Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecosystem indices to support global biodiversity conservation

Governments have committed to global targets to slow biodiversity loss and sustain ecosystem services. Biodiversity state indicators that measure progress toward these targets mostly focus on species, while indicators synthesizing ecosystem change are largely lacking. We fill this gap with three indices quantifying past and projected changes in ecosystems using data from the International Union for Conservation of Nature (IUCN) Red List of Ecosystems. Our indices quantify changes in risk of ecosystem collapse, ecosystem area and ecological processes, and capture variation in underlying patterns among ecosystems. We apply the indices to three case studies of regional and national assessments (American/Caribbean forests, terrestrial ecosystems of Colombia, and terrestrial ecosystems of South Africa) to illustrate the indices’ complementarity and versatility in revealing patterns of interest for users across sectors. Our indices have the potential to fill the recognized need for ecosystem indicators to inform conservation targets, guide policy, and prioritize management actions.
VLOGA METFORMINA PRI OBRAVNAVI BOLNIC S SINDROMOM POLICISTINIH JAJNIKOV THE ROLE OF METFORMIN IN THE TREATMENT OF PATIENTS WITH POLYCYSTIC OVARY SYNDROME

Sindrom policistinih jajnikov (PCOS) je najpogostejoa endokrinopatija v reproduktivnem obdobju uenske in prizadene 10n20 % uensk po ameriokih in 15n22 % uensk po evropskih merilih. Klinino se kaue z nepravilnostmi v menstruacijskem ciklusu, hirsutizmom, aknami, alopecijo in debelostjo. Doslej uveljavljenim oblikam zdravljenja, ki so preteuno usmerjene v obvladovanje vodilnega simptoma (hirsutizem ali menstruacijske motnje ali neplodnost), se je pridruuilo oe zdravilo metformin. Metformin je peroralni antidiabetik, ki izboljoa obutljivost na inzulin. Inzulin spodbuja izloanje androgenov v ovarijski stromi in verjetno vpliva na razvoj ovarijskih foliklov z zaviranjem apoptoze, zaradi esar folikli, ki bi sicer degenerirali, preuivijo. Dolgorone posledice inzulinske rezistence vodijo v inzulinsko-odvisen diabetes in dislipidemijo. Zakljuki Rezultati raziskav in meta analize kauejo, da metformin prepreuje razvoj inzulinske rezistence, ugodno vpliva na zmanjoanje telesne teue in je uinkovit pri indukciji ovulacije, zlasti pri uenskah, odpornih na klomifen.
Do children use language structure to discover the recursive rules of counting?

We test the hypothesis that children acquire knowledge of the successor function - a foundational principle stating that every natural number n has a successor n + 1 - by learning the productive linguistic rules that govern verbal counting. Previous studies report that speakers of languages with less complex count list morphology have greater counting and mathematical knowledge at earlier ages in comparison to speakers of more complex languages (e.g., Miller & Stigler, 1987). Here, we tested whether differences in count list transparency affected children's acquisition of the successor function in three languages with relatively transparent count lists (Cantonese, Slovenian, and English) and two languages with relatively opaque count lists (Hindi and Gujarati). We measured 3.5- to 6.5-year-old children's mastery of their count list's recursive structure with two tasks assessing productive counting, which we then related to a measure of successor function knowledge. While the more opaque languages were associated with lower counting proficiency and successor function task performance in comparison to the more transparent languages, a unique within-language analytic approach revealed a robust relationship between measures of productive counting and successor knowledge in almost every language. We conclude that learning productive rules of counting is a critical step in acquiring knowledge of recursive successor function across languages, and that the timeline for this learning varies as a function of counti list transparency.
Anisotropic ray-Born migration/inversion: A synthetic modeling study

A least-squares migration/inversion technique is used to investigate the resolution of isotropic and anisotropic parameters for a transversely isotropic earth model. The method is based on the elastic ray-Born approximation, which linearizes the forward modeling problem using far-field, high-frequency and small-perturbation assumptions. Approximate background ray-Green's tensors comprise the kernel of the scattering integral, and are computed using a finite-difference approach. Least-squares inversion is implemented using an iterative three-step conditioned-gradient procedure. The first step for each iteration resembles prestack Kirchhoff depth migration of the current data residual, yielding a gradient subimage for each model parameter. An approximate Hessian operator is then applied to partially deconvolve parametercoupling effects, producing a set of model-perturbation images. Finally, a predicted forward model is computed by scattering from the current set of model perturbations. This scheme attempts to recover short-wavelength parameter variations relative to the reference model, rather than its slowly varying components. The resolution of Pand S-wave velocities, density and Thomsen's anisotropy parameters is investigated for the case of a homogeneous, isotropic background model, using both surface and crosswell acquisition geometries. A third example, involving an anticline structure, composed of anisotropic, inhomogeneous layers is used to demonstrate the feasibility of these techniques for seismic imaging in structurally complex areas. Finally, a ray-traced (non-Born) dataset illustrates that superior resolution of subsurface features (in particular, slope discontinuities) can be achieved by migrating all elastic wave types simultaneously.
fastDEM: A method for faster DEM simulations of granular media

