bluuebunny/crossref_metadata_2025 huggingface dataset:
Age-Related Changes and Reorganization of Creativity and Intelligence Indices in Schoolchildren and University Students
Authors: Razumnikova Olga , Bakaev Maxim
Published: August 2022

Despite the lasting interest towards the relationship between intelligence and creativity, comparably less attention is paid to its age-related changes. Our paper considers the organization of fluid intelligence and psychometric indicators of creativity and is based on the experimental data obtained for children aged 11 (n = 99) and for young adults (n = 77). We used two figural and verbal tasks with and without time limit. We found that the age-related differences in creativity are dependent on the context and the type of testing. The young adults were different from the children, having higher indicators of verbal and figurative creativity, except for the originality of the drawings created within the Incomplete Figures test, and having considerably higher test results for fluid intelligence. These age-related differences, together with the discovered closer relationship between the creativity indicators in the young adults group compared to the children, might suggest insufficient contribution of the components of the executive control of information selection (inhibition, shifting, and updating), which had not fully formed in eleven-year-olds. The comparison of the various indicators of creativity suggests that the most complex task for the children was the composition of an original sentence by joining nouns from various semantic categories.
Glacial Debris Flow Blockage Event (2018) in the Sedongpu Basin of the Yarlung Zangbo River, China: Occurrence Factors and Its Implications
Authors: Huai Baojuan , Ding Minghu , Ai Songtao , Sun Weijun , Wang Yetang , Gao Jiajia
Published: August 2022

In this paper, the glacial debris flow blockage event, on 17 October 2018, in the Sedongpu basin of the Yarlung Zangbo River is taken as an example to analyse the occurrence and development of glacier hazards in this region. Multi-sources including remote sensing products, DEM, earthquake records and meteorological data were used to analyse the characteristics and mechanism of glacier hazards. The Elmer/Ice dynamic model was chosen to simulate the glacial surface velocity. It was found that topography and climate background determine that the hazard happens periodically. Based on the meteorological records of the Linzhi station, the warming rate was greater than 0.40 °C/10a during the period 1960–2017. The short-term heavy rainfall with daily values of 9.3 mm before the blockage event was also regarded as a factor. Both heavy rain and earthquake were triggering factors of the ice avalanche that led to the glacial debris flow. The glacier surface velocity of the Dongpu glacier simulated by Elmer/Ice model can reach 19 cm/d. This study has extensive applicability significance in glacier hazard mitigation under a changing climate.
Symptomatic Vascular Compression of Brainstem May Be Managed Conservatively
Authors: Ghannam Malik , Berns Meaghen , Salari Apameh , Moore Lisa , Brown Kevin
Published: August 2022

Medulla compression from vertebral artery abnormality is a very rare occurrence with few cases present in the literature. It has been documented to present with a very wide spectrum of clinical symptomatology ranging from asymptomatic to full hemiplegia. There is currently no treatment algorithm in place to guide clinicians encountering such patients but treatments have historically involved major posterior compartment surgical interventions. This case outlined a patient evaluated for dizziness without any other neurological symptoms or signs, found to have abnormal dilatation, elongation, and tortuosity of the vertebral artery with resultant compression of the medulla oblongata. The patient was managed conservatively after discussion of surgical options. This report outlined an important consideration for management of medullar compression by vertebral artery based on symptom severity with the possibility of postponing surgical or endovascular interventions and opting for conservative management with an anti-platelet regimen, particularly in the short term.
Therapeutic Potential of Human Microbiome-Based Short-Chain Fatty Acids and Bile Acids in Liver Disease
Authors: Ganesan Raja , Suk Ki Tae
Published: August 2022

Microbiome-derived short chain fatty acids (SCFAs: acetate, propionate, and butyrate) and bile acids (BAs: primary BAs and secondary BAs) widely influence liver metabolic inflammation, immune responses, and carcinogenesis. In recent literature, the role of SCFAs and BAs in various liver diseases has been discussed. SCFAs and BAs are two types of microbiome-derived metabolites and they have been shown to have immunoregulatory ability in autoimmunity, inflammation, and liver-cancer microcellular environments. SCFAs and BAs are dependent on dietary components. The numerous regulatory processes in lymphocytes and non-immune cells that underpin both the positive and harmful effects of microbial metabolites include variations in metabolic signaling and epigenetic states. As a result, histone deacetylase (HDAC) inhibitors, SCFAs, and BAs, which are powerful immunometabolism modulators, have been explored. BAs have also been shown to alter the microbiome as well as adaptive and innate immune systems. We therefore emphasize the important metabolites in liver disease for clinical therapeutic applications. A deep understanding of SCFAs and Bas, as well as their molecular risk, could reveal more about certain liver-disease conditions.
Noise-Regularized Advantage Value for Multi-Agent Reinforcement Learning
Authors: Wang Siying , Chen Wenyu , Hu Jian , Hu Siyue , Huang Liwei
Published: August 2022

