Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of print exposure on sentence processing and memory in older adults: Evidence for efficiency and reserve

ABSTRACT The present study was an examination of how exposure to print affects sentence processing and memory in older readers. A sample of older adults (N = 139; Mean age = 72) completed a battery of cognitive and linguistic tests and read a series of sentences for recall. Word-by-word reading times were recorded and generalized linear mixed effects models were used to estimate components representing attentional allocation to word-level and textbase-level processes. Older adults with higher levels of print exposure showed greater efficiency in word-level processing and in the immediate instantiation of new concepts, but allocated more time to semantic integration at clause boundaries. While lower levels of working memory were associated with smaller wrap-up effects, individuals with higher levels of print exposure showed a reduced effect of working memory on sentence wrap-up. Importantly, print exposure was not only positively associated with sentence memory, but was also found to buffer the effects of working memory on sentence recall. These findings suggest that the increased efficiency of component reading processes that come with life-long habits of literacy buffer the effects of working memory decline on comprehension and contribute to maintaining skilled reading among older adults.
Output and Inflation in Models of the Business Cycle with Nominal Rigidities: Some Counterfactual Evidence

This paper examines the relationship between cyclical output and inflation in models commonly used for monetary policy analysis. This includes models that incorporate the New Keynesian, Fuhrer-Moore and backward-looking Phillips curves. The main finding is that these models imply a strong negative relationship between inflation and output, a result that is at odds with the data. The fact that New Keynesian models yield counterfactual implications is not new,the novelty of the paper lies in the fact that the finding extends to the other variants, such as the backward-looking Phillips Curve, which has been put forward as displaying superior dynamics.
Interactive comment on “ Biogeochemical fluxes and fate of diazotroph derived nitrogen in the food web after a phosphate enrichment : Modeling of the VAHINE mesocosms experiment ” by A .

The VAHINE mesocosm experiment in the oligotrophic waters of the Noumea lagoon (New Caledonia), where high N2 fixation rates and abundant diazotroph organisms were observed, aimed to assess the role of the nitrogen input through N2 fixation on carbon production and export, and to study the fate of diazotroph-derived nitrogen (DDN) throughout the planktonic food web. A 1D-vertical biogeochemical mechanistic model was used in addition to the in situ experi5 ment to complement our comprehension enrich our understanding of the dynamics of the planktonic ecosystem and the main biogeochemical carbon (C), nitrogen (N) and phosphate (P) fluxes. The mesocosms were intentionally enriched with 0.8 μmol. L 1 of inorganic P to trigger the development of diazotrophs and amplify biogeochemical fluxes. Two simulations were run, one with and the other without the phosphate enrichment. In the P-enriched simulation, N2 fixation, primary pro10 duction and C export increased by 201, 208 and 87 %, respectively, consistent with the observed trends observed in the mesocosms (+ 124 %, + 141 %, + 261 % for N2 fixation, PP and C export, respectively). The increase in primary and export productions became significant 5-10 days after the DIP enrichment, indicating that i) several days were necessary to obtain a significant response at the population scale, and ii) classical methods (short-term microscosms experiments) used to quantify 15 nutrient limitations of primary production may not be relevant. 5-10 days were necessary to obtain an increase in primary and export productions after the DIP enrichment thereby suggesting that classical methods (short-term microcosms experiments) used to quantify nutrient limitations of primary production may not be relevant. The model allowed enabled us to follow monitor the fate of fixed N2 by providing over time the proportion of DDN in each compartment (mineral and organic) of the 20 model. At the end of the simulation (25 days), 43 % of the DDN was found in the non-diazotroph organisms, 33 % in diazotrophs, 16 % in the dissolved organic nitrogen pool, 3 % in the particulate
Factors associating with differences in the incidence of renal replacement therapy among elderly: data from the ERA-EDTA Registry

Background The incidence of renal replacement therapy (RRT) in the general population ≥75 years of age varies considerably between countries and regions in Europe. Our aim was to study characteristics and survival of elderly RRT patients and to find explanations for differences in RRT incidence. Methods Patients ≥75 years of age at the onset of RRT in 2010-2013 from 29 national or regional registries providing data to the European Renal Association-European Dialysis and Transplant Association Registry were included. Chi-square and Mann-Whitney U tests were used to assess variation in patient characteristics and linear regression was used to study the association between RRT incidence and various factors. Kaplan-Meier curves and Cox regression were employed for survival analyses. Results The mean annual incidence of RRT in the age group ≥75 years of age ranged from 157 to 924 per million age-related population. The median age at the start of RRT was higher and comorbidities were less common in areas with higher RRT incidence, but overall the association between patient characteristics and RRT incidence was weak. The unadjusted survival was lower in high-incidence areas due to an older age at onset of RRT, but the adjusted survival was similar [relative risk 1.00 (95% confidence interval, 0.97-1.03)] in patients from low- and high-incidence areas. Conclusions Variation in the incidence of RRT among the elderly across European countries and regions is remarkable and could not be explained by the available data. However, the survival of patients in low- and high-incidence areas was remarkably similar.
MASCOT: Faster Malicious Arithmetic Secure Computation with Oblivious Transfer

