Miracle-dz/UniFAR-FTUs huggingface dataset:
Fitness-related traits are maximized in recently introduced , slow-1 growing populations of an invasive clam : is this a response to strong r-2 selection ?

Fitness-related traits are maximized in recently introduced, slow1 growing populations of an invasive clam: is this a response to strong r2 selection? 3 4 Leandro A. Hünicken*, Francisco Sylvester, Nicolás Bonel 5 6 1 Museo Argentino de Ciencias Naturales ‘Bernardino Rivadavia’, Av. Angel Gallardo 470 (C1405DJR), 7 Buenos Aires, Argentina. Present Address: Centro de Investigación Aplicada y Transferencia Tecnológica 8 en Recursos Marinos ‘‘Almirante Storni’’, Güemes 1030, San Antonio Oeste, 9 R8520CXV Río Negro, Argentina 10 11 2 Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina. 12 13 3 Instituto para el estudio de la Biodiversidad de Invertebrados, Facultad de Ciencias Naturales, 14 Universidad Nacional de Salta, Av. Bolivia 5150 (4400), Salta, Argentina. 15 16 4 Laboratorio de Zoología de Invertebrados I, Departamento de Biología, Bioquímica y Farmacia, 17 Universidad Nacional del Sur (UNS), San Juan 670, (B8000ICN) Bahía Blanca, Argentina. 18 19 5 Centre d’Ecologie Fonctionnelle et Evolutive, UMR 5175, CNRS—Université de Montpellier, 20 Université Paul-Valéry Montpellier—Ecole Pratique des Hautes Etudes—IRD, 34293 Montpellier cedex 21 05, France. 22 23 * Corresponding author. E-mail: leandrohunicken@gmail.com 24
This paper is included

Most cryptographic protocols use cryptographic hash functions as a building block. The security analyses of these protocols typically assume that the hash functions are perfect (such as in the random oracle model). However, in practice, most widely deployed hash functions are far from perfect – and as a result, the analysis may miss attacks that exploit the gap between the model and the actual hash function used. We develop the first methodology to systematically discover attacks on security protocols that exploit weaknesses in widely deployed hash functions. We achieve this by revisiting the gap between theoretical properties of hash functions and the weaknesses of real-world hash functions, from which we develop a lattice of threat models. For all of these threat models, we develop fine-grained symbolic models. Our methodology’s fine-grained models cannot be directly encoded in existing state-of-the-art analysis tools by just using their equational reasoning. We therefore develop extensions for the two leading tools, T AMARIN and P RO V ERIF . In extensive case studies using our methodology, the extended tools rediscover all attacks that were previously reported for these protocols and discover several new variants.
Revegetation and Selected Terrain Disturbances Along the Trans-Alaska Pipeline, 1975-1978,

Abstract : Revegetation techniques along the trans-Alaska pipeline as employed by Alyeska Pipeline Service Company during the 1975-1978 summers were observed. Objectives included determining the success of treatments, identifying problem areas, and noticing long-term implications. Observations and photographs at 60 sites located along the trans-Alaska pipeline indicated frequent occurrence of successful revegetation as well as frequent problems, such as erosion, slope instability, poor scheduling of seed application, occurrence of weed species, failure to optimally reuse topsoil and fine-grained soil, and low rates of native species reinvation. Alyeska's visual impact engineering was observed to be very successful, as shown by high first-season survival. However, a related program for establishing willow cuttings was unsuccessful in 1977 but appeared very promising in 1978 largely due to improved management and more favorable growing conditions. Terrain disturbances due to the construction of the fuel gas line, snowpads, and oil spills were examined to identify and describe related environmental impacts on natural vegetation. Proper construction and use of snowpads minimized the extent and severity of disturbance. Crude oil spills, although damaging to vegetation did not cause total kill of vegetation, and certain types of spills may have only short-term effects. Results of restoration research by CRREL along the trans-Alaska pipeline are discussed.
"Listening In": Social Signal Detection for Crisis Prediction

