Miracle-dz/UniFAR-FTUs huggingface dataset:
Probing ultra-light axion dark matter from 21 cm tomography using Convolutional Neural Networks

We present forecasts on the detectability of Ultra-light axion-like particles (ULAP) from future 21 cm radio observations around the epoch of reionization (EoR). We show that the axion as the dominant dark matter component has a significant impact on the reionization history due to the suppression of small scale density perturbations in the early universe. This behavior depends strongly on the mass of the axion particle. Using numerical simulations of the brightness temperature field of neutral hydrogen over a large redshift range, we construct a suite of training data. This data is used to train a convolutional neural network that can build a connection between the spatial structures of the brightness temperature field and the input axion mass directly. We construct mock observations of the future Square Kilometer Array survey, SKA1-Low, and find that even in the presence of realistic noise and resolution constraints, the network is still able to predict the input axion mass. We find that the axion mass can be recovered over a wide mass range with a precision of approximately 20%, and as the whole DM contribution, the axion can be detected using SKA1-Low at 68% if the axion mass is M X < 1.86 × 10-20 eV although this can decrease to M X < 5.25 × 10-21 eV if we relax our assumptions on the astrophysical modeling by treating those astrophysical parameters as nuisance parameters.
The Generalized Gamma Distribution as a Useful RND Under Heston’s Stochastic Volatility Model

Following Boukai (2021) we present the Generalized Gamma (GG) distribution as a possible RND for modeling European options prices under Heston's (1993) stochastic volatility (SV) model. This distribution is seen as especially useful in situations in which the spot's price follows a negatively skewed distribution and hence, Black-Scholes based (i.e. the log-normal distribution) modeling is largely inapt. We apply the GG distribution as RND to modeling current market option data on three large market-index ETFs, namely the SPY, IWM and QQQ as well as on the TLT (an ETF that tracks an index of long term US Treasury bonds). The current option chain of each of the three market-index ETFs shows of a pronounced skew of their volatility `smile' which indicates a likely distortion in the Black-Scholes modeling of such option data. Reflective of entirely different market expectations, this distortion appears not to exist in the TLT option data. We provide a thorough modeling of the available option data we have on each ETF (with the October 15, 2021 expiration) based on the GG distribution and compared it to the option pricing and RND modeling obtained directly from a well-calibrated Heston's (1993) SV model (both theoretically and empirically, using Monte-Carlo simulations of the spot's price). All three market-index ETFs exhibit negatively skewed distributions which are well-matched with those derived under the GG distribution as RND. The inadequacy of the Black-Scholes modeling in such instances which involve negatively skewed distribution is further illustrated by its impact on the hedging factor, delta, and the immediate implications to the retail trader. In contrast, for the TLT ETF, which exhibits no such distortion to the volatility `smile', the three pricing models (i.e. Heston's, Black-Scholes and Generalized Gamma) appear to yield similar results.
Worst-Case Efficient Dynamic Geometric Independent Set

We consider the problem of maintaining an approximate maximum independent set of geometric objects under insertions and deletions. We present a data structure that maintains a constant-factor approximate maximum independent set for broad classes of fat objects in d dimensions, where d is assumed to be a constant, in sublinear worst-case update time. This gives the first results for dynamic independent set in a wide variety of geometric settings, such as disks, fat polygons, and their high-dimensional equivalents. Our result is obtained via a two-level approach. First, we develop a dynamic data structure which stores all objects and provides an approximate independent set when queried, with output-sensitive running time. We show that via standard methods such a structure can be used to obtain a dynamic algorithm with amortized update time bounds. Then, to obtain worst-case update time algorithms, we develop a generic deamortization scheme that with each insertion/deletion keeps (i) the update time bounded and (ii) the number of changes in the independent set constant. We show that such a scheme is applicable to fat objects by showing an appropriate generalization of a separator theorem. Interestingly, we show that our deamortization scheme is also necessary in order to obtain worstcase update bounds: If for a class of objects our scheme is not applicable, then no constant-factor approximation with sublinear worst-case update time is possible. We show that such a lower bound applies even for seemingly simple classes of geometric objects including axis-aligned rectangles in the plane. 2012 ACM Subject Classification Theory of computation → Approximation algorithms analysis; Theory of computation → Data structures design and analysis
RTE: A Tool for Annotating Relation Triplets from Text

