bluuebunny/crossref_metadata_2025_split huggingface dataset:
MicroRNAs and Cardiovascular Disease Risk
Authors: Searles Charles D. 
Published: January 2024

AbstractPurpose of ReviewMicroRNAs (miRNAs)—short, non-coding RNAs—play important roles in almost all aspects of cardiovascular biology, and changes in intracellular miRNA expression are indicative of cardiovascular disease development and progression. Extracellular miRNAs, which are easily measured in blood and can be reflective of changes in intracellular miRNA levels, have emerged as potential non-invasive biomarkers for disease. This review summarizes current knowledge regarding miRNAs as biomarkers for assessing cardiovascular disease risk and prognosis.Recent FindingsNumerous studies over the last 10–15 years have identified associations between extracellular miRNA profiles and cardiovascular disease, supporting the potential use of extracellular miRNAs as biomarkers for risk stratification. However, clinical application of extracellular miRNA profiles has been hampered by poor reproducibility and inter-study variability that is due largely to methodological differences between studies.SummaryWhile recent studies indicate that circulating extracellular miRNAs are promising biomarkers for cardiovascular disease, evidence for clinical implementation is lacking. This highlights the need for larger, well-designed studies that use standardized methods for sample preparation, miRNA isolation, quantification, and normalization.
Convergence of machine learning with microfluidics and metamaterials to build smart materials
Authors: Mittal Prateek , Nampoothiri Krishnadas Narayanan , Jha Abhishek , Bansal Shubhi 
Published: January 2024

AbstractRecent advances in machine learning have revolutionized numerous research domains by extracting the hidden features and properties of complex systems, which are not otherwise possible using conventional ways. One such development can be seen in designing smart materials, which intersects the ability of microfluidics and metamaterials with machine learning to achieve unprecedented abilities. Microfluidics involves generating and manipulating fluids in the form of liquid streams or droplets from microliter to femtoliter regimes. However, analysis of such fluid flows is always tiresome and challenging due to the complexity involved in the integration and detection of various chemical or biological processes. On the other hand, acoustic metamaterials manipulate acoustic waves to achieve unparalleled properties, which is not possible using natural materials. Nonetheless, the design of such metamaterials relies on the expertise of specialists or on analytical models that require an enormous number of expensive function evaluations, making this method extremely complex and time-consuming. These complexities and exorbitant function evaluations of both fluidic and metamaterial systems embark on the need for the support of computational tools that can identify, process, and quantify the large amounts of intricacy, thus machine learning techniques. This review discusses the shortcomings of microfluidics and acoustic metamaterials, which are overcome by neoteric machine learning approaches for building smart materials. The following review ends by providing the importance and future perspective of integrating machine learning and optimization approaches with microfluidic-based acoustic metamaterials to build smart and efficient intelligent next-generation materials.
Unleashing the power of decentralized serverless IoT dataflow architecture for the Cloud-to-Edge Continuum: a performance comparison
Authors: López Escobar Juan José , Díaz-Redondo Rebeca P. , Gil-Castiñeira Felipe 
Published: January 2024

Abstract
The advent of new computing and communication trends that link pervasive data sources and consumers, such as Edge Computing, 5G and IIoT, has led to the development of the Cloud-to-Edge Continuum in order to take advantage of the resources available in massive IoT scenarios and to conduct data analysis to leverage intelligence at all levels. This paper outlines the challenging requirements of this novel IoT context and presents an innovative IoT framework to develop dataflow applications for data-centric environments. The proposed design takes advantage of decentralized Pub/Sub communication and serverless nanoservice architecture, using novel technologies such as Zenoh and WebAssembly, respectively, to implement lightweight services along the Cloud-to-Edge infrastructure. We also describe some use cases to illustrate the benefits and concerns of the coming IoT generation, giving a communication performance comparison of Zenoh over brokered MQTT strategies.

