bluuebunny/crossref_metadata_2025 huggingface dataset:
Model Test on Grouting Properties of Alluvial Filler Soil
Authors: Wei Xingxing , Chen Guanghui
Published: September 2023

Due to the complexity and untraceability of the grouting process and the underpinning of the slurry diffusion law, the current study on the grouting properties of alluvial filler soil lags behind the engineering application. Therefore, grouting model tests, including a laboratory soil test and a dynamic penetration test, are developed in this study to investigate the diffusion law of slurry and strength characteristics in alluvial filler soil. Through the excavation of the grouting model, the diffusion pattern of the grouting slurry can be observed precisely. Then an approach proposed in this study for estimating the shear strength growth of the grouting soil is verified by the grouting model tests. In addition, to assess the grouting volume, an analytical model considering the shrinkage coefficient of the slurry is developed. The good agreement between the test data and analytical results shows that the proposed method can effectively estimate the increase in shear strength and grouting amount. The excavation results show that the slurry is generally first filled and fractured along the interface between rock and soil and mainly fractured horizontally, with widths between 0.3~6.0 cm. The curves for the diffusion radius versus the distance from the grouting hole show a wavelike relationship in all directions (i.e., horizontal, up, and down).
Dynamic Measuring Method of Laser Beam Incident Angle for Laser Doppler Vibrometer
Authors: Luo Yingchao , An Huazhen , Li Xiaobing , Jing Genqiang
Published: September 2023

Accurately measuring the incident angle of the laser Doppler vibrometer (LDV) laser beam is crucial for calculating the accurate dynamic response of a target. Nonetheless, conventional measuring methods may encounter limitations due to spatial constraints. To address this issue, a novel high-precision dynamic measuring method is proposed based on the measuring principle of LDV. Furthermore, a compact dynamic measuring device is constructed to facilitate this method. The proposed method involves the simulation of various tangential velocities utilizing a high precision rotating disk system. Subsequently, the laser beam incident angle is computed based on the projection relationship established between the average value of LDV measurements and the simulated velocities. To validate the feasibility of the dynamic measuring method and the correctness of the obtained incident angle, the paper compares this angle with that obtained through a conventional laser beam measuring method and device. This paper analyzes four key factors that may affect the angle measuring results theoretically and experimentally: environmental noise, laser spot position error, roll angle, and pitch angle of the rotating disk. The results indicate that the laser spot position error and the pitch angle of the rotating disk are more influential than the other two factors. Corresponding optimization measures are also proposed to improve the measuring accuracy.
WAID: A Large-Scale Dataset for Wildlife Detection with Drones
Authors: Mou Chao , Liu Tengfei , Zhu Chengcheng , Cui Xiaohui
Published: September 2023

Drones are widely used for wildlife monitoring. Deep learning algorithms are key to the success of monitoring wildlife with drones, although they face the problem of detecting small targets. To solve this problem, we have introduced the SE-YOLO model, which incorporates a channel self-attention mechanism into the advanced real-time object detection algorithm YOLOv7, enabling the model to perform effectively on small targets. However, there is another barrier; the lack of publicly available UAV wildlife aerial datasets hampers research on UAV wildlife monitoring algorithms. To fill this gap, we present a large-scale, multi-class, high-quality dataset called WAID (Wildlife Aerial Images from Drone), which contains 14,375 UAV aerial images from different environmental conditions, covering six wildlife species and multiple habitat types. We conducted a statistical analysis experiment, an algorithm detection comparison experiment, and a dataset generalization experiment. The statistical analysis experiment demonstrated the dataset characteristics both quantitatively and intuitively. The comparison and generalization experiments compared different types of advanced algorithms as well as the SE-YOLO method from the perspective of the practical application of UAVs for wildlife monitoring. The experimental results show that WAID is suitable for the study of wildlife monitoring algorithms for UAVs, and SE-YOLO is the most effective in this scenario, with a mAP of up to 0.983. This study brings new methods, data, and inspiration to the field of wildlife monitoring by UAVs.
Abnormality Detection of Blast Furnace Tuyere Based on Knowledge Distillation and a Vision Transformer
Authors: Song Chuanwang , Zhang Hao , Wang Yuanjun , Wang Yuhui , Hu Keyong
Published: September 2023

The blast furnace tuyere is a key position in hot metal production and is primarily observed to assess the internal state of the furnace. However, detecting abnormal tuyere conditions has relied heavily on manual judgment, leading to certain limitations. We proposed a tuyere abnormality detection model based on knowledge distillation and a vision transformer (ViT) to address this issue. In this approach, ResNet50 is employed as the Teacher model to distill knowledge into the Student model, ViT. Firstly, we introduced spatial attention modules to enhance the model’s perception and feature-extraction capabilities for different image regions. Furthermore, we simplified the depth of the ViT and improved its self-attention mechanism to alleviate training losses. In addition, we employed the knowledge distillation strategy to achieve model lightweighting and enhance the model’s generalization capability. Finally, we evaluate the model’s performance in tuyere abnormality detection and compare it with other classification methods such as VGG-19, ResNet-101, and ResNet-50. Experimental results showed that our model achieved a classification accuracy of 97.86% on a tuyere image dataset from a company, surpassing the original ViT model by 1.12% and the improved ViT model without knowledge distillation by 0.34%. Meanwhile, the model achieved a competitive classification accuracy of 90.31% and 77.65% on the classical fine-grained image datasets, Stanford Dogs and CUB-200-2011, respectively, comparable to other classification models.
Review on Wearable Technology in Sports: Concepts, Challenges and Opportunities
Authors: Seçkin Ahmet Çağdaş , Ateş Bahar , Seçkin Mine
Published: September 2023

