bluuebunny/crossref_metadata_2025 huggingface dataset:
An Assessment Scheme for Road Network Capacity under Demand Uncertainty
Authors: Ge Zhongzhi , Du Muqing , Zhou Jiankun , Jiang Xiaowei , Shan Xiaonian , Zhao Xing
Published: June 2023

Network capacity is a vital index with which to assess the operation of traffic networks. The majority of existing traffic network capacity models are formed as bi-level programming, which maximizes the traffic flows under equilibrium constraints and is extremely dependent on the current origin–destination (O–D) travel demand. However, an accurate O–D matrix is not easy to obtain in practice. This article aims to provide an assessment method for traffic network capacity under demand uncertainty. To consider the variation in real demand in traffic networks, the current travel demand is treated as unknown parameters that are defined inside a restricted set. Based on the hypothesis of different probability distributions, the road network capacity is calculated by repeated capacity loading experiments with a random sampling of uncertain parameters. To improve the efficiency of the repeated calculations of the traffic assignment model, a sensitivity-analysis-based (SAB) approximation method was developed to avoid the double calculation of the network capacity model for each random O–D matrix. The SAB method significantly improved the calculation efficiency while ensuring accuracy. Using simulation experiments, we researched the reliability of road network capacity and the probabilities of high congestion for each link under uncertain demand.
Surface Modification of Tea-Waste-Based Biochar Adsorbent: Synthesis, Characterization, and Batch Adsorption for the Removal of Zidovudine ARV Drug and Phenol
Authors: Mashoene Tumelo Nortica , Leudjo Taka Anny , Akpotu Samson O. , Lawal Isiaka A. , Klink Michael John
Published: June 2023

Domestic, agricultural, and industrial waste has been investigated as a substitute for activated carbon adsorbents. For instance, the transformation of tea waste to biochar can be utilized as a substitute for activated carbon adsorbents. In this study, tea waste-based biochar adsorbents (biochar, biochar/reduced graphene oxide (biochar/rGO), biochar/reduced graphene oxide/deep eutectic solvent-cetyltrimethylammonium bromide (biochar/rGO/DES-CTAB), and biochar/reduced graphene oxide/deep eutectic solvent-glycerol (biochar/rGO/DES-glycerol)) were synthesized by simple thermal treatment of tea waste and sucrose followed by modification with reduced graphene oxide and deep eutectic solvents. The obtained materials were characterized using a range of spectroscopy techniques, Fourier Transformed Infrared Spectroscopy (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopy–Energy-Dispersive X-ray Spectroscopy (SEM–EDS), Brunauer, Emmett, and Teller (BET) surface area analysis, and pH at point of zero charge (pH PZC). The obtained results showed that the principal material, i.e., biochar was modified, and FTIR results confirmed the presence of added functional groups. SEM images revealed surface structural changes, and BET showed a decrease in pore size from 10.16 nm to 6.87 nm. The synthesized materials were applied for the removal of ZDV and phenol from the aqueous medium. Batch adsorption studies were conducted to optimize operating parameters such as the adsorbent dose, solution pH, contact time, and initial concentration. Pseudo-first-order (PFO), Pseudo-second-order (PSO), and intraparticle diffusion (IPD) kinetic models were determined to investigate the mechanism of the adsorption process. The coefficient of correlation, R2, was used to determine the best fit of the kinetic models. The adsorption results showed that the DES-glycerol-modified adsorbent was more efficient in removing the pollutants ZDV and phenol than biochar, biochar/rGO, and biochar/rGO/DES-CTAB adsorbents. In addition, the results showed that an acidic medium of pH 2.00 and a contact time of 1 h 30 min and 30 min is sufficient for removing ZDV and phenol, respectively, from an aqueous medium.
The Thermal Analysis and Heat Dissipation Structure Optimization of a Propeller Driver System
Authors: Lai Ningchuan , Lv Ming , Pan Huachen
Published: June 2023

The thermal performance of the propeller driver system is very important for underwater vehicles. A new kind of cylindrical heat sink is designed for a certain propeller driver system. The performances of the heat sink are analyzed, mainly using numerical methods. The thermal influences of structure parameters, such as base thickness, fins length, and fin number, are studied for the heat sink with an orthogonal experimental method. The results show that all three parameters have positive impacts on the heat dissipation of the driver. Compared with the fin numbers and the fin length, the base thickness has a relatively small impact on the working temperature of the driver. Compared to the initial design, the maximum temperature of the propeller driver drops by 22.3% with the designed novel cylindrical heat sink in the studied cases.
Detecting Fine-Grained Emotions in Literature
Authors: Rei Luis , Mladenić Dunja
Published: June 2023

