bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deciphering the Role of the Ser‐Phosphorylation Pattern on the DNA‐Binding Activity of Max Transcription Factor Using Chemical Protein Synthesis
Authors: Nithun Raj V. , Yao Yumi Minyi , Lin Xiaoxi , Habiballah Shaimaa , Afek Ariel , Jbara Muhammad 
Published: August 2023

AbstractThe chemical synthesis of site‐specifically modified transcription factors (TFs) is a powerful method to investigate how post‐translational modifications (PTMs) influence TF‐DNA interactions and impact gene expression. Among these TFs, Max plays a pivotal role in controlling the expression of 15 % of the genome. The activity of Max is regulated by PTMs; Ser‐phosphorylation at the N‐terminus is considered one of the key regulatory mechanisms. In this study, we developed a practical synthetic strategy to prepare homogeneous full‐length Max for the first time, to explore the impact of Max phosphorylation. We prepared a focused library of eight Max variants, with distinct modification patterns, including mono‐phosphorylated, and doubly phosphorylated analogues at Ser2/Ser11 as well as fluorescently labeled variants through native chemical ligation. Through comprehensive DNA binding analyses, we discovered that the phosphorylation position plays a crucial role in the DNA‐binding activity of Max. Furthermore, in vitro high‐throughput analysis using DNA microarrays revealed that the N‐terminus phosphorylation pattern does not interfere with the DNA sequence specificity of Max. Our work provides insights into the regulatory role of Max′s phosphorylation on the DNA interactions and sequence specificity, shedding light on how PTMs influence TF function.
Adaptive visual servoing for the robot manipulator with extreme learning machine and reinforcement learning
Authors: Li Jiashuai , Peng Xiuyan , Li Bing , Sreeram Victor , Wu Jiawei , Mi Wansheng 
Published: August 2023

AbstractIn this study, a novel image‐based visual servo (IBVS) controller for robot manipulators is investigated using an optimized extreme learning machine (ELM) algorithm and an offline reinforcement learning (RL) algorithm. First of all, the classical IBVS method and its difficulties in accurately estimating the image interaction matrix and avoiding the singularity of pseudo‐inverse are introduced. Subsequently, an IBVS method based on ELM and RL is proposed to solve the problem of the singularity of the pseudo‐inverse solution and tune adaptive servo gain, improving the servo efficiency and stability. Specifically, the ELM algorithm optimized by particle swarm optimization (PSO) was used to approximate the pseudo‐inverse of the image interaction matrix to reduce the influence of camera calibration errors. Then, the RL algorithm was adopted to tune the adaptive visual servo gain in continuous space and improve the convergence speed. Finally, comparative simulation experiments on a 6‐DOF robot manipulator were conducted to verify the effectiveness of the proposed IBVS controller.
Fault estimation and active fault‐tolerant control for a class of nonlinear systems with actuator and sensor faults based on unknown input iterative learning
Authors: Wu Fan , Liu Yaqi , Fang Yiming , Liu Le , Lei Zhichao 
Published: August 2023

AbstractIn this paper, fault estimation and active fault‐tolerant control are studied for a class of nonlinear systems with simultaneous actuator and sensor faults, as well as unknown external disturbances. Firstly, the state equation of a class of nonlinear systems is transformed into an augmented system state equation by extending the sensor fault as an auxiliary state. Then, a novel fault estimation observer based on iterative learning with unknown inputs is designed to estimate the system state, as well as actuator and sensor faults. Subsequently, by using the fault estimation information, a dynamic output feedback active fault‐tolerant control scheme is proposed to compensate for the influence of faults on the system. Lyapunov stability theory is used to prove the stability of the closed‐loop system and the convergence of the fault estimation observer. The gain matrices of the fault estimation observer and fault‐tolerant controller are obtained by solving linear matrix inequalities. Furthermore, the paper avoids the use of the
norm in the convergence proof of the conventional iterative learning algorithm, which reduces the amount of calculation in the derivation process. Finally, the effectiveness and accuracy of the proposed method are verified through simulation of the DC motor angular velocity system.
Hidden Markov model‐based asynchronous exponential stabilization for stochastic Markovian jump systems with incomplete controller mode information
Authors: Lu Dunke , Li Xiaohang , Tian Zhaoyang 
Published: August 2023

