bluuebunny/crossref_metadata_2025_split huggingface dataset:
Failure analysis of glass fiber and basalt fiber reinforced polymer composites under an extreme environment with high‐temperature, high‐pressure and H2S/CO2 exposure
Authors: Sun Haoming , Xiang Dong , Liu Zhuxi , Liu Libing , Harkin‐Jones Eileen , Wang Menghan , Tan Wei , Luo Pingya , Zhang Jie , Wang Bin , Liu Yifeng , Wu Yuanpeng 
Published: April 2024

AbstractFiber‐reinforced polymers composites (FRPs) are widely used in the industrial field, but their failure mechanism in extreme environments is usually unclear. In this work, the effect of high‐temperature, high‐pressure and H2S/CO2 extreme environment, similar to oil and gas field conditions, on raw fibers and unidirectional FRPs was investigated. The results showed that the glass fibers (GFs) suffered extensive degradation with the presence of metal sulfides in the precipitate, whereas basalt fibers (BFs) showed localized degradation. The flexural modulus of glass fiber reinforced polymer composite (GFRP) after degradation decreased by 28.8% compared to 25.6% for the basalt fiber reinforced polymer composite (BFRP). The interlaminar shear strength and flexural strength of the BFRP decreased by 20.3% and 24.7% respectively. In contrast, the GFRP had a reduction of 55.2% in flexural strength after degradation. Finite element method (FEM) analysis showed that the GFRP exhibited severe cohesive interface damage, while the primary failure mode of BFRP remained essentially unchanged with a combination of fiber damage and cohesive interface damage. This study confirms the superior degradation resistance of BF/BFRP over GF/GFRP in the simulated environment and highlights its promising application potential in oil and gas field service.Highlights
Filament winding was used to fabricate the GFRP and BFRP.
Revealed distinct surface morphology changes in GFs and BFs under simulated oil and gas field conditions.
Superior degradation resistance of BFRP over GFRP was found in the extreme environment.
Demonstrated superior chemical stability and mechanical properties of BFRP over GFRP.
Used FEM to investigate the failure modes of FRPs before and after exposure.
Polyglutamine disease proteins: Commonalities and differences in interaction profiles and pathological effects
Authors: Bonsor Megan , Ammar Orchid , Schnoegl Sigrid , Wanker Erich E. , Silva Ramos Eduardo 
Published: April 2024

AbstractCurrently, nine polyglutamine (polyQ) expansion diseases are known. They include spinocerebellar ataxias (SCA1, 2, 3, 6, 7, 17), spinal and bulbar muscular atrophy (SBMA), dentatorubral‐pallidoluysian atrophy (DRPLA), and Huntington's disease (HD). At the root of these neurodegenerative diseases are trinucleotide repeat mutations in coding regions of different genes, which lead to the production of proteins with elongated polyQ tracts. While the causative proteins differ in structure and molecular mass, the expanded polyQ domains drive pathogenesis in all these diseases. PolyQ tracts mediate the association of proteins leading to the formation of protein complexes involved in gene expression regulation, RNA processing, membrane trafficking, and signal transduction. In this review, we discuss commonalities and differences among the nine polyQ proteins focusing on their structure and function as well as the pathological features of the respective diseases. We present insights from AlphaFold‐predicted structural models and discuss the biological roles of polyQ‐containing proteins. Lastly, we explore reported protein–protein interaction networks to highlight shared protein interactions and their potential relevance in disease development.
Navigating the digital frontier during the COVID‐19 pandemic and EVALI epidemic: The impact of social media on public health
Authors: Ngoma Chimwemwe , Matatiyo Apatsa , Oke Gabriel Ilerioluwa , Adebisi Yusuff Adebayo , Shomuyiwa Deborah Oluwaseun 
Published: April 2024

