bluuebunny/crossref_metadata_2025_split huggingface dataset:
Signatures of a surface spin–orbital chiral metal
Authors: Mazzola Federico , Brzezicki Wojciech , Mercaldo Maria Teresa , Guarino Anita , Bigi Chiara , Miwa Jill A. , De Fazio Domenico , Crepaldi Alberto , Fujii Jun , Rossi Giorgio , Orgiani Pasquale , Chaluvadi Sandeep Kumar , Chalil Shyni Punathum , Panaccione Giancarlo , Jana Anupam , Polewczyk Vincent , Vobornik Ivana , Kim Changyoung , Miletto-Granozio Fabio , Fittipaldi Rosalba , Ortix Carmine , Cuoco Mario , Vecchione Antonio 
Published: February 2024

AbstractThe relation between crystal symmetries, electron correlations and electronic structure steers the formation of a large array of unconventional phases of matter, including magneto-electric loop currents and chiral magnetism1–6. The detection of such hidden orders is an important goal in condensed-matter physics. However, until now, non-standard forms of magnetism with chiral electronic ordering have been difficult to detect experimentally7. Here we develop a theory for symmetry-broken chiral ground states and propose a methodology based on circularly polarized, spin-selective, angular-resolved photoelectron spectroscopy to study them. We use the archetypal quantum material Sr2RuO4 and reveal spectroscopic signatures that, despite being subtle, can be reconciled with the formation of spin–orbital chiral currents at the surface of the material8–10. As we shed light on these chiral regimes, our findings pave the way for a deeper understanding of ordering phenomena and unconventional magnetism.
CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2
Authors: Shor Ben , Schneidman-Duhovny Dina 
Published: February 2024

AbstractDeep learning models, such as AlphaFold2 and RosettaFold, enable high-accuracy protein structure prediction. However, large protein complexes are still challenging to predict due to their size and the complexity of interactions between multiple subunits. Here we present CombFold, a combinatorial and hierarchical assembly algorithm for predicting structures of large protein complexes utilizing pairwise interactions between subunits predicted by AlphaFold2. CombFold accurately predicted (TM-score >0.7) 72% of the complexes among the top-10 predictions in two datasets of 60 large, asymmetric assemblies. Moreover, the structural coverage of predicted complexes was 20% higher compared to corresponding Protein Data Bank entries. We applied the method on complexes from Complex Portal with known stoichiometry but without known structure and obtained high-confidence predictions. CombFold supports the integration of distance restraints based on crosslinking mass spectrometry and fast enumeration of possible complex stoichiometries. CombFold’s high accuracy makes it a promising tool for expanding structural coverage beyond monomeric proteins.
Naïve Bayes Classifiers and accompanying dataset for Pseudomonas syringae isolate characterization
Authors: Fautt Chad , Couradeau Estelle , Hockett Kevin L. 
Published: February 2024

AbstractThe Pseudomonas syringae species complex (PSSC) is a diverse group of plant pathogens with a collective host range encompassing almost every food crop grown today. As a threat to global food security, rapid detection and characterization of epidemic and emerging pathogenic lineages is essential. However, phylogenetic identification is often complicated by an unclarified and ever-changing taxonomy, making practical use of available databases and the proper training of classifiers difficult. As such, while amplicon sequencing is a common method for routine identification of PSSC isolates, there is no efficient method for accurate classification based on this data. Here we present a suite of five Naïve bayes classifiers for PCR primer sets widely used for PSSC identification, trained on in-silico amplicon data from 2,161 published PSSC genomes using the life identification number (LIN) hierarchical clustering algorithm in place of traditional Linnaean taxonomy. Additionally, we include a dataset for translating classification results back into traditional taxonomic nomenclature (i.e. species, phylogroup, pathovar), and for predicting virulence factor repertoires.
An open relaxation-diffusion MRI dataset in neurosurgical studies
Authors: Wu Ye , Liu Xiaoming , Huang Yunzhi , Zhou Tao , Zhang Fan 
Published: February 2024