AbstractIn this paper, the exponential stability of a kind of It
Markovian jump system is studied. Specifically, the exponential stability is ensured by designing an asynchronous delayed‐feedback controller, whose modes are inconsistent with those of the original system. We have built the necessary new relationship between controller modes and system modes, which can facilitate the stability analysis and also make the famous existing ones special cases of the proposed one. Moreover, practically ubiquitous controller delays, which occur between the sensors and controllers, to the detriment of the system stability, are taken into account, and their maximum values are provided in a theoretic way. In this way, the exponential stability can be well ensured against controller delays. With an eye to practical applications, the transition rates of the considered system and the designed asynchronous controller are assumed to be uncertain, and they can be well dealt with by using a new approach with lower conservatism. Furthermore, a practical example and some comparative examples are given to demonstrate the effectiveness and superiorities of the obtained conclusion.
Variable selection in linear regression models: Choosing the best subset is not always the best choice
Authors: Hanke Moritz , Dijkstra Louis , Foraita Ronja , Didelez Vanessa 
Published: August 2023

AbstractWe consider the question of variable selection in linear regressions, in the sense of identifying thecorrect directpredictors (those variables that have nonzero coefficientsgiven allcandidate predictors). Best subset selection (BSS) is often considered the “gold standard,” with its use being restricted only by its NP‐hard nature. Alternatives such as the least absolute shrinkage and selection operator (Lasso) or the Elastic net (Enet) have become methods of choice in high‐dimensional settings. A recent proposal represents BSS as a mixed‐integer optimization problem so that large problems have become computationally feasible. We present an extensive neutral comparison assessing the ability to select the correct direct predictors of BSS compared to forward stepwise selection (FSS), Lasso, and Enet. The simulation considers a range of settings that are challenging regarding dimensionality (number of observations and variables), signal‐to‐noise ratios, and correlations between predictors. As fair measure of performance, we primarily used the best possible F1‐score for each method, and results were confirmed by alternative performance measures and practical criteria for choosing the tuning parameters and subset sizes. Surprisingly, it was only in settings where the signal‐to‐noise ratio was high and the variables were uncorrelated that BSS reliably outperformed the other methods, even in low‐dimensional settings. Furthermore, FSS performed almost identically to BSS. Our results shed new light on the usual presumption of BSS being, in principle, the best choice for selecting the correct direct predictors. Especially for correlated variables, alternatives like Enet are faster and appear to perform better in practical settings.
Mastering the interplay of organizational resilience and sustainability: Insights from a hybrid literature review
Authors: Ciasullo Maria Vincenza , Chiarini Andrea , Palumbo Rocco 
Published: August 2023

AbstractOrganizational resilience enables the firm to thrive in an increasingly turbulent environment, paving the way for sustainability. Although the implications of organizational resilience on sustainability have been widely discussed in the literature, scholarly knowledge examining the interplay between these two phenomena is fragmented. The article addresses this gap through a hybrid domain‐based literature review falling at the intersection of organizational resilience and sustainability. Drawing on a knowledge core of 51 scientific contributions, we identified four research streams established on five conceptual foundations. The study findings guide us toward an eco‐social interpretation of organizational resilience, whose implications on the firm's viability should be assessed by acknowledging spillovers on environmental sustainability. Management actions to build organizational resilience should follow an ecosystem sustainability orientation. This involves embedding the firm in the eco‐social setting in which it operates, emphasizing its homeostatic exchanges with the environment.
Assessment of bacterial and viral gut communities in healthy and tumoral colorectal tissue usingRNAandDNAdeep sequencing
Authors: Garcia‐Serrano Ainhoa , Mukhedkar Dhananjay , Hultin Emilie , Rudsander Ulla , Wettergren Yvonne , Ure Agustín Enrique , Dillner Joakim , Arroyo‐Mühr Laila Sara 
Published: August 2023