Graphical abstract
Legal Information Retrieval and Entailment Using Transformer-based Approaches
Authors: Kim Mi-Young , Rabelo Juliano , Babiker Housam Khalifa Bashier , Rahman Md Abed , Goebel Randy 
Published: January 2024

AbstractThe challenge of information overload in the legal domain increases every day. The COLIEE competition has created four challenge tasks that are intended to encourage the development of systems and methods to alleviate some of that pressure: a case law retrieval (Task 1) and entailment (Task 2), and a statute law retrieval (Task 3) and entailment (Task 4). Here we describe our methods for Task 1 and Task 4. In Task 1, we used a sentence-transformer model to create a numeric representation for each case paragraph. We then created a histogram of the similarities between a query case and a candidate case. The histogram is used to build a binary classifier that decides whether a candidate case should be noticed or not. In Task 4, our approach relies on fine-tuning a pre-trained DeBERTa large language model (LLM) trained on SNLI and MultiNLI datasets. Our method for Task 4 was ranked third among eight participating teams in the COLIEE 2023 competition. For Task 4, We also compared the performance of the DeBERTa model with those of a knowledge distillation model and ensemble methods including Random Forest and Voting.
Investigating the effect of process variables for ball milling of wood chips: energy demand and particle size
Authors: Arce Carlos , Krátký Lukáš 
Published: January 2024

Abstract
Energy demand is the major drawback to using mechanical treatments within the biorefinery context. These treatments use energy to reduce particle size and crystallinity and, as a result, increase the accessibility of cellulose. However, the study of energy demand in milling needs to be more noticed. Therefore, this study aims to study how operational variables affect particle size and energy demand on one of the most used milling technologies: ball milling. The variables considered were mass of biomass, mass of balls and time. It was found that time is the most affecting variable for particle size and energy demand. Additionally, it was possible to optimise milling regarding energy demand and particle size. Furthermore, it was found that from the three traditional laws of comminution Bond was the one that gave the best results in terms of accuracy.
Lump solutions of the fractional Kadomtsev–Petviashvili equation
Authors: Borluk Handan , Bruell Gabriele , Nilsson Dag 
Published: January 2024

AbstractOf concern is the fractional Kadomtsev–Petviashvili (fKP) equation and its lump solution. As in the classical Kadomtsev–Petviashvili equation, the fKP equation comes in two versions: fKP-I (strong surface tension case) and fKP-II (weak surface tension case). We prove the existence of nontrivial lump solutions for the fKP-I equation in the energy subcritical case $$\alpha >\frac{4}{5}$$

α
>

4
5

by means of variational methods. It is already known that there exist neither nontrivial lump solutions belonging to the energy space for the fKP-II equation [9] nor for the fKP-I when $$\alpha \le \frac{4}{5}$$

α
≤

4
5

[26]. Furthermore, we show that for any $$\alpha >\frac{4}{5}$$

α
>

4
5

lump solutions for the fKP-I equation are smooth and decay quadratically at infinity. Numerical experiments are performed for the existence of lump solutions and their decay. Moreover, numerically, we observe cross-sectional symmetry of lump solutions for the fKP-I equation.
Successful treatment of glandular tularemia with azithromycin in a pregnant woman in Austria
Authors: Schubert Lorenz , Koelz Marita , Kussmann Manuel , Metz-Schimmerl Sylvia , Tobudic Selma , Traby Ludwig , Vossen Matthias G. , Winkler Stefan 
Published: January 2024

AbstractTreatment of tularemia during pregnancy is challenging due to toxicity of standard treatment regimens. Here, we report a 31-year-old woman with glandular tularemia who was successfully treated with intravenous azithromycin. Follow-up examinations over a 6-month period showed a sustained response to treatment. She later gave birth to a healthy child.
AI Adaptivity in a Mixed-Reality System Improves Learning
Authors: Yannier Nesra , Hudson Scott E. , Chang Henry , Koedinger Kenneth R. 
Published: January 2024

