bluuebunny/crossref_metadata_2025 huggingface dataset:
Environmental factors affecting the spatio-temporal distribution of zooplankton functional groups in a deep alkaline lake
Authors: Dorak Zeynep , Gaygusuz Özcan , Köker Latife , Albay Meriç , Akçaalan Reyhan
Published: August 2024

In recent years, trait-based studies have gained importance as an extension of taxonomic studies to better understanding ecosystem processes. However, these studies are still very limited in Mediterranean freshwaters. The aim of the study was to link functional groups with environmental factors and ecosystem processes for zooplankton in the Lake Iznik, which is an alkaline lake in Türkiye. Morphological, physiological and behavioural categories have been selected as response traits. Physical and chemical variables and trophic state are important predictors of functional traits. A total of 26 zooplankton taxa belonging to four taxonomic groups were classified into five functional groups according to functional traits. It was found that functional groups were significantly affected by seasonally changing environmental conditions, but not by depth. The main predictor of zooplankton functional groups was electrical conductivity. As a result of the alkaline conditions and the deterioration of the trophic state of the lake (meso ~ to eutrophy), the low taxonomic richness, dominance of the microphagous feeding type and small-bodied taxa indicate ecosystem degradation leading to functional depletion (homogenisation). The results showed that temporal variations of environmental variables can affect zooplankton functional groups and that trait-based zooplankton studies will enable a better understanding of ecosystem processes in deep alkaline lakes.
Risk of Neurodevelopmental Disorders in Offspring of Parents with Major Depressive Disorder: A Birth Cohort Study
Authors: Lin Yu-Han , Tsai Shih-Jen , Bai Ya-Mei , Chen Tzeng-Ji , Chen Mu-Hong
Published: August 2024

Studies have reported inconsistent results regarding associations between parental depression and offspring neurodevelopmental disorders, such as developmental delay and autism spectrum disorder (ASD). In all, 7,593 children who were born between 1996 and 2010 in Taiwan and had at least one parent with major depressive disorder and 75,930 birth-year- and sex-matched children of parents without major depressive disorder were followed from 1996 or time of birth to the end of 2011. Intergroup differences in neurodevelopmental conditions—including ASD, attention-deficit hyperactivity disorder (ADHD), tic disorder, developmental delay, and intellectual disability (ID)—were assessed. Compared with the children in the control group, the children of parents with major depression were more likely [hazard ratio (HR), 95% confidence interval (CI)] to develop ADHD (1.98, 1.80–2.18), ASD (1.52, 1.16–1.94), tic disorder (1.40, 1.08–1.81), developmental delay (1.32, 1.20–1.45), and ID (1.26, 1.02–1.55). Parental depression was associated with offspring neurodevelopmental disorders, specifically ASD, ADHD, developmental delay, ID, and tic disorder. Therefore, clinicians should closely monitor the neurodevelopmental conditions of children of parents with depression.
The impact of cultural amenities on inter-urban location: a discrete choice experiment on French students
Authors: Mouate Olivier , Travers Muriel
Published: August 2024

Since the late 90 s, the literature on the role of culture in the development of cities has grown. A first issue of this literature is to analyse the direction of the causality between the location of people and the one of cultural activities. The second issue is to measure the non-market values produced by cultural assets in cities. The aim of this paper is to investigate the impact of cultural amenities on students' future interurban location choice by using the discrete choice experiment method. The latter is used to address the two issues raised in the literature by modelling a location choice between cities that differ in terms of the living environment offered, and in particular the budget allocated to cultural facilities. Our data concerns students surveyed in 2018 in the city of Angers (France). Our results highlight the existence of a willingness to pay for living after graduation in a city with a budget devoted to cultural facilities which is above the average for the medium-sized French cities. We also observe a heterogeneity of students’ preferences according to their index of current cultural awareness created using a cluster analysis. Indeed, the more culturally aware students currently are, the more they will be willing to pay to live in a city offering an increased cultural budget. Finally, we observe a difference in willingness to pay depending on the faculty in which the student is enrolled, with the lowest one for students in Sciences, Engineering and Health.
Anisotropic wettability transition on nanoterraced glass surface by Ar ions
Authors: Hans Sukriti , Parida Basanta Kumar , Augustine Sebin , Pachchigar Vivek , Sooraj K. P. , Ranjan Mukesh
Published: August 2024

Ion beam sputtering (IBS) can induce nanoripple patterns in a short time on variety of materials for wide range of applications. In this work, we describe the nanoripple as well as terrace pattern formation by IBS on soda-lime glass surfaces and the mechanisms leading to such pattern formations. The role of ion energy, ion fluence, and ion incidence angle on the morphology of the structural features is systematically explored. For a range of ion beam parameter values with energy varying from 600 to 1500 eV and fluence in the range 9.7 × 1017 to 2.0 × 1019 ions/cm2 at fixed incidence angle of 45°, transition of ripples to terraces has been observed. The experimental results are explained on the basis of recently modified KS equation which clearly explains the simultaneous role of nonlinear cubic term in the terrace formation. It is also demonstrated how ion beam can be used to tailor the wettability of glass surface and makes it hydrophobic in nature. Due to pattern formation, anisotropic hydrophobicity is observed showing an increasing trend owing to the magnification of the amplitude of nanopatterns developed on the surface.
Effects of the incorporation of copper on the micro structure, charge transport and photoelectrical properties of sputtered ZnTe:Cu films
Authors: Alvarez M. A. Gomez , Calderón-Martínez A. I. , Rodríguez-Melgarejo F. , Hernández-Landaverde M. A. , Meléndez-Lira M. , Flores-Ruiz F. J. , Sandoval S. Jiménez
Published: August 2024

