammatory cytokines such as IL-6 and TNF-α. In conclusion, the SMEDDS-F1 formulation employing Capmul MCM, Tween 80, and propylene glycol (15:42.5:42.5, w/w) enhances the solubility and therapeutic efficacy of MT-102.
30-Year Development of Inactivated Virus Vaccine in China
Authors: Shi Jinrong , Shen Ailin , Cheng Yao , Zhang Chi , Yang Xiaoming
Published: December 2023

Inactivated vaccines are vaccines made from inactivated pathogens, typically achieved by using chemical or physical methods to destroy the virus’s ability to replicate. This type of vaccine can induce the immune system to produce an immune response against specific pathogens, thus protecting the body from infection. In China, the manufacturing of inactivated vaccines has a long history and holds significant importance among all the vaccines available in the country. This type of vaccine is widely used in the prevention and control of infectious diseases. China is dedicated to conducting research on new inactivated vaccines, actively promoting the large-scale production of inactivated vaccines, and continuously improving production technology and quality management. These efforts enable China to meet the domestic demand for inactivated vaccines and gain a certain competitive advantage in the international market. In the future, China will continue to devote itself to the research and production of inactivated vaccines, further enhancing the population’s health levels and contributing to social development. This study presents a comprehensive overview of the 30-year evolution of inactivated virus vaccines in China, serving as a reference for the development and production of such vaccines.
Theoretical—Experimental Approach of Chitosan/Quaternized Chitosan Nanofibers’ Behavior in Wound Exudate Media
Authors: Andreica Bianca-Iustina , Anisiei Alexandru , Iftime Manuela-Maria , Ababei Razvan-Vasile , Ochiuz Lacramioara , Vasincu Decebal , Vasilache Ingrid-Andrada , Volovat Constantin , Boboc Diana , Poroch Vladimir , Eva Lucian , Agop Maricel , Scripcariu Dragos-Viorel , Volovat Simona Ruxandra
Published: December 2023

This study aimed to investigate the behavior of chitosan/quaternized chitosan fibers in media mimicking wound exudates to understand their capacities as wound dressing. Fiber analysis of the fibers using dynamic vapor sorption proved their ability to adsorb moisture up to 60% and then to desorb it as a function of humidity, indicating their outstanding breathability. Dissolution analyses showed that quaternized chitosan leached from the fibers in water and PBS, whereas only small portions of chitosan were solubilized in water. In media containing lysozyme, the fibers degraded with a rate determined by their composition and pH, reaching a mass loss of up to 47% in media of physiologic pH. Notably, in media mimicking the wound exudate during healing, they adsorbed moisture even when their mass loss due to biodegradation was high, whereas they were completely degraded in the media of normal tissues, indicating bioabsorbable dressing capacities. A mathematical model was constructed, which characterized the degradation rate and morphology changes of chitosan/quaternized chitosan fibers through analyses of dynamics in scale space, using the Theory of Scale Relativity. The model was validated using experimental data, making it possible to generalize it to the degradation of other biopolymeric systems that address wound healing.
Genetic Diversity and Genome-Wide Association Study for the Phenology Response of Winter Wheats of North America, Western Asia, and Europe
Authors: El Baouchi Adil , Ibriz Mohammed , Dreisigacker Susanne , Lopes Marta S. , Garcia Miguel Sanchez
Published: December 2023

