bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of silages on concrete and process of its corrosion in the course of time
Authors: Chromková Ivana , Čechmánek René , Krejčí Kotlánová Michaela
Published: July 2024

Silages are important juicy bulky feedstuff, that has irreplaceable role in nutrition of farm animals – cattle, pigs and horses. The silages are made of a fresh plant mass (e.g. corn, alfalfa, rape, clover or grass), that is in a chopped form in an exactly given way ensiled, i.e. in a tamped or pressed form without access of air subjected to a fermentation process. Within this process acid juices are created and enter into a construction of containers aimed for the ensilage process. These containers are mainly from a reinforced concrete. Influence of the silage on the concrete is a difficult process and it depends on several factors. From the point of view of durability/resistance to the silage effect, a concrete composition is a significant factor, the other factors are silage properties as well as time of a contact of the concrete with the silage. In this paper we describe findings on a state of 3 concrete compositions, which were repeatedly subjected to a corn silage for 3 years. In a 1-year interval, an effect of the silages on physico-mechanical properties of the concrete (e.g. strength, absorptivity, porosity) was observed. The highest resistance to effect of the silages in the course of time was proven for the concrete with a higher content of Portland cement.
Universal optimal design in the vertebrate limb pattern and lessons for bioinspired design
Authors: Burgess Stuart
Published: July 2024

This paper broadly summarizes the variation of design features found in vertebrate limbs and analyses the resultant versatility and multifunctionality in order to make recommendations for bioinspired robotics. The vertebrate limb pattern (e.g. shoulder, elbow, wrist and digits) has been proven to be very successful in many different applications in the animal kingdom. However, the actual level of optimality of the limb for each animal application is not clear because for some cases (e.g. whale flippers and bird wings), the basic skeletal layout is assumed to be highly constrained by evolutionary ancestry. This paper addresses this important and fundamental question of optimality by analysing six limbs with contrasting functions: human arm, whale flipper, bird wing, human leg, feline hindlimb and frog hindlimb. A central finding of this study is that the vertebrate limb pattern is highly versatile and optimal not just for arms and legs but also for flippers and wings. One key design feature of the vertebrate limb pattern is that of networks of segmented bones that enable smooth morphing of shapes as well as multifunctioning structures. Another key design feature is that of linkage mechanisms that fine-tune motions and mechanical advantage. A total of 52 biomechanical design features of the vertebrate limb are identified and tabulated for these applications. These tables can be a helpful reference for designers of bioinspired robotic and prosthetic limbs. The vertebrate limb has significant potential for the bioinspired design of robotic and prosthetic limbs, especially because of progress in the development of soft actuators.
An assessment of recent peat forest disturbances and their drivers in the Cuvette Centrale, Africa
Authors: Nesha Karimon , Herold Martin , Reiche Johannes , Masolele Robert N , Hergoualc’h Kristell , Swails Erin , Murdiyarso Daniel , Ewango Corneille E N
Published: July 2024

The largest tropical peatland complex in the Cuvette Centrale is marked by persistent knowledge gaps. We assessed recent peat forest disturbances and their direct drivers from 2019 to 2021 in Cuvette Centrale, spanning the Republic of Congo (ROC) and the Democratic Republic of Congo (DRC). Utilizing peatland maps and Radar for Detecting Deforestation alert data, we analyzed spatial and temporal patterns of disturbances. Further, we examined 2267 randomly sampled peat forest disturbance events through visual interpretation of monthly Planet and Sentinel 2A data to identify direct drivers. Our findings revealed that between 2019 and 2021, about 91% of disturbances occurred in DRC, with hotspots concentrated in the northwest Sud-Ubangi district. Disturbances predominantly followed a sharp seasonal pattern, recurring during the first half of each year with temporal hotspots emerging between February and May, closely associated with smallholder agriculture activities. Smallholder agriculture accounted for over 88% of disturbances in Cuvette Centrale, representing a leading role both in ROC (∼77%) and DRC (∼89%). While small-scale logging contributed 7% to the disturbances in the region, it constituted an important driver (18%) in the ROC. Other drivers included floods, roads, and settlements. Approximately 77% of disturbances occurred outside managed forest concessions in Cuvette Centrale, with 40% extending into protected areas. About 90% of disturbances were concentrated within 1 km of peat forest edges and ∼76% of the disturbances occurred within 5 km of road or river networks. The insights underscore the crucial need for effective peat forest conservation strategies in Cuvette Centrale and can inform national policies targeting peatland protection, aligning with commitments in the Brazzaville Declaration and the Paris Agreement. Further, our findings on direct driver assessment could serve as a reference dataset for machine learning models to automate the visual interpretation and upscale the assessment across the entire region.
Ocean feedback on 50–80-day boreal winter intraseasonal oscillation in the Indian Ocean: comparison of atmospheric and coupled CESM2 simulations
Authors: Liang Yun , Xia Ruixue , Du Yan
Published: July 2024

