bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unveiling errors in soil microbial community sequencing: a case for reference soils and improved diagnostics for nanopore sequencing
Authors: Manter Daniel K. , Reardon Catherine L. , Ashworth Amanda J. , Ibekwe Abasiofiok M. , Lehman R. Michael , Maul Jude E. , Miller Daniel N. , Creed Timothy , Ewing Patrick M. , Park Stanley , Ducey Thomas F. , Tyler Heather L. , Veum Kristen S. , Weyers Sharon L. , Knaebel David B. 
Published: July 2024

AbstractThe sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.
A decade of translational engineering biology: Measuring success
Authors: Bell David 
Published: August 2024

AbstractSince joining SynbiCITE, the national centre for translating synthetic biology, a decade ago as the lone analytical chemist, the centre has gone from limited lab space to playing its part in securing funding, growth and development of more than 50 companies focused on engineering biology. Synthetic biology has proved to be viable technology, with the number of sustainable companies continuing to grow in this field. This communication provides a personal perspective of 10 years in translational engineering of biology, as seen from the experimental analytics position and working with the companies contributing to the growth of the UK bioeconomy.
A load classification method based on data augmentation and few‐shot machine learning
Authors: Liu Haoran , Li Huaqiang , Yu Xueying , Wang Ziyao , Chen Yipeng 
Published: August 2024

AbstractThe volatility of renewable energy generation impacts the safe and stable operation of power systems. Moreover, load uncertainty complicates renewable energy consumption. Therefore, accurately extracting load patterns using artificial intelligence (AI) technology is crucial. Load classification is an effective way to master load behaviour. However, issues in the collected load data, such as data class imbalance, significantly affect the accuracy of traditional load classification. To address this problem, this study proposes a novel classification method based on data augmentation and few‐shot learning, significantly enhancing the training efficiency of algorithm recognition. This addresses the challenge of real‐data recognition in power systems. First, time‐series load data are converted into images based on the Gramian angular field method to extract time‐series data features using a convolutional neural network. Subsequently, the data are augmented based on variational autoencoder generative adversarial network to generate samples with distributions similar to those of the original data. Finally, the augmented few‐shot data are classified using the embedding and relation modules of the relation network. A comparison of the experimental results reveals that the proposed method effectively improves power load classification accuracy, even with insufficient data.
LINC00963 Represses Osteogenic Differentiation of hBMSCs via the
miR-10b-5p/RAP2A/AKT Axis
Authors: Wu Zhixin , Shi Mingjuan , Zhao Xuan , Wu Guifu , Zheng Huiyuan , Cui Yuanyuan , Shang Yu 
Published: July 2024

AbstractOsteogenic differentiation of human bone marrow-derived mesenchymal stem cells
(hBMSCs) is important for human bone formation. Long non-coding RNAs (lncRNAs)
are critical regulators in osteogenic differentiation. This study aimed to
explore the function and mechanisms of long intergenic non-protein coding RNA
963 (LINC00963) in affecting osteogenesis. Cell differentiation was assessed by
alkaline phosphatase (ALP) activity detection and ALP staining assay. Meanwhile,
levels of osteogenic marker genes, including RUNX family transcription factor 2
(RUNX2), osteocalcin (OCN), and osteopontin (OPN), were detected by RT-qPCR and
western blot. Cell proliferation and apoptosis were measured using CCK-8 assay
and flow cytometry analysis. RNA immunoprecipitation (RIP), RNA pull-down and
luciferase reporter assays were used to investigate the interaction between
genes. LINC00963 expression was down-regulated in hBMSCs treated with osteogenic
induction. LINC00963 overexpression inhibited hBMSCs differentiation,
proliferation, and elevated apoptosis. LINC00963 acted as a competing endogenous
RNA (ceRNA) to interact with miR-10b-5p and thereby regulated the expression
level of Ras-related protein Rap-2a (RAP2A). LINC00963 regulated RAP2A to
inhibit the level of phosphorylated AKT (p-AKT). LINC00963 inhibited hBMSCs
differentiation, proliferation, and elevated apoptosis via the
miR-10b-5p/RAP2A/AKT signaling, which might help improve the treatment of
osteoporosis.
Optimal Minimum-Velocity Threshold to Predict One-repetition Maximum
for the Back Squat
Authors: Fitas Afonso , Gomes Miguel , Santos Paulo , Gonçalves André D , Pezarat-Correia Pedro , Mendonca Goncalo V 
Published: July 2024