Wearable technology is increasingly vital for improving sports performance through real-time data analysis and tracking. Both professional and amateur athletes rely on wearable sensors to enhance training efficiency and competition outcomes. However, further research is needed to fully understand and optimize their potential in sports. This comprehensive review explores the measurement and monitoring of athletic performance, injury prevention, rehabilitation, and overall performance optimization using body wearable sensors. By analyzing wearables’ structure, research articles across various sports, and commercial sensors, the review provides a thorough analysis of wearable sensors in sports. Its findings benefit athletes, coaches, healthcare professionals, conditioners, managers, and researchers, offering a detailed summary of wearable technology in sports. The review is expected to contribute to future advancements in wearable sensors and biometric data analysis, ultimately improving sports performance. Limitations such as privacy concerns, accuracy issues, and costs are acknowledged, stressing the need for legal regulations, ethical principles, and technical measures for safe and fair use. The importance of personalized devices and further research on athlete comfort and performance impact is emphasized. The emergence of wearable imaging devices holds promise for sports rehabilitation and performance monitoring, enabling enhanced athlete health, recovery, and performance in the sports industry.
Application of Hyperpure Chlorine Dioxide for Regenerative Endodontic Treatment of a Root-Canal-Treated Immature Tooth with External Cervical Resorption and Periapical Lesion: A Case Report
Authors: Polyák Melinda , Komora Péter , Szabó Enikő Vasziné , Lohinai Zsolt M. , Vág János
Published: September 2023

The consequences of traumatic injuries are pulp necrosis, periapical inflammation, and possible external cervical resorption (ECR). The concomitant cessation of root maturation and dentinogenesis in premature teeth result in a fragile tooth. Revascularization of the pulp might be an alternative treatment option. A 12-year-old patient was referred for retreatment of chronic apical periodontitis with acute exacerbation after root canal treatment of an upper central incisor. During gutta-percha removal, an ECR was detected. First, it was closed internally with Biodentine, followed by an external composite closure after a cone beam computed tomography evaluation. In the first session, chemomechanical cleaning was aided with sodium hypochlorite and hyperpure chlorine dioxide, and the canal was dressed with Ca(OH)2 until the next session. In the next session, only the low-toxicity, but adequate, bactericide hyperpure chlorine dioxide was applied for irrigation, before the provocation of periapical bleeding into the canal. The blood clots were covered with Biodentine, and the tooth was restored with composite filling. During the 24-month follow-up, clinical signs/symptoms had disappeared, and the periapical lesion was resolved. Increased root thickness in the apical third and decreased size of the apical foramen were detected. In conclusion, regenerative endodontic procedures could potentially be used to retreat immature teeth with persistent apical periodontitis and external cervical resorption.
Hybrid Intelligent Pattern Recognition Systems for Mass Segmentation and Classification: A Pilot Study on Full-Field Digital Mammograms
Authors: Dounis Anastasios , Avramopoulos Andreas-Nestor , Kallergi Maria
Published: September 2023

Governments and health authorities emphasize the importance of early detection of breast cancer, usually through mammography, to improve prognosis, increase therapeutic options and achieve optimum outcomes. Despite technological advances and the advent of full-field digital mammography (FFDM), diagnosis of breast abnormalities on mammographic images remains a challenge due to qualitative variations in different tissue types and densities. Highly accurate computer-aided diagnosis (CADx) systems could assist in the differentiation between normal and abnormal tissue and the classification of abnormal tissue as benign or malignant. In this paper, classical, advanced fuzzy sets and fusion techniques for image enhancement were combined with three different thresholding methods (Global, Otsu and type-2 fuzzy sets threshold) and three different classifying techniques (K-means, FCM and ANFIS) for the classification of breast masses on FFDM. The aim of this paper is to identify the performance of the advanced fuzzy sets, fuzzy sets type-2 segmentation, decisions based on K-means and FCM, and the ANFIS classifier. Sixty-three combinations were evaluated on ninety-seven digital mammographic masses (sixty-five benign and thirty-two malignant). The performance of the sixty-three combinations was evaluated by estimating the accuracy, the F1 score, and the area under the curve (AUC). LH-XWW enhancement method with Otsu thresholding and FCM classifier outperformed all other combinations with an accuracy of 95.17%, F1 score of 89.42% and AUC of 0.91. This algorithm seems to offer a promising CADx system for breast cancer diagnosis on FFDM.
Riders in the Tomb: Women Equestrians in North Chinese Funerary Art (10th–14th Centuries)
Authors: Shea Eiren L.
Published: September 2023

