Miracle-dz/UniFAR-FTUs huggingface dataset:
Plasma Gut Microbe-Derived Metabolites Associated with Peripheral Artery Disease and Major Adverse Cardiac Events

Cardiovascular diseases are associated with gut dysbiosis, but the role of microbe-derived metabolites as biomarkers or modulators of cardiovascular disease are not well understood. This is a targeted metabolomics study to investigate the association of nine microbe-derived metabolites with lower extremity peripheral artery disease (PAD), a form of atherosclerosis, and major adverse cardiac events (MACE). The study cohort consists of individuals with intermittent claudication and ankle-brachial index (ABI) < 0.9 (N = 119) and controls without clinically-apparent atherosclerosis (N = 37). The primary endpoint was MACE, a composite endpoint of myocardial infarction, coronary revascularization, stroke, transient ischemic attack, or cardiac-related death. Plasma metabolite concentrations differed significantly between the PAD and control groups. After adjustment for traditional atherosclerosis risk factors, kynurenine, hippuric acid, indole-3-propionic acid (IPA), and indole-3-aldehyde (I3A) concentrations were negatively associated with PAD, whereas indoxyl sulfate and 3-hydroxyanthranilic acid were positively associated. Hippuric acid, IPA, and I3A correlated with ABI, a surrogate for atherosclerotic disease burden. Those in the highest I3A concentration quartile had significantly improved freedom from MACE during follow-up compared to those in the lowest quartile. This study identifies specific indole- and phenyl-derived species impacted by gut microbial metabolic pathways that could represent novel microbiome-related biomarkers of PAD.
Structural Evolution of Single-Walled Carbon Nanotubes: Molecular Dynamics Simulation

We investigate the structural evolution of the single-walled carbon nanotubes (SWNTs) by molecular dynamics (MD) simulation using the Gao-Weber potential. The structural evolution of SWNTs is analyzed through the total energy per atom, the radial distribution function, coordination number, bond angle and the distribution of ring statistics. The results show that the melting temperature of SWNTs occurs at around Tm=5620 K. This value is in good agreement with the result of Zhang and co-workers. The visualization indicates that the initially perfect SWNTs is broken resulting in the ring of various.
Spectropolarimetric Observations of Prominences and Spicules, and Magnetic Field Diagnostics

A large set of high precision full-Stokes spectropolarimetric observations of the He-D3 line in prominences and spicules have been performed with the ZIMPOL polarimeter at the Gregory-Coude Telescope in Locarno. The observational technique allows to obtain measurements free from seeing induced spurious effects. The instrumental polarization is well under control and taken into account in the data analysis. The observed Stokesprofiles are interpreted according to the quantum theory of the Hanle and Zeeman effects with the aim of obtaining information on the magnetic field vector. To this end, we make use of a suitable Stokes inversion strategy technique. The results are presented giving emphasis on a few particularly interesting Stokes-profiles. Finally we show some novel prominence observations in the Hα and Hβ hydrogen lines.
Solar total and spectral irradiance reconstruction over the last 9000 years

Context.Changes in solar irradiance and in its spectral distribution are among the main natural drivers of the climate on Earth. However, irradiance measurements are only available for less than four decades, while assessment of solar influence on Earth requires much longer records.Aims. The aim of this work is to provide the most up-to-date physics-based reconstruction of the solar total and spectral irradiance (TSI/SSI) over the last nine millennia.Methods. The concentrations of the cosmogenic isotopes14C and10Be in natural archives have been converted to decadally averaged sunspot numbers through a chain of physics-based models. TSI and SSI are reconstructed with an updated SATIRE model. Reconstructions are carried out for each isotope record separately, as well as for their composite.Results. We present the first ever SSI reconstruction over the last 9000 years from the individual14C and10Be records as well as from their newest composite. The reconstruction employs physics-based models to describe the involved processes at each step of the procedure.Conclusions. Irradiance reconstructions based on two different cosmogenic isotope records, those of14C and10Be, agree well with each other in their long-term trends despite their different geochemical paths in the atmosphere of Earth. Over the last 9000 years, the reconstructed secular variability in TSI is of the order of 0.11%, or 1.5 W m−2. After the Maunder minimum, the reconstruction from the cosmogenic isotopes is consistent with that from the direct sunspot number observation. Furthermore, over the nineteenth century, the agreement of irradiance reconstructions using isotope records with the reconstruction from the sunspot number by Chatzistergos et al. (2017, A&A, 602, A69) is better than that with the reconstruction from the WDC-SILSO series (Clette et al. 2014, Space Sci. Rev., 186, 35), with a lowerχ2-value.
ELCD: Efficient Lunar Crater Detection Based on Attention Mechanisms and Multiscale Feature Fusion Networks from Digital Elevation Models

