Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in Andes Mountains snow cover from MODIS data 2000–2014

The Andes Mountains span a length of 7,000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000–2014 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent) limited between 8 °S and 36 °S due high frequency of cloud (>30 % of the time) south and north of this range. We ran Mann-Kendall and Theil-Sens analyses to identify significant areas of change in SP and snow line (the line at lower elevation which SP=20%). We evaluated whether these trends in the context of temperature and precipitation (University of Delaware dataset) and climate indices (ENSO, SAM, PDO). North of 29 °S has limited snow cover, and few trends in snow persistence were detected. A large area (70,515 km 2 ) with persistent snow cover between 29–36 °S experienced a significant loss of snow cover (2–5 fewer days of snow year −1 ). Snow loss was more pronounced (62 %) on the east side of the Andes. We also found a significant increase in the elevation of 10–30 m year −1 south of 29–30 °S. Decreasing SP correlates with decreasing precipitation, increasing temperature, and climate indices and it varies with latitude and elevation. ENSO indices better predicted SP conditions north of 31 °S, and the SAM better predicted SP south of 31 °S.
Nanolaminates Utilizing Size‐Dependent Homogeneous Plasticity of Metallic Glasses

Homogeneous plasticity in metallic glasses is generally only observed at high temperatures or in very small structures (less than ≈100 nm), so their applications for structural performance have been very limited. Here, nanolaminates with alternating layers of Cu50Zr50 metallic glass and nanocrystalline Cu are synthesized and it is found that samples with an optimal composition of 112‐nm‐thick metallic‐glass layers and 16‐nm‐thick Cu layers demonstrate a maximum strength of 2.513 GPa, a value 33% greater than that predicted by the rule‐of‐mixtures and 25% better than that of pure Cu50Zr50 metallic glass. Furthermore, ≈4% strain at fracture is achieved, suppressing the instantaneous catastrophic failure often associated with metallic glasses. It is postulated that this favorable combination of high strength and deformability is caused by the size‐dependent deformation‐mode transition in metallic glasses, from highly localized plasticity, leading to immediate failure in larger samples to homogeneous extension in the smaller ones.
Lecture notes on the big de Rham-Witt complex

We continue with the definition of the big de Rham-Witt complex. It generalizes the classical p-typical de Rham-Witt complex of Bloch, Deligne, and Illusie [8, 7, 1] and was first defined by the author and Madsen [6]. For rings in which the prime number 2 is not either invertible or zero, the original definitions of these complexes are not quite correct. The correct definition of the 2-typical de Rham-Witt complex was given by Costeanu [4] while the correct definition of the big de Rham-Witt complex is given first in these notes. The big de Rham-Witt complex associates to every ring A and every set S of integers stable under division an anti-symmetric differential graded ring WSΩ·A together with maps R T : WSΩ q A →WT Ω q A (restriction) Fn : WSΩ q A →WS/nΩ q A (Frobenius) Vn : WS/nΩ q A →WSΩ q A (Verschiebung) λ : WS(A)→WSΩ 0 A
Blank Assessment for Ultra-Small Radiocarbon Samples: Chemical Extraction and Separation Versus AMS

The Keck Carbon Cycle AMS facility at the University of California, Irvine (KCCAMS/UCI) has developed protocols for analyzing radiocarbon in samples as small as ∼0.001 mg of carbon (C). Mass-balance background corrections for modern and 14C-dead carbon contamination (MC and DC, respectively) can be assessed by measuring 14C-free and modern standards, respectively, using the same sample processing techniques that are applied to unknown samples. This approach can be validated by measuring secondary standards of similar size and 14C composition to the unknown samples. Ordinary sample processing (such as ABA or leaching pretreatment, combustion/graphitization, and handling) introduces MC contamination of ∼0.6 ± 0.3 μg C, while DC is ∼0.3 ± 0.15 μg C. Today, the laboratory routinely analyzes graphite samples as small as 0.015 mg C for external submissions and ≅0.001 mg C for internal research activities with a precision of ∼1% for ∼0.010 mg C. However, when analyzing ultra-small samples isolated by a series of complex chemical and chromatographic methods (such as individual compounds), integrated procedural blanks may be far larger and more variable than those associated with combustion/graphitization alone. In some instances, the mass ratio of these blanks to the compounds of interest may be so high that the reported 14C results are meaningless. Thus, the abundance and variability of both MC and DC contamination encountered during ultra-small sample analysis must be carefully and thoroughly evaluated. Four case studies are presented to illustrate how extraction chemistry blanks are determined.
Interstellar X-Ray Absorption Spectroscopy of Oxygen, Neon, and Iron with the Chandra LETGS Spectrum of X0614+091