Emotion detection in text is a fundamental aspect of affective computing and is closely linked to natural language processing. Its applications span various domains, from interactive chatbots to marketing and customer service. This research specifically focuses on its significance in literature analysis and understanding. To facilitate this, we present a novel approach that involves creating a multi-label fine-grained emotion detection dataset, derived from literary sources. Our methodology employs a simple yet effective semi-supervised technique. We leverage textual entailment classification to perform emotion-specific weak-labeling, selecting examples with the highest and lowest scores from a large corpus. Utilizing these emotion-specific datasets, we train binary pseudo-labeling classifiers for each individual emotion. By applying this process to the selected examples, we construct a multi-label dataset. Using this dataset, we train models and evaluate their performance within a traditional supervised setting. Our model achieves an F1 score of 0.59 on our labeled gold set, showcasing its ability to effectively detect fine-grained emotions. Furthermore, we conduct evaluations of the model’s performance in zero- and few-shot transfer scenarios using benchmark datasets. Notably, our results indicate that the knowledge learned from our dataset exhibits transferability across diverse data domains, demonstrating its potential for broader applications beyond emotion detection in literature. Our contribution thus includes a multi-label fine-grained emotion detection dataset built from literature, the semi-supervised approach used to create it, as well as the models trained on it. This work provides a solid foundation for advancing emotion detection techniques and their utilization in various scenarios, especially within the cultural heritage analysis.
Digital Twin to Control and Monitor an Industrial Cyber-Physical Environment Supported by Augmented Reality
Authors: Caiza Gustavo , Sanz Ricardo
Published: June 2023

Increasing industrial development and digital transformations have given rise to a technology called Digital Twin (DT) that has the potential to break the barrier between physical and cyberspace. DT is a virtual and dynamic model enabled through a bidirectional data flow that creates high-reliability models with interconnection and fusion between the physical and digital systems for full integration. In smart manufacturing, this technology is increasingly used in research and industry. However, the studies conducted do not provide a definition or a single integrally connected model. To develop the Digital Twin shown in this research, the literature was reviewed to learn about the enabling technologies and architectures used at the industrial level. Then, a methodology was used to obtain the physical process information, create the digital environment, communicate the physical environment, apply simulation models in the digital environment, and parameterize the simulation environment with the physical process in real-time to obtain the digital twin supported with augmented reality. The system was implemented in the MPS-500 modular production station that has industrial sensors and actuators. The virtual environment was designed with Blender and Vuforia to create the augmented reality environment. In the proposed methodology, robust devices (field and control level) and low-cost embedded systems were used for the creation and communication of the virtual environment (monitoring and control); for the joint work of these technologies, they were carried out through the use of the following protocols: Open Platform Communications United Architecture (OPC UA), Ethernet, and machine to machine (M2M), with which a communication was achieved between the different levels of the automation pyramid. The results show that the proposed methodology for the implementation of the DT allows bidirectional communication between the physical and virtual environment and can also be visualized with the support of AR, thus providing its characteristics to the proposed DT. Digital Twin is an essential factor in creating virtual environments and improving applications between the real and digital world, establishing a bidirectional communication through the Ethernet protocol, with a communication time of approximately 100 ms. This technology interacts with the virtual environment and performs mappings, thus achieving timely and dynamic adjustment. This improves data management and production and incorporates process simulation and physical control in real-time, allowing to execute and trigger actions in the physical equipment simultaneously.
Experimental and Numerical Study on the Slug Characteristics and Flow-Induced Vibration of a Subsea Rigid M-Shaped Jumper
Authors: Li Wenhua , Li Jiahao , Yin Guang , Ong Muk Chen
Published: June 2023

The subsea jumper has become an essential part of subsea production systems as a gas–liquid mixing pipeline connecting the pipeline end manifold (PLEM) to the Christmas tree. During oil and gas transportation, as a common flow pattern, the alternating flow characteristics of the slug flow easily cause pipeline vibration, resulting in pipeline instability or fatigue damage. The present study investigates experimentally and numerically the slug flow characteristics in the subsea M-shaped jumper and its induced vibrations of the jumper. The flow pattern evolution and slug characteristics of the inner slug flow under different gas–liquid velocities are obtained: the slug frequency and slug velocity, as well as the pressure fluctuation and vibration characteristics caused by the slug flow. The results show that the pressure fluctuations in the front and rear parts of the M-type jumper are obviously different. With the increase in the air–water mixing, the two characteristics, the slug frequency, and the slug velocity also increase. The gas velocity has a greater influence on the slug frequency than the liquid velocity. The slug length decreases as the slug frequency increases. Furthermore, numerical simulations under various experimental conditions are carried out. The results show that the simulation results of the pressure data, the slug characteristics, and the induced vibration amplitude are in good agreement with the experimental data.
Generating Function Reallocation to Handle Contingencies in Human–Robot Teaming Missions: The Cases in Lunar Surface Transportation
Authors: Fu Yan , Guo Wen , Wang Haipeng , Xue Shuqi , Wang Chunhui
Published: June 2023

On lunar missions, efficient and safe transportation of human–robot systems is essential for the success of human exploration and scientific endeavors. Given the fact that transportation constructs bottlenecks for numerous typical lunar missions, it is appealing to investigate what function allocation strategies can generate optimal task implementation paths for robots with low-human workloads when the situation changes. Thus, this paper presents a novel approach to dynamic human–robot function allocation explicitly designed for team transportation in lunar missions. The proposed dynamic allocation framework aims to optimize human–robot collaboration by responding to existing and potential contingencies. First, a fitness concept model is designed to quantify the factors that motivate the functional adaptation of each agent in dynamic lunar mission scenarios. A hierarchical reinforcement learning (HRL) algorithm with two layers is then employed for decision-making and optimization of human–robot function allocation. Finally, the validity of the framework and algorithm proposed is validated by a series of human–robot function allocation experiments on a simulated environment that mimics lunar transportation scenarios, and is compared with the performance of other algorithms. In the future, path-planning algorithms can be incorporated into the proposed framework to improve the adaptability and efficiency of the human–robot function allocation in lunar missions.
Overview on Intrusion Detection Systems Design Exploiting Machine Learning for Networking Cybersecurity
Authors: Dini Pierpaolo , Elhanashi Abdussalam , Begni Andrea , Saponara Sergio , Zheng Qinghe , Gasmi Kaouther
Published: June 2023

