Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution over Time of Magentic Dynamo Driven UV & X-ray Emissions of dG-M Stars and Effects on Hosted Planets

The evolution over time of the magnetic activity and the resulting X-ray and UV coronal and chromospheric emissions of main-sequence dG, dK, and dM stars with widely different ages are discussed. Young cool stars spin rapidly and have correspondingly very robust magnetic dynamos and strong coronal and chromospheric X-ray – UV (XUV) emissions. However, these stars spin-down with time as they lose angular momentum via magnetized winds and their magnetic generated activity and emissions significantly decrease. Studies of dK–dM stars over a wide range of ages and rotations show similar (but not identical) behavior. Particular emphasis is given to discussing the effects that XUV emissions have on the atmospheres and evolution of solar system planets as well as the increasing number of extrasolar planets found hosted by dG–dM stars. The results from modeling the early atmospheres of Venus, Earth and Mars using recently determined XUV irradiances and inferred winds of the young Sun are also briefly discussed. For example, the loss of water from juvenile Venus and Mars can be explained by action of the strong XUV emissions and robust winds of the young Sun. We also examine the effects of strong X-ray and UV coronal and chromospheric emissions (and frequent flares) that dM stars have on possible planets orbiting within their shrunken habitable zones (HZs) – located close to the low luminosity host stars (HZ ≤ 0.4 AU). Dwarf M stars make interesting targets for further study because of their deep outer convective zones (CZs), efficient dynamos, frequent flares and strong XUV emissions. Furthermore, a large fraction of dM stars are very old (>5 Gyr), which present intriguing possibilities for the development of highly advanced modes of intelligent life on planets that may orbit them.
Emergence of tigecycline-resistant Klebsiella pneumoniae ST11 clone in patients without exposure to tigecycline.

INTRODUCTION Tigecycline is a unique class of semi-synthetic glycylcyclines developed to treat infections caused by multidrug-resistant Klebsiella pneumoniae. In the past decades, eight tigecycline-resistant Acinetobacter baumannii isolates have been identified in Tehran and no Klebsiella pneumoniae has been reported. METHODOLOGY To elucidate the mechanism of K. pneumoniae efflux pump-mediated resistance, the expression of efflux pump genes (oqxA, oqxB, acrA, acrB, tolC) and regulators (acrR, ramA, marA, soxS, rarA, rob) was investigated by real-time RT-PCR. Multilocus sequence typing (MLST) of tigecycline-resistant strains was also performed. RESULTS Compared to the tigecycline sensitive strain K32 (negative control), all resistant strains showed higher expression levels of efflux genes and regulatory factors. Three tigecycline-resistant strains (K53, K67, K79) showed higher levels of rarA expression (38.1-fold, 41-fold and 24-fold, respectively) and oqxB pump gene (48.2-fold, 60-fold and 58-fold, respectively). The increased expression of acrB was associated with the expression of ramA. However, to the best of our knowledge, studies on the mechanisms of resistance of K. pneumoniae strains to tigecycline are limited, especially in developing countries such as Iran. CONCLUSIONS In the present study, we found that both AcrAB-TolC and OqxAB efflux pumps may play an important role in tigecycline resistance in K. pneumoniae isolates. Finally, the emergence of ST11 molecular type of resistant isolates should be monitored in hospitals to identify factors leading to tigecycline resistance.
Flavonoids in in vitro cultures of Astragalus hamosus