For many women living in parts of present-day north China and Mongolia during the 10th to 14th centuries, equestrian activities were a part of daily life. Women of all social levels were expected to know how to ride from an early age. However, documentary evidence for women’s participation in equestrian activities during this period is sparse. This paper brings together materials that highlight the important role horse riding played in the lives of northern women during the 10th to 14th centuries from the funerary context. This study connects funerary objects with women’s participation in polo, hunting, warfare, and the Mongol postal system, among other activities. The synthesis of material evidence from tombs with period texts will illuminate the important role of equestrian activities in women’s lives and afterlives during this period.
A Study on Avalanche-Triggering Factors and Activity Characteristics in Aerxiangou, West Tianshan Mountains, China
Authors: Liu Jie , Zhang Tianyi , Hu Changtao , Wang Bin , Yang Zhiwei , Sun Xiliang , Yao Senmu
Published: September 2023

Through analyzing the triggering factors and activity characteristics of avalanches in Aerxiangou in the Western Tianshan Mountains, the formation and disaster-causing process of avalanches were studied to provide theoretical support and a scientific basis for avalanche disaster prevention. In this paper, based on remote sensing interpretation and field investigation, a spatial distribution map of avalanches was established, and the induced and triggering factors in disaster-prone environments were analyzed using the certainty factor model. The degree of influence (E) of the disaster-causing factors on avalanche triggering was quantified, and the main control conditions conducive to avalanche occurrence in different periods were obtained. The RAMMS-avalanche model was used to analyze the activity characteristics at points where multiple avalanches occurred. Research results: (1) The E values of the average temperature, average snowfall, and surface roughness in February were significantly higher than those of other hazard-causing factors, reaching 1.83 and 1.71, respectively, indicating strong control. The E values of the surface cutting degree, average temperature, and average snow depth in March were all higher than 1.8, indicating that these control factors were more prominent than the other factors. In contrast, there were four hazard-causing factors with E values higher than 1.5 in April: the mean temperature, slope, surface roughness, and mean wind speed, with clear control. (2) Under the influence of the different hazard-causing factors, the types of avalanches from February–April mainly included new full-layer avalanches, surface avalanches, and full-layer wet avalanches. (3) In the RAMMS-avalanche simulation test, considering the deposition effect, compared to the previous avalanche movement path, the secondary avalanche flow accumulation area impact range changes were slight, while the movement area within the avalanche path changes was large, as were the different categories of avalanches and their different movement characteristic values. Overall, wet snow avalanches are more hazardous, and the impact force is larger. The new snow avalanches start in a short period, the sliding rate is fast, and the avalanche sliding surface (full-snow surface and face-snow) of the difference is mainly manifested in the differences in the value of the flow height.
Elevated Risk of Compound Extreme Precipitation Preceded by Extreme Heat Events in the Upper Midwestern United States
Authors: Khan Manas , Bhattarai Rabin , Chen Liang
Published: September 2023

Compound extreme events can potentially cause deadlier socio-economic consequences. Although several studies focused on individual extreme climate events, the occurrence of compound extreme events is still not well studied in the upper Midwestern United States. In this study, compound extreme precipitation preceded by extreme hot day events was investigated. Results showed a strong linkage between extreme precipitation events and extreme hot days. A significant increasing trend was noticed mainly in Iowa (10.1%), northern parts of Illinois (5.04%), and Michigan (5.04%). Results also showed a higher intensity of extreme precipitation events preceded by an extremely hot day compared to the intensity of extreme precipitation events not preceded by an extremely hot day, mostly in the central and lower parts of Minnesota, western and upper parts of Iowa, lower and upper parts of Illinois, parts of Ohio, Michigan, and Wisconsin for 1950–2010. In other words, extreme heat contributed to more extreme precipitation events. Our findings would provide important insights related to flood management under future climate change scenarios in the region.
Methods for Urban Air Pollution Measurement and Forecasting: Challenges, Opportunities, and Solutions
Authors: Mitreska Jovanovska Elena , Batz Victoria , Lameski Petre , Zdravevski Eftim , Herzog Michael A. , Trajkovik Vladimir
Published: September 2023