The Intrusion Detection System (IDS) is an effective tool utilized in cybersecurity systems to detect and identify intrusion attacks. With the increasing volume of data generation, the possibility of various forms of intrusion attacks also increases. Feature selection is crucial and often necessary to enhance performance. The structure of the dataset can impact the efficiency of the machine learning model. Furthermore, data imbalance can pose a problem, but sampling approaches can help mitigate it. This research aims to explore machine learning (ML) approaches for IDS, specifically focusing on datasets, machine algorithms, and metrics. Three datasets were utilized in this study: KDD 99, UNSW-NB15, and CSE-CIC-IDS 2018. Various machine learning algorithms were chosen and examined to assess IDS performance. The primary objective was to provide a taxonomy for interconnected intrusion detection systems and supervised machine learning algorithms. The selection of datasets is crucial to ensure the suitability of the model construction for IDS usage. The evaluation was conducted for both binary and multi-class classification to ensure the consistency of the selected ML algorithms for the given dataset. The experimental results demonstrated accuracy rates of 100% for binary classification and 99.4In conclusion, it can be stated that supervised machine learning algorithms exhibit high and promising classification performance based on the study of three popular datasets.
DIVA Meets EEG: Model Validation Using Formant-Shift Reflex
Authors: Cuadros Jhosmary , Z-Rivera Lucía , Castro Christian , Whitaker Grace , Otero Mónica , Weinstein Alejandro , Martínez-Montes Eduardo , Prado Pavel , Zañartu Matías
Published: June 2023

The neurocomputational model ‘Directions into Velocities of Articulators’ (DIVA) was developed to account for various aspects of normal and disordered speech production and acquisition. The neural substrates of DIVA were established through functional magnetic resonance imaging (fMRI), providing physiological validation of the model. This study introduces DIVA_EEG an extension of DIVA that utilizes electroencephalography (EEG) to leverage the high temporal resolution and broad availability of EEG over fMRI. For the development of DIVA_EEG, EEG-like signals were derived from original equations describing the activity of the different DIVA maps. Synthetic EEG associated with the utterance of syllables was generated when both unperturbed and perturbed auditory feedback (first formant perturbations) were simulated. The cortical activation maps derived from synthetic EEG closely resembled those of the original DIVA model. To validate DIVA_EEG, the EEG of individuals with typical voices (N = 30) was acquired during an altered auditory feedback paradigm. The resulting empirical brain activity maps significantly overlapped with those predicted by DIVA_EEG. In conjunction with other recent model extensions, DIVA_EEG lays the foundations for constructing a complete neurocomputational framework to tackle vocal and speech disorders, which can guide model-driven personalized interventions.
Optoelectronic Materials, Devices, and Applications
Authors: Niu Pingjuan , Pei Li , Mei Yunhui , Bai Hua , Shi Jia
Published: June 2023

This Special Issue entitled “Optoelectronic Materials, Devices, and Applications” is devoted to gathering a broad array of research papers on the latest advances in the development of optoelectronic materials and devices of semiconductors, fiber optics, power electronics, microwaves, and terahertz [...]
Glycerol Flow through a Shielded Coil Induces Aggregation and Activity Enhancement of Horseradish Peroxidase
Authors: Ivanov Yuri D. , Shumov Ivan D. , Kozlov Andrey F. , Ershova Maria O. , Valueva Anastasia A. , Ivanova Irina A. , Tatur Vadim Y. , Lukyanitsa Andrei A. , Ivanova Nina D. , Ziborov Vadim S.
Published: June 2023

Glycerol has found its applications as a heat-transfer fluid in heat exchangers, and as a component of functional liquids in biosensor analysis. Flowing non-aqueous fluids are known to be able to induce electromagnetic fields due to the triboelectric effect. These triboelectrically generated electromagnetic fields can affect biological macromolecules. Horseradish peroxidase (HRP) is widely employed as a convenient model object for studying how external electric, magnetic, and electromagnetic fields affect enzymes. Herein, we have studied whether the flow of glycerol in a ground-shielded cylindrical coil affects the HRP enzyme incubated at a 2 cm distance near the coil’s side. Atomic force microscopy (AFM) has been employed in order to study the effect of glycerol flow on HRP at the nanoscale. An increased aggregation of HRP on mica has been observed after the incubation of the enzyme near the coil. Moreover, the enzymatic activity of HRP has also been affected. The results reported that their application can be found in biotechnology, food technology and life sciences applications, considering the development of triboelectric generators, enzyme-based biosensors and bioreactors with surface-immobilized enzymes. Our work can also be of interest for scientists studying triboelectric phenomena, representing one more step toward understanding the mechanism of the indirect action of the flow of a dielectric liquid on biological macromolecules.
The Use of a 3D Image Comparison Program for Dental Identification
Authors: Kubo Daijiro , Itamiya Tomoki , Kawanishi Norishige , Hoshi Noriyuki , Kimoto Katsuhiko
Published: June 2023

