bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation on Novel E/Z 2-Benzylideneindan-1-One-Based Photoswitches with AChE and MAO-B Dual Inhibitory Activity
Authors: Paolino Marco , de Candia Modesto , Purgatorio Rosa , Catto Marco , Saletti Mario , Tondo Anna Rita , Nicolotti Orazio , Cappelli Andrea , Brizzi Antonella , Mugnaini Claudia , Corelli Federico , Altomare Cosimo D.
Published: August 2023

The multitarget therapeutic strategy, as opposed to the more traditional ‘one disease-one target-one drug’, may hold promise in treating multifactorial neurodegenerative syndromes, such as Alzheimer’s disease (AD) and related dementias. Recently, combining a photopharmacology approach with the multitarget-directed ligand (MTDL) design strategy, we disclosed a novel donepezil-like compound, namely 2-(4-((diethylamino)methyl)benzylidene)-5-methoxy-2,3-dihydro-1H-inden-1-one (1a), which in the E isomeric form (and about tenfold less in the UV-B photo-induced isomer Z) showed the best activity as dual inhibitor of the AD-related targets acetylcholinesterase (AChE) and monoamine oxidase B (MAO-B). Herein, we investigated further photoisomerizable 2-benzylideneindan-1-one analogs 1b–h with the unconjugated tertiary amino moiety bearing alkyls of different bulkiness and lipophilicity. For each compound, the thermal stable E geometric isomer, along with the E/Z mixture as produced by UV-B light irradiation in the photostationary state (PSS, 75% Z), was investigated for the inhibition of human ChEs and MAOs. The pure E-isomer of the N-benzyl(ethyl)amino analog 1h achieved low nanomolar AChE and high nanomolar MAO-B inhibition potencies (IC50s 39 and 355 nM, respectively), whereas photoisomerization to the Z isomer (75% Z in the PSS mixture) resulted in a decrease (about 30%) of AChE inhibitory potency, and not in the MAO-B one. Molecular docking studies were performed to rationalize the different E/Z selectivity of 1h toward the two target enzymes.
Insight into Structure Activity Relationship of DPP-4 Inhibitors for Development of Antidiabetic Agents
Authors: Mathur Vishal , Alam Ozair , Siddiqui Nadeem , Jha Mukund , Manaithiya Ajay , Bawa Sandhya , Sharma Naveen , Alshehri Sultan , Alam Prawez , Shakeel Faiyaz
Published: August 2023

This article sheds light on the various scaffolds that can be used in the designing and development of novel synthetic compounds to create DPP-4 inhibitors for the treatment of type 2 diabetes mellitus (T2DM). This review highlights a variety of scaffolds with high DPP-4 inhibition activity, such as pyrazolopyrimidine, tetrahydro pyridopyrimidine, uracil-based benzoic acid and esters, triazole-based, fluorophenyl-based, glycinamide, glycolamide, β-carbonyl 1,2,4-triazole, and quinazoline motifs. The article further explains that the potential of the compounds can be increased by substituting atoms such as fluorine, chlorine, and bromine. Docking of existing drugs like sitagliptin, saxagliptin, and vildagliptin was done using Maestro 12.5, and the interaction with specific residues was studied to gain a better understanding of the active sites of DPP-4. The structural activities of the various scaffolds against DPP-4 were further illustrated by their inhibitory concentration (IC50) values. Additionally, various synthesis schemes were developed to make several commercially available DPP4 inhibitors such as vildagliptin, sitagliptin and omarigliptin. In conclusion, the use of halogenated scaffolds for the development of DPP-4 inhibitors is likely to be an area of increasing interest in the future.
Synthesis and Biological Evaluation of New Quinoline and Anthranilic Acid Derivatives as Potential Quorum Sensing Inhibitors
Authors: Perković Ivana , Poljak Tanja , Savijoki Kirsi , Varmanen Pekka , Maravić-Vlahoviček Gordana , Beus Maja , Kučević Anja , Džajić Ivan , Rajić Zrinka
Published: August 2023

Inhibiting quorum sensing (QS), a central communication system, is a promising strategy to combat bacterial pathogens without antibiotics. Here, we designed novel hybrid compounds targeting the PQS (Pseudomonas quinolone signal)-dependent quorum sensing (QS) of Pseudomonas aeruginosa that is one of the multidrug-resistant and highly virulent pathogens with urgent need of new antibacterial strategies. We synthesized 12 compounds using standard procedures to combine halogen-substituted anthranilic acids with 4-(2-aminoethyl/4-aminobuthyl)amino-7-chloroquinoline, linked via 1,3,4-oxadiazole. Their antibiofilm activities were first pre-screened using Gram-negative Chromobacterium violaceum-based reporter, which identified compounds 15–19 and 23 with the highest anti-QS and minimal bactericidal effects in a single experiment. These five compounds were then evaluated against P. aeruginosa PAO1 to assess their ability to prevent biofilm formation, eradicate pre-formed biofilms, and inhibit virulence using pyocyanin as a representative marker. Compound 15 displayed the most potent antibiofilm effect, reducing biofilm formation by nearly 50% and pre-formed biofilm masses by 25%. On the other hand, compound 23 exhibited the most significant antivirulence effect, reducing pyocyanin synthesis by over 70%. Thus, our study highlights the potential of 1,3,4-oxadiazoles 15 and 23 as promising scaffolds to combat P. aeruginosa. Additionally, interactive QS systems should be considered to achieve maximal anti-QS activity against this clinically relevant species.
Vitamin D Physiology, Deficiency, Genetic Influence, and the Effects of Daily vs. Bolus Doses of Vitamin D on Overall Health: A Clinical Approach
Authors: Sorrenti Vincenzo , Buriani Alessandro , Davinelli Sergio , Scapagnini Giovanni , Fortinguerra Stefano
Published: August 2023