In this work, we present a Web-based annotation tool `Relation Triplets Extractor' \footnote{https://abera87.github. io/annotate/} (RTE) for annotating relation triplets from the text. Relation extraction is an important task for extracting structured information about real-world entities from the unstructured text available on the Web. In relation extraction, we focus on binary relation that refers to relations between two entities. Recently, many supervised models are proposed to solve this task, but they mostly use noisy training data obtained using the distant supervision method. In many cases, evaluation of the models is also done based on a noisy test dataset. The lack of annotated clean dataset is a key challenge in this area of research. In this work, we built a web-based tool where researchers can annotate datasets for relation extraction on their own very easily. We use a server-less architecture for this tool, and the entire annotation operation is processed using client-side code. Thus it does not suffer from any network latency, and the privacy of the user's data is also maintained. We hope that this tool will be beneficial for the researchers to advance the field of relation extraction.
VerSaChI: Finding Statistically Significant Subgraph Matches using Chebyshev's Inequality

Approximate subgraph matching, an important primitive for many applications like question answering, community detection, and motif discovery, often involves large labeled graphs such as knowledge graphs, social networks, and protein sequences. Effective methods for extracting matching subgraphs, in terms of label and structural similarities to a query, should depict accuracy, computational efficiency, and robustness to noise. In this paper, we propose VerSaChI for finding the top-k most similar subgraphs based on 2-hop label and structural overlap similarity with the query. The similarity is characterized using Chebyshev's inequality to compute the chi-square statistical significance for measuring the degree of matching of the subgraphs. Experiments on real-life graph datasets showcase significant improvements in terms of accuracy compared to state-of-the-art methods, as well as robustness to noise.
HyperSF: Spectral Hypergraph Coarsening via Flow-based Local Clustering

Hypergraphs allow modeling problems with multiway high-order relationships. However, the computational cost of most existing hypergraph-based algorithms can be heavily dependent upon the input hypergraph sizes. To address the ever-increasing computational challenges, graph coarsening can be potentially applied for preprocessing a given hypergraph by aggressively aggregating its vertices (nodes). However, state-of-the-art hypergraph partitioning (clustering) methods that incorporate heuristic graph coarsening techniques are not optimized for preserving the structural (global) properties of hypergraphs. In this work, we propose an efficient spectral hypergraph coarsening scheme (HyperSF) for well preserving the original spectral (structural) properties of hypergraphs. Our approach leverages a recent strongly-local max-flow-based clustering algorithm for detecting the sets of hypergraph vertices that minimize ratio cut. To further improve the algorithm efficiency, we propose a divide-and-conquer scheme by leveraging spectral clustering of the bipartite graphs corresponding to the original hypergraphs. Our experimental results for a variety of hypergraphs extracted from real-world VLSI design benchmarks show that the proposed hypergraph coarsening algorithm can significantly improve the multi-way conductance of hypergraph clustering as well as runtime efficiency when compared with existing state-of-the-art algorithms.
Heavy elements in barium stars

