Miracle-dz/UniFAR-FTUs huggingface dataset:
RepMet: Representative-based metric learning for classification and one-shot object detection

Distance metric learning (DML) has been successfully applied to object classification, both in the standard regime of rich training data and in the few-shot scenario, where each category is represented by only a few examples. In this work, we propose a new method for DML that simultaneously learns the backbone network parameters, the embedding space, and the multi-modal distribution of each of the training categories in that space, in a single end-to-end training process. Our approach outperforms state-of-the-art methods for DML-based object classification on a variety of standard fine-grained datasets. Furthermore, we demonstrate the effectiveness of our approach on the problem of few-shot object detection, by incorporating the proposed DML architecture as a classification head into a standard object detection model. We achieve the best results on the ImageNet-LOC dataset compared to strong baselines, when only a few training examples are available. We also offer the community a new episodic benchmark based on the ImageNet dataset for the few-shot object detection task.
Influence of a microstructured surface on the infrared radiation characteristics of a spatial target

Abstract. The radiation characteristics of a target change when a microstructured surface is used. Temperature and infrared (IR) radiation models are established for a flying spatial target with a microstructured surface. A simultaneous comparison was implemented for the temperature distribution and IR radiation characteristics of targets with normal and microstructured surfaces. This investigation was focused on the effects of detection angles on the IR radiation characteristics of a target with a microstructured surface. The results indicate that the utilization of a microstructured surface reduces the IR radiance of the spatial target, and a sudden change in the detection capacity was found for different detection angles, which is significant for the study of radiation characteristics of a target with a microstructured surface.
Predicting gleason score using the initial serum total prostate-specific antigen in Black men with symptomatic prostate adenocarcinoma in nigeria

Background: Men of Black African descent are known to have the highest incidence of prostate cancer. The disease is also more aggressive in this group possibly due to biologically more aggressive tumor or late presentation. Currently, serum prostate-specific antigen (PSA) assay plays a significant role in making the diagnosis of prostate cancer. However, the obtained value of serum PSA may not directly relate with the Gleason score (GS), a measure of tumor aggression in prostate cancer. This study explores the relationship between serum total PSA at presentation (iPSA) and GS. Patients and methods: The iPSA of patients with histologically confirmed prostate cancer was compared with the obtained GS of the prostate biopsy specimens. The age of the patients at presentation and the prostate volumes were also analyzed with respect to the iPSA and GS. The data were analyzed retrospectively using IBM SPSS Version 20. Pearson correlation was used for numeric variables, whereas Fisher’s exact test was used for categorical variables. Significance was set at P # 0.05. Results: There were 205 patients from January 2010 to November 2013 who satisfied the inclusion criteria. iPSA as well as age at presentation and prostate volume were not found to significantly correlate with the primary Gleason grade, the secondary Gleason grade, or the GS. However, the presence of distant metastasis was identified to significantly correlate positively with GS. Conclusion: GS may not be confidently predicted by the iPSA. Higher iPSA does not correlate with higher GS and vice versa.
Parabolic bundles, products of conjugacy classes, and Gromov-Witten invariants

L'ensemble des classes de conjugaison apparaissant dans un produit de classes de conjugaison d'un groupe de Lie 1-connexe compact peut etre identifie avec un polytope convexe dans une chambre pour le groupe affine de Weyl. Nous demontrons que les inegalites lineaires definissant ce polytope correspondent aux invariants de Gromov-Witten pour les varietes de drapeaux generalisees. Ceci generalise les resultats de Agnihotri, du deuxieme auteur et de Belkale sur les valeurs propres d'un produit de matrices unitaires et la cohomologie quantique des grassmanniennes.
Patient risk factors for developing a drug-related problem in a cardiology ward