The role of sea surface temperature (SST) variability in the boreal winter intraseasonal oscillation (ISO) over the tropical Indian Ocean (TIO) is investigated in this study using the Community Earth System Model Version 2. An atmospheric general coupled model (AGCM) run forced by daily SSTs derived from a parallel coupled circulation model (CGCM) run is compared with reanalysis and the original coupled simulation. The comparison of atmospheric-coupled GCMs reveals the frequency and spatial tendency of the SST effect on the atmospheric ISO. The 50–80 d component of the ISO over the TIO is significantly intensified in the AGCM run. The SST-to-atmosphere effect is most prominent over the southeastern TIO. In the AGCM run, low-level wind anomalies related to SST appear west of the ISO convection center, contrasting with the previous findings that the SST effect appears east of the convection center.
Simulation of mode transitions in capacitively coupled Ar/O2 plasmas
Authors: LIU 刘 Xiangmei 相梅 , ZHANG 张 Shuren 树人 , ZHAO 赵 Shuxia 书霞 , LI 李 Hongying 洪影 , REN 任 Xiaohui 晓辉
Published: July 2024

In this work, the effects of the frequency, pressure, gas composition, and secondary-electron emission coefficient on the discharge mode in capacitively coupled Ar/O2 plasmas were carefully studied through simulations. Three discharge modes, i.e., α, γ, and drift-ambipolar (DA), were considered in this study. The results show that a mode transition from the γ-DA hybrid mode dominated by the γ mode to the DA-α hybrid mode dominated by the DA mode is induced by increasing the frequency from 100 kHz to 40 MHz. Furthermore, the electron temperature decreases with increasing frequency, while the plasma density first decreases and then increases. It was found that the electronegativity increases slightly with increasing pressure in the low-frequency region, and it increases notably with increasing pressure in the high-frequency region. It was also observed that the frequency corresponding to the mode transition from γ to DA decreased when the secondary-electron emission coefficient was decreased. Finally, it was found that increasing the oxygen content weakens the γ mode and enhances the DA mode. More importantly, the density of oxygen atoms and ozone will increase greatly with increasing oxygen content, which is of great significance for industrial applications.
Impact of voluntary environmental regulation on green innovation from the perspective of enterprise life cycle: evidence from China
Authors: Ma Hedan , Dong Yuxin , Zhou Mingming , Fang Na
Published: July 2024

From the perspective of enterprise life cycle, the impact of voluntary environmental regulation on enterprise green innovation was examined in this study based on the data of manufacturing enterprises listed on China’s A-share market from 2012 to 2021. The results indicate that: (1) voluntary environmental regulation has a significant positive impact on enterprise green innovation as a whole. (2) Among all stages of enterprise life cycle, voluntary environmental regulation has a significant impact on enterprise green innovation in the growth and maturity stages, but has a relatively small impact on enterprise green innovation in the formation and decline stages. (3) The results of a segmented sample study on this basis show that voluntary environmental regulation has heterogeneity in property rights and factor density in promoting enterprise green innovation. It significantly promotes green innovation by state-owned enterprises in the maturity stage, green innovation by non-state-owned enterprises in the maturity and decline stages, and green innovation by capital and technology intensive manufacturing enterprises, but have no significant impact on other types of enterprises. These research conclusions are expected to provide decision-making reference for improving the voluntary environmental regulation system and promoting the level of enterprise green innovation.
From Jihad to Politics
Authors: Drevon Jerome
Published: July 2024

The Syrian regime unleashed unprecedented violence to suppress large-scale non-violent protests amid the Arab uprisings. Hundreds of armed groups formed throughout the country to defend the protesters and fight back. However, in contrast to other conflicts previously dominated by al-Qaeda and Islamic State, the two largest Syrian Jihadi groups, Ahrar al-Sham and then Jabhat al-Nusra, rejected global jihad and began to cultivate new ties with the population, other armed opposition groups, and even foreign states. This strategic shift is a response to the Jihadi paradox--a realization that while Jihadis excel at leading insurgencies, they fail to achieve political victories. In From Jihad to Politics, Jerome Drevon offers an examination of the Syrian armed opposition, tracing the emergence of Jihadi groups in the conflict, their dominance, and their political transformation. Drawing upon field research and interviews with Syrian insurgents in northwestern Syria and Turkey, Drevon demonstrates how the context of a local conflict can shape armed groups' behaviour in unexpected ways. Further, he marshals unique evidence from the Arab world's most intense conflict to explain why the trajectory of the transnational Jihadi movement has altered course in recent years.
Mandatory Disclosures and Substantive Consumer Rights
Authors: Pflücke Felix
Published: July 2024

Chapter 4 focuses on the rights consumers derive from the national rules implementing the minimum harmonization E-Commerce Directive and maximum harmonization Consumer Rights Directive. The part concerning the E-Commerce Directive examines whether the Member States decide to surpass the Directive’s level of protection. The part of the chapter exploring legal duties in the Consumer Rights Directive focuses solely on the EU level because the Directive’s standard does not permit Member States to deviate. From an evidence-driven law and policy perspective and alignment with consumer theories, the chapter illustrates a growing trend in both the utilization and enhancement of evidence, transitioning from the E-Commerce Directive to the Consumer Rights Directive.
Research Design
Authors: Pflücke Felix
Published: July 2024

