Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of the River Discharge Alteration

This article aims to analyze the alteration in water discharge due to the building of one of the largest dams in Romania. Modifications in the hydrological patterns of the studied river were emphasized by a complex technique that includes decomposition models of the series into trends, seasonal indices, and random components, as well as into Intrinsic Mode Functions (IMFs). The Mann–Kendall trend test indicates the existence of different positive slopes for the subseries S1 and S2 (before and after the inception of the Siriu dam, respectively) built from the raw series, S. The stationarity hypothesis was rejected for all series. The multifractal analysis shows two different patterns of the data series. After decomposing the subseries S1 and S2, it resulted that the seasonality indices are not the same. Moreover, the seasonal variations decreased after building the dam. Empirical Mode Decomposition (EMD) unveils different short- and long-term patterns of the series before and after building the dam, concluding that there is a significant alteration in the river discharge after the dam’s inception.
Iterative ensemble smoothers for data assimilation in coupled nonlinear multiscale models

This paper identifies and explains particular differences and properties of adjoint-free iterative ensemble methods initially developed for parameter estimation in petroleum models. The aim is to demonstrate the methods’ potential for sequential data assimilation in coupled and multiscale unstable dynamical systems. For this study, we have introduced a new nonlinear and coupled multiscale model based on two Kuramoto-Sivashinsky equations operating on different scales where a coupling term relaxes the two model variables towards each other. This model provides a convenient testbed for studying data assimilation in highly nonlinear and coupled multiscale systems. We show that the model coupling leads to cross-covariance between the two models’ variables, allowing for a combined update of both models. The measurements of one model’s variable will also influence the other and contribute to a more consistent estimate. Secondly, the new model allows us to examine the properties of iterative ensemble smoothers and assimilation updates over finite-length assimilation windows. We discuss the impact of varying the assimilation windows’ length relative to the model’s predictability time scale. Furthermore, we show that iterative ensemble smoothers significantly improve the solution’s accuracy compared to the standard ensemble-Kalman-filter update. Results and discussions provide an enhanced understanding of the ensemble methods’ potential implementation and use in operational weather and climate-prediction systems.
Assessing flood risks and exploring opportunities for flood-based farming in the dry lowlands of Ethiopia

Food grown in the rainfed system in Ethiopia is frequently insufficient to meet household food needs due to recurrent drought, which causes severe food insecurity. Ethiopia’s drylands have also been hit by an increase in torrential floods. As a result, the ability to adapt to shocks and risks decreases. Despite the opportunity of highland-to-lowland to lowland connectivity, the opportunities for flood-recession farming are poorly understood. This study maps flood recession opportunities incorporating national flood occurrence information, flood images, and SMAP surface soil moisture from Soil Moisture Active Passive (SMAP) images in Omo Gibe basin and Mile sub-basin. The analysis demonstrates that during the past three decades, there have been substantial flood incidents in the country’s eastern, south-eastern, and southern regions. Notably, floods that happened in 1996, 2005, 2006, 2013, and 2018 affected 90, 91, 74, 74, and 69 locations, respectively. In 2020, flooding affected a considerable area (274 locations), which demonstrates the rise in flood hazards. Based on multi-criteria suitability analysis, about 32 million hectares of lowlands are highly suitable (61%) and moderately suitable (39%) for flood-based farming. In the Omo-Gibe and the Mile sub-basin, flood-recession zone mapping using a change detection approach revealed that Omo-Gibe basin has 107,359 ha and 29,550 ha of flood zones suitable for flood recession farming and Mile sub-basin of 8,048 ha and 88 ha, during the major and short rainy seasons, respectively. Our results highlight the extent of flood-prone areas and their suitability for flood farming and provide evidence of alternative strategies for managing flood risks. Consequently, identifying potential flood-prone areas using remote sensing technology aids decision-makers and subject-matter experts in introducing and demonstrating various types of flood-based farming. Further research is recommended to identify and validate appropriate flood farming practices under different biophysical and socio-economic contexts and explore complementary opportunities as well as support informed decision-making on flood risk management and recession flood strategies in the dry lowlands of Ethiopia.
Design and Development of an Integrated Virtual-Reality Training Simulation Sand Table for Rail Systems

