bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patterns of aquatic nonindigenous species introductions and spread in the Ohio River basin in relation to policy milestones
Authors: Clasgens Abigail Nicole , Murry Brent , Zipp Kaylyn , Arantes Caroline , Neilson Matthew 
Published: July 2024

Abstract

Aquatic invasive species (AIS) create costly and detrimental effects when they become established. Recognition of these severe negative impacts in the United States reached a critical threshold in 1990 with the federal passage of the Nonindigenous Aquatic Nuisance Prevention and Control Act, which created six regional panels, the national Aquatic Nuisance Species Task Force, and incentivized state-level AIS planning. The management of the Ohio River basin fell under the Mississippi River Basin Panel and the state-led Mississippi Interstate Cooperative Resource Association, which collectively developed a joint action plan in 2010 to prevent, contain, and manage aquatic nuisance and invasive species. Similarly, except for West Virginia, all Ohio River basin states created aquatic nuisance species plans between 1999 and 2021. We use the USGS Nonindigenous Aquatic Species (NAS) database to examine how these legislative and planning milestones have influenced the rate of new NAS arrivals and the spread of existing and new NAS. Arrival and spread of NAS were assessed at the HUC-8 scale (8-digit hydrological unit code) along the Ohio, Wabash, Cumberland, Alleghany, Monongahela, and Tennessee rivers. We found a near-linear increase of new NAS across all rivers and no apparent change related to policy milestones. We also found that most NAS species (35–55%) remained local, not spreading beyond the HUC they were first detected in, while less than 10% spread to all HUCs within a river. Establishing coordinated local and regional monitoring programs will help to contain future invasive species.
Exploring the Impact of Missing Data on Maternal Tobacco Program Results: An Analysis of Self-Efficacy on Smoking Cessation
Authors: Zhao Mengting , Langworthy Benjamin 
Published: July 2024

Abstract

Background: Tobacco use is a major contributor to chronic illnesses worldwide, leading to significant morbidity and mortality. Effective tobacco cessation programs are crucial in reducing the health risks associated with smoking. This study aims to investigate the relationship between confidence scores, indicating individuals’ confidence in quitting smoking on a scale of 0 to 10, and carbon monoxide (CO) levels over time among participants in the North Dakota State Department of Health Maternal Tobacco Program.
Methods: We analyzed data from 226 participants using linear mixed-effects models and accounted for missing data using complete case analysis, multiple imputation under a missing at random (MAR) assumption, and multiple imputation under a missing not at random (MNAR) assumption with various delta-adjustment values. This MNAR assumption is considered because we believe patients who resume smoking may be less likely to return for follow-up visits.
Results: The findings suggest that higher confidence scores at the first prenatal visit were associated with lower CO levels, and this effect attenuated over time. This indicates that participants with higher confidence scores were less likely to smoke. Our results remained consistent under different missing data assumptions for prenatal visits, including MAR and MNAR mechanisms. The postpartum dataset yielded similar results.
Conclusion: Our study highlights the importance of evaluating participants’ self-assessed confidence during their initial baseline visit. The findings indicate that patients with lower confidence scores are at an increased risk of discontinuing their participation in the program.
Inertial microfluidic mixer for biological CubeSat missions
Authors: Graja Adrianna , Gumieniak Mateusz , Dzimira Maciej , Janisz Tymon , Krakos Agnieszka 
Published: July 2024

Abstract

Nanosatellites of CubeSat type due to, i.a., minimized costs of space missions, as well as the potential large application area, have become a significant part of the space economy sector recently. The opportunity to apply miniaturized microsystem (MEMS) tools in satellite space missions further accelerates both the space and the MEMS markets, which in the coming years are considered to become inseparable. As a response to the aforementioned perspectives, this paper presents a microfluidic mixer system for biological research to be conducted onboard CubeSat nanosatellites. As the high complexity of the space systems is not desired due to the need for failure-free and remotely controlled operation, the principal concept of the work was to design an entirely passive micromixer, based on lab-on-chip technologies. For the first time, the microfluidic mixer that uses inertial force generated by rocket engines during launch to the orbit is proposed to provide an appropriate mixing of liquid samples. Such a solution not only saves the space occupied by standard pumping systems, but also reduces the energy requirements, ultimately minimizing the number of battery modules and the whole CubeSat size. The structures of the microfluidic mixers were fabricated entirely out of biocompatible resins using MultiJet 3D printing technology. To verify the functionality of the passive mixing system, optical detection consisting of the array of blue LEDs and phototransistors was applied successfully. The performance of the device was tested utilizing an experimental rocket, as a part of the Spaceport America Cup 2023 competition.
Underwater acoustic azimuth angle estimation with a millimetre diameter flexible hydrophone towed array
Authors: Wu Su , Huang Junbin , Pang Yandong , Zhu Miao , Gu Hongcan 
Published: July 2024