This chapter outlines the research design of the monograph’s empirical investigation. It introduces the hypotheses and expected findings of the empirical inquiry and critically examines previous studies. It then discusses how it translates consumer rights and the factors potentially affecting compliance into dependent and independent variables. The chapter also deals with how it generated the data for the case study. In the next step, the chapter outlines the techniques for the data analysis, including the measurement of the levels of compliance, the statistical tools used, and the visualization of the findings. Finally, the chapter concludes by reflecting upon some of the methodological challenges of the empirical inquiry.
Shakti Chattopadhyay
Authors: Roy Sumana
Published: July 2024

Very few poets in the world wrote as obsessively about plant life as Shakti Chattopadhyay. Entering his writing through his biography, his life in Baharu and his moving to Calcutta, his nomadic education and professional life, his constant centrifugal desire to travel to forests in India, this chapter reads his poems closely to understand his world of philosophical botany, his obsession with roots, the autumnal forest, the privileging of leaves over flowers, the figures of the woodcutter and the gardener, the desire to enter a tree and live there, and how a tree’s giving is different from the human’s.
Satyajit Ray
Authors: Roy Sumana
Published: July 2024

Beginning with Upendrakishore Ray Chowdhury and Sukumar Ray, Satyajit Ray’s grandfather and father, and their stories and poems about fantastic and nonsense plant kingdoms, how that impacted children’s literature in Bengal, this chapter moves to the filmmaker’s memoir, particularly his childhood, his acquaintance with the trees of Darbhanga, the note that Rabindranath is said to have written in the little boy’s notebook. It must have been all of these that produced the fantastic nerve in Satyajit Ray’s stories about plant life—man-eating trees, murderous flowers, plants that can cure depression, the green man, and, of course, the Professor Shanku stories.
CloudATAC: a cloud-based framework for ATAC-Seq data analysis
Authors: Veerappa Avinash M , Rowley M Jordan , Maggio Angela , Beaudry Laura , Hawkins Dale , Kim Allen , Sethi Sahil , Sorgen Paul L , Guda Chittibabu
Published: July 2024

Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) generates genome-wide chromatin accessibility profiles, providing valuable insights into epigenetic gene regulation at both pooled-cell and single-cell population levels. Comprehensive analysis of ATAC-seq data involves the use of various interdependent programs. Learning the correct sequence of steps needed to process the data can represent a major hurdle. Selecting appropriate parameters at each stage, including pre-analysis, core analysis, and advanced downstream analysis, is important to ensure accurate analysis and interpretation of ATAC-seq data. Additionally, obtaining and working within a limited computational environment presents a significant challenge to non-bioinformatic researchers. Therefore, we present Cloud ATAC, an open-source, cloud-based interactive framework with a scalable, flexible, and streamlined analysis framework based on the best practices approach for pooled-cell and single-cell ATAC-seq data. These frameworks use on-demand computational power and memory, scalability, and a secure and compliant environment provided by the Google Cloud. Additionally, we leverage Jupyter Notebook's interactive computing platform that combines live code, tutorials, narrative text, flashcards, quizzes, and custom visualizations to enhance learning and analysis. Further, leveraging GPU instances has significantly improved the run-time of the single-cell framework. The source codes and data are publicly available through NIH Cloud lab https://github.com/NIGMS/ATAC-Seq-and-Single-Cell-ATAC-Seq-Analysis.

This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.
A cloud-based learning module for biomarker discovery
Authors: Hemme Christopher L , Beaudry Laura , Yosufzai Zelaikha , Kim Allen , Pan Daniel , Campbell Ross , Price Marcia , Cho Bongsup P
Published: July 2024

This manuscript describes the development of a resource module that is part of a learning platform named “NIGMS Sandbox for Cloud-based Learning” https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on basic principles in biomarker discovery in an interactive format that uses appropriate cloud resources for data access and analyses. In collaboration with Google Cloud, Deloitte Consulting and NIGMS, the Rhode Island INBRE Molecular Informatics Core developed a cloud-based training module for biomarker discovery. The module consists of nine submodules covering various topics on biomarker discovery and assessment and is deployed on the Google Cloud Platform and available for public use through the NIGMS Sandbox. The submodules are written as a series of Jupyter Notebooks utilizing R and Bioconductor for biomarker and omics data analysis. The submodules cover the following topics: 1) introduction to biomarkers; 2) introduction to R data structures; 3) introduction to linear models; 4) introduction to exploratory analysis; 5) rat renal ischemia-reperfusion injury case study; (6) linear and logistic regression for comparison of quantitative biomarkers; 7) exploratory analysis of proteomics IRI data; 8) identification of IRI biomarkers from proteomic data; and 9) machine learning methods for biomarker discovery. Each notebook includes an in-line quiz for self-assessment on the submodule topic and an overview video is available on YouTube (https://www.youtube.com/watch?v=2-Q9Ax8EW84).

