Miracle-dz/UniFAR-FTUs huggingface dataset:
Variations of the Electron Fluxes in the Terrestrial Radiation Belts Due To the Impact of Corotating Interaction Regions and Interplanetary Coronal Mass Ejections

In this paper, we study the variations of the radiation belts electron fluxes induced by the interaction of two types of solar wind structures with the Earth magnetosphere: the corotating interaction regions and the interplanetary coronal mass ejections. We use a statistical method based on the comparison of the preevent and postevent fluxes. Applied to the National Oceanic and Atmospheric Administration‐Polar Operational Environmental Satellites data, this gives us the opportunity to extend previous studies focused on relativistic electrons at geosynchronous orbit. We enlighten how corotating interaction regions and Interplanetary Coronal Mass Ejections can impact differently the electron belts depending on the energy and the L shell. In addition, we provide a new insight concerning these variations by considering their amplitude. Finally, we show strong relations between the intensity of the magnetic storms related to the events and the variation of the flux. These relations concern both the capacity of the events to increase the flux and the deepness of these increases.
Butterflies of the Kole Wetlands, a Ramsar Site in Kerala, India

A study was conducted to understand the diversity and abundance of butterflies of Kole Wetlands. Fifty-eight species in five families were identified. The relative abundance and seasonal variation in the abundance across the year have been discussed. The endemism as well as the butterflies listed in the schedules of the Wildlife (Protection) Act, 1972 have also been discussed.
Metabolic syndrome traits exhibit genotype-by-environment interaction in relation to socioeconomic status in the Mexican American family heart study

Background: Socioeconomic Status (SES) is a potent environmental determinant of health. To our knowledge, no assessment of genotype-environment interaction has been conducted to consider the joint effects of socioeconomic status and genetics on risk for metabolic disease. We analyzed data from the Mexican American Family Studies (MAFS) to evaluate the hypothesis that genotype-by-environment interaction (GxE) is an essential determinant of variation in risk factors for metabolic syndrome (MS). Methods: We employed a maximum likelihood estimation of the decomposition of variance components to detect GxE interaction. After excluding individuals with diabetes and individuals on medication for diabetes, hypertension, or dyslipidemia, we analyzed 12 MS risk factors: fasting glucose (FG), fasting insulin (FI), 2-h glucose (2G), 2-h insulin (2I), body mass index (BMI), waist circumference (WC), leptin (LP), high-density lipoprotein-cholesterol (HDL-C), triglycerides (TG), total serum cholesterol (TSC), systolic blood pressure (SBP), and diastolic blood pressure (DBP). Our SES variable used a combined score of Duncan’s socioeconomic index and education years. Heterogeneity in the additive genetic variance across the SES continuum and a departure from unity in the genetic correlation coefficient were taken as evidence of GxE interaction. Hypothesis tests were conducted using standard likelihood ratio tests. Results: We found evidence of GxE for fasting glucose, 2-h glucose, 2-h insulin, BMI, and triglycerides. The genetic effects underlying the insulin/glucose metabolism component of MS are upregulated at the lower end of the SES spectrum. We also determined that the household variance for systolic blood pressure decreased with increasing SES. Conclusion: These results show a significant change in the GxE interaction underlying the major components of MS in response to changes in socioeconomic status. Further mRNA sequencing studies will identify genes and canonical gene pathways to support our molecular-level hypotheses.
Back to (a different) emigration? Mobility from Spain and Italy during the economic crisis

The economic crisis has had a very severe impact on the economic situation of both Spain and Italy, whose employment figures fell by record levels, affecting all population categories, especially the youngest cohorts. This situation had a profound impact on the dynamics of migration in these two (traditionally emigrant-sending turned emigrant-receiving) countries, with a rising of emigration in the face of decreasing immigration. The main goal of this study is to compare Spanish and Italian emigration mechanisms through secondary sources. We lean toward the hypothesis that both countries, Spain and Italy, could have changed their migration patterns due to the economic crisis. For this purpose, we undertake a cross-national comparative analysis of stock and flow data on emigrations during the economic downturn (2009-2015).
Spatial Distribution and Sustainable Development of Living Woody and Coarse Woody Debris in Warm-Temperate Deciduous Broadleaved Secondary Forests in China

