bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Correlation-Redundancy Guided Evolutionary Algorithm and Its Application to High-Dimensional Feature Selection in Classification
Authors: Sun Xiang , Guo Shunsheng , Liu Shiqiao , Guo Jun , Du Baigang 
Published: March 2024

AbstractThe processing of high-dimensional datasets has become unavoidable with the development of information technology. Most of the literature on feature selection (FS) of high-dimensional datasets focuses on improvements in search strategies, ignoring the characteristics of the dataset itself such as the correlation and redundancy of each feature. This could degrade the algorithm's search effectiveness. Thus, this paper proposes a correlation-redundancy guided evolutionary algorithm (CRGEA) to address high-dimensional FS with the objectives of optimizing classification accuracy and the number of features simultaneously. A new correlation-redundancy assessment method is designed for selecting features with high relevance and low redundancy to speed up the entire evolutionary process. In CRGEA, a novel initialization strategy combined with a multiple threshold selection mechanism is developed to produce a high-quality initial population. A local acceleration evolution strategy based on a parallel simulated annealing algorithm and a pruning method is developed, which can search in different directions and perform deep searches combing the annealing stage around the best solutions to improve the local search ability. Finally, the comparison experiments on 16 public high-dimensional datasets verify that the designed CRGEA outperforms other state-of-the-art intelligent algorithms. The CRGEA can efficiently reduce redundant features while ensuring high accuracy.
A Novel Boundary-Guided Global Feature Fusion Module for Instance Segmentation
Authors: Gao Linchun , Wang Shoujun , Chen Songgui 
Published: March 2024

AbstractThe task of instance segmentation is widely acknowledged as being one of the most formidable challenges in the field of computer vision. Current methods have low utilization of boundary information, especially in dense scenes with occlusion and complex shapes of object instances, the boundary information may become ineffective. This results in coarse object boundary masks that fail to cover the entire object. To address this challenge, we are introducing a novel method called boundary-guided global feature fusion (BGF) which is based on the Mask R-CNN network. We designed a boundary branch that includes a Boundary Feature Extractor (BFE) module to extract object boundary features at different stages. Additionally, we constructed a binary image dataset containing instance boundaries for training the boundary branch. We also trained the boundary branch separately using a dedicated dataset before training the entire network. We then input the Mask R-CNN features and boundary features into a feature fusion module where the boundary features provide shape information needed for detection and segmentation. Finally, we use a global attention module (GAM) to further fuse features. Through extensive experiments, we demonstrate that our approach outperforms state-of-the-art instance segmentation algorithms, producing finer and more complete instance masks while also improving model capability.
Optimum Currency Area in the Eurozone
Authors: Beck Krzysztof , Okhrimenko Iana 
Published: March 2024

Abstract
We used a Bayesian dynamic factor model (BDFM) to examine the share of variance explained by the European and country factors for 59 regions in Eurozone countries in the period from 1992 to 2020. The BDFM output facilitated the construction of a criterion that enables the assessment of the cost of participation in the European Monetary Union, which is directly related to the optimum currency area theory. Over the examined period, we observed business cycle divergence, with 46 regions experiencing a drop in the share of variance explained by the European factor from 1992–2005 to 2006–2020. However, the analysis over shorter time spans demonstrated that all the regions decoupled from the European business cycle. The results contradict the predictions of "The European Commission View". On the one hand, two predictions stemming from "The Krugman View" are supported by the results: the European regions experienced a slight increase in sectoral specialization, and they experienced business cycle divergence. On the other hand, the data does not support the notion that the ongoing specialization was the underlying cause of this divergence.
Enhancing phenotyping efficiency in faba bean breeding: integrating UAV imaging and machine learning
Authors: Mohammadi Shirin , Uhlen Anne Kjersti , Lillemo Morten , Ergon Åshild , Shafiee Sahameh 
Published: March 2024