Background: Because of the high incidence of drug-related problems (DRPs) among hospitalized patients with cardiovascular diseases and their potential impact on morbidity and mortality, it is important to identify the most susceptible patients, who therefore require closer monitoring of drug therapy. Purpose: To identify the profile of patients at higher risk of developing at least one DRP during hospitalization in a cardiology ward. Method: We consecutively included all patients hospitalized in the cardiology ward of a teaching hospital in 2009. DRPs were identified through a computerized warning system designed by the pharmacy department and integrated into the electronic medical record. Results: A total of 964 admissions were included, and at least one DRP was detected in 29.8%. The variables associated with a higher risk of these events were polypharmacy (odds ratio [OR] = 1.228; 95% confidence interval [CI] = 1.153–1.308), female sex (OR = 1.496; 95% CI = 1.026–2.180), and first admission (OR = 1.494; 95% CI = 1.005–2.221). Conclusion: Monitoring patients through a computerized warning system allowed the detection of at least one DRP in one-third of the patients. Knowledge of the risk factors for developing these problems in patients admitted to hospital for cardiovascular problems helps in identifying the most susceptible patients. the to
Spectral Induced Polarization imaging to monitor seasonal and annual dynamics of frozen ground at a mountain permafrost site in the Italian Alps

We investigate the application of spectral induced polarization (SIP) monitoring to understand seasonal and annual variations of freezing and thawing processes in permafrost, in particular with regard to the frequency-dependence of the subsurface electrical properties. We installed a permanent SIP monitoring profile at a high mountain permafrost site in the Italian Alps in 2019 and collected SIP data in the frequency range between 0.1-75 Hz over 3 years. Complementary seismic 15 data were acquired, which, together with borehole data, were used to aid interpretation of the SIP imaging results. In particular, we investigated the phase frequency effect (φFE), i.e., the change of resistivity phase with frequency. We observe that this parameter (φFE) is strongly sensitive to temperature changes and might be used as a proxy to delineate spatial and temporal changes of ice content in the subsurface, providing information not accessible through electrical resistivity tomography (ERT) or single-frequency IP measurements. Temporal changes in φFE are validated through laboratory SIP measurements on 20 samples from the site in controlled freeze-thaw experiments. We demonstrate that SIP is capable of resolving temporal changes in the thermal state and the ice/water ratio associated with seasonal freeze-thaw processes. We investigate the consistency between the φFE observed in field data and ground water and ice content estimates derived from petrophysical modelling of ERT and seismic data. 25
UvA-DARE (Digital Academic Repository) On convergence to stationarity of fractional Brownian storage

With M(t) := sup s ∈[ 0 ,t ] A(s) − s denoting the running maximum of a fractional Brownian motion A( · ) with negative drift, this paper studies the rate of convergence of P (M(t) > x) to P (M > x) . We deﬁne two metrics that measure the distance between the (complementary) distribution functions P (M(t) > · ) and P (M > · ) . Our main result states that both metrics roughly decay as exp ( − ϑt 2 − 2 H ) , where ϑ is the decay rate corresponding to the tail distribution of the busy period in an fBm-driven queue, which was computed recently [ Stochastic Process. Appl. (2006) 116 1269–1293]. The proofs extensively rely on application of the well-known large deviations theorem for Gaussian processes. We also show that the identiﬁed relation between the decay of the convergence metrics and busy-period asymptotics holds in other settings as well, most notably when Gärtner–Ellis-type conditions are ful-ﬁlled.
Variability in ultra cool dwarfs: Evidence for the evolution of surface features

We present photometric light curves for a sample of 21 ultra cool M and L dwarfs in the field and in the young open clusters σ Orionis and the Pleiades. The list of targets includes both low mass hydrogen burning stars and brown dwarfs. Evidence for variability with rms amplitudes (in the I band) of 0.01 to 0.055 magnitudes on timescales of 0.4 to 100 hours is discovered in half of these objects. Power spectral analysis using the CLEAN algorithm was performed to search for evidence of periodic variability. Some objects show strong periodicities at around a few hours, which could be due to rotational modulation of the light curve by surface features. However, several objects do not have any significant periodicities to explain their variability. The $v \sin i$ values of a similar population of objects makes it very likely that our time sampling was sensitive to the expected range of rotation periods, and simulations show that we would have detected these if they were caused by long-lived surface features. We argue that this absence of periodicity is due to the evolution of the brightness, and presumably also the physical size, of surface features on timescales of a few to a few tens of hours. This is supported in the case of 2M1145 for which two light curves have been obtained one year apart and show no common periodicity. The surface features could plausibly be photospheric dust clouds or magnetically-induced spots. The recently observed decline in chromospheric activity for late type M and L dwarfs hints towards the former explanation for at least our later-type objects. Furthermore, our sample suggests that variability is more common in objects later than M9, indicating that the variability may be related to dust formation. One light curve shows a brief, but significant, dip, which could be a short-lived feature or possibly an eclipse by a companion.
Reversible magnetocaloric effect in materials with first order phase transitions in cyclic magnetic fields: Fe48Rh52 and Sm0.6Sr0.4MnO3