Advances in solar cell technology require improving the relevant physical properties of the constituent materials. One important functionality in photovoltaic devices is the efficient charge transport through the cell. Copper-doped zinc telluride (ZnTe:Cu) has been used as contact to cadmium telluride, the light-absorbing layer in photovoltaic devices. Out of the various deposition techniques, radio frequency sputtering is one of the most versatile and widely employed in research laboratories and industry. In this work, is presented a thorough characterization of ZnTe and ZnTe:Cu films grown by sputtering as a function of substrate temperature (Ts = 300 and 350 °C) and copper concentration (1, 3 and 5 at%). Besides the structural (X-ray diffraction), optical (UV-Vis spectroscopy) and electrical (Hall effect) characterizations, the present study included other studies relevant for optoelectronic applications such as photoluminescence, photoconductivity (under constant or transient illumination) and, in order to determine the effect of copper on the work function, Kelvin probe force microscopy was applied to the samples. Our results show important improvements in crystallite size, conductivity and photoconducting properties derived from the incorporation of copper in the ZnTe lattice.
An Efficient and Versatile Variational Method for High-Dimensional Data Classification
Authors: Cai Xiaohao , Chan Raymond H. , Xie Xiaoyu , Zeng Tieyong
Published: August 2024

High-dimensional data classification is a fundamental task in machine learning and imaging science. In this paper, we propose an efficient and versatile multi-class semi-supervised classification method for classifying high-dimensional data and unstructured point clouds. To begin with, a warm initialization is generated by using a fuzzy classification method such as the standard support vector machine or random labeling. Then an unconstraint convex variational model is proposed to purify and smooth the initialization, followed by a step which is to project the smoothed partition obtained previously to a binary partition. These steps can be repeated, with the latest result as a new initialization, to keep improving the classification quality. We show that the convex model of the smoothing step has a unique solution and can be solved by a specifically designed primal–dual algorithm whose convergence is guaranteed. We test our method and compare it with the state-of-the-art methods on several benchmark data sets. Thorough experimental results demonstrate that our method is superior in both the classification accuracy and computation speed for high-dimensional data and point clouds.
From Data to Decisions: Leveraging Artificial Intelligence and Machine Learning in Combating Antimicrobial Resistance – a Comprehensive Review
Authors: de la Lastra José M. Pérez , Wardell Samuel J. T. , Pal Tarun , de la Fuente-Nunez Cesar , Pletzer Daniel
Published: August 2024

The emergence of drug-resistant bacteria poses a significant challenge to modern medicine. In response, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have emerged as powerful tools for combating antimicrobial resistance (AMR). This review aims to explore the role of AI/ML in AMR management, with a focus on identifying pathogens, understanding resistance patterns, predicting treatment outcomes, and discovering new antibiotic agents. Recent advancements in AI/ML have enabled the efficient analysis of large datasets, facilitating the reliable prediction of AMR trends and treatment responses with minimal human intervention. ML algorithms can analyze genomic data to identify genetic markers associated with antibiotic resistance, enabling the development of targeted treatment strategies. Additionally, AI/ML techniques show promise in optimizing drug administration and developing alternatives to traditional antibiotics. By analyzing patient data and clinical outcomes, these technologies can assist healthcare providers in diagnosing infections, evaluating their severity, and selecting appropriate antimicrobial therapies. While integration of AI/ML in clinical settings is still in its infancy, advancements in data quality and algorithm development suggest that widespread clinical adoption is forthcoming. In conclusion, AI/ML holds significant promise for improving AMR management and treatment outcome.
Impact of Relative Humidity on the Formation of Low-Frictional Interface and its Continuity in Tribological Systems with Hydrogenated Carbon Nitride Coatings
Authors: Kuriyagawa Kazuya , Tamagawa Tatsuki , Adachi Koshi
Published: August 2024