This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.
Identifying and training deep learning neural networks on biomedical-related datasets
Authors: Woessner Alan E , Anjum Usman , Salman Hadi , Lear Jacob , Turner Jeffrey T , Campbell Ross , Beaudry Laura , Zhan Justin , Cornett Lawrence E , Gauch Susan , Quinn Kyle P
Published: July 2024

This manuscript describes the development of a resources module that is part of a learning platform named ‘NIGMS Sandbox for Cloud-based Learning’ https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on implementing deep learning algorithms for biomedical image data in an interactive format that uses appropriate cloud resources for data access and analyses. Biomedical-related datasets are widely used in both research and clinical settings, but the ability for professionally trained clinicians and researchers to interpret datasets becomes difficult as the size and breadth of these datasets increases. Artificial intelligence, and specifically deep learning neural networks, have recently become an important tool in novel biomedical research. However, use is limited due to their computational requirements and confusion regarding different neural network architectures. The goal of this learning module is to introduce types of deep learning neural networks and cover practices that are commonly used in biomedical research. This module is subdivided into four submodules that cover classification, augmentation, segmentation and regression. Each complementary submodule was written on the Google Cloud Platform and contains detailed code and explanations, as well as quizzes and challenges to facilitate user training. Overall, the goal of this learning module is to enable users to identify and integrate the correct type of neural network with their data while highlighting the ease-of-use of cloud computing for implementing neural networks.

This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.
CELA-MFP: a contrast-enhanced and label-adaptive framework for multi-functional therapeutic peptides prediction
Authors: Fang Yitian , Luo Mingshuang , Ren Zhixiang , Wei Leyi , Wei Dong-Qing
Published: July 2024

Functional peptides play crucial roles in various biological processes and hold significant potential in many fields such as drug discovery and biotechnology. Accurately predicting the functions of peptides is essential for understanding their diverse effects and designing peptide-based therapeutics. Here, we propose CELA-MFP, a deep learning framework that incorporates feature Contrastive Enhancement and Label Adaptation for predicting Multi-Functional therapeutic Peptides. CELA-MFP utilizes a protein language model (pLM) to extract features from peptide sequences, which are then fed into a Transformer decoder for function prediction, effectively modeling correlations between different functions. To enhance the representation of each peptide sequence, contrastive learning is employed during training. Experimental results demonstrate that CELA-MFP outperforms state-of-the-art methods on most evaluation metrics for two widely used datasets, MFBP and MFTP. The interpretability of CELA-MFP is demonstrated by visualizing attention patterns in pLM and Transformer decoder. Finally, a user-friendly online server for predicting multi-functional peptides is established as the implementation of the proposed CELA-MFP and can be freely accessed at http://dreamai.cmii.online/CELA-MFP.
Introducing enzymatic cleavage features and transfer learning realizes accurate peptide half-life prediction across species and organs
Authors: Tan Xiaorong , Liu Qianhui , Fang Yanpeng , Yang Sen , Chen Fei , Wang Jianmin , Ouyang Defang , Dong Jie , Zeng Wenbin
Published: July 2024

Peptide drugs are becoming star drug agents with high efficiency and selectivity which open up new therapeutic avenues for various diseases. However, the sensitivity to hydrolase and the relatively short half-life have severely hindered their development. In this study, a new generation artificial intelligence-based system for accurate prediction of peptide half-life was proposed, which realized the half-life prediction of both natural and modified peptides and successfully bridged the evaluation possibility between two important species (human, mouse) and two organs (blood, intestine). To achieve this, enzymatic cleavage descriptors were integrated with traditional peptide descriptors to construct a better representation. Then, robust models with accurate performance were established by comparing traditional machine learning and transfer learning, systematically. Results indicated that enzymatic cleavage features could certainly enhance model performance. The deep learning model integrating transfer learning significantly improved predictive accuracy, achieving remarkable R2 values: 0.84 for natural peptides and 0.90 for modified peptides in human blood, 0.984 for natural peptides and 0.93 for modified peptides in mouse blood, and 0.94 for modified peptides in mouse intestine on the test set, respectively. These models not only successfully composed the above-mentioned system but also improved by approximately 15% in terms of correlation compared to related works. This study is expected to provide powerful solutions for peptide half-life evaluation and boost peptide drug development.
Unveiling promising drug targets for autism spectrum disorder: insights from genetics, transcriptomics, and proteomics
Authors: Jiang Rui , Huang Wentao , Qiu Xinqi , Chen Jianyi , Luo Ruibang , Zeng Ruijie , Tong Shuangshuang , Lyu Yanlin , Sun Panpan , Lian Qizhou , Leung Felix W , Liu Yufeng , Sha Weihong , Chen Hao
Published: July 2024

