Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology for Efficient CNN Architectures in Profiling Attacks

The side-channel community recently investigated a new approach, based on deep learning, to significantly improve profiled attacks against embedded systems. Previous works have shown the benefit of using convolutional neural networks (CNN) to limit the effect of some countermeasures such as desynchronization. Compared with template attacks, deep learning techniques can deal with trace misalignment and the high dimensionality of the data. Pre-processing is no longer mandatory. However, the performance of attacks depends to a great extent on the choice of each hyperparameter used to configure a CNN architecture. Hence, we cannot perfectly harness the potential of deep neural networks without a clear understanding of the network’s inner-workings. To reduce this gap, we propose to clearly explain the role of each hyperparameters during the feature selection phase using some specific visualization techniques including Weight Visualization, Gradient Visualization and Heatmaps. By highlighting which features are retained by filters, heatmaps come in handy when a security evaluator tries to interpret and understand the efficiency of CNN. We propose a methodology for building efficient CNN architectures in terms of attack efficiency and network complexity, even in the presence of desynchronization. We evaluate our methodology using public datasets with and without desynchronization. In each case, our methodology outperforms the previous state-of-the-art CNN models while significantly reducing network complexity. Our networks are up to 25 times more efficient than previous state-of-the-art while their complexity is up to 31810 times smaller. Our results show that CNN networks do not need to be very complex to perform well in the side-channel context.
The roles of herbivory and omnivory in early dinosaur evolution

ABSTRACT Herbivorous and omnivorous dinosaurs were rare during the Carnian stage of the Late Triassic. By contrast, the succeeding Norian stage witnessed the rapid diversification of sauropodomorphs and the rise of the clade to ecological dominance. Ornithischians, by contrast, remained relatively rare components of dinosaur assemblages until much later in the Mesozoic. The causes underlying the differential success of ornithischians and sauropodomorphs remain unclear, but might be related to trophic specialisation. Sauropodomorphs replaced an established herbivore guild consisting of rhynchosaurs, aetosaurs and basal synapsids, but this faunal turnover appears to have been opportunistic and cannot be easily attributed to either competitive interactions or responses to floral change. Consideration of diversity patterns and relative abundance suggests that the ability to eat plants might have been a major factor promoting sauropodomorph success, but that it was less important in the early evolution of Ornithischia. On the basis of current evidence it is difficult to determine the diet of the ancestral dinosaur and scenarios in which omnivory or carnivory represent the basal condition appear equally likely.
Chronic alcohol consumption dysregulates innate immune response to SARS-1 CoV-2 in the lung 2

2 Abstract 26 Alcohol consumption is widespread with over half of the individuals over 18 years of age 27 in the U.S. reporting alcohol use in the last 30 days. Moreover, 9 million Americans 28 engaged in binge or chronic heavy drinking (CHD) in 2019. CHD negatively impacts 29 pathogen clearance and tissue repair, including in the respiratory tract, thereby 30 increasing susceptibility to infection. Although, it has been hypothesized that chronic 31 alcohol consumption negatively impacts COVID-19 outcomes; the interplay between 32 chronic alcohol use and SARS-CoV-2 infection outcomes has yet to be elucidated. 33 Therefore, in this study we investigated the impact of chronic alcohol consumption on 34 SARS-CoV-2 anti-viral responses in bronchoalveolar lavage cell samples from humans 35 with alcohol use disorder and rhesus macaques that engaged in chronic drinking. Our 36 data show that in both humans and macaques, the induction of key antiviral cytokines 37 and growth factors was decreased with chronic ethanol consumption. Moreover, in 38 macaques fewer differentially expressed genes mapped to Gene Ontology terms 39 associated with antiviral immunity following 6 month of ethanol consumption while TLR 40 signaling pathways were upregulated. These data are indicative of aberrant 41 inflammation and reduced antiviral responses in the lung with chronic alcohol drinking. 42 43
How Skill Requirements Affect the Likelihood of Recruitment of Older Workers in Poland