Dental identification involves compiling a prescribed dental chart of a deceased person’s oral findings which is then compared with antemortem dental information. However, this process is complicated, and a comparison can be difficult. In this study, the authors evaluated whether it is possible to identify images from antemortem dental information images using an image comparison program (AKAZE) with one-sided cross-sectional images generated from the STL (Standard Triangle Language) data of upper and lower jaw models acquired with an intraoral scanner. From the STL data of 20 patients, 120 cross-sectional images were generated by three practitioners and compared with the cross-sectional images of 20 patients generated later, and the degree of agreement calculated by AKAZE was analyzed. Statistically significant differences were found between images of the same and different models, and statistically significant differences were obtained when comparing one-sided images with limited information, suggesting that partial dentition information can be used to identify the same dentition.
Nonlinear Wave-Induced Uplift Force onto Pipelines Buried in Sloping Seabeds
Authors: Duan Lunliang , Zhan Bolin , Shen Linhong , Fan Meiling , Wang Duoyin
Published: June 2023

In this paper, a two-dimensional numerical model for wave-seabed-pipeline interaction is developed to examine the wave-induced uplift force onto pipelines buried in sloping seabeds. The Reynolds-averaged Navier stokes equation and the poro-elastic equation are used to simulate the wave motion and seabed response, respectively. Meanwhile, the pipeline is considered to be elastic. Firstly, three laboratory experiments are taken to verify the effectiveness of the numerical model. Then, the effects of pipeline characteristics, soil properties and wave parameters on the nonlinear wave-induced uplift force onto a pipeline buried in a sloping seabed are analyzed. Finally, an empirical formula for predicting the nonlinear wave-induced uplift force onto buried pipelines under different slope angles is proposed. It can be found that the slope angle can greatly affect the nonlinear wave-caused pore pressure response, as well as the uplift force onto the pipeline. Moreover, the simple method for predicting the uplift force proposed in this paper can facilitate engineering applications.
Muscle Function and Thickness Are Not Associated with Responsiveness to Post-Activation Performance Enhancement
Authors: Fontanetti Gabriel , Barreto Renan Vieira , Junior Rubens Correa , Mantovani Guilherme Beneduzzi , Denadai Benedito Sérgio , Greco Camila Coelho , Lima Leonardo Coelho Rabello de
Published: June 2023

There is great variability in responsiveness to post-activation performance enhancement (PAPE). Factors such as greater expression of type II muscle fibers and experience with strength training are associated with greater responsiveness to PAPE. We investigated whether there is an association between markers of muscular function and morphology and responsiveness to PAPE in untrained individuals. Sixty-six active men (22 ± 2 years, 74 ± 11 kg, and 172 ± 27 cm) participated in the study. Their countermovement jump (CMJ) heights were measured before and four minutes after a pre-activation protocol consisting of five squats with a 5RM load. Isometric knee extensor peak torque (IPT), CMJ power (POCON), and thickness of the vastus lateralis muscle (VLMT) of the participants were also determined in an unpotentiated condition. Change in CMJ height (ΔCMJ) following the pre-activation protocol was calculated and its associations with baseline CMJ height (CMJCON), POCON, IPT, and VLMT were tested. Linear stepwise multiple regression models were also applied to screen for predictors of ΔCMJ among the dependent variables. No significant change (p = 0.28) in CMJ height was observed after the PA protocol (pre: 30.8 ± 5.1 cm; post: 31.0 ± 5.5 cm). No significant associations (p > 0.05) were found between ΔCMJ and IPT, VLMT, POCON, and CMJCON (r = 0.29, 0.18, 0.09, and 0.01, respectively). Linear stepwise multiple regression analyses did not result in any significant models for ΔCMJ prediction. Although we confirmed the high individual variability in response to PA, no associations between neuromuscular performance/morphology and responsiveness to PAPE were found.
Modeling Human Encounter Situation Awareness Results Using Support Vector Machine Models
Authors: Song Jaeyoung , Shoji Ruri , Tamaru Hitoi , Kayano Jun
Published: June 2023

This study constructs a support vector machine model based on supervised learning to model the results of situation awareness for ship collision avoidance. To explain the model, collision risk situations were defined, and human situation recognition results were collected in the specified cases. Moreover, it was used to build predictors and outcome variables. Finally, the constructed variable was applied to the classification model. This model provides insight into the results of the navigator’s encounter situation awareness when collision avoidance is required. The results indicate that the proposed model can be used to predict human situation awareness outcomes in given cases.
Exploring Farmers’ Perceptions and Willingness to Tackle Drought-Related Issues in Small-Holder Cattle Production Systems: A Case of Rural Communities in the Eastern Cape, South Africa
Authors: Slayi Mhlangabezi , Zhou Leocadia , Jaja Ishmael Festus
Published: June 2023