AbstractDiffusion MRI (dMRI) is a safe and noninvasive technique that provides insight into the microarchitecture of brain tissue. Relaxation-diffusion MRI (rdMRI) is an extension of traditional dMRI that captures diffusion imaging data at multiple TEs to detect tissue heterogeneity between relaxation and diffusivity. rdMRI has great potential in neurosurgical research including brain tumor grading and treatment response evaluation. However, the lack of available data has limited the exploration of rdMRI in clinical settings. To address this, we are sharing a high-quality rdMRI dataset from 18 neurosurgical patients with different types of lesions, as well as two healthy individuals as controls. The rdMRI data was acquired using 7 TEs, where at each TE multi-shell dMRI with high spatial and angular resolutions is obtained at each TE. Each rdMRI scan underwent thorough artifact and distortion corrections using a specially designed processing pipeline. The dataset’s quality was assessed using standard practices, including quality control and assurance. This resource is a valuable addition to neurosurgical studies, and all data are openly accessible.
An empirical assessment of whether urban green ecological networks have the capacity to store higher levels of carbon
Authors: Wan Yunshan , Wang Yilei , Gao Ming , Jin Lin 
Published: February 2024

AbstractCarbon–neutral growth is a crucial long-term climatic aim in the context of global warming. This paper introduces complex network theory and explores its potential application to achieve this goal. Specifically, we investigate the spatial and temporal distribution of nodes and sources in the ecological network, and examine whether a relationship exists between the topological index of network nodes and the landscape pattern index of ecological source areas. We also determine the contribution of nodes to the carbon stock of the entire network by exploring the correlation between the carbon stock of nodes and sources to develop an optimization strategy based on the synergistic effect of node-source carbon enhancement. Finally, we test the effect of network optimization through robustness. Our results show that: (1) The correlation topological feature index analysis reveals that the degree distribution of the node network's topological characteristics becomes dispersed and modular, exhibiting the characteristics of small-world networks according to a large clustering coefficient. The heterogeneity and extent of ecological source landscapes have increased by modularity index but remain distributed and locally fragmented; (2) According to correlation analysis, by enhancing the eccentricity of the node topology, the patch cohesion index (COHESION) of the ecological source site can maximize the contribution of the node to the enhancement of the carbon stock benefits of the source site; (3) According to the tests on the robustness of nodes and edges and the robustness of network links, network stability is improved and carbon sink capacity is enhanced. Simultaneously, the restoration and rejuvenation of ecological space through national ecological construction projects can effectively improve the carbon sink within the organized region, contributing to the carbon neutrality aim. This research gives scientific and quantifiable references for potential ecological construction projects for sustainable cities and the optimization of urban ecological space structure.
Fear of COVID-19 among professional caregivers of the elderly in Central Alentejo, Portugal
Authors: Mendes Felismina Rosa , Sim-Sim Margarida , Gemito Maria Laurência , Barros Maria da Luz , Serra Isaura da Conceição , Caldeira Ana Teresa 
Published: February 2024

AbstractThe coronavirus disease 2019 (COVID-19) has infected many institutionalised elderly people. In Portugal, the level of pandemic fear among professional caregivers of the elderly is unknown, as are its predictive factors. This study aimed to investigate predictors of fear of COVID-19 among workers caring for institutionalised elderly people in nursing homes. This is a cross-sectional study using multiple linear regression applied to a population of 652 caregivers located in 14 municipalities in Central Alentejo, Portugal, at March 2021. The criterion variable was the fear of COVID-19. Standardised regression coefficients showed that the higher the level of education, the lower the level of fear (β = − 0.158; t = − 4.134; p < .001). Other predictors of the level of fear were gender, with women having higher levels (β = 0.123; t = t = 3.203; p < 0.001), higher scores on COVID-19-like suspicious symptoms (β = 0.123; t = 3.219; p < 0.001) and having received a flu vaccine (β = 0.086; t = 2.252; p = 0.025). The model explains 6.7% of the variation in fear of COVID-19 (R2Adj = 0.067). Health literacy can minimise the impact on the physical and mental health of these workers. In Central Alentejo, caregivers of the elderly play a fundamental role in social balance. Further studies are needed to better understand the factors that can improve their personal and professional well-being.
Fabrication of a novel porous nanostructure based on NiCuFe2O4@MCM-48, embedded with graphene oxide/poly (p-phenylenediamine) to construct an efficient supercapacitor
Authors: Sadat Zahra , Eivazzadeh-Keihan Reza , Daneshvari-Esfahlan Vahid , Dalvand Samad , Kashtiaray Amir , Maleki Ali 
Published: February 2024