Vitamin D is a pleiotropic hormone that plays a vital role in regulating bone growth, maintaining calcium and phosphate homeostasis, modulating immune function, and a wide range of other pleiotrophic actions in humans, which have increased the attention for its clinical applications. Despite its importance, vitamin D deficiency is prevalent worldwide and is related to a range of pathophysiological conditions, including an increased risk of osteoporosis and chronic and autoimmune diseases. The recommended daily doses of vitamin D vary depending on genetics, age, sex, and health status, with specific doses recommended for infants, children, adults, and those at increased risk of deficiency or specific health conditions. Maintaining adequate vitamin D levels is essential for optimal health, and together with sun exposure, appropriate supplementation strategies can help achieve this goal. Vitamin D supplementation is commonly used to maintain adequate levels, and the optimal administration strategy, such as a daily dose vs. a bolus, is still being investigated. This review aims to understand vitamin D physiology and the impact of relevant vitamin D polymorphisms and to evaluate the role of a daily dose versus a bolus in maintaining optimal vitamin D levels and clinical health outcomes. It also provides suggested clinical guidelines for clinicians based on the most recent scientific evidence.
Antimicrobial Activity of Diffusible and Volatile Metabolites Emitted by Beauveria bassiana: Chemical Profile of Volatile Organic Compounds (VOCs) Using SPME-GC/MS Analysis
Authors: Camele Ippolito , Sadeek Sadeek A. , Racioppi Rocco , Elshafie Hazem S.
Published: August 2023

The genus Beauveria includes important entomopathogenic and endophytic fungi; among them, Beauveria bassiana is the most studied species. However, there is little knowledge regarding their antimicrobial activity. The current research has been conducted to evaluate the in vitro antagonistic activity of B. bassiana and the antimicrobial efficacy of its Exo and Endo metabolites against Bacillus cereus, B. megaterium, Clavibacter michiganensis (Gram positive bacteria, G+ve), Xanthomonas campestris, Pseudomonas aeruginosa and P. fluorescence (Gram negative bacteria, G−ve). In addition, solid-phase microextraction (SPME) was coupled with Gas Chromatography-Mass Spectrometry (GC/MS) to qualitatively measure the volatile organic compounds’ (VOCs) metabolic profile of the most efficient studied isolate of B. bassiana. The obtained results showed that the isolate UniB2439-3 has a promising antibacterial effect against most of the studied target bacteria. An SPME-GC/MS analysis of VOCs revealed the presence of ethanol, butanal,2-methyl, 2,4-dimethyl-1-heptene, octane, 4-methyl and β-elemene as the dominant bioactive compounds. The results demonstrated that the efficient isolate of B. bassiana can be potentially used as a biocontrol agent against several bacteria, especially G+ve ones.
Plant Elicitor Peptide (Pep) Signaling and Pathogen Defense in Tomato
Authors: Zelman Alice K. , Berkowitz Gerald Alan
Published: August 2023

Endogenous signaling compounds are intermediaries in signaling pathways that plants use to respond to the perception of harmful and beneficial organisms. The plant elicitor peptides (Peps) of plants are important endogenous signaling molecules that induce elements of defense responses such as hormone production, increased expression of defensive genes, the activation of phosphorelays, and the induction of cell secondary messenger synthesis. The processes by which Peps confer resistance to pathogenic microorganisms have been extensively studied in Arabidopsis but are less known in crop plants. Tomato and many other solanaceous plants have an endogenous signaling polypeptide, systemin, that is involved in the defense against herbivorous insects and necrotrophic pathogens. This paper explores the similarity of the effects and chemical properties of Pep and systemin in tomato. Additionally, the relationship of the Pep receptor and systemin receptors is explored, and the identification of a second tomato Pep receptor in the literature is called into question. We suggest future directions for research on Pep signaling in solanaceous crops during interactions with microbes.
Optimizing Grain Yield and Radiation Use Efficiency through Synergistic Applications of Nitrogen and Potassium Fertilizers in Super Hybrid Rice
Authors: Deng Jun , Ye Jiayu , Zhong Xuefen , Yang Qingqing , Harrison Matthew Tom , Wang Chunhu , Huang Liying , Tian Xiaohai , Liu Ke , Zhang Yunbo
Published: August 2023