New elemental abundances for the neutron-capture elements Sr, Nb, Mo, Ru, La, Sm, and Eu are presented for a large sample of 180 barium (Ba) giant stars, a class of chemically peculiar objects that exhibit in their spectra enhancements of the elements created by the s-process, as a consequence of mass transfer between the components of a binary system. The content of heavy elements in these stars, in fact, points to nucleosynthesis mechanisms that took place within a former asymptotic giant branch (AGB) companion, now an invisible white dwarf. From high-resolution ($R=48\, 000$) spectra in the optical, we derived the abundances either by equivalent width measurements or synthetic spectra computations, and compared them with available data for field giant and dwarf stars in the same range of metallicity. A re-determination of La abundances resulted in [La/Fe] ratios up to 1.2 dex lower than values previously reported in literature. The programme Ba stars show overabundance of neutron-capture elements, except for Eu, for which the observational data set behave similarly to field stars. Comparison to model predictions are satisfactory for second-to-first s-process peak ratios (e.g. [La/Sr]) and the ratios of the predominantly r-process element Eu to La. However, the observed [Nb, Mo, Ru/Sr] and [Ce, Nd, Sm/La] ratios show median values higher or at the upper limits of the ranges of the model predictions. This unexplained feature calls for new neutron capture models to be investigated.
Approach for monitoring the dynamic states of water in shrimp during drying process with LF-NMR and MRI

ABSTRACT The dynamic states of water in shrimp during drying process were investigated by low-field nuclear magnetic resonance and magnetic resonance imaging. With the extension of drying time, the transverse relaxation time of immobilized and free water significantly decreased, illustrating their mobility reduced. The signal per mass of immobilized water also decreased significantly, indicating its remarkable loss during drying process. Magnetic resonance imaging results revealed that the water signal intensity decreased from the external surface to inner regions of shrimp. Good correlations between the moisture content, hardness, chewiness, cohesiveness, L*, a* and nuclear magnetic resonance T2 parameters were observed by linear regression analysis.
Obesity and high neutrophil-to-lymphocyte ratio are prognostic factors in non-metastatic breast cancer patients

Obesity has been associated with an increased risk of breast cancer recurrence and death. Some readily available biomarkers associated with systemic inflammation have been receiving attention as potential prognostic indicators in cancer, including neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). This study aimed to explore the correlation between body mass index (BMI) and invasive breast cancer and the association of NLR, PLR, and BMI with breast cancer outcomes. We undertook a retrospective study to evaluate patients treated for breast cancer over 14 years. Clinicopathological data was obtained before receiving any treatment. Of the 1664 patients included with stage I-III, 567 (34%) were obese (BMI≥30 kg/m2). Obese patients had larger tumors compared to non-obese patients. Higher BMI was associated with recurrence and worse survival only in patients with stage I disease. NLR and PLR were classified into high and low level groups. The NLRhigh (NLR>4) was found to be an independent prognostic factor for recurrence and mortality, while the PLRhigh (PLR>150) group had no impact on survival. A subgroup of patients with NLRhigh and BMIhigh had the worst disease-free survival (P=0.046), breast cancer-specific survival (P<0.001), and overall survival (P=0.006), compared to the other groups. Patients with early-stage breast cancer bearing NLRhigh and BMIhigh had worse outcomes, and this might be explained by the dysfunctional milieu of obesity in adipose tissue and its effects on the immune system. This study highlights the importance of lifestyle measures and the immune system interference with clinical outcomes in the early breast cancer setting.
Device profile of the SAPIEN 3 transcatheter heart valve in low-risk patients with aortic stenosis: overview of its safety and efficacy

ABSTRACT Introduction Transcatheter aortic valve replacement (TAVR) has become a treatment of reference for patients with symptomatic severe aortic stenosis, and the balloon-expandable SAPIEN 3 and SAPIEN 3 Ultra transcatheter heart valve systems are two of the most broadly used worldwide. Lately, TAVR has progressively expanded toward the treatment of low-risk patients. Areas covered In this review we aimed to describe the main characteristics of the SAPIEN 3 valve, and to delineate the main clinical findings regarding the safety and efficacy associated with this THV system in low-risk patients undergoing TAVR. Expert opinion The approval of THV systems for use in low-risk patients has been a significant step forward in expanding current TAVR indications. Along with procedural refinement and growing operator experience, device iterations implemented in new-generation THV systems have played a vital role in the successful spread of TAVR. The availability of SAPIEN 3 represented an inflection point, as it allows for a predictable positioning and safer navigability while dramatically decreasing the rate of residual paravalvular leakage compared to previous balloon-expandable systems. However, some unresolved issues remain like the relatively high rates of conduction disturbances and the uncertainty about valve performance in the long-term. Future studies are warranted.
Binding between elongation factor 1A and the 3ʹ‐UTR of Chinese wheat mosaic virus is crucial for virus infection