AbstractThe prediction of one-repetition maximum (1RM) is highly relevant for strength
and conditioning. The optimal minimum-velocity threshold (MVT) was recently
proposed to increase the accuracy of 1RM predictions. Individual load-velocity
profiles (LVP) were obtained in 18 athletes enrolled in recreational soccer.
Reliability analyses were computed for all LVP-derived variables. Estimations of
1RM were made based on general (0.3 m.s− 1), pre-individual (mean
velocity at 1RM obtained in a preliminary session) and optimal MVT (velocity
that eliminates the difference between actual and predicted 1RM, determined in a
preliminary session). The accuracy of 1RM predictions was examined using
absolute-percent error and Bland-Altman plots. Between-day reliability of the
LVP and 1RM was good (intraclass-correlation coefficients – ICCs>0.9 and
coefficients of variation – CVs<5%). The individual and optimal MVT reached
moderate-to-good reliability (ICCs>0.9 and CVs<10%, respectively). The
predictions based on the optimal MVT displayed greater accuracy than those
obtained with the individual and general MVT (absolute percent error: 2.8 vs.
5.5 vs. 4.9%, respectively). However, wide limits of agreement (LoA) were found
between actual and estimated 1RM using this approach (~15 kg). Data indicate
that the optimal MVT provides better estimations of 1RM for the free-weight back
squat than the general and the individual MVT.
Acute Inflammatory Response to Eccentric Exercise in Young and Master
Resistance-trained Athletes
Authors: Minuzzi Luciele Guerra , Ferrauti Alexander , Chupel Matheus Uba , Hacker Sebastian , Weyh Christopher , Valenzuela Pedro L. , Lucia Alejandro , Krüger Karsten , Reichel Thomas 
Published: July 2024

AbstractThis study aimed to compare the acute inflammatory response following
high-intensity eccentric exercise between resistance-trained young and master
athletes with similar performance levels. Resistance-trained young (n=8; 22±2
years) and master (n=8; 52±4 years) male athletes of a similar performance level
performed a standardized high-intensity eccentric squat exercise protocol (10
sets of half-squats at 70% of 1-repetition maximum). The serum concentration of
20 biomarkers related to tissue damage, inflammation, remodeling, and repair was
measured at baseline, immediately after exercise, and over a 72 h recovery
period. Both groups experienced similar muscle damage as evidenced by a
comparable increase in creatine kinase activity 24 h after exercise
(p<0.001). Interleukin-6 (p=0.009) and growth hormone (p<0.001) increased
immediately post-exercise in both groups. Monocyte chemoattractant protein-1
increased immediately post-exercise only in young athletes (p=0.003) and then
decreased 24 h later. There were no significant differences for the remaining
variables, including cell markers related to neutrophil/macrophage activation or
pro/anti-inflammatory cytokines. Resistance-trained young and master athletes,
matched for performance level, showed an overall similar inflammatory response
to eccentric exercise, possibly reflecting regulatory mechanisms or
immunological adaptations to chronic stimulation in master athletes.
Modeling price-sensitive demand in turbulent times: an application to continuous pricing
Authors: Meyer Felix , Kauermann Göran , Alder Christopher , Cleophas Catherine 
Published: July 2024