This article analyses the role of age stereotypes in the employability of older people. Unlike in existing studies, we shift emphasis from a direct consideration of stereotypes, focusing instead on skill requirements during recruitment. Using five waves of an employer survey from Poland, we assess how the likelihood of recruiting people over 50 years old depends on the skill requirements of the post. This study uses a real-life framework by referring to existing vacancies and actual requirements that reflect labour demands at the scale of an entire national labour market. The results suggest that some requirements lead to age bias during recruitment, and the chances of an older candidate being hired are especially hindered in jobs requiring computer, physical, social, creative and training skills. By illustrating an indirect link between age stereotypes and age discrimination, this study contributes to an understanding of the mechanisms that reduce employability of older people.
Extreme seasonal droughts and floods in Amazonia: causes, trends and impacts

This paper reviews recent progress in the study and understanding of extreme seasonal events in the Amazon region, focusing on drought and floods. The review includes a history of droughts and floods in the past, in the present and some discussions on future extremes in the context of climate change and its impacts on the Amazon region. Several extreme hydrological events, some of them characterized as ‘once in a century’, have been reported in the Amazon region during the last decade. While abundant rainfall in various sectors of the basin has determined extreme floods along the river's main stem in 1953, 1989, 1999, 2009, 2012–2015, deficient rainfall in 1912, 1926, 1963, 1980, 1983, 1995, 1997, 1998, 2005 and 2010 has caused anomalously low river levels, and an increase in the risk and number of fires in the region, with consequences for humans. This is consistent with changes in the variability of the hydrometeorology of the basin and suggests that extreme hydrological events have been more frequent in the last two decades. Some of these intense/reduced rainfalls and subsequent floods/droughts were associated (but not exclusively) with La Niña/El Niño events. In addition, moisture transport anomalies from the tropical Atlantic into Amazonia, and from northern to southern Amazonia alter the water cycle in the region year‐to‐year. We also assess the impacts of such extremes on natural and human systems in the region, considering ecological, economic and societal impacts in urban and rural areas, particularly during the recent decades. In the context of the future climate change, studies show a large range of uncertainty, but suggest that drought might intensify through the 21st century.
Associations between Ectomycorrhizal Fungi and Bacterial Associations between Ectomycorrhizal Fungi and Bacterial Needle Endophytes in Pinus radiata: Implications for Biotic Needle Endophytes in Pinus radiata: Implications for Biotic Selection of Microbial Communities Selection of Microbial Communit

Studies of the ecological and evolutionary relationships between plants and their associated microbes have long been focused on single microbes, or single microbial guilds, but in reality, plants associate with a diverse array of microbes from a varied set of guilds. As such, multitrophic interactions among plant-associated microbes from multiple guilds represent an area of developing research
Impact of the baseline temporal selection on the ERD/ERS analysis for Motor Imagery-based BCI

Motor Imagery-based Brain-Computer Interfaces (MI-BCIs) are neurotechnologies that exploit the modulation of sensorimotor rhythms over the motor cortices, respectively known as Event-Related Desynchronization (ERD) and Synchronization (ERS). The interpretation of ERD/ERS is directly related to the selection of the baseline used to estimate them, and might result in a misleading ERD/ERS visualization. In fact, in BCI paradigms, if two trials are separated by a few seconds, taking a baseline close to the end of the previous trial could result in an over-estimation of the ERD, while taking a baseline too close to the upcoming trial could result in an under-estimation of the ERD. This phenomenon may cause a functional misinterpretation of the ERD/ERS phenomena in MI-BCI studies. This may also impair BCI performances for MI vs Rest classification, since such baselines are often used as resting states. In this paper, we propose to investigate the effect of several baseline time window selections on ERD/ERS modulations and BCI performances. Our results show that considering the selected temporal baseline effect is essential to analyze the modulations of ERD/ERS during MI-BCI use.
COMPARACIÓN DE CUATRO PROGRAMAS UTILIZADOS EN LA DETERMINACIÓN DE LA COMPOSICIÓN GENÉTICA ANCESTRAL DE LA POBLACIÓN ANTIOQUEÑA