We find resolved interstellar O K, Ne K, and Fe L absorption spectra in the Chandra X-Ray Observatory Low-Energy Transmission Grating Spectrometer (LETGS) spectrum of the low-mass X-ray binary X0614+091. We measure the column densities in O and Ne and find direct spectroscopic constraints on the chemical state of the interstellar O. These measurements probably probe a low-density line of sight through the Galaxy, and we discuss the results in the context of our knowledge of the properties of interstellar matter in regions between the spiral arms.
Efficient Fingerprint Recognition using Wavelet Transforms

Fingerprints have long been used as a reliable biometric feature for private identification. Fingerprint classification refers to the matter of assignment fingerprints to 1 of many prespecified categories. Automatic classification may be used as a pre-processing step for fingerprint matching, reducing matching time and complexness by narrowing the search area to a set of a usually large info. Automatic fingerprint identification is one among the foremost vital biometric technologies. so as to expeditiously match fingerprints during a massive info, Associate in Nursing classification theme is critical. Fingerprint classification, that refers to assignment a fingerprint image into variety of pre-specified categories, provides a possible classification mechanism. In observe, but massive intra-class and tiny interclass variations in world pattern configuration and poor quality of fingerprint pictures build the classification drawback terribly tough. A fingerprint classification algorithmic program needs a sturdy feature extractor that ought to be ready to reliable extract salient options from input pictures
THE USE OF MUSIC AND SINGING TO HELP MANAGE ANXIETY IN OLDER ADULTS

The number of older adults in the UK is increasing, and they are vulnerable to long-term anxiety, depression, pain and dementia. These conditions can to some extent be relieved by medication, but this has variable adverse effects. Older people themselves often prefer alternatives such as relaxation and distraction, including listening to music or singing along. This review of relevant studies finds that the use of music as a valid nursing intervention can relieve anxiety and depression, help manage pain and improve quality of life.
Generalized random forests

We propose generalized random forests, a method for non-parametric statistical estimation based on random forests (Breiman, 2001) that can be used to fit any quantity of interest identified as the solution to a set of local moment equations. Following the literature on local maximum likelihood estimation, our method considers a weighted set of nearby training examples; however, instead of using classical kernel weighting functions that are prone to a strong curse of dimensionality, we use an adaptive weighting function derived from a forest designed to express heterogeneity in the specified quantity of interest. We propose a flexible, computationally efficient algorithm for growing generalized random forests, develop a large sample theory for our method showing that our estimates are consistent and asymptotically Gaussian, and provide an estimator for their asymptotic variance that enables valid confidence intervals. We use our approach to develop new methods for three statistical tasks: non-parametric quantile regression, conditional average partial effect estimation, and heterogeneous treatment effect estimation via instrumental variables. A software implementation, grf for R and C++, is available from CRAN.
Low-latency speaker spotting with online diarization and detection