We consider the task of secure multi-party computation of arithmetic circuits over a finite field. Unlike Boolean circuits, arithmetic circuits allow natural computations on integers to be expressed easily and efficiently. In the strongest setting of malicious security with a dishonest majority --- where any number of parties may deviate arbitrarily from the protocol --- most existing protocols require expensive public-key cryptography for each multiplication in the preprocessing stage of the protocol, which leads to a high total cost. We present a new protocol that overcomes this limitation by using oblivious transfer to perform secure multiplications in general finite fields with reduced communication and computation. Our protocol is based on an arithmetic view of oblivious transfer, with careful consistency checks and other techniques to obtain malicious security at a cost of less than 6 times that of semi-honest security. We describe a highly optimized implementation together with experimental results for up to five parties. By making extensive use of parallelism and SSE instructions, we improve upon previous runtimes for MPC over arithmetic circuits by more than 200 times.
Beyond HbA1c: Comparing Glycemic Variability and Glycemic Indices in Predicting Hypoglycemia in Type 1 and Type 2 Diabetes.

BACKGROUND Hypoglycemia is the major impediment to therapy intensification in diabetes. Although higher individualized HbA1c targets are perceived to reduce the risk of hypoglycemia in those at risk of hypoglycemia, HbA1c itself is a poor predictor of hypoglycemia. We assessed the use of glycemic variability (GV) and glycemic indices as independent predictors of hypoglycemia. METHODS A retrospective observational study of 60 type 1 and 100 type 2 diabetes subjects. All underwent professional continuous glucose monitoring (CGM) for 3-6 days and recorded self-monitored blood glucose (SMBG). Indices were calculated from both CGM and SMBG. Statistical analyses included regression and area under receiver operator curve (AUC) analyses. RESULTS Hypoglycemia frequency (53.3% vs. 24%, P < 0.05) and %CV (40.1% ± 10% vs. 29.4% ± 7.8%, P < 0.001) were significantly higher in type 1 diabetes compared with type 2 diabetes. HbA1c was, at best, a weak predictor of hypoglycemia. %CVCGM, Low Blood Glucose Index (LBGI)CGM, Glycemic Risk Assessment Diabetes Equation (GRADE)HypoglycemiaCGM, and Hypoglycemia IndexCGM predicted hypoglycemia well. %CVCGM and %CVSMBG consistently remained a robust discriminator of hypoglycemia in type 1 diabetes (AUC 0.88). In type 2 diabetes, a combination of HbA1c and %CVSMBG or LBGISMBG could help discriminate hypoglycemia. CONCLUSION Assessment of glycemia should go beyond HbA1c and incorporate measures of GV and glycemic indices. %CVSMBG in type 1 diabetes and LBGISMBG or a combination of HbA1c and %CVSMBG in type 2 diabetes discriminated hypoglycemia well. In defining hypoglycemia risk using GV and glycemic indices, diabetes subtypes and data source (CGM vs. SMBG) must be considered.
Inflation and Balanced-Path Growth with Alternative Payment Mechanisms

The paper shows that contrary to conventional wisdom an endogenous growth economy with human capital and alternative payment mechanisms can robustly explain major facets of the long run inflation experience. A negative inflation-growth relation is explained, including a striking nonlinearity found re-peatedly in empirical studies. A set of Tobin (1965) effects are also explained and, further, linked in magnitude to the growth effects through the interest elasticity of money demand. Undis-closed previously, this link helps fill out the intuition of how the inflation experience can be plausibly explained in a robust fashion with a model extended to include credit as a payment mechanism.
Advantages of Using the ANSI/ASHRAE 110-1995 Tracer Gas Test Method Versus the ANSI/AIHA Z9.5-1992 Face Velocity Test Method for Chemical Laboratory Hood Certification