Leveraging global state information to enhance policy optimization is a common approach in multi-agent reinforcement learning (MARL). Even with the supplement of state information, the agents still suffer from insufficient exploration in the training stage. Moreover, training with batch-sampled examples from the replay buffer will induce the policy overfitting problem, i.e., multi-agent proximal policy optimization (MAPPO) may not perform as good as independent PPO (IPPO) even with additional information in the centralized critic. In this paper, we propose a novel noise-injection method to regularize the policies of agents and mitigate the overfitting issue. We analyze the cause of policy overfitting in actor–critic MARL, and design two specific patterns of noise injection applied to the advantage function with random Gaussian noise to stabilize the training and enhance the performance. The experimental results on the Matrix Game and StarCraft II show the higher training efficiency and superior performance of our method, and the ablation studies indicate our method will keep higher entropy of agents’ policies during training, which leads to more exploration.
Optimal Triggering Policy of Protective Devices Considering Self-Exciting Mechanism of Shocks
Authors: Wu Yaguang , Qiu Qingan
Published: August 2022

Safety-critical systems are commonly required to complete specific missions in shock environments, and their failures may lead to severe economic losses and significant safety hazards. To enhance system reliability, protective devices are commonly equipped to resist external shocks. The existing literature focuses mainly on the maintenance policy of safety-critical systems, ignoring the system reliability analysis considering the effect of protective devices and the self-exciting mechanism of shocks. This paper considers multi-state systems equipped with a protective device in shock environments where valid shocks and invalid shocks occur stochastically. The system state degenerates due to valid shocks or the self-exciting behavior of invalid shocks. The self-exciting mechanism is triggered when the number of cumulative or consecutive invalid shocks suffered by the system exceeds a certain threshold, leading the system to a worse state. The protective device can be triggered to protect the system from the damage of external shocks when the state is worse than a predetermined threshold. The protective effect is characterized by reducing the probability of valid shocks. A finite Markov chain embedding approach is used to evaluate the system reliability index. In addition, an optimization model is constructed to determine the optimal triggering threshold of the protective device. The numerical results indicate that protective devices can significantly improve the reliability of the system and incorporating the self-exciting mechanism of shocks into reliability modeling contributes to accurate reliability evaluation.
Survey on Synthetic Data Generation, Evaluation Methods and GANs
Authors: Figueira Alvaro , Vaz Bruno
Published: August 2022

Synthetic data consists of artificially generated data. When data are scarce, or of poor quality, synthetic data can be used, for example, to improve the performance of machine learning models. Generative adversarial networks (GANs) are a state-of-the-art deep generative models that can generate novel synthetic samples that follow the underlying data distribution of the original dataset. Reviews on synthetic data generation and on GANs have already been written. However, none in the relevant literature, to the best of our knowledge, has explicitly combined these two topics. This survey aims to fill this gap and provide useful material to new researchers in this field. That is, we aim to provide a survey that combines synthetic data generation and GANs, and that can act as a good and strong starting point for new researchers in the field, so that they have a general overview of the key contributions and useful references. We have conducted a review of the state-of-the-art by querying four major databases: Web of Sciences (WoS), Scopus, IEEE Xplore, and ACM Digital Library. This allowed us to gain insights into the most relevant authors, the most relevant scientific journals in the area, the most cited papers, the most significant research areas, the most important institutions, and the most relevant GAN architectures. GANs were thoroughly reviewed, as well as their most common training problems, their most important breakthroughs, and a focus on GAN architectures for tabular data. Further, the main algorithms for generating synthetic data, their applications and our thoughts on these methods are also expressed. Finally, we reviewed the main techniques for evaluating the quality of synthetic data (especially tabular data) and provided a schematic overview of the information presented in this paper.
Output Power Control and Load Mitigation of a Horizontal Axis Wind Turbine with a Fully Coupled Aeroelastic Model: Novel Sliding Mode Perspective
Authors: Zhang Hongfu , Wen Jiahao , Golnary Farshad , Zhou Lei
Published: August 2022

The power control of horizontal axis wind turbines can affect significantly the vibration loads and fatigue life of the tower and the blades. In this paper, we both consider the power control and vibration load mitigation of the tower fore-aft vibration. For this purpose, at first, we developed a fully coupled model of the NREL 5MW turbine. This model considers the full aeroelastic behaviour of the blades and tower and is validated by experiment results, comparing the time history data with the FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code which is developed by NREL (National Renewable Energy Lab in the United States). In the next, novel sensorless control algorithms are developed based on the supper twisting sliding mode control theory and sliding mode observer for disturbance rejection. In region II (the wind speed is between the cut-in and rated wind velocity), the novel sensorless control algorithm increased the power coefficient in comparison to the conventional indirect speed control (ISC) method (the conventional method in the industry). In region III (the wind speed is between the rated and cut-out speed), an adaptive neural fuzzy inference system (ANFIS) is developed to estimate pitch sensitivity. The rotor speed, pitch angle, and effective wind velocity are inputs, and pitch sensitivity is the output. The designed novel pitch control performance is compared with the gain scheduled PI (GPI) method (the conventional approach in this region). The simulation results demonstrate that the flapwise blade displacement is reduced significantly. Finally, to reduce the fore-aft vibration of the tower, a tuned mass damper (TMD) was designed by using the genetic algorithm and the fully coupled model. In comparison to the literature body, we demonstrate that the fully coupled model provides much better accuracy in comparison to the uncoupled model to estimate the vibration loads.
Impulsive Control and Synchronization for Fractional-Order Hyper-Chaotic Financial System
Authors: Li Xinggui , Rao Ruofeng , Zhong Shouming , Yang Xinsong , Li Hu , Zhang Yulin
Published: August 2022