AbstractBackgroundColorectal cancer (CRC) is known to present a distinct microbiome profile compared to healthy mucosa. Non‐targeted deep‐sequencing strategies enable nowadays full microbiome characterization up to species level.AimWe aimed to analyze both bacterial and viral communities in CRC using these strategies.Materials & MethodsWe analyzed bacterial and viral communities using both DNA and RNA deep‐sequencing (Novaseq) in colorectal tissue specimens from 10 CRC patients and 10 matched control patients. Following taxonomy classification using Kraken 2, different metrics for alpha and beta diversities as well as relative and differential abundance were calculated to compare tumoral and healthy samples.ResultsNo viral differences were identified between tissue types, but bacterial speciesPolynucleobacter necessariushad a highly increased presence for DNA in tumors (p = 0.001). RNA analyses showed that bacterial speciesArabia massiliensishad a highly decreased transcription in tumors (p = 0.002) whileFusobacterium nucleatumtranscription was highly increased in tumors (p = 0.002).DiscussionSequencing of both DNA and RNA enables a wider perspective of micriobiome profiles. Lack of RNA transcription (Polynucleobacter necessarius) casts doubt on possible role of a microorganism in CRC. The association of F. nucleatum mainly with transcription, may provide further insights on its role in CRC.ConclusionJoint assessment of the metagenome (DNA) and the metatranscriptome (RNA) at the species level provided a huge coverage for both bacteria and virus and identifies differential specific bacterial species as tumor associated.
Trends in breast cancer screening during the COVID‐19 pandemic within a universally insured health system in the United States, 2017–2022
Authors: Mani Vivitha , Banaag Amanda , Munigala Satish , Umoh Ada , Schoenfeld Andrew J. , Coles Christian L. , Koehlmoos Tracey Perez 
Published: August 2023

AbstractBackgroundIn the United States, breast cancer is the most commonly diagnosed cancer and second leading cause of cancer death in women. Early detection through mammogram screening is instrumental in reducing mortality and incidence of disease. The COVID‐19 pandemic posed unprecedented challenges to the provision of care, including delays in preventive screenings. We examined trends in breast cancer screening during the COVID‐19 pandemic in a universally insured national population and evaluated rates across racial groups and socioeconomic strata.MethodsIn this retrospective open cohort study, we used the Military Health System Data Repository to identify female TRICARE beneficiaries ages 40–64 at average risk for breast cancer between FY2018 and FY2022, broken down into prepandemic (September 1, 2018–February 28, 2020), early pandemic (March 1, 2020–September 30, 2020), and late pandemic periods (October 1, 2020–September 30, 2022). The primary outcome was receipt of breast cancer screening.ResultsScreening dropped 74% in the early pandemic period and 22% in the late pandemic period, compared with the prepandemic period. Compared with White women, Asian/Pacific Islander women were less likely to receive mammograms during the late pandemic period (0.92RR; 0.90–0.93 95%CI). American Indian/Alaska Native women remained less likely to receive screenings compared with White women during the early (0.87RR; 0.80–0.94 95% CI) and late pandemic (0.94RR, 0.91–0.98 95% CI). Black women had a higher likelihood of screenings during both the early pandemic (1.10RR; 1.08–1.12 95% CI) and late pandemic (1.12RR, 1.11–1.13 95% CI) periods compared with White women. During the early and late pandemic periods, disparities by rank persisted from prepandemic levels, with a decrease in likelihood of screenings across all sponsor ranks.ConclusionOur results indicate the influence of race and socioeconomics on mammography screening during COVID‐19. Targeted outreach and further evaluation of factors underpinning lower utilization in these populations are necessary to improve access to preventative services across the population.
Anatomical, Morphological, and Chemical Characterizations and Biological Activities of Gagea taurica Steven (Liliaceae): A New Record for the Turkish Flora
Authors: Yuca Hafize , Karakaya Songul , Ekşi Gülnur , Aydin Bilge , Goger Gamze , Bona Mehmet , Tekman Enes , Şahin Aydan Acar , Sytar Oksana , Pinar Nur Münevver , Guvenalp Zuhal 
Published: August 2023