Abstract The Chinese wheat mosaic virus (CWMV) genome consists of two positive‐strand RNAs that are required for CWMV replication and translation. The eukaryotic translation elongation factor (eEF1A) is crucial for the elongation of protein translation in eukaryotes. Here, we show that silencing eEF1A expression in Nicotiana benthamiana plants by performing virus‐induced gene silencing can greatly reduce the accumulation of CWMV genomic RNAs, whereas overexpression of eEF1A in plants increases the accumulation of CWMV genomic RNAs. In vivo and in vitro assays showed that eEF1A does not interact with CWMV RNA‐dependent RNA polymerase. Electrophoretic mobility shift assays revealed that eEF1A can specifically bind to the 3ʹ‐untranslated region (UTR) of CWMV genomic RNAs. By performing mutational analyses, we determined that the conserved region in the 3ʹ‐UTR of CWMV genomic RNAs is necessary for CWMV replication and translation, and that the sixth stem‐loop (SL‐6) in the 3ʹ‐UTR of CWMV genomic RNAs plays a key role in CWMV infection. We conclude that eEF1A is an essential host factor for CWMV infection. This finding should help us to develop new strategies for managing CWMV infections in host plants.
Determination of acrylamide in potato-based foods using headspace solid-phase microextraction based on nanostructured polypyrrole fiber coupled with ion mobility spectrometry: a heat treatment study

In this work, headspace solid-phase microextraction (HS-SPME) coupled with ion mobility spectrometry (IMS) has been used as a simple and convenient method for acrylamide detection and quantification in heat treated food samples. IMS coupled with corona discharge (CD) ionization along with HS-SPME based on nanostructured polypyrrole (PPy) fiber has been successfully applied for the quantitative analysis of acrylamide in potato-based foods. The effect of various analytical parameters on the microextraction procedure like extraction temperature, extraction time, ionic strength and pH of the sample was also studied and optimized to obtain the best HS-SPME results. The HS-SPME-IMS method provided good repeatability (RSD ≤ 8%) and the calibration graph was linear in the range of 10–100 ng g−1 (R2 > 0.99) with a detection limit of 4 ng g−1. The proposed method was applied for the determination of acrylamide in potato-based foods, such as potato crisp and French fry samples. Validation of the analytical procedure was determined as the percentage of recovery and was confirmed by the add-found method in the potato-based food samples. The results obtained by the proposed method are in satisfactory agreement with the amounts added (92–96%). In conclusion, a direct relationship between temperature/time and acrylamide concentration in heat treated foods can be established.
Preoperative anxiety in preschool children: A randomized clinical trial comparing midazolam, clonidine, and dexmedetomidine

Anxiety in pediatric patients may challenge perioperative anesthesiology management and worsen postoperative outcomes. Sedative drugs aimed to reducing anxiety are available with different pharmacologic profiles, and there is no consensus on their effect or the best option for preschool children. In this study, we aimed to compare the effect of three different premedications on anxiety before anesthesia induction in preschool children aged 2−6 years scheduled for elective surgery. The secondary outcomes comprised distress during peripheral catheter (PVC) insertion, compliance at anesthesia induction, and level of sedation.
Exploring Reflections, Motivations, and Experiential Outcomes of First Same-Sex/Gender Sexual Experiences among Lesbian, Gay, Bisexual, and Other Sexual Minority Individuals