AbstractUnmanned aerial vehicles (UAVs) equipped with high-resolution imaging sensors have shown great potential for plant phenotyping in agricultural research. This study aimed to explore the potential of UAV-derived red–green–blue (RGB) and multispectral imaging data for estimating classical phenotyping measures such as plant height and predicting yield and chlorophyll content (indicated by SPAD values) in a field trial of 38 faba bean (Vicia faba L.) cultivars grown at four replicates in south-eastern Norway. To predict yield and SPAD values, Support Vector Regression (SVR) and Random Forest (RF) models were utilized. Two feature selection methods, namely the Pearson correlation coefficient (PCC) and sequential forward feature selection (SFS), were applied to identify the most relevant features for prediction. The models incorporated various combinations of multispectral bands, indices, and UAV-based plant height values at four different faba bean development stages. The correlation between manual and UAV-based plant height measurements revealed a strong agreement with a correlation coefficient (R2) of 0.97. The best prediction of SPAD value was achieved at BBCH 50 (flower bud present) with an R2 of 0.38 and RMSE of 1.14. For yield prediction, BBCH 60 (first flower open) was identified as the optimal stage, using spectral indices yielding an R2 of 0.83 and RMSE of 0.53 tons/ha. This development stage presents an opportunity to implement targeted management practices to enhance yield. The integration of UAVs equipped with RGB and multispectral cameras, along with machine learning algorithms, proved to be an accurate approach for estimating agronomically important traits in faba bean. This methodology offers a practical solution for rapid and efficient high-throughput phenotyping in faba bean breeding programs.
Performance evaluation of a quantum-resistant Blockchain: a comparative study with Secp256k1 and Schnorr
Authors: Sinai Nday Kabulo , In Hoh Peter 
Published: March 2024

AbstractPopular Secp256k1 and Schnorr algorithms offer strong security in current Blockchains. However, they are vulnerable to quantum attacks. To solve this problem, several quantum-resistant algorithms have been proposed. However, the performance evaluations and tangible analyses of these algorithms on current Blockchains have not been studied yet. In this context, a performance analysis of quantum-resistant algorithms on a Blockchain can provide valuable insight into the efficiency of quantum-resistant algorithms in real-world scenarios. To address this need, we prototyped and analyzed a quantum-resistant Blockchain using the Falcon algorithm. Falcon is selected because it provides smaller signature and key size compared to Crystals-Dilithium and Sphincs+. We then measured in real-time the key size, transaction signature size, and transaction verification time. The paper also discusses the potential scalability limitations of the proposed quantum-resistant Blockchain and suggests an approach to select quantum-resistant algorithms based on different Blockchain use cases. Our approach and benchmark results have implications for the future development and adoption of quantum-resistant Blockchains.
Description and molecular data of a new cestode parasite, Cladotaenia anomala n. sp. (Paruterinidae) from the Australasian harrier (Circus approximans Peale) in New Zealand
Authors: Presswell Bronwen , Bennett Jerusha 
Published: March 2024

AbstractCurrently comprising 12 species infecting the gastrointestinal tracts of diurnal raptors (Falconiformes, Accipitriformes), species of Cladotaenia are diagnosed by their branching uterus, testes in two fields reaching the same level anteriorly, and small rostellum armed with taenioid hooks arranged in two rows. In this study we describe a new species of Cladotaenia recovered from a number of Australasian harriers Circus approximans, from the southern half of South Island, New Zealand. The new species is distinguished from other species by its single circle of hooks. It is closest, morphologically, to C. circi, but differs in the shape of the terminal proglottids and the number of uterine branches. Sequences of 28S and cox1 gene are presented. Genetically, Cladotaenia anomalan. sp. is closest to Cladotaenia globifera but differs morphologically in the size of the suckers, testes and eggs. This description constitutes the first record of a Cladotaenia species in New Zealand. We discuss some potential routes this parasite may have taken to arrive in New Zealand.
The structural–functional-connectivity coupling of the aging brain
Authors: Zhang Hui , Cao Peng , Mak Henry K. F. , Hui Edward S. 
Published: March 2024