In today’s urban environments, accurately measuring and forecasting air pollution is crucial for combating the effects of pollution. Machine learning (ML) is now a go-to method for making detailed predictions about air pollution levels in cities. In this study, we dive into how air pollution in urban settings is measured and predicted. Using the PRISMA methodology, we chose relevant studies from well-known databases such as PubMed, Springer, IEEE, MDPI, and Elsevier. We then looked closely at these papers to see how they use ML algorithms, models, and statistical approaches to measure and predict common urban air pollutants. After a detailed review, we narrowed our selection to 30 papers that fit our research goals best. We share our findings through a thorough comparison of these papers, shedding light on the most frequently predicted air pollutants, the ML models chosen for these predictions, and which ones work best for determining city air quality. We also take a look at Skopje, North Macedonia’s capital, as an example of a city still working on its air pollution measuring and prediction systems. In conclusion, there are solid methods out there for air pollution measurement and prediction. Technological hurdles are no longer a major obstacle, meaning decision-makers have ready-to-use solutions to help tackle the issue of air pollution.
Validation and Selection of a Representative Subset from the Ensemble of EURO-CORDEX EUR11 Regional Climate Model Outputs for the Czech Republic
Authors: Meitner Jan , Štěpánek Petr , Skalák Petr , Dubrovský Martin , Lhotka Ondřej , Penčevová Radka , Zahradníček Pavel , Farda Aleš , Trnka Miroslav
Published: September 2023

To better understand the impact of climate change at a given location, it is crucial to consider a wide range of climate models that are representative of the area. In this study, we emphasize the importance of the careful validation and selection of climate models most suitable for a particular region. This step is critical to enhance the relevance of climate change impact studies and consequently design appropriate and robust adaptation measures, particularly in agriculture, forestry and water resources management. We propose validation and selection methods for regional climate models that can help identify a smaller group of well-performing models using the Central European area and Czech Republic as examples. In the validation process, 7 out of 19 regional climate models performed poorly. Of the 12 well-performing models, a subset of 7 models was selected to represent the uncertainty in the entire ensemble, which could be used in subsequent studies. The methodology is sufficiently general and may be applied to other climate model ensembles.
Dynamic and Thermodynamic Drivers of Severe Sub-Hourly Precipitation Events in Mainland Portugal
Authors: Cruz José , Belo-Pereira Margarida , Fonseca André , Santos João A.
Published: September 2023

Sub-hourly heavy precipitation events (SHHPs) associated with regional low-pressure (RegL) systems in Portugal are a natural hazard that may have significant socioeconomic implications, namely in agriculture. Therefore, in this paper, their dynamic and thermodynamic drivers are analysed. Three weather stations were used to isolate SHHPs from 2000 to 2022. Higher precipitation variability is found in southern Portugal, with a higher ratio of extreme events on fewer rainy days. This study shows that these SHHP events are associated with low-pressure systems located just to the west of the Iberian Peninsula. These systems exhibit a cold core, particularly strong at mid-levels, and a positive vorticity anomaly, which is stronger in the upper troposphere, extending downward to low levels. These conditions drive differential positive vorticity advection and, therefore, rising motion to the east of the low-pressure systems. Moreover, at low levels, these systems promote moisture advection over western Iberia, also generating instability conditions, which are assessed by instability indices (Convective available potential energy, the Total-Totals index, and the K-index). The combination of these conditions drives heavy precipitation events. Lastly, the total column cloud ice water revealed higher values for the heavier precipitation events, suggesting that it may be a useful predictor of such events.
Air Quality Mapping in Bandung City
Authors: Pontoh Resa Septiani , Saliaputri Leivina , Nashwa Audrey Nayla , Khairina Nadhira , Tantular Bertho , Toharudin Toni , Gumelar Farhat
Published: September 2023

One of the most commonly encountered issues in large cities is air pollution. As a major city, Bandung also experiences the same problem. This issue arises due to the increasing levels of human activity. This contributes to elevated levels of pollutants in the atmosphere, which can impact human life and ecosystems. This research is intended to map the regions in Bandung based on their air quality. This study used ambient air quality measurement results from Bandung, which included PM10, PM2.5, dust, SO2, CO, and NO2. This ambient air quality measurement was conducted by the Department of Environment and Hygiene in Bandung. The research methodology utilized in this study was multidimensional scaling analysis. The outcomes of the examination carried out utilizing the multidimensional scaling technique reveal a clustering of regions in Bandung, West Java, based on their air quality. According to the research findings, the locations were grouped into four quadrants, each with different air quality characteristics. Some locations showed high similarity, while others did not exhibit similarity with other groups. These findings can be used for policy-making and improving air quality in Bandung. Conclusions were drawn from the formed groups, where each group had high similarity among its members, but differed from the members of other groups. Among all observed locations in Bandung City, there were areas that were most similar when viewed based on the distance between objects, namely Punclut St. and KPAD Sarijadi; Soekarno Hatta St. (in front of Astra Bizz) and Elang St.; and Buah Batu St. (in front of STSI/ISBI) and Bunderan Cibiru.
Coastal Flooding Associated with Hurricane Irma in Central Cuba (Ciego de Ávila Province)
Authors: Matos-Pupo Felipe , Peros Matthew C. , González-De Zayas Roberto , Valero-Jorge Alexey , Pérez-López Osvaldo E. , Álvarez-Taboada Flor , Sorí Rogert
Published: September 2023