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder for which current treatments are limited and drug development costs are prohibitive. Identifying drug targets for ASD is crucial for the development of targeted therapies. Summary-level data of expression quantitative trait loci obtained from GTEx, protein quantitative trait loci data from the ROSMAP project, and two ASD genome-wide association studies datasets were utilized for discovery and replication. We conducted a combined analysis using Mendelian randomization (MR), transcriptome-wide association studies, Bayesian colocalization, and summary-data-based MR to identify potential therapeutic targets associated with ASD and examine whether there are shared causal variants among them. Furthermore, pathway and drug enrichment analyses were performed to further explore the underlying mechanisms and summarize the current status of pharmacological targets for developing drugs to treat ASD. The protein–protein interaction (PPI) network and mouse knockout models were performed to estimate the effect of therapeutic targets. A total of 17 genes revealed causal associations with ASD and were identified as potential targets for ASD patients. Cathepsin B (CTSB) [odd ratio (OR) = 2.66 95, confidence interval (CI): 1.28–5.52, P = 8.84 × 10−3], gamma-aminobutyric acid type B receptor subunit 1 (GABBR1) (OR = 1.99, 95CI: 1.06–3.75, P = 3.24 × 10−2), and formin like 1 (FMNL1) (OR = 0.15, 95CI: 0.04–0.58, P = 5.59 × 10−3) were replicated in the proteome-wide MR analyses. In Drugbank, two potential therapeutic drugs, Acamprosate (GABBR1 inhibitor) and Bryostatin 1 (CASP8 inhibitor), were inferred as potential influencers of autism. Knockout mouse models suggested the involvement of the CASP8, GABBR1, and PLEKHM1 genes in neurological processes. Our findings suggest 17 candidate therapeutic targets for ASD and provide novel drug targets for therapy development and critical drug repurposing opportunities.
Comparative analyses of gene networks mediating cancer metastatic potentials across lineage types
Authors: Wang Sheng , Stroup Emily K , Wang Ting-You , Yang Rendong , Ji Zhe
Published: July 2024

Studies have identified genes and molecular pathways regulating cancer metastasis. However, it remains largely unknown whether metastatic potentials of cancer cells from different lineage types are driven by the same or different gene networks. Here, we aim to address this question through integrative analyses of 493 human cancer cells’ transcriptomic profiles and their metastatic potentials in vivo. Using an unsupervised approach and considering both gene coexpression and protein–protein interaction networks, we identify different gene networks associated with various biological pathways (i.e. inflammation, cell cycle, and RNA translation), the expression of which are correlated with metastatic potentials across subsets of lineage types. By developing a regularized random forest regression model, we show that the combination of the gene module features expressed in the native cancer cells can predict their metastatic potentials with an overall Pearson correlation coefficient of 0.90. By analyzing transcriptomic profile data from cancer patients, we show that these networks are conserved in vivo and contribute to cancer aggressiveness. The intrinsic expression levels of these networks are correlated with drug sensitivity. Altogether, our study provides novel comparative insights into cancer cells’ intrinsic gene networks mediating metastatic potentials across different lineage types, and our results can potentially be useful for designing personalized treatments for metastatic cancers.
The activity of thermostable NiO/CeO2 heterointerface structure toward low-temperature catalytic CO–NO reaction
Authors: Moushumy Zannatul Mumtarin , Yoshida Hiroshi , Tokusada Kaori , Kuraoka Ai , Sakamoto Sota , Tsushida Masayuki , Machida Masato
Published: July 2024

The surface grafting of NiO onto CeO2 nanocrystallites generates heterointerface structures, providing efficient active sites for CO–NO reactions toward forming N2 and CO2. In this study, we investigated the effects of high-temperature thermal aging on the activity and nanostructure of the NiO/CeO2 catalyst. After thermal aging at 900 °C, the catalyst retained a high catalytic activity, whereas the reference catalysts lost theirs owing to considerable solid-state reactions and sintering. The as-prepared fresh NiO/CeO2 catalyst (calcined at 600 °C) contained high dispersions of NiO species in CeO2 crystallites. Conversely, the thermally aged catalyst comprised grown NiO and CeO2 crystallites were allowed to contact intimately to form thermostable interfaces, where the perimeter in the vicinity provided the Ni2+-incorporated CeO2 surface for removing and filling the oxygen species in the catalytic cycle toward facilitating CO–NO reactions. Based on in situ Fourier transform infrared and parallel isotopic reaction analyses, we confirmed the following as possible pathways: (i) the removal of the surface oxygen by the adsorbed CO to form an oxygen vacancy (VO), (ii) the interaction between the adsorbed NO with VO, and (iii) the N–O bond cleavage and the reaction with CO to form isocyanate, followed by the reaction with NO to produce N2.
A Bargaining Theory of US–China Economic Rivalry: Differentiating the Trade and Technology Wars
Authors: Wu Cathy Xuauxuan
Published: July 2024