AbstractThis commentary explores how social media influenced public health narratives and responses during two recent health crises, the COVID‐19 global pandemic and the e‐cigarette or vaping product use–associated lung injury (EVALI) epidemic. In the context of COVID‐19 pandemic, social media played a dual role, acting as both a catalyst for information dissemination and a breeding ground for misinformation. This situation highlighted the challenges public health institutions face in navigating online narratives and maintaining public trust during crises. Conversely, the EVALI epidemic shed light on how social media narratives can impact public perception and policy decisions. Initially, attributed to nicotine vaping, subsequent investigations revealed that contaminated cannabis oils containing vitamin E acetate were the actual cause, leading to shifts in public discourse and regulatory considerations. This case underscores the importance of accurate information dissemination to prevent misinterpretations that could negatively impact public health interventions. The commentary also highlights the evolving nature of online narratives and the need for public health agencies to adapt their strategies continually. Fact‐checking programs, public health campaigns, and collaborations with technology companies emerged as critical strategies to combat misinformation and promote evidence‐based practices. However, addressing the root causes of misinformation, such as addressing distrust in institutions, remains an ongoing challenge requiring multifaceted approaches. Looking ahead, controlling online narratives during health crises will continue to present challenges as social media platforms evolve and new challenges emerge. Finding a balance between information sharing and privacy protection while fostering digital literacy skills among the public will be paramount. Collaborative efforts among public health agencies, technology companies, and communities will be essential in navigating and managing online narratives effectively. This commentary underscores the interplay between social media and public health, highlighting the need for strategic interventions, accurate information dissemination, and ongoing adaptation to address emerging challenges in the digital age.
Functional predictability of universal gene circuits in diverse microbial hosts
Authors: Qin Chenrui , Xu Tong , Zhao Xuejin , Zong Yeqing , Zhang Haoqian M. , Lou Chunbo , Ouyang Qi , Qian Long 
Published: April 2024

AbstractAlthough the principles of synthetic biology were initially established in model bacteria, microbial producers, extremophiles and gut microbes have now emerged as valuable prokaryotic chassis for biological engineering. Extending the host range in which designed circuits can function reliably and predictably presents a major challenge for the concept of synthetic biology to materialize. In this work, we systematically characterized the cross‐species universality of two transcriptional regulatory modules—the T7 RNA polymerase activator module and the repressors module—in three non‐model microbes. We found striking linear relationships in circuit activities among different organisms for both modules. Parametrized model fitting revealed host non‐specific parameters defining the universality of both modules. Lastly, a genetic NOT gate and a band‐pass filter circuit were constructed from these modules and tested in non‐model organisms. Combined models employing host non‐specific parameters were successful in quantitatively predicting circuit behaviors, underscoring the potential of universal biological parts and predictive modeling in synthetic bioengineering.
Distributed bounded finite‐time cooperative control algorithm for multiple nonlinear manipulators
Authors: Cong Yongzheng , Du Haibo , Li Xueling , Jin Xiaozheng 
Published: April 2024

AbstractFor the position synchronization control problem of multiple nonlinear manipulator systems, a bounded distributed cooperative controller is designed in this paper. Based on a fixed‐time position observer, a distributed finite‐time synchronization controller is designed by using the saturated control technique and homogenous system theory. Compared with the existing results, the proposed distributed cooperative control algorithm not only guarantees finite‐time convergence but also satisfies the input saturation. Finally, some numerical simulation results are presented to verify the feasibility of the theory results with six‐degree‐of‐freedom robots.
Consensus of linear multi‐agent systems under switching topology by sampled‐data output feedback control
Authors: Zhang Ying , Su Youfeng 
Published: April 2024

AbstractThis paper studies both synchronous and asynchronous consensus problems for linear multi‐agent systems under switching topology. A novel distributed continuous‐discrete observer is established by solely using the relative sampled output messages, which needs neither to store messages from neighboring agents nor estimate the information of itself and all neighbors. Based on the estimation provided by the distributed observer, a distributed output feedback control with digital form is synthesized, which allows each agent to update the value of its controller at the synchronous/asynchronous sampling instants. It is of interest to see that, for the class of chain‐integrator multi‐agent systems, the proposed control approach allows the sampling periods to be chosen freely and thus would be more practical in some situations from the perspective of energy saving. The theoretical results are illustrated by formation flying of spacecraft and synchronization of multiple double‐integrators.
Adaptive finite‐time recoil control of deepwater drilling riser systems with nonlinear forces and saturation input using switched event‐triggered scheme
Authors: Cheng Tingting , Zhang Dawei , Zhu Shuqian 
Published: April 2024

AbstractThis article investigates the finite‐time recoil control problem of deepwater drilling riser systems with nonlinear friction force, tension force and saturation input. For the friction force, a new approximation model based on radial basis function neural networks is presented, which not only can ensure a better approximation effect than the sine‐function type and exponential‐polynomial‐function type computational models, but also can be easily used for control design. Different from the existing linear optimal control methods, a neural‐network‐based adaptive backstepping control method is proposed to deal with the nonlinear friction and tension forces, which can achieve better recoil control responses. An auxiliary system combining with the change of coordinates is employed to compensate the saturation input effect. To prolong the average release interval of control input while preserving satisfied control performance, a new switched event‐triggered control (ETC) scheme is developed, in which the triggering conditions are switched between the fixed and relative thresholds based on the strength of control signal. With the event‐triggered controller, the practical finite‐time stability condition of recoil control system is derived and the Zeno behavior is avoided. Numerical results are given to show the advantages of the proposed methods in handling the model nonlinearities, finite‐time stability and ETC performance of riser‐tension systems.
Collaborative interference avoidance technology in GEO‐LEO co‐existing satellite system
Authors: He Mengmin , Cui Gaofeng , Wu Mengjing , Wang Weidong 
Published: April 2024