The remarkable yield performance of super hybrid rice has played a crucial role in ensuring global food security. However, there is a scarcity of studies investigating the contribution of radiation use efficiency (RUE) to hybrid rice yields under different nitrogen and potassium treatments. In this three-year field experiment, we aimed to evaluate the impact of two hybrid rice varieties (Y-liangyou 900: YLY900 and Quanyouhuazhan: QYHZ) under varying nitrogen regimes (N90: 90 kg N ha−1, N120: 120 kg N ha−1, N180: 180 kg N ha−1) and potassium regimes (K120: 120 kg K2O ha−1, K160: 160 kg K2O ha−1, K210: 210 kg K2O ha−1) on grain yield and its physiological determinants, including RUE, intercepted photosynthetically active radiation (IPAR), aboveground biomass production, and harvest index (HI). Our results revealed that both rice varieties exhibited significantly higher yields when coupled with nitrogen and potassium fertilization. Compared to the N90 × K120 treatment, the N120 × K160 and N180 × K210 combinations resulted in substantial increases in grain yield (12.0% and 21.1%, respectively) and RUE (11.9% and 21.4%, respectively). The YLY900 variety showed notable yield improvement due to enhanced aboveground biomass production resulting from increased IPAR and RUE. In contrast, the QYHZ variety’s aboveground biomass accumulation was primarily influenced by RUE rather than IPAR, resulting in higher RUE and grain yields of 9.2% and 5.3%, respectively, compared to YLY900. Importantly, fertilization led to significant increases in yield, biomass, and RUE, while HI remained relatively constant. Both varieties demonstrated a positive relationship between grain yield and IPAR and RUE. Multiple regression analysis indicated that increasing RUE was the primary driver of yield improvement in hybrid rice varieties. By promoting sustainable agriculture and enhancing fertilizer management, elevating nitrogen and potassium levels from a low base would synergistically enhance rice yield and RUE, emphasizing the critical importance of RUE in hybrid rice productivity compared to HI.
Analysis of the Tomato mTERF Gene Family and Study of the Stress Resistance Function of SLmTERF-13
Authors: Su Ao , Ge Siyu , Zhou Boyan , Wang Ziyu , Zhou Liping , Zhang Ziwei , Yan Xiaoyu , Wang Yu , Li Dalong , Zhang He , Xu Xiangyang , Zhao Tingting
Published: August 2023

Mitochondrial transcription termination factor (mTERF) is a DNA-binding protein that is encoded by nuclear genes, ultimately functions in mitochondria and can affect gene expression. By combining with mitochondrial nucleic acids, mTERF regulates the replication, transcription and translation of mitochondrial genes and plays an important role in the response of plants to abiotic stress. However, there are few studies on mTERF genes in tomato, which limits the in-depth study and utilization of mTERF family genes in tomato stress resistance regulation. In this study, a total of 28 mTERF gene family members were obtained through genome-wide mining and identification of the tomato mTERF gene family. Bioinformatics analysis showed that all members of the family contained environmental stress or hormone response elements. Gene expression pattern analysis showed that the selected genes had different responses to drought, high salt and low temperature stress. Most of the genes played key roles under drought and salt stress, and the response patterns were more similar. The VIGS method was used to silence the SLmTERF13 gene, which was significantly upregulated under drought and salt stress, and it was found that the resistance ability of silenced plants was decreased under both kinds of stress, indicating that the SLmTERF13 gene was involved in the regulation of the tomato abiotic stress response. These results provide important insights for further evolutionary studies and contribute to a better understanding of the role of the mTERF genes in tomato growth and development and abiotic stress response, which will ultimately play a role in future studies of tomato gene function.
The Influence of a Key Indicator kv on the Diffusion Range of Underwater Oil Spill
Authors: Ji Hong , Wang Yaxin , Wang Ting , Yang Ke , Xing Zhixiang
Published: August 2023

As oil spills cause harm to the survival and environment of the ocean, the objective of the present paper is to study the oil migration range using the key indicator kv, which is defined as the ratio of oil spill speed to ocean current speed. The correctness of diffusion models created and estimated for subsea oil spills can be verified by experiments. We also considered the effect of key indicators on the horizontal and vertical dispersion ranges of oil spills. The study’s findings show that, under various kv settings, the horizontal and vertical spreading heights of oil spills both increase as kv rises. When kv is equal, the leakage velocity and water flow velocity increase synchronously, and over time, the horizontal distance and vertical diffusion height of the oil spill gradually increase. In the early stages of an oil spill, when kv = 50, 100, or 150, the vertical spreading velocity will rapidly decrease. The vertical spreading speed of spilled oil increases as kv rises when the water flow rate remains constant. The horizontal migration distance grows as kv decreases when the leakage rate is constant. Fitting curves for the vertical rise height and horizontal spreading distance for the same and various kv settings were also obtained in order to anticipate the migration mode of oil spills. This is critical for dealing with environmental damage caused by maritime oil spills, as well as emergency responses.
Research on the Optimization of the Operating Parameters of Methane Carbon Dioxide Reforming Using the Response Surface Methodology
Authors: Huang Xing , Lv Zhengguo , Yao Xin , Liu Yang , Wang Yuhe , Zhu Sijia
Published: August 2023

