Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the anti-inflammatory potential of Mesua ferrea linn. stem bark through network pharmacology approach

Mesua ferrea Linn. (MF) is a medicinal plant whose stem bark has historically been used to treat skin disorders, gastrointestinal, and anti-inflammatory conditions. Although the MF stem bark’s contribution to inflammation was assessed, its exact mode of action remained unknown. This study aimed to investigate the pharmacological mechanisms of MF against inflammation utilizing network pharmacology, molecular docking, and molecular dynamics (MD) simulation. An integrated network pharmacology approach was used to predict the pharmacological basis and potential mechanisms by which these ingredients may treat and prevent inflammation. This approach included target identification, network construction, topological analysis, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, molecular docking, and MD simulation. Utilizing the pre-Absorption, Distribution, Metabolism, Elimination, and Toxicity tool, the drug-likeness of the phytoconstituents was evaluated. Protein-protein interaction network and protein interaction network was constructed. The results indicated that androgen receptor, Estrogen Receptor alpha, CYP19A1, retinoic acid receptor alpha, nuclear factor erythroid 2-related factor 2, thyrotropin receptor, nuclear factor kappa B subunit 1, and Albumin are crucial proteins engaged directly or indirectly in inflammatory pathways and illnesses. Finally, the targets are validated by molecular docking and MD simulation. MF may be effective for alleviating inflammatory conditions and the mechanism of action is characterized by multi-compound, multi-target, and multi-pathways. Thus, our study provides certain evidence for the development and utilization of medicinal plants.
Derivation via Hamilton's principle of a new shallow-water model using a color function for the macroscopic description of partial wetting phenomena

This paper presents a new shallow-water type model suitable for the simulation of partially wetting liquid films without the need for very fine resolution of the contact line phenomena, which is particularly suitable for industrial applications. This model is based on the introduction of a color function, propagated at the averaged velocity of the bulk flow, and equal to one where there is a liquid film and zero in the dry zone, which implies a non zero gradient only at the interface. This approach has the advantage of easily locating the interface, allowing to model macroscopically the forces acting at the contact line, which is essential for the simulation of partial wetting phenomena. The formal derivation of this model is based on the principle of least action known as Hamilton's principle. Here this principle is applied in a full Eulerian form to derive the complete system of equations with the color function. This method proves to be particularly suitable for this type of development and as an illustration it is also applied to recover another model proposed by Lallement et al. [39, 73]. Finally, both models are compared from a theoretical point of view and the advantages of the new color function based model are discussed.
PALEOECOLOGÍA DE LA FORMACIÓN SANTA CRUZ (MIOCENO INFERIOR) EN EL EXTREMO SUDESTE DE LA PATAGONIA

"The Santa Cruz Formation cointains one of the most di verse and rich vertebrate fossil assemblages in South America. Palaeoecological interpretation of this unit is based on the analysis of 22 fossiliferous horizons (20 of which include specimens identifiable at specific level, collectively including representatives 60 species of 44 genera, 25 families and 13 orders). Mammals are the most commonly recorded vertebrates, although amphibians and birds are also present. Main trends from base to top of sequence are: 1) decrease of taxonomic diversity; 2) increase of number of species with euhypsodont teeth, and decrease of those with brachyodont dentition; 3) decrease of number of species at the largest and smallest body sizes; 4) glyptodontids and toxodontids become more diverse; 5) reduction of megatheroideid average body size; 6) protheroteid diversity decreases. This suggests that during the deposition of the Estancia La Costa Member, the climate deteriorated and became less humid; thus, the paleoenvironmental conditions, and consequently the fauna, changed. "
Integrative Transcriptomic Analysis Reveals Upregulated Apoptotic Signaling in Wound-Healing Pathway in Rat Liver Fibrosis Models

Liver fibrosis, defined by the aberrant accumulation of extracellular matrix proteins in liver tissue due to chronic inflammation, represents a pressing global health issue. In this study, we investigated the transcriptomic signatures of three independent liver fibrosis models induced by bile duct ligation, carbon tetrachloride, and dimethylnitrosamine (DMN) to unravel the pathological mechanisms underlying hepatic fibrosis. We observed significant changes in gene expression linked to key characteristics of liver fibrosis, with a distinctive correlation to the burn-wound-healing pathway. Building on these transcriptomic insights, we further probed the p53 signaling pathways within the DMN-induced rat liver fibrosis model, utilizing western blot analysis. We observed a pronounced elevation in p53 protein levels and heightened ratios of BAX/BCL2, cleaved/pro-CASPASE-3, and cleaved/full length-PARP in the livers of DMN-exposed rats. Furthermore, we discovered that orally administering oligonol—a polyphenol, derived from lychee, with anti-oxidative properties—effectively countered the overexpressions of pivotal apoptotic genes within these fibrotic models. In conclusion, our findings offer an in-depth understanding of the molecular alterations contributing to liver fibrosis, spotlighting the essential role of the apoptosis pathway tied to the burn-wound-healing process. Most importantly, our research proposes that regulating this pathway, specifically the balance of apoptosis, could serve as a potential therapeutic approach for treating liver fibrosis.
The Impact of Twitter Users' Characteristics on Behaviors: Insights Into the Role of Followers