SummaryRecently, the Low Earth Orbit (LEO) satellite and Geostationary Earth Orbit (GEO) satellites share the same frequency to enhance spectrum efficiency in response to the scarcity of spectral resources. However, overlapping coverage areas emerge when LEO‐GEO and LEO‐LEO beams cover the same ground area in the GEO‐LEO co‐existing satellite system. Thus, the GEO‐LEO inter‐system interference and the LEO intra‐system interference are generated, which leads to more severe and complex interference. To solve the co‐channel interference problem without sacrificing the performance of the LEO system, a collaborative interference avoidance technology is proposed for the GEO‐LEO co‐existing satellite system. Firstly, the LEO satellite and user regrouping strategy (SURS) is employed to effectively avoid severe co‐channel interference by changing service satellites. Then, based on regrouping satellite and user pairs, a proximal policy optimization (PPO)‐based deep reinforcement learning (DRL) method is adopted to realize further continuous beam pointing optimization (BPO) of the LEO user antenna and reduce the co‐channel interference. Finally, simulation results verify that the proposed scheme can achieve the goal of interference mitigation and continuous service.
Dealing with soft variables and data scarcity: lessons learnt from quantification in a participatory system dynamics modelling process
Authors: Pluchinotta Irene , Zhou Ke , Zimmermann Nici 
Published: April 2024

AbstractSystem dynamics (SD) models are commonly used for structuring complex problems to support decision‐making. They are used to investigate areas in which limited knowledge is available, describing nonlinear relationships and including intangible elements. Although this explorative nature is one of the key advantages, it also represents a challenge for quantifying the intangible, i.e. more qualitative aspects of an SD model, especially when it is not possible to apply conventional analytical methods due to data scarcity. Procedures to obtain and analyse information using participatory approaches are limited. First, this article outlines existing quantification methods and related open questions when dealing with soft variables and data scarcity. Secondly, it summarises the quantification process developed during a participatory SD process, describing how we dealt with data scarcity and soft variables. Lastly, we suggest a quantification framework in relation to data availability and level of stakeholder engagement. © 2024 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society.
PCG: A joint framework of graph collaborative filtering for bug triaging
Authors: Dai Jie , Li Qingshan , Xie Shenglong , Li Daizhen , Chu Hua 
Published: April 2024

AbstractBug triaging is a vital process in software maintenance, involving assigning bug reports to developers in the issue tracking system. Current studies predominantly treat automatic bug triaging as a classification task, categorizing bug reports using developers as labels. However, this approach deviates from the essence of triaging, which is establishing bug–developer correlations. These correlations should be explicitly leveraged, offering a more comprehensive and promising paradigm. Our bug triaging model utilizes graph collaborative filtering (GCF), a method known for handling correlations. However, GCF encounters two challenges in bug triaging: data sparsity in bug fixing records and semantic deficiency in exploiting input data. To address them, we propose PCG, an innovative framework that integrates prototype augmentation and contrastive learning with GCF. With bug triaging modeled as predicting links on the bipartite graph of bug–developer correlations, we introduce prototype clustering‐based augmentation to mitigate data sparsity and devise a semantic contrastive learning task to overcome semantic deficiency. Extensive experiments against competitive baselines validate the superiority of PCG. This work may open new avenues for investigating correlations in bug triaging and related scenarios.
The effect of tax‐based price increases on cigarette and fermented liquor consumption: Evidence from tax reform laws in the Philippines
Authors: Lacaza Rutcher M. , Estrada Miguel Antonio G. 
Published: April 2024

AbstractWe evaluate the effect of the recent spate of tax reform laws on cigarette and fermented liquor consumption in the Philippines using an error correction model that utilizes regularly available national data. Since 2012, the Philippine government passed three reform measures that substantially increases cigarette and alcohol excise taxes to address the problems of smoking and noncommunicable diseases, and raises revenue for the country's national health insurance program. This paper offers a potential alternative, considering the estimation challenges stemming from the scarcity of data from individual‐ and household‐based surveys in developing countries like the Philippines. The volume of removals is used to measure consumption while the consumer price index is used to measure price changes. Quarterly national data from 2000 to 2021 yields an elasticity estimate for cigarette demand that is consistent with earlier studies that used individual‐ and household‐level data. Estimates for fermented liquors, meanwhile, offer a basis for policymaking and future studies. Overall, findings highlight the potential of using the error correction model and cointegration techniques to estimate elasticity for countries with limited data, and bolsters the argument on the effectiveness of taxes in influencing health behavior.
Linc-NSC affects cell differentiation, apoptosis and proliferation in mouse neural stem cells and embryonic stem cells in vitro and in vivo
Authors: Guo Lili , Zou Dan , Qiu Wenqiao , Fei Fan , Chen Lihua , Chen Wenjin , Xiong Huan , Li Xinda , Wang Yangyang , Gao Mingjun , Zhu Jianwei , Zhang Jin , He Yunsen , Gao Mou , Xu Ruxiang 
Published: April 2024

