Miracle-dz/UniFAR-FTUs huggingface dataset:
Inducing Predictive Uncertainty Estimation for Face Verification

Knowing when an output can be trusted is critical for reliably using face recognition systems. While there has been enormous effort in recent research on improving face verification performance, understanding when a model's predictions should or should not be trusted has received far less attention. Our goal is to assign a confidence score for a face image that reflects its quality in terms of recognizable information. To this end, we propose a method for generating image quality training data automatically from 'mated-pairs' of face images, and use the generated data to train a lightweight Predictive Confidence Network, termed as PCNet, for estimating the confidence score of a face image. We systematically evaluate the usefulness of PCNet with its error versus reject performance, and demonstrate that it can be universally paired with and improve the robustness of any verification model. We describe three use cases on the public IJB-C face verification benchmark: (i) to improve 1:1 image-based verification error rates by rejecting low-quality face images; (ii) to improve quality score based fusion performance on the 1:1 set-based verification benchmark; and (iii) its use as a quality measure for selecting high quality (unblurred, good lighting, more frontal) faces from a collection, e.g. for automatic enrolment or display.
Dietary overlap between frugivorous birds and bats in the Peruvian Amazon

To assess the potential for competition between fruit-eating birds and bats, we quantified overlap in their use of fruit in a matrix of disturbed and undisturbed tropical forest. Seeds were obtained from 897 bats (31 species) and 200 birds (29 species) mist-netted over 2.5 yr. We calculated pairwise overlap in fruit diet by the simplified Morisita index for those frugivore species with the most diet data (11 bats and 7 birds). Overlap was 0 for 70% of the bird-bar species pairs, and less than 0.05 for the remainder. Two tanagers, Tachyphonus surinamus and Tangara schrankii, had greater dietary overlap with bats than did other bird species. Cluster analysis based on diet overlap separated birds and bats into different clusters. Correspondence analysis was used to reduce the dimensionality of the frugivore x fruit diet matrix. The first axis separated bats and the fruits on which they primarily fed from birds and their major fruits and was related to fruit length, type, and color. The second axis separated the frugivorous bats by size and was correlated with fruit length and plant growth form. Six fruits were eaten by both bats and birds : Phytolacca rivinoides, Marcgravia sp. , Souroubea guianensis, Philodendron cuneatum, Coussapoa villosa, and Havetiopsis flavida. As a group, these shared fruits comprised a minor fraction ( 10%) of most bird diets. These shared fruits were morphologically similar to those eaten by birds (arillate or berry-like, brightly colored exterior or aril), suggesting bats may be sampling bird fruits.
Current Trend in Antimicrobial Resistance of E.coli to Fluoroquinolones: A Comparative Study of Four Years

Fluoroquinolones are being extensively used for the treatment of OPD patients suffering from various infective diseases. Extensive use of these of drugs has resulted in high drug resistance among common pathogens. We analyzed the current antibiotic resistance pattern of E.coli to fluoroquinolones for four consecutive years. 9186 samples were processed and 716 E.coli were isolated. Antimicrobial susceptibility testing was done in accordance with latest Clinical and Laboratory Standards Institute (CLSI) guidelines.6644were urinary samples followed by blood (1321), pus ((704), and miscellaneous (517). Maximum positivity was seen in pus samples (43.18%, 308/704) followed by miscellaneous (18.56%, 96/517), blood (18.01%, 238/1321). Antibiotic resistance trend, during 2016, revealed least resistance against levoflox (12%) followed by gatiflox (13%) and moxifloxacin (28%). Maximum resistance was seen against norflox (42%) and ciproflox (40%). Nitrofurantoin showed minimum resistance (8%) among all. We observed a pattern of decreasing resistance against fluoroquinolones for E.coli during the study period.
Imperfect Contract Enforcement and Nominal Liabilities

This paper introduces the court’s inability to discern different qualities of goods of the same kind into an overlapping generations model. This friction makes fiat money circulate not only as a means of payments for goods, but also as a means of liability repayments in an equilibrium. This result holds with or without dynamic inefficiency. In this equilibrium, a shortage of real money balances for liability repayments can cause underinvestment by borrowers, even if the money supply follows a Friedman rule. This problem can be resolved by an elastic money supply through an intraday discount window at a zero discount fee. In this case, supplying no fiat money overnight maximizes aggregate consumption in a monetary steady state in a dynamically efficient economy. This policy, however, can also lead to a self-fulfilling crunch of discount window lending if commercial banks intermediate the lending from the central bank with a collateral constraint, and if the discount window market is segregated. This equilibrium can be eliminated if the central bank is the monopolistic public issuer of fiat money that also acts as the lender of last resort.
Histopathological Study of Psoriasis: A Prospective Cum Retrospective Study at a Tertiary Care Centre

