bluuebunny/crossref_metadata_2025 huggingface dataset:
Abiotic synthesis of graphitic carbons in the Eoarchean Saglek-Hebron metasedimentary rocks
Authors: Guo Zixiao , Papineau Dominic , O’Neil Jonathan , Rizo Hanika , Chen Zhong-Qiang , Qiu Xincheng , She Zhenbing
Published: July 2024

Graphite in metasedimentary rocks of the Eoarchean Saglek-Hebron Gneiss Complex (Canada) is depleted in 13C and has been interpreted as one of the oldest traces of life on Earth. The variation in crystallinity of this oldest graphitic carbon could possibly confirm the effect of metamorphism on original biomass, but this is still unexplored. Here, we report specific mineral associations with graphitic carbons that also have a range of crystallinity in the Saglek-Hebron metasedimentary rocks. Petrographic, geochemical and spectroscopic analyses in the Saglek-Hebron banded iron formations suggest that poorly crystalline graphite is likely deposited from C-H-O fluids derived from thermal decomposition of syngenetic organic matter, which is preserved as crystalline graphite during prograde metamorphism. In comparison, in the Saglek-Hebron marble, disseminations of graphite co-occur with carbonate and magnetite disseminations, pointing to abiotic synthesis of graphitic carbons via decarbonation. Our results thus highlight that variably crystalline graphitic carbons in the Saglek-Hebron metasedimentary rocks are potential abiotic products on early Earth, which lay the groundwork for identifying the preservation of prebiotic organic matter through metamorphism on Earth and beyond.
A review of biomaterial degradation assessment approaches employed in the biomedical field
Authors: Mndlovu Hillary , Kumar Pradeep , du Toit Lisa C. , Choonara Yahya E.
Published: July 2024

The biological response to biomaterials plays a crucial role in selecting suitable materials for the formulation and development of tissue engineering platforms. Biodegradation is one of the properties that is considered in selecting appropriate biomaterials for biomedical applications. Biodegradation is the process of breaking down large molecules into smaller molecules with/without the aid of catalytic enzymes. The biodegradation process is crucial in the chemical absorption, distribution, metabolism, excretion, and toxicity (ADMET) process of biomaterials and small molecules in the body. Degradation of biomaterials can be followed by assessing the physical, mechanical, and chemical attributes of biomaterials. There are several techniques/parameters that can be targeted when studying the degradation of biomaterials, with gravimetric analysis, surface erosion, and morphological changes being the largely employed techniques. However, the techniques present a few limitations, such as technical errors and material solubility being mistaken for degradation, and these techniques can infer but not confirm degradation as they do not provide the chemical composition of fragmenting/fragmented molecules. The American Society for Testing and Materials (ASTM) guidelines provide techniques and parameters for assessing biodegradation. However, the ASTM guidelines for degradation assessment approaches and techniques need to be updated to provide sufficient evidence to draw conclusive decisions regarding the degradation of biomaterials. In this review, the degradation assessment approaches and techniques are critically reviewed about their advantages and disadvantages, and to provide suggestions on how they can still play a role in assessing the degradation of biomaterials. This review could assist researchers employ cost-effective, efficient, and multiple degradation assessment techniques to evaluate and provide sufficient information about the degradation of biomaterials. Suggested future ASTM guidelines for assessing biodegradation should include measuring parameters (such as chemical, mechanical, or physical attributes of biomaterials) in real-time, employing non-invasive, continuous, and automated processes.
The impact of premature birth on auditory-visual processes in very preterm schoolchildren
Authors: Décaillet Marion , Denervaud Solange , Huguenin-Virchaux Cléo , Besuchet Laureline , Fischer Fumeaux Céline J. , Murray Micah M. , Schneider Juliane
Published: July 2024

Interactions between stimuli from different sensory modalities and their integration are central to daily life, contributing to improved perception. Being born prematurely and the subsequent hospitalization can have an impact not only on sensory processes, but also on the manner in which information from different senses is combined—i.e., multisensory processes. Very preterm (VPT) children (<32 weeks gestational age) present impaired multisensory processes in early childhood persisting at least through the age of five. However, it remains largely unknown whether and how these consequences persist into later childhood. Here, we evaluated the integrity of auditory-visual multisensory processes in VPT schoolchildren. VPT children (N = 28; aged 8–10 years) received a standardized cognitive assessment and performed a simple detection task at their routine follow-up appointment. The simple detection task involved pressing a button as quickly as possible upon presentation of an auditory, visual, or simultaneous audio-visual stimulus. Compared to full-term (FT) children (N = 23; aged 6–11 years), reaction times of VPT children were generally slower and more variable, regardless of sensory modality. Nonetheless, both groups exhibited multisensory facilitation on mean reaction times and inter-quartile ranges. There was no evidence that standardized cognitive or clinical measures correlated with multisensory gains of VPT children. However, while gains in FT children exceeded predictions based on probability summation and thus forcibly invoked integrative processes, this was not the case for VPT children. Our findings provide evidence of atypical multisensory profiles in VPT children persisting into school-age. These results could help in targeting supportive interventions for this vulnerable population.
Chromosome-level genome assembly of an oligophagous leaf beetle Ophraella communa (Coleoptera: Chrysomelidae)
Authors: Wang Yi-Ting , Zhang Yan , Ma Chao , Ma Wei-Hua , Cao Li-Jun , Chen Jin-Cui , Song Wei , Yang Jing-Fang , Gao Xu-Yuan , Chen Hong-Song , Tian Zhen-Ya , Desneux Nicolas , Wei Shu-Jun , Zhou Zhong-Shi
Published: July 2024