The detection and counting of lunar impact craters are crucial for the selection of detector landing sites and the estimation of the age of the Moon. However, traditional crater detection methods are based on machine learning and image processing technologies. These are inefficient for situations with different distributions, overlaps, and crater sizes, and most of them mainly focus on the accuracy of detection and ignore the efficiency. In this paper, we propose an efficient lunar crater detection (ELCD) algorithm based on a novel crater edge segmentation network (AFNet) to detect lunar craters from digital elevation model (DEM) data. First, in AFNet, a lightweight attention mechanism module is introduced to enhance the feature extract capabilities of networks, and a new multiscale feature fusion module is designed by fusing different multi-level feature maps to reduce the information loss of the output map. Then, considering the imbalance in the classification and the distributions of the crater data, an efficient crater edge segmentation loss function (CESL) is designed to improve the network optimization performance. Lastly, the crater positions are obtained from the network output map by the crater edge extraction (CEA) algorithm. The experiment was conducted on the PyTorch platform using two lunar crater catalogs to evaluate the ELCD. The experimental results show that ELCD has a superior detection accuracy and inference speed compared with other state-of-the-art crater detection algorithms. As with most crater detection models that use DEM data, some small craters may be considered to be noise that cannot be detected. The proposed algorithm can be used to improve the accuracy and speed of deep space probes in detecting candidate landing sites, and the discovery of new craters can increase the size of the original data set.
Antioxidant attributes of tea in North Bengal, India: Relation with its principal constituents and properties of soil

This study was performed in 18 tea gardens in North Bengal, India, from 2012 to 2017. The data were pooled to investigate the relationship with soil physico-chemical properties, phyto-constituents, antioxidant attributes and age of the tea bushes and principal component analysis (PCA). PCA and dendro-hit maps were also performed with each region. The 28 principal components were chosen based on their eigen values, explaining the total data variance for tea in Dooars, Terai and Darjeeling hill. In almost all cases, composite soil physico-chemical attributes were heavily loaded on the second principal component and clustered, as visual evidenced by the dendro-hit map. Different attributes were significantly correlated each other in case of Terai i.e. (value of “r’’ at P<0.01 level) clay fraction (0.778), electrical conductivity (0.618), N (0.777), S (0.748), P (0.514 ppm), flavour index (0.918), total polyphenol (0.687) DPPH (0.794), nitric oxide (0.913), anti-lipid peroxidation (0.717) and metal chelating (0.665). In Dooars region, attributes were significantly correlated with silt (0.718), pH (0.875), P (0.615 ), chloride (0.858), TP (0.776), flavonol (0.923), quinone (0.666), tannins (0.865), DPPH (0.536), superoxide (0.576), ABTS (0.520) and MC (0.777) and in the case of Darjeeling hills, attributes were highly correlated with clay (0.812), sand (0.818), silt fraction (0.974), K (0.932), S (0.999), MC of soil (0.671), TP (0.853), tannins (0.912), DPPH (0.624), ABTS (0.661) and MC (0.633) repectively.
Some Predictors of University Students’ Subjective Well-Being in Croatia During The COVID-19 Pandemic

Introduction: Changes caused by the COVID-19 pandemic significantly altered the functioning of different social systems, including the educational one. Closing educational institutions and transferring the educational process to online platforms posed new challenges for students’ academic functioning and well-being in these unexpected circumstances. Aims: This study aimed to explore the role of university students’ academic functioning and personality in predicting their subjective well-being during the online studying implemented in Croatia due to the pandemic caused by the coronavirus. Methods: A sample of 505 university students from different Croatian faculties participated in the online survey, which included their ratings of adjustment to the online learning environment, related difficulties in learning and self-regulation, perception of the online education’s quality, the level of life disruption caused by the pandemic, personality traits, and subjective well-being measures (life satisfaction, positive affect, and negative affect). Results: Results generally revealed that certain aspects of students’ academic functioning during online studying as well as their personality explained a significant proportion of the subjective well-being measures’ variance. Also, the perceived level of life disruption caused by the pandemic and neuroticism were the strongest predictors of students’ subjective well-being, followed by extraversion and conscientiousness. Conclusions: Obtained results indicate that some aspects of academic functioning upon the transition to online studying could contribute to students’ subjective well-being and should be considered when planning interventions to increase their well-being and enhance the quality of the online learning environment in these challenging times.
On the geometry of affine Kähler immersions

In this paper we extend the work on affine immersions [N-Pi]-1 to the case of affine immersions between complex manifolds and lay the foundation for the geometry of affine Kähler immersions. The notion of affine Kähler immersion extends that of a holomorphic and isometric immersion between Kähler manifolds and can be contrasted to the notion of holomorphic affine immersion which has been established in the work of Dillen, Vrancken and Verstraelen [D-V-V] and that of Abe [A].
Actively Controllable Terahertz Metal–Graphene Metamaterial Based on Electromagnetically Induced Transparency Effect

