Miracle-dz/UniFAR-FTUs huggingface dataset:
Early Eocene Paromomyidae (Mammalia, Primates) from the Southern Bighorn Basin, Wyoming: Systematics and Evolution

Abstract We present a critical review of the alpha taxonomy and evolution of Eocene North American paromomyid primates, based on analysis of more than 570 stratigraphically controlled dental and gnathic specimens from the early Eocene of the southern Bighorn Basin, Wyoming (Wasatchian, Willwood Formation). In addition to documenting numerous previously unpublished specimens of known taxa (including deciduous teeth), we also describe a new species, Phenacolemur willwoodensis n. sp. , from the upper part of the Willwood Formation (Wa 5 and 6). The new species is intermediate in size between Phenacolemur simonsi and Phenacolemur citatus and has both primitive features (e.g., retention of m2–3 paraconids, relatively long molar trigonids) and derived traits (e.g., relatively reduced paraconid on m1 and no p4 paracristid, unlike Paromomys). Overall patterns of dental evolution in southern Bighorn Basin paromomyids provide some support for previously hypothesized periods of faunal change (Biohorizons). In particular, Phenacolemur praecox evolves into the similarly sized but morphologically distinct Phenacolemur fortior at Biohorizon A, and P. fortior is replaced by P. citatus just below Biohorizon B. Two taxa previously believed to have become extinct at Biohorizon A (Ignacius graybullianus, P. simonsi) are shown to have persisted about a million years longer than previously thought. The Bighorn Basin paromomyids are of general interest in comprising a very dense sample that allows for the study of patterns of evolution against the backdrop of well-understood patterns of change in other mammalian lineages, and in climatic variables.
Antarctic seismic stratigraphy

This report provides a brief overiew of Antarctic seismic reflection surveys, and how they are used to map Antarctic seismic stratigraphy and, inconjunction with drilling data, help decipher geologic and glacial histories of circum-Antarctic offshore regions. Citation: Bart, P.J. (2007), Antarctic seismic stratigraphy, in Antarctica: A Keystone in a Changing World __ Online Proceedings of the 10 ISAES, edited by A.K. Cooper, C.R. Raymond, et al., USGS Open-File Report 2007-1047, MWR02B, 5 p.
RegT-Band: a tropical band version of RegCM4

We present RegT-Band, a tropical band version of the regional climate model RegCM4, and analyze a 5 yr simulation for the period 1998−2002 with observed sea-surface temperature (SST) and lateral boundary condition forcing. The domain extends from 50° S to 50° N and covers the entire tropics at a grid spacing of about 39 km, i.e. it includes lateral boundary forcing only at the southern and northern boundaries. RegT-Band captures the basic features of the tropical circulation and associated precipitation patterns. The most noticeable model deficiencies occur over the Indian Ocean, where the convective parameterization used presents some problems. Monsoon precipitation patterns over different regions are captured, although the model shows a tendency for an early onset of the Indian and northern Australian monsoon. The model also captures the ENSO signal on the precipitation anomaly patterns for the 1998 El Niño event compared to the 2000 La Niña event. Although further testing is needed, this simulation shows encouraging results towards the use of RegT-Band for the study of tropical climate processes.
Automatic detection of alpine rockslides in continuous seismic data using hidden Markov models

Data from continuously recording permanent seismic networks can contain information about rockslide occurrence and timing complementary to eyewitness observations and thus aid in construction of robust event catalogs. However, detecting infrequent rockslide signals within large volumes of continuous seismic waveform data remains challenging and often requires demanding manual intervention. We adapted an automatic classification method using hidden Markov models to detect rockslide signals in seismic data from two stations in central Switzerland. We first processed 21 known rockslides, with event volumes spanning 3 orders of magnitude and station event distances varying by 1 order of magnitude, which resulted in 13 and 19 successfully classified events at the two stations. Retraining the models to incorporate seismic noise from the day of the event improved the respective results to 16 and 19 successful classifications. The missed events generally had low signal‐to‐noise ratio and small to medium volumes. We then processed nearly 14 years of continuous seismic data from the same two stations to detect previously unknown events. After postprocessing, we classified 30 new events as rockslides, of which we could verify three through independent observation. In particular, the largest new event, with estimated volume of 500,000 m3, was not generally known within the Swiss landslide community, highlighting the importance of regional seismic data analysis even in densely populated mountainous regions. Our method can be easily implemented as part of existing earthquake monitoring systems, and with an average event detection rate of about two per month, manual verification would not significantly increase operational workload.
A Systematic Comparison of English Noun Compound Representations