AbstractPricing drives demand for service industries such as air transport, hotels, and car rentals. To optimise the price, firms have to predict real-time customer demand at the micro level and optimise the price. This paper contributes to revenue management by introducing a nonparametric statistical approach to predict price-sensitive demand and its application to continuous pricing. Continuous pricing lets service companies maximise revenue by using customers’ willingness to pay. However, it requires accurate demand estimations, particularly of customers’ price sensitivity. This paper introduces an augmented generalised additive model to estimate price sensitivity, which identifies substantial variations in price sensitivity, exceeds the predictive performance of state-of-the-art alternatives, and controls for price endogeneity. In addition, the demand model has variable price derivatives enabling continuous pricing. The proposed approach offers a simple and efficient way to implement continuous pricing with a closed-form solution. Our research also highlights the relevance of considering the problem of price endogeneity when estimating price-sensitive demand based on observations from prior pricing decisions. We demonstrate how continuous pricing is applied using empirical airline ticket data. We document a field study, which shows a revenue increase of 6% on average, and outline how the approach applies to turbulent market conditions caused by the COVID-19 pandemic, the surge in inflation since mid-2021, and the start of the Ukraine war in April 2022.
Ladybug-inspired hierarchical composite adhesives for enhanced surface adaptability
Authors: Wang Tao , Gu Ping , Gao Tianyan , Li Haoyu , Meng Ting , Zhang Peng , Zhao Yang 
Published: July 2024

Abstract
Enhanced adhesion on rough surfaces is highly desired for a wide range of applications. On the other hand, surface roughness compatibility and structure stability are two critical but competing factors for biologically-inspired dry adhesives in the real world. Inspired by ladybug, a hierarchical structural composite dry adhesive (denoted as PP-M) with enhanced robustness on surface roughness is developed, which is composed of a thin compliant contact layer (a thin soft polydimethylsiloxane (PDMS) film supported discretely by PDMS micropillars) and a rigid bottom layer magnetorheological elastomers (MREs). The PP-M shows a high pull-off strength of 8.2 N cm−2 on a smooth surface and nano-scale rough surface at a mild preload (2 N cm−2). For micro-scale rough surfaces, the PP-M exhibits better surface adaptability compared to the double-layered adhesive (PDMS on MRE) without micropillar support. The increased compliance of the contact layer also leads to a 2.11 fold superior pull-off strength at a wider range of roughness (Sq > 2.23 μm). Element analysis confirms PP-M’s enhanced adaptability, attributed to deeper indentation and lower contact stress. This hierarchical composite structure in PP-M, characterized by a ‘soft on top and hard on bottom’ stiffness distribution, synergizes the flexible contact layer with the stiff MRE bottom layer, leading to superior adhesive properties. The results provide a new reference for achieving enhanced adhesion on rough surfaces.
A piezoelectric-electromagnetic hybrid energy harvester for rotational motion driven by magnetic repulsion
Authors: Wang Chensheng , Lv Xingqian , Liu Zhenxin , Li Xiaotao , Yang Bowen , He Lipeng 
Published: July 2024

Abstract
Harvesting energy from rotational motion is an efficient and widely used technology that provides power support for various electronic devices and systems by converting mechanical kinetic energy into electrical energy. This energy harvesting method shows great potential and advantages in industrial automation, transportation, wind power generation, and smart homes. This study proposes a piezoelectric-electromagnetic hybrid energy harvester (HEH) for rotational motion driven by magnetic repulsion. HEH comprises of two parts: a piezoelectric energy harvester (PEH) and an electromagnetic energy harvester (EMH). HEH utilizes the magnetic drive reciprocating motion to enhance the energy collection efficiency of PEH and EMH. Additionally, by adding the magnetic effect to the ends of bimorph piezoelectric sheets, the spectrum of energy harvesting is expanded. Its parameters are analyzed using theoretical analysis and simulation, and an experimental testbed is established to explore the influence of HEH output performance. The results indicate that the output power reaches its maximum when there are 2 circular magnets on the rotor, the gap distance of magnets is 15 mm, and 2 mass blocks at the end of the bimorph piezoelectric sheet. The PEH and EMH outputs are 173.36 V and 4.81 V, respectively. The maximum output power of HEH is 53.45 mW. The power density can reach 6.818 mW cm−3. Compared with PEH and EMH, the output performance is improved by 46.94% and 174.95%, respectively. When the rotation speed is 500 r min−1, HEH can effortlessly light up 80 LEDs. The experimental results all demonstrate the potential of HEH to power low-power sensors.
The Politics of Social Protection in Latin America
Authors: Barrientos Armando 
Published: August 2024