One of the main challenges for the simulation of particulate processes is the ability to perform simulations of large-scale processes on the equipment scale. The goal is to reproduce accurate macroscale representation of granular dynamics. However, this granular dynamics is controlled via the micro-scale mechanics which is cannot be explicitly resolved for many applications, since this would be computationally infeasible. One common approach is to derive constitutive model relationships for continuum models which provide for faster calculations. An alternative approach is to use mesoparticles in Discrete Element Method (DEM) simulations [1], sometimes also referred to as parcel, coarse-graining or up-scaling method. Here, we present a method which can be combined with the parcel-based DEM method. It is useful to simulate longer time-scales with DEM for steady-state (or pseudo steady-state) processes. It consists of the following steps: (i) Calculate the flow field with DEM until it reaches a (pseudo) steady-state, (ii) Average the flow field on a Eulerian grid, (iii) and move the particles along the steady-state velocity field (“forward projection”). Steps (ii) and (iii) are then repeated iteratively to update the steady state flow field. We term this iterative coupling between DEM and forward projection “fastDEM”. The method presented has been implemented in our DEM software LIGGGHTS [2]. For the forward projection phase, time-steps of up to 0.01 sec can be applied, which is a factor 1001000 higher than typical DEM time-step sizes. Fig. 1. shows the result for a silo discharge simulation. An effective speed-up of ~10 could be obtained in this case using the fastDEM method with almost identical outflow rate prediction. Fig. 1. : Silo discharge setup (left) and mass-flow rate over time (right) with classical DEM (red), pure forward projection using the initial steady state (black) and fastDEM (blue)
Augmentation de l'incidence du cancer broncho- pulmonaire chez les patients fumeurs ayant présenté une infection respiratoire basse: mythe ou réalité ? Increase of lung cancer incidence in smoker patients with lower respiratory tract infection: myth or reality

Le cancer broncho-pulmonaire est actuellement un probleme de sante publique de part sa frequence, son incidence et sa mortalite. En 2008, au niveau mondial, le cancer bronchique representait 13 % des cas de cancers (1,6 million) et 18 % des deces (1,44 million) [1]. Chez l’homme, le cancer bronchique est la premiere cause de mortalite par cancer et chez la femme, son incidence ne cesse d’augmenter [2]. Aussi son pronostic reste sombre avec une survie a 5 ans inferieure a 15 % tous stades confondus [2].
Early lexical influences on sublexical processing in speech perception: Evidence from electrophysiology

Contextual information influences how we perceive speech, but it remains unclear at which level of processing contextual information merges with acoustic information. Theories differ on whether early stages of speech processing, like sublexical processing during which articulatory features and portions of speech sounds are identified, are strictly feed-forward or are influenced by semantic and lexical context. In the current study, we investigate the time-course of lexical context effects on judgments about the individual sounds we perceive by recording electroencephalography as an online measure of speech processing while subjects engage in a lexically biasing phoneme categorization task. We find that lexical context modulates the amplitude of the N100, an ERP component linked with sublexical processes in speech perception. We demonstrate that these results can be modeled in an interactive speech perception model and are not well fit by any established feed-forward mechanisms of lexical bias. These results support interactive speech perception theories over feed-forward theories in which sublexical speech perception processes are only driven by bottom-up information.
Determinants of Digital Learning Implementation in Public Primary Schools: A Case of Nairobi County Schools

Digital learning has become a widely accepted learning module in recent years and has been linked with positive, cumulatively progressive gains in learning outcomes. This study sought to assess the Digital Learning Strategy Implementation in public primary schools in Nairobi County. Records in the County Education Office indicate that there are 196 public primary schools within Nairobi County that have implemented the digital learning strategy. Specifically the study sought to assess and determine the influence of digital content, digital infrastructure, security of ICT infrastructure and equipment and resource allocation on the digital learning implementation strategy. To achieve these objectives the study adopted a descriptive research design. The target population were the users of the digital learning system in these schools. Three users from each school were identified from the stakeholders who interact with the platform on a regular basis by the nature of their jobs. These were the ICT Teachers the Deputy Head Teacher and Head teachers. The data collection instrument of choice used to collect primary data was questionnaires. These were administered through a drop and pick methodology because of it was convenient for the respondents to complete at their pace. The data collected was analyzed using descriptive statistics, correlation and regression analysis. The results of the correlation analysis indicated that there was a weak correlation between the digital content and ICT infrastructure, but a stronger correlation between the was also done to establish the relationship between the implementation strategy as the dependent variable and digital content, ICT infrastructure, Security and Resources as the independent variables. Results of the study gave a strong positive correlation between the independent and dependent variables. The results of this study will be of immense benefit to the teachers, students and the government bodies charged with its implementation such as the ICT Authority.
Ovarian malignancy risk strati fi cation of the adnexal mass using a multivariate index assay ☆