The impact of relative humidity on the formation of low-frictional interface in hydrogenated carbon nitride (CNx:H) coatings sliding against Si3N4 balls and the formation continuity was elucidated through friction tests conducted in both air and nitrogen atmospheres with controlled relative humidity levels. In air atmosphere, a carbonaceous tribolayer with a transformed structure from the initial CNx:H was formed on Si3N4 at less than the critical humidity that existed in 1.0–3.0% RH, resulting in low friction (μ < 0.05) and a low specific wear rate of the balls (< 2 × 10–9 mm3/N·m). In contrast, this tribolayer failed to form above 3.0% RH. In nitrogen atmosphere, within the 0.25–1.0% RH range, the tribolayer continued to form concurrently with wear progression, maintaining low friction for over 50,000 cycles. However, in less than this humidity range, the lifetime of low friction was limited owing to the tribolayer’s structural alteration. Thus, relative humidity influences not only the formation of the low-frictional interface but also the formation continuity. On the CNx:H friction surface, hydrogen, hydroxyl, and oxygen groups from environmental water and oxygen molecules continued to chemisorb owing to tribochemical reactions on the uppermost few nanometers during continuous low friction in a nitrogen atmosphere, while hydrogen content of CNx:H desorbed. This study experimentally confirmed the critical role of controlling relative humidity in tribological systems using CNx:H coatings to achieve low friction and improve its durability of low friction through the continuous formation of the low-frictional interface.
Effects of climate change on seed germination may contribute to habitat homogenization in freshwater forested wetlands
Authors: Carr Kori , Ozowara Xavier , Sloey Taylor M.
Published: August 2024

Climate changes in temperate regions are expected to result in warmer, shorter winters in temperate latitudes. These changes may have consequences for germination of plant species that require a period of physiological dormancy. The effect of cold duration on seed germination has been investigated in a number of plant taxa, but has not been well studied in wetland and bottomland forest tree species, an ecosystem that is threatened by habitat homogenization. Our work sought to test the role of changing winter temperatures on seed germination in specialist (Nyssa aquatica and Taxodium distichum) and generalist (Acer rubrum and Liquidambar styraciflua) tree species within forested wetlands throughout the eastern U.S. The experiment was conducted in an environmental chamber in Norfolk, VA, USA. Seeds of T. distichum, N. aquatica, A. rubrum, and L. styraciflua were exposed to each of seven pre-germination cold exposure durations (0, 15, 30, 45, 60, 75, and 90 days) and observed for germination for 30 days. Cold stratification duration positively impacted total percent germination in N. aquatica (p < 0.0001) as well as A. rubrum (p = 0.0008) and T. distichum (p = 0.05). Liquidambar styraciflua seeds exhibited more rapid rates of germination with increasing cold exposure duration and greater percent germination compared to the others regardless of cold stratification duration. Our results provide insight into how community dynamics and biodiversity of wetland and bottomland trees may shift with a changing climate. Further, this work emphasizes the importance of understanding the role of plant functional traits in early life stages in community dynamics and has implications for management practices.
Identification of candidate genes and molecular mechanisms related to asthma progression using bioinformatics
Authors: Zou Songbing , Meng Fangchan , Xu Guien , Yu Rongchang , Yang Chaomian , Wei Qiu , Xue Yanlong
Published: August 2024

Background

Asthma is a heterogeneous disorder. This study aimed to identify changes in gene expression and molecular mechanisms associated with moderate to severe asthma.

Methods

Differentially expressed genes (DEGs) were analyzed in GSE69683 dataset among moderate asthma and its controls as well as between severe asthma and moderate asthma. Key module genes were identified via co-expression analysis, and the molecular mechanism of the module genes was explored through enrichment analysis and gene set enrichment analysis (GSEA). GSE89809 was used to verify the characteristic genes related to moderate and severe asthma.

Results

Accordingly, 2540 DEGs were present between moderate asthma and the control group, while 6781 DEGs existed between severe asthma and moderate asthma. These genes were identified into 14 co-expression modules. Module 7 had the highest positive correlation with severe asthma and was recognized to be a key module by STEM. Enrichment analysis demonstrated that the module genes were mainly involved in oxidative stress-related signaling pathways. The expression of HSPA1A, PIK3CG and PIK3R6 was associated with moderate asthma, while MAPK13 and MMP9 were associated with severe asthma. The AUC values were verified by GSE89809. Additionally, 322 drugs were predicted to target five genes.

Conclusion

These results identified characteristic genes related to moderate and severe asthma and their corresponding molecular mechanisms, providing a basis for future research.
Comparison of golden-angle radial sparse parallel (GRASP) and conventional cartesian sampling in 3D dynamic contrast-enhanced mri for bladder cancer: a preliminary study
Authors: Ueno Yoshiko , Sofue Keitaro , Tamada Tsutomu , Takeuchi Mitsuru , Ebisu Naoya , Nishiuchi Kentaro , Hara Takuto , Hyodo Toshiki , Miyake Hideaki , Murakami Takamichi
Published: August 2024

Purpose

To compare the image quality, inter-reader agreement, and diagnostic capability for muscle-invasive bladder cancer (MIBC) of the reconstructed images in sections orthogonal to the bladder tumor obtained by 3D Dynamic contrast-enhanced (DCE)-MRI using the Golden-angle Radial Sparse Parallel (GRASP) technique with the images directly captured using the Cartesian sampling.