In order to reduce the production cost of the methane carbon dioxide reforming reaction, and improve its actual production efficiency, in this paper, the optimal working parameters of the methane carbon dioxide reforming reaction are studied. The influence of different factors on methane conversion is studied via a single-factor numerical simulation analysis and the response surface methodology. Firstly, a numerical model of the methane carbon dioxide reforming reaction is established using Ansys Chemkin Pro software to analyze the influence of single factors (reactor temperature, reaction pressure, gas velocity) on methane conversion rate; secondly, the response surface model with the methane conversion rate as the response value is established using the BBD (Box–Behnken design) method; and finally, the order of influence of each variable on methane conversion and the optimal reaction conditions are determined using the response surface method. The factors are listed in order of their influence on methane conversion as follows: reactor temperature > pressure > speed. The results show that when the temperature is 1135.114 K, the pressure is 0.103 MPa and the speed is 10slpm, the methane conversion rate is 93.7018%. In this paper, a method is adopted in which chemical reaction process simulation and numerical results prediction are combined, significantly reducing the simulation time and improving the calculation efficiency and accuracy, thus being of considerable scientific significance and theoretical value.
Development and Validation of Gas Chromatography–Mass Spectrometry Method for Quantification of Sibutramine in Dietary Supplements
Authors: Kozhuharov Vanya Rangelov , Ivanov Kalin , Karcheva-Bahchevanska Diana , Prissadova Natalia , Ivanova Stanislava
Published: August 2023

The use of dietary supplements (DSs) has dramatically increased in recent decades. However, around 20% of these products are reported to contain pharmacologically active undeclared compounds, most of which could expose consumers to serious side effects. According to recent data, some of the most commonly detected undeclared compounds are also considered doping and are prohibited by the World Anti-Doping Agency (WADA). One of the most frequently detected undeclared substances in DSs used for promoting weight loss is sibutramine. In 2011, all medicines containing sibutramine were urgently withdrawn from Europe and US markets because of serious side effects. In the present study, in order to detect and quantify sibutramine in DSs, a rapid, sensitive, and reliable gas chromatography with mass spectrometry (GC-MS) method was developed. The method was validated according to the ICH guidelines and demonstrated good linearity, accuracy, precision, and robustness. The limits of detection and quantification were 0.181 μg/mL and 0.5488 μg/mL, respectively. The method was applied to analyze 50 DSs promoting weight loss, fat burning, and performance enhancement. Sibutramine was detected in six of them in a range of 16.59–14,854.94 μg/per capsule. The high concentrations of sibutramine detected in some samples raise concerns about the potential health risks associated with the use of adulterated DSs. The proposed GC-MS method could be used successfully in the quality control of DSs or in different research programs, contributing to safety and the prevention of associated side effects.
Simulation Experiment and Mathematical Model of Liquid Carrying in the Entire Wellbore of Shale Gas Horizontal Wells
Authors: Yang Jian , Wang Qingrong , Sun Fengjing , Zhong Haiquan , Yang Jian
Published: August 2023

Shale gas is mostly produced using horizontal wells, since shale gas reservoirs have low porosity and permeability. It is challenging to predict a horizontal well’s critical liquid-carrying gas flow rate because horizontal wells have more complicated well structures and gas–liquid two-phase pipe flows than vertical wells. In addition, there are significant differences between shale gas reservoirs and conventional natural gas reservoirs as well as dynamic changes in the liquid production rate. The majority of critical liquid-carrying models currently in use in engineering are based on the force analysis of droplets in the gas stream or liquid film on the pipe wall in annular-mist flow in the vertical wellbore. However, they do not take into account the impact of changes to the entire wellbore structure and dynamic changes in the liquid production rate on gas–liquid two-phase flow patterns and liquid carrying in the wellbore. In order to perform the critical gas velocity test for liquid carrying in the entire wellbore of horizontal wells, a visual liquid-carrying simulation experimental device for the entire wellbore of horizontal wells and a high-speed camera were used in this study. The onset of liquid accumulation was analyzed comprehensively according to the overall increase of the wellbore liquid and the change of the system pressure. A modified K–H wave theory liquid-carrying model was developed by taking into account the impacts of liquid production rate and well inclination angle based on the experimental data, the K–H wave theory, the cross-section actual gas velocity, and the angle correction correlation formula. The improved liquid-carrying model is in good accordance with the test findings, according to the experimental results. In Shunan Gas Mine, Sichuan, China, there are eight deep shale gas wells, which produced a total of 25 sets of tests. The modified model was used to forecast and diagnose the liquid-carrying capacity in the entire wellbore of these wells. The diagnosis results are in good agreement with the actual production situation, and the coincidence rate is 92%.
Bayesian Regularized SEM: Current Capabilities and Constraints
Authors: van Erp Sara
Published: August 2023