A total of 484 tests were performed on chemical laboratory Hoods (chemical hoods), using the ANSI/AIHA Z9.5-1992 (American National Standard Institute / American Industrial Hygiene Association, Laboratory Ventilation Standard) test method (ANSI-1992). Same numbers of the tests were performed on same chemical hoods, using the ANSI/ASHRAE 110-1995 (American National Standards Institute/American Society of Heating, Refrigerating, and Air Conditioning Engineers, Method of Testing Performance of Laboratory Fume Hoods) test method (ASHRAE 110). The three types of chemical hoods available for this study were Constant Air Volume (CAV), Variable Air Volume (VAV), and Low Flow. Overall, CAV hoods had the highest passing rate for the ASHRAE 110 (83%) followed by VAV hoods (82%) and low flow hoods (68%). The X2 test for homogeneity found a statistically significant difference between the test outcomes (pass/fail) of the ASHRAE 110 and the ANSI-1992 methods (X2 = 4.248, P=0.038) for VAV hoods only. Overall, 18% of the CAV and VAV chemical hoods tested in the 80- 120 feet per minute (fpm) average face velocities, failed to meet the ASHRAE 110 test criteria. If the ANSI-1992 test method was performed alone, 18% of the chemical hoods would be certified while they were not able to meet the ASHRAE 110 criteria. Logistic regression analysis for VAV and CAV chemical hoods revealed that for VAV chemical hoods, the ASHRAE = Velocity model and for CAV chemical hoods, the multi variable regression model ASHRAE = ANSI + Velocity were appeared to be the best model for the ASHRAE 110 test outcome prediction.
Profiling OSN Users Based on Temporal Posting Patterns

In this paper, we study the posting behavior of OSN users, in particular the posting frequency and temporal patterns, and consider possible interpretations of how users use the platform. At the aggregate (macro) level, we find two distinct peaks, one during morning working hours, and one in the evening. The morning peak is more pronounced for frequent posters, while the evening peak is pronounced in the remaining users. We postulate that this difference results from qualitatively different usage of the OSN platform (e.g. for work, with customers, etc.) than purely social interactions (e.g., friends, family, etc.). We also study user posting behavior at an individual (micro) level and apply LDA to cluster user temporal patterns, interpret our results. Our study provides possibly new insights into user activity in today's OSNs, and suggests a framework for profiling users based on their posting activities. In the process, we provide a novel application of LDA, to temporal user posting behavior by equating the time epochs of posts to words in documents. We believe our approach will complement other methods of user profiling based on static demographic information and friendship network information.
Quantitative morphometry of hippocampal pyramidal cells: Differences between anatomical classes and reconstructing laboratories

The dendritic trees of hippocampal pyramidal cells play important roles in the establishment and regulation of network connectivity, synaptic plasticity, and firing dynamics. Several laboratories routinely reconstruct CA3 and CA1 dendrites to correlate their three‐dimensional structure with biophysical, electrophysiological, and anatomical observables. To integrate and assess the consistency of the quantitative data available to the scientific community, we exhaustively analyzed 143 completely reconstructed neurons intracellularly filled and digitized in five different laboratories from 10 experimental conditions. Thirty morphometric parameters, including the most common neuroanatomical measurements, were extracted from all neurons. A consistent fraction of parameters (11 of 30) was significantly different between CA3 and CA1 cells. A considerably large number of parameters was also found that discriminated among neurons within the same morphological class, but reconstructed in different laboratories. These interlaboratory differences (8 of 30 parameters) far outweighed the differences between experimental conditions within a single lab, such as aging or preparation method (at most two significant parameters). The set of morphometrics separating anatomical regions and that separating reconstructing laboratories were almost entirely nonoverlapping. CA3 and CA1 neurons could be distinguished by global quantities such as branch order and Sholl distance. Differences among laboratories were largely due to local variables such as branch diameter and local bifurcation angles. Only one parameter (a ratio of branch diameters) separated both morphological classes and reconstructing laboratories. Compartmental simulations of electrophysiological activity showed that both differences between anatomical classes and reconstructing laboratories could dramatically affect the firing rate of these neurons under different experimental conditions. J. Comp. Neurol. 473:177–193, 2004. © 2004 Wiley‐Liss, Inc.
Multilingual Distributed Representations without Word Alignment

