Miracle-dz/UniFAR-FTUs huggingface dataset:
Are facial attributes adversarially robust?

Facial attributes are emerging soft biometrics that have the potential to reject non-matches, for example, based on mismatching gender. To be usable in stand-alone systems, facial attributes must be extracted from images automatically and reliably. In this paper, we propose a simple yet effective solution for automatic facial attribute extraction by training a deep convolutional neural network (DCNN) for each facial attribute separately, without using any pre-training or dataset augmentation, and we obtain new state-of-the-art facial attribute classification results on the CelebA benchmark. To test the stability of the networks, we generated adversarial images - formed by adding imperceptible non-random perturbations to original inputs which result in classification errors - via a novel fast flipping attribute (FFA) technique. We show that FFA generates more adversarial examples than other related algorithms, and that DCNNs for certain attributes are generally robust to adversarial inputs, while DCNNs for other attributes are not. This result is surprising because no DCNNs tested to date have exhibited robustness to adversarial images without explicit augmentation in the training procedure to account for adversarial examples. Finally, we introduce the concept of natural adversarial samples, i.e., images that are misclassified but can be easily turned into correctly classified images by applying small perturbations. We demonstrate that natural adversarial samples commonly occur, even within the training set, and show that many of these images remain misclassified even with additional training epochs. This phenomenon is surprising because correcting the misclassification, particularly when guided by training data, should require only a small adjustment to the DCNN parameters.
Career Patterns of Doctoral Graduates: Evidence from Estonia

Considering the resources that countries invest in training people at doctorate level we can easily claim that PhDs are among the most invested ‘brains’ in each country. Yet what is missing from the discussion is what happens with their career after they gain their PhD. Based on two studies we reveal the job-related movements (career) of PhDs from Estonia. The results signpost a great share of heterogeneity across research fields – a diversity that has considerable effect on how universities can manage their academic workforce and their career, but also, factors that shape movements between the academic and non-academic labour market.
Quantitative Evaluation of Diffusion and Dynamic Contrast-Enhanced MR in Tumor Parenchyma and Peritumoral Area for Distinction of Brain Tumors

Purpose To quantitatively evaluate the diagnostic efficiency of parameters from diffusion and dynamic contrast-enhanced MR which based on tumor parenchyma (TP) and peritumoral (PT) area in classification of brain tumors. Methods 45 patients (male: 23, female: 22; mean age: 46 y) were prospectively recruited and they underwent conventional, DCE-MR and DWI examination. With each tumor, 10–15 regions of interest (ROIs) were manually placed on TP and PT area. ADC and permeability parameters (Ktrans, Ve, Kep and iAUC) were calculated and their diagnostic efficiency was assessed. Results In TP, all permeability parameters and ADC value could significantly discriminate Low- from High grade gliomas (HGG) (p<0.001); among theses parameters, Ve demonstrated the highest diagnostic power (iAUC: 0.79, cut-off point: 0.15); the most sensitive and specific index for gliomas grading were Ktrans (84%) and Kep (89%). While, in PT area, only Ktrans could help in gliomas grading (P = 0.009, cut-off point: 0.03 min-1). Moreover, in TP, mean Ve and iAUC of primary central nervous system lymphoma (PCNSL) and metastases were significantly higher than that in HGG (p<0.003). Further, in PT area, mean Ktrans (p≤0.004) could discriminate PCNSL from HGG and ADC (p≤0.003) could differentiate metastases with HGG. Conclusions Quantitative ADC and permeability parameters from Diffusion and DCE-MR in TP and PT area, especially DCE-MR, can aid in gliomas grading and brain tumors discrimination. Their combined application is strongly recommended in the differential diagnosis of these tumor entities.
Diving into the shallows: a computational perspective on large-scale shallow learning