Background and Objectives: Psoriasis is a chronic papulosquamous disorder with constant exacerbations and remissions. Based on the clinical overlap with other papulosquamous disorders and the role of histopathology in diagnosis, we undertook a study on psoriasis. The objective of this study was to identify combination of histopathological parameters for the diagnosis of psoriasis and establish their reliability and significance. Material and Methods: A retrospective cum prospective study over a period of 5 years was carried out. 56 clinically diagnosed cases of psoriasis were taken into consideration. Skin biopsies were taken from these cases and histopathological examination was done. These lesions were then assessed based on various histopathological parameters. Results and Discussion: Maximum number of cases were in the age group of 31–40 years, males being three times more affected than females. The most common symptom was pruritis and psoriasis vulgaris was the most common variant. Upper limbs and back were most frequently affected. Among the microscopic parameters, acanthosis and parakeratosis were observed and when present with features like hypogranulosis, elongation of rete ridges, dermal inflammation and vasodilation or perivascular lymphocytic infiltrate were likely to indicate psoriasis. Munro micro abscesses and spongiform pustules of Kogoj, diagnostic features of psoriasis were also seen in significant proportion. Conclusion: Diagnosis of psoriasis is made based on the analysis of clinical symptoms and signs with a correlation with histopathological features. The relative ambiguity associated with this disease makes such histopathologic studies all the more important.
Minimax estimation of norms of a probability density: II. Rate-optimal estimation procedures

In this paper we develop rate--optimal estimation procedures in the problem of estimating the $L_p$--norm, $p\in (0, \infty)$ of a probability density from independent observations. The density is assumed to be defined on $R^d$, $d\geq 1$ and to belong to a ball in the anisotropic Nikolskii space. We adopt the minimax approach and construct rate--optimal estimators in the case of integer $p\geq 2$. We demonstrate that, depending on parameters of Nikolskii's class and the norm index $p$, the risk asymptotics ranges from inconsistency to $\sqrt{n}$--estimation. The results in this paper complement the minimax lower bounds derived in the companion paper \cite{gl20}.
Adapting Security Warnings to Counter Online Disinformation

Disinformation is proliferating on the internet, and platforms are responding by attaching warnings to content. There is little evidence, however, that these warnings help users identify or avoid disinformation. In this work, we adapt methods and results from the information security warning literature in order to design and evaluate effective disinformation warnings. In an initial laboratory study, we used a simulated search task to examine contextual and interstitial disinformation warning designs. We found that users routinely ignore contextual warnings, but users notice interstitial warnings--and respond by seeking information from alternative sources. We then conducted a follow-on crowdworker study with eight interstitial warning designs. We confirmed a significant impact on user information-seeking behavior, and we found that a warning's design could effectively inform users or convey a risk of harm. We also found, however, that neither user comprehension nor fear of harm moderated behavioral effects. Our work provides evidence that disinformation warnings can -- when designed well -- help users identify and avoid disinformation. We show a path forward for designing effective warnings, and we contribute repeatable methods for evaluating behavioral effects. We also surface a possible dilemma: disinformation warnings might be able to inform users and guide behavior, but the behavioral effects might result from user experience friction, not informed decision making.
Continual Domain Adaptation for Machine Reading Comprehension

Machine reading comprehension (MRC) has become a core component in a variety of natural language processing (NLP) applications such as question answering and dialogue systems. It becomes a practical challenge that an MRC model needs to learn in non-stationary environments, in which the underlying data distribution changes over time. A typical scenario is the domain drift, i.e. different domains of data come one after another, where the MRC model is required to adapt to the new domain while maintaining previously learned ability. To tackle such a challenge, in this work, we introduce the Continual Domain Adaptation (CDA) task for MRC. So far as we know, this is the first study on the continual learning perspective of MRC. We build two benchmark datasets for the CDA task, by re-organizing existing MRC collections into different domains with respect to context type and question type, respectively. We then analyze and observe the catastrophic forgetting (CF) phenomenon of MRC under the CDA setting. To tackle the CDA task, we propose several BERT-based continual learning MRC models using either regularization-based methodology or dynamic-architecture paradigm. We analyze the performance of different continual learning MRC models under the CDA task and show that the proposed dynamic-architecture based model achieves the best performance.
Combination of cluster number counts and two-point correlations: validation on mock Dark Energy Survey

We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy–cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations.
Minimax estimation of norms of a probability density: I. Lower bounds

