bluuebunny/crossref_metadata_2025_split huggingface dataset:
Views and experience of non-hospitalised individuals with Long COVID of using pacing interventions: a mixed methods study
Authors: McMullan Christel , Haroon Shamil , Turner Grace , Aiyegbusi Olalekan , Hughes Sarah , Flanagan Sarah , Subramanian Anuradhaa , Nirantharakumar Krish , Davies Elin , Frost Chris , Jackson Louise , Guan Naijie , Alder Yvonne , Chong Amy , Buckland Lewis , Jeyes Felicity , Stanton David , Calvert Melanie 
Published: June 2024

Abstract

Background
Long COVID is highly prevalent and debilitating, with key symptoms including fatigue, breathlessness, and brain fog. Pacing is an approach to energy conservation used to help people with chronic conditions like ME/CFS manage the impact of their condition, and could be a useful strategy for people with Long COVID. The aim of this study was to explore the views and experiences of non-hospitalised adults with Long COVID of pacing as an intervention.
Methods
This mixed methods study is part of the Therapies for Long COVID (TLC) Feasibility trial. A feasibility questionnaire was developed for participants. In addition, a sub-sample of participants were interviewed at the end of the study.
Results
28 participants completed the feasibility questionnaire and 19 participants took part in a qualitative interview. Participants found that pacing helped improve motivation and activity planning. Concerns included challenges due to time constraints, complexity of the intervention, and limited instructions.
Conclusion
Pacing for Long COVID may offer potential benefits and is feasible but further research is required to demonstrate its benefits. Overall, research on pacing in the context of Long COVID has the potential to enhance our understanding of symptom management and rehabilitation strategies for this emerging population.
Graphene-Modified Concrete: Understanding Mechanical Behaviour with Varied Coarse Aggregates
Authors: Kaushik Pooja , Hassan Owais Ul , Mehmood Gauhar 
Published: June 2024

Abstract

Concrete, a widely used construction material, faces challenges such as resource depletion, noise, and dust pollution. Conventional concrete has a reduced lifespan and increased maintenance, with brittleness issues. To address these issues, graphene oxide, an admixture, has been proposed as an alternative binder in cement coarse aggregations. The study uses three types of coarse aggregations which employ coarse aggregates from different sites in Delhi: granite from Vasant Kunj (Phase-2), sandstone from Sarai Madhavpur, and quartzite from Delhi Metro Mall. The study aims to understand the synergistic effects of graphene oxide and aggregates on the mechanical properties of the composite, including compressive, tensile, and flexural strength. Graphene insertion in concrete results in ultra-high performance, with slump values decreasing as the percentage of graphene increases. Sandstone, quartzite, and granite exhibit the slump decrease, with sandstone showing the maximum decrease. Graphene incorporation positively influences compressive strength, with granite showing the most significant improvement. Split tensile strength also shows a notable increase, with granite demonstrating the most significant increase, even at moderate graphene percentages. Flexural strength also shows a substantial increase. This is due to enhanced bonding between aggregate particles and graphene oxide sheets, resulting in heightened tensile strength and improved crack resistance.
Global-scale multidecadal variability in climate models and observations. Part II: The stadium wave
Authors: Kravtsov Sergey , Westgate Andrew , Gavrilov Andrei 
Published: June 2024

Abstract

A significant fraction of multidecadal fluctuations in the reanalysis-based gridded estimates of the observed climate variability over the past century and a half lie outside of the envelope generated by ensembles of climate-model historical simulations. Several pattern-recognition methods have been previously used to map out a truly global reach of the observed vs. simulated climate-data differences; in our own work we dubbed these global discrepancies the stadium wave to highlight their most striking spatiotemporal characteristic. Here we used a novel combination of such methods in conjunction with a large multi-model ensemble and two popular twentieth-century reanalysis products to: (i) succinctly describe the geographical evolution of the observed stadium wave in the annually sampled near-surface atmospheric temperature and mean sea-level pressure fields in terms of three basic patterns; (ii) show the robustness of this identification with respect to methodological details, including the demonstration of the truly global character of the stadium wave; and (iii) provide essential clues to its dynamical origin. Part I of this study decomposed all input time series into the forced signal and the residual internal variability; multi-model forced-signal estimates were also decomposed into their common-evolution part and the individual-model residuals. Analysis of the latter residuals suggests a contribution to the stadium-wave dynamics from a delayed climate response to variable external forcing despite the observed stadium-wave patterns’ exhibiting the magnitudes and the level of global teleconnectivity unmatched by the forced-signal residuals. Part III of this paper will compare the observed stadium wave with the model simulated internal patterns.
Isolation and Identification of Endophytic Fungi from the Roots of two epiphytic orchids: Rhynchostylis retusa (L.) Bl. and Vanda tessellata (L.) Bl
Authors: Sayem M Abu , Miah M Shahin , Hossain Mohammad Musharof 
Published: June 2024