ABSTRACT First sex is an important event in an individual’s sexual development. Previous literature has, however, primarily investigated first heterosexual sex, overlooking important contextual factors specific to same-sex/gender sexual experiences. Seventeen in-depth semi-structured interviews were conducted with lesbian, gay, bisexual, and other sexual minority (LGB+) individuals, ages 18–23 years. Four themes emerged from thematic analysis of reported thoughts, affect, and behavior. First, participants reported difficulty defining sex between same-sex/gender partners, especially women who reported that this undermined their personal relationships and identity. Second, participants met partners through several means; however, it was almost exclusively men who reported meeting their first partners online. Third, motivations for first same sex/gender sex included affirmation of personal sexual identity, sexual exploration, social expectation, and spontaneity. Fourth, participants felt underprepared for their first same-sex/gender sex, noting that their earlier sex and relationship education had not included information on same-sex/gender sex or LGB+ identities. Consequently, participants reported relying on experienced partners and seeking information on the internet, including pornography and social media. Greater cultural representation and more comprehensive sex education that recognizes sexual diversity is needed to better prepare LGB+ young people for early sexual encounters.
Panax notoginseng saponin attenuates the hypoxic–ischaemic injury in neonatal rats by regulating the expression of neurotrophin factors

Neonatal hypoxic–ischaemic (HI) injury is a serious complication of neonatal asphyxia and the leading cause of neonatal acute death and chronic neurological injury, and the effective therapeutic method is lacking to improve patients' outcomes. We reported in this study that panax notoginseng saponin (PNS) may provide a treatment option for HI. HI model was established using neonatal Sprague–Dawley rats and then intraperitoneally injected with different dosage of PNS, once a day for 7 days. Histological staining and behavioural evaluations were performed to elucidate the pathological changes and neurobehavioural variation after PNS treatment. We found PNS administration significantly reduced the infarct volume of brain tissues and improved the autonomous activities of neonatal rats, especially with higher dosage. PNS treatment at 40 mg/kg reduced neuronal damage, suppressed neuronal apoptosis and depressed astroglial reactive response. Moreover, the long‐term cognitive and motor functions were also improved after PNS treatment at 40 mg/kg. Importantly, PNS treatment elevated the levels of BDNF and TrkB but decreased the expression of p75NTR both in the cortex and hippocampus of HI rats. The therapeutic efficacy of PNS might be correlated with PNS‐activated BDNF/TrkB signalling and inactivation of p75NTR expression, providing a novel potential therapy for alleviating HI injury.
Effect of a common exercise programme with an individualised progression criterion based on the measurement of neuromuscular capacity versus current best practice for lower limb tendinopathies (MaLaGa trial): a protocol for a randomised clinical trial

Introduction High-load resistance training has shown positive effects in pain and function in lower limb tendinopathies. However, some authors suggest that current exercise programmes produce an increase in tolerance to load and exercise in general but without fixing some existing issues in tendinopathy. This may indicate the need to include training aspects not currently taken into account in the current programmes. The main objective of this study will be to compare the effect of a common exercise protocol for the three predominant lower limb tendinopathies (Achilles, patellar and gluteal), based on an individualised control of the dose and training of specific aspects of the neuromuscular system versus the current best practice for each location. Methods and analysis This study will be conducted among people with mid-portion Achilles, patellar or gluteal tendinopathy. The participants allocated to the experimental group will perform a 14-week innovative common therapeutic exercise programme. Participants allocated to the control group will carry out a 14-week exercise programme based on the best current practice for each of the studied locations. The Victorian Institute of Sports Assessment questionnaire will be considered the primary outcome. Pain, central sensitisation, fear avoidance behaviour, quality of life, treatment satisfaction, lower-limb strength and function, and high-density electromyography profile will be evaluated as secondary outcomes. Outcomes will be assessed at baseline, 7 weeks, after the intervention (week 14), 26 weeks and 52 weeks. Ethics and dissemination The study has been approved by the Portal de Ética de la Investigación Biomédica de Andalucía Ethics Committee (1221-N-19). All participants will be informed about the purpose and content of the study and written informed consent will be completed. The results of this study will be published in a peer-reviewed journal and will be disseminated electronically and in print. Trial registration number NCT03853122; Pre-results.