The magnetocaloric effect (MCE) in an Fe48Rh52 alloy and Sm0.6Sr0. 4MnO3 manganite was studied in cyclic magnetic fields. The adiabatic temperature change in the Fe48Rh52 alloy for a magnetic field change (ΔB) of 8 T and a frequency (f) of 0.13 Hz reaches the highest value of (ΔTad) of −20.2 K at 298 K. The magnitude of the MCE in Sm0.6Sr0. 4MnO3 reaches ΔTad = 6.1 K at the same magnetic field change at 143 K. The temperature regions, where a strong MCE is exhibited in an alternating magnetic field, are bounded in both compounds. In the case of the Fe48Rh52 alloy, the temperature range for this phenomenon is bounded above by the ferromagnetic to antiferromagnetic transition temperature in the zero field condition during cooling. In the case of the Sm0.6Sr0. 4MnO3 manganite, the temperature range for the MCE is bounded below by the ferromagnetic-paramagnetic transition temperature in zero field during heating. The presence of these phase boundaries is a consequence of the existence of areas of irreversible ma.
Geometric inequalities involving mean curvature for convex surfaces

In this paper we prove some geometric inequalities for closed surfaces in Euclidean $3$-space. Motivated by Gage's inequality for convex curves, we first verify that for convex surfaces the Willmore energy is bounded below by some scale-invariant quantities. In particular, we obtain an optimal scaling law between the Willmore energy and the isoperimetric ratio under convexity. In addition, we also address Topping's conjecture relating diameter and mean curvature for connected closed surfaces. We prove this conjecture in the class of simply-connected axisymmetric surfaces, and moreover obtain a sharp remainder term which ensures the first evidence that optimal shapes are necessarily straight even without convexity.
Equivalent excitability through different sodium channels and implications for the analgesic efficacy of selective drugs

Nociceptive sensory neurons convey pain-related signals to the CNS using action potentials. Loss-of-function mutations in the voltage-gated sodium channel NaV1.7 cause insensitivity to pain (presumably by reducing nociceptor excitability) but efforts to treat pain by inhibiting NaV1.7 pharmacologically have largely failed. This may reflect the variable contribution of NaV1.7 to nociceptor excitability. Contrary to claims that NaV1.7 is necessary for nociceptors to initiate action potentials, we show that nociceptors can achieve equivalent excitability using different combinations of NaV1.3, NaV1.7, and NaV1.8. Selectively blocking one of those NaV subtypes reduces nociceptor excitability only if the other two subtypes are weakly expressed. For example, excitability relies on NaV1.8 in acutely dissociated nociceptors but responsibility shifts to NaV1.7 and NaV1.3 by the fourth day in culture. A similar shift in NaV dependence occurs in vivo after inflammation, impacting ability of the NaV1.7-selective inhibitor PF-05089771 to reduce pain in behavioral tests. Flexible use of different NaV subtypes exemplifies degeneracy – equivalent function using different components – and compromises the reliable modulation of nociceptor excitability by subtype-selective inhibitors. Identifying the dominant NaV subtype to predict drug efficacy is not trivial. Degeneracy at the cellular level must be considered when choosing drug targets at the molecular level. SIGNIFICANCE STATEMENT Nociceptors can achieve equivalent excitability using different sodium channel subtypes. The analgesic efficacy of subtype-selective drugs hinges on which subtype controls excitability. This contingency likely contributes to poor clinical outcomes.
Theoretical Population Biology