The investigation into the spatial patterns of living woody (LWD) and coarse woody debris (CWD) in warm-temperate deciduous broadleaved secondary forests serves as a foundational exploration of the mechanisms governing coexistence and mortality in forest ecosystems. The complete spatial randomness null model (CSR) was employed to analyze spatial distribution patterns, with the independent component null model (IC) and canonical correspondence analysis (CCA) utilized to elucidate spatial correlations and topographic influences. All three models were applied to LWD and CWD across various size classes within a 20-hectare plot in the Dongling Mountains. The study’s findings indicate that both LWD and CWD predominantly exhibited aggregated patterns, transitioning to a random distribution as the size class increased. Both increasing abundance and maximum diameter at breast height (DBH) also have a significant influence on the distribution of species. Notably, rare species exhibited higher aggregation compared to common and abundant species. The spatial correlation results between LWD and CWD across various size classes predominantly showed positive correlations and uncorrelated patterns within the sampled plots. CCA analysis further revealed that elevation, convexity, slope, and aspect significantly influenced the spatial patterns of LWD and CWD across different size classes. Within the sample site, trees display a tendency to grow and die in clusters. Biotic factors have a more significant influence on species distribution than abiotic factors.
Future climate change of stability indices for the Iberian Peninsula

Stability indices evaluate the atmospheric instability which is a basic and precursor ingredient needed for storms to develop. In this study, we evaluated changes of some atmospheric stability indices, namely Convective Available Potential Energy (CAPE), Deep‐Layer Wind Shear (SHR06) and Severe Weather Threat (SWEAT), for the Iberian Peninsula, for a future climate scenario (2081–2100), considering the greenhouse gases emission scenario RCP8.5, relative to a historical period (1986–2005). The Weather Research and Forecasting (WRF) was forced by ERA‐Interim, for validation purposes, and by the Max Planck Institute (MPI) Earth System Model. The novelty of this approach is the study of extreme weather events through the evaluation of conditions favourable to their development instead of directly studying them. The latter approach may be problematic since these phenomena are known to be poorly reproduced by models due to their relatively low resolution and parametrization processes such as clouds and precipitation. Our approach uses stability indices obtained from simulated variables, such as temperature and winds, which are, generally, much better simulated by models. The WRF‐MPI model was validated against WRF‐ERA. Overall, the WRF‐MPI simulates well the three indices considered here, particularly CAPE, when compared to WRF‐ERA. Their spatial patterns were similar, although there is a systematic positive bias in the WRF‐MPI. This is minimized when we evaluate climate change by computing differences of WRF‐MPI simulations between the future climate scenario and the historical period.
Family support, need for achievement, and entrepreneurial orientation on entrepreneurial intentions in vulnerable groups

This study aims to design and test the goodness of fit of a theoretical model that describes the effect of family support, need for achievement, and entrepreneurial orientation on entrepreneurial intentions with empirical data in the field. Research participation used subjects totaling 66 people from Ngalang village who were female, did not have permanent jobs, and were included in the poor category. Data collection uses four measurement scales: the entrepreneurial intention scale, family support scale, need for achievement scale, and entrepreneurial orientation scale, and is analyzed using partial least square (PLS) via smartPLS 3.0. The results of the study show the formation of a theoretical model of the influence of family support, need for achievement, and entrepreneurial orientation on entrepreneurial intentions that fit with empirical data. Family support has a positive and very significant effect on entrepreneurial intentions, the need for achievement does not affect an entrepreneurial orientation, and entrepreneurial orientation has a positive and very significant impact on entrepreneurial intentions. This research implies that this model can be used as a reference and applied to overcoming economic problems in vulnerable groups.
Atypical clinical variants of Alzheimer’s disease: are they really atypical?

