bluuebunny/crossref_metadata_2025 huggingface dataset:
Is the Slag Heap of a Former Ferrochromium Plant a Significant Environmental Hazard?
Authors: Wróbel Magdalena , Pieśniewska Angelika , Zeynalli Farhad , Kapelko Kacper , Hanus-Lorenz Beata , Rybak Justyna
Published: February 2023

This study assessed the possible impact of a former ferrochromium plant in Siechnice (Lower Silesia, Poland) on water reservoirs and living organisms. The metal concentrations (Zn, Cu, Pb, Fe, and Cr) in the sediments were determined, along with ecotoxicological studies that were conducted on both the sediments and the surface water of three water bodies that border the slag heap. The samples of the sediments and water were taken at different distances from the landfill area. The studies also covered a human health risk assessment. The highest concentrations of all the studied elements were observed in the sediments taken from the water reservoir closest to the landfill. In the case of the sediments, a 30% death rate for Heterocypris incongruens (Ostracodtoxkit F) was recorded at the same site. Additionally, at this site, the ecotoxicological studies on the surface water revealed the highest mortality for Daphnia magna (Daphtoxkit F magna) and the lowest values of LC50 for algae (Algaltoxkit). The health risk assessment of the sediments was estimated by calculating the noncarcinogenic health risk using the hazard quotient (HQ) and hazard index (HI), and the carcinogenic risk was calculated using the excessive risk of cancer development (ECR) measurement. The hazard index (HIing) for Cr exceeded 1 for children, which suggests that possible adverse health effects might occur for humans. The ECR values calculated for Cr and Pb were above the range limit of 10−6. The value for Cr was the highest for the sediments from the closest water reservoir to the landfill for both children and adults. Studies prove that the water reservoirs located near landfills pose potential ecological risks, and the risk is the highest where the distance is the shortest from the slag heap. In prospective human health risk assessments, the sediments from the closest water body pose a potential carcinogenic health risk to humans, especially to fish consumers, i.e., the residents of neighboring areas who might experience severe health problems from the intake of Cr and Pb through fish consumption. Significant steps should be taken to reduce Cr concentrations in the sediments to minimize the risk of human health adverse effects.
Dynamic Load Test and Contact Force Analysis of the AERORail Structure
Authors: Li Fangyuan , Guo Zhenwei , Cui Yunxuan , Wu Peifeng
Published: February 2023

The flexible structure of the new type of aerial track studied in this paper is formed by strings and tracks, which have obvious dynamic characteristics under the action of vehicle moving loads and is also an important factor affecting its performance. The paper uses the full-scale model of AERORail, based on the modal test under a specific span, combined with the fundamental frequency analysis of the structure, and carries out the dynamic load test to determine the change law of the contact force acting on the rail by the dynamic load. The time-domain improved algorithm based on the method of moments is used to identify and analyze the dynamic loads under different spans and vehicle speeds and to determine the correlation between the dispatched loads and the spans and vehicle speeds. It is proven that the occurrence time and frequency of the contact force are related to the passing time of the vehicle. The contact force fluctuates with the change in the vehicle speed, but with the increase in the span, the fluctuation of the contact force decreases obviously. The relevant conclusions provide support for the layout of the AERORail vehicle load. For this innovative structure, the relevant conclusions provide the basis for the application of this novel structure.
Evaluation of Artifacts and Misinterpretation in 2D Electrical Resistivity Tomography Caused by Three-Dimensional Resistive Structures of Regular or Irregular Shapes
Authors: Martorana Raffaele , Capizzi Patrizia
Published: February 2023

Electrical resistivity tomography (ERT) is a well-known geophysical method applied to geological, hydrogeological and geoenvironmental research. To date, 2D ERT is still used much more than 3D ERT, thanks to its greater immediacy, survey speed and lower complexity in processing and inversion. However, the assumption of two-dimensionality of the underground structures can mean that the effects of 3D structures on the 2D ERT can sometimes lead to gross errors in interpretation. This work aims to evaluate these effects by testing synthetic and experimental models. Numerical simulations are performed starting from different resistivity models, and from the results, 2D data sets are derived to study and quantify the effects of 2D inversion on 3D structures. Tests simulating prismatic resistive blocks with a vertical square section are presented. Prisms extend orthogonally to the survey line. Depending on their length, they range from a minimum equal to the length of the section (cubic resistive block) to infinity (2D prism). On these models, 2D and 3D electrical resistivity tomography (ERT) surveys are simulated. The results show that resistive blocks with a limited extension orthogonal to the profile are not effectively resolved by 2D ERT. Additionally, resistivity values obtained from a 2D ERT inversion on a 3D resistive prism are underestimated more than those obtained on the corresponding 2D prism when compared with the true value. This underestimation increases with the three-dimensional characteristics. Furthermore, resistive blocks located near the survey line but not crossed by it create artifacts that can lead to erroneous interpretations. A field test performed on a calcarenite quarry, of which the three-dimensional geophysical model was reconstructed, confirmed the results obtained by the synthetic tests, highlighting that the effects of three-dimensionality can lead to the identification of artifacts in the vertical section or produce strong errors in the estimation of depth and size, thus causing misleading statements.
Applicable Conditions of Room-and-Pillar Mining Goaf Treatment Methods under a Traffic Load
Authors: Zu Fajin , Du Chao , Han Chunpeng , Xu Lanyu , Peng Qiuying
Published: February 2023