An important challenge in statistical modeling is to balance how well our model explains the phenomenon under investigation with the parsimony of this explanation. In structural equation modeling (SEM), penalization approaches that add a penalty term to the estimation procedure have been proposed to achieve this balance. An alternative to the classical penalization approach is Bayesian regularized SEM in which the prior distribution serves as the penalty function. Many different shrinkage priors exist, enabling great flexibility in terms of shrinkage behavior. As a result, different types of shrinkage priors have been proposed for use in a wide variety of SEMs. However, the lack of a general framework and the technical details of these shrinkage methods can make it difficult for researchers outside the field of (Bayesian) regularized SEM to understand and apply these methods in their own work. Therefore, the aim of this paper is to provide an overview of Bayesian regularized SEM, with a focus on the types of SEMs in which Bayesian regularization has been applied as well as available software implementations. Through an empirical example, various open-source software packages for (Bayesian) regularized SEM are illustrated and all code is made available online to aid researchers in applying these methods. Finally, reviewing the current capabilities and constraints of Bayesian regularized SEM identifies several directions for future research.
The Management of Inflammatory Bowel Disease during Reproductive Years: An Updated Narrative Review
Authors: Hossein-Javaheri Nariman , Youssef Michael , Jeyakumar Yaanu , Huang Vivian , Tandon Parul
Published: August 2023

Inflammatory bowel disease (IBD) frequently affects women of childbearing age and often coincides with pregnancy. With an increased incidence of IBD, gastroenterologists and obstetricians are more frequently involved in caring for women of reproductive age. While the development of novel therapies has allowed for successful conception and pregnancy outcomes, many patients may hesitate to conceive due to concerns for presumed adverse IBD effects on maternal and fetal health. As such, a noticeable percentage of patients may choose voluntary childlessness. Indeed, active IBD carries a greater risk of adverse pregnancy outcomes, including a loss of pregnancy, preterm delivery, and emergent C-sections. However, those with a quiescent disease tend to have fewer pregnancy complications. Therefore, it is essential to achieve remission prior to conception to optimize pregnancy outcomes. Dedicated IBD and pregnancy clinics can greatly assist in improving patient knowledge and attitudes towards pregnancy; through individualized pre-conception counseling, education, and medication adherence, the risks of poor pregnancy outcomes can be minimized. Furthermore, it is important for healthcare providers to have a sufficient understanding of the medication safety and tools to measure the disease activity, while counseling patients during gestation and breastfeeding periods. This review article aims to provide the most recent evidence-based management methods for IBD during pregnancy.
Pricing of Pseudo-Swaps Based on Pseudo-Statistics
Authors: Franco Sebastian , Swishchuk Anatoliy
Published: August 2023

The main problem in pricing variance, volatility, and correlation swaps is how to determine the evolution of the stochastic processes for the underlying assets and their volatilities. Thus, sometimes it is simpler to consider pricing of swaps by so-called pseudo-statistics, namely, the pseudo-variance, -covariance, -volatility, and -correlation. The main motivation of this paper is to consider the pricing of swaps based on pseudo-statistics, instead of stochastic models, and to compare this approach with the most popular stochastic volatility model in the Cox–Ingresoll–Ross (CIR) model. Within this paper, we will demonstrate how to value different types of swaps (variance, volatility, covariance, and correlation swaps) using pseudo-statistics (pseudo-variance, pseudo-volatility, pseudo-correlation, and pseudo-covariance). As a result, we will arrive at a method for pricing swaps that does not rely on any stochastic models for a stochastic stock price or stochastic volatility, and instead relies on data/statistics. A data/statistics-based approach to swap pricing is very different from stochastic volatility models such as the Cox–Ingresoll–Ross (CIR) model, which, in comparison, follows a stochastic differential equation. Although there are many other stochastic models that provide an approach to calculating the price of swaps, we will use the CIR model for comparison within this paper, due to the popularity of the CIR model. Therefore, in this paper, we will compare the CIR model approach to pricing swaps to the pseudo-statistic approach to pricing swaps, in order to compare a stochastic model to the data/statistics-based approach to swap pricing that is developed within this paper.
Comparative Analysis of Diurnal Thermal Radiation Variation among Lunar Craters of Different Ages Using CE-2 MRM Data
Authors: Wu Lianghai , Cai Zhanchuan , He Xiu , Chen Yuyun , Meng Zhiguo
Published: August 2023

Microwave radiometer (MRM) is one of the important payloads on the Chang’e-2 (CE-2) Lunar satellite. In the Chang’e satellite’s observation of the microwave radiation brightness temperature (TB) on the lunar surface, there are some “cold spots” of microwave thermal radiation at night containing the Jackson crater. In order to compare the diurnal radiation TB differences of “cold spots” on the lunar surface, two typical craters at similar latitudes on the northern hemisphere on the lunar farside were selected: Jackson, which represents the new craters with a large number of discrete rocks on their surfaces; and Morse, which no longer has a large number of rocks after long-term meteorite impact and lunar evolution. In this paper, the diurnal variation of CE-2 MRM data in the two craters is presented, and a comparative analysis is made with the (FeO + TiO2) abundance (FTA) obtained by Clementine UV-VIS data and the rock abundance (RA) data of LRO Diviner. We find that the variation of the "cold spots" of lunar surface thermal radiation is closely related to the RA distribution in the newly formed craters on the lunar surface, and also has a certain correlation with the FTA.
Tensor Completion via Smooth Rank Function Low-Rank Approximate Regularization
Authors: Yu Shicheng , Miao Jiaqing , Li Guibing , Jin Weidong , Li Gaoping , Liu Xiaoguang
Published: August 2023