Building meaningful representations of noun compounds is not trivial since many of them scarcely appear in the corpus. To that end, composition functions approximate the distributional representation of a noun compound by combining its constituent distributional vectors. In the more general case, phrase embeddings have been trained by minimizing the distance between the vectors representing paraphrases. We compare various types of noun compound representations, including distributional, compositional, and paraphrase-based representations, through a series of tasks and analyses, and with an extensive number of underlying word embeddings. We find that indeed, in most cases, composition functions produce higher quality representations than distributional ones, and they improve with computational power. No single function performs best in all scenarios, suggesting that a joint training objective may produce improved representations.
Journal of Internet Banking and Commerce the Relationship between Consumer Confidence Index and Online Credit Card Using in Turkey: New Evidence from Frequency Domain Causality Test Online Shopping and Risk Perception

Monthly data for the period between January 2008 and December 2012 were examined in this study which investigated the relationship between consumer confidence index (CCI) and online credit card using (CCU). The variables were found to have an integrated structure after testing of the collected data with Hatemi-J cointegration test (2008) which enables two-structural break. It has been observed that the results are inconsistent when the relationship between these two variables examined with Toda Yamamoto (1995) and Hacker Hatemi-J (2006) causality tests. Therefore, frequency domain causality test has been used and the conclusion reached that a one-way and temporary relationship from consumer confidence index to online credit card using. It's seen that the existence of this relationship supports the studies in the literature. Development of Internet and information technologies changed the structure of sales channels day after day. This new economic system which can be described as e-commerce, online shopping, virtual market and so on provided great conveniences to manufacturers and retailers in terms of reaching to consumers Thereby the physical markets where the exchanges occur with the manufacturers and consumers have been turned into virtual markets. This paved the way for the rise of online shopping. Shopping made through Internet is not an instant decision-making activity; conversely is a process which includes different activities inside. Consumers prefer to shop on the Internet for reasons such as ease of information access, unlimited choice, low price, speed and customization etc. In this context, it can be easily expressed that online shopping facilitates consumers' lives in today's hectic working tempo. However, there are also some risks as well as these conveniences of online shopping. Information asymmetry and unobservability can be shown as the main reason of risk in online shopping (Tan and Thoen, 2010; Liu and Wei, 2003). Information asymmetry refers to the uncertainties arising from different types of information parties have (Sandmo, 1999). Consumers can not know exactly the quality of product/service whether demonstrated on the Internet because of the information asymmetry; on the contrary the seller has full information. In other words, the consumer thinks that the seller would benefit from this process in an opportunistic way. In addition, consumers can not evaluate the quality of product directly due to the unobservability (Wan et al., 2012). Consumers do not have the ability of experiences such as try, taste, touch and smell as virtually in online shopping. This can be shown …
Response of growing pigs to the inclusion of hybrid rye in low or high-energy diets

Abstract Previous research has shown reduced feed intake and growth rate in pigs fed diets with hybrid rye replacing wheat. A reduction in growth rate caused by reduced feed intake will conceivably be counteracted by increasing the dietary energy level. Our objective, therefore, was to determine the effects of 40% hybrid rye inclusion replacing wheat in diets formulated to be either low or high net energy (NE) on growth, feed intake, energy digestibility, and lesion scores in growing-finishing pigs. We hypothesized that pigs fed 40% hybrid rye would perform better on the high than the low energy diets. A total of 160 pigs (body weight [BW] 70.1 kg) housed in 32 pens, 5 pigs per pen, were fed diets with 0% or 40% hybrid rye (var. ‘KWS Bono’; KWS LOCHOW GMBH), either with low (2,350) or high (2,450) kcal NE per kg of diet over two growth phases (phase 1; 70 to 85 kg BW; phase 2; 85 to 130 kg BW). The BW, and feed disappearance were measured on days 0, 8, 17, 28, 42, and 50. Fecal samples obtained in phase 2 (~100 kg BW) were used to calculate apparent total tract digestibility (ATTD) of gross energy (GE). Lesion scores were measured weekly. The ATTD of GE was unaffected by rye inclusion and was reduced in low vs. high NE diets. Overall, (days 0 to 50), pigs fed the low-energy rye diet gained 0.08 kg/d less (P < 0.01) than those fed the high-energy rye diet or the low-energy diet without rye, which was caused by a reduced weight gain during the initial 17 d of the trial. Final BW and overall feed intake were not affected by rye inclusion or NE level. The NE intake was greater (P < 0.05) and feed efficiency (G:F) was reduced (P < 0.05) in pigs fed rye diets compared to those fed diets without rye, whereas there was no effect of NE level on NE intake or G:F. There was no effect of rye inclusion or NE level on lesion scores. In conclusion, pigs can be fed diets including 40% hybrid rye with only minor changes in growth performance. Increasing the NE level of the first phase diet in the grower-finisher barn may be useful to avoid a reduction in growth performance when feeding hybrid rye.
Validity Arguments for Automated Essay Scoring of Young Students’ Writing Traits