The disturbance depth of traffic load has a direct impact on the stability of a room-and-pillar mining goaf. To quantitatively calculate the relationship between the traffic load disturbance depth and influencing factors, 49 groups of horizontal combinations of different influencing parameters are designed in this study, based on the orthogonal experimental design method. Midas GTS is used to simulate and obtain the corresponding traffic load disturbance depth data. A multivariate linear regression analysis of the traffic load disturbance depth is conducted, and a regression formula for calculating the traffic load disturbance depth is established. According to the traffic load disturbance depth, goaf depth, and the stability of the roof, coal pillar, and base plate under traffic load conditions, a judgment flow of the room-and-pillar mining goaf treatment method under traffic load conditions is established, and it is applied to the reconstruction and expansion project of the Jixi section of the Dan-A national highway. The results show that a geogrid can be used for treatment purposes when the traffic load disturbance depth is 1.5 times lower than the depth of the room-and-pillar mining goaf, or when the traffic load disturbance depth is 1.5 times greater than the depth of the room-and-pillar mining goaf but the roof, coal pillar, and base plate are stable. Additionally, grouting is needed for treatment in other cases. The results of this study can provide a scientific basis for the selection of treatment methods for room-and-pillar mining goafs underlying highways in the future. The results are of great significance in the field of engineering for the safety measures concerning highway room-and-pillar mining goafs.
Kinesthetic Learning Based on Fast Marching Square Method for Manipulation
Authors: Prados Adrián , Mora Alicia , López Blanca , Muñoz Javier , Garrido Santiago , Barber Ramón
Published: February 2023

The advancement of robotics in recent years has driven the growth of robotic applications for more complex tasks requiring manipulation capabilities. Recent works have focused on adapting learning methods to manipulation applications which are stochastic and may not converge. In this paper, a kinesthetic learning method based on fast marching square is presented. This method poses great advantages such as ensuring convergence and is based on learning from the experience of a human demonstrator. For this purpose, the demonstrator teaches paths by physically guiding one of the UR3 arms of a mobile manipulator. After this first phase, the fast marching Learning method is used to make the robot learn from this experience. As a novelty, an auto-learning functionality is presented, which provides the kinesthetic learning algorithm with an exploration capacity. The base of this algorithm is not only using the information provided by the taught trajectories, but also expanding its ability in order to explore unknown states of the environment. The effectiveness of the proposed method has been evaluated through simulations in 2D and 3D environments and in a real mobile manipulator. The learning process is analyzed with other 2D learning approaches using the LASA dataset and it is tested in complex 3D scenarios with different obstacles, proving its effectiveness.
Recycling of Macro-Synthetic Fiber-Reinforced Concrete and Properties of New Concretes with Recycled Aggregate and Recovered Fibers
Authors: Liu Guanzhi , Tošić Nikola , de la Fuente Albert
Published: February 2023

The study aims to investigate the feasibility of using recycled aggregate (RA) and recovered fibers (RFs) obtained from recycling polypropylene fiber-reinforced concrete (PPFRC) in new concrete production. The mechanical properties were compared between a parent PPFRC, polypropylene fiber-reinforced recycled aggregate concrete (PPRAC), and recovered polypropylene fiber concrete (Re-PPRFC). All concretes were designed to have the same compressive strength and slump. The parent concrete was produced with 3 and 9 kg/m3 of polypropylene fibers. After recycling, the RA and RF were collected, and new concretes with RA and RF, PPRAC and Re-PPRFC, respectively, were produced with the same fiber content as the parent concretes. Both the compressive and flexural tensile strength (pre- and post-cracking) were characterized and the stress–strain relations derived accordingly. The results obtained for the different concretes were compared, proving that the RA and RF obtained by PPFRC recycling can benefit the design-oriented properties (workability and mechanical performance) of new concretes.
An Historical Review of the Simplified Physical Fire Spread Model PhyFire: Model and Numerical Methods
Authors: Asensio María Isabel , Cascón José Manuel , Prieto-Herráez Diego , Ferragut Luis
Published: February 2023

A historical review is conducted of PhyFire, a simplified physical forest fire spread model developed by the research group on Numerical Simulation and Scientific Computation (SINUMCC) at the University of Salamanca. The review ranges from the first version of the model to the current one now integrated into GIS, considering all the mathematical problems and numerical methods involved throughout its development: finite differences, mixed, classical and adaptive finite elements, data assimilation, sensitivity analysis, parameter adjustment, and parallel computation, among others. The simulation of processes as complex as forest fires involves a multidisciplinary effort that is constantly being enhanced, while posing interesting challenges from a mathematical, numerical, and computational perspective, without losing sight of the overriding aim of developing an efficient, effective, and useful simulation tool.
Explainable AI for Machine Fault Diagnosis: Understanding Features’ Contribution in Machine Learning Models for Industrial Condition Monitoring
Authors: Brusa Eugenio , Cibrario Luca , Delprete Cristiana , Di Maggio Luigi Gianpio
Published: February 2023