This paper reports a new global Mittag-Leffler synchronization criterion with regard to fractional-order hyper-chaotic financial systems by designing the suitable impulsive control and the state feedback controller. The significance of this impulsive synchronization lies in the fact that the backward economic system can synchronize asymptotically with the advanced economic system under effective impulse macroeconomic management means. Matlab’s LMI toolbox is utilized to deduce the feasible solution in a numerical example, which shows the effectiveness of the proposed methods. It is worth mentioning that the LMI-based criterion usually requires the activation function of the system to be Lipschitz, but the activation function in this paper is fixed and truly nonlinear, which cannot be assumed to be Lipschitz continuous. This is another mathematical difficulty overcome in this paper.
Indicators of Mental Health Disorder, COVID-19 Prevention Compliance and Vaccination Intentions among Refugees in Kenya
Authors: Oyekale Abayomi Samuel
Published: August 2022

Background and Objectives: COVID-19 remains a major development challenge in many developing countries. This study analysed the effect of mental health disorder and indicators of COVID-19 preventive practices on vaccination intentions among refugees in Kenya. Materials and Methods: The data were the fourth and fifth waves of the High Frequency Phone Surveys on the impacts of COVID-19 that were collected by the Kenyan National Bureau of Statistics (KNBS) between May 2020 and June 2021. The data were collected from Kakuma, Kalobeyei, Dadaab and Shona camps using the stratified random sampling method. The data were analysed with random effects instrumental variable Probit regression model. Results: The results showed that 69.32% and 93.16% of the refugees were willing to be vaccinated during the 4th and 5th waves, respectively. The fear of dying was reported by 85.89% and 74.19% during the 4th and 5th waves, respectively. COVID-19 contact prevention and immune boosting indicators were differently influenced by some demographic and anxiety index variables, while being endogenous influenced vaccine hesitancy along with urban residence, age, knowing infected persons, days of depression, days of anxiety, days of physical reactions, members losing job, searching for jobs, accepting job offers and being employed. Conclusions: It was concluded that efforts to promote COVID-19 vaccination should address mental health disorder and compliance with existing COVID-19 contact and immune boosting behaviour with a focus on urban residents and youths.
A Selective and Sensitive LC-MS/MS Method for Quantitation of Indole in Mouse Serum and Tissues
Authors: Joshi Vineet , Chhonker Yashpal S. , Soni Dhruvkumar , Cunningham Kelly C. , Samuelson Derrick R. , Murry Daryl J.
Published: August 2022

Indole is an endogenous substance currently being evaluated as a biomarker for ulcerative colitis, irritable bowel syndrome, Crohn’s disease and non-alcoholic fatty liver disease. A novel, selective, and sensitive method using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was developed for quantitation of indole concentrations in mouse plasma and tissues. Samples were prepared by protein precipitation using ice-cold acetonitrile (ACN) followed by injecting the extracted analyte to LC-MS/MS system. Indole was separated using Synergi Fusion C18 (4 µm, 250 × 2.0 mm) column with mobile phase 0.1% aqueous formic acid (A) and methanol (B) using gradient flow with run time 12 min. The mass spectrometer was operated in atmospheric pressure chemical ionization (APCI) positive mode at unit resolution in multiple reaction monitoring (MRM) mode, using precursor ion > product ion combinations of 118.1 > 91.1 m/z for indole and 124.15 > 96.1 m/z for internal standard (IS) indole d7. The MS/MS response was linear over the range of indole concentrations (1–500 ng/mL). The validated method was applied for quantitation of indole concentrations range in mouse lungs (4.3–69.4 ng/g), serum (0.8–38.7 ng/mL) and cecum (1043.8–12,124.4 ng/g). This method would help investigate the role of indole as a biomarker and understand its implications in different disease states.
Machine Learning to Predict Junction Temperature Based on Optical Characteristics in Solid-State Lighting Devices: A Test on WLEDs
Authors: Azarifar Mohammad , Ocaksonmez Kerem , Cengiz Ceren , Aydoğan Reyhan , Arik Mehmet
Published: August 2022

While junction temperature control is an indispensable part of having reliable solid-state lighting, there is no direct method to measure its quantity. Among various methods, temperature-sensitive optical parameter-based junction temperature measurement techniques have been used in practice. Researchers calibrate different spectral power distribution behaviors to a specific temperature and then use that to predict the junction temperature. White light in white LEDs is composed of blue chip emission and down-converted emission from photoluminescent particles, each with its own behavior at different temperatures. These two emissions can be combined in an unlimited number of ways to produce diverse white colors at different brightness levels. The shape of the spectral power distribution can, in essence, be compressed into a correlated color temperature (CCT). The intensity level of the spectral power distribution can be inferred from the luminous flux as it is the special weighted integration of the spectral power distribution. This paper demonstrates that knowing the color characteristics and power level provide enough information for possible regressor trainings to predict any white LED junction temperature. A database from manufacturer datasheets is utilized to develop four machine learning-based models, viz., k-Nearest Neighbor (KNN), Radius Near Neighbors (RNN), Random Forest (RF), and Extreme Gradient Booster (XGB). The models were used to predict the junction temperatures from a set of dynamic opto-thermal measurements. This study shows that machine learning algorithms can be employed as reliable novel prediction tools for junction temperature estimation, particularly where measuring equipment limitations exist, as in wafer-level probing or phosphor-coated chips.
Metalloporphyrin Metal–Organic Frameworks: Eminent Synthetic Strategies and Recent Practical Exploitations
Authors: Ebrahimi Arash , Krivosudský Lukáš
Published: August 2022