Irma was a major hurricane that developed during the 2017 season. It was a category 5 on the Saffir–Simpson Hurricane wind scale. This hurricane caused severe damage in the Caribbean area and the Florida Keys. The social, economic, and environmental impacts, mainly related to coastal flooding, were also significant in Cuba. The maximum limits of coastal flooding caused by this hurricane were determined in this research. Field trips and the use of the GPS supported our work, which focused on both the northern and southern coasts of the Ciego de Ávila province. This work has been critical for improving coastal flooding scenarios related to a strong hurricane, as it has been the first experience according to hurricane data since 1851. Results showed that the Punta Alegre and Júcaro towns were the most affected coastal towns. The locals had never seen similar flooding in these places before. The differences between flood areas associated with Hurricane Irma and previous modeled hazard scenarios were evident (the flooded areas associated with Hurricane Irma were smaller than those modeled for categories 1, 3, and 5 hurricanes). The effects of this hurricane on the most vulnerable coastal settlements, including the impacts on the archeological site “Los Buchillones”, were also assessed.
Long-Term Tropospheric Ozone Data Analysis 1997–2019 at Giordan Lighthouse, Gozo, Malta
Authors: Matasović Brunislav , Saliba Martin , Muscat Rebecca , Grima Marvic , Ellul Raymond
Published: September 2023

Long-term data analysis of the hourly ozone volume fractions in the middle of the Mediterranean Seawas carried out covering a period of 22 years. It was noticed that the amount of ozone during this period very rarely exceeded the recommended upper limit value of 80 ppb and that the amount of tropospheric ozone in the area is rather low. Fourier data analysis shows the presence of only a seasonal cycle in ozone concentrations. Statistical analysis of the data is showing a slightly negative trend in ozone concentrations of −0.46 ± 0.08 ppb/year for average values and a slightly higher negative trend of −0.54 ± 0.11 ppb/year for the 95th percentile values. These results obtained through simple linear regression were confirmed using the more appropriate Mann–Kendall test. The possible quadratic trend was not observed for the whole series of data. Air mass trajectories were calculated for those days in the year with the highest pollution, indicating that during those days horizontal air transfer, in most cases, brings the air mass from the North and from Sicily in Southern Italy.
Hydrological Drought Prediction Based on Hybrid Extreme Learning Machine: Wadi Mina Basin Case Study, Algeria
Authors: Achite Mohammed , Katipoğlu Okan Mert , Jehanzaib Muhammad , Elshaboury Nehal , Kartal Veysi , Ali Shoaib
Published: September 2023

Drought is one of the most severe climatic calamities, affecting many aspects of the environment and human existence. Effective planning and decision making in disaster-prone areas require accurate and reliable drought predictions globally. The selection of an effective forecasting model is still challenging due to the lack of information on model performance, even though data-driven models have been widely employed to anticipate droughts. Therefore, this study investigated the application of simple extreme learning machine (ELM) and wavelet-based ELM (W-ELM) algorithms in drought forecasting. Standardized runoff index was used to model hydrological drought at different timescales (1-, 3-, 6-, 9-, and 12-month) at five Wadi Mina Basin (Algeria) hydrological stations. A partial autocorrelation function was adopted to select lagged input combinations for drought prediction. The results suggested that both algorithms predict hydrological drought well. Still, the performance of W-ELM remained superior at most of the hydrological stations with an average coefficient of determination = 0.74, root mean square error = 0.36, and mean absolute error = 0.43. It was also observed that the performance of the models in predicting drought at the 12-month timescale was higher than at the 1-month timescale. The proposed hybrid approach combined ELM’s fast-learning ability and discrete wavelet transform’s ability to decompose into different frequency bands, producing promising outputs in hydrological droughts. The findings indicated that the W-ELM model can be used for reliable drought predictions in Algeria.
A Case Study of Drought during Summer 2022: A Large-Scale Analyzed Comparison of Dry and Moist Summers in the Midwest USA
Authors: Weaver Sarah M. , Guinan Patrick E. , Semenova Inna G. , Aloysius Noel , Lupo Anthony R. , Hunt Sherry
Published: September 2023

The summer of 2022 was very dry across Missouri and the surrounding regions including much of the Great Lakes, Midwest, and southern plains of the USA. A comparison of this summer to the dry summer of 2012 and the relatively wet summers of 2018 and 2021 was carried out using the National Centers for Environmental Prediction/National Centers for Atmospheric Research reanalysis, the Climate Prediction Center teleconnection indexes, and the blocking archive at the University of Missouri. The summer of 2022 was like that of 2012 which was characterized by a strong 500 hPa height anomaly centered over the western US and plains as well as very little blocking in the East Pacific. The summers of 2018 and 2021 were characterized by more zonal flow over the USA and more blocking in the East Pacific, similarly to the results of an earlier study. The teleconnection indexes for the prior spring and summer were largely similar for the two drier years and opposite for the wetter years. The surface conditions for the drier years were more similar while these were opposite for the wetter years. The integrated enstrophy (IE) used in earlier studies identified a change in the large-scale flow regime in early June 2022, which coincided with a decrease in the precipitation over the study region. However, one key difference was that the spring of 2022 was characterized by blocking more consistent with a wetter summer. This would have made the predictability of the drought of summer 2022 less certain.
Electronic Structure, Spectroscopy, Cold Ion–Atom Elastic Collision Properties, and Photoassociation Formation Prediction of the (MgCs)+ Molecular Ion
Authors: Farjallah Mohamed , Sardar Dibyendu , Deb Bimalendu , Berriche Hamid
Published: September 2023