Abstract

Two fungal endophytes were isolated and identified from two indigenous orchids of Bangladesh namely, Rhynchostylis retusa (L.) Bl. and Vanda tessellata (L.) Bl. Nature of fungal colonization, seasonal variations of colonization in root cortex cells were also studied. The fungal endophytes isolated from two different orchids differed in their cultural morphology and microscopic features such as colony morphology, colour of the colony, presence/absence of monilioid cells or spores and diameter of vegetative hyphae. The microscopic features i.e., hyphal structure, right-angle branching of hyphae, slight constriction at the branching point, shape and diameter of monilioid cells of the endophytic fungus isolated from R. retusa showed resemblance with the anamorphic Rhizoctonia-like fungi Ceratobasidium sp. On the other hand, the fungal endophytes isolated from the roots of V. tessellata produced huge number of spores. The cultural characteristics and spore morphology of this fungi corroborated resemblance with pathogenic fungi, Fusarium sp. The identity of the fungi was further reconfirmed through sequencing of the internal transcribed spacer (ITS) of the nuclear ribosomal DNA (nrDNA). The BLASTn search of ITS region sequences of the endophytic fungi isolated from R. retusa exhibited maximum similarity (97%) with an orchid mycorrhizal fungi (OMF), Ceratobasidium papillatum (GeneBank Accession No. OQ073691), while the fungal endophyte isolated from V. tessellata showed maximum similarity (99%) with Fusarium ambrosium (GeneBank Accession No. OP752102). The phylogenetic tree constructed using ITS region sequences of the isolated fungal endophytes and their closely linked species from genebank data developed two distinct groups. The conventional and molecular approaches applied for identification of these OMF can be followed for easy and accurate identification of other OMF.
ZTA: A Novel Zero Trust Framework for Detection and Prevention of Malicious Android Applications
Authors: Nazir Aleena , Iqbal Zafar , Muhammad Zia 
Published: June 2024

Abstract

The proliferation of preloaded apps and third-party applications has raised significant concerns regarding user security and privacy. This study introduces the Zero Trust Architecture (ZTA), a novel approach to addressing the issues caused by poorly designed vulnerable mobile applications. ZTA employs a comprehensive strategy to safeguard user privacy, incorporating thorough app permission analysis alongside dynamic behavior assessment. The proposed framework closely monitors real-time app behavior and leverages the MITRE ATT&CK framework to identify security threats, vulnerabilities, and essential Tactics, Techniques, and Procedures (TTPs). The ZTA empowers users to make informed choices about app usage, promote data security, and cultivate a safer environment. Through this framework, users can confidently decide on app usage, ensuring the safeguarding of their data and fostering a more secure mobile app ecosystem. This research presents a proactive approach to privacy-conscious app utilization, bolstering user trust in the continually evolving realm of Android applications.
Modulation of Neural Correlates of Model-based Performance with Impulsivity and Compulsivity
Authors: Dück Kerstin , Wüllhorst Raoul , Overmeyer Rebecca , Endrass Tanja 
Published: June 2024