Abstract

This paper investigates a millimetre diameter hydrophone towed array cable for acoustic direction finding. The mechanism of the underwater acoustic waves received by this linear array without any mandrel structure is deduced and it is demonstrated that the amplitude of its response varies with the direction of the sound wave. An anechoic pool experiment is carried out to test the performance of such a hydrophone array. The hydrophone unit consists of a sensing fiber between adjacent UWFBGs, coiled into 9 cm diameter fiber rings, with arbitrary 6 fiber rings, called a 6-element hydrophone array, suspended horizontally in the sound-absorbing wedge to receive acoustic signals. An average sensitivity of − 141.2 dB re rad/µPa at frequencies from 2.5 kHz to 6.3 kHz was achieved. Direction detection at an angle of 75° is realised, validating the detection of the azimuth of underwater acoustic waves. The ultra-thin towing cable system, with free structure, high sensitivity and underwater target detection capability that it has demonstrated has great potential for future Unmanned Underwater Vehicle (UUV) applications.
Dielectric behaviour of succinic acid doped Polyvinyl Alcohol (PVA)
Authors: Kumari Anita , Kumar Sandeep , Kant Ravi , ansari mohammed fahim 
Published: July 2024

Abstract

The present paper reports the dielectric behaviour of high molecular weight water soluble polyvinyl alcohol (PVA) system doped with a dicarboxylic acid (succinic acid). Doped PVA samples were synthesized in the laboratory using solution casting method by changing the concentration of succinic acid (0, 10, 20, 30, 40 and 50 wt%) in PVA solution. These samples were characterised for their structural behaviour using FT-IR and XRD while dielectric measurements were done at a fixed frequency of 100Hz, 120 Hz, 1 kHz, 10kHz, 20 kHz and 100 kHz from room temperature to 65oC (< Tg=80oC of PVA). It was observed that dielectric permittivity (∈′) of 30wt% acid doped PVA significantly increased compared to undoped PVA. However, dielectric permittivity decreased with further rise in dopant content (> 30 wt%). At all frequencies, room temperature dielectric properties (∈′ and ∈′′) of both undoped and doped samples showed a frequency dispersive behaviour.
Genetic variation perspective reveals potential drug targets for subtypes of endometrial cancer
Authors: Zhu Jiamei , Chen Youguo , Zhang Ting , Jiang Juan , Xia Nan 
Published: July 2024

Abstract

The study aims to identify potential drug targets for subtypes of endometrial cancer through a Mendelian randomization study and analyze their clinical value. Data from three quantitative trait loci and Genome-wide association studies (GWAS) Meta-analysis study explored potential drug targets in endometrial cancers (including endometrioid and non-endometrioid). Complementary analysis (including network analysis, therapeutic efficacy analysis, gene differential expression, and prognosis analysis) was investigated. Furthermore, immunohistochemical staining and clinical pathological features were explored to validate potential clinical significance. Five drug targets for endometrial carcinomas, seven drug targets for endometrioid histology, and seven drug targets for non-endometrioid histology were identified, with IGF2R (OR = 1.165; 95% CI 1.067–1.272; p = 1.046 × 10− 2) and CST3 (OR = 0.523; 95% CI 0.339–0.804; p = 7.010×10− 3) demonstrating core therapeutic potential supported by causal evidence at the transcriptional, translational, and tissue-specific levels. Our research explored potential therapeutic targets associated with endometrial cancer and provided new ideas for biomarker screening and drug development.
Assessment of Heavy Metal Pollution and Human Health Risks Associated with Etroplus suratensis (Green Chromide) in Koggala Lagoon, Sri Lanka
Authors: Abeysooriya APSW , Bandara EGKYC , Sanjaya HLK , Jye Mok Wen , Patabandi PPSK , Mejjad Nezha , Sung Yeong Yik , Wijesinghe RDN 
Published: July 2024