Reconstructing past population size from present day genetic data is a major goal of population genetics. Recent empirical studies infer population size history using coalescent-based models applied to a small numberofindividuals.Hereweprovidetightboundsontheamountofexactcoalescencetimedataneeded to recover the population size history of a single, panmictic population at a certain level of accuracy. In practice, coalescence times are estimated from sequence data and so our lower bounds should be taken as rather conservative. © 2014
Nonparametric Estimation and Misspecification Testing of Diffusion Models

We propose novel misspecification tests of semiparametric and fully parametric univariate diffusion models based on the estimators developed in Kristensen (Journal of Econometrics, 2010). We first demonstrate that given a preliminary estimator of either the drift or the diffusion term in a diffusion model, nonparametric kernel estimators of the remaining term can be obtained. We then propose misspecification tests of semparametric and fully parametric diffusion models that compare estimators of the transition density under the relevant null and alternative. The asymptotic distribution of the estimators and tests under the null are derived, and the power properties are analyzed by considering contiguous alternatives. Test directly comparing the drift and diffusion estimators under the relevant null and alternative are also analyzed. Markov Bootstrap versions of the test statistics are proposed to improve on the finite-sample approximations. The finite sample properties of the estimators are examined in a simulation study.
LIGHTPAFF: A TWO-STAGE DISTILLATION FRAME-

While pre-training and fine-tuning, e.g., BERT (Devlin et al., 2018), GPT-2 (Radford et al., 2019), have achieved great success in language understanding and generation tasks, the pre-trained models are usually too big for online deployment in terms of both memory cost and inference speed, which hinders them from practical online usage. In this paper, we propose LightPAFF, a Lightweight Pre-training And Fine-tuning Framework that leverages two-stage knowledge distillation to transfer knowledge from a big teacher model to a lightweight student model in both pre-training and fine-tuning stages. In this way the lightweight model can achieve similar accuracy as the big teacher model, but with much fewer parameters and thus faster online inference speed. LightPAFF can support different pretraining methods (such as BERT, GPT-2 and MASS (Song et al., 2019)) and be applied to many downstream tasks. Experiments on three language understanding tasks, three language modeling tasks and three sequence to sequence generation tasks demonstrate that while achieving similar accuracy with the big BERT, GPT-2 and MASS models, LightPAFF reduces the model size by nearly 5x and improves online inference speed by 5x-7x.
Revisiting Friedmann-like cosmology with torsion: newest constraints from high-redshift observations

As one of the possible extensions of Einstein's General Theory of Relativity, it has been recently suggested that the presence of space-time torsion could solve problems of the very early and the late-time universe undergoing accelerating phases. In this paper, we use the latest observations of high-redshift data, coming from multiple measurements of quasars and baryon acoustic oscillations, to phenomenologically constrain such cosmological model in the framework of Einstein-Cartan (EC) endowed with space-time torsion. Such newly compiled quasar datasets in the cosmological analysis is crucial to this aim, since it will extend the Hubble diagram to high-redshift range in which predictions from different cosmologies can be distinguished. Our results show that out of all the candidate models, the torsion plus cosmological constant model is strongly favoured by the current high-redshift data, where torsion would be expected to yield the late-time cosmic acceleration. Specially, in the framework of Friedmann-like cosmology with torsion, the determined Hubble constant is in very good agreement with that derived from the Planck 2018 CMB results. On the other hand, our results are compatible with zero spatial curvature and there is no significant deviation from flat spatial hypersurfaces. Finally, we check the robustness of high-redshift observations by placing constraints on the torsion parameter α, which is strongly consistent with other recent works focusing on torsion effect on the primordial helium-4 abundance.
Economic evaluations of hepatitis A vaccination in middle-income countries

Economic evaluations of hepatitis A vaccination are important to assist national and international policy makers in different jurisdictions on making effective decisions. Up to now, a comprehensive review of the potential health and economic benefits on hepatitis A vaccination in middle-income countries (MICs) has not been performed yet. In this study, we reviewed the literature on the cost–effectiveness of hepatitis A vaccination in MICs. Most of the studies confirmed that hepatitis A vaccination was cost effective or even cost saving under certain conditions. We found that vaccine price, medical costs, incidence and discount rate were the most influential parameters on the sensitivity analyses. Vaccine price has been shown as a barrier for MICs in implementing universal vaccination of hepatitis A. Given their relatively limited financial resources, implementation of single-dose vaccination could be considered. Despite our findings, we argue that further economic evaluations in MICs are still required in the near future.
Natural Resources for Human Health