Although the effectiveness of machine learning (ML) for machine diagnosis has been widely established, the interpretation of the diagnosis outcomes is still an open issue. Machine learning models behave as black boxes; therefore, the contribution given by each of the selected features to the diagnosis is not transparent to the user. This work is aimed at investigating the capabilities of the SHapley Additive exPlanation (SHAP) to identify the most important features for fault detection and classification in condition monitoring programs for rotating machinery. The authors analyse the case of medium-sized bearings of industrial interest. Namely, vibration data were collected for different health states from the test rig for industrial bearings available at the Mechanical Engineering Laboratory of Politecnico di Torino. The Support Vector Machine (SVM) and k-Nearest Neighbour (kNN) diagnosis models are explained by means of the SHAP. Accuracies higher than 98.5% are achieved for both the models using the SHAP as a criterion for feature selection. It is found that the skewness and the shape factor of the vibration signal have the greatest impact on the models’ outcomes.
Investigating and Compensating for Periphery-Center Effect among Commercial Near Infrared Imaging Systems Using an Indocyanine Green Phantom
Authors: Joosten Johanna J. , Bloemen Paul R. , van den Elzen Richard M. , Dalli Jeffrey , Cahill Ronan A. , van Berge Henegouwen Mark I. , Hompes Roel , de Bruin Daniel M.
Published: February 2023

Near infrared imaging (NIR) camera systems have been clinically deployed to visualize intravenous injected indocyanine green (ICG) spreading through the vascular bed, thereby creating the ability to assess tissue perfusion. While standardization is key to make fluorescence angiography (FA) comparable and reproducible, optical characteristics like field illumination homogeneity are often not considered. Therefore the aim of this study is to investigate light distribution and the center-periphery effect among five different NIR imaging devices in an indocyanine green phantom. A 13 × 13 cm fluorescence phantom was created by diluting ICG in Intralipid (representing 0.1 mg/kg dose in an 80 kg reference male), to evaluate the overall spatial collection efficiency with fluorescent modalities of five different NIR camera systems using a 0-degree laparoscope. The fluorescence signal from the phantom was quantified at a fixed distance of 16 cm using tailor-made software in Python. The results showed considerable variability in regard to light distribution among the five camera systems, especially toward the periphery of the field of view. In conclusion, NIR signal distribution varies between different systems and within the same displayed image. The fluorescence intensity diminishes peripherally away from the center of the field of view. These optical phenomena need to be considered when clinically interpreting the signal and in the development of computational fluorescence quantification.
Detection of Terahertz Frequencies in S-Doped GaSe Crystals Using Laser Pulses at Telecom Wavelengths
Authors: Shevchenko Olesya N. , Mikerin Sergey L. , Kokh Konstantin A. , Nikolaev Nazar A.
Published: February 2023

Nonlinear optical crystals of gallium selenide are efficient up- and downconverters of infrared and terahertz frequencies. Their nonlinear properties have been investigated at wavelengths within the main transparency window. However, insufficient attention has been paid to studies at the telecommunication wavelength, especially for sulfur-doped crystals. Closing this gap, we report on the optical and electro-optical properties of GaSe(1–x)Sx crystals (where x = 0, 0.03, 0.12, 0.16, and 0.22). For this purpose, the refractive indexes of the ordinary waves at terahertz frequencies and at a wavelength of 1.55 μm have been measured. The detection efficiency of the subterahertz waves in the crystals was studied using Er-fiber laser pulses and compared with that of GaAs, the etalon electro-optical crystal, at this wavelength. This allows us to estimate the dependence of the electro-optic coefficient r22 of GaSe(1–x)Sx on the sulfur concentration. It was shown that the sample with x = 0.12 has the largest value of the electro-optical coefficient r22 = 1.26 pm/V and provides the highest detection efficiency among the samples. The potential of employing S-doped GaSe crystals as nonlinear optical converters for photonic devices operating at telecom wavelengths is discussed.
Estimation of Interaction Locations in Super Cryogenic Dark Matter Search Detectors Using Genetic Programming-Symbolic Regression Method
Authors: Anđelić Nikola , Baressi Šegota Sandi , Glučina Matko , Car Zlatan
Published: February 2023

The Super Cryogenic Dark Matter Search (SuperCDMS) experiment is used to search for Weakly Interacting Massive Particles (WIMPs)—candidates for dark matter particles. In this experiment, the WIMPs interact with nuclei in the detector; however, there are many other interactions (background interactions). To separate background interactions from the signal, it is necessary to measure the interaction energy and to reconstruct the location of the interaction between WIMPs and the nuclei. In recent years, some research papers have been investigating the reconstruction of interaction locations using artificial intelligence (AI) methods. In this paper, a genetic programming-symbolic regression (GPSR), with randomly tuned hyperparameters cross-validated via a five-fold procedure, was applied to the SuperCDMS experiment to estimate the interaction locations with high accuracy. To measure the estimation accuracy of obtaining the SEs, the mean and standard deviation (σ) values of R2, the root-mean-squared error (RMSE), and finally, the mean absolute error (MAE) were used. The investigation showed that using GPSR, SEs can be obtained that estimatethe interaction locations with high accuracy. To improve the solution, the five best SEs were combined from the three best cases. The results demonstrated that a very high estimation accuracy can be achieved with the proposed methodology.
Automated Analysis of Open-Ended Students’ Feedback Using Sentiment, Emotion, and Cognition Classifications
Authors: Fargues Melanie , Kadry Seifedine , Lawal Isah A. , Yassine Sahar , Rauf Hafiz Tayyab
Published: February 2023