Abstract

Fish have long been identified as good indicators for scientific studies particularly to examine heavy metal pollution in aquatic environments and its associated human health risks. This study assesses the accumulation of heavy metals in different tissues of the food fish Etroplus suratensis (Green Chromide) collected from Koggala lagoon, Sri Lanka. We quantified the concentrations of the four heavy metal ions; Cu2+, Cd3+, Pb2+, and Cr3+ across distinct tissues including skin, liver, gill, and flesh in fish in varying sizes using Atomic Absorption Spectrophotometer (AAS). Samples comprised thirty-six (n=36) fish from three different locations in the lagoon; the area near the KEPZ (L1), the middle of the lagoon (L2), and the area near the cultivation site (L3). The highest concentrations of heavy metals were found in the flesh and skin, while the lowest were observed in the gills. The range of heavy metal concentrations (g/g) in the body tissue varied by fish size; for small-sized fish, Cu (0.0443-0.6210), Cd (0.0110-0.0214), Pb (below detection level-0.46), and Cr (below detection level-39.633); for medium-sized fish, Cu (0.0713-0.6210), Cd (0.0134-0.0170), Pb (below detection level-40.906), and Cr (0.0014-0.0500) and for larger-sized fish, Cu (0.0553-0.345), Cd (0.0110-0.0256), Pb (0.0204-0.2103) and Cr (0.0194-0.0773). The levels of Cd, Cr, and Pb in the flesh tissues of E. suratensis flesh tissues were below the FAO’s recommended standards, however, the nontoxic heavy metal Cu exceeded these limits. Given the bioaccumulation and biomagnification of the studied heavy metals and the consumption of E. suratensis in the Koggala lagoon, regular monitoring is essential to ensure consumer safety.
Contributing to an evidence-based discourse regarding invasibility, stage of invasion and impacts of Robinia pseudoacacia L. in European forests
Authors: Mateo Hernández , Alberdi Iciar , Adame Patricia , Cañellas Isabel , Moreno-Fernández Daniel 
Published: July 2024

Abstract

Robinia pseudoacacia L. (black locust) is a deciduous tree native to North America, widely introduced and naturalized in Europe. Despite being one of the world's most invasive woody angiosperms, its role in European forest policy remains contentious, with debates about its invasion potential, ecological impacts, and control measures and it is not formally classified as invasive in European regulation. This study uses data from three cycles of the Spanish National Forest Inventory (SFI) to examine the distribution, abundance, and dominance of black locust in Spanish forests over the past three decades. The study also assesses the invasibility and invasion stage across various forest types, identifying the biotic and abiotic factors influencing its distribution. Additionally, the impacts of black locust on forest ecosystem services, such as native tree species diversity and abundance, are evaluated. Black locust now occupies over 75,000 hectares of Spanish woodlands, with an average invasion degree of 1.55% at the forest type level. Its population has steadily increased, reaching an established invasion stage in most invaded native forests. The invasion affects forest attributes, including native species abundance and dominance, and overall plot richness. The impact varies with the degree of invasibility and invasion stage, being particularly significant in priority conservation habitats like depleted temperate and alluvial forests. These findings highlight the need for further research on black locust impacts in forest ecosystems to contribute to an evidence-based discourse regarding the reconsideration as an invasive species in European and national regulations.
SynSimPred: Leveraging Cell Line Similarities for Drug Combination Synergy Prediction
Authors: Zakeri Soodabeh , Meybodi Fatemeh Yassaee , Eslahchi Changiz 
Published: July 2024