With the rapid development of the economy, it is imperative to improve the quality of training for operational and managerial talents in the railway industry. To address issues such as efficiency, safety, and cost in railway industry practical training, it is crucial to establish a more comprehensive and efficient high-value virtual–real integration simulation experimental training resource. Therefore, this paper takes the actual work process as the core driving force, utilizes advanced information technology and intelligent devices, and is based on the comprehensive training platform for automatic control of physical trains combined with unmanned aerial vehicle (UAV) equipment. It achieves the integration of hardware and software construction to design and develop a comprehensive simulation training sand table system that incorporates functions such as training, demonstration, testing, and experiments. This system builds an integrated platform for training simulation functions, capable of simulating a railway centralized traffic control system, enabling railway dispatching simulation, driving simulation, and inspection simulation experiences. Additionally, it designs experimental processes at three levels: cognition, practical operation, and enhancement, tailored to the needs of talent development. The rail transportation training simulation sand table effectively reduces training costs and enhances the practical ability training quality of railway operation management personnel, meeting the requirements for talent development in the railway and related industries under new circumstances.
What drives microplate motion and deformation in the northeastern Caribbean plate boundary region?

The north Caribbean plate boundary zone is a broad deformation zone with several fault systems and tectonic blocks that move with different velocities. The indentation by the Bahamas Platform (the “Bahamas Collision”) is generally invoked as a cause of this fragmentation. We propose that a second driver of deformation is the western edge of the south dipping Puerto Rico slab moving sideways with the North America plate. The westward motion of the slab edge results in a push on the Caribbean plate farther west. We refer to this second mechanism for deformation as “Slab Edge Push. ” The motion of the North America plate relative to the Caribbean plate causes both drivers to migrate from east to west. The Bahamas Collision and Slab Edge Push have been operating simultaneously since the Miocene. The question is the relative importance of the two mechanisms. We use mechanical finite element models that represent the two mechanisms from the late Oligocene (30 Ma) to the present. For the present, both models successfully reproduce observed deformation, implying that both models are viable. Back in time the Slab Edge Push mechanism better reproduces observations. Neither mechanism successfully reproduces the observed Miocene counterclockwise rotation of Puerto Rico. We use this rotation to tune a final model that includes fractional contributions of both mechanisms. We find that the Slab Edge Push was the dominant driver of deformation in the north Caribbean plate boundary zone since 30 Ma.
A Multi-Sensor Approach to Characterize Winter Water-Level Drawdown Patterns in Lakes

Artificial manipulation of lake water levels through practices like winter water-level drawdown (WD) is prevalent across many regions, but the spatiotemporal patterns are not well documented due to limited in situ monitoring. Multi-sensor satellite remote sensing provides an opportunity to map and analyze drawdown frequency and metrics (timing, magnitude, duration) at broad scales. This study developed a cloud computing framework to process time series of synthetic aperture radar (Sentinel 1-SAR) and optical sensor (Landsat 8, Sentinel 2) data to characterize WD in 166 lakes across Massachusetts, USA, during 2016–2021. Comparisons with in situ logger data showed that the Sentinel 1-derived surface water area captured relative water-level fluctuations indicative of WD. A machine learning approach classified lakes as WD versus non-WD based on seasonal water-level fluctuations derived from Sentinel 1-SAR data. The framework mapped WD lakes statewide, revealing prevalence throughout Massachusetts with interannual variability. Results showed WDs occurred in over 75% of lakes during the study period, with high interannual variability in the number of lakes conducting WD. Mean WD magnitude was highest in the wettest year (2018) but % lake area exposure did not show any association with precipitation and varied between 8% to 12% over the 5-year period. WD start date was later and duration was longer in wet years, indicating climate mediation of WD implementation driven by management decisions. The data and tools developed provide an objective information resource to evaluate ecological impacts and guide management of this prevalent but understudied phenomenon. Overall, the results and interactive web tool developed as part of this study provide new hydrologic intelligence to inform water management and policies related to WD practices.
Blood Markers Show Neural Consequences of LongCOVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) persists throughout the world with over 65 million registered cases of survivors with post-COVID-19 sequelae, also known as LongCOVID-19 (LongC). LongC survivors exhibit various symptoms that span multiple organ systems, including the nervous system. To search for neurological markers of LongC, we investigated the soluble biomolecules present in the plasma and the proteins associated with plasma neuronal-enriched extracellular vesicles (nEVs) in 33 LongC patients with neurological impairment (nLongC), 12 COVID-19 survivors without any LongC symptoms (Cov), and 28 pre-COVID-19 healthy controls (HC). COVID-19 positive participants were infected between 2020 and 2022, not hospitalized, and were vaccinated or unvaccinated before infection. IL-1β was significantly increased in both nLongC and Cov and IL-8 was elevated in only nLongC. Both brain-derived neurotrophic factor and cortisol were significantly elevated in nLongC and Cov compared to HC. nEVs from people with nLongC had significantly elevated protein markers of neuronal dysfunction, including amyloid beta 42, pTau181 and TDP-43. This study shows chronic peripheral inflammation with increased stress after COVID-19 infection. Additionally, differentially expressed nEV neurodegenerative proteins were identified in people recovering from COVID-19 regardless of persistent symptoms.
SAR Ship Detection Based on Explainable Evidence Learning Under Intraclass Imbalance