Crises send out early warning signals; mostly weak and difficult to detect amidst the noise of everyday life. Signal detection based on social media enables early identification of such signals supporting pro-active organizational responses before a crisis occurs. Nonetheless, social signal detection based on Twitter data is not applied in crisis management in practice as it is challenging due to the high volume of noise. With OSOS, we introduce a method for open-domain social signal detection of crisis-related indicators in tweets. OSOS works with multi-lingual Twitter data and combines multiple state-of-the-art models for data pre-processing (SoMaJo) and data filtration (GPT-3). It excels in crisis domains by leveraging fine-tuned GPT-3 FT (Curie) model and achieving benchmark results in the CrisisBench dataset. The method was exemplified within a signaling service for crisis management. We were able to evaluate the proposed approach by means of a data set obtained from Twitter (X) in terms of performance in identifying potential social signals for energy-related crisis events.
NOTE TO USERS

4 Résumé . 5 Acknowledgements . 6 CHAPTER 1 . 7 Introduction . 8 Literature Review . Il The P DZ Domain: . Il The Nitric Oxide Synthase Family: . 12 nNOS: . 13 Vacl4 and Fablp/PIKfyve: . 15 AMPK and Contraction-Induced GLUT-4 Translocation: . 17 The Nitric Oxide Pathway and GLUT-4 Translocation: . 18 lnsu/in-Induced GLUT-4 Translocation: . 19 PIKfyve, Phosphoinositides and GLUT-4 Translocation: . 20 Figure 1-1. Contraction-Induced GLUT-4 Translocation and nNOS . 22 Figure 1-2. Insulin-Induced GL UT -4 Translocation and PIKfyve . 23 CHAPTER 2 . 24 Contribution of Authors . 25 Binding ofVac14 to Neuronal Nitric Oxide Synthase: . 26 Abstract: . 27 peter.mcpherson@mcgill.ca 2/64 Introduction: . 28 Material and Methods: . 31 Results: . 34 Discussion: . 39 Acknowledgements: . 42 Figure 2-1: Expression pattern ofVac14 . 43 Figure 2-2: Vac14 interacts with nNOS . 44 Figure 2-3: Vac14 interacts with the nNOS PDZ domain through an internai motif . 45 Figure 2-4: Characterization of the internai motif responsible for PDZ interactions . 46 Table 2-1: List of sense and anti-sense primers and oligonucleotides used for cloning . 47 Figure 2-5: BLAST alignments of the C-terminal regions of vertebrate orthologs of 5-HT28 receptor and Vac14 . 48 CHAPTER 3 . 49 Summary & Conclusion . 50 Figure 3-1: BLAST alignments on the vertebrate orthologs ofVac14 and AMPK y3 subunit, harboring the proposed PDZ binding consensus motif . 53 Figure 3-2. Regulation ofGLUT-4 Trafficking by Insulin and Contraction . 54 Abbreviations . 55 Bibliography . 57 Appendix . 64 Research Compliance Certificates: . 64
The 2011 off the Pacific coast of Tohoku Earthquake and its aftershocks observed by GEONET

The large displacement induced by the 2011 M 9.0 off the Pacific coast of Tohoku Earthquake was observed by GPS stations of the permanent GPS Earth Observation Network system (GEONET) in northeastern Japan. The displacement was characterized by the eastward displacement and subsidence in the Pacific coastal area. The horizontal displacement exceeded 5.3 m, which is the largest ever detected by GEONET. The mainshock was followed by a sequence of aftershocks. We processed the GPS data through a kinematic positioning strategy to clarify the deformation, including the deformation caused by the mainshock, with high temporal resolutions. The offsets calculated from the kinematic coordinates separately depict the coseismic displacements of the mainshock, the largest aftershock, and the third largest. The fault model for these earthquakes suggests that the largest (M 7.7) and third largest (M 7.3) aftershocks ruptured the southern and northern extensions of the mainshock fault, respectively.
Radiative‐dynamical climatology of the first‐generation Canadian middle atmosphere model