Students’ feedback is pertinent in measuring the quality of the educational process. For example, by applying lexicon-based sentiment analysis to students’ open-ended course feedback, we can detect not only their sentiment orientation (positive, negative, or neutral) but also their emotional valences, such as anger, anticipation, disgust, fear, joy, sadness, surprise, or trust. However, most currently used assessment tools cannot effectively measure emotional engagement, such as interest level, enjoyment, support, curiosity, and sense of belonging. Moreover, none of those tools utilize Bloom’s taxonomy for students’ learning-level assessment. In this work, we develop a user-friendly application based on NLP to help the teachers understand the students’ perception of their learning by analyzing their open-ended feedback. This allows us to examine the sentiment and the embedded emotions using a customized dictionary of emotions related to education. The application can also classify the students’ emotions according to Bloom’s taxonomy. We believe our application will help teachers improve their course delivery.
Estimation of Sedimentary Rock Porosity Using a Digital Image Analysis
Authors: Tang Qianhao , Gratchev Ivan
Published: February 2023

Pore space characterisation is important in assessing the strength and hydraulic characteristics of rock. This paper proposes a new relationship to estimate the porosity of natural rocks using the data from a scanning electron microscope (SEM) and a pore and crack analysis system (PCAS). The obtained results were compared with the data obtained from a series of conventional mercury intrusion porosimetry (MIP) experiments. Three different rocks, namely siltstone, sandstone, and coal, collected from a depth below 400 m, were investigated in this study. The results indicated that the proposed method of digital analysis could accurately identify the pore size and porosity values, which were in agreement with the experimental data. The relationship between the two-dimensional porosity estimated from the digital analysis and the three-dimensional porosity obtained from laboratory experiments was established. A few limitations on the use of the proposed method have also been identified and discussed.
Cloud Computing Considering Both Energy and Time Solved by Two-Objective Simplified Swarm Optimization
Authors: Yeh Wei-Chang , Zhu Wenbo , Yin Ying , Huang Chia-Ling
Published: February 2023

Cloud computing is an operation carried out via networks to provide resources and information to end users according to their demands. The job scheduling in cloud computing, which is distributed across numerous resources for large-scale calculation and resolves the value, accessibility, reliability, and capability of cloud computing, is important because of the high development of technology and the many layers of application. An extended and revised study was developed in our last work, titled “Multi Objective Scheduling in Cloud Computing Using Multi-Objective Simplified Swarm Optimization MOSSO” in IEEE CEC 2018. More new algorithms, testing, and comparisons have been implemented to solve the bi-objective time-constrained task scheduling problem in a more efficient manner. The job scheduling in cloud computing, with objectives including energy consumption and computing time, is solved by the newer algorithm developed in this study. The developed algorithm, named two-objective simplified swarm optimization (tSSO), revises and improves the errors in the previous MOSSO algorithm, which ignores the fact that the number of temporary nondominated solutions is not always only one in the multi-objective problem, and some temporary nondominated solutions may not be temporary nondominated solutions in the next generation based on simplified swarm optimization (SSO). The experimental results implemented show that the developed tSSO performs better than the best-known algorithms, including nondominated sorting genetic algorithm II (NSGA-II), multi-objective particle swarm optimization (MOPSO), and MOSSO in the convergence, diversity, number of obtained temporary nondominated solutions, and the number of obtained real nondominated solutions. The developed tSSO accomplishes the objective of this study, as proven by the experiments.
A Lightweight Transfer Learning Model with Pruned and Distilled YOLOv5s to Identify Arc Magnet Surface Defects
Authors: Huang Qinyuan , Zhou Ying , Yang Tian , Yang Kun , Cao Lijia , Xia Yan
Published: February 2023

Surface defects in arc magnets constitute the main culprit for performance degradation and safety hazards in permanent magnet motors. Machine-vision methods offer the possibility to identify surface defects automatically. However, the current methods still do not adequately solve the problems of low identification accuracy, excessive dependency on training data, and sizeable computational complexity. This paper proposes a lightweight YOLOv5s-based transfer learning model with network pruning and knowledge distillation to address these issues. Our model was derived from a pre-trained YOLOv5s for general object detection. A transfer learning mechanism was designed to obtain the optimal surface defect identification accuracy of the model from fewer training samples. Network pruning and knowledge distillation were combined to compress the transferred model. The transferred model serves as the teacher model of knowledge distillation, while its pruned model acts as the student model. To weaken the loss of the accuracy after model compression, a new λ factor was introduced into the confidence loss function of the student model to increase the sensitivity of identifying the defects. The experimental results show that our model’s performance is higher than other regular lightweight models. The identification accuracy for different defective arc magnets could reach 100%, the model size could achieve 1.921 MB, and the average inference time was 9.46 ms. Our model also has high accuracy in other defect identification applications besides arc magnets.
Achieving Zero-Impact Emissions with a Gasoline Passenger Car
Authors: Maurer Robert , Kossioris Theodoros , Sterlepper Stefan , Günther Marco , Pischinger Stefan
Published: February 2023