In this paper, we extensively study the electronic structure, interactions, and dynamics of the (MgCs)+ molecular ion. The exchanges between the alkaline atom and the low-energy cationic alkaline earths, which are important in the field of cold and ultracold quantum chemistry, are studied. We use an ab initio approach based on the formalism of non-empirical pseudo-potential for Mg2+ and Cs+ cores, large Gaussian basis sets, and full-valence configuration interaction. In this context, the (MgCs)+ cation is treated as an effective two-electron system. Adiabatic potential energy curves and their spectroscopic constants for the ground and the first 20 excited states of 1,3Σ+ symmetries are determined. Furthermore, we identify the avoided crossings between the electronic states of 1,3Σ+ symmetries. These crossings are related to the charge transfer process between the two ionic limits, Mg/Cs+ and Mg+/Cs. Therefore, vibrational-level spacings and the transition and permanent dipole moments are presented and analyzed. Using the produced potential energy data, the ground-state scattering wave functions and elastic cross-sections are calculated for a wide range of energies. In addition, we predict the formation of a translationally and rotationally cold molecular ion (MgCs)+ in the ground-state electronic potential energy through a stimulated Raman-type process aided by ion–atom cold collision. In the low-energy limit (<1 mK), elastic scattering cross-sections exhibit Wigner law threshold behavior, while in the high-energy limit, the cross-sections act as a function of energy E go as E−1/3. A qualitative discussion about the possibilities of forming cold (MgCs)+ molecular ions by photoassociative spectroscopy is presented.
Ionization of Hydrogen Atom by Proton Impact—How Accurate Is the Ionization Cross Section?
Authors: Tőkési Károly , Alassaf Saleh
Published: September 2023

For the control of fusion reactors, we need to accurately know all the possible reactions and collisional cross sections. Although large-scale trials have been performed over the last decades to obtain this data, many basic atomic and molecular cross section data are missing and the accuracy of the available cross sections need to be checked. Using the available measured cross sections and theoretical predictions of hydrogen atom ionization by proton impact, critical analysis of the data is presented. Moreover, we also present our recent classical results based on the standard classical trajectory Monte Carlo (CTMC) and quasi-classical trajectory Monte Carlo (C-QCTMC) models. According to our model calculations and comparison with the experimental data, recom-mended cross sections for ionization of hydrogen were presented in a wide range of pro-jectile impact energies. We found that, while in the low energy region, the experimental cross sections are very close to the C-QCTMC results, at higher energies, they are close to the results of our standard CTMC results.
Self-FI: Self-Supervised Learning for Disease Diagnosis in Fundus Images
Authors: Nguyen Toan Duc , Le Duc-Tai , Bum Junghyun , Kim Seongho , Song Su Jeong , Choo Hyunseung
Published: September 2023

Self-supervised learning has been successful in computer vision, and its application to medical imaging has shown great promise. This study proposes a novel self-supervised learning method for medical image classification, specifically targeting ultra-wide-field fundus images (UFI). The proposed method utilizes contrastive learning to pre-train a deep learning model and then fine-tune it with a small set of labeled images. This approach reduces the reliance on labeled data, which is often limited and costly to obtain, and has the potential to improve disease detection in UFI. This method employs two contrastive learning techniques, namely bi-lateral contrastive learning and multi-modality pre-training, to form positive pairs using the data correlation. Bi-lateral learning fuses multiple views of the same patient’s images, and multi-modality pre-training leverages the complementary information between UFI and conventional fundus images (CFI) to form positive pairs. The results show that the proposed contrastive learning method achieves state-of-the-art performance with an area under the receiver operating characteristic curve (AUC) score of 86.96, outperforming other approaches. The findings suggest that self-supervised learning is a promising direction for medical image analysis, with potential applications in various clinical settings.
A New Chengjiang Worm Sheds Light on the Radiation and Disparity in Early Priapulida
Authors: Wang Deng , Vannier Jean , Sun Jie , Yu Chiyang , Han Jian
Published: September 2023