AbstractAging primarily affects memory and executive functions, a relationship that may be underpinned by the fact that almost all adults over 60 years old develop small vessel disease (SVD). The fact that a wide range of neuropathologies could only explain up to 43% of the variation in age-related cognitive impairment suggests that other factors, such as cognitive reserve, may play a role in the brain’s resilience against aging-related cognitive decline. This study aims to examine the relationship between structural–functional-connectivity coupling (SFC), and aging, cognitive abilities and reserve, and SVD-related neuropathologies using a cohort of n = 176 healthy elders from the Harvard Aging Brain Study. The SFC is a recently proposed biomarker that reflects the extent to which anatomical brain connections can predict coordinated neural activity. After controlling for the effect of age, sex, and years of education, global SFC, as well as the intra-network SFC of the dorsolateral somatomotor and dorsal attention networks, and the inter-network SFC between dorsolateral somatomotor and frontoparietal networks decreased with age. The global SFC decreased with total cognitive score. There were significant interaction effects between years of education versus white matter hyperintensities and between years of education versus cerebral microbleeds on inter-network SFC. Enlarged perivascular space in basal ganglia was associated with higher inter-network SFC. Our results suggest that cognitive ability is associated with brain coupling at the global level and cognitive reserve with brain coupling at the inter-functional-brain-cluster level with interaction effect from white matter hyperintensities and cerebral microbleed in a cohort of healthy elderlies.
Ergothioneine promotes longevity and healthy aging in male mice
Authors: Katsube Makoto , Ishimoto Takahiro , Fukushima Yutaro , Kagami Asuka , Shuto Tsuyoshi , Kato Yukio 
Published: March 2024

AbstractHealthy aging has emerged as a crucial issue with the increase in the geriatric population worldwide. Food-derived sulfur-containing amino acid ergothioneine (ERGO) is a potential dietary supplement, which exhibits various beneficial effects in experimental animals although the preventive effects of ERGO on aging and/or age-related impairments such as frailty and cognitive impairment are unclear. We investigated the effects of daily oral supplementation of ERGO dissolved in drinking water on lifespan, frailty, and cognitive impairment in male mice from 7 weeks of age to the end of their lives. Ingestion of 4 ~ 5 mg/kg/day of ERGO remarkably extended the lifespan of male mice. The longevity effect of ERGO was further supported by increase in life and non-frailty spans of Caenorhabditis elegans in the presence of ERGO. Compared with the control group, the ERGO group showed significantly lower age-related declines in weight, fat mass, and average and maximum movement velocities at 88 weeks of age. This was compatible with dramatical suppression by ERGO of the age-related increments in plasma biomarkers (BMs) such as the chemokine ligand 9, creatinine, symmetric dimethylarginine, urea, asymmetric dimethylarginine, quinolinic acid, and kynurenine. The oral intake of ERGO also rescued age-related impairments in learning and memory ability, which might be associated with suppression of the age-related decline in hippocampal neurogenesis and TDP43 protein aggregation and promotion of microglial shift to the M2 phenotype by ERGO ingestion. Ingestion of ERGO may promote longevity and healthy aging in male mice, possibly through multiple biological mechanisms.
Custom orthotic design by integrating 3D scanning and subject-specific FE modelling workflow
Authors: Peng Yinghu , Wang Yan , Zhang Qida , Chen Shane Fei , Zhang Ming , Li Guanglin 
Published: March 2024

AbstractThe finite element (FE) foot model can help estimate pathomechanics and improve the customized foot orthoses design. However, the procedure of developing FE models can be time-consuming and costly. This study aimed to develop a subject-specific scaled foot modelling workflow for the foot orthoses design based on the scanned foot surface data. Six participants (twelve feet) were collected for the foot finite element modelling. The subject-specific surface-based finite element model (SFEM) was established by incorporating the scanned foot surface and scaled foot bone geometries. The geometric deviations between the scaled and the scanned foot surfaces were calculated. The SFEM model was adopted to predict barefoot and foot-orthosis interface pressures. The averaged distances between the scaled and scanned foot surfaces were 0.23 ± 0.09 mm. There was no significant difference for the hallux, medial forefoot, middle forefoot, midfoot, medial hindfoot, and lateral hindfoot, except for the lateral forefoot region (p = 0.045). The SFEM model evaluated slightly higher foot-orthoses interface pressure values than measured, with a maximum deviation of 7.1%. These results indicated that the SFEM technique could predict the barefoot and foot-orthoses interface pressure, which has the potential to expedite the process of orthotic design and optimization.
Graphical abstract
Discretised Flux Balance Analysis for Reaction–Diffusion Simulation of Single-Cell Metabolism
Authors: Chew Yin Hoon , Spill Fabian 
Published: March 2024