Wheat is a staple food in many areas around the World. In the 20th century, breeders and scientists were able to boost wheat yield considerably. However, a yield plateau has become a concern and is threatening food security. Investments in cutting-edge technologies, including genomics and precision phenology measurements, can provide valuable tools to drive crop improvement. The objectives of this study were to (i) investigate the genetic diversity in a set of winter wheat lines, (ii) characterize their phenological response under different vernalization and photoperiod conditions, and (iii) identify effective markers associated with the phenological traits. A total of 249 adapted genotypes of different geographical origin were genotyped using the 35K Axiom® Wheat Breeder’s Array. A total of 11,476 SNPs were used for genetic analysis. The set showed an average polymorphism information content of 0.37 and a genetic diversity of 0.43. A population structure analysis revealed three distinct subpopulations mainly related to their geographical origin (Europe, North America, and Western Asia). The lines of CGIAR origin showed the largest diversity and the lowest genetic distance to all other subpopulations. The phenology of the set was studied under controlled conditions using four combinations of long (19 h light) and short photoperiod (13 h light) and long vernalization (49 days at 5 °C) and no vernalization. With this, phenological traits such as earliness per se (Eps), relative response to vernalization (RRV), and relative response to photoperiod (RRP) were calculated. The phenotypic variation of growing degree days was significant in all phenology combinations. RRV ranged from 0 to 0.56, while RRP was higher with an overall average of 0.25. The GWAS analysis detected 30 marker-trait associations linked to five phenological traits. The highest significant marker was detected on chromosome 2D with a value of −log10(p) = 11.69. Only four loci known to regulate flowering exceeded the Bonferroni correction threshold of −log10(p) > 5.1. These results outline a solid foundation to address global food security and offer tremendous opportunities for advancing crop improvement strategies.
Structure, Thermal, and Mechanical Behavior of the Polysulfone Solution Impregnated Unidirectional Carbon Fiber Yarns
Authors: Chukov Dilyus I. , Tcherdyntsev Victor V. , Stepashkin Andrey A. , Zadorozhnyy Mikhail Y.
Published: December 2023

The paper is devoted to the study of thermal and mechanical behavior and structural features of the polysulfone solution impregnated unidirectional carbon fiber yarns depending on fabrication conditions and appearance for optimum production method of the composites. The effect of producing conditions, such as polysulfone solution concentration, drying and post-heating temperatures, and the residual solvent content on the structure, mechanical, and thermal properties of the carbon fiber-reinforced composites was studied. The polysulfone solution impregnated carbon fiber yarns show relatively high mechanical properties, realizing up to 80% of the carbon fibers’ tensile strength, which can be attributed to good wettability and uniform polymer matrix distribution throughout the entire volume of the composites. It was found that the composites impregnated with 40 wt.% of the polysulfone solution showed lower porosity and higher mechanical properties. The results of a dynamic mechanical analysis indicate that residual solvent has a significant effect on the composites’ thermal behavior. The composites heated to 350 °C for a 30 min showed higher thermal stability compared to ones dried at 110 °C due to removal of residual solvent during heating. The impregnated carbon fiber yarns can be used for the further producing bulk unidirectional composites by compression molding and the proposed method can be easily transformed to continuous filament production, for example for further use in 3-D printing technology.
Effect of Powder Bed Fusion Laser Sintering on Dimensional Accuracy and Tensile Properties of Reused Polyamide 11
Authors: Gunputh Urvashi F. , Williams Gavin , Pawlik Marzena , Lu Yiling , Wood Paul
Published: December 2023

Polyamide 11 (PA11) is a plant-based nylon made from castor beans. Powder bed fusion laser sintering (PBF-LS) is an additive manufacturing process used for PA11 which allows for the reuse of the unsintered powder. The unsintered powder is mixed with virgin powders at different refresh rates, a process which has been studied extensively for most semi-crystalline polyamides. However, there is lack of information on the effect of using 100% reused PA11 powder and the effect of the number of times it is reused on its own, during powder bed fusion laser sintering. This paper investigates the effect of reusing PA11 powder in PBF-LS and the effect of the number of times it is reused on the dimensional accuracy, density and thermal and tensile properties. From the 100% virgin powder to the third reuse of the powder, there is a decrease in powder wastage, crystallinity and tensile strength. These are associated with the polymerisation and cross-linking process of polymer chains, upon exposure to high temperatures. This results in a higher molecular weight and, hence, a higher density. From the fourth reuse to the tenth reuse, the opposite is observed, which is associated with an increase in high-viscosity unmolten particles, resulting in defects in the PBF-LS parts.
Rheological Properties and Kinetics of Gelation of Binary Polymers between Xanthan Gum and Locust Bean Gum
Authors: Zhang Hui , Yan Zhun , Xie Fan , Tian Yanjun , Ai Lianzhong
Published: December 2023