The leaf beetle Ophraella communa LeSage (Coleoptera: Chrysomelidae) is an effective biological control agent of the common ragweed. Here, we assembled a chromosome-level genome of the O. communa by combining Illumina, Nanopore, and Hi-C sequencing technologies. The genome size of the final genome assembly is 733.1 Mb, encompassing 17 chromosomes, with an improved contig N50 of 7.05 Mb compared to the original version. Genome annotation reveals 25,873 protein-coding genes, with functional annotations available for 22,084 genes (85.35%). Non-coding sequence annotation identified 204 rRNAs, 626 tRNAs, and 1791 small RNAs. Repetitive elements occupy 414.41 Mb, constituting 57.76% of the genome. This high-quality genome is fundamental for advancing biological control strategies employing O. communa.
Pixel-wise segmentation of cells in digitized Pap smear images
Authors: Harangi Balazs , Bogacsovics Gergo , Toth Janos , Kovacs Ilona , Dani Erzsebet , Hajdu Andras
Published: July 2024

A simple and cheap way to recognize cervical cancer is using light microscopic analysis of Pap smear images. Training artificial intelligence-based systems becomes possible in this domain, e.g., to follow the European recommendation to screen negative smears to reduce false negative cases. The first step for such a process is segmenting the cells. A large and manually segmented dataset is required for this task, which can be used to train deep learning-based solutions. We describe a corresponding dataset with accurate manual segmentations for the enclosed cells. Altogether, the APACS23 (Annotated PAp smear images for Cell Segmentation 2023) dataset contains about 37 000 manually segmented cells and is separated into dedicated training and test parts, which could be used for an official benchmark of scientific investigations or a grand challenge.
Improved solar still productivity using PCM and nano- PCM composites integerated energy storage
Authors: Murali G. , Ramani P. , Murugan M , Elumalai P. V. , Ranjan Goud Nayani Uday , Prabhakar S.
Published: July 2024

The study investigates the impact of Phase Change Material (PCM) and nano Phase Change Materials (NPCM) on solar still performance. PCM and a blend of NPCM are placed within 12 copper tubes submerged in 1 mm of water to enhance productivity. Thermal performance is assessed across four major scenarios with a fixed water level of 1 mm in the basin. These scenarios include the conventional still, equipped with 12 empty copper rods and 142 g of PCM in each tube, as well as stills with NPCM Samples 1 and 2. Sample 1 contains 0.75% nanoparticle concentration plus 142 g of PCM in the first 6 tubes, while Sample 2 features 2% nanoparticle concentration plus 142 g of PCM in the subsequent 6 tubes. Aluminum oxide (Al2O3) nanoparticles ranging in size from 20 to 30 nm are utilized, with paraffin wax (PW) serving as the latent heat storage (LHS) medium due to its 62 °C melting temperature. The experiments are conducted under the local weather conditions of Vaddeswaram, Vijayawada, India (Latitude-80.6480 °E, Longitude-16.5062 °N). A differential scanning calorimeter (DSC) is utilized to examine the thermal properties, including the melting point and latent heat fusion, of the NPCM compositions. Results demonstrate that the addition of nanoparticles enhances both the specific heat capacity and latent heat of fusion (LHF) in PCM through several mechanisms, including facilitating nucleation, improving energy absorption during phase change, and modifying crystallization behavior within the phase change material. Productivity and efficiency measurements reveal significant improvements: case 1 achieves 2.66 units of daily production and 46.23% efficiency, while cases 2, 3, and 4 yield 3.17, 3.58, and 4.27 units of daily production, respectively. Notably, the utilization of NPCM results in a 60.37% increase overall productivity and a 68.29% improvement in overall efficiency.
Exploring secular variation of the gravitational constant from high-resolution quasar spectra
Authors: Le T. D.
Published: July 2024

The exploration of potential variations in fundamental physical constants is crucial for testing of Grand Unification Theories (GUTs), which aim to unify the fundamental forces of nature. This study utilizes direct observational tests to explore these variations, offering a deep-look into the universe's distant past. By analyzing high-resolution quasar spectra of HE 0515–4414* and comparing them with laboratory-calibrated Ritz wavelengths, we establish an upper limit on the possible cosmological deviation of the gravitational constant: $$\dot{\text{G}}/\text{G}=(0.918 \pm 2.830)\times {10}^{-15}{\text{ yr}}^{-1}$$

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over cosmic timescales. Our findings provide a novel tool for probing the physical implications of GUTs, contributing to our understanding of fundamental physics.
Exploring the impacts of risk factors on mortality patterns of global Alzheimer’s disease and related dementias from 1990 to 2021
Authors: Mobaderi Tofigh , Kazemnejad Anoshirvan , Salehi Masoud
Published: July 2024