This study explored the perceptions and willingness of farmers in vulnerable communities in the Eastern Cape, South Africa, to tackle drought-related issues in their communally preserved cattle herds. This research utilized a mixed-methods approach, combining qualitative and quantitative data from interviews and surveys with 250 farmers from 10 villages in the area. The findings indicate that farmers are aware of the impact of drought on their cattle herds and livelihoods but face several challenges in mitigating its effects. These challenges include limited access to water and grazing land, lack of infrastructure, and insufficient support from the government. Despite these challenges, farmers display high resilience and adaptability, using various strategies to cope with drought, such as destocking, shifting to alternative livelihoods, and seeking support from their social networks. Moreover, the study reveals that farmers are willing to collaborate with other stakeholders to address drought-related issues and are receptive to interventions that can enhance their adaptive capacity. The study concludes that addressing the root causes of drought-related issues requires a multi-stakeholder approach that engages farmers as key partners in designing and implementing sustainable solutions.
A GRASS GIS Scripting Framework for Monitoring Changes in the Ephemeral Salt Lakes of Chotts Melrhir and Merouane, Algeria
Authors: Lemenkova Polina
Published: June 2023

Automated classification of satellite images is a challenging task that enables the use of remote sensing data for environmental modeling of Earth’s landscapes. In this document, we implement a GRASS GIS-based framework for discriminating land cover types to identify changes in the endorheic basins of the ephemeral salt lakes Chott Melrhir and Chott Merouane, Algeria; we employ embedded algorithms for image processing. This study presents a dataset of the nine Landsat 8–9 OLI/TIRS satellite images obtained from the USGS for a 9-year period, from 2014 to 2022. The images were analyzed to detect changes in water levels in ephemeral lakes that experience temporal fluctuations; these lakes are dry most of the time and are fed with water during rainy periods. The unsupervised classification of images was performed using GRASS GIS algorithms through several modules: ‘i.cluster’ was used to generate image classes; ‘i.maxlik’ was used for classification using the maximal likelihood discriminant analysis, and auxiliary modules, such as ‘i.group’, ‘r.support’, ‘r.import’, etc., were used. This document includes technical descriptions of the scripts used for image processing with detailed comments on the functionalities of the GRASS GIS modules. The results include the identified variations in the ephemeral salt lakes within the Algerian part of the Sahara over a 9-year period (2014–2022), using a time series of Landsat OLI/TIRS multispectral images that were classified using GRASS GIS. The main strengths of the GRASS GIS framework are the high speed, accuracy, and effectiveness of the programming codes for image processing in environmental monitoring. The presented GitHub repository, which contains scripts used for the satellite image analysis, serves as a reference for the interpretation of remote sensing data for the environmental monitoring of arid and semi-arid areas of Africa.
Wind Simulations over Western Patagonia Using the Weather Research and Forecasting model and Reanalysis
Authors: Vásquez Anacona Hugo , Mattar Cristian , G. Alonso-de-Linaje Nicolás , Sepúlveda Héctor H. , Crisóstomo Jessica
Published: June 2023

The Chilean Western Patagonia has the highest wind potential resources in South America. Its complex terrain deserves a special attention for wind modeling and assessments. In this work, we have performed a comprehensive meso-scale climate simulation on Weather Research and Forecasting (WRF) in order to provide new insights into the wind climatology in Western Patagonia. Simulations were carried out from 1989 to 2020, and we considered a previous sensitivity analysis for their configuration. In situ data from a wind mast, meteorological information and data from eddy flux stations were used to evaluate the results. Reanalysis data from ERA-5, MERRA-2 and RECON80-17 were also used to perform a comparison of the obtained results with the WRF simulation. The results show that the WRF simulation using ERA-5 presented in this work is slightly different to a mathematical reconstruction using MERRA-2 (RECON80-17), which is widely accepted in Chile for wind resource assessments, presenting a statistical difference of about EMD = 0.8 [m s−1] and RMSE = 0.5. Non-significative differences were found between the WRF simulation and MERRA-2 reanalysis, while ERA-5 with MERRA-2 presented a remarkable statistical difference of about EMD = 1.64 [m s−1] and RMSE = 1.8. In relation to flux comparison, reanalysis and WRF in contrast with in situ observations presented a good performance during the summer season, although a spatial resolution bias was noticed. These results can be used as an input for further research related to WRF simulations in Western Patagonia to provide reliable information on wind energy exploration and extreme climatological phenomena such as heat waves.
Air Temperature Variability of the Northern Mountains in the Czech Republic
Authors: Dolák Lukáš , Řehoř Jan , Láska Kamil , Štěpánek Petr , Zahradníček Pavel
Published: June 2023

Analysis of a long-term temperature variability of mountains has been neglected for a long time. Here we homogenised and reconstructed four temperature series (1961–2020) of selected mountain stations situated above 1000 m representing the area of northern Moravian mountain ridges (the Czech Republic) and their spatiotemporal variability was examined. A statistically significant increase of 10-year linear trends of annual (0.26–0.38), summer/winter half-year and seasonal mean temperatures were found at most stations. Summer (JJA) was detected as the season with the highest mean temperature increase between 1961–1990 and 1991–2020 normal periods (1.5 °C). From the spatial point of view, the climate conditions were becoming warmer faster in higher elevations compared to the lower ones. At all stations, a statistically significant decrease in ice and frost days was observed (−9.1–19.9 and −9.5–16.3, respectively). Moreover, it was proved that the temperature series of a newly established Vysoká hole station are representative enough and comparable with measurements of other meteorological stations in the studied region. This research provided valuable insight into the temperature variability of mountain ridges and the results completed our sparse knowledge about temperature changes in the mountain regions in Central Europe.
Charged Atmospheric Aerosols from Charged Saltating Dust Aggregates
Authors: Onyeagusi F. Chioma , Meyer Christian , Teiser Jens , Becker Tim , Wurm Gerhard
Published: June 2023