Materials and methods

This study involved 68 initial cases of bladder cancer examined with DCE-MRI (GRASP: n = 34, Cartesian: n = 34) at 3 Tesla. Four radiologists conducted qualitative evaluations (overall image quality, absence of motion artifact, absence of streak artifact, and tumor conspicuity) using a five-point Likert scale (5 = Excellent/None) and quantitative signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements. The areas under the receiver-operating characteristic curves (AUCs) for the Vesical Imaging-Reporting and Data System (VI-RADS) DCE score for MIBC assessment were calculated. Inter-reader agreement was also assessed.

Results

GRASP notably enhanced overall image quality (pooled score: GRASP 4 vs. Cartesian 3, P < 0.0001), tumor conspicuity (5 vs. 3, P < 0.05), SNR (Median 38.2 vs. 19.0, P < 0.0001), and CNR (7.9 vs. 6.0, P = 0.005), with fewer motion artifacts (5 vs. 3, P < 0.0001) and minor streak artifacts (5 vs. 5, P > 0.05). Although no significant differences were observed, the GRASP group tended to have higher AUCs for MIBC (pooled AUCs: 0.92 vs. 0.88) and showed a trend toward higher inter-reader agreement (pooled kappa-value: 0.70 vs. 0.63) compared to the Cartesian group.

Conclusions

Using the GRASP for 3D DCE-MRI, the reconstructed images in sections orthogonal to the bladder tumor achieved higher image quality and improve the clinical work flow, compared to the images directly captured using the Cartesian. GRASP tended to have higher diagnostic ability for MIBC and showed a trend toward higher inter-reader agreement compared to the Cartesian.
Workplace Learning Environment and Participation in Work Communities: A Qualitative Comparison of Stayers’ and Leavers’ Perceptions and Experiences
Authors: Schmid Evi , Nordlie Gøril Stokke , Jørstad Beate
Published: August 2024

In many countries with apprenticeship-based vocational education and training (VET), dropout from apprenticeship training is a major concern. Leaving an apprenticeship early can be problematic, particularly for young people who do not continue their training at another company or in another occupation, and drop out of the education system without obtaining a qualification. Previous research mostly has used a quantitative design focussing mainly on the perspective of apprentices who left training early and on attributes of the individual that may lead to dropout. Drawing on literature on quality of workplace learning environments, this study used a qualitative comparative approach to analyse the workplace learning environment from the perspectives of both young people who left their apprenticeships early and apprentices at the end of their training. The analysis revealed striking differences between the stayers and leavers in terms of two main characteristics of the workplace learning environment. The findings illustrate how being given responsibility can promote professional development and self-confidence, but also can lead to stress, exhaustion and insecurity if an early transfer of responsibility is not accompanied by support and guidance. Furthermore, the findings emphasise the importance of creating safe learning environments in which apprentices experience support and room for making mistakes. The study concludes that future research may include measures related to transfer and fulfilment of responsibility and handling of mistakes in workplaces to gain a more comprehensive understanding of the processes leading to early contract terminations.
Evaluation of monthly variations in electrometer calibration coefficients using a charge generator for radiation therapy
Authors: Kawashima Motohiro , Varnava Maria , Ozawa Shuichi , Higuchi Hiromitsu , Hoshino Yoshihiko , Tashiro Mutsumi
Published: August 2024

Electrometers are important devices that are part of the standard dosimetry system. Therefore, we evaluated the variation of electrometer calibration coefficients (kelec) over 1 year in this study. We investigated two types of electrometers: a rate mode and an integrate mode. Each electrometer was connected to a charge generator, a constant charge was applied, and kelec was determined by measuring the current. The current measurements were repeated once a month. For electrometers with multiple ranges, measurements were taken at low and medium ranges. Almost all kelec measurements agreed within 0.2% of the initial measurements. However, the low range of the electrometer with an integrate mode showed seasonal variation, with a variation greater than 0.2%. This study shows that electrometers may exhibit errors that cannot be detected through annual inspections. The importance of quality assurance using a charge generator at one’s own institution was demonstrated.
Pd0–Ov–Ce3+ Interfacial Sites with Charge Redistribution for Enhanced Hydrogenation of Methyl Oleate to Methyl Stearate
Authors: Meng Zhaohui , Liao Ying , Liu Ling , Li Yaqian , Yan Hao , Feng Xiang , Chen Xiaobo , Liu Yibin , Yang Chaohe
Published: August 2024

Improving the efficiency of metal/reducible metal oxide interfacial sites for hydrogenation reactions of unsaturated groups (e.g., C=C and C=O) is a promising yet challenging endeavor. In our study, we developed a Pd/CeO2 catalyst by enhancing the oxygen vacancy (OV) concentration in CeO2 through high-temperature treatment. This process led to the formation of an interface structure ideal for supporting the hydrogenation of methyl oleate to methyl stearate. Specifically, metal Pd0 atoms bonded to the OV in defective CeO2 formed Pd0–OV–Ce3+ interfacial sites, enabling strong electron transfer from CeO2 to Pd. The interfacial sites exhibit a synergistic adsorption effect on the reaction substrate. Pd0 sites promote the adsorption and activation of C=C bonds, while OV preferably adsorbs C=O bonds, mitigating competition with C=C bonds for Pd0 adsorption sites. This synergy ensures rapid C=C bond activation and accelerates the attack of active H* species on the semi-hydrogenated intermediate. As a result, our Pd/CeO2-500 catalyst, enriched with Pd0–OV–Ce3+ interfacial sites, demonstrated excellent hydrogenation activity at just 30 °C. The catalyst achieved a Cis–C18:1 conversion rate of 99.8% and a methyl stearate formation rate of 5.7 mol/(h·gmetal). This work revealed the interfacial sites for enhanced hydrogenation reactions and provided ideas for designing highly active hydrogenation catalysts.
Local Reinforcement of a Fuel Cell End Plate for Package Improvements Using Steel–Aluminium Hybrid-Casting Technology
Authors: Mielke Florian , Anand Sharath Christy , Fang Xiangfan
Published: August 2024