The paper deals with the problem of nonparametric estimating the $L_p$--norm, $p\in (1,\infty)$, of a probability density on $R^d$, $d\geq 1$ from independent observations. The unknown density %to be estimated is assumed to belong to a ball in the anisotropic Nikolskii's space. We adopt the minimax approach, and derive lower bounds on the minimax risk. In particular, we demonstrate that accuracy of estimation procedures essentially depends on whether $p$ is integer or not. Moreover, we develop a general technique for derivation of lower bounds on the minimax risk in the problems of estimating nonlinear functionals. The proposed technique is applicable for a broad class of nonlinear functionals, and it is used for derivation of the lower bounds in the~$L_p$--norm estimation.
Quasinormal modes of massive vector fields on the Kerr spacetime

We study the spectrum of quasinormal mode frequencies for a Proca field on a rotating black hole spacetime. First, we review how the introduction of field mass modifies the spectrum in the scalar-field case, leading to evanescent modes and to quasiresonance. Next, we examine the three physical polarizations of the Proca field and their relation to the electromagnetic field modes in the massless limit. Exploiting a separation of variables, we obtain a five-term recurrence relation from an appropriate ansatz for the radial function. Gaussian elimination and the modified Lentz algorithm are applied, and the quasinormal frequencies are computed from the roots of a continued fraction. We validate our method by calculating quasibound state frequencies, which are complementary to quasinormal modes, and which can be calculated using the same method. We present a selection of results for the low-lying overtones of all three polarizations, across a range of black hole spins and field masses.
Topolectric circuits: Theory and construction

We highlight a general theory to engineer arbitrary Hermitian tight-binding lattice models in electrical LC circuits, where the lattice sites are replaced by the electrical nodes, connected to its neighbors and to the ground by capacitors and inductors. In particular, by supplementing each node with $n$ subnodes, where the phases of the current and voltage are the $n$ distinct roots of \emph{unity}, one can in principle realize arbitrary hopping amplitude between the sites or nodes via the \emph{shift capacitor coupling} between them. This general principle is then implemented to construct a plethora of topological models in electrical circuits, \emph{topoelectric circuits}, where the robust zero-energy topological boundary modes manifest through a large boundary impedance, when the circuit is tuned to the resonance frequency. The simplicity of our circuit constructions is based on the fact that the existence of the boundary modes relies only on the Clifford algebra of the corresponding Hermitian matrices entering the Hamiltonian and not on their particular representation. This in turn enables to implement a wide class of topological models through rather simple topoelectric circuits with nodes consisting of only two subnodes. We anchor these outcomes from the numerical computation of the on-resonance impedance in circuit realizations of first-order ($m=1$), such as Chern and quantum spin Hall insulators, second- ($m=2$) and third- ($m=3$) order topological insulators in different dimensions, featuring sharp localization on boundaries of codimensionality $d_c=m$. Finally, we subscribe to the \emph{stacked topoelectric circuit} construction to engineer three-dimensional Weyl, nodal-loop, quadrupolar Dirac and Weyl semimetals, respectively displaying surface and hinge localized impedance.
Unconstrained optimisation on Riemannian manifolds

In this paper, we give explicit descriptions of versions of (Local-) Backtracking Gradient Descent and New Q-Newton's method to the Riemannian setting.Here are some easy to state consequences of results in this paper, where X is a general Riemannian manifold of finite dimension and $f:X\rightarrow \mathbb{R}$ a $C^2$ function which is Morse (that is, all its critical points are non-degenerate). {\bf Theorem. } For random choices of the hyperparameters in the Riemanian Local Backtracking Gradient Descent algorithm and for random choices of the initial point $x_0$, the sequence $\{x_n\}$ constructed by the algorithm either (i) converges to a local minimum of $f$ or (ii) eventually leaves every compact subsets of $X$ (in other words, diverges to infinity on $X$). If $f$ has compact sublevels, then only the former alternative happens. The convergence rate is the same as in the classical paper by Armijo. {\bf Theorem. } Assume that $f$ is $C^3$. For random choices of the hyperparametes in the Riemannian New Q-Newton's method, if the sequence constructed by the algorithm converges, then the limit is a critical point of $f$. We have a local Stable-Center manifold theorem, near saddle points of $f$, for the dynamical system associated to the algorithm. If the limit point is a non-degenerate minimum point, then the rate of convergence is quadratic. If moreover $X$ is an open subset of a Lie group and the initial point $x_0$ is chosen randomly, then we can globally avoid saddle points. As an application, we propose a general method using Riemannian Backtracking GD to find minimum of a function on a bounded ball in a Euclidean space, and do explicit calculations for calculating the smallest eigenvalue of a symmetric square matrix.
Student perceptions of laboratory classroom activities and experimental physics practice

We report results from a study designed to identify links between undergraduate students' views about experimental physics and their engagement in multiweek projects in lab courses. Using surveys and interviews, we explored whether students perceived particular classroom activities to be features of experimental physics practice. We focused on 18 activities, including maintaining lab notebooks, fabricating parts, and asking others for help. Interviewees identified activities related to project execution as intrinsic to experimental physics practice based on high prevalence of those activities in interviewees' own projects. Fabrication-oriented activities were identified as conditional features of experimentation based on differences between projects, which interviewees attributed to variations in project resources. Interpersonal activities were also viewed as conditional features of experimentation, dependent upon one's status as novice or expert. Our findings suggest that students' views about experimental physics are shaped by firsthand experiences of their own projects and secondhand experiences of those of others.
Smart Healthcare for Diabetes: A COVID-19 Perspective.