Alzheimer’s disease (AD) is a neuropathological disorder defined by the deposition of the proteins, tau and β-amyloid. Alzheimer’s disease is commonly thought of as a disease of the elderly that is associated with episodic memory loss. However, the very first patient described with AD was in her 50’s with impairments in multiple cognitive domains. It is now clear that AD can present with multiple different non-amnestic clinical variants which have been labeled as atypical variants of AD. Instead of these variants of AD being considered “atypical,” I propose that they provide an excellent disease model of AD and reflect the true clinical heterogeneity of AD. The atypical variants of AD usually have a relatively young age at onset, and they show striking cortical tau deposition on molecular PET imaging which relates strongly with patterns of neurodegeneration and clinical outcomes. In contrast, elderly patients with AD show less tau deposition on PET, and neuroimaging and clinical outcomes are confounded by other age-related pathologies, including TDP-43 and vascular pathology. There is also considerable clinical and anatomical heterogeneity across atypical and young-onset amnestic variants of AD which reflects the fact that AD is a disease that causes impairments in multiple cognitive domains. Future studies should focus on careful characterization of cognitive impairment in AD and consider the full clinical spectrum of AD, including atypical AD, in the design of research studies investigating disease mechanisms in AD and clinical treatment trials, particularly with therapeutics targeting tau.
A Deep Long-Term Joint Temporal–Spectral Network for Spectrum Prediction

Spectrum prediction is a promising technique to release spectrum resources and plays an essential role in cognitive radio networks and spectrum situation generating. Traditional algorithms normally focus on one-dimensional or predict spectrum values in a slot-by-slot manner and thus cannot fully perceive the spectrum states in complex environments and lack timeliness. In this paper, a deep learning-based prediction method with a simple structure is developed for temporal–spectral and multi-slot spectrum prediction simultaneously. Specifically, we first analyze and construct spectrum data suitable for the model to simultaneously achieve long-term and multi-dimensional spectrum prediction. Then, a hierarchical spectrum prediction system is developed that takes advantage of the advanced Bi-ConvLSTM and the seq2seq framework. The Bi-ConvLSTM captures time–frequency characteristics of spectrum data, and the seq2seq framework is used for long-term spectrum prediction. Furthermore, the attention mechanism is used to address the limitations of the seq2seq framework that compresses all inputs into fixed-length vectors, resulting in information loss. Finally, the experimental results have shown that the proposed model has a significant advantage over the benchmark schemes. Especially, the proposed spectrum prediction model achieves 6.15%, 0.7749, 1.0978, and 0.9628 in MAPE, MAE, RMSE, and R2, respectively, which is better than all the baseline deep learning models.
Biological Effects of Orthodontic Tooth Movement on the Periodontium in Regenerated Bone Defects: A Scoping Review

The aim of this scoping review is to analyse the biological effects of the orthodontic tooth movement (OTM) in areas with bone defects that are undergoing regeneration using different types of regenerative materials and techniques. The electronic research was performed on four databases as follows: PubMed, Scopus, EMBASE, and Web of Science. Data were extracted according to publication information, study design, sample characteristics, parameters of OTM, biological repercussions on the periodontium complex, methods of analysis, and conclusions. A total of thirty studies were included in the final review. In twenty-two studies, the most widely adopted grafting materials were alloplastics. In most studies, the orthodontic force used was 10 or 100 g, and the timing of application ranged from immediate to 6 months after grafting surgery. Twenty-four studies showed an increase in osteogenesis; in five studies, the clinical attachment level (CAL) increased; in five others, the probing pocket depth (PPD) decreased; in sixteen studies, there was root resorption of a different magnitude. Though the effects of OTM on the periodontium in the grafted areas were positive, the outcomes should be interpreted with caution as future preclinical and clinical studies are needed to extrapolate more valid conclusions.
Exploring the Prospective Role of Propolis in Modifying Aging Hallmarks