The emergence of metal–organic frameworks (MOFs) in recent years has stimulated the interest of scientists working in this area as one of the most applicable archetypes of three-dimensional structures that can be used as promising materials in several applications including but not limited to (photo-)catalysis, sensing, separation, adsorption, biological and electrochemical efficiencies and so on. Not only do MOFs have their own specific versatile structures, tunable cavities, and remarkably high surface areas, but they also present many alternative procedures to overcome emerging obstacles. Since the discovery of such highly effective materials, they have been employed for multiple uses; additionally, the efforts towards the synthesis of MOFs with specific properties based on planned (template) synthesis have led to the construction of several promising types of MOFs possessing large biological or bioinspired ligands. Specifically, metalloporphyrin-based MOFs have been created where the porphyrin moieties are either incorporated as struts within the framework to form porphyrinic MOFs or encapsulated inside the cavities to construct porphyrin@MOFs which can combine the peerless properties of porphyrins and porous MOFs simultaneously. In this context, the main aim of this review was to highlight their structure, characteristics, and some of their prominent present-day applications.
Oleanane-Type Triterpene Conjugates with 1H-1,2,3-Triazole Possessing of Fungicidal Activity
Authors: Chen Zili , Jiang Yu , Xu Chen , Sun Xiangyu , Ma Chao , Xia Zihao , Zhao Hanqing
Published: August 2022

The triazole pesticide is an organic nitrogen-containing heterocyclic compound with a 1,2,3-Triazole ring. In order to develop a potential glucosamine-6-phosphate synthase (GlmS) inhibitor bactericide, 18 triazole-derivative compounds were synthesized efficiently. In addition, these compounds have not been reported in the literature. The structure was confirmed by high-resolution mass spectrometry (HRMS), 1H NMR and 13C NMR. The potential use of the most promising derivatives has been investigated by testing their antifungal activity and enzyme inhibitory activity, revealing inhibitory activities in the low micromolar range. Among them, the antifungal effects of compounds 1e, 1f, 1g, 2e, 2f, and 2g on Sclerotinia sclerotiorum were particularly significant, all of which were above 83%. These compounds will be further investigated as potential antifungal lead compounds. Their structure–activity relationships are discussed based on the effects of substituted phenyl groups on compounds.
Degradation Mechanism of Micro-Nanobubble Technology for Organic Pollutants in Aqueous Solutions
Authors: Zhou Youbin , Cao Dapeng , Zhang Xianren
Published: August 2022

Micro-nanobubbles (MNBs) technology has emerged as an effective means of sewage treatment, while the molecular mechanism for its pollutant degradation is still unknown. In this paper, the reactive molecular dynamics simulation technique is used to study the degradation mechanism of pollutants caused by shock-induced nanobubble collapse. We first demonstrate that the propagating shock wave can induce nanobubble collapse, and the collapsing nanobubble has the ability to focus mechanical energy via the converging motion of liquid in the interior of the bubble, leading to the formation of a high-speed jet with a much higher energy density. We also unveil the mechanical nature of long-chain pollutant degradation and the mechanism of free radical generation. Due to the impacting jet, the high-gradient flow has the ability to stretch the long-chain molecule and cause mechanical scission of the molecule in a homolytic manner. Finally, our simulation results reveal that adding ozone molecules to the collapsing bubble would introduce an additional dehydrogenation mechanism.
The Polish Version of the Avoidant/Restrictive Food Intake Disorder Questionnaire—Parents Report (ARFID-Q-PR) and the Nine Items Avoidant/Restrictive Food Intake Disorder Screen—Parents Report (NIAS-PR): Maternal Perspective
Authors: Ziółkowska Beata , Ocalewski Jarosław , Zickgraf Hana , Brytek-Matera Anna
Published: August 2022

The aim of the present study was to develop and validate the Avoidant/Restrictive Food Intake Disorder Questionnaire—Parents Report (ARFID-Q-PR), a new tool to diagnose ARFID, based on a report submitted by Polish mothers of children aged 2 to 10 years. In total, 167 mothers of boys and girls aged 2 to 10 participated in the study. We used the ARFID-Q-PR and the Nine Items Avoidant/Restrictive Food Intake Disorder Screen—Parents Report (NIAS-PR). In addition, all mothers were asked to provide information on age, sex, height and weight, chronic somatic diseases, neurodevelopmental and mental disorders as well as intellectual disability of their children. Results of the reliability analysis demonstrated that the ARFID-Q-PR had adequate internal consistency (Cronbach’s alpha of 0.84). The stability of the ARFID-Q-PR factorial structure was confirmed. It is composed of three subscales: (1) attitudes to food; (2) justification for restrictions; (3) somatic symptoms. Our findings demonstrated that the ARFID-Q-PR total score was positively associated with the NIAS-PR total score. In addition, children with developmental and mental disorders substantially demonstrated more ARFID symptoms than did the children in the general population. The Polish version ARFID-Q-PR can be used to recognize the ARFID symptoms in young children by the main feeder in the family—mother or father.
Isolation, Partial Characterization and Application of Bacteriophages in Eradicating Biofilm Formation by Bacillus cereus on Stainless Steel Surfaces in Food Processing Facilities
Authors: Gdoura-Ben Amor Maroua , Culot Antoine , Techer Clarisse , AlReshidi Mousa , Adnan Mohd , Jan Sophie , Baron Florence , Grosset Noël , Snoussi Mejdi , Gdoura Radhouane , Gautier Michel
Published: August 2022