This paper introduces a new task termed low-latency speaker spotting (LLSS). Related to security and intelligence applications, the task involves the detection, as soon as possible, of known speakers within multi-speaker audio streams. The paper describes differences to the established fields of speaker diarization and automatic speaker verification and proposes a new protocol and metrics to support exploration of LLSS. These can be used together with an existing, publicly available database to assess the performance of LLSS solutions also proposed in the paper. They combine online diarization and speaker detection systems. Diarization systems include a naive, over-segmentation approach and fully-fledged online diarization using segmental i-vectors. Speaker detection is performed using Gaussian mixture models, i-vectors or neural speaker embeddings. Metrics reflect different approaches to characterise latency in addition to detection performance. The relative performance of each solution is dependent on latency. When higher latency is admissible, i-vector solutions perform well; embeddings excel when latency must be kept to a minimum. With a need to improve the reliability of online diarization and detection, the proposed LLSS framework provides a vehicle to fuel future research in both areas. In this respect, we embrace a reproducible research policy; results can be readily reproduced using publicly available resources and open source codes.
Motion Optimization of a Planar Kangaroo Model

We report on the development of a planar kangaroo model, which has a tail with two degrees of freedom and a compliant and rolling leg. The full body dynamics of the model are investigated, and it serves as an underlying model for the optimization of leg and tail trajectories. Keywordsmotion optimization, kangaroo, model
Measuring macroeconomic volatility - Applications to export revenue data, 1970-2005

La litterature sur l’instabilite macroeconomique couvre un champ extremement vaste qui se revele par le spectre tres large de mesures utilisees pour apprehender ce phenomene. Le choix de la mesure de l’instabilite macroeconomique apparait generalement peu discute sous le pretexte que les differentes methodes, basees sur la stationnarisation des series, resultent en des scores d’instabilite fortement correles entre eux. Pourtant, si effectivement ces methodes convergent lorsque seule l’ampleur moyenne d’une distribution autour d’une valeur de reference est analysee, elles divergent significativement quand on s’interesse a son asymetrie ou a sa voussure (occurrence des deviations extremes). Dans cet article, nous proposons une revue de la litterature sur le sujet et presentons les principales methodes de calcul de l’instabilite. A partir de donnees sur les recettes d’exportation de 134 pays de 1970 a 2005, nous comparons ces methodes et analysons leurs proprietes. Nous distinguons notamment les mesures d’ampleur de l’instabilite, des mesures d’asymetrie, et d’occurrence des deviations extremes.
Comparaison entre modèles d'ondes de surface en dimension 2

Partant du principe de conservation de la masse et du principe fondamental de la dynamique, on retrouve l'equation d'Euler nous permettant de decrire les modeles asymptotiques de propagation d'ondes dans des eaux peu profondes en dimension 1. Pour decrire la propagation des ondes en dimension 2, Kadomtsev et Petviashvili [ 15 (1970) 539] utilisent une perturbation lineaire de l'equation de KdV. Mais cela ne precise pas si les equations ainsi obtenues derivent de l'equation d'Euler, c'est ce que montrent Ablowitz et Segur dans l'article [J. Fluid Mech. 92 (1979) 691–715]. On insistera, de la meme maniere, sur le fait que les equations de KP-BBM peuvent etre aussi obtenues a partir de l'equation d'Euler, et dans quelle mesure elles decrivent le modele physique. Dans un second temps, on reprend la methode introduite dans l'article de Bona et al. [Lect. Appl. Math. 20 (1983) 235–267] dans lequel ils comparent les solutions d'ondes longues en dimension 1, a savoir les solutions des equations KdV et BBM, pour montrer ici que les solutions des equations KP-II et KP-BBM-II sont proches sur un intervalle de temps inversement proportionnel a l'amplitude des ondes. Du point de vue de la modelisation, il sera clair, d'apres la premiere partie, que seul le modele decrit par KP-BBM-II est bien pose, et comme du point de vue physique, KP-II et KP-BBM-II decrivent les ondes longues de faible amplitude lorsque la tension de surface est negligeable, il est interessant de les comparer. De plus, on verra que la methode utilisee ici reste valable pour les problemes periodiques.
Vertical GPS ground motion rates in the Euro‐Mediterranean region: New evidence of velocity gradients at different spatial scales along the Nubia‐Eurasia plate boundary