AbstractMetabolites have to diffuse within the sub-cellular compartments they occupy to specific locations where enzymes are, so reactions could occur. Conventional flux balance analysis (FBA), a method based on linear programming that is commonly used to model metabolism, implicitly assumes that all enzymatic reactions are not diffusion-limited though that may not always be the case. In this work, we have developed a spatial method that implements FBA on a grid-based system, to enable the exploration of diffusion effects on metabolism. Specifically, the method discretises a living cell into a two-dimensional grid, represents the metabolic reactions in each grid element as well as the diffusion of metabolites to and from neighbouring elements, and simulates the system as a single linear programming problem. We varied the number of rows and columns in the grid to simulate different cell shapes, and the method was able to capture diffusion effects at different shapes. We then used the method to simulate heterogeneous enzyme distribution, which suggested a theoretical effect on variability at the population level. We propose the use of this method, and its future extensions, to explore how spatiotemporal organisation of sub-cellular compartments and the molecules within could affect cell behaviour.
SAA1 regulated by S1P/S1PR1 promotes the progression of ESCC via β-catenin activation
Authors: Li Qianqian , Tang Maolin , Zhao Shisheng , Yang Junjie , Meng Yuanlin , Meng Chunmei , Ren Ling , Hu Weimin 
Published: March 2024

AbstractSerum amyloid A1 (SAA1), an inflammation-related molecule, is associated with the malignant progression of many tumors. This study aimed to investigate the role of SAA1 in the progression of esophageal squamous cell carcinoma (ESCC) and its molecular mechanisms. The expression of SAA1 in ESCC tissues and cell lines was analyzed using bioinformatics analysis, western blotting, and reverse transcription-quantitative PCR (RT‒qPCR). SAA1-overexpressing or SAA1-knockdown ESCC cells were used to assess the effects of SAA1 on the proliferation, migration, apoptosis of cancer cells and the growth of xenograft tumors in nude mice. Western blotting, immunofluorescence and RT‒qPCR were used to investigate the relationship between SAA1 and β-catenin and SAA1 and sphingosine 1-phosphate (S1P)/sphingosine 1-phosphate receptor 1 (S1PR1). SAA1 was highly expressed in ESCC tissues and cell lines. Overexpression of SAA1 significantly promoted the proliferation, migration and the growth of tumors in nude mice. Knockdown of SAA1 had the opposite effects and promoted the apoptosis of ESCC cells. Moreover, SAA1 overexpression promoted the phosphorylation of β-catenin at Ser675 and increased the expression levels of the β-catenin target genes MYC and MMP9. Knockdown of SAA1 had the opposite effects. S1P/S1PR1 upregulated SAA1 expression and β-catenin phosphorylation at Ser675 in ESCC cells. In conclusion, SAA1 promotes the progression of ESCC by increasing β-catenin phosphorylation at Ser675, and the S1P/S1PR1 pathway plays an important role in its upstream regulation.
Investigating the impact of company announcements on stock prices: an application of machine learning on Australian lithium market
Authors: Kianrad Ahmad , Arani Mohadeseh Najafi , Hasani Karim , Zargar Masoumeh , Erfani Eila , Razmjou Amir 
Published: March 2024