This article examines the outbreak and persistence of US–China economic war, which comprises both the trade war, featured with retaliatory tariffs, and the technology war, featured with restrictions on Chinese access to US technologies. Building on the analytical framework of bargaining and war, I argue that different components of the economic war emerged from distinct causes. The outbreak of the trade war was primarily driven by the information problem, characterized by mutual uncertainty and the lack of effective communications. The technology war was largely a result of the commitment problem driven by the existing power’s concern regarding potential future changes in the balance of power. After examining the initiation stage during the Trump era, I further analyze how the economic war has unfolded during the Biden administration. While the prospect of a new trade war seems unlikely as mutual uncertainty diminishes, existing tariffs remain as the commitment problem on trade issues has become more critical. The preventive technology war is expected to persist, reflecting Washington’s ongoing concerns over China’s growing leadership in technology.
Temporal trends in mortality, heart failure hospitalization, and stroke in heart failure patients with and without atrial fibrillation: a nationwide study from 1997 to 2018 on 152 059 patients
Authors: Austreim Marte , Nouhravesh Nina , Malik Mariam E , Abassi Noor , Zahir Deewa , Garred Caroline Hartwell , Andersen Camilla F , Hansen Morten Lock , Olesen Jonas Bjerring , Fosbøl Emil , Østergaard Lauge , Køber Lars , Schou Morten
Published: July 2024

Aims

We aimed to investigate temporal trends in all-cause mortality, heart failure (HF) hospitalization, and stroke from 1997 to 2018 in patients diagnosed with both HF and atrial fibrillation (AF).

Methods and results

From Danish nationwide registers, we identified 152 059 patients with new-onset HF between 1997 and 2018. Patients were grouped according to year of new-onset HF and AF-status: Prevalent AF (n = 34 734), New-onset AF (n = 12 691), and No AF (n = 104 634). Median age decreased from 76 to 73 years between 1997 and 2018. The proportion of patients with prevalent or new-onset AF increased from 24.7% (n = 9256) to 35.8% (n = 14 970). Five-year risk of all-cause mortality went from 69.1% [confidence interval (CI): 67.9–70.2%] to 51.3% (CI: 49.9–52.7%), 62.3% (CI: 60.5–64.4%) to 43.0% (CI: 40.5–45.5%), and 61.9% (CI: 61.3–62.4%) to 36.7% (CI: 35.9–37.6%) for the Prevalent AF, New-onset AF, and No AF-group, respectively. Minimal changes were observed in the risk of HF-hospitalization. Five-year stroke risk decreased from 8.5% (CI: 7.8–9.1%) to 5.0% (CI: 4.4–5.5%) for the prevalent AF group, 8.2% (CI: 7.2–9.2%) to 4.6% (CI: 3.7–5.5%) for new-onset AF, and 6.3% (CI: 6.1–6.6%) to 4.9% (CI: 4.6–5.3%) for the No AF group. Simultaneously, anticoagulant therapy increased for patients with prevalent (from 42.7 to 93.1%) and new-onset AF (from 41.9 to 92.5%).

Conclusion

From 1997 to 2018, we observed an increase in patients with HF and co-existing AF. Mortality decreased for all patients, regardless of AF-status. Anticoagulation therapy increased, and stroke risk for patients with AF was reduced to a similar level as patients without AF in 2013–2018.
Microbial remineralization processes during postspring-bloom with excess phosphate available in the northern Baltic Sea
Authors: Vanharanta Mari , Santoro Mariano , Villena-Alemany Cristian , Piiparinen Jonna , Piwosz Kasia , Grossart Hans-Peter , Labrenz Matthias , Spilling Kristian
Published: July 2024

The phosphorus (P) concentration is increasing in parts of the Baltic Sea following the spring bloom. The fate of this excess P-pool is an open question, and here we investigate the role of microbial degradation processes in the excess P assimilation phase. During a 17-day-long mesocosm experiment in the southwest Finnish archipelago, we examined nitrogen, phosphorus, and carbon acquiring extracellular enzyme activities in three size fractions (<0.2, 0.2–3, and >3 µm), bacterial abundance, production, community composition, and its predicted metabolic functions. The mesocosms received carbon (C) and nitrogen (N) amendments individually and in combination (NC) to distinguish between heterotrophic and autotrophic processes. Alkaline phosphatase activity occurred mainly in the dissolved form and likely contributed to the excess phosphate conditions together with grazing. At the beginning of the experiment, peptidolytic and glycolytic enzymes were mostly produced by free-living bacteria. However, by the end of the experiment, the NC-treatment induced a shift in peptidolytic and glycolytic activities and degradation of phosphomonoesters toward the particle-associated fraction, likely as a consequence of higher substrate availability. This would potentially promote retention of nutrients in the surface as opposed to sedimentation, but direct sedimentation measurements are needed to verify this hypothesis.
Spatio-temporal changes of small protist and free-living bacterial communities in a temperate dimictic lake: insights from metabarcoding and machine learning
Authors: Karlicki Michał , Bednarska Anna , Hałakuc Paweł , Maciszewski Kacper , Karnkowska Anna
Published: July 2024