The synergistic interaction and gelling kinetics between xanthan gum (XG) and locust bean gum (LBG) at different mass ratios (XG/LBG 9:1, 7:3, 5:5, 3:7, 1:9) were investigated using a rheometer. The results showed that the mixtures of XG and LBG induced gel formation, and the strongest gel structure was found for the mixture of XG/LBG 3:7 according to the yield stress, storage modulus (G′), and power law parameters. Temperature ramp studies indicated that heating destroyed the gels at 55~60 °C, while cooling induced the sol–gel transition at around 52 °C for all mixtures. Structure developing rate (SDR) curves showed that XG/LBG 3:7 exhibited the highest SDR during the cooling ramp among all the samples. Non-isothermal kinetic analysis demonstrated that the gelation process of XG/LBG mixtures during cooling included two steps: a high-temperature region (55~39 °C) needing higher activation energy (Ea, 111.97 to 199.20 kJ/mol for different mixtures) and a low-temperature region (39~20 °C) needing lower Ea (74.33 to 85.31 kJ/mol), which indicated higher energy barriers to overcome at the initial stage of gel formation. The lowest Ea of 74.33 kJ/mol was found for XG/LBG 3:7 in the low-temperature region. Scanning electron microscopy (SEM) showed that the gel of XG/LBG 3:7 presented the densest entanglements. These results indicated the strongest synergism interaction occurred in XG/LBG 3:7 to form gel network structures. This study will help promote the application of XG-LBG blends to design novel food structures.
Preparation and Performance Evaluation of Amphiphilic Polymers for Enhanced Heavy Oil Recovery
Authors: Fei Dongtao , Guo Jixiang , Xiong Ruiying , Zhang Xiaojun , Kang Chuanhong , Kiyingi Wyclif
Published: December 2023

The continuous growth in global energy and chemical raw material demand has drawn significant attention to the development of heavy oil resources. A primary challenge in heavy oil extraction lies in reducing crude oil viscosity. Alkali–surfactant–polymer (ASP) flooding technology has emerged as an effective method for enhancing heavy oil recovery. However, the chromatographic separation of chemical agents presents a formidable obstacle in heavy oil extraction. To address this challenge, we utilized a free radical polymerization method, employing acrylamide, 2-acrylamido-2-methylpropane sulfonic acid, lauryl acrylate, and benzyl acrylate as raw materials. This approach led to the synthesis of a multifunctional amphiphilic polymer known as PAALB, which we applied to the extraction of heavy oil. The structure of PAALB was meticulously characterized using techniques such as infrared spectroscopy and Nuclear Magnetic Resonance Spectroscopy. To assess the effectiveness of PAALB in reducing heavy oil viscosity and enhancing oil recovery, we conducted a series of tests, including contact angle measurements, interfacial tension assessments, self-emulsification experiments, critical association concentration tests, and sand-packed tube flooding experiments. The research findings indicate that PAALB can reduce oil–water displacement, reduce heavy oil viscosity, and improve swept volume upon injection into the formation. A solution of 5000 mg/L PAALB reduced the contact angle of water droplets on the core surface from 106.55° to 34.95°, shifting the core surface from oil-wet to water-wet, thereby enabling oil–water displacement. Moreover, A solution of 10,000 mg/L PAALB reduced the oil–water interfacial tension to 3.32 × 10−4 mN/m, reaching an ultra-low interfacial tension level, thereby inducing spontaneous emulsification of heavy oil within the formation. Under the condition of an oil–water ratio of 7:3, a solution of 10,000 mg/L PAALB can reduce the viscosity of heavy oil from 14,315 mPa·s to 201 mPa·s via the glass bottle inversion method, with a viscosity reduction rate of 98.60%. In sand-packed tube flooding experiments, under the injection volume of 1.5 PV, PAALB increased the recovery rate by 25.63% compared to traditional hydrolyzed polyacrylamide (HPAM) polymer. The insights derived from this research on amphiphilic polymers hold significant reference value for the development and optimization of chemical flooding strategies aimed at enhancing heavy oil recovery.
Hierarchical Porous Carbon Aerogel Derived from Sodium Alginate for High Performance Electrochemical Capacitor Electrode
Authors: Li Xuequan , Lai Liting , Wu Fangdi , Xie Wenju , Liu Junshao
Published: December 2023