The Euro 7 legislation and the Zero-Impact Emissions concept aim at significantly improving air quality. Technologies that reduce pollutant emissions beyond current gasoline passenger cars have already been intensively investigated, but a holistic system layout considering extended boundary conditions is missing so far. This paper therefore develops technical solutions to achieve a Euro 7 scenario and Zero-Impact Emissions for a 2030+ vehicle. First, challenging test scenarios are identified to develop compliant vehicles. The scenarios cover extreme conditions in real-world driving, such as hot and cold ambient conditions, stop-and-go in rural areas or high speed and steep gradients on highways. Different technology options are discussed and selected for the investigations. An empirical–physical simulation model for the exhaust gas aftertreatment system is extended with new technologies, such as an electrical heater disc in front of the catalyst or a burner in the exhaust system. In addition to stoichiometric engine operation and increased catalyst volume, the results show that the expected Euro 7 regulations can be achieved in all extreme scenarios by combining additional exhaust gas heating with engine power limitation or pre-heating. Moreover, even Zero-Impact Emissions are achieved in most cases with the same technology options.
Impacts of a Prescribed Fire on Air Quality in Central New Mexico
Authors: Carrico Christian M. , Karacaoglu Jaimy
Published: February 2023

A short-duration but high-impact air quality event occurred on 28 November 2018 along the Rio Grande Valley of New Mexico. This fire occurred outside the typical wildfire season, and greatly impacted the air quality in Socorro, NM, and the surroundings. Measurements were taken during the event using an aerosol light scattering technique (integrating nephelometer) and a particulate mass concentration monitor (DustTrak PM optical monitor). The instruments sampled the ambient air during the event on the campus of the New Mexico Institute of Mining and Technology in Socorro, New Mexico. The peak values on a 5-min basis of light scattering and the PM mass concentration reached 470 Mm−1 and 270 µg/m3, respectively. We examined the meteorological context of the event using local meteorological data and back trajectories using the NOAA HYSPLIT model to determine atmospheric transport and possible sources. Several fires, both prescribed and wildfires, occurred in the region including a prescribed burn at Bosque del Apache National Wildlife Refuge (17 km south-southeast of the receptor site). The data suggest that the prescribed burn at Bosque del Apache was the dominant contributor due to transport evidence and the event’s narrow spatiotemporal extent. The increasing importance of restoring ecosystem function using prescribed fire in wildland fire management will likely lead to more frequent air quality impacts and sets up policy tradeoffs that require a balance between these public goals. This study examines the evidence of the effects of a prescribed fire in a protected wildland area impacting the air quality in a nearby populated area.
Analysis of PM2.5 Characteristics in Yancheng from 2017 to 2021 Based on Kolmogorov–Zurbenko Filter and PSCF Model
Authors: Dai Mingming , Liu Ankang , Sheng Ye , Xian Yue , Wang Honglei , Wang Chanjuan
Published: February 2023

Based on the hourly monitoring data including meteorological elements and PM2.5 mass concentration in Yancheng from 2017 to 2021, PM2.5 mass concentration variations, influencing factors and source apportionment were studied by the Kolmogorov–Zurbenko filter and Potential Source Contribution Function Analysis (PSCF) method. The results showed that the mass concentration of PM2.5 in Yancheng showed a decreasing trend from 2017 to 2021, with a decline rate of about 33.8% (2017, 44.79 ± 31.22 μg/m3; 2021, 29.66 ± 21.69 μg/m3); the visibility increased by 18.4% (2017, 11.69 ± 6.46 km; 2021,13.8 ± 6.24 km), which is mainly related to emission reduction measures in China. The mass concentration of PM2.5 has significant seasonal variation characteristics, with the highest in winter, reaching 60.61 μg/m3, and the lowest in summer, only 23.11 μg/m3. The diurnal variation of PM2.5 showed a unimodal distribution, and concentration difference is obvious under the influence of land–sea breeze (36.60 μg/m3, easterly wind; 43.57 μg/m3, westerly wind). Meteorological factors have an important impact on the mass concentration of PM2.5, which fluctuates with seasons. It is calculated to have a good fitting relationship between the visibility and PM2.5 concentration, and the correlation decreases with the increase in humidity (−0.71 ~ −0.41). The relatively clean atmosphere under high humidity conditions is also prone to the obstruction to vision. The corresponding PM2.5 concentration varies significantly under different wind directions and wind speeds in Yancheng, and high values mainly come from the northwest–southeast–southwest direction. The potential source regions in autumn are mainly distributed in southwestern Jiangsu and northwestern Zhejiang; the potential source regions in winter are mainly located in southwestern Jiangsu, southern Anhui and northern Jiangxi.
Volatile Organic Compounds in the North China Plain: Characteristics, Sources, and Effects on Ozone Formation
Authors: Yang Xue , Gao Luhong , Zhao Shiyang , Pan Guang , Fan Guolan , Xia Zhiyong , Sun Xiaoyan , Xu Hongyu , Chen Yanjun , Jin Xiaolong
Published: February 2023

Enhanced volatile organic compounds (VOCs) observations were made on ozone-exceeding days in June 2020 in Linyi, China. A total of 69 VOCs were collected (1 alkyne, 29 alkanes, 10 alkenes, 14 aromatic hydrocarbons, and 15 oxygenated volatile organic compounds (OVOCs)). The average concentration of total VOCs (TVOCs) was 36.0 ± 0.66 ppb, and the top three VOCs components were alkanes, OVOCs, and aromatic hydrocarbons, which accounted for 40.75%, 27.02%, and 11.30%, respectively. Based on the positive matrix factorization (PMF) model, the main sources of VOCs in Linyi City were divided into vehicle exhaust sources (39.11%), biomass combustion sources (21.82%), oil and gas volatilization sources (21.46%), and solvent use sources (17.61%). The ozone formation potential (OFP) contribution rate was dominated by alkenes, OVOCs, and aromatics, with contribution rates of 26.37%, 25.30%, and 23.65%, respectively. The top six VOCs that contributed the most to the OFP were formaldehyde, acetaldehyde, 1-butene, butadiene, trans-2-butene, and propylene. The empirical kinetic modelling approach (EKMA) curve indicated that the in situ ozone (O3) production was limited by VOCs, and reducing the concentration of O3 precursors in accordance with the VOCs/NOx concentration ratio of 1.15 can control O3 pollution more effectively.
Experimental and Theoretical Study of Photoionization of Cl III
Authors: Nahar Sultana , Hernández Edgar , Kilcoyne David , Antillón Armando , Covington Aaron , González-Magaña Olmo , Hernández Lorenzo , Davis Vernon , Calabrese Dominic , Morales-Mori Alejandro , Hanstorp Dag , Juárez Antonio , Hinojosa Guillermo
Published: February 2023