Alzheimer’s Disease and Related Dementias (ADRD) affect millions of people worldwide, with mortality rates influenced by several risk factors and exhibiting significant heterogeneity across geographical regions. This study aimed to investigate the impact of risk factors on global ADRD mortality patterns from 1990 to 2021, utilizing clustering and modeling techniques. Data on ADRD mortality rates, cardiovascular disease, and diabetes prevalence were obtained for 204 countries from the GBD platform. Additional variables such as HDI, life expectancy, alcohol consumption, and tobacco use prevalence were sourced from the UNDP and WHO. All the data were extracted for men, women, and the overall population. Longitudinal k-means clustering and generalized estimating equations were applied for data analysis. The findings revealed that cardiovascular disease had significant positive effects of 1.84, 3.94, and 4.70 on men, women, and the overall ADRD mortality rates, respectively. Tobacco showed positive effects of 0.92, 0.13, and 0.39, while alcohol consumption had negative effects of − 0.59, − 9.92, and − 2.32, on men, women, and the overall ADRD mortality rates, respectively. The countries were classified into five distinct subgroups. Overall, cardiovascular disease and tobacco use were associated with increased ADRD mortality rates, while moderate alcohol consumption exhibited a protective effect. Notably, tobacco use showed a protective effect in cluster A, as did alcohol consumption in cluster B. The effects of risk factors on ADRD mortality rates varied among the clusters, highlighting the need for further investigation into the underlying causal factors.
Fuzzy random sensitivity analysis for the overall structure reliability of reinforced concrete freezing wellbores in deep alluvium based on hidden Markov model
Authors: Yao Yafeng , Zhu Yan , Li Yongheng , Wang Wei , Zhang Zhemei
Published: July 2024

To address the shortcomings of traditional reliability theory in characterizing the stability of deep underground structures, the advanced first order second moment of reliability was improved to obtain fuzzy random reliability, which is more consistent with the working conditions. The traditional sensitivity analysis model was optimized using fuzzy random optimization, and an analytical calculation model of the mean and standard deviation of the fuzzy random reliability sensitivity was established. A big data hidden Markov model and expectation-maximization algorithm were used to improve the digital characteristics of fuzzy random variables. The fuzzy random sensitivity optimization model was used to confirm the effect of concrete compressive strength, thick-diameter ratio, reinforcement ratio, uncertainty coefficient of calculation model, and soil depth on the overall structural reliability of a reinforced concrete double-layer wellbore in deep alluvial soil. Through numerical calculations, these characteristics were observed to be the main influencing factors. Furthermore, while the soil depth was negatively correlated, the other influencing factors were all positively correlated with the overall reliability. This study provides an effective reference for the safe construction of deep underground structures in the future.
DeepPIG: deep neural network architecture with pairwise connected layers and stochastic gates using knockoff frameworks for feature selection
Authors: Oh Euiyoung , Lee Hyunju
Published: July 2024

Selecting relevant feature subsets is essential for machine learning applications. Among the feature selection techniques, the knockoff filter procedure proposes a unique framework that minimizes false discovery rates (FDR). However, employing a deep neural network architecture for a knockoff filter framework requires higher detection power. Using the knockoff filter framework, we present a Deep neural network with PaIrwise connected layers integrated with stochastic Gates (DeepPIG) for the feature selection model. DeepPIG exhibited better detection power in synthetic data than the baseline and recent models such as Deep feature selection using Paired-Input Nonlinear Knockoffs (DeepPINK), Stochastic Gates (STG), and SHapley Additive exPlanations (SHAP) while not violating the preselected FDR level, especially when the signal of the features were weak. The selected features determined by DeepPIG demonstrated superior classification performance compared with the baseline model in real-world data analyses, including the prediction of certain cancer prognosis and classification tasks using microbiome and single-cell datasets. In conclusion, DeepPIG is a robust feature selection approach even when the signals of features are weak. Source code is available at https://github.com/DMCB-GIST/DeepPIG.
Audio-visual modelling in a clinical setting
Authors: Jiao Jianbo , Alsharid Mohammad , Drukker Lior , Papageorghiou Aris T. , Zisserman Andrew , Noble J. Alison
Published: July 2024

Auditory and visual signals are two primary perception modalities that are usually present together and correlate with each other, not only in natural environments but also in clinical settings. However, audio-visual modelling in the latter case can be more challenging, due to the different sources of audio/video signals and the noise (both signal-level and semantic-level) in auditory signals—usually speech audio. In this study, we consider audio-visual modelling in a clinical setting, providing a solution to learn medical representations that benefit various clinical tasks, without relying on dense supervisory annotations from human experts for the model training. A simple yet effective multi-modal self-supervised learning framework is presented for this purpose. The proposed approach is able to help find standard anatomical planes, predict the focusing position of sonographer’s eyes, and localise anatomical regions of interest during ultrasound imaging. Experimental analysis on a large-scale clinical multi-modal ultrasound video dataset show that the proposed novel representation learning method provides good transferable anatomical representations that boost the performance of automated downstream clinical tasks, even outperforming fully-supervised solutions. Being able to learn such medical representations in a self-supervised manner will contribute to several aspects including a better understanding of obstetric imaging, training new sonographers, more effective assistive tools for human experts, and enhancement of the clinical workflow.
Reduced dynamic changes in pulmonary artery compliance during isometric handgrip exercise in patients with heart failure
Authors: Hashemi Djawid , Hou Xuewen , Doeblin Patrick , Weiß Jakob , Beyer Rebecca , Neye Marthe , Erley Jennifer , Bucius Paulius , Tanacli Radu , Kuehne Titus , Kelm Marcus , Blum Moritz , Edelmann Frank , Kuebler Wolfgang M. , Düngen Hans-Dirk , Schuster Andreas , Stoiber Lukas , Kelle Sebastian
Published: July 2024