Abstract

Impaired goal-directed behavior is associated with a range of mental disorders, implicating underlying transdiagnostic factors. While compulsivity has been linked to reduced model-based (MB) control, impulsivity has rarely been studied in the context of reinforcement learning despite its links to reward processing and cognitive control. This study investigated the neural mechanisms underlying MB control and the influence of impulsivity and compulsivity. We analyzed EEG data from 238 individuals during a two-step decision making task. Single-trial analyses revealed that while feedback-related negativity (FRN) amplitudes were higher after common transitions and negative/neutral reward prediction error (RPE), the P3a and P3b were enhanced after rare transitions and both positive and negative RPE. In a second step, we regressed the mean b values of the effect of RPE on the EEG signals onto self-reported impulsivity and compulsivity and weighting parameter w (representing behavioral MB control). The effect of RPE on FRN-related activity was mainly associated with higher wscores. The interaction of impulsivity and w influenced both FRN- and P3a-related activity. The modulation of P3a by RPE was also negatively associated with compulsivity, pointing to a deficient mental model in highly compulsive individuals. Further research is needed to understand these alterations in decision-making processes.
Identification of soluble biomarkers that associate with distinct manifestations of long COVID
Authors: Buggert Marcus , Gao Yu , Cai Curtis , Adamo Sarah , Biteus Elsa , Kamal Habiba , Dager Lena , Miners Kelly , Llewellyn-Lacey Sian , Ladell Kristin , Sabberwal Pragati , Bentley Kirsten , Wu Jinghua , Akhirunnesa Mily , Jones Samantha , Julin Per , Lidman Christer , Stanton Richard , Davies Helen , Aleman Soo , Price David , Goepfert Paul , Deeks Steven , Peluso Michael 
Published: June 2024

Abstract

Long COVID is a heterogeneous clinical syndrome of uncertain etiology triggered by infection with SARS-CoV-2. We employed ultrasensitive approaches to profile the immune system and plasma proteome in healthy convalescent individuals and patients with long COVID. Symptomatic disease was not consistently associated with quantitative differences in immune cell lineage composition or antiviral T cell immunity. Healthy convalescent individuals nonetheless exhibited higher titers of neutralizing antibodies against SARS-CoV-2 than patients with long COVID, and extensive phenotypic analyses revealed a subtle increase in the expression of some coinhibitory receptors, most notably PD-1 and TIM-3, among SARS-CoV-2 nonspike-specific CD8+ T cells in patients with long COVID. We further identified a plasma biomarker signature of disease linking breathlessness with apoptotic inflammatory networks centered on the hub protein TRAF2 and dysregulated pathways associated with lung injury, cell cycle progression, and platelet activation, which could potentially inform the diagnosis and treatment of long COVID.
Multi-Modality Deep Infarct: Non-invasive identification of infarcted myocardium using composite in-silico-human data learning
Authors: Mehdi Rana Raza , Kadivar Nikhil , Mukherjee Tanmay , Mendiola Emilio A. , Shah Dipan J. , Karniadakis George , Avazmohammadi Reza 
Published: June 2024

Abstract

Myocardial infarction (MI) continues to be a leading cause of death worldwide. The precise quantification of infarcted tissue is crucial to diagnosis, therapeutic management, and post-MI care. Late gadolinium enhancement-cardiac magnetic resonance imaging (LGE-CMR) is regarded as the gold standard for precise infarct tissue localization in MI patients. A fundamental limitation of LGE-CMR is the invasive intravenous introduction of gadolinium-based contrast agents that present potential high-risk toxicity, particularly for individuals with underlying chronic kidney diseases. Herein, we develop a completely non-invasive methodology that identifies the location and extent of an infarct region in the left ventricle via a machine learning (ML) model using only cardiac strains as inputs. In this transformative approach, we demonstrate the remarkable performance of a multi-fidelity ML model that combines rodent-based in-silico-generated training data (low-fidelity) with very limited patient-specific human data (high-fidelity) in predicting LGE ground truth. Our results offer a new paradigm for developing feasible prognostic tools by augmenting synthetic simulation-based data with very small amounts of in-vivo human data. More broadly, the proposed approach can significantly assist with addressing biomedical challenges in healthcare where human data are limited.
Electron Density Distribution using Maximum Entropy Method and Conductivity Studies of Highly Dense BaZr0.85Ho0.10Y0.025Nd0.025O3-δ Electrolyte Ceramic for Intermediate Temperature Solid Oxide Fuel Cells
Authors: Singh Bijendra , Kumar Sandeep , Singh Sunder , Kumar Upendra , Kumar Manindra , Kumar Anil , Saini Deepash Shekhar 
Published: June 2024