Grain collisions in aeolian events, e.g., due to saltation, result in atmospheric aerosols. They may regularly be electrically charged, but individual charge balances in collisions including small grains are not easily obtained on the ground. We therefore approach this problem in terms of microgravity, which allows for the observation of collisions and the determination of small charges. In a drop tower experiment, ∼1 mm dust aggregates are traced before and after a collision within the electric field of a plate capacitor. The sum of the electric charge of two particles (total charge) before and after the collision often strongly deviates from charge conservation. Due to the average low collision velocities of 0.2 m/s, there is no large scale fragmentation. However, we do observe small charged particles emerging from collisions. The smallest of these particles are as small as the current resolution limit of the optical system, i.e., they are at least as small as tens of µm. In the given setting, these small fragments may carry 1 nC/m2–1 µC/m2 which is between 1% and ten times the surface charge density of the large aggregates. These first experiments indicate that collisions of charged aggregates regularly shed charged grains into the atmosphere, likely down to the suspendable aerosol size.
In Vitro Bioaccessibility and Health Risk of Heavy Metals from PM2.5/PM10 in Arid Areas—Hotan City, China
Authors: Liu Bowen , Zhang Yuanyu , Talifu Dilinuer , Ding Xiang , Wang Xinming , Abulizi Abulikemu , Zhao Qilong , Zhang Xiaohui , Zhang Runqi
Published: June 2023

The impact of heavy metals in particulates plays an assignable role in human health—especially in the northwest region of China, which is affected by severe dust storms—and the bioaccessibility and health risks of heavy metals in particulate matter have not yet been quantified and evaluated. This study used Gamble’s solution and PBET (physiologically based extraction test) experiments to simulate the human respiratory and digestive systems, and analyzed the concentrations and bioaccessibility of Pb, Mn, Ni, Cd and As in PM2.5 and PM10 samples in the urban area of Hotan City during summer (July) and winter (January). The result shows that Mn and Pb are the most abundant elements in five metals. The bioaccessibility of Mn in gastric fluid was the highest in both summer (PM2.5: 64.1%, PM10: 52.0%) and winter (PM2.5: 88.0%, PM10: 85.1%). Meanwhile, in the respiratory system, the highest bioaccessibility of PM2.5 and PM10 in summer was Ni (53.3%), and Pb (47.9%), respectively. Although the concentration of Cd is low in winter, its bioaccessibility in lung fluid was the highest (PM2.5: 74.7%, PM10: 62.3%). The USEPA standard model and Monte Carlo simulation results show that the heavy metals in PM2.5 and PM10 would give rise to non-carcinogenic risk for both adults and children through the respiratory system in summer but had little risk in winter. However, the metal may have non-carcinogenic risk to children through intake. In addition, there is a cancer risk to adults through the respiratory system in winter (PM2.5: CR = 1.80 × 10−6, PM10: CR = 2.82 × 10−6), while there is a carcinogenic risk through the digestive system regardless of season and age.
Preliminary Population Exposure to Indoor Radon and Thoron in Dhaka City, Bangladesh
Authors: Hasan Md. Mahamudul , Janik Miroslaw , Pervin Shikha , Iimoto Takeshi
Published: June 2023

Radon, an element of natural radiation, is considered one of the leading causes of lung cancer worldwide. In Bangladesh, radon has been clarified as a foremost source of radiation exposure. Potential natural-radiation-induced elevated cancer risks were estimated in Bangladesh previously for the population. In this survey, as a very preliminary study in the country, comparative indoor radon (222Rn, Rn) and thoron (220Rn, Tn) concentration/population exposure was determined for the multistoried dwellings of south-western areas of Dhaka city. RADUET was used to assess annual Rn and Tn concentrations in determining the primary inhalation dose for the population. The annual effective dose of Rn and Tn was evaluated in this study for dwellings at 0.3 mSvy−1, constituting a Tn dose contribution of an average of 40% with a dwelling-based wide range of 10–96%. Thus, Tn should not be neglected for Bangladesh while estimating radiological inhalation dose from the indoor environment. Again, the equilibrium factors, F of Rn and Tn, were determined by short-term measurement at averages of 0.6 and 0.02, respectively. Furthermore, using questionnaire estimation by principal component analysis, PCA following the dwelling characteristics, human lifestyles, and estimated long-term indoor Rn and Tn concentrations, this paper discussed indoor atmospheric/Rn factors for the investigated multistoried dwellings in Dhaka city.
Global Classical Solutions of the 1.5D Relativistic Vlasov–Maxwell–Chern–Simons System
Authors: Chen Jing , Bazighifan Omar , Luo Chengjun , Song Yanlai
Published: June 2023