In this research work, a method for integrating a local reinforcement structure in a medium-pressure plate (MPP) for fuel cell electric vehicle (FCEV) applications was developed using steel–aluminium hybrid-casting technology. Using this technology, it is possible to create a bonded enclosure of a steel reinforcement patch with the cast aluminium pressure plate to increase its stiffness and achieve 15% package space savings. A load-compliant, manufacturable patch was chosen and optimised for maximum stiffness gains using non-linear static finite-element (FE) calculations. Special form and process requirements due to hybrid-casting technology were examined and secured with casting simulations. The reinforcement patch was manufactured and coated with a unique aluminium–silicon coating enabling a ductile material connection between the steel and aluminium, and casting trials were conducted to create prototypes. Additionally, the insulating plastic layer on top of the metallic pressure plate carrier was substituted from costly short-fibre-reinforced high-performance plastic to cheaper and stiffer glass-mat reinforced thermoplastic material. Finally, the new hybrid MPP was tested mechanically, and the FE-Model was verified. In summary, through the package gain, 2.1 kW more power output and 11% less weight could be achieved while remaining stiffness neutral.
From “stars” to nano: Porous poly(ethylene glycol) hydrogel films and nanosheets as a versatile platform for sensing and nanofabrication
Authors: Zharnikov Michael
Published: August 2024

The use of bioinert materials is crucially important for medicine and bioengineering. The most popular systems in this context are oligo- and poly(ethylene glycols) (OEGs and PEGs), applied generally in different forms as bulk materials, thin films, and functional molecular groups. Here, I review the fabrication, properties, and applications of porous hydrogel PEG films (PHFs) and nanosheets (PHNs) formed by thermally activated crosslinking of amino- and epoxy-terminated, star-branched PEG oligomers with variable molecular weight. These systems possess various useful characteristics, including tunable thickness and porosity, hydrogel properties, bioinertness, robustness, and extreme elasticity. They can serve as the basis for composite materials, advanced nanofabrication, and lithography, bioinert supports for high-resolution transmission electron microscopy, susceptible elements in micro-electromechanical systems, and basic building blocks of temperature, humidity, chemical, and biological sensors. Representative examples of the respective applications are provided. Even though these examples span a broad field-from nanoengineering to biosensing, the applications of the PHFs and PHNs are certainly not limited to these cases but can be specifically adapted and extended to other fields, such as tissue engineering and drug delivery, relying on versatility and tunability of these systems.
Outlier detection and selection of representative fluid samples using machine learning: a case study of Iranian oil fields
Authors: Hosseini Mahdi , Zaheri Seyed Hayan , Roosta Ali
Published: August 2024

During the development of a field, many fluid samples are taken from wells. Selecting a robust fluid sample as the reservoir representative helps to have a better field characterization, reliable reservoir simulation, valid production forecast, efficient well placement and finally achieving optimized ultimate recovery. First, this paper aims to detect and separate the samples that have been collected under poor conditions or analyzed in a non-standard way. Moreover, it introduces a novel ranking method to score the samples based on the amount of coordination with other fluid samples in the region. The dataset includes 136 fluid samples from five reservoirs in Iranian fields, each of them consisting of 21 key parameters. Five acknowledged machine learning based anomaly detection techniques are implemented to compare fluid samples and detect those whose results deviate from others, indicating non-standard samples. To ensure the proper detection of outlier data, the results are compared with the traditional validation method of gas-oil ratio estimation. All five outlier detection methods demonstrate acceptable performance with average accuracy of 79% compared to traditional validation. Furthermore, the fluid samples with the highest scores in scoring-based algorithms are introduced as the best reservoir’s representative fluid. Finally, fuzzy logic is used to obtain a final score for each sample, taking the results of the six methods as input and ranking the samples based on their output score. The study confirms the robustness of the novel approach for fluid validation using outlier detection techniques and the value of machine learning and fuzzy logic for sample ranking, excelling in considering all critical fluid parameters simultaneously over traditional methods.
Performance Analysis of Embedding Methods for Deep Learning-Based Turkish Sentiment Analysis Models
Authors: Ba Alawi Abdulfattah , Bozkurt Ferhat
Published: August 2024