Photoionization of Cl III ions into Cl IV was studied theoretically using the ab initio relativistic Breit–Pauli R-matrix (BPRM) method and experimentally at the Advanced Light Source (ALS) synchrotron at the Lawrence Berkeley National Laboratory. A relative-ion-yield spectrum of Cl IV was measured with a photon energy resolution of 10 meV. The theoretical study was carried out using a large wave-function expansion of 45 levels of configurations 3s23p2, 3s3p3, 3s23p3d, 3s23p4s, 3s3p23d, and 3p4. The resulting spectra are complex. We have compared the observed spectrum with photoionization cross sections (σPI) of the ground state 3s23p3(4S3/2o) and the seven lowest excited levels 3s23p3(2D5/2o), 3s23p3(2D3/2o), 3s23p3(2P3/2o), 3s23p3(2P1/2o), 3s3p4(4P5/2), 3s3p4(4P3/2) and 3s3p4(4P1/2) of Cl III, as these can generate resonances within the energy range of the experiment. We were able to identify most of the resonances as belonging to various specific initial levels within the primary Cl III ion beam. Compared to the first five levels, resonant structures in the σPI of excited levels of 3s3p4 appear to have a weaker presence. We have also produced combined theoretical spectra of the levels by convolving the cross sections with a Gaussian profile of experimental width and summing them using statistical weight factors. The theoretical and experimental features show good agreement with the first five levels of Cl III. These features are also expected to elucidate the recent observed spectra of Cl III by Sloan Digital Scan Survey project.
Deep Laser Cooling of Thulium Atoms to Sub-µK Temperatures in Magneto-Optical Trap
Authors: Provorchenko Daniil , Tregubov Dmitry , Mishin Denis , Yaushev Mikhail , Kryuchkov Denis , Sorokin Vadim , Khabarova Ksenia , Golovizin Artem , Kolachevsky Nikolay
Published: February 2023

Deep laser cooling of atoms, ions, and molecules facilitates the study of fundamental physics as well as applied research. In this work, we report on the narrow-line laser cooling of thulium atoms at the wavelength of 506.2nm with the natural linewidth of 7.8kHz, which widens the limits of atomic cloud parameters control. Temperatures of about 400nK, phase-space density of up to 3.5×10−4 and 2×106 number of trapped atoms were achieved. We have also demonstrated formation of double cloud structure in an optical lattice by adjusting parameters of the 506.2nm magneto-optical trap. These results can be used to improve experiments with BEC, atomic interferometers, and optical clocks.
Method for Solving Difficulties in Rhythm Classification Caused by Few Samples and Similar Characteristics in Electrocardiograms
Authors: Lee Jaewon , Shin Miyoung
Published: February 2023

A method for accurately analyzing electrocardiograms (ECGs), which are obtained from electrical signals generated by cardiac activity, is essential in heart disease diagnosis. However, rhythms are typically obtained with relatively few data samples and similar characteristics, making them difficult to classify. To solve these issues, we proposed a novel method that distinguishes a given ECG rhythm using a beat score map (BSM) image. Through the proposed method, the associations between beats and previously used features, such as the R–R interval, were considered. Rhythm classification was implemented by training a convolutional neural network model and using transfer learning with the created BSM image. As a result, the proposed method for ECG rhythms with small data samples showed significant results. It also showed good performance in differentiating atrial fibrillation (AFIB) and atrial flutter (AFL) rhythms, which are difficult to distinguish due to their similar characteristics. The performance for rhythms with a small number of samples of the proposed method is 20% better than an existing method. In addition, the performance based on the F-1 score for classifying AFIB and AFL of the proposed method is 30% better than the existing method. This study solved the previous limitations caused by small sample numbers and similar rhythms.
Effects of Ventromedial Hypothalamic Nucleus (VMN) Aromatase Gene Knockdown on VMN Glycogen Metabolism and Glucoregulatory Neurotransmission
Authors: Briski Karen P. , Mahmood A. S. M. Hasan , Uddin Md. Main , Ibrahim Mostafa M. H. , Bheemanapally Khaggeswar
Published: February 2023