AbstractAdaptivity in advanced learning technologies offer the possibility to adapt to different student backgrounds, which is difficult to do in a traditional classroom setting. However, there are mixed results on the effectiveness of adaptivity based on different implementations and contexts. In this paper, we introduce AI adaptivity in the context of a new genre of Intelligent Science Stations that bring intelligent tutoring into the physical world. Intelligent Science Stations are mixed-reality systems that bridge the physical and virtual worlds to improve children’s inquiry-based STEM learning. Automated reactive guidance is made possible by a specialized AI computer vision algorithm, providing personalized interactive feedback to children as they experiment and make discoveries in their physical environment. We report on a randomized controlled experiment where we compare learning outcomes of children interacting with the Intelligent Science Station that has task-loop adaptivity incorporated, compared to another version that provides tasks randomly without adaptivity. Our results show that adaptivity using Bayesian Knowledge Tracing in the context of a mixed-reality system leads to better learning of scientific principles, without sacrificing enjoyment. These results demonstrate benefits of adaptivity in a mixed-reality setting to improve children’s science learning.
Renewable Energy Harvesting for Wireless Sensor Networks in Precision Agriculture
Authors: Khernane Sara , Bouam Souheila , Arar Chafik 
Published: January 2024

AbstractWireless sensors are used for smart building monitoring, biomedical applications, intelligent home appliances, urgent disaster management and precision agriculture production. These devices today operate with batteries that are very difficult to change. The major problem hindering the widespread deployment of wireless sensor networks is the need to constantly replace them because their batteries expires. We can see that it is possible to charge them using energy harvested from solar, vibration, thermal or ambient radio frequency sources. we can implement sustainable health surveillance systems, agriculture, mining, environmental protection and national infrastructure, which will improve the quality of life, save money and achieve ecological goals. We realized that it would be wise to specify a field of application for internet of things in order to be able to clarify the identification of the problem of energy consumption and its relation with renewable energies. In addition, one of the most interesting applications for the socio-economic fields in the world in recent years is Smart Farming. In this paper, we reviewed a state of the art on the use of renewable energy harvesting in precision agriculture.
Controllable augmentations for video representation learning
Authors: Qian Rui , Lin Weiyao , See John , Li Dian 
Published: January 2024

AbstractThis paper focuses on self-supervised video representation learning. Most existing approaches follow the contrastive learning pipeline to construct positive and negative pairs by sampling different clips. However, this formulation tends to bias the static background and has difficulty establishing global temporal structures. The major reason is that the positive pairs, i.e., different clips sampled from the same video, have limited temporal receptive fields, and usually share similar backgrounds but differ in motions. To address these problems, we propose a framework to jointly utilize local clips and global videos to learn from detailed region-level correspondence as well as general long-term temporal relations. Based on a set of designed controllable augmentations, we implement accurate appearance and motion pattern alignment through soft spatio-temporal region contrast. Our formulation avoids the low-level redundancy shortcut with an adversarial mutual information minimization objective to improve the generalization ability. Moreover, we introduce local-global temporal order dependency to further bridge the gap between clip-level and video-level representations for robust temporal modeling. Extensive experiments demonstrate that our framework is superior on three video benchmarks in action recognition and video retrieval, and captures more accurate temporal dynamics.
Plastid-encoded RNA polymerase variation in Pelargonium sect Ciconium
Authors: Breman FC , Korver JW , Snijder RC , Villard C , Schranz ME , Bakker FT 
Published: January 2024

AbstractCyto-Nuclear Incompatibility (CNI), in which there is a mismatch in the interaction between organelles and nucleus, impacts plant species evolution as it has a direct effect on the fitness of plants. It can reduce fertility and/or result in bleached plants devoid of functional chloroplasts. Understanding the processes leading to CNI could help to improve breeding efforts, especially in cases where species with desirable traits need to be crossed into existing cultivars. To better understand the occurrence of CNI and its effects on plant phenotype, we combined near comprehensive crossing series across a clade of species from Pelargonium section Ciconium with comparative genomics and protein modelling for plastid-encoded RNA polymerase (PEP), as the rpo genes encoding PEP subunits were found to be unusually highly divergent, especially in two length-variable regions. Of all plastome-encoded genes, we found these genes to contain more variation than observed across angiosperms and that this underlies structural variation inferred for PEP in P. sect. Ciconium. This variation, resulting in differing physico-chemical properties of the rpo-encoded peptides, provides a possible explanation for the observed CNI, but we cannot directly correlate plastid related CNI phenotypes to rpo genotypes. This suggests that more than one interaction between the nuclear genome and the plastome genes are needed to fully explain the observed patterns.
The effect of vitamin K supplementation on cardiovascular risk factors: a systematic review and meta-analysis
Authors: Zhao Qiu-Yan , Li Qiu , Hasan Rashedi Minoo , Sohouli Mohammadhassan , Rohani Pejman , Velu Periyannan 
Published: January 2024