In recent years, the tensor completion algorithm has played a vital part in the reconstruction of missing elements within high-dimensional remote sensing image data. Due to the difficulty of tensor rank computation, scholars have proposed many substitutions of tensor rank. By introducing the smooth rank function (SRF), this paper proposes a new tensor rank nonconvex substitution function that performs adaptive weighting on different singular values to avoid the performance deficiency caused by the equal treatment of all singular values. On this basis, a novel tensor completion model that minimizes the SRF as the objective function is proposed. The proposed model is efficiently solved by adding the hot start method to the alternating direction multiplier method (ADMM) framework. Extensive experiments are carried out in this paper to demonstrate the resilience of the proposed model to missing data. The results illustrate that the proposed model is superior to other advanced models in tensor completeness.
The Seasonality of Eddy-Induced Chlorophyll-a Anomalies in the Kuroshio Extension System
Authors: Wang Tongyu , Zhang Shuwen , Chen Fajin , Xiao Luxing
Published: August 2023

The Kuroshio Extension (KE) System exhibits highly energetic mesoscale phenomena, but the impact of mesoscale eddies on marine ecosystems and biogeochemical cycling is not well understood. This study utilizes remote sensing and Argo floats to investigate how eddies modify surface and subsurface chlorophyll-a (Chl-a) concentrations. On average, cyclones (anticyclones) induce positive (negative) surface Chl-a anomalies, particularly in winter. This occurs because cyclones (anticyclones) lift (deepen) isopycnals and nitrate into (out of) the euphotic zone, stimulating (depressing) the growth of phytoplankton. Consequently, cyclones (anticyclones) result in greater (smaller) subsurface Chl-a maximum (SCM), depth-integrated Chl-a, and depth-integrated nitrate. The positive (negative) surface Chl-a anomalies induced by cyclones (anticyclones) are mainly located near (north of) the main axis of the KE. The second and third mode represent monopole Chl-a patterns within eddy centers corresponding to either positive or negative anomalies, depending on the sign of the principal component. Chl-a concentrations in cyclones (anticyclones) above the SCM layer are higher (lower) than the edge values, while those below are lower (higher), regardless of winter variations. The vertical distributions and displacements of Chl-a and SCM depth are associated with eddy pumping. In terms of frequency, negative (positive) Chl-a anomalies account for approximately 26% (18%) of the total cyclones (anticyclones) across all four seasons. The opposite phase suggests that nutrient supply resulting from stratification differences under convective mixing may contribute to negative (positive) Chl-a anomalies in cyclone (anticyclone) cores. Additionally, the opposite phase can also be attributed to eddy stirring, trapping high and low Chl-a, and/or eddy Ekman pumping. Based on OFES outputs, the seasonal variation of nitrate from winter to summer primarily depends on the effect of vertical mixing, indicating that convective mixing processes contribute to an increase (decrease) in nutrients during winter (summer) over the KE.
Dynamic Output Feedback and Neural Network Control of a Non-Holonomic Mobile Robot
Authors: Cardona Manuel , Serrano Fernando E.
Published: August 2023

This paper presents the design and synthesis of a dynamic output feedback neural network controller for a non-holonomic mobile robot. First, the dynamic model of a non-holonomic mobile robot is presented, in which these constraints are considered for the mathematical derivation of a feasible representation of this kind of robot. Then, two control strategies are provided based on kinematic control for this kind of robot. The first control strategy is based on driftless control; this means that considering that the velocity vector of the mobile robot is orthogonal to its restriction, a dynamic output feedback and neural network controller is designed so that the control action would be zero only when the velocity of the mobile robot is zero. The Lyapunov stability theorem is implemented in order to find a suitable control law. Then, another control strategy is designed for trajectory-tracking purposes, in which similar to the driftless controller, a kinematic control scheme is provided that is suitable to implement in more sophisticated hardware. In both control strategies, a dynamic control law is provided along with a feedforward neural network controller, so in this way, by the Lyapunov theory, the stability and convergence to the origin of the mobile robot position coordinates are ensured. Finally, two numerical experiments are presented in order to validate the theoretical results synthesized in this research study. Discussions and conclusions are provided in order to analyze the results found in this research study.
Optimization of Signal Timing for Urban Expressway Exit Ramp Connecting Intersection
Authors: Deng Mingjun , Chen Fei , Gong Yongtai , Li Xiang , Li Shuhang
Published: August 2023

To alleviate the traffic problems of congestion and queue overflow on a mainline at the intersection of an urban expressway exit ramp articulation during peak hours, a bi-level programming optimization model of signal timing is proposed. The lower-level optimization objective is to maximize the capacity of the expressway exit ramp that articulates with the entrance road, while the upper-level optimization objective is to minimize the average vehicle delay and the number of stops per vehicle, taking into account the queue length in the direction of the ramp and other directions. The particle swarm optimization algorithm is selected to solve the proposed model, applied to a real case, and is validated using MATLAB and VISSIM simulation platforms. The simulation results show that the average vehicle delay and the number of stops per vehicle in the exit ramp on the expressway are reduced by 22.09% and 18.60%, while those in the intersection area are reduced by 20.96% and 17.19%, respectively. The conclusion indicates that the signal timing scheme obtained by this method can effectively improve the traffic efficiency at the intersection of the exit ramp on the expressway and alleviate the problem of congestion and the overflow of the exit ramp back to the mainline.
Continuous Glucose Monitoring: A Possible Aid for Detecting Hypoglycemic Events during Insulin Tolerance Tests
Authors: Sim Soo Yeun , Ahn Moon Bae
Published: August 2023