We investigate the kinetic model of the relativistic Vlasov–Maxwell–Chern–Simons system, which originates from gauge theory. This system can be seen as an electromagnetic fields (i.e., Maxwell–Chern–Simons fields) perturbation for the classical Vlasov equation. By virtue of a nondecreasing function and an iteration method, the uniqueness and existence of the global solutions for the 1.5D case are obtained.
Fuzzy Hom–Lie Ideals of Hom–Lie Algebras
Authors: Shaqaqha Shadi
Published: June 2023

In the given study, we intended to gain familiarity with the idea of fuzzy Hom–Lie subalgebras (ideals) of Hom–Lie algebras. It primarily seeks to study a few of their properties. This research investigates the relationship between fuzzy Hom–Lie subalgebras (ideals) and Hom–Lie subalgebras (ideals). Additionally, this study constructs new fuzzy Hom–Lie subalgebras based on the direct sum of a finite number of existing ones. Finally, the properties of fuzzy Hom–Lie subalgebras and fuzzy Hom–Lie ideals are examined in the context of the morphisms of Hom–Lie algebras.
Combination Effects of Integrin-linked Kinase and Abelson Kinase Inhibition on Aberrant Mitosis and Cell Death in Glioblastoma Cells
Authors: Cunningham Abigail , Brown Maddisen , Dresselhuis Jonathan , Robinson Nicole , Hervie Keni , Cox Michael E. , Mills Julia
Published: June 2023

In cancer cells, inhibition of integrin-linked kinase (ILK) increases centrosome declustering causing mitotic arrest and cell death. Yet, not all cancer cells are susceptible to anti-ILK treatment alone. We investigate a combination drug strategy targeting ILK and another oncogenic kinase, Abelson kinase (ABL). Drug-concentration viability assays (i.e., MTT assays) indicate that ILK and ABL inhibitors in combination decreased the viability of glioblastoma cells over the ILK drug QLT-0267 alone. Combination strategies also increased aberrant mitoses and cell death over QLT-0267 alone. This was evident from an increase in mitotic arrest, apoptosis and a sub-G1 peak following FAC analysis. In vitro, ILK and ABL localized to the centrosome and the putative ILK kinase domain was important for this localization. Increased levels of cytosolic ABL are associated with its transformative abilities. ILK inhibitor effects on survival correlated with its ability to decrease cytosolic ABL levels and inhibit ABL’s localization to mitotic centrosomes in glioblastoma cells. ILK inhibitor effects on ABL’s centrosomal localization were reversed by the proteasomal inhibitor MG132 (a drug that inhibits ABL degradation). These results indicate that ILK regulates ABL at mitotic centrosomes and that combination treatments targeting ILK and ABL are more effective then QLT-0267 alone at decreasing the survival of dividing glioblastoma cells.
Winter Is (Not) Coming: Is Climate Change Helping Drosophila suzukii Overwintering?
Authors: Sario Sara , Melo-Ferreira José , Santos Conceição
Published: June 2023

Anthropogenic challenges, particularly climate change-associated factors, are strongly impacting the behavior, distribution, and survival of insects. Yet how these changes affect pests such as Drosophila suzukii, a cosmopolitan pest of soft-skinned small fruits, remains poorly understood. This polyphagous pest is chill-susceptible, with cold temperatures causing multiple stresses, including desiccation and starvation, also challenging the immune system. Since the invasion of Europe and the United States of America in 2009, it has been rapidly spreading to several European and American countries (both North and South American) and North African and Asian countries. However, globalization and global warming are allowing an altitudinal and latitudinal expansion of the species, and thus the colonization of colder regions. This review explores how D. suzukii adapts to survive during cold seasons. We focus on overwintering strategies of behavioral adaptations such as migration or sheltering, seasonal polyphenism, reproductive adaptations, as well as metabolic and transcriptomic changes in response to cold. Finally, we discuss how the continuation of climate change may promote the ability of this species to survive and spread, and what mitigation measures could be employed to overcome cold-adapted D. suzukii.
Endangered Forest Communities in Central Europe: Mapping Current and Potential Distributions of Euro-Siberian Steppic Woods with Quercus spp. in South Slovak Basin
Authors: Oravec Peter , Wittlinger Lukáš , Máliš František
Published: June 2023

In this article we focus on the issue of determining the presence and status of the priority habitat 91I0* Euro-Siberian steppic woods with Quercus spp. in the South Slovak basin. As part of the issue, we try to verify the correctness of the procedure of the State Nature Conservancy of the Slovak Republic in the search for potential habitats and areas of European importance by converting the typological map to a map of habitats. Habitat 91I0* occurs in Slovakia in the form of three subtypes, namely Thermophilous and supra-Mediterranean oak woods (Carpineto-Quercetum and Betuleto-Quercetum), Acidophilous oak forests (Quercetum), while the last-named subtype is divided into two subunits: Medio-European acidophilous oak forests—part A and Pannonic hairy greenweed sessile oak woods—part B. Due to the current unsatisfactory state of the mentioned habitats, the requirement of the State Nature Conservancy of the Slovak Republic is to find and add new areas with the occurrence of habitat 91I0* in the south of Central Slovakia. During the mapping in the Lučenecká and Rimavská basins, greater emphasis was placed on the occurrence of the subtype Thermophilic Pontic-Pannonian oak forests on loess and sand, but its presence has not been confirmed. Subsequently, we focused on the search and identification of habitats in the model area, which is the area of European importance SKUEV0957 Uderinky. The result is a map of habitats in this area, which we then compare with a typological map, which determines the reliability of the converter used by the State Nature Conservancy of the Slovak Republic.
Coffee-Associated Endophytes: Plant Growth Promotion and Crop Protection
Authors: Asad Suhail , Priyashantha Alviti Kankanamalage Hasith , Tibpromma Saowaluck , Luo Yinling , Zhang Jianqiang , Fan Zhuqing , Zhao Likun , Shen Ke , Niu Chen , Lu Li , Promputtha Itthayakorn , Karunarathna Samantha C.
Published: June 2023