The Bacillus cereus (B. cereus) group is a widespread foodborne pathogen with a persistent ability to form biofilm, and with inherent resistance to traditional treatment in the food industry. Bacteriophages are a promising biocontrol agent that could be applied to prevent or eliminate biofilms formation. We have described, in this study, the isolation from sewage samples and preliminary characterization of bacteriophages that are active against the B. cereus group. The effectiveness of phage treatment for reducing B. cereus attachment and biofilms on stainless steel surfaces has been also assessed using three incubation periods at different titrations of each phage. Out of 62 phages isolated, seven showed broad-spectrum lytic action against 174 B. cereus isolates. All selected phages appeared to be of the Siphoviridae family. SDS-PAGE proved that two phages have a similar profile, while the remainder are distinct. All isolated phages have the same restriction pattern, with an estimated genome size of around 37 kb. The isolated bacteriophages have been shown to be effective in preventing biofilm formation. Reductions of up to 1.5 log10 UFC/cm2 have been achieved, compared to the untreated biofilms. Curative treatment reduced the bacterial density by 0.5 log10 UFC/cm2. These results support the prospect of using these phages as a potential alternative strategy for controlling biofilms in food systems.
Mexican Strains of Anaplasma marginale: A First Comparative Genomics and Phylogeographic Analysis
Authors: Dantán-González Edgar , Quiroz-Castañeda Rosa Estela , Aguilar-Díaz Hugo , Amaro-Estrada Itzel , Martínez-Ocampo Fernando , Rodríguez-Camarillo Sergio
Published: August 2022

The One Health approach looks after animal welfare and demands constant monitoring of the strains that circulate globally to prevent outbreaks. Anaplasma marginale is the etiologic agent of bovine anaplasmosis and is endemic worldwide. This study aimed to analyze, for the first time, the genetic diversity of seven Mexican strains of A. marginale and their relationship with other strains reported. The main features of A. marginale were obtained by characterizing all 24 genomes reported so far. Genetic diversity and phylogeography were analyzed by characterizing the msp1a gene and 5′-UTR microsatellite sequences and constructing a phylogenetic tree with 540 concatenated genes of the core genome. The Mexican strains show 15 different repeat sequences in six MSP1a structures and have phylogeographic relationships with strains from North America, South America, and Asia, which confirms they are highly variable. Based on our results, we encourage the performance of genome sequencing of A. marginale strains to obtain a high assembly level of molecular markers and the performance of extensive phylogeographic analysis. Undoubtedly, genomic surveillance helps build a picture of how a pathogen changes and evolves in geographical regions. However, we cannot discard the study of relationships pathogens establish with ticks and how they have co-evolved to establish themselves as a successful transmission system.
Polymyxin B in Combination with Glycerol Monolaurate Exerts Synergistic Killing against Gram-Negative Pathogens
Authors: Zheng Yun , Yang Ning , Ding Yuting , Li Jiajia , Liu Yanyan , Chen Haoran , Li Jiabin
Published: August 2022

The rapid emergence and spread of multidrug-resistant (MDR) bacterial pathogens pose a serious danger to worldwide human health, and resistance to last-resort drugs, such as polymyxins, is being increasingly detected in MDR Gram-negative pathogens. There is an urgent need to find and optimize combination therapies as an alternative therapeutic strategy, with a dry pipeline in novel antibiotic research and development. We found a monoester formed from the combination of lauric acid and glycerol, glycerol monolaurate (GML), possessing prominent antibacterial and anti-inflammatory activity. However, it is still unclear whether GML in combination could increase antimicrobial activity. Here, we reported that polymyxin B (PMNB) combined with GML exhibited a synergistic antimicrobial impact on Gram-negative strains in vitro, including clinical MDR isolates. This synergistic antimicrobial activity correlated with the destruction of bacterial cell structures, eradication of preformed biofilms, and increased reactive oxygen species (ROS) accumulation. We also showed that PMNB synergized with GML effectively eliminated pathogens from bacterial pneumonia caused by Klebsiella pneumoniae to rescue mice. Our research demonstrated that the PMNB and GML combination induced synergistic antimicrobial activity for Gram-negative pathogens in vitro and in vivo. These findings are of great importance for treating bacterial infections and managing the spread of infectious diseases.
Functionalized Self-Assembled Monolayers: Versatile Strategies to Combat Bacterial Biofilm Formation
Authors: Lundin Pamela M. , Fiser Briana L. , Blackledge Meghan S. , Pickett Hannah L. , Copeland Abigail L.
Published: August 2022