Abstract The Canadian Middle Atmosphere Modelling (MAM) project is a collaboration between the Atmospheric Environment Service (AES) of Environment Canada and several Canadian universities. Its goal is the development of a comprehensive General Circulation Model of the troposphere‐stratosphere‐mesosphere system, starting from the AES/CCCma third‐generation atmospheric General Circulation Model. This paper describes the basic features of the first‐generation Canadian MAM and some aspects of its radiative‐dynamical climatology. Standard first‐order mean diagnostics are presented for monthly means and for the annual cycle of zonal‐mean winds and temperatures. The mean meridional circulation is examined, and comparison is made between the steady diabatic, downward controlled, and residual streamfunctions. It is found that downward control holds quite well in the monthly mean through most of the middle atmosphere, even during equinoctal periods. The relative roles of different drag processes in determining the.
Time‐dependent mapping of the magnetic field at the core‐mantle boundary

We consider the problem of constructing a time-dependent map of the magnetic field at the core-mantle boundary. We use almost all the available data from the last 300 years to produce two maps, one for the period 1690–1840 and the other for 1840–1990. We represent the spatial dependency of the field using spherical harmonics, the time dependency using a cubic B-spline basis, and seek the smoothest solutions compatible with the observations. Particular attention must be paid to the effects of the crustal field in the data. We argue that for observations from permanent magnetic observatories the most efficient strategy is to use first-differences of annual means; for satellite data the most efficient strategy is simply to limit the number of data used so as to minimize any tendency to map the crustal field into the core field. The resulting model fits the observatory data better than any previous model yet has less power in the secular variation than previous models, demonstrating that very simple models fit the data. The resulting time-dependent field map exhibits much of the same structure in the field and its secular variation identified in earlier studies.
Design of a delay/Doppler mapping receiver for GPS remote sensing

This paper describes the design, construction and testing of a delay/Doppler-mapping receiver (DDMR) that was specially designed for gathering and processing Global Positioning System (GPS) reflected signals for earth remote sensing. The DDMR can process GPS L1-C/A signals received directly and after reflection, and compute complexvalued cross correlations of GPS L1-C/A reflected signals as well as navigation solutions acquired from direct signals in real time. The outputs of the DDMR can be used for altimetry applications, soil moisture measurement, ice characterization and ocean state retrieval, and other future applications. This paper presents the DDMR hardware architecture, signal processing issues and some preliminary experiment results.
A Head-Start to Teaching: Exploring the Early Field Experiences in Pre-service EFL Education in Turkey

This Article is brought to you for free and open access by the School of Education at DigitalCommons@URI. It has been accepted for inclusion in School of Education Faculty Publications by an authorized administrator of DigitalCommons@URI. For more information, please contact digitalcommons@etal.uri. edu. Citation/Publisher Attribution Hos, R. , Cinarbas, H. I. , & Yagci, H. (2019). A Head-Start to Teaching: Exploring the Early Field Experiences in Pre-service EFL Education in Turkey. International Journal of Teacher Education and Professional Development (IJTEPD), 2(2), 68-84. doi:10.4018/IJTEPD.2019070105 Available at: http://dx.doi. org/10.4018/IJTEPD.2019070105 Follow this and additional works at: https://digitalcommons.uri. edu/education_facpubs
Effects of heterogeneities in a braided stream channel sandbody on the simulation of oil recovery: a case study from the Lower Jurassic Statfjord Formation, Snorre Field, North Sea