To improve the performance of electrochemical capacitors, there is a notable focus on carbon materials characterized by a large surface area, reasonable pore size, pore size distribution, appropriate electronic conductivity, and excellent chemical durability. Herein, the hierarchical porous carbon aerogel originating from sodium alginate (SA) with well-defined porosity are proposed. The resultant hierarchical porous carbon aerogel shows a substantial specific surface area of 2050.6 m2 g−1 with macropores, mesopores and micropores confirmed by techniques such as TEM, SEM, BET, etc., resulting from a sequence of aerogel formation-carbonization-activation. By electrochemical measurement, the hierarchical porous carbon aerogel exhibits a specific capacitance of 204 F g−1 at an operating current density of 0.2 A g−1 employing 6 M KOH aqueous solution. The hierarchical carbon aerogel displays outstanding cycling stability with a 96.2% capacity maintenance for 10,000 cycles at an operating current density of 1 A g−1. This study presents a viable method for for preparing hierarchical porous carbon aerogel derived from biopolymer for electrochemical capacitors.
Satellite-Based Localization of IoT Devices Using Joint Doppler and Angle-of-Arrival Estimation
Authors: Mohamad Hashim Iza , Al-Hourani Akram
Published: December 2023

While global navigation satellite system (GNSS) technologies have always been the go-to solution for localization problems, they may not be the best choice for some Internet-of-Things (IoT) applications due to the incurred power consumption and cost. In this paper, we present an alternative satellite-based localization method exploiting the signature of Doppler shifts and angle-of-arrival measurements as seen by a low-Earth-orbit (LEO) satellite. We first derive the joint likelihood function of the measurements, which is represented as a combination of three Gaussian distributions. Then, we show that the maximum likelihood problem reduces to a more-efficient mean squared error minimization in the Gaussian case as inferred from real measurements we collected from low-Earth-orbit satellite using a tracking ground station. Thus, we propose utilizing a stochastic optimizer to search for the global minimum of the mean squared error, which represents the location of the ground IoT device as estimated by the satellite platform. The emulated results show that the IoT device localization, in such a realistic model, can be performed with sufficient accuracy for IoT applications.
Planetary Radar—State-of-the-Art Review
Authors: Virkki Anne , Neish Catherine , Rivera-Valentín Edgard , Bhiravarasu Sriram , Hickson Dylan , Nolan Michael , Orosei Roberto
Published: December 2023

Planetary radar observations have provided invaluable information on the solar system through both ground-based and space-based observations. In this overview article, we summarize how radar observations have contributed in planetary science, how the radar technology as a remote-sensing method for planetary exploration and the methods to interpret the radar data have advanced in the eight decades of increasing use, where the field stands in the early 2020s, and what are the future prospects of the ground-based facilities conducting planetary radar observations and the planned spacecraft missions equipped with radar instruments. The focus of the paper is on radar as a remote-sensing technique using radar instruments in spacecraft orbiting planetary objects and in Earth-based radio telescopes, whereas ground-penetrating radar systems on landers are mentioned only briefly. The key scientific developments are focused on the search for water ice in the subsurface of the Moon, which could be an invaluable in situ resource for crewed missions, dynamical and physical characterization of near-Earth asteroids, which is also crucial for effective planetary defense, and a better understanding of planetary geology.
A Multi-Source-Data-Assisted AUV for Path Cruising: An Energy-Efficient DDPG Approach
Authors: Xing Tianyu , Wang Xiaohao , Ding Kaiyang , Ni Kai , Zhou Qian
Published: December 2023