AbstractGagea genus, which is native to the Mediterranean and Black Sea regions, has attracted significant attention due to its biodiversity and potential health benefits. In this study, the biochemical composition and biological activities of methanol extracts from various parts of G. taurica were investigated, along with their anatomical and morphological characteristics. The best antimicrobial activity was found to be MeOH extracts of corm and leaf against several Candida strains with MIC=640 μg/mL. The highest level of phenolics together with significant results of antioxidant activities were observed in flowers extracts. The α‐amylase inhibition assay results showed that the highest inhibition percentage was observed with acarbose (59 %), followed by leaf extract (43 %). Leaf exhibited the most effective inhibitory activity in AChE inhibition assay, whereas flower demonstrated the most significant inhibitory activity in BChE inhibition assay. Hesperidin was found as 1621.0001 ng/ml value in flower extract and 283.9339 ng/ml value leaf.
Recent Developments in Biobased Foams and Foam Composites for Construction Applications
Authors: DSouza Glen Cletus , Ng Harrison , Charpentier Paul , Xu Chunbao Charles 
Published: August 2023

AbstractA surge of research into renewable foams has yielded an array of high‐performance polymeric materials, many of which exhibit promising properties for next generation thermal insulating materials. Biobased materials are of particular interest, due to growing concerns towards enhancing the circular economy while reducing fossil fuel dependency in the construction industry. This review outlines recent developments in biobased foams based on biobased polyurethanes (BPU), biobased phenol formaldehyde (BPF) and cellulose nanofibers (CNF) foams. These three areas of polymers are of particular interest due to their early stage of market adoption, yet significant industrial potential. As our focus is on construction materials, we will review their thermal, mechanical, and fire‐retardant performance, their synthesis/fabrication methods and future prospects. Improving the scalability, reproducibility and cost‐effectiveness of their production is vital for successful commercialization adoption.
Exploring the relationship between personality and money scripts while controlling for demography, ideology, and self‐esteem
Authors: Furnham Adrian , Cuppello Stephen 
Published: August 2023

AbstractFinancial planners seek to learn more about their clients' personalities and money scripts due to the significant influence these factors have on financial behavior and decision‐making. This study surveyed 288 adults with a personality assessment (HPTI: High Potential Trait Indicator), and their money scripts (KMSI‐R: Klontz Money Script Inventory) while controlling for demography (sex, age, and education), ideology (religious, political beliefs, and optimism), and self‐esteem (measurements of personal ratings on a variety of scales). The results indicated that each of the six traits measured by the HPTI (Conscientiousness, Adjustment, Curiosity, Risk Approach, Ambiguity Acceptance, and Competitiveness) related to the four money scripts measured by the KMSI‐R (avoidant, worship, status, and vigilance). More Adjustable individuals were less likely to have Money Avoidance scripts, whereas more Competitive people had higher Money Worship and Money Status scripts. The study underlined the role of personality variables in understanding money beliefs.
Herringbone Helical Foldamers from Aromatic Ether Derived ϵ‐Amino Acid Peptides
Authors: Yang Yong , Xue Min 
Published: August 2023

AbstractOligomers based on an aromatic ether derived ϵ‐amino acid peptides folded into herringbone helical structures, induced by successive NH−O−NH & O−NH−O bifurcated hydrogen bonding interactions and reinforced by π‐π stacking between aryls from adjacent layers. The diaryl ether bonds −O− worked both as structural units to provide turn motifs for changing the amplitude of the slope along the axis of helix for herringbone formation, and also as acceptors for hydrogen bonding. Attachment of a single chiral carbon to the C‐termini of the peptides induced excess of single‐handed screw sense and amplification through the chain propagation as exemplified by chain length dependent circular dichroism (CD) investigations.
Effects of salt content on secondary formation of hydrates in complex systems
Authors: Jiang Xiangchun , Wang Xiao , Ma Guiyang , Liang Zhuo , Jiang Yeqiang , Yu Lufei 
Published: August 2023

AbstractThe phenomenon of ‘memory effect’ exists in the secondary generation of natural gas hydrates, which is mainly manifested in the fact that the induction time required for the nucleation of hydrates in the secondary generation of hydrates is significantly shorter than that of the primary generation, thus accelerating the generation of hydrates. At present, the research on the memory effect phenomenon has been proven to exist, and its influencing factors have become a research hotspot. In order to study the influence of decomposition time and salt content on the memory effect, the hydrate was generated under the system of porous medium alumina complexed with surfactant SDS, and hydrate secondary generation experiments were carried out by adding different contents of NaCl according to four different decomposition times. The influence of four different decomposition times on the memory effect phenomenon in the secondary generation of hydrates and the influence of different salt contents on the memory effect phenomenon were analyzed by observing the pressure drop changes in the reactor during the hydrate generation process and calculating the methane gas consumption. The experimental results show that different decomposition times can affect the effect and time of the memory effect, and the effect of decomposition time on the memory effect does not show a linear relationship. The addition of salt may have an inhibitory effect on the memory effect.
Identifying the causal relationship between sedentary behavior and heart failure: Insights from a Mendelian randomization study and mediation analysis
Authors: Zheng Xifeng , Liu Manqi , Wu Zijun , Jia Zhen 
Published: August 2023