Exercise intolerance is a debilitating symptom in heart failure (HF), adversely affecting both quality of life and long-term prognosis. Emerging evidence suggests that pulmonary artery (PA) compliance may be a contributing factor. This study aims to non-invasively assess PA compliance and its dynamic properties during isometric handgrip (HG) exercise in HF patients and healthy controls, using cardiovascular magnetic resonance (CMR). We prospectively enrolled 36 subjects, comprising 17 HF patients (NYHA class II and III) and 19 healthy controls. Participants performed an HG test, and we assessed changes in PA compliance and hemodynamic flow parameters using advanced CMR techniques. We also explored the relationship between CMR-derived PA compliance metrics and established clinical indicators, ensuring the validity of our findings through intra- and interobserver agreements. HF patients had significantly lower resting PA compliance compared to controls (28.9% vs. 50.1%, p < 0.01). During HG exercise, HF patients exhibited a dampened adaptability in PA compliance. Hemodynamic responses, including heart rate and blood pressure, were not significantly different between the groups. Further analyses revealed a significant correlation between changes in PA compliance and functional capacity, and an inverse relationship with NYHA class. Our study demonstrates a marked difference in PA vascular responses during HG exercise between HF patients and healthy controls. The compromised adaptability in PA compliance in HF patients is correlated with diminished functional capacity. These findings have significant clinical implications and may guide future interventional strategies in HF management.
Positive public attitudes towards agricultural robots
Authors: Zeddies Hendrik Hilmar , Busch Gesa , Qaim Matin
Published: July 2024

Robot technologies could lead to radical changes in farming. But what does the public know and think about agricultural robots? Recent experience with other agricultural technologies—such as plant genetic engineering—shows that public perceptions can influence the pace and direction of innovation, so understanding perceptions and how they are formed is important. Here, we use representative data from an online survey (n = 2269) to analyze public attitudes towards crop farming robots in Germany—a country where new farming technologies are sometimes seen with skepticism. While less than half of the survey participants are aware of the use of robots in agriculture, general attitudes are mostly positive and the level of interest is high. A framing experiment suggests that the type of information provided influences attitudes. Information about possible environmental benefits increases positive perceptions more than information about possible food security and labor market effects. These insights can help design communication strategies to promote technology acceptance and sustainable innovation in agriculture.
A recirculating device of cooling water powered by solar energy for the laboratory
Authors: He Jiahui , Deng Wenhao , Zhu Maochun , Máille Gearóid M. Ó. , Wu Zihang , Wang Longsheng , Wei Yongge
Published: July 2024

Aimed at energy conservation and water saving for the lab, we have designed and constructed one kind of lab-scale small recirculating device of cooling water utilizing a water recirculator coupled to a solar energy system via a self-made multifunctional voltage regulator, which is equipped with an active heat radiator and powered by a solar energy system. It can provide cooling water for 1–3 sets of ordinary refluxing setups in series without additional consumption of water and electricity. The temperature difference between the water in the bucket and the environment is less than 4 °C for eight common solvents in single refluxing set-up or three combined refluxing setups with different solvents in series. In the performance assessment experiments for the refluxing of eight common solvents with different boiling point, the largest solvent loss is less than 6% if the condenser is open to the air in the refluxing time of 8 h, but none obvious solvent loss are found if the condensers were equipped with an oil bubbler. Control experiments indicates that the preparation of bromoethane/ethyl acetate/propyl hexanoate using our water recirculator can achieve almost unanimous yields in relative to those reactions using tap water as cooling water.
Electrical integrity and week-long oscillation in fungal mycelia
Authors: Fukasawa Yu , Akai Daisuke , Takehi Takayuki , Osada Yutaka
Published: July 2024

The electrical potential of the mycelia of a cord-forming wood decay fungus, Pholiota brunnescens, was monitored for over 100 days on a plain agar plate during the colonization onto a wood bait. Causality analyses of the electrical potential at different locations of the mycelium revealed a clear and stable causal relationship with the directional flow of the electrical potential from the hyphae at the bait location to other parts of the mycelium. However, this causality disappeared after 60 days of incubation, coinciding with the onset of slow electrical oscillation at the bait location, which occurred over one week per oscillation cycle. We speculated that the hyphae that initially colonized the bait may act as a temporary activity center, which generates electrical signals to other parts of the mycelium, thereby facilitating the colonization of the entire mycelial body to the bait. The week-long electrical oscillation represents the longest oscillation period ever recorded in fungi and warrants further investigation to elucidate its function and stability in response to environmental stimuli.
Reasons why life on Earth rarely makes fluorine-containing compounds and their implications for the search for life beyond Earth
Authors: Petkowski Janusz J. , Seager Sara , Bains William
Published: July 2024