► The multivariate index assay (MVA) was evaluated in an intended-use population of non-gynecologic oncology practices. ► The MVA demonstrated high sensitivity and NPV for ovarian malignancy. ► The MVA correctly identified 83.3% malignancies missed by clinical impression and 70.8% cases missed by CA125-II. ☆ This study was funded by Vermillion Inc., Austin, TX ⁎ Corresponding author at: Division of Gynecologic O Building 56, Room 260, Orange, CA 92868, USA. Fax: + E-mail address: rbristow@uci.edu (R.E. Bristow). 0090-8258/$ – see front matter © 2012 Elsevier Inc. All http://dx.doi. org/10.1016/j.ygyno. 2012.11. 022 a b s t r a c t a r t i c l e i n f o
Combination Immunotherapy for Glioblastoma Multiforme With the Combination of GVAX and PD-1 Blockade, Using Anti-PD1 Antibody

Glioblastoma Multiforme (GBM), also known as grade IV astrocytoma, is generally found in the cerebral hemispheres but can be found anywhere else in the brain or the spinal cord. Even after surgery and chemotherapy, GBM has a high rate of recurrence. Median survival after diagnosis is 12 months, with less than 3 to 5% people surviving greater than 5 years. Without treatment, average survival is about 3 months. Immune checkpoint inhibition is a recent addition to the regimen of treatment of cancers and has shown some promising results in Melanoma and lung cancer. The primary research goal of this thesis was to study if treatment with a combination of GVAX and PD-1 blockade leads to improved survival in comparison to PD-1 treatment alone in a mouse glioma model. If a combination treatment of GVAX and PD-1 leads to improved survival as compared to PD-1 treatment alone, a secondary goal of my research was to identify the underlying immune mechanisms that were responsible for this survival advantage. Finally, a third goal of my research was to examine survival advantage, if any, from treatment with GVAX and PD-1 can be enhanced further with the addition of a second immune checkpoint molecule. Data from this study is presented which shows that combination immunotherapy with GVAX and Anti-PD1 does provide survival advantage by increasing tumor infiltration of Cd8 T-cells into the tumor and by increasing Cd8 T-cells to Treg cell ratio. The survival advantages conferred by the combination of GVAX and Anti-PD1 was further enhanced by the addition of second immune checkpoint molecule OX40.Triple combination treated mice also developed immune memory towards the tumor and long-term survivors rejected a tumor challenge with three times more cells than the initial tumor challenge. These results confirm the initial hypothesis that combination immunotherapy with GVAX and immune checkpoint molecules can be an efficacious treatment for patients with GBM.
Adaptive control of dynamic balance in human walking

Walking is the most important means of transport for humans. Only when our walking ability decreases due to aging or injury, we come to realize how important the ability to walk is in our lives. To understand how we can increase walking performance after aging or injury, we studied an important aspect of walking: balance control; as without control of our balance, we would fall down before even making the first step. In this thesis, we studied balance control during walking on a split-belt treadmill, a treadmill with two parallel belts, on which people walk faster with one leg than the other. Although this is a challenging task, healthy humans flexibly controlled their dynamic balance to stay upright during split-belt walking. This can be compared with real-life walking flexibility, where to avoid pedestrians, walk up curbs or text while walking, we constantly change our steps to control our balance, without even thinking about it. Furthermore, we found that when balance is assisted during gait training, by holding handrails, you learn less from this training. This suggests that learning to control your balance is an important element of learning how to walk. Finally, we found that people post-stroke who increase their forward balance with their paretic leg after a slip or trip might lose their side-ward balance due to decreased control of the paretic leg. Further research is necessary to find out whether we can decrease this problem in post-stroke rehabilitation.
Something old , something new : disorders specifically thassociated with stress in the ICD 11 revision