AbstractThis paper investigates the effects of various types of announcements made by lithium producers on stock prices. We collected data from 40 lithium-producing companies listed on the world's largest stock exchanges, spanning from May 2020 to September 2022. To analyze the impact of announcements such as quoted and unquoted securities, market announcements, company reports, public meetings and presentations, financial announcements, and technical announcements on stock prices, we employed an extreme gradient boosting (XGBoost) model. Our results indicate that stock exchange market announcements and announcements about public meetings and presentations significantly influenced the stock prices of all eight large-cap companies studied. Announcements about public meetings and presentations were crucial predictors of stock prices for 73% of all companies analyzed. Additionally, positive financial announcements were key predictors for 70% of the companies. These findings suggest that investors should consider these predictors when making investment decisions in the lithium-related stock market. This study contributes to the existing literature by providing empirical evidence on the impact of different types of announcements made by lithium producers on stock prices. Furthermore, the XGBoost model used in this study can be applied to other industries and markets to analyze the impact of various types of announcements on stock prices.
Supply Chain Flexibility and Post-pandemic Resilience
Authors: Agrawal Nishant , Sharma Mahak , Raut Rakesh D. , Mangla Sachin Kumar , Arisian Sobhan 
Published: March 2024

AbstractThe COVID-19 outbreak in 2020–2021 caused unprecedented disruptions to global supply networks. Companies worldwide faced significant challenges as they dealt with the unexpected surge in demand for specific goods and services. This study delves into the importance of supply chain coordination (SCCO), supply chain resilience (SCRE), and supply chain robustness (SCRB), considering supply chain flexibility (SCFL) and Internet of Things and Big Data Analytics (IoT-BDA) integration. We explore how SCFL influences SCCO, SCRE, and SCRB, enhancing supply chain performance (SCFP). Using a cross sectional approach, we collected survey-based responses to ensure comprehensive representation from the supply chain domain. A total of 217 complete responses were collected and analyzed using AMOS 20. The findings suggest that SCCO, SCRE, and SCRB act as mediators between SCFL and IoT-BDA. However, statistical significance between SCCO and SCRB with SCRE was not established. The study emphasizes the robust predictive nature of SCFL, highlighting its pivotal role in fostering SCCO, SCRE, and SCBR through empirical evidence. Furthermore, it emphasizes the influence of SCFL on enhancing SCFP, particularly in the post-pandemic era.
Association between natriuretic peptides and C-reactive protein with frailty in heart failure: a systematic review and meta-analysis
Authors: Prokopidis Konstantinos , Ishiguchi Hironori , Jordan Cara , Irlik Krzysztof , Nabrdalik Katarzyna , Formiga Francesc , Sankaranarayanan Rajiv , Lip Gregory Y. H. , Isanejad Masoud 
Published: March 2024

Abstract
Background
Heart failure (HF) and frailty are accompanied by a bidirectional relationship, sharing common risk factors including elevated levels of natriuretic peptides and inflammation. The aim of this study was to compare biomarkers associated with poor clinical outcomes, that is, plasma brain natriuretic peptide (BNP), N-terminal-pro B-type natriuretic peptide (NT-proBNP), and C-reactive protein (CRP) in patients with HF and frailty vs. patients with HF without frailty.

Methods
From inception until July 2023, PubMed, Scopus, Web of Science, and Cochrane Library a systematic literature search was conducted. To evaluate whether frailty is linked with greater levels of BNP, NT-proBNP, and CRP, a meta-analysis using a random-effects model was used to calculate the pooled effects (CRD42023446607).

Results
Fifty-three studies were included in this systematic review and meta-analysis. Patients with HF and frailty displayed significantly higher levels of BNP (k = 11; SMD: 0.53, 95%CI 0.30–0.76, I2 = 86%, P < 0.01), NT-proBNP (k = 23; SMD: 0.33, 95%CI 0.25–0.40, I2 = 72%, P < 0.01), and CRP (k = 8; SMD: 0.30, 95%CI 0.12–0.48, I2 = 62%, P < 0.01) vs. patients with HF without frailty. Using meta-regression, body mass index (BMI) and age were deemed potential moderators of these findings.

Conclusions
Frailty in HF is linked to increased concentrations of BNP, NT-proBNP, and CRP, which have been epidemiologically associated with adverse outcomes. The increased risk of NYHA III/IV classification further emphasizes the clinical impact of frailty in this population.