In this paper we first identify a basic limitation in gradient descent-based optimization methods when used in conjunctions with smooth kernels. An analysis based on the spectral properties of the kernel demonstrates that only a vanishingly small portion of the function space is reachable after a polynomial number of gradient descent iterations. This lack of approximating power drastically limits gradient descent for a fixed computational budget leading to serious over-regularization/underfitting. The issue is purely algorithmic, persisting even in the limit of infinite data. To address this shortcoming in practice, we introduce EigenPro iteration, based on a preconditioning scheme using a small number of approximately computed eigenvectors. It can also be viewed as learning a new kernel optimized for gradient descent. It turns out that injecting this small (computationally inexpensive and SGD-compatible) amount of approximate second-order information leads to major improvements in convergence. For large data, this translates into significant performance boost over the standard kernel methods. In particular, we are able to consistently match or improve the state-of-the-art results recently reported in the literature with a small fraction of their computational budget. Finally, we feel that these results show a need for a broader computational perspective on modern large-scale learning to complement more traditional statistical and convergence analyses. In particular, many phenomena of large-scale high-dimensional inference are best understood in terms of optimization on infinite dimensional Hilbert spaces, where standard algorithms can sometimes have properties at odds with finite-dimensional intuition. A systematic analysis concentrating on the approximation power of such algorithms within a budget of computation may lead to progress both in theory and practice.
Composición y función de la comunidad microbiana relacionada con el ciclaje de nitrógeno en la rizosfera de Solanum tuberosum (BAHUIN) grupo phureja

In the S. tuberosum group phureja crops, mineral fertilizer and organic amendments are applied to meet the plants’ nutritional demands, however the effect of such practices on the associated rizospheric microbial communities are still unknown. Nitrogen plays an important role in agricultural production, and a great diversity of microorganisms regulates its transformation in the soil, affecting its availability for the plant. The aim of this study was to assess the structure of microbial communities related with the N cycle of S. tuberosum group phureja rizospheric soil samples, with contrasting physical-chemical properties and fertilization strategy. Few significant differences between the community composition at the phylum level were found, only Planctomycetes phylum was different between samples of different soil type and fertilization strategy. However, the analysis of nitrogen-associated functional groups made by ribotyping characterization, grouped soils in terms of such variables in a similar way to the physical-chemical properties. Major differences between soil samples were typified by higher percentages of the ribotypes from nitrite oxidation, nitrogen fixation and denitrification on organic amendment soils. Our results suggest that, the dominant rhizosphere microbial composition is very similar between soils, possibly as a result of population’s selection mediated by the rhizosphere effect. However, agricultural management practices in addition to edaphic properties of sampled areas, appear to affect some functional groups associated with the nitrogen cycling, due to differences found on soil’s physicalchemical properties, like the concentration of ammonium that seems to have an effect regulating the distribution and activity of nitrogen related functional groups in the S. tuberosum rhizosphere.
Expansion of HIV-1 screening and anti-retroviral treatment programs in a resource-poor setting: results from a faith-based organization in Jos, Plateau State, Nigeria.

BACKGROUND Until recently, availability of anti-retroviral therapy (ART) in Nigeria has been limited to government and university based programs. Through the United States' President's Emergency Plan For AIDS Relief (PEPFAR), additional funding has become available for the treatment of HIV-positive patients. OBJECTIVE To report the expansion of HIV-1 screening, enrollment in an ART program, and treatment outcomes over twelve months among HIV-positive patients at a nonprofit, non-governmental faith-based clinic providing free and holistic care in Jos City, Plateau State, Nigeria. DESIGN This was a retrospective analysis of HIV-1 screening and ART received by patients at Faith Alive Foundation Hospital (FAFH). From January through December 2005, voluntary counseling and testing (VCT) was freely available to all patients who requested it. Also beginning in December 2004, HIV-1 infected patients were enrolled in an expanded HIV/AIDS program at FAFH, where patients in clinical stages 3 or 4 based on World Health Organization (WHO) clinical classification, or had a CD4(+) cell count of less than 200/ml, were initiated on a simplified highly active ART (HAART) regimen through PEPFAR funding. Data from the first six quarters of the FAFH-PEPFAR ART program are presented here. Additionally, analysis of 645 patients who have received ART for one year, including changes in CD4(+) cell count from baseline is shown. RESULTS In 2005, a total of 7672 persons received VCT and 3869 (50.4%) HIV-1 positive results were found. From October 2004 to March 2006, the total number of patients enrolled in the FAFH HIV/AIDS program rose from 1330 to 5946 people. Over the same period, the number of patients who received ART increased from 302 to 1667. A majority of patients received an oral ART regimen consisting of generic nevirapine, lamivudine, and stavudine. The number of patients initiated on ART each quarter ranged from 57-578, and the number of deaths of patients on ART was between 12 and 21 people per quarter. Analysis of 645 patients initiated on ART during the first quarter of the FAFH-PEPFAR ART program revealed that the median CD4(+) cell count at baseline was 106/ml and the median increase was 173/ml (median time of follow-up, 7.0 months). CONCLUSIONS Comprehensive HIV/AIDS care has been significantly expanded at FAFH, a free and holistic medical center in Jos, Nigeria. Cumulative data from the first year of this PEPFAR-funded ART program indicated that promising outcomes are achievable through delivery of care at this faith-based medical center.
Vision-Based Imitation Learning in Heterogeneous Multi-Robot Systems: Varying Physiology and Skill

