Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying the Extent to Which Race and Gender Features Determine Identity in Commercial Face Recognition Algorithms

Human face features can be used to determine individual identity as well as demographic information like gender and race. However, the extent to which black-box commercial face recognition algorithms (CFRAs) use gender and race features to determine identity is poorly understood despite increasing deployments by government and industry. In this study, we quantified the degree to which gender and race features influenced face recognition similarity scores between different people, i.e. non-mated scores. We ran this study using five different CFRAs and a sample of 333 diverse test subjects. As a control, we compared the behavior of these non-mated distributions to a commercial iris recognition algorithm (CIRA). Confirming prior work, all CFRAs produced higher similarity scores for people of the same gender and race, an effect known as "broad homogeneity". No such effect was observed for the CIRA. Next, we applied principal components analysis (PCA) to similarity score matrices. We show that some principal components (PCs) of CFRAs cluster people by gender and race, but the majority do not. Demographic clustering in the PCs accounted for only 10 % of the total CFRA score variance. No clustering was observed for the CIRA. This demonstrates that, although CFRAs use some gender and race features to establish identity, most features utilized by current CFRAs are unrelated to gender and race, similar to the iris texture patterns utilized by the CIRA. Finally, reconstruction of similarity score matrices using only PCs that showed no demographic clustering reduced broad homogeneity effects, but also decreased the separation between mated and non-mated scores. This suggests it's possible for CFRAs to operate on features unrelated to gender and race, albeit with somewhat lower recognition accuracy, but that this is not the current commercial practice.
Seed coat microsculpturing in Gingko biloba L. cultivars

This article presents the results of a study on seed coat micromorphology and epicuticular structure of Ginkgo biloba cultivars. The micromorphology of the seed coat of 10 cultivars and one clone of female G. biloba were analysed. The taxa differed in the size and shape. Homogeneous epicuticular wax deposited in the form of wax tubules on the sarcotesta and sclerotesta surfaces. There were great differences in wax between the outer and inner layer of the sarcotesta. In the endotesta wax was diversified in the form of tubules, platelets or it was mixed. The article includes descriptions and illustrations of several micromorphological features which have not been published previously. The results of the SEM and LM investigation confirmed the taxonomic significance of the micromorphological traits in the Ginkgo genus. In the seeds many characters are present in of all the taxa and may be typical of Ginkgo. Key wordS: Ginkgo biloba, seed coat sculpture, SEM, LM
Nucleosynthetic yields of Z = 10−5 intermediate-mass stars

Context. Observed abundances of extremely metal-poor stars in the Galactic halo hold clues for understanding the ancient universe. Interpreting these clues requires theoretical stellar models in a wide range of masses in the low-metallicity regime. The existing literature is relatively rich with extremely metal-poor massive and low-mass stellar models. However, relatively little information is available on the evolution of intermediate-mass stars of Z ≲ 10−5, and the impact of the uncertain input physics on the evolution and nucleosynthesis has not yet been systematically analysed. Aims. We aim to provide the nucleosynthetic yields of intermediate-mass Z = 10−5 stars between 3 and 7.5 M⊙, and quantify the effects of the uncertain wind rates. We expect these yields could eventually be used to assess the contribution to the chemical inventory of the early universe, and to help interpret abundances of selected C-enhanced extremely metal-poor (CEMP) stars. Methods. We compute and analyse the evolution of surface abundances and nucleosynthetic yields of Z = 10−5 intermediate-mass stars from their main sequence up to the late stages of their thermally pulsing (Super) AGB phase, with different prescriptions for stellar winds. We use the postprocessing code MONSOON to compute the nucleosynthesis based on the evolution structure obtained with the Monash-Mount Stromlo stellar evolution code MONSTAR. By comparing our models and others from the literature, we explore evolutionary and nucleosynthetic trends with wind prescriptions and with initial metallicity (in the very low-Z regime). We also compare our nucleosynthetic yields to observations of CEMP-s stars belonging to the Galactic halo. Results. The yields of intermediate-mass extremely metal-poor stars reflect the effects of very deep or corrosive second dredge-up (for the most massive models), superimposed with the combined signatures of hot-bottom burning and third dredge-up. Specifically, we confirm the reported trend that models with initial metallicity Zini ≲ 10−3 give positive yields of 12C, 15N, 16O, and 26Mg. The 20Ne, 21Ne, and 24Mg yields, which were reported to be negative at Zini ≳ 10−4, become positive for Z = 10−5. The results using two different prescriptions for mass-loss rates differ widely in terms of the duration of the thermally pulsing (Super) AGB phase, overall efficiency of the third dredge-up episode, and nucleosynthetic yields. We find that the most efficient of the standard wind rates frequently used in the literature seems to favour agreement between our yield results and observational data. Regardless of the wind prescription, all our models become N-enhanced EMP stars.
Stochastic Models of Neural Synaptic Plasticity