Abstract
Inequality is the salient feature of social protection in Latin America. Existing social protection institutions neatly segment the population in Latin American countries. Occupational insurance funds and/or individual retirement savings plans are accessible to skilled workers in large firms and the public sector. Social assistance targets less skilled workers and their families. How and why have countries in Latin America constructed dual social protection institutions? What political conditions explain this stratification? This chapter argues that an understanding of the politics of stratified social protection emerges from connecting these institutions to political realignments that impact on the political incorporation of wage earners.
Conclusion
Authors: Pellissery Sony 
Published: August 2024

Abstract
Over the past 70 years, both the state and industrialized capitalism have undergone significant changes. The singular idea that citizenship is associated with the boundaries of a nation-state has undergone transformation, and claims for new modalities of citizenship have become more vocal. These developments have facilitated novel ways of thinking about the interface between social policy in the Global North and South. The developmental approaches taken by states to address the postwar or postcolonial situations in the Global South emphasized economic transformation. By the 1980s, although this developmental approach coupled with market penetration reduced absolute poverty measurably, inequality rose significantly. This new unintended consequence has invited resistance from the bottom of the pyramid. Politics of welfare is primarily in the form of its ideations. These ideations further influence actors, institutions, and resource allocation. In this chapter, a distinction is made between welfare ideations for the South and from the South through a periodization approach. Since decolonization, the development approach, as given to the Global South, has been the road for welfare. This chapter identifies a set of propositions for welfare as demanded by social movements from the Global South.
VQCNN: variational quantum convolutional neural networks based on quantum filters and fully connected layers
Authors: Qi Han , Wang Jingtong , Cui Yufan 
Published: July 2024

Abstract
Classical machine learning is more susceptible to adversarial examples due to its linear and non-robust nature, which results in a severe degradation of the recognition accuracy of classical machine learning models. Quantum techniques are shown to have a higher robustness advantage and are more resistant to attacks from adversarial examples than classical machine learning. Inspired by the robustness advantage of quantum computing and the feature extraction advantage of convolutional neural networks, this paper proposes a novel variational quantum convolutional neural network model (VQCNN), whose quantum fully connected layer consists of a combination of a quantum filter and a variational quantum neural network to increase the model’s adversarial robustness. The network intrusion detection model based on VQCNN is verified on KDD CUP99 and UNSW-NB datasets. The results show that under the attack of Fast Gradient Sign Method, the decline values of accuracy, precision, and recall rate of the intrusion detection model based on VQCNN are less than those of the other four models, and it has higher adversarial robustness.
Pornographic video detection based on semantic and image enhancement
Authors: Zeng Junhao , Liang Gang , Ma Yixin , Yang Xinyan , Chen Cheng 
Published: July 2024

Abstract
Pornographic video detection is of significant importance in curbing the proliferation of pornographic information on online video platforms. However, existing works often employ generic frame extraction methods that ignore the low-latency requirements of detection scenarios and the characteristics of pornographic videos. Additionally, existing detection methods have difficulties in detail characterization and semantic understanding, resulting in low accuracy. Therefore, this paper proposes an efficient pornographic video detection framework based on semantic and image enhancement. Firstly, a keyframe extraction method tailored for pornographic video detection is proposed to select representative frames. Secondly, a light enhancement method is introduced to facilitate accurate capture of pornographic visual cues. Moreover, a compression-reconstruction network is employed to eliminate adversarial perturbations, enabling models to obtain reliable features. Subsequently, YOLOv5 is introduced to locate and crop human targets in keyframes, reducing background interference and enhancing the expression of human semantic information. Finally, MobileNetV3 is employed to determine if the human targets contain pornographic content. The proposed framework is validated on the publicly available NPDI dataset, achieving an accuracy of 95.9%, surpassing existing baseline methods.
K-Nearest neighbor smart contract classification with semantic feature enhancement
Authors: Tian Gang , Zhao Guangxin , Wang Rui , Wang Jiachang , He Cheng 
Published: July 2024