Aging populations worldwide are placing age-related diseases at the forefront of the research agenda. The therapeutic potential of natural substances, especially propolis and its components, has led to these products being promising agents for alleviating several cellular and molecular-level changes associated with age-related diseases. With this in mind, scientists have introduced a contextual framework to guide future aging research, called the hallmarks of aging. This framework encompasses various mechanisms including genomic instability, epigenetic changes, mitochondrial dysfunction, inflammation, impaired nutrient sensing, and altered intercellular communication. Propolis, with its rich array of bioactive compounds, functions as a potent functional food, modulating metabolism, gut microbiota, inflammation, and immune response, offering significant health benefits. Studies emphasize propolis’ properties, such as antitumor, cardioprotective, and neuroprotective effects, as well as its ability to mitigate inflammation, oxidative stress, DNA damage, and pathogenic gut bacteria growth. This article underscores current scientific evidence supporting propolis’ role in controlling molecular and cellular characteristics linked to aging and its hallmarks, hypothesizing its potential in geroscience research. The aim is to discover novel therapeutic strategies to improve health and quality of life in older individuals, addressing existing deficits and perspectives in this research area.
DATA-DRIVEN SIMULATIONS OF WILDFIRE SPREAD AT REGIONAL SCALES

Title of dissertation: DATA-DRIVEN SIMULATIONS OF WILDFIRE SPREAD AT REGIONAL SCALES Cong Zhang Doctor of Philosophy, 2018 Dissertation directed by: Professor Arnaud Trouvé Department of Mechanical Engineering Current wildfire spread simulators lack the ability to provide accurate prediction of the active flame burning areas at regional scales due to two main challenges: a modeling challenge associated with providing accurate mathematical representations of the multi-physics multi-scale processes that induce the fire dynamics, and a data challenge associated with providing accurate estimates of the initial fire position and the physical parameters that are required by the fire spread models. A promising approach to overcome these limitations is data assimilation: data assimilation aims at integrating available observations into the fire spread simulator, while accounting for their respective uncertainties, in order to infer a more accurate estimate of the fire front position and to produce a more reliable forecast of the wildfire behavior. The main objective of the present study is to design and evaluate suitable algorithms for regional-scale wildfire spread simulations, which are able to properly handle the variations in wildfire spread due to the significant spatial heterogeneity in the model inputs and to the temporal changes in the wildfire behavior. First we developed a grid-based spatialized parameter estimation approach where the estimation targets are the spatially-varying input model parameters. Then we proposed an efficient and robust method to compute the discrepancy between the observed and simulated fire fronts, which is based on a front shape similarity measure inspired from image processing theory. The new method is demonstrated in the context of Luenberger observer-based state estimation strategy. Finally we developed a dual state-parameter estimation method where we estimate both model state and model parameters simultaneously in order to retrieve more accurate physical values of model parameters and achieve a better forecast performance in terms of fire front positions. All these efforts aim at designing algorithmic solutions to overcome the difficulties associated with spatially-varying environmental conditions and potentially complex fireline shapes and topologies. It paves the way towards real-time monitoring and forecasting of wildfire dynamics at regional scales. DATA-DRIVEN SIMULATIONS OF WILDFIRE SPREAD AT REGIONAL SCALES
Morphological variability and cluster analysis of 16 bambara groundnut (Vigna subterranea) genotypes

Abstract. Hamdi MFFA, Ilyas S, Qadir A, Mayes S. 2024. Morphological variability and cluster analysis of 16 bambara groundnut (Vigna subterranea) genotypes. Biodiversitas 25: 97-106. Identifying morphological and germination characters in bambara groundnut (Vigna subterranea (L.) Verdc. ) is important to determine the advantages and disadvantages of several genotypes. This study aimed to identify the characteristics of 16 bambara groundnut genotypes based on morphological markers, NDVI score, and germination variables. This study was conducted in Sumedang, West Java, Indonesia in March-July 2018. The experiment was arranged in a randomized complete block design with one factor: genotype, which consisted of 16 genotypes originating from Indonesia and Africa. The NDVI score did not affect the yield produced. Tiga Nicuru, DodR-R II, M-14 Gresik, Black Sukabumi, and Black Madura were the genotypes with the highest germination speed, while LunT was the lowest. Cluster analysis showed that bambara groundnut genotypes are classified into 4 clusters. The first cluster belongs to Sumedang and Sukabumi, the second belongs to Gresik, Madura, and Tasikmalaya, the third comes from West Africa (LunT and Tiga Nicuru), and the fourth comes from East Africa (IITA 686 and DodR-R II) and Southern Africa (S 19-3, Uniswa R and Uniswa R/G). The low similarity (28%) between genotypes from Indonesia and Africa shows that there are many differences in morphological characteristics. This high diversity is beneficial for creating superior cultivars.
Correlation Analysis of Pulmonary Vein Anatomy and Paroxysmal Atrial Fibrillation Recurrence after Cryoballoon Ablation