Researchers have focused on leadership, often overlooking followership. The notion of followership was irreversibly transformed with the advent and societal adoption of followership systems, such as Twitter. To examine such emergent systems, this paper advances a distinct form of followership: eFollowership. To understand Twitter and its users, the eFollowership concept is explicated and synthesized by adapting several followership lenses from the literature. The authors empirically examined eFollowership by assessing the roles constructed by 301 Twitter users and the relationships between these users' role-based characteristics and behaviors with partial least squares structural equation modeling (PLS-SEM). Results showed that users' voicing and empowering behaviors were significantly influenced by users' characteristics: personal sense of power, eCourage, and social capital. Users' helping behaviors were related to users' personal sense of power and social capital, but not to eCourage. Surprisingly, users' disempowering behaviors were unrelated to all three users' characteristics.
ULTIMA: Ultimate Balance of Centralized and Distributed Benefits for Interference Management in 5G Cellular Networks

To cope with unprecedented mobile traffic explosion, various state-of-the-art wireless technologies such as small cell, mmWave, and heterogeneous networks have been intensively studied. Especially, small cell enhances the network capacity at the same area by deploying more next-generation NodeBs (gNBs) with the universal frequency reuse; nevertheless, it increases interference due to the shorter distance between cells requiring more exchange of feedback message for interference management (IM). In this paper, we first propose a practical cellular network architecture, namely EdgeSON, that provides network operators the opportunity to strike a balance between centralized and distributed cellular managements for the enhancement of the network performance with a reasonable feedback information exchange and spatio-temporal power sharing. On top of EdgeSON, we formulate an optimization problem aiming to maximize the time-averaged utility of users constrained by the time average transmit power budget per cluster. Although we exploit Lyapunov optimization to induce slot-by-slot subproblems, one of the transformed subproblems to find a set of power allocation and user scheduling is known as NP-hard. To tackle this issue, we propose a low-complex and practical interference management algorithm, namely IMPowerShare by introducing a critical user and power sharing virtual queue concepts which maximally exploit structural characteristics of EdgeSON to efficiently solve the NP-hard problem. IMPowerShare definitely differs from the existing interference management or spatio-temporal power sharing works in perspectives of practical feedback information exchange in EdgeSON and optimization framework. Finally, via extensive simulations in real gNB topologies in Korea, we verify that IMPowerShare outperforms the existing interference management algorithms in small cell networks.
Spatiotemporal K-Nearest Neighbors Algorithm and Bayesian Approach for Estimating Urban Link Travel Time Distribution From Sparse GPS Trajectories

Travel time distribution (TTD) estimation on urban arterial links with sparse trajectory data is a practically important while substantially challenging subject. Although several methods have been proposed to estimate link TTDs, the applications of the existing methods are often limited by their shortcomings, such as the needs for extra road geometric features, signal control plans, model assumptions, etc. As an alternative, this article makes full use of ubiquitous incomplete trajectories that only traverse part of the link and introduces a novel bilevel Bayesian sampling method to alleviate the data sparsity problem. The focus of this study is to develop a framework of estimating link TTDs based on incomplete and complete trajectories by using the spatiotemporal K-nearest neighbors (KNN) algorithm and Bayesian approach. Three major steps are involved: • First, we consider a straightforward trajectory imputation method for missing GPS points to improve the input data quality and serve as a basis for measuring the similarity between incomplete and complete trajectories. • Then, a spatiotemporal KNN algorithm is proposed to estimate virtual link travel times of incomplete trajectories for the purposes of increasing the travel time sample size. • Finally, a bilevel Bayesian-based sampling method comprising an improved particle filter and Gibbs sampling is introduced to approximate the posterior distribution of link travel times based on the enhanced data. A case study was conducted on a major arterial in Nanjing, China. The results indicate that the proposed approach with the augmented data can achieve promising performance compared to the competing methods in terms of effectiveness and adaptiveness.
Un Modèle de collision arc insulaire - ride océanique : évolution sismo-tectonique et pétrologie des volcanites de la zone d'affrontement arc des Nouvelles-Hébrides - ride des Loyauté