AbstractIn this study, a new nanocomposite was created by combining copper-doped nickel ferrite (NiCuFe2O4) nanoparticles with MCM-48 (Mobil Composition of Matter No. 48) on a graphene oxide (GO) substrate functionalized with poly(ρ-phenylenediamine) abbreviated as (PρPD). This nanocomposite was developed to investigate its potential for enhancing the function of a supercapacitor in energy storage. Following NiCuFe2O4@MCM-48 preparation, Hummer’s technique GO was applied. In-situ polymerization of NiCuFe2O4@MCM-48/GO nanoparticles with ρ-phenylenediamine (ρPD) in the presence of ammonium persulfate (APS) produced PρPD, a conductive polymer. Structural characterization of the nanocomposite includes FTIR, XRD, VSM, TGA-DTG, EDX, and FE-SEM. Results from BET indicate a pore size increase of up to 5 nm. Fast ion penetration and higher storage in capacitor material are explained by this. Additionally, the nanocomposite’s electrochemical performance was evaluated using GCD and CV tests. The NiCuFe2O4@MCM-48/GO/PρPD nanocomposite has a specific capacitance of 203.57 F g−1 (1 A g−1). Furthermore, cyclical stability is essential for energy storage applications. The nanocomposite retains 92.5% of its original capacitance after 3000 cycles, indicating outstanding electrochemical stability.
Genome-wide identification of AAAP gene family and expression analysis in response to saline-alkali stress in foxtail millet (Setaria italica L.)
Authors: Wang Huimin , Li Yun , Guo Zhenqing , Zhou Xiaoke , Zhao Yuxue , Han Yucui , Lin Xiaohu 
Published: February 2024

AbstractAmino acid/auxin permease (AAAP) genes encode a large family of protein transporters that play important roles in various aspects of plant growth and development. Here, we performed genome-wide identification of members in the foxtail millet (Setaria italica L.) AAAP family (SiAAAP) and their saline-alkali stress-induced expression patterns, resulting in the identification of 65 SiAAAP genes, which could be divided into eight subfamilies. Except for SiAAAP65, the remaining 64 genes were located on nine chromosomes of foxtail millet. Gene structure and conserved motif analyses indicated that the members in the same subfamily are highly conserved. Gene duplication event analysis suggested that tandem duplication may be the main factor driving the expansion of this gene family, and Ka/Ks analysis indicated that all the duplicated genes have undergone purifying selection. Transcriptome analysis showed differential expression of SiAAAPs in roots, stems, leaves, and tassel inflorescence. Analysis of cis-acting elements in the promoter indicated that SiAAAPs contain stress-responsive cis-acting elements. Under saline-alkali stress, qRT-PCR analysis showed that SiAAP3, SiLHT2, and SiAAP16 were differentially expressed between salt-alkali tolerant millet variety JK3 and salt-alkali sensitive millet variety B175. These results suggest that these genes may be involved in or regulate the response to saline-alkali stress, providing a theoretical basis for further studying the function of SiAAAPs.
Enhancing automic and optimal control systems through graphical structures
Authors: Panda Sumati Kumari , Khan Ilyas , Velusamy Vijayakumar , Niazai Shafiullah 
Published: February 2024

AbstractThe concept of graphical structures of extended suprametric space is introduced in this study and applied to supra-graphical contractive mapping. A recursive algorithm in connection with graphical notions can be employed in adaptive systems to construct a desired output function iteratively after specific conditions are first defined to ensure the existence of the solution by use of supra-graphical contractive mapping. After analyzing the historical context and relevant outcomes, we discuss the usage of graphical structures and supra-graphical contractive mappings in the conceptual frameworks of adaptive control and optimal control systems.
Performance analysis and modelling of circular jets aeration in an open channel using soft computing techniques
Authors: Puri Diksha , Kumar Raj , Kumar Sushil , Thakur M. S. , Fekete Gusztáv , Lee Daeho , Singh Tej 
Published: February 2024