Classification of mental and behavioural disorders in World Health Organization’s International Classification of Diseases (ICD) is presently under revision. There is a proposal for a class of Disorders specifically associated with stress that includes, for example, post-traumatic stress disorder (PTSD) with revised criteria. There will be new diagnoses of complex PTSD and prolonged grief disorder. In this article we review main post-traumatic disorders as they are proposed to be in the forthcoming ICD-11. There is some but limited literature on how the revision will affect epidemiology and clinical picture of the existing diagnoses. The introduction of complex PTSD and prolonged grief disorder diagnoses facilitates recognition of their specific treatment needs.
Bayesian Uncertainty Quantification with Multi-Fidelity Data and Gaussian Processes for Impedance Cardiography of Aortic Dissection

In 2000, Kennedy and O’Hagan proposed a model for uncertainty quantification that combines data of several levels of sophistication, fidelity, quality, or accuracy, e.g., a coarse and a fine mesh in finite-element simulations. They assumed each level to be describable by a Gaussian process, and used low-fidelity simulations to improve inference on costly high-fidelity simulations. Departing from there, we move away from the common non-Bayesian practice of optimization and marginalize the parameters instead. Thus, we avoid the awkward logical dilemma of having to choose parameters and of neglecting that choice’s uncertainty. We propagate the parameter uncertainties by averaging the predictions and the prediction uncertainties over all the possible parameters. This is done analytically for all but the nonlinear or inseparable kernel function parameters. What is left is a low-dimensional and feasible numerical integral depending on the choice of kernels, thus allowing for a fully Bayesian treatment. By quantifying the uncertainties of the parameters themselves too, we show that “learning” or optimising those parameters has little meaning when data is little and, thus, justify all our mathematical efforts. The recent hype about machine learning has long spilled over to computational engineering but fails to acknowledge that machine learning is a big data problem and that, in computational engineering, we usually face a little data problem. We devise the fully Bayesian uncertainty quantification method in a notation following the tradition of E.T. Jaynes and find that generalization to an arbitrary number of levels of fidelity and parallelisation becomes rather easy. We scrutinize the method with mock data and demonstrate its advantages in its natural application where high-fidelity data is little but low-fidelity data is not. We then apply the method to quantify the uncertainties in finite element simulations of impedance cardiography of aortic dissection. Aortic dissection is a cardiovascular disease that frequently requires immediate surgical treatment and, thus, a fast diagnosis before. While traditional medical imaging techniques such as computed tomography, magnetic resonance tomography, or echocardiography certainly do the job, Impedance cardiography too is a clinical standard tool and promises to allow earlier diagnoses as well as to detect patients that otherwise go under the radar for too long.
Work-Efficient Schedulers

The scheduling of multithreaded computations has attracted extensive research over past decades. Most of the research focused on design schedulers that are efficient in terms of runtime and space consumption, very often at the cost of performing more work than the computation itself required. This work considers a new class of schedulers, called work-efficient schedulers. Work-efficient schedulers aim to minimize extra work, measured by the total number of instructions executed by all processors due to scheduling, including idle (referred to as spinning in this work) time. Specifically, the total amount of work performed during the scheduling of a computation must be within a small constant factor of the total work of the computation. This work first presents an offline elastic scheduler that achieves the goal by dynamically scaling up or down the processors it utilizes in response to the instantaneous parallelism. We prove a runtime and total work bound for our offline elastic scheduler and show that it achieves linear speedup with respect to the number of processors, while maintaining work efficiency. This work further presents an online elastic work-stealing algorithm that aims at approximating the offline work-efficient schedulers. The elastic workstealing scheduler augments the traditional work-stealing algorithm with a lifeline forest communication structure that allows processors to respond swiftly to varying instantaneous parallelism in a distributed manner. We implemente this algorithm then evaluate its performance and work efficiency by comparing it agaist existing implementations of traditional work-stealing schedulers. Results show that 1) for highly parallel computations, our elastic work-stealing scheduler is comparable to classic work stealing in its speedup; 2) for computations where parallelism is more limited, our elastic work-stealing scheduler performs considerably less work.
A decision support tool using OWA for conference review assignment

Assigning papers to reviewers is a large, long and difficult task for conference chairs and scientific committees. The paper reviewer assignment problem is a multi-agent problem which requires understanding reviewer expertise and paper topics for the matching process. This paper proposes to elaborate on some features used to compute reviewer expertise and aggregate multiple factors to find the fittest combination of reviewers for each paper. Expertise information is gathered implicitly from publicly available information and a reviewer profile is generated automatically. An OWA (Ordered Weighted Average) aggregation function is used to summarize information coming from different sources and rank candidate reviewers for each paper. General constraints for the RAP (Reviewer Assignment Problem) have been incorporated into a real case example: (i) conflicts of interest between a reviewer and authors should be avoided, (ii) each paper must have a minimum number of reviewers, and (iii) each reviewer load cannot exceed a certain number of papers. c © 2017 Elsevier Ltd. All rights reserved.