In neuroscience, learning and memory are usually associated to long-term changes of connection strength between neurons. In this context, synaptic plasticity refers to the set of mechanisms driving the dynamics of neuronal connections, called synapses and represented by a scalar value, the synaptic weight. A Spike-Timing Dependent Plasticity (STDP) rule is a biologically-based model representing the time evolution of the synaptic weight as a functional of the past spiking activity of adjacent neurons. If numerous models of neuronal cells have been proposed in the mathematical literature, few of them include a variable for the time-varying strength of the connection. In this article, a new, general, mathematical framework to study the phenomenon of synaptic plasticity associated to STDP rules is introduced. A system composed of two neuronal cells connected by a single synapse is investigated and a stochastic process describing its dynamical behavior is presented and analyzed. The notion of plasticity kernel is introduced as a key component of plastic neural networks models. We show that a large number of STDP rules from neuroscience and physics applied to neural systems can be represented by this formalism. Experiments show that long-term synaptic plasticity evolves on a much slower timescale than the cellular mechanisms driving the activity of neuronal cells. For this reason a scaling model of our stochastic model is also introduced and averaging principles for a sub-class of plasticity kernels are stated, and proved in a companion paper. These results are used to analyze two STDP models widely used in applied physics: Pair-based rules and calcium-based rules. We compare results of computational neuroscience on models of timing-based synaptic plasticity with our results derived from averaging principles.
Quantile regression with ReLU Networks: Estimators and minimax rates

Quantile regression is the task of estimating a specified percentile response, such as the median, from a collection of known covariates. We study quantile regression with rectified linear unit (ReLU) neural networks as the chosen model class. We derive an upper bound on the expected mean squared error of a ReLU network used to estimate any quantile conditional on a set of covariates. This upper bound only depends on the best possible approximation error, the number of layers in the network, and the number of nodes per layer. We further show upper bounds that are tight for two large classes of functions: compositions of Holder functions and members of a Besov space. These tight bounds imply ReLU networks with quantile regression achieve minimax rates for broad collections of function types. Unlike existing work, the theoretical results hold under minimal assumptions and apply to general error distributions, including heavy-tailed distributions. Empirical simulations on a suite of synthetic response functions demonstrate the theoretical results translate to practical implementations of ReLU networks. Overall, the theoretical and empirical results provide insight into the strong performance of ReLU neural networks for quantile regression across a broad range of function classes and error distributions. All code for this paper is publicly available at this https URL.
Minimax Classification with 0-1 Loss and Performance Guarantees

Supervised classification techniques use training samples to find classification rules with small expected 0-1 loss. Conventional methods achieve efficient learning and out-of-sample generalization by minimizing surrogate losses over specific families of rules. This paper presents minimax risk classifiers (MRCs) that do not rely on a choice of surrogate loss and family of rules. MRCs achieve efficient learning and out-of-sample generalization by minimizing worst-case expected 0-1 loss w.r. t. uncertainty sets that are defined by linear constraints and include the true underlying distribution. In addition, MRCs' learning stage provides performance guarantees as lower and upper tight bounds for expected 0-1 loss. We also present MRCs' finite-sample generalization bounds in terms of training size and smallest minimax risk, and show their competitive classification performance w.r. t. state-of-the-art techniques using benchmark datasets.
Categorical Semantics of Cyber-Physical Systems Theory

Cyber-physical systems require the construction and management of various models to assure their correct, safe, and secure operation. These various models are necessary because of the coupled physical and computational dynamics present in cyber-physical systems. However, to date the different model views of cyber-physical systems are largely related informally, which raises issues with the degree of formal consistency between those various models of requirements, system behavior, and system architecture. We present a category-theoretic framework to make different types of composition explicit in the modeling and analysis of cyber-physical systems, which could assist in verifying the system as a whole. This compositional framework for cyber-physical systems gives rise to unified system models, where system behavior is hierarchically decomposed and related to a system architecture using the systems-as-algebras paradigm. As part of this paradigm, we show that an algebra of (safety) contracts generalizes over the state of the art, providing more uniform mathematical tools for constraining the behavior over a richer set of composite cyber-physical system models, which has the potential of minimizing or eliminating hazardous behavior.
Online non-convex optimization with imperfect feedback

We consider the problem of online learning with non-convex losses. In terms of feedback, we assume that the learner observes - or otherwise constructs - an inexact model for the loss function encountered at each stage, and we propose a mixed-strategy learning policy based on dual averaging. In this general context, we derive a series of tight regret minimization guarantees, both for the learner's static (external) regret, as well as the regret incurred against the best dynamic policy in hindsight. Subsequently, we apply this general template to the case where the learner only has access to the actual loss incurred at each stage of the process. This is achieved by means of a kernel-based estimator which generates an inexact model for each round's loss function using only the learner's realized losses as input.
Tail bounds for the averaged empirical distribution on a geodesic in first-passage percolation.