We use 2.5 to 14 years long position time series from >800 continuous Global Positioning System (GPS) stations to study vertical deformation rates in the Euro‐Mediterranean region. We estimate and remove common mode errors in position time series using a principal component analysis, obtaining a significant gain in the signal‐to‐noise ratio of the displacements data. Following the results of a maximum likelihood estimation analysis, which gives a mean spectral index ~ −0.7, we adopt a power law + white noise stochastic model in estimating the final vertical rates and find 95% of the velocities within ±2 mm/yr, with uncertainties from filtered time series ~40% smaller than from the unfiltered ones. We highlight the presence of statistically significant velocity gradients where the stations density is higher. We find undulations of the vertical velocity field at different spatial scales both in tectonically active regions, like eastern Alps, Apennines, and eastern Mediterranean, and in regions characterized by a low or negligible tectonic activity, like central Iberia and western Alps. A correlation between smooth vertical velocities and topographic features is apparent in many sectors of the study area. Glacial isostatic adjustment and weathering processes do not completely explain the measured rates, and a combination of active tectonics and deep‐seated geodynamic processes must be invoked. Excluding areas where localized processes are likely, or where subduction processes may be active, mantle dynamics is the most likely process, but regional mantle modeling is required for a better understanding.
Efficacy of the Muguga cocktail east coast fever vaccine at a cattle-buffalo interface in Laikipia county, Kenya

The study was conducted to assess the efficacy of Muguga Cocktail East Coast Fever (ECF) vaccine at a cattle-buffalo interface in some ranches in Laikipia County. It is not known with certainty how the current vaccine for cattle against East Coast Fever, that is, Infection and Treatment Method (ITM) using the Muguga Cocktail would perform in areas where buffalos exist with cattle. This is because of the suspicion that buffalo strain of T. parva circulating at the cattle-buffalo interface would lower the efficacy of the ITM with T. parva strains sourced from cattle. The specific objectives of the study were to; 1. Assess the efficacy of ECF vaccine in cattle at a cattle-buffalo interface in Laikipia County. 2 . Determine the viability of the ECF vaccine. The study was conducted in two ranches which were conveniently selected including Mutara and Ole Naishu with herd sizes of 986 and 2,796 heads of cattle, respectively. A controlled trial was conducted on the two ranches whereby calves were recruited for the study. The calves had no previous history of East Coast Fever (ECF) infection. In both the treatment and control group, a total of 65 immunized and control calves were recruited in each of the ranches. The calves were randomly selected and allocated to immunized and control groups. Calves in the treatment group were injected with Muguga cocktail using a standard protocol developed at the Veterinary Research Institute, Muguga. Prior to the injection of the vaccine, a 30% long acting oxytetracycline was administered at a dose of 30mg per body weight by deep intramuscular injection. Any immunized calf that developed clinical signs of ECF with fever and presence of macroschizonts (7-10 days post immunization) in lymph node smears for at least three days was designated as ―ECF reactor‖. Calves were bled pre-immunization at day 0 and then again 35 days post immunization to determine the antibody response using an Indirect ELISA test, this was to test for the viability of the vaccine. Daily clinical surveillance was kept on all the calves in both the treatment and control groups for twelve months. The sero-conversion in the vaccinated group was 83% in Ole Naishu and 69% in Mutara. The sero-conversion among the control groups was 3.1% and 6.2% in Ole Naishu and Mutara respectively. The efficacy of the vaccine was established at 97.8% for Ole Naishu, and 78.4% for Mutara. The ECF vaccine (Muguga cocktail) was not as efficacious in Mutara ranch as in Ole Naishu ranch. This may be attributed to sharing of grazing of cattle with buffalos in Mutara which was not the case in Ole Naishu.
Ultrasound-guided pain interventions in the knee region

Abstract Most routine intra-articular and extra-articular knee infiltrations performed in pain management are carried out by means of blind techniques or fluoroscopy-guided techniques. Alternatively, ultrasound-guided techniques are a safer and more precise way to perform these procedures. An extensive knowledge of knee anatomy will help us to obtain high-quality real-time ultrasound images before performing any infiltrations. In the current article, we present how to systematically examine the knee sonoanatomy and also describe the ultrasound-guided interventional basis for knee joint pain management.
INHIBITION AND SET -SHIFTING TASKS IN CENTRAL EXECUTIVE FUNCTION OF WORKING MEMORY : AN EVENT -RELATED POTENTIAL (ERP) STUDY