The complex syntactic structure of Turkish text makes sentiment analysis in natural language processing (NLP) a challenging task. Conventional sentiment analysis methods often fail to effectively identify attitudes in Turkish texts, creating an urgent need for more efficient approaches. To fill this need, our study investigates the effectiveness of embedding techniques including pre-trained Turkish models such as Word2Vec, GloVe, and FastText in addition to two character-level embedding methods, namely, character-integer embedding (CIE) and character one-hot encoding embedding (COE), in conjunction with deep learning models specifically long short-term memory (LSTM), convolution neural networks (CNNs), bidirectional LSTM (Bi-LSTM), and hybrid models, for Turkish short-texts sentiment analysis. DL-based models were investigated on two datasets (e.g., an original Twitter (X) dataset and an accessible hotel reviews dataset). In addition to providing an intensive performance analysis of different embedding strategies and assessing their efficacy in dealing with the linguistic intricacies of Turkish, this study proposed a previously unexplored method in Turkish text representation that relies on a character-level one-hot encoding technique. The obtained findings indicate positive progress using a novel approach utilizing a dual-pathway architecture for both character level and word level that constitutes a substantial contribution to the area of natural language processing (NLP), specifically in the context of complex morphological languages. By employing a hybrid strategy that combines character and word levels on Twitter (X) data, the LSTM model obtained an F1 score of $$0.835 \pm 0.005$$

0.835
±
0.005

concerning cross-validation while CNN-BiLSTM attained the highest F1 Score (0.8392) using holdout validation. This strategy consistently produced modest improvements across the second public dataset (hotel reviews dataset) by emerging as the runner-up embedding technique in effectiveness, surpassed only by FastText. Findings provide practical recommendations for practitioners on how to effectively use sentiment analysis to make informed decisions by introducing an extensive performance analysis of the use of embedding techniques and deep learning models for sentiment analysis in Turkish texts, which is crucial in the current age of data analysis.
A scale development study on the perception of the sustainable urban environment
Authors: Altanlar A. , Özdemir Z.
Published: August 2024

In order to assess sustainability, it is necessary to monitor social conditions on environmental, global, national and urban scales. Therefore, the objective of this study is to develop a scale to determine PSUE. In addition, it is also examined whether there is a significant difference between the components that determine the perception of sustainable urban environment according to the characteristics of the participants. For this purpose, Exploratory Factor Analysis, Spearman–Brown correlation test, Cronbach alpha test, Mann–Whitney test and Kruskal–Wallis test are implemented. According to the findings acquired, it has been detected that the components that determine PSUE are “spatial strategies related to sustainable environment and transportation”, “spatial strategies related to ecological sustainability and solid waste management” and “spatial strategies related to social and economic sustainability” respectively. In this study, differences have been identified in the perspectives on social and economic sustainability strategies according to gender. However, participant’s viewpoints regarding strategies related to sustainable environment and transportation, as well as ecological sustainability and solid waste management, are similar. Additionally, significant differences exist in social and economic sustainability strategies based on the age of the participants. The urban or rural character of the settlement where the students families live or grew up influences their perspectives on strategies based on social sustainability and economic relations.
Reconciling Signal-Detection Models of Criterion Learning with the Generalized Matching Law
Authors: Koß Christina , de la Cuesta-Ferrer Luis , Stüttgen Maik C. , Jäkel Frank
Published: August 2024

To make decisions that lead to favorable outcomes, animals have to consider both their perceptual uncertainty as well as uncertainty about the outcomes of their actions, such as reinforcements. There is a long tradition of research investigating how the reinforcement structure of a task controls animals’ response behavior. The relation between reinforcement and response rates has been described by the matching law and its generalizations for tasks with and without perceptual uncertainty. The influence of perceptual uncertainty on decision behavior is traditionally modeled with signal detection theory, which posits that a decision criterion is placed on an internal evidence axis. Where this criterion is placed and how it is updated based on reinforcements are open questions within signal detection theory. Various criterion learning models have been proposed; however, their steady-state behavior across different experimental conditions is not consistent with the aforementioned empirical matching laws. Here, we integrate models of criterion learning from signal detection theory with matching laws from animal learning theory to gain a better understanding of the mechanisms by which reinforcements and perceptual uncertainty jointly shape behavior. To do so, we first derive the criterion position that leads to behavior aligned with those laws. We then develop a model that updates the decision criterion trial by trial to learn this criterion position. Our model fits data from a previous experiment well and generates behavior in simulations that is in line with matching laws for perceptual tasks and the subjects’ behavior in the experiment.
Supervised machine learning-based Hall thruster scaling
Authors: Marianacci Alfredo , Mazouffre Stéphane
Published: August 2024

The scaling methodology described in this paper to find the geometry and working parameters of Hall Thrusters is based on algorithms of supervised Machine Learning. The approach considers the determination of the geometrical sizes, propellant mass flow rate and discharge voltage taking thrust and specific impulse as requirements. The magnetic field is also considered. The Gradient Boosting Regression is found as the most suitable algorithm for our purpose. Scaling relies on a specific database of 54 thrusters for the determination of all parameters. The database includes measurements carried out with xenon, krypton and argon as propellant. A unique analytical approach based on the GBR algorithm has been developed and validated to determine the suitable design for a Hall thruster according to space mission requirements.
Acusicola rochai n. sp. (Copepoda: Ergasilidae) parasitizing Anableps anableps (Anablepidae) from the Amazon Coast, with a key for Acusicola spp.
Authors: Couto João Victor , Silva Nunes Jorge Luiz , Paschoal Fabiano , Bisaggio Pereira Felipe
Published: August 2024