Astragalus hamosus contains valuable biologically active compounds, incl. flavonoids. The possibility for in vitro cultivation of the species as a source of important flavonoids was studied. Shoot and callus cultures were established and successfully cultivated on different nutrition media, complemented or not with growth regulators. An ultra-high performance liquid chromatography – high-resolution electrospray ionisation mass spectrometry (UHPLC-HRESIMS) qualitative and quantitative analysis of non-purified methanol extracts of these cultures was performed. It was found that the cultures produced rutin in comparable quantity. Interestingly, both shoots and callus cultures accumulated the rare triglycosides alcesefoliside and mauritianin. The quantity of mauritianin, biosynthesized in shoots, was significantly higher to that in callus cultures. Alcesefoliside, was in lower quantity, compared to mauritianin. In addition, callus cultures produced alcesefoliside trice as the shoots, besides their lower level of differentiation. These findings could serve as initial research to establish the value of in vitro cultures from A. hamosus as an alternative mean of production of pharmaceutically important flavonol glycosides.
NBER WORKING PAPER SERIES THE GREAT UNEQUALIZER: INITIAL HEALTH EFFECTS OF COVID-19 IN THE UNITED STATES

We measure inequities from the COVID-19 pandemic on mortality and hospitalizations in the United States during the early months of the outbreak. We discuss challenges in measuring health outcomes and health inequality, some of which are specific to COVID-19 and others that complicate attribution during most large health shocks. As in past epidemics, pre-existing biological and social vulnerabilities profoundly influenced the distribution of disease. In addition to the elderly, Hispanic, Black and Native American communities were disproportionately affected by the virus, particularly when assessed using the years of potential life lost metric. For example, Hispanic and Black Americans in 2020 saw 39.5 and 25 percent increases in excess mortality relative to trend, compared to a less than 15 percent increase for Whites; we find losses in potential years of life three to four times larger among Hispanic and Black compared to White Americans. Individual-level data from a commercially insured population show that otherwise similar Black and Hispanic enrollees were hospitalized due to COVID-19 at a higher rate than White enrollees. We provide a conceptual framework and initial empirical analysis which seek to shed light on contributors to pandemic-related health inequality, and suggest areas for future research. Marcella Alsan Kennedy School of Government Harvard University 79 John F. Kennedy St. Rubenstein Bldg R403 Cambridge, MA 02138 and NBER marcella_alsan@hks.harvard.edu Amitabh Chandra John F. Kennedy School of Government Harvard University 79 JFK Street Cambridge, MA 02138 and NBER amitabh_chandra@harvard.edu Kosali I. Simon O’Neill School of Public and Environmental Affairs Indiana University 1315 East Tenth Street Bloomington, IN 47405-1701 and NBER simonkos@indiana.edu
Hacking the Systems from Within

—Information security is a fundamental aspect of our current technological society. Side-Channel Attacks allow compromising a device using information leaked through its physical properties, such as the power consumption or the duration of certain operation. On the other hand, modern processors include power consumption sensors which can be accessed by its users. The goal of this research is to analyse the possibility and threat of a side-channel attack using the processors’ energy counters. This method aims for an attack without physical access to the device, in contrast with the usual usage of an oscilloscope. Challenges include the much lower sampling frequency and worst resolution, imposing new adaptations of the current attacking methods. For this article, an Intel processor was used to analyse and carry out a modulation attack against a simpliﬁed version of AES. Its performance was measured and results show that a detectable leakage exists which allows compromising the simpliﬁed version of the algorithm, but is not enough for the real one using the proposed method. Future evaluation of this leakage is proposed towards other methods and algorithms.
Approach for Face Spoof Detection Using KNN classifier

: In order to classify the spoofed as well as non-spoofed faces from images, the face spoof detection technique has been proposed. In order to analyze the textual features present within a test image, the DWT algorithm is applied. In order to classify the spoofed and non-spoofed features, the already existing approach used SVM classifier. However, the accuracy of results needs to be enhanced in the proposed work in order to identify the spoofed daces. In order to analyze the proposed approach, comparisons are made amongst the proposed and existing mechanisms in terms of accuracy and execution time
A Speed Control Algorithm for Planar Path Maneuvering

Abstract This paper considers the problem of speed control for vehicles maneuvering along planar paths. Maneuverability constraints are taken into account when determining a purposefully commanded forward speed which prevents a given vehicle from derailing when traversing a given path. A lookahead system is first developed to collect relevant path curvature information ahead of the vehicle. This system is able to maintain a constant along-path distance in front of the current vehicle location, even for paths that are not arc-length parameterized. A speed assignment algorithm is subsequently developed which employs both the lookahead system information and known vehicle maneuverability constraints to yield feasible speed commands. Finally, the behavior of the proposed speed control system is illustrated through simulations which also demonstrate its improved performance compared to using constant speed.
Explicit loss asymptotics in the gradient descent training of neural networks