Understanding of neuro-dynamics of a complex higher cognitive process, Working Memory (WM) is challenging. In WM, information processing occurs through four subsystems: phonological loop, visual sketch pad, memory buffer and central executive function (CEF). CEF plays a principal role in WM. In this study, our objective was to understand the neurospatial correlates of CEF during inhibition and set-shifting processes. Thirty healthy educated subjects were selected. Event-Related Potential (ERP) related to visual inhibition and set-shifting task was collected using 32 channel EEG system. Activation of those ERPs components was analyzed using amplitudes of positive and negative peaks. Experiment was controlled using certain parametric constraints to judge behavior, based on average responses in order to establish relationship between ERP and local area of brain activation and represented using standardized low resolution brain electromagnetic tomography. The average score of correct responses was higher for inhibition task (87.5%) as compared to set-shifting task (59.5%). The peak amplitude of neuronal activity for inhibition task was lower compared to set-shifting task in fronto-parieto-central regions. Hence this proposed paradigm and technique can be used to measure inhibition and set-shifting neuronal processes in understanding pathological central executive functioning in patients with neuro-psychiatric disorders.
VARIATIONAL STOCHASTIC GRADIENT DESCENT

In Bayesian approach to probabilistic modeling of data we select a model for probabilities of data that depends on a continuous vector of parameters. For a given data set Bayesian theorem gives a probability distribution of the model parameters. Then the inference of outcomes and probabilities of new data could be found by averaging over the parameter distribution of the model, which is an intractable problem. In this paper we propose to use Variational Bayes (VB) to estimate Gaussian posterior of model parameters for a given Gaussian prior and Bayesian updates in a form that resembles SGD rules. It is shown that with incremental updates of posteriors for a selected sequence of data points and a given number of iterations the variational approximations are defined by a trajectory in space of Gaussian parameters, which depends on a starting point defined by priors of the parameter distribution, which are true hyper-parameters. The same priors are providing a weight decay or L2 regularization for the training. Then a selection of L2 regularization parameters and a number of iterations is completely defining a learning rule for VB SGD optimization, unlike other methods with momentum (Duchi et al., 2011; Kingma & Ba, 2014; Zeiler, 2012) that need selecting learning, regularization rates, etc., separately. We consider application of VB SGD for important practical case of fast training neural networks with very large data. While the speedup is achieved by partitioning data and training in parallel the resulting set of solutions obtained with VB SGD forms a Gaussian mixture. By applying VB SGD optimization to the Gaussian mixture we can merge multiple neural networks of same dimensions into a new single neural network that has almost the same performance as an original Gaussian mixture.
Toward Measuring Proactivity in Person-Environment Transactions in Late Adulthood

Abstract Both a life-span developmental control perspective as well as an environmental gerontology view, particularly Lawton's notion of environmental proactivity, served as the theoretical background to suggest a new dimension of domain-specific control, namely housing-related control beliefs. The newly developed 23-item Housing-Related Control Beliefs Questionnaire (HCQ) is based on the widely used dimensions of Internal Control, External Control: Powerful Others, and External Control: Chance. In two studies of older adults (N= 485; 66-69 years and N= 107; 65-91 years), we examined the psychometric quality of the questionnaire and explored its relation with socio-structural variables, general control beliefs, and a set of housing-related aspects. Psychometric results indicate satisfactory levels of internal consistency and re-test stability in all three scales of the instrument and factor analysis supported the theoretically expected three-factor solution. Also, HCQ's external control subscales were correlated with higher age, lower education, and lower income and the correlational pattern between the HCQ and a general control measure was substantial and consistent with theoretical expectations. Relations between the HCQ and objective and subjective housing-related variables tended to be low in size. These preliminary findings suggest the potential usefulness of the HCQ as a measure to address environmental proactivity in late adulthood.