AbstractBackgroundObservational studies have revealed that a lack of physical exercise may be linked to a higher risk of heart failure (HF). Here, the causal relationship between sedentary behavior (SB) and HF was investigated using Mendelian randomization (MR).HypothesisSB was considered as an important risk factor of HF.MethodsSingle nucleotide polymorphisms with a genome‐wide statistical significance threshold of <5 × 10−8 among the SB‐proxied phenotypes (TV screen time, computer use, and driving) from genome‐wide association study (GWAS) datasets were identified as instrumental variables (IVs). The MR study was performed using the inverse‐variance weighting (IVW) model as a primary standard to evaluate causal relationships. Simultaneously, MR‐Egger regression, weighted median, and maximum likelihood models were used as supplements. Sensitivity analysis, consisting of a heterogeneity and horizontal pleiotropy test, was performed using Cochran's Q, MR‐Egger intercept, and MR‐PRESSO tests to ensure the reliability of conclusions.ResultsThe IVW model results showed that increased TV screen time correlated with a higher genetic susceptibility for HF in both HF‐associated GWAS datasets, which was also supported by weighted median and maximum likelihood model results. The odds ratios with 95% confidence intervals were 1.418 (1.182–1.700) and 1.486 (1.136–1.943), respectively. Although the results of Cochran's Q test indicated certain heterogeneity among the IVs. The MR‐Egger intercept and MR‐PRESSO tests suggested no horizontal pleiotropy and verified the reliability of the conclusion.ConclusionsThis MR study identified that increased TV screen time may predispose individuals to the development of HF.
Autonomous eDNA collection using an uncrewed surface vessel over a 4200‐km transect of the eastern Pacific Ocean
Authors: Preston Christina , Yamahara Kevan , Pargett Douglas , Weinstock Chloe , Birch James , Roman Brent , Jensen Scott , Connon Brian , Jenkins Richard , Ryan John , Scholin Christopher 
Published: August 2023

AbstractThe collection of environmental DNA (eDNA) samples is often laborious, costly, and logistically difficult to accomplish at high frequency in remote locations and over large geographic areas. Here, we addressed those challenges by combining two robotic technologies: an uncrewed surface vessel (USV) fitted with an automated eDNA sample collection device to survey surface waters in the eastern North Pacific Ocean from Alameda, CA to Honolulu, HI. USV Surveyor SD 1200 (Saildrone) carrying the Environmental Sample Processor (ESP) collected 2‐L water samples by filtration followed by RNAlater preservation at regular intervals over a 4200‐km, 29‐day transit. Sixty samples (52 field and 8 controls) were acquired and used to estimate the concentration of specific genes and assess eukaryotic diversity via targeted qPCR and metabarcoding of the cytochrome oxidase subunit I (COI) gene, respectively. Comparisons of control samples revealed important considerations for interpreting results. Samples stored at ambient temperatures onboard Surveyor over the length of the voyage had less total recoverable DNA and specific target gene concentrations compared to the same material immediately flash‐frozen after collection and stored in a laboratory. In contrast, the biodiversity of the COI genes in those samples was similar regardless of sample age and storage condition. COI genes affiliated with 40 eukaryotic phyla were found in native samples collected during the voyage. The distribution and dominance of those phyla varied across different regions, with some taxa spanning large continuous stretches >2000 km, while others were only detected in a single sample. This work highlights the utility and potential of using USVs fitted with autonomous eDNA sample collection devices to improve ocean exploration and support large, basin‐scale, systematic biodiversity surveys. Results of this study also inform future technical considerations for using automated eDNA samplers to acquire material and store it over prolonged periods under prevailing environmental conditions.