AbstractDissolved oxygen (DO) is an important parameter in assessing water quality. The reduction in DO concentration is the result of eutrophication, which degrades the quality of water. Aeration is the best way to enhance the DO concentration. In the current study, the aeration efficiency (E20) of various numbers of circular jets in an open channel was experimentally investigated for different channel angle of inclination (θ), discharge (Q), number of jets (Jn), Froude number (Fr), and hydraulic radius of each jet (HRJn). The statistical results show that jets from 8 to 64 significantly provide aeration in the open channel. The aeration efficiency and input parameters are modelled into a linear relationship. Additionally, utilizing WEKA software, three soft computing models for predicting aeration efficiency were created with Artificial Neural Network (ANN), M5P, and Random Forest (RF). Performance evaluation results and box plot have shown that ANN is the outperforming model with correlation coefficient (CC) = 0.9823, mean absolute error (MAE) = 0.0098, and root mean square error (RMSE) = 0.0123 during the testing stage. In order to assess the influence of different input factors on the E20 of jets, a sensitivity analysis was conducted using the most effective model, i.e., ANN. The sensitivity analysis results indicate that the angle of inclination is the most influential input variable in predicting E20, followed by discharge and the number of jets.
Molecular crosstalk between MUC1 and STAT3 influences the anti-proliferative effect of Napabucasin in epithelial cancers
Authors: Bose Mukulika , Sanders Alexa , Handa Aashna , Vora Aabha , Cardona Manuel R. , Brouwer Cory , Mukherjee Pinku 
Published: February 2024

AbstractMUC1 is a transmembrane glycoprotein that is overexpressed and aberrantly glycosylated in epithelial cancers. The cytoplasmic tail of MUC1 (MUC1 CT) aids in tumorigenesis by upregulating the expression of multiple oncogenes. Signal transducer and activator of transcription 3 (STAT3) plays a crucial role in several cellular processes and is aberrantly activated in many cancers. In this study, we focus on recent evidence suggesting that STAT3 and MUC1 regulate each other’s expression in cancer cells in an auto-inductive loop and found that their interaction plays a prominent role in mediating epithelial-to-mesenchymal transition (EMT) and drug resistance. The STAT3 inhibitor Napabucasin was in clinical trials but was discontinued due to futility. We found that higher expression of MUC1 increased the sensitivity of cancer cells to Napabucasin. Therefore, high-MUC1 tumors may have a better outcome to Napabucasin therapy. We report how MUC1 regulates STAT3 activity and provide a new perspective on repurposing the STAT3-inhibitor Napabucasin to improve clinical outcome of epithelial cancer treatment.
Identification of pyroptosis-related gene signature in nonalcoholic steatohepatitis
Authors: Mao Fei , Wang E. , Fu Li , Fan Wenhua , Zhou Jing , Yan Guofeng , Liu Tiemin , Li Yao 
Published: February 2024

AbstractNon-alcoholic fatty liver disease (NAFLD) has emerged as one of the major causes of liver-related morbidity and mortality globally. It ranges from simple steatosis to non-alcoholic steatohepatitis (NASH) characterized by ballooning and hepatic inflammation. In the past few years, pyroptosis has been shown as a type of programmed cell death that triggers inflammation and plays a role in the development of NASH. However, the roles of pyroptosis-related genes (PRGs) in NASH remained unclear. In this study, we studied the expression level of pyroptosis-related genes (PRGs) in NASH and healthy controls, developed a diagnostic model of NASH based on PRGs and explored the pathological mechanisms associated with pyroptosis. We further compared immune status between NASH and healthy controls, analyzed immune status in different subtypes of NASH. We identified altogether twenty PRGs that were differentially expressed between NASH and normal liver tissues. Then, a novel diagnostic model consisting of seven PRGs including CASP3, ELANE, GZMA, CASP4, CASP9, IL6 and TP63 for NASH was constructed with an area under the ROC curve (AUC) of 0.978 (CI 0.965–0.99). Obvious variations in immune status between healthy controls and NASH cases were detected. Subsequently, the consensus clustering method based on differentially expressed PRGs was constructed to divide all NASH cases into two distinct pyroptosis subtypes with different immune and biological characteristics. Pyroptosis-related genes may play an important role in NASH and can provide new insights into the diagnosis and underlying mechanisms of NASH.
A study on the evolution of tripartite collaborative prevention and control under public health emergencies using COVID-19 as an example
Authors: Mingyue Liu , Wei Shen , Zhang Xin 
Published: February 2024