Microbial communities, which include prokaryotes and protists, play an important role in aquatic ecosystems and influence ecological processes. To understand these communities, metabarcoding provides a powerful tool to assess their taxonomic composition and track spatio-temporal dynamics in both marine and freshwater environments. While marine ecosystems have been extensively studied, there is a notable research gap in understanding eukaryotic microbial communities in temperate lakes. Our study addresses this gap by investigating the free-living bacteria and small protist communities in Lake Roś (Poland), a dimictic temperate lake. Metabarcoding analysis revealed that both the bacterial and protist communities exhibit distinct seasonal patterns that are not necessarily shaped by dominant taxa. Furthermore, machine learning and statistical methods identified crucial amplicon sequence variants (ASVs) specific to each season. In addition, we identified a distinct community in the anoxic hypolimnion. We have also shown that the key factors shaping the composition of analysed community are temperature, oxygen, and silicon concentration. Understanding these community structures and the underlying factors is important in the context of climate change potentially impacting mixing patterns and leading to prolonged stratification.
Modeling dominant height with USGS 3DEP LiDAR to determine site index in even-aged loblolly pine (Pinus taeda L.) plantations in the southeastern US
Authors: Ribas-Costa Vicent A , Gastón Aitor , Cook Rachel L
Published: July 2024

Accurate quantification and mapping of forest productivity are critical to understanding and managing forest ecosystems. Local LiDAR or photogrammetric surveys have been used to obtain reliable estimates of canopy heights, yet these acquisitions can entail substantial expenses. Therefore, we developed models using freely available US Geological survey (USGS) LiDAR data for prediction of dominant height to map site index across loblolly pine (Pinus taeda L.) plantations in the southeastern US. We used 2017–2020 national USGS 3D Elevation Program LiDAR acquisitions and explored how different height percentiles, grid output resolutions, time difference between LiDAR and ground acquisitions, tree height, and dominant height definition affected the proposed model. We built the dominant height models using 1301 ground plots. The final regression model was constructed with the 95th percentile of the height distribution of the first returns above-ground and had values of R2 = 0.89, RMSE = 1.55 m, and RRMSE = 7.66 per cent at a 20-m pixel grid, yet all the examined percentile-resolution combinations were acceptable. No effect evidence was found for time difference when the flight was less than 4 months in advance or after the ground measurement, and it was also found independent of pulse density when this variable was lower than 9.5 pulses m−2. Using the recorded age of the plantations, we assessed the error propagation when translating dominant height to site index in two site index models, obtaining an RRMSE lower than 10 per cent in both. We found that USGS LiDAR acquisitions can be reliably used to map dominant height at a large scale, and consequently used to map forest productivity when age is known. This ability adds more value to a tool proven widely applicable in time and space and offers a great opportunity for stakeholders in different fields of use.
Redesigning the Drosophila histone gene cluster: an improved genetic platform for spatiotemporal manipulation of histone function
Authors: Crain Aaron T , Nevil Markus , Leatham-Jensen Mary P , Reeves Katherine B , Matera A Gregory , McKay Daniel J , Duronio Robert J
Published: July 2024

Mutating replication-dependent (RD) histone genes is an important tool for understanding chromatin-based epigenetic regulation. Deploying this tool in metazoans is particularly challenging because RD histones in these organisms are typically encoded by many genes, often located at multiple loci. Such gene arrangements make the ability to generate homogenous histone mutant genotypes by site-specific gene editing quite difficult. Drosophila melanogaster provides a solution to this problem because the RD histone genes are organized into a single large tandem array that can be deleted and replaced with transgenes containing mutant histone genes. In the last ∼15 years several different RD histone gene replacement platforms were developed using this simple strategy. However, each platform contains weaknesses that preclude full use of the powerful developmental genetic capabilities available to Drosophila researchers. Here we describe the development of a newly engineered platform that rectifies many of these weaknesses. We used CRISPR to precisely delete the RD histone gene array (HisC), replacing it with a multifunctional cassette that permits site-specific insertion of either one or two synthetic gene arrays using selectable markers. We designed this cassette with the ability to selectively delete each of the integrated gene arrays in specific tissues using site-specific recombinases. We also present a method for rapidly synthesizing histone gene arrays of any genotype using Golden Gate cloning technologies. These improvements facilitate the generation of histone mutant cells in various tissues at different stages of Drosophila development and provide an opportunity to apply forward genetic strategies to interrogate chromatin structure and gene regulation.
The inclined conductive column effect: a new simple model for magnetotelluric anomalous phases
Authors: Inoue Tomohiro , Hashimoto Takeshi
Published: July 2024

Magnetotelluric data are sometimes accompanied by ‘anomalous’ impedance phases ($\phi $xy and $\phi $yx) in the off-diagonal components deviating from the first (0° < $\phi $xy < 90°) or third (−180° < $\phi $yx < −90°) quadrant, especially in long-period bands. This phenomenon is called the phases out-of-quadrant (POQ). The POQ poses a challenge in magnetotelluric modelling because simple 1-D or 2-D models cannot explain it. Previous studies have reported that strong inhomogeneity, anisotropy, or particular 3-D structures, such as the L-shaped or cross-shaped conductors, could explain the POQ. Aside from these models, we have discovered that a slanted columnar conductor also generates the POQ. Our systematic investigation through the synthetic forward modelling of an inclined conductive column with a varying geometry showed that the inclination angle and the column length may affect the POQ appearance. We investigated herein the behaviour of the electric currents around the inclined conductive column embedded in a resistive half-space. We found that the induced electric field in the region with the POQ tends to point in the opposite direction to the surrounding vectors. This result can reasonably explain the inverted phase in long-period bands. Furthermore, we confirmed that current is sucked into one end of the column, but discharged from the other end, suggesting that the column works as a current channel. The localized reverse vectors are associated with the current channelling along the inclined conductor, which generates the POQ. A volcanic conduit within a resistive host rock is one of the typical field examples of such an inclined channel. Our study suggests that the POQ is a helpful clue in imaging the geometry of a volcanic magma plumbing system through magnetotelluric surveys.
Quantifying the mineral magnetic signature of petroleum systems and their source rocks: a study on the Inner Moray Firth, UK North Sea
Authors: Perkins J R , Muxworthy A R , Fraser A J , Hu P
Published: July 2024