The combined pituitary function test evaluates the anterior pituitary gland, while the insulin tolerance test evaluates growth hormone deficiencies. However, successful stimulation requires achieving an appropriate level of hypoglycemia. Close medical supervision for glucose monitoring is required during hypoglycemia induction and the test is often very tedious. In addition, a capillary blood sugar test (BST) and serum glucose levels may differ greatly. An alternative approach may be utilizing a continuous glucose-monitoring (CGM) system. We provide three cases in which CGM was successfully used alongside a standard BST and serum glucose levels during the combined pituitary function test to better detect and induce hypoglycemia. Three participants who were diagnosed with multiple pituitary hormone deficiencies during childhood were re-evaluated in adulthood; a Dexcom G6 CGM was used. The CGM sensor glucose and BST levels were simultaneously assessed for glycemic changes and when adequate hypoglycemia was reached during the combined pituitary function test. The CGM sensor glucose, BST, and serum glucose levels showed similar glucose trends in all three patients. A Bland–Altman analysis revealed that the CGM underestimated the BST values by approximately 9.68 mg/dL, and a Wilcoxon signed-rank test showed that the CGM and BST measurements significantly differed during the stimulation test (p = 0.003). Nevertheless, in all three cases, the CGM sensor mimicked the glycemic variability changes in the BST reading and assisted in monitoring appropriate hypoglycemia nadir. Thus, CGM can be used as a safe aid for clinicians to use during insulin tolerance tests where critical hypoglycemia is induced.
Online Continual Learning in Acoustic Scene Classification: An Empirical Study
Authors: Ha Donghee , Kim Mooseop , Jeong Chi Yoon
Published: August 2023

Numerous deep learning methods for acoustic scene classification (ASC) have been proposed to improve the classification accuracy of sound events. However, only a few studies have focused on continual learning (CL) wherein a model continually learns to solve issues with task changes. Therefore, in this study, we systematically analyzed the performance of ten recent CL methods to provide guidelines regarding their performances. The CL methods included two regularization-based methods and eight replay-based methods. First, we defined realistic and difficult scenarios such as online class-incremental (OCI) and online domain-incremental (ODI) cases for three public sound datasets. Then, we systematically analyzed the performance of each CL method in terms of average accuracy, average forgetting, and training time. In OCI scenarios, iCaRL and SCR showed the best performance for small buffer sizes, and GDumb showed the best performance for large buffer sizes. In ODI scenarios, SCR adopting supervised contrastive learning consistently outperformed the other methods, regardless of the memory buffer size. Most replay-based methods have an almost constant training time, regardless of the memory buffer size, and their performance increases with an increase in the memory buffer size. Based on these results, we must first consider GDumb/SCR for the continual learning methods for ASC.
Intelligent Soft Sensors
Authors: Tomažič Simon
Published: August 2023

In this Special Issue, we embark on a journey into the exciting field of intelligent soft sensors, and take a deep dive into the groundbreaking advances and potential that these software algorithms have introduced in various fields [...]
Adherence and the Diabetic Foot: High Tech Meets High Touch?
Authors: Srass Hadia , Ead J. Karim , Armstrong David G.
Published: August 2023

Diabetic foot ulcers, which are a common complication of diabetes, can have a negative impact on a person’s physical and mental health, including an increased risk of depression. Patients suffering from depression are less likely to keep up with diabetic foot care, thus increasing the risk of developing ulcers. However, with the use of artificial intelligence (AI), at-home patient care has become easier, which increases adherence. To better understand how new technologies, including machine learning algorithms and wearable sensors, might improve patient adherence and outcomes, we conducted a literature review of several sensor technologies, including SmartMat© and Siren Care© socks for temperature, SurroSense Rx/Orpyx© for pressure, and Orthotimer© for adherence. An initial search identified 143 peer-reviewed manuscripts, from which we selected a total of 10 manuscripts for further analysis. We examined the potential benefits of personalized content and clinician support for those receiving mobile health interventions. These findings may help to demonstrate the current and future utility of advanced technologies in improving patient adherence and outcomes, particularly in the context of diabetes management and the link between behavior and complications in diabetes, such as diabetic foot ulcers.
Skylight Polarization Pattern Simulator Based on a Virtual-Real-Fusion Framework for Urban Bionic Polarization Navigation
Authors: Li Qianhui , Dong Liquan , Hu Yao , Hao Qun , Lv Jiahang , Cao Jie , Cheng Yang
Published: August 2023