Synthetic aperture radar (SAR) ship detection is an important technology supporting water traffic monitoring and marine safety maintenance. In recent years, many methods based on deep neural networks (DNNs) have been used to improve the performance of SAR ship detection. These methods mainly focus on two issues: one is the false alarm of ship detection in complex inshore environments, and the other is the effective extraction and utilization of SAR ship features. The topic discussed in this article is one of the culprits that has caused the aforementioned two problems but has long been overlooked. Specifically, it pertains to the issue of intraclass imbalance in SAR ship detection. There are imbalances in the size distribution, azimuth distribution, and background distribution under the real data collection environment. However, since SAR ship detection is a single-class detection task, the aforementioned imbalances lack reliable descriptors during training. This article proposes using evidence learning to obtain the epistemic uncertainty as a descriptor of biased learning on samples. Contrastive learning is used to further utilize the uncertainty label of samples to correct biased learning under intraclass imbalance. The proposed method is proven to be effective on multiple network models. AP50 reaches 94.8% on the HRSID dataset, 98.4% on the SSDD dataset, and 80.9% on the LS-SSDD dataset, both achieving SOTA performance.
Numerical and graphical simulation of the non-linear fractional dynamical system of bone mineralization

The objective of the present study was to improve our understanding of the complex biological process of bone mineralization by performing mathematical modeling with the Caputo-Fabrizio fractional operator. To obtain a better understanding of Komarova's bone mineralization process, we have thoroughly examined the boundedness, existence, and uniqueness of solutions and stability analysis within this framework. To determine how model parameters affect the behavior of the system, sensitivity analysis was carried out. Furthermore, the fractional Adams-Bashforth method has been used to carry out numerical and graphical simulations. Our work is significant owing to its comparison of fractional- and integer-order models, which provides novel insight into the effectiveness of fractional operators in representing the complex dynamics of bone mineralization.
A Double-Slotted Microstrip Rectangular 6x6 Array for Sub-6 GHz Wireless Applications