Abstract

In this research work, highly dense BaZr0.85Ho0.10Y0.025Nd0.025O3-δ electrolyte ceramic was synthesized through a cost-effective flash pyrolysis route followed by conventional sintering for intermediate-temperature solid oxide fuel cells. The calcined powder and sintered pellet were characterized through various techniques like HRXRD, HRTEM, FESEM, EDS, and Raman spectroscopy. The XRD pattern of calcined and sintered pellet shows the pure cubic phase with space group symmetry through the Rietveld refinement. The study of the electron density distribution of calcined powder and sintered pellet calculated by the maximum entropy method reveals the presence of oxygen vacancies at the octahedral site in the sintered sample. The microstructure of the fracture surface of the sintered sample indicates highly dense with a relative density of 97.4% through FESEM. The Raman analysis confirms the distortion along the c-axis and oxygen vacancies in the octahedral site of BaZr0.85Ho0.10Y0.025Nd0.025O3-δ. Impedance spectroscopy measurements was conduct in the temperature range of 50 to 700 ℃ and frequency range of 1 Hz to 1 MHz. The Nyquist plots in the temperature range of 350 to 700 ℃ provide information of three types of relaxations corresponding to grain and grain boundary, and electrode effect. The temperature-dependent exponent (n) associated with grain and grain boundary decreases with the increase in temperature, indicating that large polaron hopping is involved in the electrical conduction mechanism.
High-Altitude Parabolic Detection: An Innovative Algorithm That Combines MOG-CNN and Enhanced SORT
Authors: Zhu QiGuang , Liu Meng , Wu WenLong , Chen WeiDong 
Published: June 2024

Abstract

Addressing the challenges of complex backgrounds, small parabolic targets, indistinct appearance features of parabolas, and easy loss of parabolic tracking in high-altitude parabolic object detection, this paper proposes a hybrid approach integrating the Mixture of Gaussians Background Modeling (MOG) algorithm with neural networks and an improved Simple Online and Realtime Tracking (SORT) algorithm for parabolic tracking. Firstly, to mitigate the issues of small target parabolas and complex backgrounds, a region-specific conditional filtering is introduced to reduce non-parabolic foreground in foreground detection while preserving parabolic foreground. Secondly, to tackle the problem of indistinct appearance features of parabolas, a multi-frame channel fusion technique is employed to enhance motion features, and a lightweight classification network is designed to differentiate parabolic objects. Finally, to address the challenge of easy loss of parabolic tracking, the state space and matching metrics of SORT are improved to better match parabolic trajectories. Experimental results demonstrate that the improved parabolic detection method reduces detection quantity by 97\% compared to the original MOG algorithm while exhibiting a 7\% decrease in recall rate. Additionally, compared to the original SORT algorithm, the improved parabolic tracking method reduces the number of ID switches by 50%, increases the MOTA metric by 8%, and increases the TIOU metric by 7%.
Code: https://figshare.com/articles/dataset/High-Altitude Object Detection algorithm/25778430. Dataset:https://figshare.com/articles/dataset/High-Altitude Object Detection Dataset/25778289.
Laser-Activated Lightweight Porous Linear Actuation Micro Mechanisms through Multiscale Topology Optimization with Considering Radiation
Authors: Ali Musaddiq Al , Shimoda Masatoshi 
Published: June 2024

Abstract

This study applies multi-physics concurrent multiscale topology optimization to develop a lightweight porous linear actuation mechanism activated by laser energy. It meticulously explores thermal dissipation mechanisms, incorporating conduction, convection, and radiation dynamics. By examining various numerical cases, the study reveals a substantial 45% performance improvement in porous designs compared to solid actuators. The investigation extends to simultaneous optimization of multiscale porous displacement actuators, achieving a remarkable 75% weight reduction and demonstrating significant performance enhancements over single-scale designs. The increased freedom in micro-scale design allows more efficient material distribution, optimizing both macro and overall layouts. Sequential optimization of macro and micro-scale actuators is contrasted with concurrent multiscale optimization, showing inferior performance for separate optimizations. The study also delves into topology optimization under energy dissipation, focusing on multiple-rate thermal convection and revealing adaptive design behaviors in response to thermal stresses. Macro-scale designs influenced by convection exhibit perpendicular links and adaptive microstructures to enhance resilience and elasticity. The investigation also includes thermal radiation and convection, highlighting intricate design considerations for effective thermal dissipation. Ultimately, this study advances the understanding of multiscale effects in topology optimization, paving the way for more efficient and lightweight laser-activated porous actuators.
Improved global estimation of seasonal variations in C3 photosynthetic capacity based on eco-evolutionary optimality hypotheses and remote sensing
Authors: Liu Yihong , Chen Jing M. , Xu Mingzhu , Wang Rong , Fan Weiliang , Li Wenyu , Kammer Lucas , Prentice Colin , Keenan Trevor F. , Smith Nicholas G. 
Published: June 2024