Abstract
Cardiovascular disease (CVD) is one of the most important diseases which controlling its related risk factors, such as metabolic and inflammatory biomarkers, is necessary because of the increased mortality risk of that. The aim of our meta-analysis is to reveal the general effect of vitamin K supplementation on its related risk factors. Original databases were searched using standard keywords to identify all randomized clinical trials (RCTs) investigating the effects of vitamin K on CVD. Pooled weighted mean difference (WMD) and 95 % confidence intervals (95 % CI) were achieved by random-model effect analysis for the best estimation of outcomes. The statistical heterogeneity was determined using the Cochran's Q test and I2 statistics. Seventeen studies were included in this systematic review and meta-analysis. The pooled findings showed that vitamin K supplementation can reduce homeostatic model assessment insulin resistance (HOMA-IR) (WMD: −0⋅24, 95 % CI: −0⋅49, −0⋅02, P = 0⋅047) significantly compared to the placebo group. However, no significant effect was observed on other outcomes. Subgroup analysis showed a significant effect of vitamin K2 supplementation compared to vitamin K1 supplementation on HOMA-IR. However, no significant effect was observed on other variables. Also, subgroup analysis showed no potential effect of vitamin K supplementation on any outcome and omitting any articles did not affect the final results. We demonstrated that supplementation with vitamin K has no effect on anthropometrics indexes, CRP, glucose metabolism, and lipid profile factors except HOMA-IR.
Cambrian trilobites from the Nounan Dolomite and lower St. Charles Formation (upper Marjuman to lower Sunwaptan; Miaolingian to Furongian Series), Smithfield Canyon, northern Utah
Authors: Sundberg Frederick A. , Cothren Hannah R. , Dehler Carol M. 
Published: January 2024

AbstractThe trilobite faunas that occur with the Steptoean Positive Isotope Carbon Excursion (SPICE) at Smithfield Canyon, Utah, have been reported, but not illustrated. Given the importance of the SPICE at this section for international correlations, the trilobites from new collections from the upper Nounan Dolomite to lower St. Charles Formation at Smithfield Canyon are reported herein and integrated with the previously reported taxa. Trilobite assemblages indicate that the upper Cedaria to the Ellipsocephaloides biozones (Miaolingian Series, Guzhangian Stage to Furongian Series, Jiangshanian Stage) are present stratigraphically below or above the SPICE.Some of the taxa reported herein may represent new species, but they are not represented by well-enough preserved specimens and are left in open nomenclature. However, Kingstonia smithfieldensis n. sp. and Bromella utahensis n. sp. are named on the basis of common and well-preserved specimens.New carbon isotope data from Smithfield Canyon from an overlapping section of the lower St. Charles Formation, that add to the overall shape of the SPICE curve, are presented. The new δ13C values above the Elvinia Biozone range from –0.36‰ to +1.5‰, confirming that the SPICE concludes within the Elvinia Biozone.UUID: http://zoobank.org/ad4fd372-8da4-4caa-98ed-ea82700cca60
DEVELOPMENT OF A 14C PROTOCOL AT THE LMC14 FOR THE DATING OF CULTURAL HERITAGE MATERIALS: HISTORICAL MORTARS. PARTICIPATION IN THE MODIS INTERNATIONAL INTERCOMPARISON CAMPAIGN
Authors: Moreau Christophe , Dumoulin Jean-Pascal , Jaber Maguy , Caffy Ingrid , Delqué-Količ Emmanuelle , Goulas Cédric , Hain Stéphane , Perron Marion , Setti Valérie , Sieudat Marc , Thellier Bruno , Beck Lucile 
Published: January 2024