- In this article, a double-slotted microstrip rectangular 6×6 MIMO array antenna is proposed with an intention for the sub-6 GHz smartphone and wireless applications. In this proposed design, the Partial Ground Plane (PGP) technique is applied to the Single-Element Antenna (SEA) design to achieve an Ultra-Wideband (UWB) response of 1.43GHz. The design works within 3.1 to 4.53 GHz of -10 dB S-parameter bandwidth (BW). The SEA has a small dimensions of only 40 × 30 mm² and a 0.508 mm thickness. Moreover, the 6-element array aligns with 6.6-inch display smartphones by having a final dimension of 75 × 150 mm². The MIMO performance parameters of this proposed design have a good isolation of below -16.6 dB between the ports. Furthermore, the maximum Realized Gain (RG) of 5.44 dBi, and a Total antenna Efficiency (TE) of as high as 80% are achieved by simulation and also validated through measurement. Likewise, the Envelope Correlation Coefficient (ECC) of this MIMO array stays consistently below 0.004 and has a Diversity Gain (DG) of more than 9.98 throughout the entire BW. Additionally, the Specific Absorption Rate (SAR) analysis with Hand-Head phantom reveals a remarkable result of as low as 0.094 W/kg for 10g mass at port 2, whereby the value never goes higher than 0.413 W/kg at any port that ensures compliance with MIMO standards for smartphone applications.
Inhibition of PRMT1 Suppresses the Growth of U87MG-Derived Glioblastoma Stem Cells by Blocking the STAT3 Signaling Pathway

Glioblastoma stem cells (GSCs) play a pivotal role in the initiation, progression, resistance to treatment, and relapse of glioblastoma multiforme (GBM). Thus, identifying potential therapeutic targets and drugs that interfere with the growth of GSCs may contribute to improved treatment outcomes for GBM. In this study, we first demonstrated the functional role of protein arginine methyltransferase 1 (PRMT1) in GSC growth. Furamidine, a PRMT1 inhibitor, effectively inhibited the proliferation and tumorsphere formation of U87MG-derived GSCs by inducing cell cycle arrest at the G0/G1 phase and promoting the intrinsic apoptotic pathway. Moreover, furamidine potently suppressed the in vivo tumor growth of U87MG GSCs in a chick embryo chorioallantoic membrane model. In particular, the inhibitory effect of furamidine on U87MG GSC growth was associated with the downregulation of signal transducer and activator of transcription 3 (STAT3) and key GSC markers, including CD133, Sox2, Oct4, Nanog, aldehyde dehydrogenase 1, and integrin α6. Our results also showed that the knockdown of PRMT1 by small interfering RNA significantly inhibited the proliferation of U87MG GSCs in vitro and in vivo through a molecular mechanism similar to furamidine. In addition, combined treatment with furamidine and berbamine, a calcium/calmodulin-dependent protein kinase II gamma (CaMKIIγ) inhibitor, inhibited the growth of U87MG GSCs more strongly than single-compound treatment. The increased antiproliferative effect of combining the two compounds resulted from a stronger downregulation of STAT3-mediated downstream GBM stemness regulators through dual PRMT1 and CaMKIIγ function blockade. In conclusion, these findings suggest that PRMT1 and its inhibitor, furamidine, are potential novel therapeutic targets and drug candidates for effectively suppressing GSC growth.
Histological and Molecular Assessment of Anti-inflammatory Effect of Different Concentrations of Hyaluronic Acid Injected in Inflamed Rabbit’s Tempromandibular Joint

Introduction: Several studies indicated that Hyaluronic acid (HA) has anti-inflammatory role through suppressing mediators of inflammation involved in the osteoarthritic disease state. Aim: Investigating the anti-inflammatory effect of different concentrations of hyaluronic acid on experimentally induced inflammatory changes in rabbits temporomandibular joint (TMJ). Material and Methods: Forty male rabbits were prepared and randomly divided into 5 groups each group formed of 8 rabbits as follow: Group (1): 8 animals injected with saline only served a negative control group. Group (2): 8 animals injected with formalin served as positive control. Group (3): 8 animals injected with 0.1ml of formalin once, followed by 2.5mg/0.5ml /week of HA for three weeks. Group (4): formed of 8 animals injected with 0.1ml of formalin once, followed by 5mg/0.5ml /week of HA for three weeks. Group (5): 8 animals injected with 0.1ml of formalin once, followed by 7.5mg/0.5ml /week of HA for three weeks. Eventually blood samples were collected and animals were euthanized. Evaluation in this study included measuring pro inflammatory markers IL-6, IL-1β and CRP by ELISA. Histological evaluation of TMJ tissues to detect changes in the muscles, ligaments, and bones. Results: all animals injected with HA showed a significant reduction in levels of IL-6, IL-1β and CRP in addition to improvement in tissue structure. Animals in G4 and G5 showed significantly better results than G3. Conclusion : there is a statistically significant anti-inflammatory effect of HA on TMJ at different concentrations.
Ramial wood amendments (Piliostigma reticulatum) mitigate degradation of tropical soils but do not replenish nutrient exports