Abstract Three heterogeneous models of a channel sandbody of braided stream origin were constructed by combining reservoir data from the middle reservoir unit of the Lower Jurassic Statfjord Formation in the Snorre Field in the Norwegian Sector of the North Sea, with facies and geometry data from an exposed analogue channel sandbody in the Pennsylvanian-Permian Maroon Formation, Colorado. Permeability classes corresponding to those in the Statfjord Formation were distributed according to facies variation in the analogue sandbody and to the recorded vertical distribution in the Middle Statfjord sandbodies. Relative permeability and capillary pressure curves were made for individual permeability classes. Two-dimensional (yz-plane) reservoir simulation of waterflooding was carried out with injection at the down-dip end and production at the up-dip end of the models, which measured 104 m × 8.75 m and had a structural dip of 8°. The results were compared with simulations on two reference models, one of a homogeneous sandbody and one with the permeability zonation organized in parallel layers with decreasing permeability from base to top. All models had the same volume-weighted arithmetic mean permeability. The 104 m long basic models were also compared with scaled-up versions measuring 312 m and 936 m, respectively. The simulations show that variation in internal heterogeneity has considerable impact on recovery efficiency. Compared with the homogeneous reference model, the heterogeneous models had reduced recovery efficiencies at water breakthrough of 11% to 33%, depending on the type and degree of heterogeneity, and a corresponding reduction in mean effective permeability of 9% to 42%. This study also demonstrated the importance of using capillary pressure data in simulations of this type. Capillary pressure allows imbibition into the low permeability rocks during waterflooding and explains the higher recovery efficiency on simulation runs on the scaled-up models compared to the short basic models. The effect of capillary pressure also results in higher recovery efficiency in runs with low flow rate than in runs with high rate. Similar simulation studies, also in 3-D, should be performed on various types of internal heterogeneities in complex fluvial reservoirs.
A comparison of methods for estimating soil characteristics in regional acidification models; an application of the MAGIC model to Scotland

Abstract. The results from an application of MAGIC (Model of Acidification of Groundwater In Catchments) to 733 Scottish catchments are presented. The availability of representative, good quality soil data is frequently limiting factor for biogeochemical modelling, particularly those involving modelling at various spatial scales. This study tests the sensitivity of MAGIC to soil input data derived from two different methodologies; the "nearest neighbour method" considers the closest representative soil profile to a catchment, and the "spatial weighting method" of all soil types identified in a catchment, based on a soil physico-chemical classification of Scotland. Soil data (soil depth, density, cation exchange capacity and base saturation) calculated using the "nearest neighbour method" and the "spatial weighting method" were highly variable, although the range of upper and lower limits were greater for soil data produced using the nearest neighbour method. In contrast to the predominantly organic soil data calculated by the nearest neighbour method, the spatially weighted soil parameters included a greater proportion of mineral soils. With regard to simulated surface water Acid Neutralising Capacity (ANC) for 1851, 1997 and 2050, MAGIC predictions were similar irrespective of the methodology used to determine soil input parameters. However, soil input data derived from both methods resulted in variable base saturation predictions. It is concluded that the "nearest neighbour" methodology is most appropriate if the objective is to determine the predicted response of the most acid- sensitive sites within a region in line with the approach used in Critical Laod mapping. On the other hand, "spatial weighting" integrates catchment soils and represents a more robust methodology by which to determine changes in median soil and water response in a regional context. The anticipated reductions in S emissions associated with the Second S Protocol are predicted to have a marginal beneficial effect on the recovery of soils and surface waters of Scotland.
GRAU DE MATEMÀTIQUES Treball final de grau

Artificial intelligence (AI) and more specifically machine learning (ML) have shown their potential by approaching or even exceeding human levels of accuracy for a variety of real-world problems. However, the highest accuracy for large modern datasets is often achieved by complex models that even experts struggle to interpret, creating a tradeoff between accuracy and interpretability. These models are known for being "black box" and opaque, which is especially problematic in industries like healthcare. Therefore, understanding the reasons behind predictions is crucial in establishing trust, which is fundamental if one plans to take action based on a prediction, or when deciding whether or not to implement a new model. Here is where explainable artificial intelligence (XAI) comes in by helping humans to comprehend and trust the results and output created by a machine learning model. This project is organised in 3 chapters with the aim of introducing the reader to the field of explainable artificial intelligence. Machine learning and some related concepts are introduced in the first chapter. The second chapter focuses on the theory of the random forest model in detail. Finally, in the third chapter, the theory behind two contemporary and influential XAI methods, LIME and SHAP, is formalised. Additionally, a public diabetes tabular dataset is used to illustrate an application of these two methods in the medical sector. The project concludes with a discussion of its possible future works.
Stabilization of Neutral Systems with Saturating Control Inputs