Bacterial infections due to biofilms account for up to 80% of bacterial infections in humans. With the increased use of antibiotic treatments, indwelling medical devices, disinfectants, and longer hospital stays, antibiotic resistant infections are sharply increasing. Annual deaths are predicted to outpace cancer and diabetes combined by 2050. In the past two decades, both chemical and physical strategies have arisen to combat biofilm formation on surfaces. One such promising chemical strategy is the formation of a self-assembled monolayer (SAM), due to its small layer thickness, strong covalent bonds, typically facile synthesis, and versatility. With the goal of combating biofilm formation, the SAM could be used to tether an antibacterial agent such as a small-molecule antibiotic, nanoparticle, peptide, or polymer to the surface, and limit the agent’s release into its environment. This review focuses on the use of SAMs to inhibit biofilm formation, both on their own and by covalent grafting of a biocidal agent, with the potential to be used in indwelling medical devices. We conclude with our perspectives on ongoing challenges and future directions for this field.
PEG Spacer Length Substantially Affects Antibody-Based Nanocarrier Targeting of Dendritic Cell Subsets
Authors: Brückner Maximilian , Fichter Michael , da Costa Marques Richard , Landfester Katharina , Mailänder Volker
Published: August 2022

Successful cell targeting depends on the controlled positioning of cell-type-specific antibodies on the nanocarrier’s (NC) surface. Uncontrolled antibody immobilization results in unintended cell uptake due to Fc-mediated cell interaction. Consequently, precise immobilization of the Fc region towards the nanocarrier surface is needed with the Fab regions staying freely accessible for antigen binding. Moreover, the antibody needs to be a certain distance from the nanocarrier surface, influencing the targeting performance after formation of the biomolecular corona. This can be achieved by using PEG linker molecules. Here we demonstrate cell type-specific targeting for dendritic cells (DC) as cellular key regulators of immune responses. However, to date, dendritic cell targeting experiments using different linker lengths still need to be conducted. Consequently, we focused on the surface modification of nanocarriers with different molecular weight PEG linkers (0.65, 2, and 5 kDa), and their ability to reduce undesired cell uptake, while achieving efficient DC targeting via covalently immobilized antibodies (stealth targeting). Our findings demonstrate that the PEG linker length significantly affects active dendritic cell targeting from cell lines (DC2.4) to primary cells (BMDCs, splenocytic conventional DCs type 1 (cDC1)). While antibody-functionalized nanocarriers with a shorter PEG length (0.65 kDa) showed the best targeting in DC2.4, a longer PEG length (5 kDa) was required to specifically accumulate in BMDCs and splenocytic cDC1. Our study highlights that these crucial aspects must be considered when targeting dendritic cell subsets, which are of great importance in the fields of cancer immunotherapy and vaccine development.
Auxin-Cytokinin Cross Talk in Somatic Embryogenesis of Coffea canephora
Authors: Avilez-Montalvo Johny R. , Quintana-Escobar Ana O. , Méndez-Hernández Hugo A. , Aguilar-Hernández Víctor , Brito-Argáez Ligia , Galaz-Ávalos Rosa M. , Uc-Chuc Miguel A. , Loyola-Vargas Víctor M.
Published: August 2022

Cytokinins (CK) are plant growth regulators involved in multiple physiological processes in plants. One less studied aspect is CK homeostasis (HM). The primary genes related to HM are involved in biosynthesis (IPT), degradation (CKX), and signaling (ARR). This paper demonstrates the effect of auxin (Aux) and CK and their cross talk in a Coffea canephora embryogenic system. The transcriptome and RT-qPCR suggest that Aux in pre-treatment represses biosynthesis, degradation, and signal CK genes. However, in the induction, there is an increase of genes implicated in the CK perception/signal, indicating perhaps, as in other species, Aux is repressing CK, and CK are inducing per se genes involved in its HM. This is reflected in the endogenous concentration of CK; pharmacology experiments helped study the effect of each plant growth regulator in our SE system. We conclude that the Aux–CK balance is crucial to directing somatic embryogenesis in C. canephora.
Construction of Genetic Linkage Map and Mapping QTL Specific to Leaf Anthocyanin Colouration in Mapping Population ‘Allahabad Safeda’ × ‘Purple Guava (Local)’ of Guava (Psidium guajava L.)
Authors: Sohi Harjot Singh , Gill Manav Indra Singh , Chhuneja Parveen , Arora Naresh Kumar , Maan Sukhjinder Singh , Singh Jagmohan
Published: August 2022

In the present investigation, F1 hybrids were developed in guava (Psidium guajava L.) by crossing high leaf-anthocyanin reflective-index (ARI1) content cultivars purple guava (local) ‘PG’, ‘CISH G-1’ and low leaf-ARI1 content cultivar Seedless ‘SL’ with Allahabad Safeda ‘AS’. On the basis of phenotypic observations, high ARI1 content was observed in the cross ‘AS’ × ‘PG’ (0.214). Further, an SSR-markers-based genetic linkage map was developed from a mapping population of 238 F1 individuals derived from cross ‘AS’ × ‘PG’. The linkage map comprised 11 linkage groups (LGs), spanning 1601.7 cM with an average marker interval distance of 29.61 cM between adjacent markers. Five anthocyanin-content related gene-specific markers from apple were tested for parental polymorphism in the genotypes ‘AS’ and ‘PG’. Subsequently, a marker, viz., ‘MdMYB10F1′, revealed a strong association with leaf anthocyanin content in the guava mapping population. QTL (qARI-6-1) on LG6 explains much of the variation (PVE = 11.51% with LOD = 4.67) in levels of leaf anthocyanin colouration. This is the first report of amplification/utilization of apple anthocyanin-related genes in guava. The genotypic data generated from the genetic map can be further exploited in future for the enrichment of linkage maps and for identification of complex quantitative trait loci (QTLs) governing economically important fruit quality traits in guava.
Synthesis and Characterization of Polymeric Blends Containing Polysulfone Based on Cyclic Bisphenol
Authors: Gargol Mateusz , Podkościelna Beata
Published: August 2022