Imitation learning enables a learner to improve its abilities by observing others. Most robotic imitation learning systems only learn from demonstrators that are similar physically and in terms of skill level. In order to employ imitation learning in a heterogeneous multi-agent environment, we must consider both differences in skill, and physical differences (physiology, size). This paper describes an approach to imitation learning from heterogeneous demonstrators, using global vision. It supports learning from physiologically different demonstrators (wheeled and legged, of various sizes), and self-adapts to demonstrators with varying levels of skill. The latter allows different parts of a task to be learned from different individuals (that is, worthwhile parts of a task can still be learned from a poorly-performing demonstrator). We assume the imitator has no initial knowledge of the observable effects of its own actions, and train a set of Hidden Markov Models to create an understanding of the imitator’s own abilities. We then use a combination of tracking sequences of primitives and predicting future primitives from existing combinations of primitives, using forward models to learn abstract behaviors from demonstrations. This approach is evaluated using a group of heterogeneous robots that have been previously used in RoboCup soccer competitions.
A Statistical Model for Indoor UWB LOS Channels

SV/IEEE 802.15. 3a model has been the standard model for ultra-wide bandwidth (UWB) indoor non-line-of-sight (NLOS) wireless propagation, but for line-of-sight (LOS) case, it is not well defined. In this paper, a new statistical distribution model exclusive used for LOS environment is proposed based on investigation of the experimental data. By reducing the number of the visible random arriving clusters, the model itself and the parameters estimating of the corresponding model are simplified in comparison with SV/IEEE 802.15. 3a model. The simulation result indicates that the proposed model is more accurate in modeling small-scale LOS environment than IEEE model when considering cumulative distribution functions (CDFs) for the three key channel impulse response (CIR) statistics
Activation in Nonobese Diabetic Mice Genetic Control of T and B Lymphocyte

Type 1 diabetes in nonobese diabetic (NOD) mice is characterized by the inﬁltration of T and B cells into pancreatic islets. T cells bearing the TCR V (cid:1) 3 chain are disproportionately represented in the earliest stages of islet inﬁltration (insulitis) despite clonal deletion of most V (cid:1) 3 (cid:2) immature thymocytes by the mammary tumor virus-3 ( Mtv-3 ) superantigen (SAg). In this report we showed that a high frequency of NOD V (cid:1) 3 (cid:2) T cells that escape deletion are activated in vivo and that this phenotype is linked to the Mtv-3 locus. One potential mechanism of SAg presentation to peripheral T cells is by activated B cells. Consistent with this idea, we found that NOD mice harbor a signiﬁcantly higher frequency of activated B cells than nondiabetes-prone strains. These activated NOD B cells expressed cell surface molecules consistent with APC function. At the molecular level, the IgH repertoire of activated B cells in NOD mice was equivalent to resting B cells, suggesting a polyclonal response in vivo. Genetic analysis of the activated B cell phenotype showed linkage to Idd1 , the NOD MHC haplotype (H-2 g7 ). Finally, V (cid:1) 3 (cid:2) thymocyte deletion and peripheral T cell activation did not require B cells, suggesting that other APC populations are sufﬁcient to generate both Mtv-3 -linked phenotypes. These data provide insight into the genetic regulation of NOD autoreactive lymphocyte activation that may contribute to failure of peripheral tolerance and the pathogenesis of type I diabetes. The Journal of Immunology, 2001, 167: 7169–7179. 2 B ). Multiple LN sites (pancreatic, mesenteric, inguinal, and ax-illary) were compared for V (cid:1) 3 (cid:2) T cell CD69 and CD25 cell surface expression. No signiﬁcant difference in the percentages of CD69 (cid:2) or CD25 (cid:2) NOD V (cid:1) 3 (cid:2) T cells was observed between these LN sites (data not shown). Collectively, these results suggest a higher frequency of NOD V (cid:1) 3 (cid:2) T cells are systemically activated in vivo compared with other T cell subsets.
A unified architecture for DPA-resistant PRESENT