De 34 a 9 ma un volcanisme anorogenique a caracterise la ride des loyaute. La collision entre cette ride et l'arc des nouvelles-hebrides a entraine une restructuration des parties meridionales de la zone de subduction des nouvelles-hebrides et du bassin nord-fidjien. En particulier, une nouvelle limite de plaque est apparue a travers l'arc. Au sud de cette limite, seules des laves derivees de boninites sont presentes. La comparaison entre les nouvelles-hebrides et les tonga permet de proposer un modele dans lequel la collision entre une ride massive et une terminaison d'arc mene a l'accretion de cette terminaison a la plaque plongeante.
Physical Devices-Agnostic Hybrid Fuzzing of IoT Firmware

With the rapid expansion of the Internet of Things, a vast number of microcontroller-based (MCU) IoT devices are now susceptible to attacks through the Internet. Vulnerabilities within the firmware are one of the most important attack surfaces. Fuzzing has emerged as one of the most effective techniques for identifying such vulnerabilities. However, when applied to IoT firmware, several challenges arise, including: 1) the inability of firmware to execute properly in the absence of peripherals; 2) the lack of support for exploring input spaces of multiple peripherals; 3) difficulties in instrumenting and gathering feedback; and 4) the absence of a fault detection mechanism. To address these challenges, we have developed and implemented an innovative peripheral-independent hybrid fuzzing tool called FirmHybirdFuzzer. This tool enables testing of MCU firmware without reliance on specific peripheral hardware. First, a unified virtual peripheral was integrated to model the behaviors of various peripherals, thus enabling the physical devices-agnostic firmware execution. Then, a hybrid event generation approach was used to generate inputs for different peripheral accesses. Furthermore, two-level coverage feedback was collected to optimize the testcase generation. Finally, a plugin-based fault detection mechanism was implemented to identify typical memory corruption vulnerabilities. A large-scale experimental evaluation has been performed to show FirmHybirdFuzzer’s effectiveness and efficiency.
Sustainable Isolation of Bioactive Compounds and Proteins from Plant-Based Food (and Byproducts)

Plant-based food produces significantly less greenhouse gases, and due to its wealth of bioactive components and/or plant-based protein, it becomes an alternative in a sustainable food system. However, the processing and production of products from plant sources creates byproducts, which can be waste or a source of useful substances that can be reused. The waste produced during the production and processing of food is essentially nutrient- and energy-rich, and it is recognized as an excellent source of secondary raw materials that could be repurposed in the process of manufacturing and preparing food, or as feed for livestock. This review offers an overview of the sources and techniques of the sustainable isolation of bioactive substances and proteins from various sources that might represent waste in the preparation or production of food of plant origin. The aim is to uncover novel approaches to use waste and byproducts from the process of making food to provide this waste food an additional benefit, not forgetting the expectations of the end user, the consumer. For the successful isolation of bioactive ingredients and proteins from food of plant origin, it is crucial to develop more eco-friendly and efficient extraction techniques with a low CO2 footprint while considering the economic aspects.
An Improved Adaptive Sparrow Search Algorithm for TDOA-Based Localization

The Ultra-Wideband (UWB) indoor positioning method is widely used in areas where no satellite signals are available. However, during the measurement process of UWB, the collected data contain random errors. To alleviate the effect of random errors on positioning accuracy, an improved adaptive sparrow search algorithm (IASSA) based on the sparrow search algorithm (SSA) is proposed in this paper by introducing three strategies, namely, the two-step weighted least squares algorithm, adaptive adjustment of search boundary, and producer–scrounger quantity adaptive adjustment. The simulation and field test results indicate that the IASSA algorithm achieves significantly higher localization accuracy than previous methods. Meanwhile, the IASSA algorithm requires fewer iterations, which overcomes the problem of the long computation time of the swarm intelligence optimization algorithm. Therefore, the IASSA algorithm has advantages in indoor positioning accuracy and robustness performance.
Development of a self-contained robotic hand with dexterous grasping capabilities for research applications

—Thumb loss can diminish one’s hand’s functionality by up to 40% and the loss of one’s entire hand can severely impact a person’s ability to perform simple day-to-day tasks. Therefore, there exists a need to focus on the development of a thumb mechanism which supports dexterous grasping activities in anthropomorphic robotic hands. This paper documents the design process of a novel robotic hand, and shows experimental results validating its overall performance. A large focus was placed on developing a novel thumb mechanism which could replicate the thumb’s characteristic movement types, namely flexion-extension, abduction-adduction, and opposition-reposition. Additional focus was placed on developing a mechanism for flexion-extension movement of the fingers which did not incorporate passive components and on producing a fully self-contained prototype – with the electronics and actuators contained inside the palm, and the power supply inset against the back of the palm. The hand successfully followed motion commands from a sensor glove, and was able to replicate 14 grasp configurations which demonstrated its dexterous grasping abilities.
CNT-NeRF: Carbon Nanotube Forest Depth Layer Decomposition in SEM Imagery using Generative Adversarial Networks