Among the large group of natural polyphenolic flavonoids, acacetin is widely distributed throughout the plant kingdom and remained part of the world’s food and traditional medication systems. Acacetin is found naturally in more than 200 plant species belonging to 60 different plant families, but mainly in Asteraceae and Lamiaceae families in Artemisia, Cirsium, Dendranthema, Saussurea, Dracocephalum, andOriganum. In the Traditional ChineseMedicine (TCM) system, plant extracts having acacetin with various biological activities are given to cure different ailments, including microbial or viral infections, cardiovascular issues, blood glucose fluctuations or diabetes, neurological and immunological disorders, hyperlipidemia, chronic inflammations, cancers or tumor control, hepatic issues, and lot more to count. Acacetin mainly exerts its remarkable effects both at transcriptional as well as translational levels. Acacetin suppressed the phosphorylation of p38 mitogen-activated protein kinases (MAPKs) and nuclear factor (NF)-κB and reduces lipid peroxidation through reactive oxygen species (ROS) scavenging capability. For many proteins and enzymes, acacetin directly binds with them to regulate their activities. It hence acts as a potent inhibitor of that particular function such as inhibition of sortase enzyme, translational protein enzymes, aldose reductase enzyme, inhibition of cell signaling channels and molecules, and much more. It is concluded that acacetin can be used as a potent inhibitor of multiple proteins, enzymes, signaling molecules, and ion channels. These properties make acacetin an appealing candidate to be designed and screened as a multipurpose inhibitor for diseases.
Natural Resources for Human Health

Seaweed extracts have been used as fertilizer for crops to enhance the yield and quality of crop products. Only very few studies have been carried out on the effects of seaweed extracts and beneficial soil microbes on the growth of crop plants. Hence, the present study was conducted to investigate the synergistic effect of seaweed extract (SE) prepared from Sargassum wightii Greville, with and without applying Rhizobium biofertilizer, on seed germination, seedling growth, biochemical constituents and yield of cowpea (Vigna unguiculata Walp Var. pusa 151 (family Fabaceae). Seaweed extract (1% concentration), with or without Rhizobium (biofertilizer) treatment, compared with the control, significantly (p≤ 0.05) enhanced vegetative growth (dry weight of shoot and root, number of lateral roots and total leaf area), biochemical parameters (total chlorophyll, carotenoids, proteins, lipids, total sugar and amino acids) and yield and yield components (pod number, length, weight, number of seeds per pod and 100 seeds weight). Seaweed extract application, along with Rhizobium biofertilizer, exhibited better results in vegetative growth, biochemical and yield than the seaweed extract alone in enhancing the growth and yield of cowpea.
A Bug Bounty Perspective on the Disclosure of Web Vulnerabilities

Bug bounties have become increasingly popular in recent years. This paper discusses bug bounties by framing these theoretically against so-called platform economy. Empirically the interest is on the disclosure of web vulnerabilities through the Open Bug Bounty (OBB) platform between 2015 and late 2017. According to the empirical results based on a dataset covering nearly 160 thousand web vulnerabilities, (i) OBB has been successful as a community-based platform for the dissemination of web vulnerabilities. The platform has also attracted many productive hackers, (ii) but there exists a large productivity gap, which likely relates to (iii) a knowledge gap and the use of automated tools for web vulnerability discovery. While the platform (iv) has been exceptionally fast to evaluate new vulnerability submissions, (v) the patching times of the web vulnerabilities disseminated have been long. With these empirical results and the accompanying theoretical discussion, the paper contributes to the small but rapidly growing amount of research on bug bounties. In addition, the paper makes a practical contribution by discussing the business models behind bug bounties from the viewpoints of platforms, ecosystems, and vulnerability markets.