A metal–graphene metamaterial device exhibiting a tunable, electromagnetically induced transparency (EIT) spectral response at terahertz frequencies is investigated. The metamaterial structure is composed of a strip and a ring resonator, which serve as the bright and dark mode to induce the EIT effect. By employing the variable conductivity of graphene to dampen the dark resonator, the response frequency of the device shifts dynamically over 100 GHz, which satisfies the convenient post-fabrication tunability requirement. The slow-light behavior of the proposed device is also analyzed with the maximum group delay of 1.2 ps. The sensing performance is lastly studied and the sensitivity can reach up to 100 GHz/(RIU), with a figure of merit (FOM) value exceeding 4 RIU−1. Therefore, the graphene-based metamaterial provides a new miniaturized platform to facilitate the development of terahertz modulators, sensors, and slow-light applications.
THE USE OF SMARTPHONE APPLICATIONS IN LEARNING ENGLISH VOCABULARY OF FIRST-YEAR STUDENTS AT VNU INTERNATIONAL SCHOOL

This research focuses on the use of smartphone applications in learning English vocabulary of over 400 first-year students of elementary level at International School - Vietnam National University, Hanoi (VNU-IS). It helps to clarify what aspects students should know when learning a new word and aims to find out what criteria these students take into consideration when choosing smartphone applications to learn English vocabulary, which smartphone applications are most frequently used by them and how they evaluate the effectiveness of these smartphone applications in learning English vocabulary. From the data collected and the findings, some conclusions are made relating to the use of smartphone applications in English vocabulary learning of first-year elementary students at VNU-IS.
Rare and declining bee species are key to consistent pollination of wildflowers and crops across large spatial scales.

Biodiversity promotes ecosystem function in experiments, but it remains uncertain how biodiversity loss affects function in larger-scale natural ecosystems. In these natural ecosystems, rare and declining species are more likely to be lost, and function needs to be maintained across space and time. Here we explore the importance of rare and declining bee species to the pollination of three wildflowers and three crops using large-scale (72 sites across 5,000 km2 ), multi-year datasets. Half of the sampled bee species (82/164) were rare or declining, but these species provided only ~15% of overall pollination. To determine the number of species important to ecosystem function, we used two methods of 'scaling up', both of which have previously been used for biodiversity-function analysis. First, we summed bee species' contributions to pollination across space and time and then found the minimum set of species needed to provide a threshold level of function across all sites; according to this method, effectively no rare and declining bee species were important to pollination. Second, we account for the "insurance value" of biodiversity by finding the minimum set of bee species needed to simultaneously provide a threshold level of function at each site in each year. The second method leads to the conclusion that 25 rare and eight declining bee species (36% and 53% of all rare and declining bee species, respectively) are included in the minimum set. Our findings provide some of the strongest evidence yet that rare and declining species are key to meeting threshold levels of ecosystem function, thereby providing a more direct link between real-world biodiversity loss and ecosystem function. This article is protected by copyright. All rights reserved.
FROM CRIME SCENE TO COURT. From Crime Scene to Court: How Should Future Research Address the Current Limitations in Forensic Entomology?

: Over the last 50 years, there has been a dramatic increase in the amount of research being conducted in forensic entomology. Given the gravity of the consequences of court decisions, it is essential to assess how research in forensic entomology supports its practical application in criminal investigations and in court. In this study, we employed a questionnaire-based approach, gathering information from professionals from across the world involved in the collection and preparation of forensic entomological evidence, as well as those who present and utilize such evidence in court. This was supported by a bibliometric approach that examined research publication and collaboration patterns. The questionnaire survey indicated that forensic entomology is predominantly utilized to determine minimum post-mortem intervals. While entomologists are generally confident in their ability to collect, preserve, store, identify and interpret entomological evidence, several weaknesses in the application and use of forensic entomology were identified. Additionally, the bibliometric study revealed extensive research clustering within countries, with relatively little cross-country collaboration. This may result in inhibited flow of research findings, which is likely exacerbated by the small number of appropriate open-access journals. The vast array of factors that may affect insect behavior, development, community structure, and dynamics, as well as sampling reliability, make forensic entomology particularly challenging. Therefore, standardization of procedures, validation of methodologies, and accreditation frameworks will be critical for maximizing the utility of practical forensic entomology. Research must underpin the future development of forensic entomology, but it will be most effective with greater collaboration between research teams and researchers and practitioners. The global research community will need to be more coordinated and standardized to achieve its potential in supporting practical applications inside and outside of the court, thereby maximizing the societal value of forensic entomology.
Formation of a protocluster: A virialized structure from gravoturbulent collapse - II. A two-dimensional analytical model for a rotating and accreting system