AbstractThe problem of repeated epidemic fluctuations in the normalized prevention and control stage is revealed by data from January 20, 2020, to January 30, 2023. In order to improve the collaborative response of the public and government departments to public health emergencies and avoid repeated fluctuations of the epidemic, a tripartite evolutionary game model of the public, local government, and central government departments is constructed, focusing on the evolutionary paths and evolutionary stabilization strategies of the three subjects, and the influence of each element on the evolutionary results is simulated by numerical simulation in Matlab, and based on the inadequacy of the static reward and punishment mechanism, a dynamic Based on the shortcomings of static reward and punishment mechanism, dynamic reward and punishment mechanism is introduced to control the stability of the evolving system. The study shows that (1) with the increase of the initial willingness of the three parties, the rate of the public choosing the discretionary flow strategy slows down, and the collaborative prevention and control process can be accelerated. (2) The reward and punishment mechanism of central government departments has a positive incentive effect on the local government's strict prevention and control and the public's conscious isolation. Appropriately increasing rewards, formulating reasonable subsidy strategies, and increasing penalties for violations are conducive to the overall optimization of the system, and the punishment mechanism is most sensitive to the regulation of the public's discretionary mobility behavior. (3) Government departments' prevention and control costs can influence their enthusiasm for strict prevention and control and real-time supervision. Reducing the human resources cost, time cost, and financial cost of prevention and control is conducive to government departments performing their duties more responsibly. (4) The static punishment mechanism fails to make timely adjustments according to the strategy choice of each actor. It cannot control the stability of the evolving system. In contrast, the dynamic punishment mechanism considers the punishment parameters to link the casual isolation rate with the lenient prevention and control rate, which can effectively control the system's fluctuating instability and is the system's stability control strategy. Finally, combining theoretical and simulation analysis, management suggestions are made for controlling repeated fluctuations of the epidemic in practice, and the research limitations of this paper are explained.
Characteristics of limb kinematics in the gait disorders of post-stroke patients
Authors: Mizuta Naomichi , Hasui Naruhito , Kai Takumi , Inui Yasuhiro , Sato Masahiro , Ohnishi Sora , Taguchi Junji , Nakatani Tomoki 
Published: February 2024

AbstractPost-stroke gait disorders involve altered lower limb kinematics. Recently, the endpoint of the lower limb has been used as a control variable to understand gait kinematics better. In a cross-sectional study of sixty-seven post-stroke patients, the limb extension angle and effective limb length during gait were used as input variables with a mixed Gaussian model-based probabilistic clustering approach to identify five distinct clusters. Each cluster had unique characteristics related to motor paralysis, spasticity, balance ability, and gait strategy. Cluster 1 exhibited high limb extension angle and length values, indicating increased spasticity. Cluster 2 had moderate extension angles and high limb lengths, indicating increased spasticity and reduced balance ability. Cluster 3 had low limb extension angles and high limb length, indicating reduced balance ability, more severe motor paralysis, and increased spasticity. Cluster 4 demonstrated high extension angles and short limb lengths, with a gait strategy that prioritized stride length in the component of gait speed. Cluster 5 had moderate extension angles and short limb lengths, with a gait strategy that prioritized cadence in the component of gait speed. These findings provide valuable insights into post-stroke gait impairment and can guide the development of personalized and effective rehabilitation strategies.