Endophytic microbes are a ubiquitous group of plant-associated communities that colonize the intercellular or intracellular host tissues while providing numerous beneficial effects to the plants. All the plant species are thought to be associated with endophytes, majorly constituted with bacteria and fungi. During the last two decades, there has been a considerable movement toward the study of endophytes associated with coffee plants. In this review, the main consideration is given to address the coffee-associated endophytic bacteria and fungi, particularly their action on plant growth promotion and the biocontrol of pests. In addition, we sought to identify and analyze the gaps in the available research. Additionally, the potential of endophytes to improve the quality of coffee seeds is briefly discussed. Even though there are limited studies on the subject, the potentiality of coffee endophytes in plant growth promotion through enhancing nitrogen fixation, availability of minerals, nutrient absorption, secretion of phytohormones, and other bioactive metabolites has been well recognized. Further, the antagonistic effect against various coffee pathogenic bacteria, fungi, nematodes, and also insect pests leads to the protection of the crop. Furthermore, it is recognized that endophytes enhance the sensory characteristics of coffee as a new field of study.
Novel Peptides with Dual Properties for Treating Pseudomonas aeruginosa Keratitis: Antibacterial and Corneal Wound Healing
Authors: Cappiello Floriana , Verma Sudhir , Lin Xiao , Moreno Isabel Y. , Casciaro Bruno , Dutta Debarun , McDermott Alison M. , Willcox Mark , Coulson-Thomas Vivien J. , Mangoni Maria Luisa
Published: June 2023

The corneal epithelium is a layer in the anterior part of eye that contributes to light refraction onto the retina and to the ocular immune defense. Although an intact corneal epithelium is an excellent barrier against microbial pathogens and injuries, corneal abrasions can lead to devastating eye infections. Among them, Pseudomonas aeruginosa-associated keratitis often results in severe deterioration of the corneal tissue and even blindness. Hence, the discovery of new drugs able not only to eradicate ocular infections, which are often resistant to antibiotics, but also to elicit corneal wound repair is highly demanded. Recently, we demonstrated the potent antipseudomonal activity of two peptides, Esc(1-21) and its diastereomer Esc(1-21)-1c. In this study, by means of a mouse model of P. aeruginosa keratitis and an in vivo corneal debridement wound, we discovered the efficacy of these peptides, particularly Esc(1-21)-1c, to cure keratitis and to promote corneal wound healing. This latter property was also supported by in vitro cell scratch and ELISA assays. Overall, the current study highlights Esc peptides as novel ophthalmic agents for treating corneal infection and injury, being able to display a dual function, antimicrobial and wound healing, rarely identified in a single peptide at the same micromolar concentration range.
Combining 16S Sequencing and qPCR Quantification Reveals Staphylococcus aureus Driven Bacterial Overgrowth in the Skin of Severe Atopic Dermatitis Patients
Authors: De Tomassi Amedeo , Reiter Anna , Reiger Matthias , Rauer Luise , Rohayem Robin ,   CK-CARE Study Group, Traidl-Hoffmann Claudia , Neumann Avidan U. , Hülpüsch Claudia
Published: June 2023

Atopic dermatitis (AD) is an inflammatory skin disease with a microbiome dysbiosis towards a high relative abundance of Staphylococcus aureus. However, information is missing on the actual bacterial load on AD skin, which may affect the cell number driven release of pathogenic factors. Here, we combined the relative abundance results obtained by next-generation sequencing (NGS, 16S V1-V3) with bacterial quantification by targeted qPCR (total bacterial load = 16S, S. aureus = nuc gene). Skin swabs were sampled cross-sectionally (n = 135 AD patients; n = 20 healthy) and longitudinally (n = 6 AD patients; n = 6 healthy). NGS and qPCR yielded highly inter-correlated S. aureus relative abundances and S. aureus cell numbers. Additionally, intra-individual differences between body sides, skin status, and consecutive timepoints were also observed. Interestingly, a significantly higher total bacterial load, in addition to higher S. aureus relative abundance and cell numbers, was observed in AD patients in both lesional and non-lesional skin, as compared to healthy controls. Moreover, in the lesional skin of AD patients, higher S. aureus cell numbers significantly correlated with the higher total bacterial load. Furthermore, significantly more severe AD patients presented with higher S. aureus cell number and total bacterial load compared to patients with mild or moderate AD. Our results indicate that severe AD patients exhibit S. aureus driven increased bacterial skin colonization. Overall, bacterial quantification gives important insights in addition to microbiome composition by sequencing.