Life on Earth is known to rarely make fluorinated carbon compounds, as compared to other halocarbons. We quantify this rarity, based on our exhaustive natural products database curated from available literature. We build on explanations for the scarcity of fluorine chemistry in life on Earth, namely that the exclusion of the C–F bond stems from the unique physico-chemical properties of fluorine, predominantly its extreme electronegativity and strong hydration shell. We further show that the C–F bond is very hard to synthesize and when it is made by life its potential biological functions can be readily provided by alternative functional groups that are much less costly to incorporate into existing biochemistry. As a result, the overall evolutionary cost-to-benefit balance of incorporation of the C–F bond into the chemical repertoire of life is not favorable. We argue that the limitations of organofluorine chemistry are likely universal in that they do not exclusively apply to specifics of Earth’s biochemistry. C–F bonds, therefore, will be rare in life beyond Earth no matter its chemical makeup.
Shoreline barriers may amplify coastal groundwater hazards with sea-level rise
Authors: Su Xin , Befus Kevin M. , Hummel Michelle A.
Published: July 2024

Subsurface barriers have been proposed to protect coastal aquifers from sea-level rise induced seawater intrusion, but the potential for groundwater emergence near subsurface barriers remains unknown. Here, we investigated how emergence changes groundwater flow conditions and influences the protective performance of subsurface barriers with sea-level rise. We tested the subterranean consequences of sea-level rise for cutoff walls and subsurface dams with cross-shore groundwater flow and salt transport models, investigating how barrier design, aquifer properties, and hydrological conditions control the potential for emergence, groundwater partitioning at the barrier, and seawater intrusion with sea-level rise. We find that most subsurface infrastructure cannot prevent seawater intrusion and emergence simultaneously. Subsurface dams spanning more than half of the aquifer thickness created emergence hazards and subsequent groundwater partitioning for all scenarios tested. Cutoff walls were less effective at reducing seawater intrusion for all opening sizes but could reduce the emergence potential compared to similarly sized subsurface dams. Our results demonstrate the challenging trade-offs in mitigating the coastal groundwater hazards of seawater intrusion and emergence with sea-level rise, where groundwater flooding inland of protective infrastructure would require combinations of subsurface impoundments and other mitigation techniques, such as pumping or drains.
Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI
Authors: Gomez Daniela , Selvaraj Michael Gomez , Casas Jorge , Mathiyazhagan Kavino , Rodriguez Michael , Assefa Teshale , Mlaki Anna , Nyakunga Goodluck , Kato Fred , Mukankusi Clare , Girma Ellena , Mosquera Gloria , Arredondo Victoria , Espitia Ernesto
Published: July 2024

Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring both nutrition and economic stability in diverse communities, particularly in Africa and Latin America. However, CB cultivation poses a significant threat to diseases that can drastically reduce yield and quality. Detecting these diseases solely based on visual symptoms is challenging, due to the variability across different pathogens and similar symptoms caused by distinct pathogens, further complicating the detection process. Traditional methods relying solely on farmers’ ability to detect diseases is inadequate, and while engaging expert pathologists and advanced laboratories is necessary, it can also be resource intensive. To address this challenge, we present a AI-driven system for rapid and cost-effective CB disease detection, leveraging state-of-the-art deep learning and object detection technologies. We utilized an extensive image dataset collected from disease hotspots in Africa and Colombia, focusing on five major diseases: Angular Leaf Spot (ALS), Common Bacterial Blight (CBB), Common Bean Mosaic Virus (CBMV), Bean Rust, and Anthracnose, covering both leaf and pod samples in real-field settings. However, pod images are only available for Angular Leaf Spot disease. The study employed data augmentation techniques and annotation at both whole and micro levels for comprehensive analysis. To train the model, we utilized three advanced YOLO architectures: YOLOv7, YOLOv8, and YOLO-NAS. Particularly for whole leaf annotations, the YOLO-NAS model achieves the highest mAP value of up to 97.9% and a recall of 98.8%, indicating superior detection accuracy. In contrast, for whole pod disease detection, YOLOv7 and YOLOv8 outperformed YOLO-NAS, with mAP values exceeding 95% and 93% recall. However, micro annotation consistently yields lower performance than whole annotation across all disease classes and plant parts, as examined by all YOLO models, highlighting an unexpected discrepancy in detection accuracy. Furthermore, we successfully deployed YOLO-NAS annotation models into an Android app, validating their effectiveness on unseen data from disease hotspots with high classification accuracy (90%). This accomplishment showcases the integration of deep learning into our production pipeline, a process known as DLOps. This innovative approach significantly reduces diagnosis time, enabling farmers to take prompt management interventions. The potential benefits extend beyond rapid diagnosis serving as an early warning system to enhance common bean productivity and quality.
Modeling of scour hole characteristics under turbulent wall jets using machine learning
Authors: Khuntia Jnana Ranjan , Devi Kamalini , Mumtaz Mohd Aamir
Published: July 2024