The vast majority of early Paleozoic ecdysozoan worms are often resolved as stem-group Priapulida based on resemblances with the rare modern representatives of the group, such as the structure of the introvert and the number and distribution of scalids (a spiny cuticular outgrowth) and pharyngeal teeth. In Priapulida, both scalids and teeth create symmetry patterns, and three major diagnostic features are generally used to define the group: 25 longitudinal rows of scalids (five-fold symmetry), 8 scalids around the first introvert circle and the pentagonal arrangement of pharyngeal teeth. Here we describe Ercaivermis sparios gen. et sp. nov., a new priapulid from the early Cambrian Chengjiang Lagerstätte, characterized by an annulated trunk lacking a sclerotized ornament, four pairs of anal hooks and 16 longitudinal rows of scalids along its introvert and eight scalids around each introvert circle, giving the animal an unusual octoradial symmetry. Cladistic analyses resolve Ercaivermis as a stem-group priapulid. Ercaivermis also suggests that several biradial symmetry patterns (e.g., pentagonal, octagonal) expressed in the cuticular ornament, may have co-existed among early Cambrian priapulids and that the pentaradial mode may have become rapidly dominant during the course of evolution, possibly via the standardization of patterning, i.e., the natural selection of one symmetry type over others.
A549 as an In Vitro Model to Evaluate the Impact of Microplastics in the Air
Authors: Shahzadi Chman , Di Serafino Alessandra , Aruffo Eleonora , Mascitelli Alessandra , Di Carlo Piero
Published: September 2023

Airborne microplastics raise significant concerns due to their potential health impacts. Having a small size, larger surface area, and penetrative ability into the biological system, makes them hazardous to health. This review article compiles various studies investigating the mechanism of action of polystyrene micro- and nanoplastics affecting lung epithelial cells A549. These inhalable microplastics damage the respiratory system, by triggering a proinflammatory environment, genotoxicity, oxidative stress, morphological changes, and cytotoxic accumulation in A549 cells. PS-NP lung toxicity depends on various factors such as size, surface modifications, concentration, charge, and zeta potential. However, cellular uptake and cytotoxicity mechanisms depend on the cell type. For A549 cells, PS-NPs are responsible for energy imbalance by mitochondrial dysfunction, oxidative stress-mediated cytotoxicity, immunomodulation, and apoptosis. Additionally, PS-NPs have the ability to traverse the placental barrier, posing a risk to offspring. Despite the advancements, the precise mechanisms underlying how prolonged exposure to PS-NPs leads to the development and progression of lung diseases have unclear points, necessitating further investigations to unravel the root cause. This review also sheds light on data gaps, inconsistencies in PS-Nos research, and provides recommendations for further research in this field.
Molecular Diet Analysis of Asian Clams for Supplementary Biodiversity Monitoring: A Case Study of Nakdong River Estuary
Authors: Kim Kanghui , Joo Gea-Jae , Jeong Kwang-Seuk , Gim Jeong-Soo , Lee Yerim , Hong Donghyun , Jo Hyunbin
Published: September 2023

Environmental DNA (eDNA) extracted from the gut contents of filter feeders can be used to identify biodiversity in aquatic ecosystems. In this study, we used eDNA from the gut contents of the Asian clam Corbicula fluminea to examine biodiversity within estuarine ecosystem. Field sampling was conducted at three points in the Nakdong River Estuary, which is characterised by closed estuarine features resulting from the presence of an estuarine barrage. The collected C. fluminea samples were dissected to separate the gut contents, and the extracted eDNA was amplified using 18S V9 primer targeting all eukaryote-derived DNA. The amplified DNA was sequenced using a next-generation sequencing (NGS) technique, and a BLASTn search was performed based on the National Centre for Biotechnology Information (NCBI) database for taxa identification. We obtained 23 unique operational taxonomic units (OTUs), including fish (approximately 8.70%), copepods (approximately 17.39%), and green algae (approximately 21.74%), representing a wide range of habitats. Furthermore, 8 out of the 20 families were identified through comparisons with reference data from conventional field surveys, and the OTUs of elusive migratory fish were detected. The results support the application of C. fluminea as an eDNA sampler for supplementary biodiversity monitoring.
Contrasting Marine Microbial Communities of the Fram Strait with the First Confirmed Record of Cyanobacteria Prochlorococcus marinus in the Arctic Region
Authors: Mioduchowska Monika , Pawłowska Joanna , Mazanowski Karol , Weydmann-Zwolicka Agata
Published: September 2023

The seawater microbiome is crucial in marine ecosystems because of its role in food chains and biogeochemical cycles; thus, we studied the composition of the pelagic marine microbiome collected in the upper 50 m on the opposite sides of Fram Strait: Spitsbergen and Greenland shelves. We found out that it differed significantly, with salinity being the main environmental variable responsible for these differences. The Spitsbergen shelf was dominated by Atlantic Waters, with a rather homogenous water column in terms of salinity and temperature down to 300 m; hence, the marine microbial community was also homogenous at all sampled depths (0, 25, 50 m). On the contrary, stations on the Greenland shelf were exposed to different water masses of both Arctic and Atlantic origin, which resulted in a more diverse microbial community there. Unexpectedly, for the very first time, we identified cyanobacterium Prochlorococcus marinus in Arctic waters (Spitsbergen shelf, 75–77° N). Till now, the distribution of this cyanobacteria in oceans has been described only between 40° N and 40° S. Considering the accelerated rate of climate warming in the Arctic, our results indicated that the seawater microbiome can be viewed as an amplifier of global change and that the Atlantification is in progress.
In Vitro Enzymatic Studies Reveal pH and Temperature Sensitive Properties of the CLIC Proteins
Authors: Alghalayini Amani , Hossain Khondker Rufaka , Moghaddasi Saba , Turkewitz Daniel R. , D’Amario Claudia , Wallach Michael , Valenzuela Stella M.
Published: September 2023