This paper focuses on the stabilization problem of neutral systems in the presence of time-varying delays and control saturation. Based on a descriptor approach and the use of a modiﬁed sector relation, global and local stabilization conditions are derived using Lyapunov-Krasovskii functionals. These conditions, formulated directly as linear matrix inequalities (LMIs), allow to relate the control law to be computed to a set of admissible initial conditions, for which the asymptotic and exponential stabilities of the closed-loop system are ensured. An extension of these conditions to the particular case of retarded systems is also provided. From the theoretical conditions, optimization problems with LMI constraints are therefore proposed to compute stabilizing state feedback gains with the aim of ensuring stability for a given set of admissible initial conditions or the global stability of the closed-loop system. A numerical example illustrates the application of the proposed results.
Soil Fertility Status of Cassava Fields in South Western Nigeria

Aims: Current information on nutrient status of south western Nigeria soils is needed to develop appropriate integrated nutrient management packages for sustainable cassava production within the area. This stu dy is designed to provide information on fertility status of some soils of the area. Study Design:A field survey. Place and Duration of Study:The study was carried out in March 2009 within two agro ecological zones of Osun state, south western Nigeria.
Graph Model Selection Using Maximum Likelihood

In recent years, there has been a proliferation of theoretical graph models, e.g., preferential attachment and small-world models, motivated by real-world graphs such as the Inter-net topology. To address the natural question of which model is best for a particular data set, we propose a model selection criterion for graph models. Since each model is in fact a probability distribution over graphs, we suggest using Maximum Likelihood to compare graph models and select their parameters. Interestingly, for the case of graph models, computing likelihoods is a difficult algorith-mic task. However, we design and implement MCMC algorithms for computing the maximum likelihood for four popular models: a power-law random graph model, a preferential attachment model, a small-world model, and a uniform random graph model. We hope that this novel use of ML will objectify comparisons between graph models.
Emergency Physician Twitter Use in the COVID-19 Pandemic as a Emergency Physician Twitter Use in the COVID-19 Pandemic as a Potential Predictor of Impending Surge: Retrospective Potential Predictor of Impending Surge: Retrospective Observational Study Observational Study

Background: The early conversations on social media by emergency physicians offer a window into the ongoing response to the COVID-19 pandemic. Objective: This retrospective observational study of emergency physician Twitter use details how the health care crisis has influenced emergency physician discourse online and how this discourse may have use as a harbinger of ensuing surge. Methods: Followers of the three main emergency physician professional organizations were identified using Twitter’s application programming interface. They and their followers were included in the study if they identified explicitly as US-based emergency physicians. Statuses, or tweets, were obtained between January 4, 2020, when the new disease was first reported, and December 14, 2020, when vaccination first began. Original tweets underwent sentiment analysis using the previously validated Valence Aware Dictionary and Sentiment Reasoner (VADER) tool as well as topic modeling using latent Dirichlet allocation unsupervised machine learning. Sentiment
Comparison of Parameterized Cloud Variability to ARM Data

Cloud parameterizations in large-scale models often try to predict the amount of sub-grid scale variability in cloud properties to address the significant non-linear effects of radiation and precipitation. Statistical cloud schemes provide an attractive framework to self-consistently predict the variability in radiation and microphysics but require accurate predictions of the width and asymmetry of the distribution of cloud properties. Data from the Atmospheric Radiation Measurement (ARM) program are used to assess the variability in boundary layer cloud properties for a well- mixed stratocumulus observed at the Oklahoma ARM site during the March 2000 Intensive Observing Period. Cloud boundaries, liquid water content, and liquid water path are retrieved from the millimeter wavelength cloud radar and the microwave radiometer. Balloon soundings, aircraft data, and satellite observations provide complementary views on the horizontal cloud inhomogeneity. It is shown that the width of the liquid water path probability distribution function is consistent with a model in which horizontal fluctuations in liquid water content are vertically coherent throughout the depth of the cloud. Variability in cloud base is overestimated by this model, however; perhaps because an additional assumption that the variance of total water is constant with altitude throughout the depth of the boundary layer is incorrect.