Recently, there is a new kinds of cryptographic algorithms are proposed to meet the requirements of “lightweight” applications. PRESENT is one of them, which is built based on 4-bit substitution transformation (S-box) and suitable for low cost hardware implementations. Usually, there needs two 4-bit S-boxes, Sp, ISp, for PRESENT encryption and decryption, in which ISp can be computed from Sp. Therefore, we proposed a unified architecture to supporting the operations of PRESENT encryption and decryption. There also exists a kind of power analysis attacks pose a serious threat on hardware based PRESENT. In order to resist against DPA, we proposed a new masking scheme for PRESENT, in which the nonlinear substitution needs to be carefully masked. In order to reduce the hardware resources for the proposed masking scheme, we reuse the masked Sp to generate masked ISp. The experimental results show that our proposed unified masked PRESENT takes up only one time larger than the unmasked existing design. But, it is obvious that our proposed design has the ability to defend against DPA.
View Invariant Appearance-Based Person Reidentification Using Fast Online Feature Selection and Score Level Fusion

Fast and robust person reidentification is an important task in multi-camera surveillance and automated access control. We present an efficient appearance-based algorithm, able to reidentify a person regardless of occlusions, distance to the camera, and changes in view and lighting. The use of fast online feature selection techniques enables us to perform reidentification in hyper-real-time for a multi-camera system, by taking only 10 seconds for evaluating 100 minutes of HD-video data. We demonstrate, that our approach surpasses current appearance-based state-of-the-art in reidentification quality and computational speed and sets a new reference in non-biometric reidentification.
Performance analysis of modulation techniques in multilevel inverters for direct grid connected photovoltaic arrays

Development of renewable energy has become crucial for the global warming and shortage of fossil fuel. Solar energy is one of the promising renewable energy to meet the energy crisis. One of the big disadvantage of solar array is the efficiency level remains between 14%–25%. So maximum power extraction and reduction of associate losses is a challenge for the researchers. Multilevel inverters are being used in grid connected photovoltaic arrays to enhance the output voltage. This paper analyses the performance of different existing and proposed modulation techniques for an 11 KV system applied in 15 level H bridge inverter in Matlab environment in a view to reduce the harmonics as well as switching loss.
Curvature Map-Based Magnetic Guidance for Automated Vehicles in an Urban Environment

Magnetic guidance is commonly used in real applications of automated vehicles for its reliability. However, due to the downward view of magnet detectors, the control of a vehicle based on magnetic guidance is difficult, particularly in an urban environment. This paper proposes the strategy of using a curvature map of magnets to carry out look-ahead control for magnetic guidance-based vehicles. First, a Gauss curve fitting-based lateral offset estimation method is proposed in the magnet localization to improve the robustness to sensors' noise. Then, the curvature of the road is generated based on a magnet-tracking algorithm, which records passed road segments by tracking every magnet detected by the magnetic sensor. Magnet-tracking results describe the relative position of the vehicle with respect to the reference road, whereas the curvature map contains forward road information. The fusion of these two sources of information gives a full description of the local road segment. Furthermore, to suppress noises, a simple local road model with a general form is used to fuse tracking results and curvature map information. Compared with magnetic guidance methods based on accurately positioned magnets, the proposed curvature map-based method boasts a simple map-generation process, in which the vehicle only needs to be driven manually along the reference trajectory once. Experiments on real application scenarios have verified the effectiveness of the proposed methods.
Overcoming methodological challenges in evolutionary psychological research on differential grandparental kin investment