Abstract

The maximum carboxylation rate of plant leaves (Vcmax) at 25°C (Vcmax25) is a fundamental parameter in terrestrial biosphere models (TBMs) to estimate carbon assimilation of C3 biomes. It has been reported that ignoring the seasonal variations inVcmax25induces considerable uncertainties in TBMs. Recently, a model was developed to estimateVcmax25of C3 biomes mechanistically from climate data based on eco-evolutionary optimality hypotheses, which hypothesized that plants acclimate to the environment to achieve maximum carbon assimilation with minimum related costs. However, uncertainties of this optimality-based model (EEO model) have been found to correlate to leaf nitrogen content, partly due to the lack of parameterization on how the acclimation ofVcmax25is constrained by photosynthetic nitrogen other than that in RuBisCO. This constraint could be parametrized by remote sensing methods globally. In this study, we developed remote sensing methods to estimate leaf absorptance of radiation based on MODIS LCC (leaf chlorophyll content) data and the ratio of the maximum electron transport rate of plant leaves (Jmax) toVcmaxat 25°C (rJV25) based on TROPOMI SIF (solar-induced chlorophyll fluorescence) data (RS-rJV25). These two parameters contain photosynthetic nitrogen information related to light harvesting, electron transport, and carboxylation, and they were then incorporated into the EEO model to constrain howVcmax25acclimates to the environment. The simulatedVcmax25constrained by MODIS LCC and RS-rJV25agreed well with seasonal variations in field-measuredVcmax25at 18 sites (R2 = 0.76, RMSE = 13.40 µmol·m− 2·s− 1), showing better accuracy than the simulation without incorporating leaf absorptance andrJV25(R2 = 0.63, RMSE = 31.59 µmol·m− 2·s− 1). Our results indicated that variations in leaf absorptance andrJV25constrained the acclimation ofVcmax25to the environment and contributed to the variation inVcmax25that cannot be fully captured by environmental factors alone in the EEO model. The remote-sensing-based leaf absorptance andrJV25captured the sensitivity of these two parameters to environmental conditions on the global scale. The influence of leaf absorptance onVcmax25was primarily affected by the irradiance level, whilerJV25was determined by the growing season mean temperature. The simulatedVcmax25had large spatiotemporal variations on the global scale, and the environment drove the variation pattern more greatly than the biome distribution. With reasonably accurate seasonal variations inVcmax25, this study can help improve the global carbon cycle and leaf trait modelling.
Discovery of an EP300 Inhibitor using Structure-based Virtual Screening and
Bioactivity Evaluation
Authors: Pan Dabo , Huang Yaxuan , Jiang Dewen , Zhang Yonghao , Wu Mingkai , Han Minzhen , Jin Xiaojie 
Published: June 2024

Background:
EP300 (E1A binding protein p300) played a significant role in serial diseases such as
cancer, neurodegenerative disease. Therefore, it became a significant target.

Methods:
Targeting EP300 discovery of a novel drug to alleviate these diseases. In this paper, 17 candidate
compounds were obtained using a structure-based virtual screening approach, 4449-0460, with an IC50 of 5.89
± 2.08 uM, which was identified by the EP300 bioactivity test. 4449-0460 consisted of three rings. The middle
benzene ring connected the 5-ethylideneimidazolidine-2,4-dione group and the 3-F-Phenylmethoxy group.

Results:
Furthermore, the interaction mechanism between 4449-0460 and EP300 was explored by combining
molecular dynamics (MD) simulations and binding free energy calculation methods.

Conclusion:
The binding free energy of EP300 with 4449-0460 was -10.93 kcal/mol, and mainly came from
the nonpolar energy term (ΔGnonpolar). Pro1074, Phe1075, Val1079, Leu1084, and Val1138 were the key residues
in EP300/4449-0460 binding with more -1 kcal/mol energy contribution. 4449-0460 was a promising inhibitor
targeting EP300, which had implications for the development of drugs for EP300-related diseases.