Diabetes is considered as an critical comorbidity linked with the latest coronavirus disease 2019 (COVID-19) which spreads through Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2). The diabetic patients have higher threat of infection from novel corona virus. Depending on the region in the globe, 20% to 50% of patients infected with COVID-19 pandemic had diabetes. The current article discussed the risk associated with diabetic patients and also recommendation for controlling diabetes during this pandemic situation. The article also discusses the case study of COVID-19 at various regions around the globe and the preventive actions taken by various countries to control the effect from the virus. The article presents several smart healthcare solutions for the diabetes patients to have glucose insulin control for the protection against COVID-19.
Ventilatory Activity in Amphiuma Tridactylum and Siren lacertina (Amphibia, Caudata)

Siren lacertina obtains 75% of its oxygen and eliminates 60% of its carbon dioxide via the lungs (Guimond and Hutchison, 1973a), and Amphiuma tridactylum obtains 56% of its oxygen and releases 23% of its carbon dioxide aerially (Guimond and Hutchison, 1974). Siren can utilize up to 26%, and Amphiuma up to 50%, of the inspired oxygen (Guimond and Hutchison, 1973a; Toews, 1973), the most efficient oxygen utilization in amphibian lungs studied. (Guimond and Hutchison, 1974). These two aquatic genera have the smallest total surface area of respiratory capillaries per g found in amphibians (Czopek, 1962b), and lowest metabolic rate at comparable temperatures of all amphibians studies (Whitford, 1973; Guimond and Hutchison, 1976). These respiratory adaptations enable Siren and Amphiuma to survive in hypoxic, hypercarbic shallow and warm water which would be inhospitable to other amphibians
The large scale polarization explorer (LSPE) for CMB measurements: performance forecast

The measurement of the polarization of the Cosmic Microwave Background (CMB) radiation is one of the current frontiers in cosmology. In particular, the detection of the primordial divergence-free component of the polarization field, the B-mode, could reveal the presence of gravitational waves in the early Universe. The detection of such a component is at the moment the most promising technique to probe the inflationary theory describing the very early evolution of the Universe. We present the updated performance forecast of the Large Scale Polarization Explorer (LSPE), a program dedicated to the measurement of the CMB polarization. LSPE is composed of two instruments: LSPE-Strip, a radiometer-based telescope on the ground in Tenerife-Teide observatory, and LSPE-SWIPE (Short-Wavelength Instrument for the Polarization Explorer) a bolometer-based instrument designed to fly on a winter arctic stratospheric long-duration balloon. The program is among the few dedicated to observation of the Northern Hemisphere, while most of the international effort is focused into ground-based observation in the Southern Hemisphere. Measurements are currently scheduled in Winter 2022/23 for LSPE-SWIPE, with a flight duration up to 15 days, and in Summer 2022 with two years observations for LSPE-Strip. We describe the main features of the two instruments, identifying the most critical aspects of the design, in terms of impact on the performance forecast. We estimate the expected sensitivity of each instrument and propagate their combined observing power to the sensitivity to cosmological parameters, including the effect of scanning strategy, component separation, residual foregrounds and partial sky coverage. We also set requirements on the control of the most critical systematic effects and describe techniques to mitigate their impact. LSPE will reach a sensitivity in tensor-to-scalar ratio of σ r < 0.01, set an upper limit r < 0.015 at 95% confidence level, and improve constraints on other cosmological parameters.
Looking deeper into LIME

Interpretability of machine learning algorithm is a pressing need. Numerous methods appeared in recent years, but do they make sense in simple cases? In this paper, we present a thorough theoretical analysis of Tabular LIME. In particular, we show that the explanations provided by Tabular LIME are close to an explicit expression in the large sample limit. We leverage this knowledge when the function to explain has some nice algebraic structure (linear, multiplicative, or depending on a subset of the coordinates) and provide some interesting insights on the explanations provided in these cases. In particular, we show that Tabular LIME provides explanations that are proportional to the coefficients of the function to explain in the linear case, and provably discards coordinates unused by the function to explain in the general case.