ABSTRACTThe absolute dating of mortar by accelerator mass spectrometry (AMS) has been the subject of renewed interest for several years. International intercomparison campaigns, called MODIS (MOrtar Dating Intercomparison Study), have been carried out. The first MODIS-1 campaign highlighted limitations in mortar dating, due to the similarity between the primary material to be dated (binder) and the contaminant (exogenous CaCO3). Methods have since emerged to overcome this problem and the need for a good preliminary characterization has been proven. The Laboratoire de Mesure du Carbone 14 (LMC14) took part in the second intercomparison campaign, MODIS2, by applying thermal decomposition increments to distinguish the carbonated binder, the organic matter contaminants (late in formation pyrogenic carbonate, LDH) and limestone. The LMC14 results on MODIS2 are quite conclusive on “pure” re-carbonated lime mortar binders containing little contaminant geological limestone but show their weaknesses for mortars heavily contaminated in Dolomites, which are difficult to discern from the binder. Recommendations for users of radiocarbon (14C) dating on mortar-based materials are made in the conclusion.
Divisive or Descriptive?: How Americans Understand Critical Race Theory
Authors: Safarpour Alauna , Lunz Trujillo Kristin , Green Jon , Pippert Caroline High , Lin Jennifer , Druckman James N 
Published: January 2024

AbstractCritical Race Theory (CRT) has become a flashpoint of elite political discord, yet how Americans actually perceive CRT is unclear. We theorize that Republican elites utilized a strong framing strategy to re-define CRT as an “empty signifier” representing broader racial and cultural grievances. Using a survey and a pre-registered experiment among U.S. adults (N = 19,060), we find that this strategy worked. Republicans exhibit more familiarity with CRT and hold more negatively valenced (and wide ranging) sentiments toward CRT, relative to Democrats. Moreover, compared to teaching the legacy of racism in schools, Republicans are significantly more opposed to teaching CRT while Democrats express greater uncertainty. Our findings suggest that by framing CRT as a broad term that envelopes many grievances (including those beyond the scope of CRT), Republican elites have shaped a subset of Americans’ understanding of and attitudes toward CRT.
Black Millennials, Slipping Alliances, and the Democratic Party
Authors: Watts Donovan A. 
Published: January 2024

AbstractRecent election cycles show a reluctance among Black millennials to support the Democratic Party, which suggests that they are not captured by the party like their predecessors. While we know that African Americans have historically remained a loyal voting bloc, it is important to analyze whether there are generational differences with respect to Black Democratic Party loyalty. In this study, I analyze Black millennial partisanship identification and compare it to Black non-millennials (Baby Boomers and Gen X’ers). To test this, I employ a multi-method approach. My results show that while Black millennials continue to identify with the Democratic Party, they are not as loyal to the Democratic Party when compared to Black non-millennials. Further, I find that Black millennials are not changing loyalties to the Republican or a third party. Instead, Black millennials are willing to withhold their vote altogether if they are not satisfied with any Democratic candidates. My work has critical implications in how we understand Black politics and reveals that Democratic candidates will have to earn Black millennials vote going forward.
Emissions Sufficientarianism
Authors: Duus-Otterstrom Goran 
Published: January 2024

AbstractThis paper defends strong emissions sufficientarianism as an approach to assigning moral rights to generate greenhouse gas emissions. Strong emissions sufficientarianism holds that only subsistence emitting is morally permissible. This paper argues that, since it is uncertain how many subsistence emissions there will be, the present generation owes it to future generations to refrain from generating non-subsistence emissions, not to risk imposing on them a tragic choice between sacrificing themselves and contributing to very dangerous climate change. The paper also addresses the charge that emissions sufficientarianism, in general, is too permissive since it entails a right to contribute to very dangerous climate change. The overall message is that, given the moral urgency posed by climate change, there is little room for distributive principles besides emissions sufficientarianism. This casts doubt on the appropriateness of relying on carbon budgets in assigning rights to emit.