Context. Most stars are born in the gaseous protocluster environment where the gas is reprocessed after the global collapse from the diffuse molecular cloud. The knowledge of this intermediate step gives more accurate constraints on star formation characteristics. Aims. We demonstrate that a virialized globally supported structure, in which star formation happens, is formed out of a collapsing molecular cloud, and we derive a mapping from the parent cloud parameters to the protocluster to predict its properties with a view to confront analytical calculations with observations and simulations. Methods. We decomposed the virial theorem into two dimensions to account for the rotation and the flattened geometry. Equilibrium was found by balancing rotation, turbulence, and self-gravity, while turbulence was maintained through accretion driving and it dissipates in one crossing time. We estimated the angular momentum and the accretion rate of the protocluster from the parent cloud properties. Results. The two-dimensional virial model predicts the size and velocity dispersion given the mass of the protocluster and that of the parent cloud. The gaseous protoclusters lie on a sequence of equilibrium with the trend R ~ M 0.5 with limited variations, depending on the evolutionary stage, parent cloud, and parameters that are not well known, such as turbulence driving efficiency by accretion and turbulence anisotropy. The model reproduces observations and simulation results successfully. Conclusions. The properties of protoclusters follow universal relations and they can be derived from that of the parent cloud. The gaseous protocluster is an important primary stage of stellar cluster formation, and should be taken into account when studying star formation. Using simple estimates to infer the peak position of the core mass function (CMF) we find a weak dependence on the cluster mass, suggesting that the physical conditions inside protoclusters may contribute to set a CMF, and by extension an initial mass function (IMF), that appears to be independent of the environment.
Towards approximately optimal assessments — A tractable methodology

An important challenge in education is estimating whether an individual has attained competency based on multiple aspects simultaneously, e.g., response accuracy and response time data. It is not trivial to obtain reliable estimates with few samples and provide decisions in an online and personalized manner. We propose an approach to solve that problem. The approach is grounded in stochastic control theory combined with the statistical power of Reinforcement Learning (RL) and machine learning. It leads to the development of an offline RL method that can efficiently leverage student data sequences of accuracy and response time. We develop a novel method that combines three components: (1) the learner model combines the data in a reward function effectively and efficiently; (2) a reinforcement learning-based prediction technique estimates the parameters of the model, and (3) a machine learning model generalizes the quality of decisions to sequential problems. We provide support that our methodology has a merit enabling robust, computationally efficient and tractable planning of personalized competency assessments.
Formal Proof of the Fundamental Theorem of Decorated Interval Arithmetic

Interval arithmetic is used to enclose roundoff, truncation, and modeling errors in interval methods, thus obtaining numerical methods with automatic verification of the results. The Fundamental Theorem of Interval Arithmetic (FTIA) shows that, when evaluating an expression using interval arithmetic, the computed result contains the mathematically correct value of the expression. Decorations were introduced in the IEEE P1788 working group for standardizing interval arithmetic. Their role is to help track properties of interval evaluations. That is, we wish to say if a function is defined, undefined, or continuous in its inputs. Moreover, decorations act as local exception flags and do not lead to interruption of the computations. The FTIA plus the decoration system is expanded into the Fundamental Theorem of Decorated Interval Arithmetic (FTDIA). Several versions of this theorem are formulated and proved by J. Pryce. This thesis formalizes and proves the core of this theorem (version 3.0 of the IEEE-P1788 proposal) using the theorem prover Coq. Namely, we prove it for the common case where all the inputs to a function are non-empty intervals. There are two distinctive features of our formalization and proof. First, we define the semantics of an interval as a set of real numbers (including the empty set), and we do not impose any other restrictions on such a set, except that models of this interval can decide if the set is empty or not. For example, an interval need not be closed and
China’s Bilateral Currency Swap in International Trade Clearance: An Empirical Investigation

The emerging economic prosperity of China and its increasing economic integration with the rest of the world as the second largest economy seems to give her an edge to amplify its global competitiveness. An important avenue for this ongoing debate relates to the diversification of the international monetary system. In effect, the development reveals a pertinent reason to expect that the world‟s currency regime and global financial architecture is changing. Evidently, the currency bilateral swap agreement signed by the People‟s Bank of China and some central banks is reinforcing the trend of Renminbi internationalization. The paper applies gravity model to investigate China‟s Renminbi bilateral swap agreements (BSAs) and trade flows. Lie beside the fore mentioned objective; we empirically investigate the decision of countries to engage in currency swapping through China‟ s RMB swap route, using large panel data of over 200 countries from 1979 - 2013 for the first time to the best our knowledge. The empirical results show that currency swap as an emerging trade-type of international agreement is trade creating with a magnitude relatively close to what is documented in the literature for other kinds of trade agreements like the currency unions and free trade agreements, this may potentially provide bilateral trade preference for countries that embrace China‟s currency swap li ne.