Background: Cryoballoon ablation (CBA) is a reliable therapy for paroxysmal atrial fibrillation (pAF). However, the relatively high recurrence rate poses a perplexing challenge for clinicians; thus, a more detailed understanding of the pulmonary vein anatomy and the left atrial (LA)-pulmonary vein (PV) conjunction mode is needed. This study aimed to explore the correlation between the PV anatomy and pAF recurrence in patients who underwent the index CBA. Methods: We included 274 consecutive pAF patients (men: 60%, mean age: 58.8 ± 11.5 years, median AF history: 25 (8, 63) months) with pAF who underwent their first cryoballoon ablation between October 2019 and March 2022. All data were collected from the patient’s medical records. Subsequent post-procedural long-term follow-up and statistical analysis were conducted. Results: Amongst the total patients, 220 (80%) remained AF-free. Multivariate analysis showed that the right inferior PV (RIPV) vertical angle (hazard ratio (HR): 1.097, 95% CI: 1.071–1.124, p < 0.001) and PV variation (HR: 1.905, 95% CI: 1.079–3.362, p = 0.026) correlated with postoperative AF recurrence. The study investigated the effectiveness of the RIPV vertical angle, either alone or in combination with other recognized factors. Conclusions: In patients with pAF who underwent the index CBA, the RIPV vertical angle and PV variation served as reliable prognostic predictors. Specifically, the RIPV vertical angle, either alone or in combination with recognized factors, demonstrated effective predictive performance.
The petrology, geochemistry and structure of the plutonic rocks of the Oman ophiolite

The Oman Ophiolite represents a fragment of oceanic crust and upper mantle that was emplaced onto the Arabian continental margin during the late Cretaceous. An area of 3000km2, comprising the Haylayn and Rustaq Blocks, has been mapped and specific localities were investigated in order to examine the petrological and structural processes that operate during and subsequent to the formation of oceanic lithosphere at a spreading axis. Four successive plutonic suites have been recognized : (i) the Mantle Sequence, Cumulate Sequence and High Level Intrusives that form the lower part of the classic Penrose ophiolite stratigraphy, which has been intruded by three Later Plutonic Suites, (ii) the Late Trondhjemite-Gabbro Complexes, (iii) the Late Peridotite-Gabbro Complexes, and (iv) the Late Biotite Granites. The tectonite harzburgite of the Mantle Sequence represents the residuum formed during 177. partial melting of upward flowing fertile spinet lherzolite mantle at pressures of 20kB or more. The primary magmas generated (tholeiitic picrites, minimum MgO 14%) supplied a sub-oceanic spreading ridge magma chamber in which formed the layered mafic and ultramafic rocks of the Cumulate Sequence and the isotropic gabbros, diorites and trondhjemites of the High Level Intrusives. Structures and petrofabrics developed in the Mantle Sequence preserve lines and planes of mantle flow beneath the oceanic crust. Layering in the Cumulate Sequence formed in situ within a long-lived, dynamic, compositionally stratified, open system magma chamber. The Later Plutonic Suites record the post-spreading igneous history of the Oman Ophiolite. The Late Trondhjemite-Gabbro Complexes and the Late Peridotite-Gabbro Complexes reflect incipient arc formation and subsequent arc-rifting on and in young oceanic crust. The Late Biotite Granites are considered to be syn-emplacement plutons derived from the underthrust Arabian continental margin. A back-arc (marginal) basin rather than a major ocean basin is considered to be the likely tectonic setting in which these successive magmatic episodes occurred.