As marine activities expand, deploying underwater autonomous vehicles (AUVs) becomes critical. Efficiently navigating these AUVs through intricate underwater terrains is vital. This paper proposes a sophisticated motion-planning algorithm integrating deep reinforcement learning (DRL) with an improved artificial potential field (IAPF). The algorithm incorporates remote sensing information to overcome traditional APF challenges and combines the IAPF with the traveling salesman problem for optimal path cruising. Through a combination of DRL and multi-source data optimization, the approach ensures minimal energy consumption across all target points. Inertial sensors further refine trajectory, ensuring smooth navigation and precise positioning. The comparative experiments confirm the method’s energy efficiency, trajectory refinement, and safety excellence.
A Review on the Effects of Thermal Inversions and Electromagnetic Fields on Cell Cultures and Wireless Communications
Authors: López-Álvarez Cibrán , López-Martín María Elena , Rodríguez-González Juan Antonio , Ares-Pena Francisco José
Published: December 2023

Thermal inversions, typical in the winter season, consist of cold air at the Earth’s surface being trapped under a layer of warmer air. Such an effect keeps normal convective overturning of the atmosphere from penetrating through. This phenomenon highly increases the toxicity of the atmosphere, while modifying its dielectric constant, resulting in major implications in terms of public health and wireless communications. Indeed, air pollution in large cities (related, in most cases, to particulate matter that consists of different chemical components, which can have warming or cooling effects) is primarily caused by chemical and photochemical reactions in the atmosphere. Appropriate usage of array antennas allows the effective tracking of changes in humidity (e.g., coated Yagi-Uda antennas, which do not interfere with 5G) and in the dielectric constant (e.g., optimized quasi-Yagi-Uda antennas, yielding to accurate measurements of sulfides and black carbon concentration). Remarkably, important health effects come from the combined action of electromagnetic fields with fine and coarse black carbon particles. The appearance of ducts, which are caused by thermal inversions, provokes the creation of super-refractive regions in the troposphere as well, which result in the anomalous propagation of wireless communications.
A Multi-Angle Appearance-Based Approach for Vehicle Type and Brand Recognition Utilizing Faster Regional Convolution Neural Networks
Authors: Zhang Hongying , Li Xusheng , Yuan Huazhi , Liang Huagang , Wang Yaru , Song Siyan
Published: December 2023

Vehicle type and brand information constitute a crucial element in intelligent transportation systems (ITSs). While numerous appearance-based classification methods have studied frontal view images of vehicles, the challenge of multi-pose and multi-angle vehicle distribution has largely been overlooked. This paper proposes an appearance-based classification approach for multi-angle vehicle information recognition, addressing the aforementioned issues. By utilizing faster regional convolution neural networks, this method automatically captures crucial features for vehicle type and brand identification, departing from traditional handcrafted feature extraction techniques. To extract rich and discriminative vehicle information, ZFNet and VGG16 are employed. Vehicle feature maps are then imported into the region proposal network and classification location refinement network, with the former generating candidate regions potentially containing vehicle targets on the feature map. Subsequently, the latter network refines vehicle locations and classifies vehicle types. Additionally, a comprehensive vehicle dataset, Car5_48, is constructed to evaluate the performance of the proposed method, encompassing multi-angle images across five vehicle types and 48 vehicle brands. The experimental results on this public dataset demonstrate the effectiveness of the proposed approach in accurately classifying vehicle types and brands.
Robust Epileptic Seizure Detection Using Long Short-Term Memory and Feature Fusion of Compressed Time–Frequency EEG Images
Authors: Khan Shafi Ullah , Jan Sana Ullah , Koo Insoo
Published: December 2023