The novelty of the present study is to investigate the parameters that depict the scour hole characteristics caused by turbulent wall jets and develop new mathematical relationships for them. Four significant parameters i.e., depth of scouring, location of scour depth, height of the dune and location of dune crest are identified to represent a complete phenomenon of scour hole formation. From the gamma test, densimetric Froude number, apron length, tailwater level, and median sediment size are found to be the key parameters that affect these four dependent parameters. Utilizing the previous data sets, Multi Regression Analysis (linear and non-linear) has been performed to establish the relationships between the dependent parameters and influencing independent parameters. Further, artificial neural network-particle swarm optimisation (ANN-PSO) and gene expression programming (GEP) based models are developed using the available data. In addition, results obtained from these models are compared with proposed regression equations and the best models are identified employing statistical performance parameters. The performance of the ANN-PSO model (RMSE = 1.512, R2 = 0.605), (RMSE = 6.644, R2 = 0.681), (RMSE = 6.386, R2 = 0.727) and (RMSE = 1.754, R2 = 0.636) for predicting four significant parameters are more satisfactory than that of regression and other soft computing techniques. Overall, by analysing all the statistical parameters, uncertainty analysis and reliability index, ANN-PSO model shows good accuracy and predicts well as compared to other presented models.
The mediating role of ego depletion in the relationship between state anxiety and academic procrastination among University students
Authors: Fan Junqiang , Cheng Yongjie , Tang Ming , Huang Yuxin , Yu Jingjing
Published: July 2024

The issue of academic procrastination is highly prevalent among university students. It not only has a deterimental effect on students' academic performance but also poses a risk to their physical and mental well-being. Anxiety, as a negative emotion, has attracted researchers’ attention in relation to academic procrastination. Research indicates a correlation between state anxiety and academic procrastination, but the underlying mechanisms that drive this association remain unclear. When individuals experience ego-depletion, it can lead to psychological exhaustion, subsequently leading to procrastination. Gender role conceptions, shaped by sociocultural and psychological mechanisms, have profound implications on individuals’ cognition, emotions, and behaviors. This study primarily aims to explore the relationship between state anxiety and academic procrastination among university students, with a particularly focus on the mediating role of ego-depletion and the moderating role of gender. A survey using the State Anxiety Scale, Ego-Depletion Scale, and Irrational Procrastination Scale was administered to 3370 undergraduates. State anxiety shows positive correlations with ego depletion and academic procrastination (r = 0.665, p < 0.01; r = 0.491, p < 0.01), while ego depletion is also positively linked to academic procrastination (r = 0.500, p < 0.01). State anxiety serves as a positive predictor of academic procrastination, with a confidence interval of 95% [0.626, 0.696]; additionally, ego depletion partially mediates the relationship between state anxiety and academic procrastination, with a confidence interval of 95% [0.168, 0.251]. Gender acts as a moderator in directly predicting the impact of state anxiety on academic procrastination and in the latter stage of mediating the effect of ego depletion. State anxiety can significantly and positively predict academic procrastination among university students. Ego-depletion partially mediates the relationship between state anxiety and academic procrastination. The direct predictive effect of state anxiety on academic procrastination, as well as the mediating role of ego-depletion, is moderated by gender. This provides educators and university students themselves with reference for addressing the issue of academic procrastination.
Edge-enhanced infrared image super-resolution reconstruction model under transformer
Authors: Hu Lei , Hu Long , Chen MingHui
Published: July 2024

Infrared images have important applications in military, security and surveillance fields. However, limited by technical factors, the resolution of infrared images is generally low, which seriously limits the application and development of infrared images in various fields. To address the problem of difficult recovery of edge information and easy ringing effect in the super-resolution reconstruction process of infrared images, an edge-enhanced infrared image super-resolution reconstruction model TESR under transformer is proposed. The main structure of this model is transformer. First, in view of the problem of difficult recovery of edge information of infrared images, an edge detection auxiliary network is designed, which can obtain more accurate edge information from the input low-resolution images and enhance the edge details during image reconstruction; then, the CSWin Transformer is introduced to compute the self-attention of horizontal and vertical stripes in parallel, so as to increase the receptive field of the model and enable it to utilize features with higher semantic levels. The super-resolution reconstruction model proposed in this paper can extract more comprehensive image information, and at the same time, it can obtain more accurate edge information to enhance the texture details of super-resolution images, and achieve better reconstruction results.
Children and adults produce distinct technology- and human-directed speech
Authors: Cohn Michelle , Barreda Santiago , Graf Estes Katharine , Yu Zhou , Zellou Georgia
Published: July 2024

This study compares how English-speaking adults and children from the United States adapt their speech when talking to a real person and a smart speaker (Amazon Alexa) in a psycholinguistic experiment. Overall, participants produced more effortful speech when talking to a device (longer duration and higher pitch). These differences also varied by age: children produced even higher pitch in device-directed speech, suggesting a stronger expectation to be misunderstood by the system. In support of this, we see that after a staged recognition error by the device, children increased pitch even more. Furthermore, both adults and children displayed the same degree of variation in their responses for whether “Alexa seems like a real person or not”, further indicating that children’s conceptualization of the system’s competence shaped their register adjustments, rather than an increased anthropomorphism response. This work speaks to models on the mechanisms underlying speech production, and human–computer interaction frameworks, providing support for routinized theories of spoken interaction with technology.
Unveiling a new oceanic anoxic event at the Norian/Rhaetian boundary (Late Triassic)
Authors: Rigo Manuel , Jin Xin , Godfrey Linda , Katz Miriam E. , Sato Honami , Tomimatsu Yuki , Zaffani Mariachiara , Maron Matteo , Satolli Sara , Concheri Giuseppe , Cardinali Alessandra , Wu Qiangwang , Du Yixing , Lei Jerry Zhen Xiao , van Wieren Connor S. , Tackett Lydia S. , Campbell Hamish , Bertinelli Angela , Onoue Tetsuji
Published: July 2024