Abstract
How to quickly and accurately retrieve relevant smart contracts from a huge amount of smart contracts has become an urgent need for users. The classification of smart contracts offers a solution by narrowing down the search space. Existing smart contract classification methods suffer from incomplete semantic feature extraction and a lack of consideration of the existence of rich semantics in existing smart contracts of the same class. To address the above problems, we propose a contrast learning and semantic feature embedding approach to enhance K-Nearest Neighbor (CL-SFE-IKNN). Our method fuses local features, global features, and account transaction features of the smart contract source code to perfect the semantics of the contract. Our method adopts KNN to retrieve multiple instances of contracts in the same class and assigns weights to the model output based on their labels. Meanwhile, we introduce contrastive learning and semantic feature embedding to enhance KNN retrieval to high-quality nearest neighbors of the same class. Experimental results show that by combining a KNN classifier with a traditional linear classifier, our model achieves the best performance compared with other baseline models.
Discordant Effects of Janus Kinase Inhibition Ex Vivo on Inflammatory Responses in Colonic Compared to Ileal Mucosa
Authors: Kaboub Kawsar , Abu-Taha Hanan , Arrouasse Jessica , Shaham-Barda Efrat , Wasserberg Nir , Hayman-Manzur Lucille , Friedenberg Adi , Levy-Barda Adva , Goren Idan , Levi Zohar , Banai-Eran Hagar , Avni-Biron Irit , Ollech Jacob E , Sharar-Fischler Tali , Yanai Henit , Cohen-Kedar Sarit , Dotan Iris , Rabinowitz Keren M 
Published: July 2024

Abstract

Background and Aims
Janus kinase [JAK] inhibitors are used for treating inflammatory bowel diseases [IBD]. We aimed to identify the molecular effects of JAK inhibition in human intestinal mucosa, considering IBD location and phenotype.

Methods
Colonic and ileal explants from patients with ulcerative colitis [UC], Crohn’s disease [CD], and non-IBD controls [NC] were assessed for levels of phosphorylated signal transducers and activators of transcription [p-STAT] and expression of inflammatory genes in response to an ex vivo JAK inhibitor [tofacitinib]. Cytokine production by lamina propria lymphocytes in response to tofacitinib was assessed. Human intestinal organoids were used to investigate the effects of JAK inhibitors on inducible nitric oxide synthase [iNOS] expression.

Results
Explants were collected from 68 patients [UC = 20, CD = 20, NC = 28]. p-STAT1/3/5 inhibition rates varied, being higher in colonic compared to ileal explants. p-STAT1/3 inhibition rates negatively correlated with levels of C-reactive protein [CRP]. While significant alterations in 120 of 255 inflammatory genes were observed in colonic explants, only 30 were observed in ileal NC explants. In colonic explants from UC, significant alterations were observed in five genes, including NOS2. JAK inhibition significantly decreased Th1/Th2/Th17-related cytokine production from lamina propria lymphocytes. Various JAK inhibitors reduced the interferon-γ-induced increase in iNOS expression in organoids.

Conclusions
A site-specific anti-inflammatory effect of JAK inhibition by tofacitinib was noted, whereby the colon was more robustly affected than the ileum. The ex vivo response to tofacitinib is individual. JAK inhibition may attenuate inflammation by decreasing iNOS expression. Ex vivo mucosal platforms may be a valuable resource for studying personalized drug effects in patients with IBD.