Restoring degraded soils to support food production is a major challenge for West African smallholders who have developed local innovations to counter further degradation. The objective of this study was to evaluate a local farmer's technique that uses ramial wood (RW) as soil amendment (Piliostigma reticulatum shrub). Three treatments were applied in an experimental plot in Burkina Faso: control (no amendment), low RW (3 Mg fresh mass·ha−1·yr−1), and high RW (12 Mg fresh mass·ha−1·yr−1). RW was chipped to <5‐cm pieces and either buried or mulched. Topsoil carbon (C), nitrogen (N), and phosphorus (P) in control and low‐RW treatments declined after 7 years of continuous sorghum cultivation. Use of high‐RW amendment stabilized soil C content while N and P declined, thus not replenishing nutrient exports. Net contribution to soil C in the layer measuring 0–15 cm was 15% of the applied C in the high‐RW amendments. Although biomass and grain yields were higher in high‐RW treatments, crop productivity declined throughout the experiment for all treatments. Termite casts on RW treatments evidenced the potential role of wood‐foraging termites in diluting the impact of RW on soil fertility build‐up and soil water content. We conclude that mitigating soil degradation under semiarid conditions in Burkina Faso would require large amounts of woody amendments, particularly if the level of termite activity is high. Additional nutrient sources would be needed to compensate for removal in exported products so that biomass and grain production can be stabilized or increased.
New Evidence of an Ancient Martian Ocean From the Global Distribution of Valley Networks

We examine the connection between true polar wander (TPW) and the evidence for an ancient ocean on Mars. Previous studies have investigated the plausibility of a Mars ocean by examining the topography of possible ancient sea level markers on the planet's surface. One such study argued that features interpreted as ancient shorelines display long‐wavelength topographic variations consistent with postformational TPW (Perron et al., 2007, https://doi.org/10.1038/nature05873). In contrast, a second study argued that the elevations of possible ancient deltaic deposits associated with an ocean on early Mars are not consistent with the TPW scenario (di Achille & Hynek, 2010, https://doi.org/10.1038/ngeo891). Herein we revisit this issue by examining another marker of ancient shorelines—fluvial valley networks observed on the surface of Mars. Our results support the existence of an ancient Martian ocean and that long‐wavelength deformation of related surface features (ancient shorelines and valley networks) was driven by some combination of TPW and surface loading associated with the formation of the Tharsis volcanic province.
Respiratory Oscillometry and Functional Performance in Different COPD Phenotypes

Purpose Chronic obstructive pulmonary disease (COPD) phenotypes may introduce different characteristics that need to be known to improve treatment. Respiratory oscillometry provides a detailed analysis and may offer insight into the pathophysiology of COPD. In this paper, we used this method to evaluate the differences in respiratory mechanics of COPD phenotypes. Patients and Methods This study investigated a sample of 83 volunteers, being divided into control group (CG = 20), emphysema (n = 23), CB (n = 20) and asthma-COPD overlap syndrome (ACOS, n = 20). These analyses were performed before and after bronchodilator (BD) use. Functional capacity was evaluated using the Glittre‑ADL test, handgrip strength and respiratory pressures. Results Initially it was observed that oscillometry provided a detailed description of the COPD phenotypes, which was consistent with the involved pathophysiology. A correlation between oscillometry and functional capacity was observed (r=−0.541; p = 0.0001), particularly in the emphysema phenotype (r = −0.496, p = 0.031). BD response was different among the studied phenotypes. This resulted in an accurate discrimination of ACOS from CB [area under the receiver operating curve (AUC) = 0.84] and emphysema (AUC = 0.82). Conclusion These results offer evidence that oscillatory indices may enhance the comprehension and identification of COPD phenotypes, thereby potentially improving the support provided to these patients.