The latest Triassic was characterised by protracted biotic extinctions concluding in the End-Triassic Extinction (~ 200 Ma) and a global carbon cycle perturbation. The onset of declining diversity is closely related to reducing conditions that spread globally from upper Sevatian (uppermost Norian) to across the Norian-Rhaetian boundary, likely triggered by unusually high volcanic activity. We correlate significant organic carbon cycle perturbations to an increase of CO2 in the ocean–atmosphere system, likely outgassed by the Angayucham igneous province, the onset of which is indicated by the initiation of a rapid decline in 87Sr/86Sr and 188Os/187Os seawater values. A possible causal mechanism involves elevated CO2 levels causing global warming and accelerating chemical weathering, which increased nutrient discharge to the oceans and greatly increased biological productivity. Higher export production and oxidation of organic matter led to a global O2 decrease in marine water across the Norian/Rhaetian boundary (NRB). Biotic consequences of dysoxia/anoxia include worldwide extinctions in some fossil groups, such as bivalves, ammonoids, conodonts, radiolarians.
Scanpro is a tool for robust proportion analysis of single-cell resolution data
Authors: Alayoubi Yousef , Bentsen Mette , Looso Mario
Published: July 2024

In higher organisms, individual cells respond to signals and perturbations by epigenetic regulation and transcriptional adaptation. However, in addition to shifting the expression level of individual genes, the adaptive response of cells can also lead to shifts in the proportions of different cell types. Recent methods such as scRNA-seq allow for the interrogation of expression on the single-cell level, and can quantify individual cell type clusters within complex tissue samples. In order to identify clusters showing differential composition between different biological conditions, differential proportion analysis has recently been introduced. However, bioinformatics tools for robust proportion analysis of both replicated and unreplicated single-cell datasets are critically missing. In this manuscript, we present Scanpro, a modular tool for proportion analysis, seamlessly integrating into widely accepted frameworks in the Python environment. Scanpro is fast, accurate, supports datasets without replicates, and is intended to be used by bioinformatics experts and beginners alike.
Advanced enhancement technique for infrared images of wind turbine blades utilizing adaptive difference multi-scale top-hat transformation
Authors: He Yinchao , Kang Shuang , Li Wenwen , Xu Hongyan , Liu Sen
Published: July 2024

Enhancing infrared images is essential for detecting wind turbine blades using infrared technology. This paper introduces an Infrared Image Enhancement Method based on Adaptive Iterative Cutoff Threshold Difference Multi-Scale Top-Hat Transformation (AICT-DMTH) to address the challenge of low image clarity in infrared detection. The method involves performing a black-white difference top-hat transformation by utilizing structural elements of varying scales for dilation and erosion. Additionally, an iterative threshold method is applied to extract more detailed image features, followed by setting a cutoff constant to determine the final scale of the structural element. The effectiveness of the proposed method is evaluated both qualitatively and quantitatively, with infrared images from laboratory and wind farm settings enhanced and compared against existing methods. The experimental results indicate that the proposed method significantly improves the clarity of infrared images, demonstrating robustness in enhancing images from various environments.
Production and stability of cultured red blood cells depends on the concentration of cholesterol in culture medium
Authors: Claessen M. J. A. G. , Yagci N. , Fu K. , Brandsma E. , Kersten M. J. , von Lindern M. , van den Akker E.
Published: July 2024

The production of cultured red blood cells (cRBC) for transfusion purposes requires large scale cultures and downstream processes to purify enucleated cRBC. The membrane composition, and cholesterol content in particular, are important during proliferation of (pro)erythroblasts and for cRBC quality. Therefore, we tested the requirement for cholesterol in the culture medium during expansion and differentiation of erythroid cultures with respect to proliferation, enucleation and purification by filtration. The low cholesterol level (22 µg/dl) in serum free medium was sufficient to expand (pro)erythroblast cultures. Addition of 2.0 or 5.0 mg/dL of free cholesterol at the start of differentiation induction inhibited enucleation compared to the default condition containing 3.3 mg/dl total cholesterol derived from the addition of Omniplasma to serum free medium. Addition of 5.0 mg/dl cholesterol at day 5 of differentiation did not affect the enucleation process but significantly increased recovery of enucleated cRBC following filtration over leukodepletion filters. The addition of cholesterol at day 5 increased the osmotic resistance of cRBC. In conclusion, cholesterol supplementation after the onset of enucleation improved the robustness of cRBC and increased the yield of enucleated cRBC in the purification process.
The limited role of serum neurofilament light chain in predicting pain severity of patients with diabetic polyneuropathy
Authors: Kim A-Sol , Lee Jong-Mok
Published: July 2024