The elaboration of the composition and methods of preparation of new types of materials is an important issue from the plastics industry’s point of view. The paper presents the polysulfone synthesis based on 4,4′-cyclohexylidenebisphenol (bisphenol Z). This compound was used (in an amount of 5 or 10 wt.% sample) for the synthesis and characterization of new polymeric blends based on the two different acrylic resins (EB-150 and EB-600) and the active solvent N-vinyl-2-pyrrolidone (NVP). The weight ratio of the used resin to solvent was 1:2; 1:1 or 2:1. These new materials were obtained applying the photoinitiated free radical polymerization with 2,2-dimethoxy-2-phenyloacetophenone as a photoinitiator used in an amount of 1 wt.%. Six polymeric blends and six copolymers without polysulfone were cured by this method. By means of ATR/FT-IR (Attenuated Total Reflection–Fourier Transform Infrared) spectroscopy the chemical structure of the synthesized polysulfone was proved. The effect of the presence of the polysulfone presence on the thermal properties of the obtained blends was analyzed by means of thermogravimetry and differential thermogravimetry (TG/DTG), as well as differential scanning calorimetry (DSC). Moreover, the dynamic mechanical studies (DMA) of these materials were also carried out, demonstrating which of the materials showed the influence of the percentage of polysulfone on the selected properties in the blended- and parent-copolymers samples.
Thermal Degradation Process of Ethinylestradiol—Kinetic Study
Authors: Simu Sebastian , Ledeţi Adriana , Moacă Elena-Alina , Păcurariu Cornelia , Dehelean Cristina , Navolan Dan , Ledeţi Ionuţ
Published: August 2022

The present study reports the results obtained after the analysis of the thermal stability and decomposition kinetics of widely used synthetic derivative of estradiol, ethinylestradiol (EE), as a pure active pharmaceutical ingredient. As investigational tools, Fourier transformed infrared spectroscopy (FTIR), thermal analysis, and decomposition kinetics modeling of EE were employed. The kinetic study was realized using three kinetic methods, namely Kissinger, Friedman, and Flynn-Wall-Ozawa. The results of the kinetic study are in good agreement, suggesting that the main decomposition process of EE that takes place in the 175–375 °C temperature range is a single-step process, invariable during the modification of heating rate of the sample.
Parameter-Adaptive Event-Triggered Sliding Mode Control for a Mobile Robot
Authors: Tran Tri Duc , Nguyen Trong Trung , Duong Van Tu , Nguyen Huy Hung , Nguyen Tan Tien
Published: August 2022

Mobile robots have played a vital role in the transportation industries, service robotics, and autonomous vehicles over the past decades. The development of robust tracking controllers has made mobile robots a powerful tool that can replace humans in industrial work. However, most of the traditional controller updates are time-based and triggered at every predetermined time interval, which requires high communication bandwidth. Therefore, an event-triggered control scheme is essential to release the redundant data transmission. This paper presents a novel parameter-adaptive event-trigger sliding mode to control a two-wheeled mobile robot. The adaptive control scheme ensures that the mobile robot system can be controlled accurately without the knowledge of physical parameters. Meanwhile, the event trigger sliding approach guarantees the system robustness and reduces resource usage. A simulation in MATLAB and an experiment are carried out to validate the efficiency of the proposed controller.
Micro-Doppler Curves Extraction of Space Target Based on Modified Synchro-Reassigning Transform and Ridge Segment Linking
Authors: Yang Degui , Wang Xing , Li Jin , Peng Zhenghong
Published: August 2022

The micro-movement feature is recognized as one of the practical features of space target recognition in academic circles. The separation of the micro-Doppler curve of the scattering center is the key to feature extraction and parameter estimation, which depends on the time–frequency analysis method. The existing techniques have low separation accuracy and adaptability when there are overlap and noise in the time–frequency domain. This paper proposes a micro-Doppler feature extraction algorithm of a space target based on the modified synchro-reassigning transform (MSRT) and ridge segment linking. The MSRT can eliminate repeated assignment problems, has more accurate micro-Doppler frequency estimates than the synchro-reassigning transform, and has lower computational complexity than second-order synchronous compression and synchronous extraction transforms. The re-linking of the ridge realizes the correct connection of the micro-Doppler curves of each scattering center. The simulation data and the electromagnetic calculation data verify the method’s effectiveness.
A Novel Method to Simultaneously Measure Leaf Gas Exchange and Water Content
Authors: Junttila Samuli , Hölttä Teemu , Salmon Yann , Filella Iolanda , Peñuelas Josep
Published: August 2022