The genetic structure of the population of Antioquia is complex and arises from the historical admixture of European, African and Amerindian populations. The genetic makeup of 849 Antioquian individuals was determined using a set of 75 ancestry informative markers and four computer programs based on Bayesian methods in order to infer the composition of ancestral admixture. A great European component (60%) was twice as high as the Amerindian contribution (28%), both with broad distributions, followed by a smaller African contribution (12%). The average number of generations since the admixture event was 11 generations per 100 cM, which makes this population a useful resource to implement admixture mapping studies. The usefulness of the marker set as well as the power and helpfulness of the computer programs were assessed.
Discontinuous Galerkin finite element approximation of quasilinear elliptic boundary value problems I: the scalar case

We develop a one-parameter family of hp-version discontinuous Galerkin finite element methods, parameterised by θ ∈ [-1, 1], for the numerical solution of quasilinear elliptic equations in divergence form on a bounded open set Q c R d , d ≥ 2. In particular, we consider the analysis of the family for the equation - ⊇. {μ(x, |⊇u|)⊇u) = f(x) subject to mixed Dirichlet-Neumann boundary conditions on 8Q. It is assumed that μ is a real-valued function, μ ∈C(Ω x [0, oo)), and there exist positive constants m μ and M μ such that m μ (t - s) ≤ μ(x, t)t - μ(x, s)s ≤ M μ (t - s) for t ≥ s ≥ 0 and all x ∈ Ω. Using a result from the theory of monotone operators for any value of θ ∈ [-1, 1], the corresponding method is shown to have a unique solution μ DG in the finite element space. If u ∈ C 1 (Q) ∩ H k (Ω), k ≥ 2, then with discontinuous piecewise polynomials of degree p ≥ 1, the error between u and μ DG , measured in the broken H 1 (Ω)-norm, is O(h s-1 /p k-3/2 ), where 1 ≤ s≤ min{p + 1, k}.
A Portable Vision-Based Head Tracking Exergame Solution for Neck Rehabilitation

The current practice of neck rehabilitation is done through laser-pointing devices in a physical setup or Virtual Reality head-mounted devices, whereby the patient will control and navigate a laser beam to follow a specific pattern. These setups are cumbersome to the patient. We propose a portable computer vision-based marker-less head tracking exergame for neck rehabilitation. Our system retargets head postures to control a game object and considers neck mobility while incorporating movement modulation during posture overcompensation. This system would be tailored to the specific patient in the steps of automatic calibration and gameplay interaction. We used the head and body pose to calibrate the game scene dimensions, and the upper body joint angles to feedback the posture over-compensation in the form of gameplay variables augmentation. From our testing, it has shown that this is a viable exergame solution that could be adopted for neck exercise.
Long lead rainfall forecasts for the Australian sugar industry

Rainfall variability is a crucial element that impinges on the success of sugarcane growing regions around the world. As the scientific community and industry personnel gain more experience at working participatively, the ability of long‐range rainfall forecasts to reduce the risk and uncertainty associated with decisions impacted by rainfall variability has become increasingly recognized. Some important decisions, however, require knowing the chances of rain at early lead times that span the austral autumn period. These types of decisions remain largely unassisted by climate forecasting technologies owing to the boreal spring (austral autumn) persistence barrier. Taking the Australian sugar industry as a case study example, this article explores the capability of a long lead statistical El Niño Southern Oscillation phenomenon (ENSO) prediction model to reduce the risk associated with decisions that must be made before autumn and are effected by rainfall anomalies post‐autumn. Results shown across all regions considered in this study indicated a higher risk of obtaining an above‐median rainfall index when the statistical model predicted La Niña type conditions to emerge post‐spring. For selected regions, this risk was reduced when the model predicted El Niño type conditions for the same period. In addition, the model would have provided an earlier indication of the likelihood of disruption due to wet harvest conditions in a year that devastated the Australian sugar industry. This benchmark study has highlighted the potential of an ENSO prediction model to aid industry decisions that have previously been made in isolation of probabilistic knowledge about future rainfall conditions. Copyright © 2007 Royal Meteorological Society
Specular 3D shape measurement with a compact fringe reflection system