The enzyme aromatase is expressed at high levels in the ventromedial hypothalamic nucleus (VMN), a principal component of the brain gluco-regulatory network. Current research utilized selective gene knockdown tools to investigate the premise that VMN neuroestradiol controls glucostasis. Intra-VMN aromatase siRNA administration decreased baseline aromatase protein expression and tissue estradiol concentrations and either reversed or attenuated the hypoglycemic regulation of these profiles in a VMN segment-specific manner. Aromatase gene repression down-regulated protein biomarkers for gluco-stimulatory (nitric oxide; NO) and -inhibitory (gamma-aminobutyric acid; GABA) neurochemical transmitters. Insulin-induced hypoglycemia (IIH) up- or down-regulated neuronal nitric oxide synthase (nNOS) and glutamate decarboxylase65/67 (GAD), respectively, throughout the VMN. Interestingly, IIH caused divergent changes in tissue aromatase and estradiol levels in rostral (diminished) versus middle and caudal (elevated) VMN. Aromatase knockdown prevented hypoglycemic nNOS augmentation in VMN middle and caudal segments, but abolished the GAD inhibitory response to IIH throughout this nucleus. VMN nitrergic and GABAergic neurons monitor stimulus-specific glycogen breakdown. Here, glycogen synthase (GS) and phosphorylase brain- (GPbb; AMP-sensitive) and muscle- (GPmm; noradrenergic –responsive) type isoform responses to aromatase siRNA were evaluated. Aromatase repression reduced GPbb and GPmm content in euglycemic controls and prevented hypoglycemic regulation of GPmm but not GPbb expression while reversing glycogen accumulation. Aromatase siRNA elevated baseline glucagon and corticosterone secretion and abolished hypoglycemic hyperglucagonemia and hypercorticosteronemia. Outcomes document the involvement of VMN neuroestradiol signaling in brain control of glucose homeostasis. Aromatase regulation of VMN gluco-regulatory signaling of hypoglycemia-associated energy imbalance may entail, in part, control of GP variant-mediated glycogen disassembly.
Preliminary Findings of Elevated Inflammatory Plasma Cytokines in Children with Autism Who Have Co-Morbid Gastrointestinal Symptoms
Authors: Ashwood Paul
Published: February 2023

Autism spectrum disorder (AU) is present in approximately 2% of the population and is often associated with co-morbidities that can impact quality of life. One of the most common co-morbidities in autism is the presence of gastrointestinal (GI) symptoms consisting of irregular bowel habits such as constipation, diarrhea, or alternating bowel habit. Evidence of immune infiltration and immune activation has been shown in the ileum and colon of children with AU with GI symptoms. Moreover, immune dysfunction is a contributing factor in many GI diseases, and we hypothesize that it would be more apparent in children with AU that exhibit GI symptoms than those who do not present with GI symptoms. The aim of this preliminary study was to determine whether there are altered cytokine levels in plasma in children with AU with GI symptoms compared with children with AU without GI symptoms, typically developing (TD) children with GI symptoms and TD children without GI symptoms, from the same population-based cohort. Plasma cytokine levels were assessed by multiplex assays. No differences in plasma cytokines were observed in TD controls with or without GI symptoms; however, many innate (IL-1α, TNFα, GM-CSF, IFNα) and adaptive cytokines (IL-4, IL-13, IL-12p70) were increased in AU children with GI symptoms compared with children with AU with no GI symptoms. The mucosal relevant cytokine IL-15 was increased in AU with GI symptoms compared with all groups. In contrast, the regulatory cytokine IL-10, was reduced in AU with GI symptoms and may suggest an imbalance in pro-inflammatory/regulatory signals. These data suggest that children with AU and GI symptoms have an imbalance in their immune response that is evident in their circulating plasma cytokine levels. A finding that could point to potential therapeutic and/or monitoring strategies for GI issues in AU.
Energy Homeostasis-Associated (Enho) mRNA Expression and Energy Homeostasis in the Acute Stress Versus Chronic Unpredictable Mild Stress Rat Models
Authors: Abulmeaty Mahmoud M. A. , Almajwal Ali M. , Razak Suhail , Al-Ramadhan Fatimah R. , Wahid Reham M.
Published: February 2023

The energy homeostasis-associated (Enho) gene, the transcript for the Adropin peptide, is usually linked to energy homeostasis, adiposity, glycemia, and insulin resistance. Studies on Enho expression in stressful conditions are lacking. This work aimed to investigate Enho mRNA expression and energy homeostasis in acute stress (AS) versus chronic unpredictable mild stress (CUMS) rat models. A total of thirty male Wistar rats (180–220 g) were fed a balanced diet with free access to water. Rats were divided into three equal groups (n = 10): (a) the normal control (NC) group; (b) the AS group, where one episode of stress for 2 h was applied; and (c) the CUMS group, in which rats were exposed to a variable program of mild stressors for 4 weeks. Energy homeostasis was analyzed by the PhenoMaster system for the automatic measuring of food intake (FI), respiratory O2 volume (VO2), CO2 volume (VCO2), respiratory quotient (RQ), and total energy expenditure (TEE). Finally, liver, whole brain, and adipose (WAT) tissue samples were collected, total RNA was prepared, and RT-PCR analysis of the Enho gene was performed. The CUMS group showed higher VO2 consumption and VCO2 production, and a higher RQ than the AS group. Furthermore, the TEE and FI were higher in the CUMS group compared to the AS group. Enho gene expression in the liver, brain, and WAT was significantly higher in the CUMS group than in the AS and NC groups. We can conclude that in the chew-fed AS rats, hypophagia was evident, with a shift in the RQ toward fat utilization, with no changes in body weight despite the increase in Enho mRNA expression in all studied tissues. In the CUMS group, the marked rise in Enho mRNA expression may have contributed to weight loss despite increased FI and TEE.
The Role of COX-2 and PGE2 in the Regulation of Immunomodulation and Other Functions of Mesenchymal Stromal Cells
Authors: Kulesza Agnieszka , Paczek Leszek , Burdzinska Anna
Published: February 2023