We establish tail estimates for the averaged empirical distribution of edge weights along geodesics in first-passage percolation on $\mathbb{Z}^d$. Our upper bounds also come with exponentially decaying tail estimates for the empirical distribution. As an application, we show that if the edge weight distribution has finite positive moments of any order, then any limit point of the averaged empirical distribution of finite geodesics has finite positive moments of all orders.
Annual Reproductive Success of American Robins (Turdus migratorius) At the Northern Edge of Their Range

ABSTRACT High arctic latitudes are characterized by short summers with continuous daylight, high seasonality, and low temperatures. In stable bird populations, mortality risks associated with the harsh climate and/or the long migration to reach the Arctic should be balanced by increased recruitment to the population through increased fecundity. We report on annual reproductive success of the American Robin (Turdus migratorius) nesting at its most northerly geographic limits in Ivvavik National Park, Yukon Territory, Canada during the 2010–2012 breeding seasons. Our objective was to determine whether fecundity was increased relative to similar populations breeding at more southerly latitudes. We also examined inter-annual variation in breeding parameters, which we predicted would vary because of interannual variation in local weather conditions. Clutch completion date, clutch size, and fledglings per nest varied significantly among years. No re-nests or double-brooding were documented. There was a significant decrease in incubation period and increase in nest success and clutch size with increasing latitude. Nests in Ivvavik National Park contained more fledglings per successful nest than nests farther south, and the nestling period (11 days) was the shortest recorded for this species. The lack of double-brooding appears to be at least partially compensated by higher fecundity during the single breeding event, at this northerly location.
Interspecies analysis of the NCAM homophilic binding site

Previous studies have identified the sequence 243-KYSFNYDGSE-252 in the third irnmunoglobulin-like (Ig3) domain of chick NCAM as the homophilic binding site. Several reports suggest that the rodent NCAM Ig3 domain may not contain homophilic binding activity. To investigate these differences, a series of fusion proteins were created and tested in binding assays. A rat GST-Ig3 fusion protein showed negligible binding activity, confirming the absence of rat Ig3-mediated homophilic binding. Through the creation of chimeric fusion proteins in chick and rat Ig3, putative rat and human homophilic binding sequence have been identified. However, the rat sequence appeared to have a much lower binding affinity than the chick and human sequences. Further mutational analysis suggests that al1 NCAM species possess the arnino acid residues necessary to mediate homophilic binding, but this ability may be hindered by neighbouring residues. We suggest histidine244 to be responsible for disrupting Ig3-mediated homophilic binding in rat NCAM.
Effects of Different Levels of Clove Bud (Syzygium Aromaticum) Dietary Supplementation on Immunity, Antioxidant Status, and Performance in Broiler Chickens

One hundred fifty-one-day old of Cobb broiler chicks were used to investigate the effect of dietary clove bud supplementation on growth performance, immune response and antioxidant status of broiler chickens. Chicks were allotted into five equal groups as the first control that supplemented by the basal diet, the second vitamin E supplemented group fed on the basal diet with vitamin E and selenium supplementation in water, Clove I that fed a basal diet containing 0.5 g clove/kg diet, Clove II that fed a basal diet containing 1.0 g clove/kg diet, and Clove III that fed a basal diet containing 1.5 g clove/kg diet (3 rd , 4 th , and 5 th groups). The GC-MS analysis of an n -hexane extract of clove evidenced the presence of isoeugenol (21.38 %) as a major active ingredient of antioxidant potentials. Clove significantly increased the serum total protein, globulin, IgG, IgM, INF-γ, IL-10, muscle GSH levels, T.SOD, and GST activities. Whereas, the serum total cholesterol, TAG, and muscle MDA levels were significantly decreased. The obtained results stated that BWG, FCR, and PER were improved in Vit. E and Clove I supplemented groups respectively, compared to control and other clove supplemented groups. Although, higher doses of clove had no effect on growth performance parameters with enhancement of immunity and antioxidant activities in broiler chickens that concomitantly, provide a healthy broiler’s meat with less MDA that favorable to human consumption.
Development of avian influenza vaccine on the basis of structurally modified plant virus