The three-dimensional (3D) metrology for specular reflecting surfaces attracted much attention due to their various applications in optics, electronics, or semiconductor industry. Fringe reflection technique is an effective tool to measure the specular surface slopes (gradient information), and then reconstruct the surface shape from gradient. However, most of the fringe reflection systems are built up for middle size (~10,000 mm2) or larger size (~100,000 mm2) objects by using the off-the-shelf desktop displays. In order to measure samples with smaller size (~200 mm2) with higher measuring resolution, a compact fringe reflection system is proposed. The performance of the compact specular 3D shape measurement system is demonstrated with experiments.
Understanding the Sensitivity of a GCM Simulation of Amazonian Deforestation to the Specification of Vegetation and Soil Characteristics

Abstract The experiment reported on here presents a realistic portrayal of Amazonian deforestation that uses measurements of vegetation characteristics, taken as part of the Anglo–Brazilian Amazonian Climate Observation Study field campaigns, to define the forest and replacement pasture vegetation in the Hadley Centre GCM. The duration of the main experiment (10 yr) leads to greater confidence in assessing regional changes than in previous shorter experiments. Complete removal of the Amazonian forest produced area-mean changes that resemble earlier experiments with decreases in evaporation of 0.76 mm day−1 (18%) and rainfall of 0.27 mm day−1 (4%) and a rise in surface temperature of 2.3°C. However, the relative changes in magnitude indicate that increased moisture convergence partly compensates for the reduced evaporation, in contrast to many previous deforestation experiments. Results also showed large regional variations in the change in annual mean rainfall over South America, with widespread decreases.
Reconstruction et augmentation simultanées de scènes planes par morceaux Simultaneous reconstruction and augmentation of piecewise planar surfaces

A simultaneous localization and mapping (SLAM) method is presented, which is particularly suited to AR applications. The method is based on inter-image tracking of planar surfaces, whose intersections with a reference plane are automatically extracted using a particle ﬁlter. These intersections are used to clean up the ambiguity of the SFM problem using a single plane, and to get the equations of the intersecting planes with the reference plane. A semi-automatic system is proposed, which requires minimum intervention from the user, who only has to aim the planes to be integrated with the camera , and validate or cancel the solutions generated by the system. Different strategies of particle ﬁltering are compared on synthetical data, and a complete use of the interactive system is presented on a real scene. Finally, preliminary results are shown that illustrate how the method can be extended to a fully automatic SLAM system.
Improving High‐Impact Weather Forecasts

To accelerate improvements in 1- to 14-day high-impact weather forecasts, the World Meteorological Organization's (WMO) World Weather Research Programme established the Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) in 2005. The key objectives of TIGGE are enhancing international collaboration on ensemble prediction, determining new methods for combining ensembles from different sources, gaining a deeper understanding of forecast error and the feasibility of interactive ensemble systems, and developing a prototype for a future Global Interactive Forecasting System (GIFS).
Contamination of roadside soil and vegetation with cadmium, nickel, lead, and zinc

MOTOR VEHICLES CONTAMINATE ROADSIDE SOILS AND VEGETATION WITH FOUR HEAVY METAL ATMOSPHERIC POLLUTANTS. THE CONTAMINATION HAS BEEN CORRELATED WITH COMPOSITION OF GASOLINE, MOTOR OIL, AND CAR TIRES. THESE CONCENTRATIONS DECREASE WITH DISTANCE FROM TRAFFIC AND WITH DEPTH IN SOIL PROFILE. IN SPITE OF THE DEPENDENCE OF ROADSIDE CADMIUM, NICKEL, LEAD, AND ZINC ON TRAFFIC, IT APPEARS THAT HIGH CONCENTRATIONS OF ONE METAL IN THE SOIL DO NOT NECESSARILY ENTAIL HIGH CONCENTRATIONS OF ANOTHER ONE OF THE METALS. /AUTHOR/
Foraminiferal responses to arsenic in a shallow-water hydrothermal system in papua new guinea and in the laboratory