Chloride intracellular ion channel (CLIC) proteins exist as both soluble and integral membrane proteins, with CLIC1 capable of shifting between two distinct structural conformations. New evidence has emerged indicating that members of the CLIC family act as moonlighting proteins, referring to the ability of a single protein to carry out multiple functions. In addition to their ion channel activity, CLIC family members possess oxidoreductase enzymatic activity and share significant structural and sequence homology, along with varying overlaps in their tissue distribution and cellular localization. In this study, the 2-hydroxyethyl disulfide (HEDS) assay system was used to characterize kinetic properties, as well as the temperature and pH profiles of three CLIC protein family members (CLIC1, CLIC3, CLIC4). We also assessed the effects of the drugs rapamycin and amphotericin B, on the three CLIC proteins’ enzymatic activity in the HEDS assay. Our results demonstrate CLIC1 to be highly heat-sensitive, with optimal enzymatic activity observed at neutral pH7 and at a temperature of 37 °C, while CLIC3 had higher oxidoreductase activity in more acidic pH5 and was found to be relatively heat stable. CLIC4, like CLIC1, was temperature sensitive with optimal enzymatic activity observed at 37 °C; however, it showed optimal activity in more alkaline conditions of pH8. Our current study demonstrates individual differences in the enzymatic activity between the three CLIC proteins, suggesting each CLIC protein is likely regulated in discrete ways, involving changes in the subcellular milieu and microenvironment.
Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated with Postoperative Delirium
Authors: Dillon Simon T. , Vasunilashorn Sarinnapha M. , Otu Hasan H. , Ngo Long , Fong Tamara , Gu Xuesong , Cavallari Michele , Touroutoglou Alexandra , Shafi Mouhsin , Inouye Sharon K. , Xie Zhongcong , Marcantonio Edward R. , Libermann Towia A.
Published: September 2023

Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort, and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p < 0.05). Due to the limited sample size, these proteins did not remain significant by multiple hypothesis testing using the Benjamini–Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case–control samples correctly, and principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80–0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identified 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.
Promoter Optimization Circumvents Bcl-2 Transgene-Mediated Suppression of Lentiviral Vector Production
Authors: Kok Cindy Y. , MacLean Lauren M. , Rao Renuka , Tsurusaki Shinya , Kizana Eddy
Published: September 2023

Lentiviral vectors are a robust gene delivery tool for inducing transgene expression in a variety of cells. They are well suited to facilitate the testing of therapeutic candidate genes in vitro, due to relative ease of packaging and ability to transduce dividing and non-dividing cells. Our goal was to identify a gene that could be delivered to the heart to protect against cancer-therapy-induced cardiotoxicity. We sought to generate a lentivirus construct with a ubiquitous CMV promoter driving expression of B-cell lymphocyte/leukemia 2 gene (Bcl-2), a potent anti-apoptotic gene. Contrary to our aim, overexpression of Bcl-2 induced cell death in the producer HEK293T cells, resulting in failure to produce usable vector titre. This was circumvented by exchanging the CMV promoter to the cardiac-specific NCX1 promoter, leading to the successful production of a lentiviral vector which could induce cardioprotective expression of Bcl-2. In conclusion, reduced expression of Bcl-2 driven by a weaker promoter improved vector yield, and led to the production of functional cardioprotective Bcl-2 in primary cardiomyocytes.
Phytocannabinoids Reduce Seizures in Larval Zebrafish and Affect Endocannabinoid Gene Expression
Authors: Kollipara Roshni , Langille Evan , Tobin Cameron , French Curtis R.
Published: September 2023

Cannabis has demonstrated anticonvulsant properties, and about thirty percent of epileptic patients do not have satisfactory seizure management with standard treatment and could potentially benefit from cannabis-based intervention. Here, we report the use of cannabinoids to treat pentylenetetrazol (PTZ)-induced convulsions in a zebrafish model, their effect on gene expression, and a simple assay for assessing their uptake in zebrafish tissues. Using an optimized behavioral assay, we show that cannabidiol (CBD) and cannabichromene (CBC) and cannabinol (CBN) are effective at reducing seizures at low doses, with little evidence of sedation, and our novel HPLC assay indicates that CBC is effective with the lowest accumulation in larval tissues. All cannabinoids tested were effective at higher concentrations. Pharmacological manipulation of potential receptors demonstrates that Gpr55 partially mediates the anticonvulsant effects of CBD. Treatment of zebrafish larvae with endocannabinoids, such as 2-arachidonoylglycerol (2-AG) and anandamide (AEA), altered larvae movement, and the expression of genes that regulate their metabolism was affected by phytocannabinoid treatment, highlighting the possibility that changes to endocannabinoid levels may represent one facet of the anticonvulsant effect of phytocannabinoids.