Epilepsy is a prevalent neurological disorder with considerable risks, including physical impairment and irreversible brain damage from seizures. Given these challenges, the urgency for prompt and accurate seizure detection cannot be overstated. Traditionally, experts have relied on manual EEG signal analyses for seizure detection, which is labor-intensive and prone to human error. Recognizing this limitation, the rise in deep learning methods has been heralded as a promising avenue, offering more refined diagnostic precision. On the other hand, the prevailing challenge in many models is their constrained emphasis on specific domains, potentially diminishing their robustness and precision in complex real-world environments. This paper presents a novel model that seamlessly integrates the salient features from the time–frequency domain along with pivotal statistical attributes derived from EEG signals. This fusion process involves the integration of essential statistics, including the mean, median, and variance, combined with the rich data from compressed time–frequency (CWT) images processed using autoencoders. This multidimensional feature set provides a robust foundation for subsequent analytic steps. A long short-term memory (LSTM) network, meticulously optimized for the renowned Bonn Epilepsy dataset, was used to enhance the capability of the proposed model. Preliminary evaluations underscore the prowess of the proposed model: a remarkable 100% accuracy in most of the binary classifications, exceeding 95% accuracy in three-class and four-class challenges, and a commendable rate, exceeding 93.5% for the five-class classification.
Visual Attention and Emotion Analysis Based on Qualitative Assessment and Eyetracking Metrics—The Perception of a Video Game Trailer
Authors: Villegas Eva , Fonts Elisabet , Fernández Marta , Fernández-Guinea Sara
Published: December 2023

Video game trailers are very useful tools for attracting potential players. This research focuses on analyzing the emotions that arise while viewing video game trailers and the link between these emotions and storytelling and visual attention. The methodology consisted of a three-step task test with potential users: the first step was to identify the perception of indie games; the second step was to use the eyetracking device (gaze plot, heat map, and fixation points) and link them to fixation points (attention), viewing patterns, and non-visible areas; the third step was to interview users to understand impressions and questionnaires of emotions related to the trailer’s storytelling and expectations. The results show an effective assessment of visual attention together with visualization patterns, non-visible areas that may affect game expectations, fixation points linked to very specific emotions, and perceived narratives based on the gaze plot. The innovation in the mixed methodological approach has made it possible to obtain relevant data regarding the link between the emotions perceived by the user and the areas of attention collected with the device. The proposed methodology enables developers to understand the strengths and weaknesses of the information being conveyed so that they can tailor the trailer to the expectations of potential players.
Evaluation of InSAR Tropospheric Delay Correction Methods in the Plateau Monsoon Climate Region Considering Spatial–Temporal Variability
Authors: Yang Qihang , Zuo Xiaoqing , Guo Shipeng , Zhao Yanxi
Published: December 2023

The tropospheric delay caused by the temporal and spatial variation of meteorological parameters is the main error source in interferometric synthetic aperture radar (InSAR) applications for geodesy. To minimize the impact of tropospheric delay errors, it is necessary to select the appropriate tropospheric delay correction method for different regions. In this study, the interferogram results of the InSAR, corrected for tropospheric delay using the Linear, Generic Atmospheric Correction Online Service for InSAR (GACOS) and ERA-5 atmospheric reanalysis dataset (ERA5) methods, are presented for the study area of the junction of the Hengduan Mountains and the Yunnan–Kweichow Plateau, which is significantly influenced by the plateau monsoon climate. Four representative regions, Eryuan, Binchuan, Dali, and Yangbi, are selected for the study and analysis. The phase standard deviation (STD), phase–height correlation, and global navigation satellite system (GNSS) data were used to evaluate the effect of tropospheric delay correction by integrating topographic, seasonal, and meteorological factors. The results show that all three methods can attenuate the tropospheric delay, but the correction effect varies with spatial and temporal characteristics.
RepECN: Making ConvNets Better Again for Efficient Image Super-Resolution
Authors: Chen Qiangpu , Qin Jinghui , Wen Wushao
Published: December 2023