The ability of MSCs to modulate the inflammatory environment is well recognized, but understanding the molecular mechanisms responsible for these properties is still far from complete. Prostaglandin E2 (PGE2), a product of the cyclooxygenase 2 (COX-2) pathway, is indicated as one of the key mediators in the immunomodulatory effect of MSCs. Due to the pleiotropic effect of this molecule, determining its role in particular intercellular interactions and aspects of cell functioning is very difficult. In this article, the authors attempt to summarize the previous observations regarding the role of PGE2 and COX-2 in the immunomodulatory properties and other vital functions of MSCs. So far, the most consistent results relate to the inhibitory effect of MSC-derived PGE2 on the early maturation of dendritic cells, suppressive effect on the proliferation of activated lymphocytes, and stimulatory effect on the differentiation of macrophages into M2 phenotype. Additionally, COX-2/PGE2 plays an important role in maintaining the basic life functions of MSCs, such as the ability to proliferate, migrate and differentiate, and it also positively affects the formation of niches that are conducive to both hematopoiesis and carcinogenesis.
Peptides That Block RAS-p21 Protein-Induced Cell Transformation
Authors: Pincus Matthew R. , Lin Bo , Patel Purvi , Gabutan Elmer , Zohar Nitzan , Bowne Wilbur B.
Published: February 2023

This is a review of approaches to the design of peptides and small molecules that selectively block the oncogenic RAS-p21 protein in ras-induced cancers. Single amino acid substitutions in this protein, at critical positions such as at Gly 12 and Gln 61, cause the protein to become oncogenic. These mutant proteins cause over 90 percent of pancreatic cancers, 40–50 percent of colon cancers and about one third of non-small cell cancers of the lung (NSCCL). RAS-p21 is a G-protein that becomes activated when it exchanges GDP for GTP. Several promising approaches have been developed that target mutant (oncogenic) RAS-p21 proteins in these different cancers. These approaches comprise: molecular simulations of mutant and wild-type proteins to identify effector domains, for which peptides can be made that selectively inhibit the oncogenic protein that include PNC-1 (ras residues 115–126), PNC-2 (ras residues 96–110) and PNC7 (ras residues 35–47); the use of contiguous RAS-p21 peptide sequences that can block ras signaling; cyclic peptides from large peptide libraries and small molecule libraries that can be identified in high throughput assays that can selectively stabilize inactive forms of RAS-p21; informatic approaches to discover peptides and small molecules that dock to specific domains of RAS-p21 that can block mitogenic signal transduction by oncogenic RAS-p21; and the use of cell-penetrating peptides (CPPs) that are attached to the variable domains of the anti-RAS-p21 inactivating monoclonal antibody, Y13 259, that selectively enters oncogenic RAS-p21-containing cancer cells, causing these cells to undergo apoptosis. Several new anti-oncogenic RAS-p21 agents, i.e., Amgen’s AMG510 and Mirati Therapeutics’ MRTX849, polycyclic aromatic compounds, have recently been FDA-approved and are already being used clinically to treat RAS-p21-induced NSCCL and colorectal carcinomas. These new drugs target the inactive form of RAS-p21 bound to GDP with G12C substitution at the critical Gly 12 residue by binding to a groove bordered by specific domains in this mutant protein into which these compounds insert, resulting in the stabilization of the inactive GDP-bound form of RAS-p21. Other peptides and small molecules have been discovered that block the G12D-RAS-p21 oncogenic protein. These agents can treat specific mutant protein-induced cancers and are excellent examples of personalized medicine. However, many oncogenic RAS-p21-induced tumors are caused by other mutations at positions 12, 13 and 61, requiring other, more general anti-oncogenic agents that are being provided using alternate methods.
Delineating Ultrafast Structural Dynamics of a Green-Red Fluorescent Protein for Calcium Sensing
Authors: Krueger Taylor D. , Tang Longteng , Fang Chong
Published: February 2023

Fluorescent proteins (FPs) are indispensable tools for noninvasive bioimaging and sensing. Measuring the free cellular calcium (Ca2+) concentrations in vivo with genetically encodable FPs can be a relatively direct measure of neuronal activity due to the complex signaling role of these ions. REX-GECO1 is a recently developed red-green emission and excitation ratiometric FP-based biosensor that achieves a high dynamic range due to differences in the chromophore response to light excitation with and without calcium ions. Using steady-state electronic measurements (UV/Visible absorption and emission), along with time-resolved spectroscopic techniques including femtosecond transient absorption (fs-TA) and femtosecond stimulated Raman spectroscopy (FSRS), the potential energy surfaces of these unique biosensors are unveiled with vivid details. The ground-state structural characterization of the Ca2+-free biosensor via FSRS reveals a more spacious protein pocket that allows the chromophore to efficiently twist and reach a dark state. In contrast, the more compressed cavity within the Ca2+-bound biosensor results in a more heterogeneous distribution of chromophore populations that results in multi-step excited state proton transfer (ESPT) pathways on the sub-140 fs, 600 fs, and 3 ps timescales. These results enable rational design strategies to enlarge the spectral separation between the protonated/deprotonated forms and the Stokes shift leading to a larger dynamic range and potentially higher fluorescence quantum yield, which should be broadly applicable to the calcium imaging and biosensor communities.