Abstract

Cancer treatment faces significant challenges, necessitating innovative approaches to predict and enhance drug efficacy. Computational models, particularly advanced machine learning methods, have shown promise in customizing drug response predictions and improving patient outcomes. However, predicting synergistic drug combinations remains complex due to the vast number of potential interactions and the limitations of both data availability and traditional research methodologies. In response, our study introduces SynSimPred, a computational approach that leverages cell line similarities, gene expression, mutations, dependencies, and copy number variations to predict drug synergy scores. SynSimPred employs a suite of sophisticated regression methodologies to navigate the complex interplay between these biological characteristics and their impact on drug efficacy. A key component of our research involved a detailed case study where SynSimPred predicted the synergistic and antagonistic interactions of drug pairs such as Vinblastine and Veliparib, and Deforolimus and Dactolisib, demonstrating its practical utility and accuracy in real-world scenarios. We rigorously evaluated SynSimPred against leading methods including DeepSynergy, HypergraphSynergy, and SynPred, across two comprehensive datasets, O'NEIL and ALMANAC. Our evaluations, using metrics such as MSE, Precision, F-Measure, and Accuracy, demonstrate that SynSimPred consistently outperforms existing models, establishing it as a frontrunner in the field of predictive methodologies for cancer treatment.
A New Initial Distribution for Quantum Generative Adversarial Networks to Load Probability Distributions
Authors: Sano Yuichi , Koga Ryosuke , Abe Masaya , Nakagawa Kei 
Published: July 2024

Abstract

Quantum computers are gaining attention for their ability to solve certain problems faster than classical computers, and one example is the quantum expectation estimation algorithm that accelerates the widely-used Monte Carlo method in fields such as finance.
A previous study has shown that quantum generative adversarial networks(qGANs), a quantum circuit version of generative adversarial networks(GANs), can generate the probability distribution necessary for the quantum expectation estimation algorithm in shallow quantum circuits.
However, a previous study has also suggested that the convergence speed and accuracy of the generated distribution can vary greatly depending on the initial distribution of qGANs' generator.
In particular, the effectiveness of using a normal distribution as the initial distribution has been claimed, but it requires a deep quantum circuit, which may lose the advantage of qGANs.

Therefore, in this study, we propose a novel method for generating an initial distribution that improves the learning efficiency of qGANs.
Our method uses the classical process of {\it label replacement} to generate various probability distributions in shallow quantum circuits.
We demonstrate that our proposed method can generate the log-normal distribution, which is pivotal in financial engineering, as well as the triangular distribution and the bimodal distribution, more efficiently than current methods.

Additionally, we show that the initial distribution proposed in our research is related to the problem of determining the initial weights for qGANs.
IKKβ inhibits cognitive memory and adult hippocampal neurogenesis via the β-catenin pathway
Authors: Seong Kyung-Joo , Mun Bo-Ram , Kim Shintae , Choi Won-Seok , Lee Sung Joong , Jung Ji-Yeon , Kim Won-Jae 
Published: July 2024

Abstract

The role of IκB kinase β (IKKβ) and its underlying mechanism in regulating cognitive memory and hippocampal neurogenesis were investigated using GFAP-CreERT2/IKKβflox/flox transgenic mice, where the IKKβ gene is specifically knocked down in hippocampal neural stem cells (NSCs) to generate IKKβ conditional knockdown (cKD) mice. Our findings indicate that IKKβ cKD led to increased exploratory activity in the open-field test, promoted hyperactivity in the Y-maze test, and enhanced spatial learning and memory function in the object location and the Morris water maze tests. Furthermore, IKKβ cKD increased the proliferation of adult hippocampal NSCs by upregulating positive cell cycle regulators through the inhibition of negative cell cycle regulators. Neuronal differentiation of adult hippocampal NSCs was also increased by IKKβ cKD, affecting β-catenin signaling and Neurogenic differentiation 1. Additionally, IKKβ cKD enhanced NSC survival, as indicated by decreased cleaved caspase-3 levels and diminished Bax and Cytochrome c expression in the hippocampal dentate gyrus. These findings indicate that in hippocampal NSCs, IKKβ inhibits locomotion, cognitive function, and adult hippocampal neurogenesis by suppressing the β-catenin signaling pathway. Our findings highlight a key role for IKKβ in the inhibition of cognitive function and decrease in hippocampal neurogenesis through NF-κB signaling in adult NSCs.
Noise Mitigation An Efficient Approach for Quantum Convolutional Neural Networks to Enhance Performance in NISQ
Authors: Ding Yuze , Zhang Shibin , Li Xiaoyu , Chang Yan , Yan Lili 
Published: July 2024