Traditional Convolutional Neural Network (ConvNet, CNN)-based image super-resolution (SR) methods have lower computation costs, making them more friendly for real-world scenarios. However, they suffer from lower performance. On the contrary, Vision Transformer (ViT)-based SR methods have achieved impressive performance recently, but these methods often suffer from high computation costs and model storage overhead, making them hard to meet the requirements in practical application scenarios. In practical scenarios, an SR model should reconstruct an image with high quality and fast inference. To handle this issue, we propose a novel CNN-based Efficient Residual ConvNet enhanced with structural Re-parameterization (RepECN) for a better trade-off between performance and efficiency. A stage-to-block hierarchical architecture design paradigm inspired by ViT is utilized to keep the state-of-the-art performance, while the efficiency is ensured by abandoning the time-consuming Multi-Head Self-Attention (MHSA) and by re-designing the block-level modules based on CNN. Specifically, RepECN consists of three structural modules: a shallow feature extraction module, a deep feature extraction, and an image reconstruction module. The deep feature extraction module comprises multiple ConvNet Stages (CNS), each containing 6 Re-Parameterization ConvNet Blocks (RepCNB), a head layer, and a residual connection. The RepCNB utilizes larger kernel convolutions rather than MHSA to enhance the capability of learning long-range dependence. In the image reconstruction module, an upsampling module consisting of nearest-neighbor interpolation and pixel attention is deployed to reduce parameters and maintain reconstruction performance, while bicubic interpolation on another branch allows the backbone network to focus on learning high-frequency information. The extensive experimental results on multiple public benchmarks show that our RepECN can achieve 2.5∼5× faster inference than the state-of-the-art ViT-based SR model with better or competitive super-resolving performance, indicating that our RepECN can reconstruct high-quality images with fast inference.
Lower Limb Joint Torque Prediction Using Long Short-Term Memory Network and Gaussian Process Regression
Authors: Wang Mengsi , Chen Zhenlei , Zhan Haoran , Zhang Jiyu , Wu Xinglong , Jiang Dan , Guo Qing
Published: December 2023

The accurate prediction of joint torque is required in various applications. Some traditional methods, such as the inverse dynamics model and the electromyography (EMG)-driven neuromusculoskeletal (NMS) model, depend on ground reaction force (GRF) measurements and involve complex optimization solution processes, respectively. Recently, machine learning methods have been popularly used to predict joint torque with surface electromyography (sEMG) signals and kinematic information as inputs. This study aims to predict lower limb joint torque in the sagittal plane during walking, using a long short-term memory (LSTM) model and Gaussian process regression (GPR) model, respectively, with seven characteristics extracted from the sEMG signals of five muscles and three joint angles as inputs. The majority of the normalized root mean squared error (NRMSE) values in both models are below 15%, most Pearson correlation coefficient (R) values exceed 0.85, and most decisive factor (R2) values surpass 0.75. These results indicate that the joint prediction of torque is feasible using machine learning methods with sEMG signals and joint angles as inputs.
Ethanol-Gas-Sensing Performances of Built-in ZrO2/Co3O4 Hybrid Nanostructures
Authors: Khan Madiha , Ferlazzo Angelo , Hussain Mozaffar , Fazio Enza , Corsaro Carmelo , Mezzasalma Angela Maria , Neri Giovanni
Published: December 2023

The development of novel nanomaterials as highly efficient gas-sensing materials is envisaged as one of the most important routes in the field of gas-sensing research. However, developing stable, selective, and efficient materials for these purposes is a highly challenging task requiring numerous design attempts. In this work, a ZrO2/Co3O4 composite is reported, for the first time, as a gas-sensing material for the detection of ethanol. The sensitive and selective detection of ethanol gas at 200 °C has been demonstrated for the ZrO2/Co3O4 (0.20 wt%/0.20 wt%)-based sensor. Furthermore, the sensor showed a very low response/recovery time of 56 s and 363 s, respectively, in response to a pulse of 20 ppm of ethanol and good stability. The interesting gas-sensing property of ZrO2/Co3O4 can be ascribed to both the porous structure, which facilitates the interaction between the target gas and the sensing site, and the p–p-junction-induced built-in electric field. These results indicate that the ZrO2/Co3O4 composite can serve as a heterostructured nanomaterial for the detection of ethanol gas.