xiii CHAPTER 1. ARSENIC IN THE ENVIRONMENT AND THE ENVIRONMENTAL SETTING AROUND TUTUM BAY, AMBITLE ISLAND, PNG 1 1.1 Overview of Dissertation Research 1 1.2 Environmental Setting 4 1.2. 1 Regional Context 4 1.2. 2 Vent Fluid Properties 13 1.2. 3 Other Environmental Parameters 20 1.3 Arsenic in the Environment 27 1.4 Arsenic Chemistry 32 CHAPTER 2. TAXONOMY OF THE FORAMINIFERA OF TUTUM BAY, AMBITLE ISLAND, PAPUA NEW GUINEA 35 2.
Disodium cromoglycate in the treatment of chronic proctitis.

SUMMARY The effect of topical disodium cromoglycate (DSCG) has been examined in 30 patients with chronic active proctitis using a double-blind crossover trial. Each treatment period was four weeks and patients were given DSCG 200 mg by enema twice daily and 100 mg orally three times each day. Twenty-six patients completed the trial successfully, 14 responded to DSCG treatment, two improved with placebo, and 10 responded to neither. Patients who responded to DSCG had significantly more eosinophils in their rectal biopsies than those who failed to respond and in some instances the counts were very high. The findings support the hypothesis that an allergic reaction is important in the pathogenesis of proctitis.
Variations of U.S. Regional Precipitation and Simulations by the NCEP CFS: Focus on the Southwest

Abstract Variations of U.S. regional precipitation in both observations and free-run experiments with the NCEP Climate Forecast System (CFS) are investigated. The seasonality of precipitation over the continental United States and the time–frequency characteristics of precipitation over the Southwest (SW) are the focus. The differences in precipitation variation among different model resolutions are also analyzed. The spatial distribution of U.S. precipitation is characterized by high values over the East and the West Coasts, especially over the Gulf Coast and southeast states, and low values elsewhere except over the SW in summer. A large annual cycle of precipitation occurs over the SW, northern plains, and the West Coast. Overall, the CFS captures the above features reasonably well, except for the SW. However, it overestimates the precipitation over the western United States, except the SW in summer, and underestimates the precipitation over the central South, except in springtime. It also overestimate.
On the need for a theory of wildland fire spread

We explore the basis of understanding wildland fire behaviour with the intention of stimulating curiosity and promoting fundamental investigations of fire spread problems that persist even in the presence of tremendous modelling advances. Internationally, many fire models have been developed based on a variety of assumptions and expressions for the fundamental heat transfer and combustion processes. The diversity of these assumptions raises the question as to whether the absence of a sound and coherent fire spread theory is partly responsible. We explore the thesis that, without a common understanding of what processes occur and how they occur, model reliability cannot be confirmed. A theory is defined as a collection of logically connected hypotheses that provide a coherent explanation of some aspect of reality. Models implement theory for a particular purpose, including hypotheses of phenomena and practical uses, such as prediction. We emphasise the need for theory and demonstrate the difference between theory and modelling. Increasingly sophisticated fire management requires modelling capabilities well beyond the fundamental basis of current models. These capabilities can only be met with fundamental fire behaviour research. Furthermore, possibilities as well as limitations for modelling may not be known or knowable without first having the theory.
D-ViSA: A Dataset for Detecting Visual Sentiment from Art Images

Detecting emotions evoked by art has been receiving great attention recently. Although previous works provide a variety of datasets consisting of art images and corresponding emotion labels, little attention has been paid to the continuous and dimensional characteristics of human emotions, especially in the domain of art. We propose a dataset for detecting visual sentiment from art images, D-ViSA, whose labels consist of both categorical and dimensional emotion labels which can be implemented in a wide range of visual sentiment analysis research regarding art. We compare several deep learning baselines in two specific tasks, single-feature, and multi-feature dimensional emotion regression. Our experiments lead to the conclusion that our dataset is plausible for both regression tasks with deep learning baselines. We assume that our dataset contributes to the field of artwork analysis and provides insights into human emotions evoked by art. The dataset is available at https://github.com/dxlabskku/D-ViSA