Avian influenza is an infectious viral disease that affects various species of birds, including poultry (chicken, turkeys, ducks and geese). Vaccination is a key strategy in the prevention of epizootics and epidemics of influenza. Now, the actual problem is the development of rapid, safe and effective methods for the production of avian flu vaccines. The using of recombinant flu antigen is a promising approach for creating universal, safe and effective poultry flu vaccines. To increasing of low immunogenicity of recombinant antigens plant viruses and virus-like particles can be applied. We have previously shown that spherical particles (SPs) with unique adsorption property and immunostimulating activity. Here we design the candidate vaccine against the avian flu virus (H5N1). The complexes containing the antigenic determinants of the avian flu virus — hemagglutinin (HA) and the extracellular domain of the M2 matrix protein (M2e) presented on the surface of SPs were developed. By indirect immunofluorescence microscopy the specific antigenic activity of recombinant proteins adsorbed on the SPs surface were demonstrated. The SPs—HA-M2e (SPs—HA62/284-М2е) complexes were highly immunogenic. The candidate vaccine induced a strong humoral immune response to both antigenic determinants of avian flu A virus. HA and M2e adsorption on the SPs allowed a 10-fold increase in the production of blood antibodies to antigens in immunized animals. The advantage of this approach for the vaccine development is high efficiency based on the stability and adjuvant activity of SPs, safety and low cost of using plant viruses. Obtaining veterinary vaccines based on structurally modified plant viruses allows the creation of marker veterinary vaccines. Development and creation of marker vaccines is extremely important for the recovery of the poultry population in agro-industrial complexes. The proposed vaccine can be considered as a candidate recombinant vaccine against avian influenza virus.
Prevalence and identification of subclinical mastitis in cows at BLRI Regional Station, Sirajganj, Bangladesh -

Objective: The study was conducted to assess the prevalence of subclinical mastitis in dairy cows at Baghabari milk shed area of Sirajganj and Pabna districts in Bangladesh. Materials and methods: A total of 300 milk samples were collected from crossbred dairy cows, and the milk samples were subjected for using California Mastitis Test (CMT). Besides, data related to farm management were taken from 60 farmers through direct interviews. The CMT was compared with White Slide Test (WST) and Surf Field Mastitis Test (SFMT). The samples showing strong positive reaction to mastitis by CMT were used for the isolation of associated bacteria using conventional bacteriological examinations and biochemical properties. The isolated bacteria were subjected for antibiogram studies by disc diffusion method. Results: Out of 300 samples, 153 (51%) revealed positive reactions denoting that the cows were suffering from subclinical mastitis. Of the 153 samples, 39(13%) were trace-positive, 56(18.56%) were weak-positive, 33(11%) were distinct-positive, and the rest 25(8.3%) samples were strongly positive. In comparison economically among CMT, WST and SFMT, SFMT was found to be the cheapest and easiest. In this study, the cows were mostly infected with mixed infection with Staphylococcus spp. , Streptococcus spp. , Escherichia coli, Salmonella spp. , and some cows had single bacterial infection. It was observed that most of the microorganisms were sensitive to Gentamycin, Amoxicillin and Ceftriaxone, and were resistant to Penicillin, Ciprofloxacin and Colistin sulphate. Conclusion: Overall prevalence of subclinical mastitis in the crossbred dairy cows at Sirajganj and Pabna district is 51%. It indicates that subclinical mastitis is a major threat for dairy industry in the studied areas. Early detection and appropriate preventive measures are suggestive to successful control of the disease.
Implementation and optimization of a large-scale ENU mouse mutagenesis screen and characterisation of five ENU-induced limb mutant lines

Aim of this thesis was the implementation of an ENU mouse mutagenesis screen in order to identify and further analyse mouse models for human inherited diseases. More than 30.000 animals were assessed, and more than 400 lines with defined inherited phenotypes were established. As proof-of-principle, five mutant lines with limb anomalies were phenotypically characterised and the molecular alterations causing the phenotype were identified. Four mutant lines represent novel alleles of the transcription factor Gli3 and new models for polydactyly in human. The fifth line serves as a model for polydactyly and early infertility in men caused by a mutation in a potentially new regulatory domain of the transcription factor Plzf.
Missense mutations of NCPAG gene affect calving ease in Piedmontese cattle: preliminary evidences

Abstract A previous genome scan on 323 Piedmontese individuals identified a cluster of 13 SNPs significantly associated with direct calving ease and centred on the three genes LAP3, LCORL and NCAPG in chromosome 6. We investigated missense mutations affecting calving ease in Piedmontese cattle in the identified region using sequences from the whole exome in eight Piedmontese individuals chosen from the extremes of the direct calving ease estimated breeding values distribution for this trait. The present study has not found missense variants in LAP3 and LCORL, while two were identified on NCAPG by three different variant calling methods. Other gene candidates in the same region harbour missense mutations, such as PPM1K, PKD2, SPP1 and MEPE, but both SIFT analysis and chi-square test on frequency of alleles make us hypothesise that NCAPG is the single gene responsible for the trait variation. The two SNPs on NCAPG are in complete linkage disequilibrium in our samples; therefore, further investigations are needed in order to discriminate their role.