Pain is one of many complaints expressed by patients with diabetic polyneuropathy. However, no objective measure for pain severity has been available. Neurofilament light chains have been widely used for assessing axonal damage in the neuronal system. Hence, we sought to investigate whether neurofilament light chains can serve as a marker reflecting pain severity in diabetic polyneuropathy. We enrolled the patients with diabetic polyneuropathy. Serum concentrations of neurofilament light chain were then measured using a single-molecule array. Pain severity was evaluated using painDETECT and the Brief Pain Inventory. Moreover, laboratory results including, serum creatinine, HbA1c, and glomerular filtration rate. A correlation test was used to analyze each variable. A total of 42 patients were enrolled. Neurofilament light chain levels were unable to reflect current neuropathic pain severity. However, high levels of neurofilament light chain were a significant predictor of poor diabetes control (r = 0.41; p = 0.02) and kidney damage (r = 0.45; p = 0.01). Serum levels of neurofilament light chain could not reflect current pain severity but was strongly associated with kidney dysfunction and poor diabetes control. Other biomarkers that could predict pain severity need to be uncovered.
LILRB4 knockdown inhibits aortic dissection development by regulating pyroptosis and the JAK2/STAT3 signaling pathway
Authors: Xiong Jianxian , Ling Jiayuan , Yan Jie , Duan Yanyu , Yu Junjian , Li Wentong , Yu Wenbo , Gao Jianfeng , Xie Dilin , Liu Ziyou , Deng Yongzhi , Liao Yongling
Published: July 2024

Aortic dissection (AD) is a life-threatening condition with a high mortality rate and without effective pharmacological therapies. Our previous study illustrated that leukocyte immunoglobulin-like receptor B4 (LILRB4) knockdown promoted the contractile phenotypic switch and apoptosis of AD cells. This study aimed to further investigate the role of LILRB4 in animal models of AD and elucidate its underlying molecular mechanisms. Animal models of AD were established using 0.1% beta-aminopropionitrile and angiotensin II and an in vitro model was developed using platelet-derived growth factor BB (PDGF-BB). The effects of LILRB4 knockdown on histopathological changes, pyroptosis, phenotype transition, extracellular matrix (ECM), and Janus kinase 2 (JAK2)/signal transducers and activators of transcription 3 (STAT3) pathways were assessed using a series of in vivo and in vitro assays. The effects of the JAK2 inhibitor AG490 on AD cell function, phenotypic transition, and ECM were explored. LILRB4 was highly expressed in AD and its knockdown increased survival rate, reduced AD incidence, and alleviated histopathological changes in the AD mouse model. Furthermore, LILRB4 knockdown promoted contractile phenotype switch, stabilized the ECM, and inhibited pyroptosis. Mechanistically, LILRB4 knockdown inhibited the JAK2/STAT3 signaling pathway. JAK2 inhibitor AG490 inhibited cell viability and migration, enhanced apoptosis, induced G0/G1 cell cycle arrest, and suppressed S-phase progression in PDGF-BB-stimulated human aortic smooth muscle cells. LILRB4 knockdown suppresses AD development by inhibiting pyroptosis and the JAK2/STAT3 signaling pathway.
Investigation on the molecular mechanism of SPA interference with osteogenic differentiation of bone marrow mesenchymal stem cells
Authors: Wen Hong-jie , Zhu Shou-yan , Yang Hua-gang , Guo Feng-yong
Published: July 2024

Binding of Staphylococcus aureus protein A (SPA) to osteoblasts induces apoptosis and inhibits bone formation. Bone marrow-derived mesenchymal stem cells (BMSCs) have the ability to differentiate into bone, fat and cartilage. Therefore, it was important to analyze the molecular mechanism of SPA on osteogenic differentiation. We introduced transcript sequence data to screen out differentially expressed genes (DEGs) related to SPA-interfered BMSC. Protein–protein interaction (PPI) network of DEGs was established to screen biomarkers associated with SPA-interfered BMSC. Receiver operating characteristic (ROC) curve was plotted to evaluate the ability of biomarkers to discriminate between two groups of samples. Finally, we performed GSEA and regulatory analysis based on biomarkers. We identified 321 DEGs. Subsequently, 6 biomarkers (Cenpf, Kntc1, Nek2, Asf1b, Troap and Kif14) were identified by hubba algorithm in PPI. ROC analysis showed that six biomarkers could clearly discriminate between normal differentiated and SPA-interfered BMSC. Moreover, we found that these biomarkers were mainly enriched in the pyrimidine metabolism pathway. We also constructed '71 circRNAs-14 miRNAs-5 mRNAs' and '10 lncRNAs-5 miRNAs-2 mRNAs' networks. Kntc1 and Asf1b genes were associated with rno-miR-3571. Nek2 and Asf1b genes were associated with rno-miR-497-5p. Finally, we found significantly lower expression of six biomarkers in the SPA-interfered group compared to the normal group by RT-qPCR. Overall, we obtained 6 biomarkers (Cenpf, Kntc1, Nek2, Asf1b, Troap, and Kif14) related to SPA-interfered BMSC, which provided a theoretical basis to explore the key factors of SPA affecting osteogenic differentiation.