Carbon nanotube (CNT) forests are imaged using scanning electron microscopes (SEMs) that project their multilayered 3D structure into a single 2D image. Image analytics, particularly instance segmentation is needed to quantify structural characteristics and to predict correlations between structural morphology and physical properties. The inherent complexity of individual CNT structures is further increased in CNT forests due to density of CNTs, interactions between CNTs, occlusions, and lack of 3D information to resolve correspondences when multiple CNTs from different depths appear to cross in 2D. In this paper, we propose CNT-NeRF, a generative adversarial network (GAN) for simultaneous depth layer decomposition and segmentation of CNT forests in SEM images. The proposed network is trained using a multi-layer, photo-realistic synthetic dataset obtained by transferring the style of real CNT images to physics-based simulation data. Experiments show promising depth layer decomposition and accurate CNT segmentation results not only for the front layer but also for the partially occluded middle and back layers. This achievement is a significant step towards automated, image-based CNT forest structure characterization and physical property prediction.
Myeloperoxidase Alters Lung Cancer Cell Function to Benefit Their Survival

Myeloperoxidase (MPO) is a neutrophil-derived enzyme that has been recently associated with tumour development. However, the mechanisms by which this enzyme exerts its functions remain unclear. In this study, we investigated whether myeloperoxidase can alter the function of A549 human lung cancer cells. We observed that MPO promoted the proliferation of cancer cells and inhibited their apoptosis. Additionally, it increased the phosphorylation of AKT and ERK. MPO was rapidly bound to and internalized by A549 cells, retaining its enzymatic activity. Furthermore, MPO partially translocated into the nucleus and was detected in the chromatin-enriched fraction. Effects of MPO on cancer cell function could be reduced when MPO uptake was blocked with heparin or upon inhibition of the enzymatic activity with the MPO inhibitor 4-aminobenzoic acid hydrazide (4-ABAH). Lastly, we have shown that tumour-bearing mice treated with 4-ABAH had reduced tumour burden when compared to control mice. Our results highlight the role of MPO as a neutrophil-derived enzyme that can alter the function of lung cancer cells.
The Early Records of Sir Robert Cotton's Library: Formation, Cataloguing, Use

Following the dissolution of the monasteries in the 1530s and the dispersal of their libraries, a number of British collectors set to work to recover as much as possible. Of their second generation, Sir Robert Cotton (1571-1631) was an outstanding member, also acquiring a wide range of other material. Indeed, so important was his library that it became one of the foundation collections of the British Museum in 1753. Significant records- never previously studied as a whole- survive from the early years of Cotton's library and this book edits and analyses these, throwing important new light on Sir Robert, his son and grandson as collectors, and providing much fresh evidence on the history of their collection and its development. "
A Pilot Study on the Feasibility of an Extended Suckling System for Pasture-Based Dairies

Simple Summary There is an increased global effort to develop and identify the opportunities and challenges of extended dairy cow-calf suckling systems due to societal concerns about removing calves from cows soon after birth. Implementing a pasture-based system where the dams have half-day contact with their calves and are milked once a day could potentially serve as a viable choice for developing alternative practices in the dairy industry. However, most research on extended suckling systems has been conducted on indoor dairy farms. This paper describes an investigation into the productivity of cows and calves in a pasture-based extended suckling system featuring part-time cow-calf contact and once-a-day milking. Although suckled cows produced less saleable milk than commercially managed cows, their reduced milk yield did not persist after weaning. Dam-reared calves grew faster than commercially reared calves from weeks 3 to 9. The system offers a promising foundation for future large-scale and longitudinal research on the benefits, challenges, and scalability of pastoral cow-calf dairy systems. This approach would be in line with public expectations of enhanced animal welfare in the dairy industry by addressing the concern of removing calves from cows soon after birth. Abstract This study investigated cow-calf productivity in a 10-week, pasture-based, extended suckling system featuring part-time cow-calf contact and once-a-day milking. A total of 30 dairy cows and their calves were assigned to two treatments: (1) cow and calf managed in an extended suckling system; or (2) cow and calf separated at birth and managed as usual. Cow-calf pairs grazed together during the day and spent the night separated by fence-line contact. The dams were reunited with the calves after once-a-day milking every morning. The commercial treatment pairs were separated after birth, and cows were milked twice a day and managed within the farm herd. Commercial calves were reared and managed as per commercial Australian practices. Cow-calf dams yielded 9 L/cow/day less saleable milk (p < 0.001), and their milk had lower fat (p = 0.04) but a higher protein percentage (p < 0.001) than commercial cows during pre-weaning. However, milk yield and composition were comparable post-weaning. Dam-suckled calves gained weight faster and were therefore weaned 2 weeks earlier than commercial calves, which were offered 8 L/day milk. This study has demonstrated a novel system of extended cow-calf suckling that could be practical to implement in pasture-based dairies. The long-term effects and scalability of the extended suckling system described here require further validation.