ABSTRACT Machines have a long-demonstrated ability to find statistical relationships between qualities of texts and surface-level linguistic indicators of writing. More recently, unlocked by artificial intelligence, the potential of using machines to identify content-related writing trait criteria has been uncovered. This development is significant, especially in formative assessment contexts where feedback is key. Yet the extent to which writing traits can be validly scored by machines remains under-researched, especially in the K-12 context. The present study investigated the validity of machine learning (ML) models designed for students in grades 3–6 to score three writing traits: task fulfillment, organization and coherence, and vocabulary and expression. The study utilized an argument-based approach, focusing on two primary inferences: evaluation and explanation. The evaluation inference investigated human-machine score alignment, the ability for the models to detect off-topic and gibberish responses, and the consistency of human-machine score alignment across grades and language backgrounds. The explanation inference investigated the relevance of features used in the models. Results indicated that human-machine score alignment was sufficient for all writing traits; however, validity concerns were raised regarding the models’ performances detecting off-topic and gibberish responses and the consistency across sub-groups. Implications for language assessment professionals and other educators were discussed.
The Influence of Market Orientation on Export Performance of Small and Medium-Sized Enterprises (SMEs) in Rwanda

Grounded on the resource-based theory, this study examined the role of market orientation (MO) dimensions in the export performance of small and medium enterprises (SMEs) in Rwanda. The study adopted an explanatory survey design and a cross-sectional strategy. Data were collected from a final sample of 105 respondents selected from 58 exporting firms purposively chosen due to the absence of a formal sampling frame. The collected data were analyzed using the structural equation modelling (SEM) technique with the analysis of moment structure (AMOS) version 25.0. The findings revealed that market intelligence generation (MIG) and market intelligence responsiveness (MIR) have a positive and significant influence on export performance but the influence of market intelligence diffusion (MID) was weak and insignificant. The mixed findings of this study confirmed that the development of MO is important for a firm to go international and that not all dimensions of MO are equally important factors for export performance, so much so that only MI and MIG contributed significantly to export performance. The proposed model, which was based on RBT, was therefore partially validated. The study recommends that policymakers develop an export education strategy for exporting SMEs to improve their performance.
Geophysical study of subsurface structure in southern Owens Valley, California

Gravity and seismic measurements in southern Owens Valley, California, have outlined a deep subsurface trough, bounded throughout the greater part of its length by steep faults. Depths to the bedrock floor along the central part of the valley range from 3,000 to 9,000 ft below the surface. The subsurface trough is divided into two parts, a narrow channel‐like depression near Lone Pine bounded by northwest‐trending faults, and a broad basin at Owens Lake bounded by a more complex series of border faults. The bedrock ridge that crops out to form Alabama Hills is shown to extend from Independence to the north edge of Owens Lake, nearly twice its visible extent. The main direction of faults that have formed the valley is northwest; subsidiary faults trend north, northeast, and east. A fairly sharp velocity boundary within the Cenozoic valley deposits suggests a change in the rate and character of deposition which was probably the result of renewed uplift in the nearby mountains.
Neuroscience and Biobehavioral Reviews Review Moment-to-moment Brain Signal Variability: a next Frontier in Human Brain Mapping?

Keywords: Brain signal variability Noise Complexity Dynamics fMRI EEG MEG a b s t r a c t Neuroscientists have long observed that brain activity is naturally variable from moment-to-moment, but neuroimaging research has largely ignored the potential importance of this phenomenon. An emerging research focus on within-person brain signal variability is providing novel insights, and offering highly predictive, complementary, and even orthogonal views of brain function in relation to human lifespan development, cognitive performance, and various clinical conditions. As a result, brain signal variability is evolving as a bona fide signal of interest, and should no longer be dismissed as meaningless noise when mapping the human brain.
Finite-element analysis of a piled embankment with reinforcement and subsoil

In 2014, the authors of this paper considered predictions of reinforcement tension in a piled embankment from British standard BS 8006 published in 2010 and the 2012 amended version, and compared the results with finite-element model predictions. In keeping with BS 8006, any contribution from the subsoil beneath the embankment was ignored. The present paper extends that earlier work by also considering the potentially beneficial contribution of a lightly overconsolidated clay subsoil layer, both in the finite-element predictions and as a simple modification to the BS 8006 predictive method. It is assumed that there is no ‘working platform’ (granular) material below the pile cap level, and that the water table in the subsoil does not drop, since either of these factors would be likely to significantly reduce the ability of the subsoil to carry load from the embankment. As anticipated, the subsoil support reduces reinforcement tension. When compared to the finite-element results the proposed modified BS 800.
Neuroscience and Biobehavioral Reviews