Abstract

Quantum machine learning has achieved great success in many areas of image classification, however, in the Noisy Intermediate-Scale Quantum (NISQ) era, most of the quantum machine learning experimental results are obtained from simulations on classical computers, and most of the experimental environments do not take into account the detrimental effects of quantum noise on quantum classifiers. In fact, the prevalent quantum noise, such as Depolarization, Phase flip, etc., has the potential to significantly undermine the classification performance of quantum circuits. Addressing the challenge of mitigating the disturbing impact of quantum noise on quantum neural networks has become a prominent research focus in recent years. In this paper, we propose a Noise Mitigation method based on the image classification task, which is deployed on the constructed quantum convolutional neural network with noise, aiming to improve the classification accuracy by using Noise Mitigation to reduce the expressibility of quantum circuits. The designed Noise Mitigation method can adjust the parameters according to the complexity of the circuit to achieve better results. Numerical simulations conducted on the MNIST and Fashion-MNIST datasets substantiate the efficacy of the proposed methodology.
MCANet: A lightweight action recognition network with multidimensional convolution and attention
Authors: Tian Qiuhong , Miao Weilun , Zhang Lizao , Yang Ziyu , Yang Yu , Zhao Yanying , Yao Lan 
Published: July 2024

Abstract

The majority of lightweight networks currently employed in action recognition tasks are based on convolutional neural networks. The spatial inductive biases of convolutional neural networks, which enables them to complete action recognition tasks with fewer parameters and faster reasoning speeds. Although convolutional neural networks are highly effective at extracting local spatiotemporal features, they lack the global spatiotemporal modelling capabilities of transformer-based networks. However, the transformer-based network has a considerable number of model parameters and a relatively slow inference time, which makes it incompatible with the lightweight requirements. In order to meet the requirements of both lightweight design and high recognition accuracy, this paper proposes MCANet, an action recognition network that is suitable for deployment on lightweight devices. MCANet integrates the strengths of convolutional neural networks and transformer-based networks. Furthermore, the network maintains a low number of model parameters and a fast reasoning speed, while also exhibiting local and global spatiotemporal modelling capabilities, thus achieving high recognition accuracy. The efficacy of the proposed methodology was validated on a diverse array of datasets, including Kinetics400, UCF101, and HMDB51, demonstrate the effectiveness of the proposed method.
Single cell regulatory architecture of human pancreatic islets suggests sex differences in β cell function and the pathogenesis of type 2 diabetes.
Authors: Mauvais-Jarvis Franck 
Published: July 2024

Abstract

Type 2 and type 1 diabetes (T2D, T1D) exhibit sex differences in insulin secretion, the mechanisms of which are unknown. We examined sex differences in human pancreatic islets from 52 donors with and without T2D combining single cell RNA-seq (scRNA-seq), single nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq), hormone secretion, and bioenergetics. In nondiabetic (ND) donors, sex differences in islet cells gene accessibility and expression predominantly involved sex chromosomes. Islets from T2D donors exhibited similar sex differences in sex chromosomes differentially expressed genes (DEGs), but also exhibited sex differences in autosomal genes. Comparing β cells from T2D vs. ND donors, gene enrichment of female β cells showed suppression in mitochondrial respiration, while male β cells exhibited suppressed insulin secretion. Thus, although sex differences in gene accessibility and expression of ND β cells predominantly affect sex chromosomes, the transition to T2D reveals sex differences in autosomes highlighting mitochondrial failure in females.
Circulating microclots are structurally associated with Neutrophil Extracellular Traps and their amounts are strongly elevated in long COVID patients
Authors: Pretorius Etheresia , THIERRY Alain , Sanchez Cynthia , Ha Tram , Pastor Brice , Mirandola Alexia , Pisareva Ekaterina , Prevostel Corinne , Laubscher Gert , Usher Tom , Venter Chantelle , Turner Simone , Waters Maxine , Kell Douglas 
Published: July 2024

Abstract

BACKGROUND: The persistence of vasculo-thrombotic complications has been put forward as a possible contributing factor in the long COVID (LC) syndrome.
OBJECTIVES: Given the recently reported separate demonstration of the association of LC with elevated levels of fibrin amyloid microclots (FAM) and with those neutrophil extracellular traps (NETs), markers that are linked to thromboinflammation, this study considers the association of FAM with NETs.
RESULTS: The results show that NETs markers are quantitatively and structurally associated with the size and number of FAM in patients with LC. These markers showed a strong diagnostic performance, both independently and when combined.
CONCLUSIONS: Our study revealed that NETs may be a component of circulating FAM, We suggest that higher NETs formation promotes the stabilization of FAM in the circulation, leading to deleterious effects which contribute causally to the LC syndrome.