Understanding the relationship between plant water status and productivity and between plant water status and plant mortality is required to effectively quantify and predict the effects of drought on plants. Plant water status is closely linked to leaf water content that may be estimated using remote sensing technologies. Here, we used an inexpensive miniature hyperspectral spectrometer in the 1550–1950 nm wavelength domain to measure changes in silver birch (Betula pendula Roth) leaf water content combined with leaf gas exchange measurements at a sub-minute time resolution, under increasing vapor pressure deficit, CO2 concentrations, and light intensity within the measurement cuvette; we also developed a novel methodology for calibrating reflectance measurements to predict leaf water content for individual leaves. Based on reflectance at 1550 nm, linear regression modeling explained 98–99% of the variation in leaf water content, with a root mean square error of 0.31–0.43 g cm−2. The prediction accuracy of the model represents a c. ten-fold improvement compared to previous studies that have used destructive sampling measurements of several leaves. This novel methodology allows the study of interlinkages between leaf water content, transpiration, and assimilation at a high time resolution that will increase understanding of the movement of water within plants and between plants and the atmosphere.
Investigation of Potential of GNSS-R Polarization: Theoretical Simulations
Authors: Wu Xuerui , Du Xiaoyong , Yan Feng , Bai Weihua , Song Shaohui
Published: August 2022

Global navigation satellite system (GNSS) reflectometry (GNSS-R) developed into a promising remote sensing technique. However, few previous related studies considered the potential of its polarization. Owing to lack of sufficient in situ measurement data to support comprehensive investigation of GNSS-R polarization, this study used theoretical models and reference to our previous work to explore this topic. The commonly used microwave scattering models are employed to get the bare soil or vegetation scattering properties of GNSS-R configurations, i.e., the random surface scattering model and the first-order radiative transfer equation were improved and then employed to obtain the scattering properties of both bare soil and vegetation. Since the final output of the space-borne GNSS-R missions is a delay Doppler map (DDM), a spaceborne (DDM) simulator, oriented for the Chinese FengYun-3E (FY-3E) GNSS-R payload, was utilized to obtain the final output at different polarizations. Using the developed models (such as the bare soil and vegetation scattering models), corresponding polarization simulations were performed. That is to say, not only the commonly used LR (left hand circular polarizations (LHCP) received and the right hand circular polarizations (RHCP) received) can be presented, but also the scattering properties at RR, VR, and HR (the transmitted signals are RHCP, while the received polarizations are RHCP, vertical (V) and horizontal (H) polarizations, respectively) can be predicted by our developed models. Results reveal obvious polarization differences for the bistatic scattering and DDM. Therefore, the use of GNSS-R polarization information has potential to provide competitive and fruitful results in the future detection of land surface geophysical parameters.
Urban Waterfront Development, through the Lens of the Kyrenia Waterfront Case Study
Authors: Üzümcüoğlu Doğa , Polay Mukaddes
Published: August 2022

This study’s primary objective is to investigate the fundamentals of urban waterfront development. Consequently, the study created and validated two assessment scales (questionnaires). Using SPSS and AMOS, descriptive statistics assessed data gathered via questionnaires. Current approaches to urban development are starting to bring to the fore the rich historical and cultural heritage of Cyprus. Over the past few decades, Cyprus has encountered many political, sociocultural, economic, and technological challenges. These factors consequently influence urban design and produce distinct characteristics and tendencies. The waterfront of Kyrenia is a district that notably exemplifies progressive urban design. Specifically, this article aims to assess various urban aspects of Kyrenia’s waterfront. An ancient harbor in Kyrenia and its surroundings have served as the focus of the investigation to examine the evolution of general urban features across time. Participants included members of the creative class, employees and employer groups, students, and tourists. Physical, functional, social, economic, cultural, and political considerations underlie urban waterfronts. An evaluation of the Kyrenia waterfront revealed, based on the results of many statistical investigations, that the variables reflect varying degrees of user participation. According to the study findings, most people living in the community view the selected area favorably since it offers distinctive urban features and social opportunities. However, locals think that the region will need new technologies and ideas in the future to help the creative class be more productive by generating a creative economy.
Assessment of Public Flood Risk Perception and Influencing Factors: An Example of Jiaozuo City, China
Authors: Liu Delin , Li Mengjie , Li Yue , Chen Hao
Published: August 2022

There are many studies showing that public flood risk perception may promote people’s motivation to reduce flood risk and enhance their coping behavior, thus providing useful insights for flood risk management. The purpose of this article is to estimate residents’ flood risk perception in Jiaozuo City and to identify the influencing factors. A questionnaire survey method was used to collect data and a composite index was constructed to measure public risk perception. Each respondent’s grade of flood risk perception was calculated using the relationship between the standard deviation (SD) and the mean value (MV) of flood risk perception index (RPI) scores. Moreover, the hypotheses concerning different groups were tested using an independent sample T-test and one-way ANOVA (analysis of variance), and the group differences in flood risk perception on each observed dependent variable were explored using post hoc tests. The flood risk perception of the total respondents was divided into three levels based on the SD and MV of RPI scores: low (68.4%), moderate (13.7%), and high (17.9%). Respondents with low education, low income, less flood experiences, and who have married, lived in rural areas or near rivers/reservoirs had a higher flood risk perception than others, and respondents who lived in flood storage areas had a lower risk perception. Moreover, the ability to mitigate floods and the trust in flood-control projects were negatively related to the flood risk perception.