Current theoretical results on optimization trajectories of neural networks trained by gradient descent typically have the form of rigorous but potentially loose bounds on the loss values. In the present work we take a different approach and show that the learning trajectory of a wide network in a lazy training regime can be characterized by an explicit asymptotic at large training times. Speciﬁcally, the leading term in the asymptotic expansion of the loss behaves as a power law L ( t ) ∼ Ct − ξ with exponent ξ expressed only through the data dimension, the smoothness of the activation function, and the class of function being approximated. Our results are based on spectral analysis of the integral operator representing the linearized evolution of a large network trained on the expected loss. Importantly, the techniques we employ do not require a speciﬁc form of the data distribution, for example Gaussian, thus making our ﬁndings sufﬁciently universal.
Initiation of Depleted Uranium Oxide and Spent Fuel Testing for the Spent Fuel Sabotage Aerosol Ratio Programme

Abstract The authors provide a detailed overview of an on-going, multinational test programme thatis developing aerosol data for some spent fuel sabotage scenarios on spent fuel transportand storage casks. Experiments are being performed to quantify the aerosolised materials plus volatilised fission products generated from actual spent fuel and surrogate materialtest rods, due to impact by a high-energy-density device. The programme participants in the United States plus Germany, France and the United Kingdom, part of the international Working Group for Sabotage Concerns of Transport and Storage Casks (WGSTSC) have strongly supported and coordinated this research programme. Sandia National Laboratories has the lead role for conducting this research programme; test programme support is provided by both the US Department of Energy and the US Nuclear Regulatory Commission. The authors provide a summary of the overall, multiphase test design and a description of all explosive containment and aerosol collection test components used. They focus on the recentlyinitiated tests on 'surrogate' spent fuel, unirradiated depleted uranium oxide and forthcoming actual spent fuel tests, and briefly summarise similar results from completed surrogate tests that used non-radioactive, sintered cerium oxide ceramic pellets in test rods.
Bulk hydrometeor optical properties for microwave and sub-millimetre radiative transfer in RTTOV-SCATT v13.0

Satellite observations of radiation in the microwave and sub-millimetre spectral regions (broadly from 1 to 1000 GHz) can have strong sensitivity to cloud and precipitation particles in the atmosphere. These particles (known as hydrometeors) scatter, absorb, and emit radiation according to their mass, composition, shape, internal structure, and orientation. Hence, microwave and sub-millimetre observations have applications including weather forecasting, geophysical retrievals and model validation. To simulate these observations requires a scattering-capable radiative transfer model and an estimate of the bulk optical properties of the hydrometeors. This article describes the module used to integrate single-particle optical properties over a particle size distribution (PSD) to provide bulk optical properties for the Radiative Transfer for TOVS microwave and sub-millimetre scattering code, RTTOV-SCATT, a widely used fast model. Bulk optical properties can be derived from a range of particle models including Mie spheres (liquid and frozen) and non-spherical ice habits from the Liu and Atmospheric Radiative Transfer Simulator (ARTS) databases, which include pristine crystals, aggregates, and hail. The effects of different PSD and particle options on simulated brightness temperatures are explored, based on an analytical two-stream solution for a homogeneous cloud slab. The hydrometeor scattering “spectrum” below 1000 GHz is described, along with its sensitivities to particle composition (liquid or ice), size and shape. The optical behaviour of frozen particles changes in the frequencies above 200 GHz, moving towards an optically thick and emission-dominated regime more familiar from the infrared. This region is little explored but will soon be covered by the Ice Cloud Imager (ICI).
A new decade for social changes