This study aims to expand on existing connections between magnetic minerals and hydrocarbons within petroleum systems. Previous studies have focussed on single-source petroleum systems whereas this study, for the first time, analyses a multi-source petroleum system to investigate potential correlations between different kerogen type source rocks and magnetic minerals. To do this, the study investigates the magnetic mineral characteristics of the Inner Moray Firth (IMF), UK North Sea, through room-, low- and high-temperature techniques, and correlates this to published basin and petroleum systems modelling results that show a three-source hydrocarbon mix. Magnetic mineral analysis identifies extensive evidence for magnetite, goethite and siderite, alongside more minor lepidocrocite and iron sulphides. Although we find that magnetite is ubiquitous within the IMF, its abundance is relatively low, and, in contrast, the relatively magnetically weak goethite is more likely the most abundant magnetic mineral throughout the IMF. In agreement with previous studies, we find magnetic enhancement at oil-water contacts (OWCs); however, here, we identify two different magnetic enhancement processes at OWCs in wells, which are dependent on the amount of sulphur available in the local environment. Wells with low levels of sulphur have increasing levels of magnetite towards the OWC, with the magnetic enhancement occurring at the top of the water-saturated section. Sulphur-rich environments display an increase in iron sulphides near the OWC at the bottom of the oil-saturated sediments. Additionally, we confirm the presence of siderite as indicator of upward vertical migration. Combining with petroleum system model predictions, we find direct links between iron hydroxide presence and Type I and II–III kerogen source rocks, and iron sulphide presence with Type II kerogen source rocks. This study shows the potential for further utilization of magnetic mineral analysis within hydrocarbon exploration and petroleum system definition.
Accumulation of Heavy Metals in Conyza canadensis
Authors: Wright Patrick B , Steven Janet C
Published: July 2024

Synopsis

Many plant species are known to take up metals from the soil and accumulate them to potentially toxic levels. This may provide tolerance to soils with high metal content or a defensive mechanism against herbivores and pathogens. Accumulators, plants that uptake and store elevated concentrations of metals, can be used in phytoremediation as a means to remove metals from contaminated soils. In this study, the native weed Conyza canadensis was grown in soils contaminated with elevated levels of lead (Pb), barium (Ba), zinc (Zn), copper (Cu), or chromium (Cr). All metals, except for Cr, were accumulated by the plants. Zinc and Cu, both essential elements, accumulated to the highest levels, while Pb and Ba were present at lower levels. All treatments except Cr showed accelerating rates of accumulation over the eight-week experiment. Barium, Cu, and Cr reduced aboveground biomass of the plants, indicating toxicity or a cost to metal accumulation. Lead and Zn promoted early flowering, while plants accumulating Ba, Cr, and Cu flowered in lower numbers. Overall, C. canadensis has promise in the phytoremediation of Pb, Cu, and Zn.
Predicted ecological consequences of wave energy extraction and climate-related changes in wave exposure on rocky shore communities
Authors: Want Andrew , Waldman Simon , Burrows Michael T , Side Jonathan C , Venugopal Vengatesan , Bell Michael C
Published: July 2024

Wave energy has the potential to contribute in the transition to decarbonized electricity generation. Extracting wave energy might be expected to have ecological impacts on rocky shore intertidal communities where exposure is one of the most important factors determining species structure and composition. With global climatic change, coastal exposure is predicted to increase with greater significant wave height. The wave-exposed west coast of Orkney, Scotland, UK, is the site of pre-commercial wave device testing. Surveys of 39 rocky shore sites along this coast identified key species and abundances, and quantified exposure-modifying topographic variables. A spectral wave model was constructed to compare baseline, wave extraction, climate change, and combined scenarios. Generalized additive modelling was used to describe the relationship between species, topography, and exposure. Results show that individual species differentially respond to exposure changes with ‘winners’ and ‘losers’ at site level. Overall, community responses are expected to be far greater following predicted climatic change than to industrial-scale wave energy extraction, depending on spatial scale. In combination, energy extraction may reduce the effects of climate-change-related increases in wave exposure of rocky shores. Predicting how location-specific biotic assemblages respond to changes in wave energy as a result of long-term forcing agents provides a valuable marine resource management tool.