Central nervous system diseases are not currently diagnosed based on knowledge of biological mechanisms underlying their symptoms. Greater understanding may be offered through an agnostic approach to traditional disease categories, where learning more about shared biological mechanisms across conditions could potentially reclassify sub-groups of patients to allow realisation of more effective treatments. This review represents the output of the collaborative group “PRISM”, tasked with considering assay choices for assessment of attention and working memory in a transdiagnostic cohort of Alzheimer’s disease and schizophrenia patients exhibiting symptomatic spectra of social withdrawal. A multidimensional analysis of this nature has not been previously attempted. Nominated assays (continuous performance test III, attention network test, digit symbol substitution, N-back, complex span, spatial navigation in a virtual environment) reflected a necessary compromise between the need for broad assessment of the neuropsychological constructs in question with several pragmatic criteria: patient burden, compatibility with neurophysiologic measures and availability of preclinical homologues.
Evaluation of the snow cover variation in the Canadian Regional Climate Model over eastern Canada using passive microwave satellite data

Snow cover from a 3 year (1992/93–1994/95) simulation of the Canadian Regional Climate Model (CRCM; operational version 3·5·3) driven by National Centers for Environmental Prediction analysis data over eastern Canada was evaluated using passive‐microwave‐derived snow cover information from the daily Special Sensor Microwave/Imager (SSM/I) data. The presence of snow on the ground was derived from 19 and 37 GHz normalized difference brightness temperature series to which a low‐pass filter was applied to remove day‐to‐day noise, and thresholding was also applied at different levels for taking into account the variation in vegetation density. The thresholds calibrated for four density classes with surface observations show a mean residual underestimation in the SSM/I number of days with snow cover during seasonal transition of −7 days. Compared with the SSM/I‐derived information, the CRCM was found to delay systematically the onset of the snow cover (typically 50 days late) and to ablate snow too quickly during the spring melt period (typically 30 days early). These systematic errors were attributed to the single‐layer force–restore representation of the soil–snow layer and contributed to snow cover extent underestimations in the order of 9% relative to the total area. Copyright © 2004 John Wiley & Sons, Ltd.
Neuroscience and Biobehavioral Reviews Review Reconsidering Anhedonia in Depression: Lessons from Translational Neuroscience

Anhedonia is a core symptom of major depressive disorder (MDD), the neurobiological mechanisms of which remain poorly understood. Despite decades of speculation regarding the role of dopamine (DA) in anhedonic symptoms, empirical evidence has remained elusive, with frequent reports of contradictory findings. In the present review, we argue that this has resulted from an underspecified definition of anhedonia, which has failed to dissociate between consummatory and motivational aspects of reward behavior. Given substantial preclinical evidence that DA is involved primarily in motivational aspects of reward, we suggest that a refined definition of anhedonia that distinguishes between deficits in pleasure and motivation is essential for the purposes of identifying its neurobiological substrates. Moreover, bridging the gap between preclinical and clinical models of anhedonia may require moving away from the conceptualization of anhedonia as a steady-state, mood-like phenomena. Consequently, we introduce the term " decisional anhedonia " to address the influence of anhedonia on reward decision-making. These proposed modifications to the theoretical definition of anhedonia have implications for research, assessment and treatment of MDD.
Neuroscience and Biobehavioral Reviews the Role of High-frequency Oscillatory Activity in Reward Processing and Learning

Oscillatory activity has been proposed as a key mechanism in the integration of brain activity of distant structures. Particularly, high frequency brain oscillatory activity in the beta and gamma range has received increasing interest in the domains of attention and memory. In addition, a number of recent studies have revealed an increase of beta–gamma activity (20–35 Hz) after unexpected or relevant positive reward outcomes. In the present manuscript we review the literature on this phenomenon and we propose that this activity is a brain signature elicited by unexpected positive outcomes in order to transmit a fast motivational value signal to the reward network. In addition, we hypothesize that beta–gamma oscillatory activity indexes the interaction between attentional and emotional systems, and that it directly reflects the appearance of unexpected positive rewards in learning-related contexts.
Neuroscience and Biobehavioral Reviews on the Functions, Mechanisms, and Malfunctions of Intracortical Contextual Modulation

A broad neuron-centric conception of contextual modulation is reviewed and reassessed in the light of recent neurobiological studies of amplification, suppression, and synchronization. Behavioural and computational studies of perceptual and higher cognitive functions that depend on these processes are outlined, and evidence that those functions and their neuronal mechanisms are impaired in schizophrenia is summarized. Finally, we compare and assess the long-term biological functions of contextual modulation at the level of computational theory as formalized by the theories of coherent infomax and free energy reduction. We conclude that those theories, together with the many empirical findings reviewed, show how contextual modulation at the neuronal level enables the cortex to flexibly adapt the use of its knowledge to current circumstances by amplifying and grouping relevant activities and by suppressing irrelevant activities.