Human’s involvement with culture is a vital part of his life, but what happens when someone is blind or visually impaired (VI) and how Information and Communication Technologies (ICTs) help the access to cultural locations? The difficulties and limitations that blind and visually impaired (BVI) persons face while visiting museums or art exhibitions are of high importance. These limitations concern both the access to the location and the perception of the exhibits. This bibliographic research is divided into four main parts. In the first part of our paper we will analyze the difficulties that these people face as visitors in art exhibitions and how their disabilities affect an autonomous visit. Afterwards, we will refer to the importance of the disability arts when combined with ICTs. In the next part, we will mention the projects that are already applied or those for which efforts have been made globally for their implementation. These will be accompanied by recorded feedback from blind and visually impaired visitors. Finally, we will make a scheduled visit to the Tactual Museum of Athens in order to collect material on practices used in their exhibition and we shall record reactions from visually impaired visitors.
Journal of Agric. 2020 Vol. 20 No.1& 2. (Read-Only)

Pig is one of the most consumed meat across the globe. However, its production is limited by high cost of feed ingredients. Hence, the search for alternative cheap feed ingredients without any loss to animal’s performance is on the increase. The influence of different protein sources and feed types (wet or dry) was investigated on the growth performance, haematology and serum biochemistry of weaned pigs. Weight gain and feed conversion ratio were higher for soybean and full-fat soya-based diets. Feed and water intake were not significantly different amongst treatments. Nature of feed did not influence weight gain, feed intake and feed conversion ratio. Groundnut cake meal may compare with soybean meal in pig’s diet, but it may have to be supplemented with lysine, methionine or fish meal.
A new decade for social changes

Drought events were assessed using remote sensing index MODIS (MODerate resolution Imaging Spectroradiometer) and Standardized Precipitation Index (SPI) over the steppe regions of Algeria between 2000 and 2012. In this study, the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) were determined from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The VCI (Vegetation Condition Index) was based on the Normalized Difference Vegetation Index (NDVI) datasets. The TCI (Temperature Condition Index) was derived from land surface temperature (LST) datasets. The VCI and TCI were then combined to calculate the Vegetation Health Index (VHI). Also, the one-month Standardized Precipitation Index (SPI) data from rainfall stations in the study area was calculated. The results show that years of normal condition (least drought) were year 2006, 2009, 2010 and 2012. However, all indices recorded a drought with different classes for 2000, 2001, 2002, 2003, 2004, 2005, 2007,2008 and 2011 can be considered unusual conditions. According to the results obtained from this study, a large part of the study area is located in severe of drought classes that likely is related to the rainfall reduction and topographic characteristics of the area and poor vegetation, which need more attention to water resource management in this region.
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach

Rule sets are highly interpretable logical models in which the predicates for decision are expressed in disjunctive normal form (DNF, OR-of-ANDs), or, equivalently, the overall model comprises an unordered collection of if-then decision rules. In this paper, we consider a submodular optimization based approach for learning rule sets. The learning problem is framed as a subset selection task in which a subset of all possible rules needs to be selected to form an accurate and interpretable rule set. We employ an objective function that exhibits submodularity and thus is amenable to submodular optimization techniques. To overcome the difﬁculty arose from dealing with the exponential-sized ground set of rules, the subproblem of searching a rule is casted as another subset selection task that asks for a subset of features. We show it is possible to write the induced objective function for the subproblem as a difference of two submodular (DS) functions to make it approximately solvable by DS optimization algorithms. Overall, the proposed approach is simple, scalable, and likely to be beneﬁted from further research on submodular optimization. Experiments on real datasets demonstrate the effectiveness of our method.
Hybrid algorithm for optimisation of m-loop electric power distribution networks