Abstract
Background
Stem cell therapy is a promising therapeutic strategy. In a previous study, we evaluated tumorigenicity by the stereotactic transplantation of neural stem cells (NSCs) and embryonic stem cells (ESCs) from experimental mice. Twenty-eight days later, there was no evidence of tumor formation or long-term engraftment in the NSCs transplantation group. In contrast, the transplantation of ESCs caused tumor formation; this was due to their high proliferative capacity. Based on transcriptome sequencing, we found that a long intergenic non-coding RNA (named linc-NSC) with unknown structure and function was expressed at 1100-fold higher levels in NSCs than in ESCs. This finding suggested that linc-NSC is negatively correlated with stem cell pluripotency and tumor development, but positively correlated with neurogenesis. In the present study, we investigated the specific role of linc-NSC in NSCs/ESCs in tumor formation and neurogenesis.

Methods
Whole transcriptome profiling by RNA sequencing and bioinformatics was used to predict lncRNAs that are widely associated with enhanced tumorigenicity. The expression of linc-NSC was assessed by quantitative real-time PCR. We also performed a number of in vitro methods, including cell proliferation assays, differentiation assays, immunofluorescence assays, flow cytometry, along with in vivo survival and immunofluorescence assays to investigate the impacts of linc-NSC on tumor formation and neurogenesis in NSCs and ESCs.

Results
Following the knockdown of linc-NSC in NSCs, NSCs cultured in vitro and those transplanted into the cortex of mice showed stronger survival ability (P < 0.0001), enhanced proliferation(P < 0.001), and reduced apoptosis (P < 0.05); the opposite results were observed when linc-NSC was overexpressed in ESCs. Furthermore, the overexpression of linc-NSC in ECSs induced enhanced apoptosis (P < 0.001) and differentiation (P < 0.01), inhibited tumorigenesis (P < 0.05) in vivo, and led to a reduction in tumor weight (P < 0.0001).

Conclusions
Our analyses demonstrated that linc-NSC, a promising gene-edited target, may promote the differentiation of mouse NSCs and inhibit tumorigenesis in mouse ESCs. The knockdown of linc-NSC inhibited the apoptosis in NSCs both in vitro and in vivo, and prevented tumor formation, revealing a new dimension into the effect of lncRNA on low survival NSCs and providing a prospective gene manipulation target prior to transplantation. In parallel, the overexpression of linc-NSC induced apoptosis in ESCs both in vitro and in vivo and attenuated the tumorigenicity of ESCs in vivo, but did not completely prevent tumor formation.
Optimal fissioning strategies of social insects with respect to colony dynamics and nest founding probability
Authors: Hovestadt T. , Kohl P. , Mitesser O. 
Published: April 2024

AbstractSocial insects demonstrate two fundamentally different modes of reproduction, independent colony foundation (ICF) by single fertilized queens or dependent colony foundation (DCF) by fissioning of existing colonies into two or several new colonies (swarms). In some species, both reproductive modes occur in parallel. The benefits and disadvantages of DCF vs. ICF have been widely discussed and been subject to empirical studies, but a formal theoretical treatment of the topic is still incomplete. Taking honey bees as example, we provide a resource allocation model of colony dynamics to analyze the ecological conditions under which DCF may be favored over ICF. Using mathematical and numerical methods, we show that it critically depends on the survivorship function linking swarm size to the probability of swarm establishment whether ICF or DCF results in a higher output of surviving new colonies. Because building larger swarms requires larger inter-swarm time intervals, DCF can only be a better strategy if this disadvantage is over-compensated for by a strong size-dependent swarm survivorship and survival of single queens is very low. Colony growth rate has no effect on this decision and the impact of maximum possible colony size is negligible. Further, there is a discontinuity in the optimal swarm size, so that either a swarm size of 1 (ICF) is the best strategy, or emitting swarms of considerable size (DCF). Consequently, a direct evolutionary transition from ICF to DCF appears unlikely and may have been triggered by selective pressures promoting movement of complete nests or distributing single colonies over several nests (polydomy).