Ergasilid copepods represent one of the commonest groups of fish parasites in Brazil. Within Ergasilidae, three genera share a peculiar latching mechanism on the antenna that completely encircles the gill filament, one of which is Acusicola Cressey, 1970. During a survey of estuarine fish from the Brazilian Amazon Coast, a new species of Acusicola was found on the gills of the largescale foureyes Anableps anableps (Linnaeus, 1758) (Actinopterygii: Anablepidae) in São Marcos Bay, State of Maranhão. Acusicola rochai n. sp. can be distinguished from its closest congeners mainly by three protrusions on the dorsal surface of third and fourth pedigerous somites, and by smooth interpodal plates. This work is the first report of a parasitic copepod infesting a fish from Anablepidae and, consequently, the host An. anableps. The existing dichotomous key proposed for the genus Acusicola includes only ten species, excluding the eight species subsequently described. Therefore, in the present work, a new dichotomous key is provided based on reliable and well-documented features.
Robust Hydropower Planning Balances Energy Generation, Carbon Emissions and Sediment Connectivity in the Mekong River Basin
Authors: Tangi M. , Schmitt R. , Almeida R. , Bossi S. , Flecker A. , Sala F. , Castelletti A.
Published: August 2024

We present a framework for strategic dam planning under uncertainty, which includes GHG emissions mitigation as a novel objective. We focus on the Mekong River Basin, a fast‐developing region heavily relying on river‐derived ecosystem services. We employ a multi‐objective evolutionary algorithm to identify strategic dam portfolios for different hydropower expansion targets, using process‐related and statistical models to derive indicators of sediment supply disruption and GHG emissions. We introduce a robust optimization approach that explores variations in optimal portfolio compositions for more than 5,000 state‐of‐the‐world configurations, regarding sediment origins and trapping and GHG emissions. Thus, we can rank dam projects' attractiveness based on their frequency of inclusion in optimal portfolios and explore how uncertainty affects these rankings. Our results suggest that developing dams in the upper Mekong would be a more robust option for near‐term development than, for example, the lower Mekong and its tributaries, for both environmental and energy objectives. Our work presents a novel approach to better understand the basin‐scale cumulative impacts of dam development in high‐uncertainty, data‐scarce contexts like the Mekong Basin.
Response of a Terrestrial Polar Ecosystem to the March 2022 Antarctic Weather Anomaly
Authors: Barrett J. E. , Adams Byron J. , Doran Peter T. , Dugan Hilary A. , Myers Krista F. , Salvatore Mark R. , Power Sarah N. , Snyder Meredith D. , Wright Anna T. , Gooseff Michael N.
Published: August 2024

Record high temperatures were documented in the McMurdo Dry Valleys, Antarctica, on 18 March 2022, exceeding average temperatures for that day by nearly 30°C. Satellite imagery and stream gage measurements indicate that surface wetting coincided with this warming more than 2 months after peak summer thaw and likely exceeded thresholds for rehydration and activation of resident organisms that typically survive the cold and dry conditions of the polar fall in a freeze‐dried state. This weather event is notable in both the timing and magnitude of the warming and wetting when temperatures exceeded 0°C at a time when biological communities and streams have typically entered a persistent frozen state. Such events may be a harbinger of future climate conditions characterized by warmer temperatures and greater thaw in this region of Antarctica, which could influence the distribution, activity, and abundance of sentinel taxa. Here we describe the ecosystem responses to this weather anomaly reporting on meteorological and hydrological measurements across the region and on later biological observations from Canada Stream, one of the most diverse and productive ecosystems within the McMurdo Dry Valleys.
Large Isotopic Shift in Volcanic Plume CO2 Prior to a Basaltic Paroxysmal Explosion
Authors: D’Arcy Fiona , Aiuppa Alessandro , Grassa Fausto , Rizzo Andrea Luca , Stix John
Published: August 2024

Carbon dioxide is a key gas to monitor at volcanoes because its concentration and isotopic signature can indicate changes to magma supply and degassing behavior prior to eruptions, yet carbon isotopic fluctuations at volcanic summits are not well constrained. Here we present δ13C results measured from plume samples collected at Stromboli volcano, Italy, by Uncrewed Aerial Systems (UAS). We found contrasting volcanic δ13C signatures in 2018 during quiescence (−0.36 ± 0.59‰) versus 10 days before the 3 July 2019 paroxysm (−5.01 ± 0.56‰). Prior to the eruption, an influx of CO2‐rich magma began degassing at deep levels (∼100 MPa) in an open‐system fashion, causing strong isotopic fractionation and maintaining high CO2/St ratios in the gas. This influx occurred between 10 days and several months prior to the event, meaning that isotopic changes in the gas could be detected weeks to months before unrest.
Resolving Strain Localization in Frictional and Time‐Dependent Plasticity: Two‐ and Three‐Dimensional Numerical Modeling Study Using Graphical Processing Units (GPUs)
Authors: Alkhimenkov Yury , Khakimova Lyudmila , Utkin Ivan , Podladchikov Yury
Published: August 2024