A heuristic method using artificial neural networks (ANN) for designing m-loop electric power distribution networks is presented. The task is to connect transformer stations (with given locations and loads) into m loops in order to minimise the given aim function, subject to technical constraints. The problem of designing the described network is similar to the travelling salesman problem and is a NP-hard problem. As the optimisation criterion, the minimal annual cost of electric power network was chosen. The network structure obtained with use of ANN is improved in the last stage of the proposed algorithm by the simulated annealing method or by manual exchange of transformer stations. Definition of the problem, as well as a short algorithm and some results of tests performed on m-loop electric power network models, are presented in the paper.
HEALTH IMPACTS OF PM2.5 AND NO2 SHIP-RELATED AIR POLLUTION IN MATOSINHOS MUNICIPALITY, PORTUGAL

Air pollution is considered the most significant environmental risk to health, causing substantial economic consequences. International maritime traffic has been identified as a major air pollution source, emitting nitrogen oxides (NOx), sulphur oxides (SOx) and particulate matter (PM). Thus, this work aimed to study the local health impacts of PM2.5 and NO2 ship-related air pollution in Matosinhos municipality, where Leixões port is located (one of the major ports in Portugal), in 2014. Hourly shipping emissions were obtained using STEAM model with a resolution of 250 × 250 m for a 50 × 50 km domain. The contributions of PM2.5 and NO2 concentrations in Matosinhos were modelled using the AERMOD model. The annual mean background concentrations of PM2.5 and NO2 were acquired from the fixed monitoring stations of the QualAr network. Log-linear functions based on WHOHRAPIE relative risks (RR) for PM2.5 and NO2 all-cause natural mortality were used to calculate the excess of premature deaths. The costs associated with the health impacts were estimated as the product of the additional premature deaths and the value of statistical life (VSL). It was estimated that shipping emissions caused 15 additional deaths (95% CI 19–21), corresponding to 29 million € (95% CI 17–40) for the Matosinhos municipality in 2014. These results show that shipping emissions are an environmental concern that affects the Matosinhos municipality population.
Learning in Non-Cooperative Configurable Markov Decision Processes

The Conﬁgurable Markov Decision Process framework includes two entities: a Reinforcement Learning agent and a conﬁgurator that can modify some environmental parameters to improve the agent’s performance. This presupposes that the two actors have identical reward functions. What if the conﬁgurator does not have the same intentions as the agent? This paper introduces the Non-Cooperative Conﬁgurable Markov Decision Process, a framework that allows modeling two (possibly different) reward functions for the conﬁgurator and the agent. Then, we consider an online learning problem, where the conﬁgurator has to ﬁnd the best among a ﬁnite set of possible conﬁgurations. We propose two learning algorithms to minimize the conﬁgurator’s expected regret, which exploit the problem’s structure, depending on the agent’s feedback. While a naïve application of the UCB algorithm yields a regret that grows indeﬁnitely over time, we show that our approach suffers only bounded regret. Furthermore, we empirically validate the performance of our algorithm in simulated domains.
Pedestrian detection at daytime and nighttime conditions based on YOLO-v5

1Ingeniería en Electrónica, Automatización y Control, Universidad de las Fuerzas Armadas ESPE, Av. Gral. Rumiñahui s/n, PBX 171-5-231B, Sangolquí (Pichincha), Ecuador. 2Departamento de Eléctrica, Electrónica y Telecomunicaciones, Universidad de las Fuerzas Armadas ESPE, Av. Gral. Rumiñahui s/n, PBX 171-5-231B, Sangolquí (Pichincha), Ecuador. 3,∗Departamento de Sistemas Inteligentes I&H Tech. Corresponding author ✉: mjflores@espe.edu. ec.
Resistance of reinforced concrete members with hollow circular cross‐sections under combined bending and shear – Part I: experimental investigation

Part I of this paper introduces an experimental programme carried out on RC members with thick‐walled hollow circular cross‐sections to study their behaviour under combined bending and shear. The study looked at ultimate resistance and propagation of characteristic crack pattern as well as the shape and behaviour of the failure sections as a function of wall thickness, amount of longitudinal and transverse reinforcement, shear span and axial force. Test results were used to verify a newly developed calculation model describing the behaviour of the members investigated at failure under combined bending and shear. This model will be presented in Part II.