In a data-driven context, bionic polarization navigation requires a mass of skylight polarization pattern data with diversity, complete ground truth, and scene information. However, acquiring such data in urban environments, where bionic polarization navigation is widely utilized, remains challenging. In this paper, we proposed a virtual-real-fusion framework of the skylight polarization pattern simulator and provided a data preparation method complementing the existing pure simulation or measurement method. The framework consists of a virtual part simulating the ground truth of skylight polarization pattern, a real part measuring scene information, and a fusion part fusing information of the first two parts according to the imaging projection relationship. To illustrate the framework, we constructed a simulator instance adapted to the urban environment and clear weather and verified it in 174 urban scenes. The results showed that the simulator can provide a mass of diverse urban skylight polarization pattern data with scene information and complete ground truth based on a few practical measurements. Moreover, we released a dataset based on the results and opened our code to facilitate researchers preparing and adapting their datasets to their research targets.
Breathable and Stretchable Organic Electrochemical Transistors with Laminated Porous Structures for Glucose Sensing
Authors: Guo Haihong , Liu Changjian , Peng Yujie , Gao Lin , Yu Junsheng
Published: August 2023

Dynamic glucose monitoring is important to reduce the risk of metabolic diseases such as diabetes. Wearable biosensors based on organic electrochemical transistors (OECTs) have been developed due to their excellent signal amplification capabilities and biocompatibility. However, traditional wearable biosensors are fabricated on flat substrates with limited gas permeability, resulting in the inefficient evaporation of sweat, reduced wear comfort, and increased risk of inflammation. Here, we proposed breathable OECT-based glucose sensors by designing a porous structure to realize optimal breathable and stretchable properties. The gas permeability of the device and the relationship between electrical properties under different tensile strains were carefully investigated. The OECTs exhibit exceptional electrical properties (gm ~1.51 mS and Ion ~0.37 mA) and can retain up to about 44% of their initial performance even at 30% stretching. Furthermore, obvious responses to glucose have been demonstrated in a wide range of concentrations (10−7–10−4 M) even under 30% strain, where the normalized response to 10−4 M is 26% and 21% for the pristine sensor and under 30% strain, respectively. This work offers a new strategy for developing advanced breathable and wearable bioelectronics.
Machine Learning Model Application and Comparison in Actuated Traffic Signal Forecasting
Authors: Xie Feng , Naumann Sebastian , Czogalla Olaf , Zadek Hartmut
Published: August 2023

Traffic signal forecasting plays a significant role in intelligent traffic systems since it can predict upcoming traffic signal without using traditional radio-based direct communication with infrastructures, which causes high risk in the communication security. Previously, mathematical and statistical approach has been adopted to predict fixed time traffic signals, but it is no longer suitable for modern traffic-actuated control systems, where signals are dependent on the dynamic requests from traffic flows. And as a large amount of data is available, machine learning methods attract more and more attention. This paper views signal forecasting as a time-series problem. Firstly, a large amount of real data is collected by detectors implemented at an intersection in Hanover via IoT communication among infrastructures. Then, Baseline Model, Dense Model, Linear Model, Convolutional Neural Network, and Long Short-Term Memory (LSTM) machine learning models are trained by one-day data and the results are compared. At last, LSTM is selected for a further training with one-month data producing a test accuracy over 95%, and the median of deviation is only 2 s. Moreover, LSTM is further evaluated as a binary classifier, generating a classification accuracy over 92% and AUC close to 1.
Traffic Stream Analysis by Radar Sensors on Two-Lane Roads for Free-Moving and Constrained Vehicles Identification
Authors: Cantisani Giuseppe , Del Serrone Giulia , Mauro Raffaele , Peluso Paolo , Pompigna Andrea
Published: August 2023

This paper focuses on the analysis of traffic streams on two-lane highways, which are crucial components of transportation networks. Traffic flow measurement technologies, such as detection stations, radar guns, or video cameras, have been used over the years to detect the level of traffic and the operating conditions. This type of sensor can record a large amount of data which is useful to evaluate and monitor road traffic conditions, and it is possible to identify free-moving and constrained vehicles by processing the collected data. This study introduces an exponential headway model to identify the headway threshold above which vehicles can be considered as unconditioned. However, this value could identify vehicles which still retain some autonomy in their speed and maneuvering. Therefore, an additional criterion to distinguish between apparently and actually conditioned vehicles has been introduced, analyzing the speed differences between a vehicle and the preceding one. Three-month sequences of traffic monitored through radar devices placed on some Italian two-lane roads have been analyzed and an exponential headway model has been introduced, as an illustrative example. The results show that introducing the criterion of maneuvering freedom can significantly improve traffic flow analysis, modifying the starting critical values of 4 and 8 s per each studied section, to 2.5 and 3 s, approaching the values suggested by international manuals for traffic flow quality analysis.
Modelling and Predictive Monitoring of Business Processes under Uncertainty with Reinforcement Learning
Authors: Bousdekis Alexandros , Kerasiotis Athanasios , Kotsias Silvester , Theodoropoulou Georgia , Miaoulis Georgios , Ghazanfarpour Djamchid
Published: August 2023

The analysis of business processes based on their observed behavior recorded in event logs can be performed with process mining. This method can discover, monitor, and improve processes in various application domains. However, the process models produced by typical process discovery methods are difficult for humans to understand due to their high complexity (the so-called “spaghetti-like” process models). Moreover, these methods cannot handle uncertainty or perform predictions because of their deterministic nature. Recently, researchers have been developing predictive approaches for running business cases of processes. This paper focuses on developing a predictive business process monitoring approach using reinforcement learning (RL), which has been successful in other contexts but not yet explored in this area. The proposed approach is evaluated in the banking sector through a use case.