Das Forschungsfeld der diskriminativen Fursorglichkeit von Groseltern hat unterschiedlicheste Befunde hervorgebracht um deren Erklarung verschiedene sozial-wissenschaftliche und evolutionarpsychologische Theorien konkurrieren. In dieser wissenschaftlichen Arbeit wurden verschiedenste Forschungsansatze der bisherigen Forschung miteinander verbunden. Mit Hilfe einer Stichprobe von 40 Familien, einschlieslich gegengeschlechtlicher Enkelkinder, beiden Elternteilen und allen vier Groseltern, wurden Geschlechtseffekte der Generationen und deren Interaktionen untersucht. Die retrospektiven Beurteilungen aller Generationen haben den bereits vielfach replizierten Geschlechtseffekt der Groseltern eindeutig nachgewiesen. Die Untersuchung konnte jedoch keinen Geschlechtseffekt der Eltern bzw. der groselterlichen Linie sowie keinen direkten Geschlechtseffekt der Enkelkinder aufzeigen. Lediglich die Kin-Keeper Theorie erfahrt vollstandige Unterstutzung durch die Daten. Theorien zur Geschlechtschromosomenvererbung bleiben weiter interessant, da sich einige gleichgeschlechtliche Praferenzen gezeigt haben.
Structural flexibility in proteins: impact of the crystal environment

MOTIVATION In the study of the structural flexibility of proteins, crystallographic Debye-Waller factors are the most important experimental information used in the calibration and validation of computational models, such as the very successful elastic network models (ENMs). However, these models are applied to single protein molecules, whereas the experiments are performed on crystals. Moreover, the energy scale in standard ENMs is undefined and must be obtained by fitting to the same data that the ENM is trying to predict, reducing the predictive power of the model. RESULTS We develop an elastic network model for the whole protein crystal in order to study the influence of crystal packing and lattice vibrations on the thermal fluctuations of the atom positions. We use experimental values for the compressibility of the crystal to establish the energy scale of our model. We predict the elastic constants of the crystal and compare with experimental data. Our main findings are (1) crystal packing modifies the atomic fluctuations considerably and (2) thermal fluctuations are not the dominant contribution to crystallographic Debye-Waller factors. AVAILABILITY The programs developed for this work are available as supplementary material at Bioinformatics Online.
Reduced miR-550a-3p leads to breast cancer initiation, growth, and metastasis by increasing levels of ERK1 and 2

Hyperactivation of the Ras/ERK pathway contributes to breast cancer initiation and progression, and recent evidence suggests aberrant signaling of miRNAs that regulate the Ras/ERK pathway play important roles during carcinogenesis and cancer progression. In this study, we demonstrate that miR-550a-3p expression is negatively correlated with levels of ERK1 and ERK2, two pivotal effectors in the Ras/ERK pathway. MiR-550a-3p gradually decreased during breast cancer initiation and progression and this reduction was a prognostic indicator of poorer overall survival (OS) and disease-free survival (DFS) among breast cancer patients. Our mechanistic studies demonstrated that miR-550a-3p exerts its tumor-suppressor role by directly repressing ERK1 and ERK2 protein expression, thereby suppressing the oncogenic ERK/RSK cascades, which reduced breast cancer cell viability, survival, migration, invasion, tumorigenesis, and metastasis. The inhibitory effects of miR-550a-3p were rescued by ectopic expression of ERK1 and/or ERK2. The novel connection between miR-550a-3p and ERK defines a new diagnostic and prognostic role for miR-550a-3p and highlights ERK inhibition as a candidate therapeutic target for breast cancers exhibiting hyperactivated Ras/ERK signaling.