Shear strain localization refers to the phenomenon of accumulation of material deformation in narrow slip zones. Many materials exhibit strain localization under different spatial and temporal scales, particularly rocks, metals, soils, and concrete. In the Earth's crust, irreversible deformation can occur in brittle as well as in ductile regimes. Modeling of shear zones is essential in the geodynamic framework. Numerical modeling of strain localization remains challenging due to the non‐linearity and multi‐scale nature of the problem. We develop a numerical approach based on graphical processing units (GPU) to resolve the strain localization in two and three dimensions of a (visco)‐hypoelastic‐perfectly plastic medium. Our approach allows modeling both the compressible and incompressible visco‐elasto‐plastic flows. In contrast to symmetric shear bands frequently observed in the literature, we demonstrate that using sufficiently small strain or strain rate increments, a non‐symmetric strain localization pattern is resolved in two‐ and three‐dimensions, highlighting the importance of high spatial and temporal resolution. We show that elasto‐plastic and visco‐plastic models yield similar strain localization patterns for material properties relevant to applications in geodynamics. We achieve fast computations using three‐dimensional high‐resolution models involving more than 1.3 billion degrees of freedom. We propose a new physics‐based approach explaining spontaneous stress drops in a deforming medium.
The Impact of Model Horizontal Resolution on Simulating Regional Climate Over East Asia Using Variable‐Resolution CESM2
Authors: Wang Weiyi , Liu Xiaohong , Lin Guangxing , Wu Chenglai
Published: August 2024

In this study, a variable‐resolution version of the Community Earth System Model (VR‐CESM) with mesh refinement (∼0.125°) over East Asia is used to simulate the regional climate in this region. For the evaluation of model performance and sensitivity to model resolution, the simulated near‐surface temperature and precipitation are compared with observations and simulation results from a globally quasi‐uniform (∼1°) CESM (UN‐CESM). Results show that VR‐CESM better simulates the spatial patterns and seasonal variations of mean temperature and precipitation than UN‐CESM over China. For extreme events, VR‐CESM improves the simulation of the occurrence frequency of wintertime daily minimum temperature and heavy precipitation. In regions with complex terrains, VR‐CESM better resolves the topographic forcing and captures the observed fine‐scale spatial patterns of temperature and precipitation, although precipitation is still overestimated. For East Asian summer monsoon precipitation, both UN‐CESM and VR‐CESM tend to overestimate (underestimate) the precipitation over northern (southern) China, which is associated with too strong meridional water vapor transport in the models and biases in the large‐scale circulation in the middle and upper troposphere. Different from previous studies with different physics parameterizations and refined domains, as the model resolution increases, simulated monsoon precipitation evolution is not obviously improved, and convective precipitation intensity decreases over eastern China. Despite this, our results indicate that VR‐CESM simulates regional climate, topographical forcing, and large‐scale circulations over East Asia reasonably well, and thus it can be applied for the future climate projection in the region.
Inter‐Basin Versus Intra‐Basin Sea Surface Temperature Forcing of the Western North Pacific Subtropical High's Westward Extensions
Authors: Jones Jhordanne J. , Chavas Daniel R. , Johnson Zachary F.
Published: August 2024

Zonal extensions of the Western Pacific subtropical high (WPSH) strongly modulate extreme rainfall activity and tropical cyclone (TC) landfall over the Western North Pacific (WNP) region. These zonal extensions are primarily forced on seasonal timescales by inter‐basin zonal sea surface temperature (SST) gradients. However, despite the presence of large‐scale zonal SST gradients, the WPSH response to SSTs varies from year to year. In this study, we force the atmosphere‐only NCAR Community Earth System Model version 2 simulations with two real‐world SST patterns, both featuring the large‐scale zonal SST gradient characteristic of decaying El Niño‐developing La Niña summers. For each of these patterns, we performed four experimental sets that tested the relative contributions of the tropical Indian Ocean, Pacific, and Atlantic basin SSTs to simulated westward extensions over the WNP during June–August. Our results indicate that the subtle differences between the two SST anomaly patterns belie two different mechanisms forcing the WPSH's westward extensions. In one SST anomaly pattern, extratropical North Pacific SST forcing suppresses the tropical Pacific zonal SST gradient forcing, resulting in tropical Atlantic and Indian Ocean SSTs being the dominant driver. The second SST anomaly pattern drives a similar westward extension as the first pattern, but the underlying SST gradient driving the WPSH points to intra‐basin forcing mechanisms originating in the Pacific. The results of this study have implications for understanding and predicting the impact of the WPSH's zonal variability on tropical cyclones and extreme rainfall over the WNP.