Distributed representations of meaning are a natural way to encode covariance relationships between words and phrases in NLP. By overcoming data sparsity problems, as well as providing information about semantic relatedness which is not available in discrete representations, distributed representations have proven useful in many NLP tasks. Recent work has shown how compositional semantic representations can successfully be applied to a number of monolingual applications such as sentiment analysis. At the same time, there has been some initial success in work on learning shared word-level representations across languages. We combine these two approaches by proposing a method for learning distributed representations in a multilingual setup. Our model learns to assign similar embeddings to aligned sentences and dissimilar ones to sentence which are not aligned while not requiring word alignments. We show that our representations are semantically informative and apply them to a cross-lingual document classification task where we outperform the previous state of the art. Further, by employing parallel corpora of multiple language pairs we find that our model learns representations that capture semantic relationships across languages for which no parallel data was used.
Cross-linguistic influence at the discourse–syntax interface: Insights from anaphora resolution in child second language learners of Italian

This paper reports the results of an experimental study on the resolution of intra-sentential anaphora in Italian by two groups of 13–14-year-olds: monolingual native Italian speakers and highly proficient child second language (L2) learners of Italian whose native language is Croatian. In a picture selection task the participants were asked to identify antecedents of null and overt subject pronouns in ambiguous forward and backward anaphora sentences. Our assumption in the paper was that Italian and Croatian do not differ with respect to the antecedent biases of null and overt subject pronouns in the contexts under investigation. As predicted, the L2 learners expressed pragmatically appropriate antecedent preferences in all conditions. They even selected the pragmatically inappropriate subject antecedent for the overt pronoun less often than the native speakers, especially in backward anaphora. The L2 learners’ antecedent preferences closely mirror those established in previous research for their age-matched monolingual Croatian peers. We take this as evidence for our position that cross-linguistic influence is operative at the discourse–syntax influence in child L2 acquisition and that it might be the main cause of non-target-like behaviour of some groups of highly proficient bilinguals concerning certain properties pertaining to this interface.
AHRQ Grant Final Report Title of Project : Exploring Clinically-relevant Image Retrieval for Diabetic Retinopathy Diagnosis

Purpose: The objectives of the project were to develop a content-based retrieval system for referencing diabetic retinal images to improve diagnosis and to develop a prototypical DR image management system to improve reviewers’ diagnostic performance. Scope: Diabetic retinopathy (DR) is a common cause of blindness. Despite advances in diabetes care, visual impairment is still a devastating complication. The project intended to develop new methodologies and computer software tools for assisting clinicians in reviewing fundus images for DR evaluation. Methods: The key approach of the project was to develop a machine-learning-based image retrieval engine that would be able to retrieve a number of reference images from a database of standard images or previously-diagnosed images, for any given new fundus image to be diagnosed. A key aspect of the method was on designing feature extractors that can detect image features appropriate for distinguishing DR lesions. The method was evaluated by examining whether the retrieved images have similar DR severity to that of the new image. Results: A database containing image samples of two representative DR lesions, neovascularization and microaneurysm, was used to evaluate the developed retrieval engine. On average, the proposed method was able to outperform other approaches in the literature. A retrieval interface was also developed to support the deployment of the retrieval engine in a user-friendly fashion. The source code and the dataset were posted on a Website for other researchers to further explore.
Relationship between motion sickness susceptibility and vestibulo-ocular reflex gain and phase.

BACKGROUND It has been proposed that individual susceptibility to motion sickness is related to the vestibulo-ocular reflex (VOR) through the activation of the velocity storage mechanism. OBJECTIVE We investigated whether motion sickness level was related to the gain and phase of the VOR. METHODS VOR gain and phase were measured in 214 subjects while they rotated in yaw at 0.01 Hz, 0.02 Hz, 0.04 Hz, 0.08 Hz, and 0.16 Hz in darkness, and results were compared to the severity of symptoms the subjects experienced during subsequent tests to provoke motion sickness. These tests included cross-coupled angular accelerations, sudden stops in light or in dark, off-vertical axis rotation, and parabolic flight. The subjects were grouped according to the motion sickness level reached during these tests (none, low, medium, or high). RESULTS No correlation was found between the horizontal VOR gain and motion sickness level. However, for the subjects with high motion sickness level, the VOR phase lead was significantly lower during rotation at frequencies ranging from 0.04 Hz to 0.16 Hz (i.e. the VOR time constant was longer) than the other motion sickness groups. CONCLUSION These results support the theory that the longer the time constant for velocity storage, the more severe the motion sickness.
Automatic labeling of software components and their evolution using log-likelihood ratio of word frequencies in source code

As more and more open-source software components become available on the internet we need automatic ways to label and compare them. For example, a developer who searches for reusable software must be able to quickly gain an understanding of retrieved components. This understanding cannot be gained at the level of source code due to the semantic gap between source code and the domain model. In this paper we present a lexical approach that uses the log-likelihood ratios of word frequencies to automatically provide labels for software components. We present a prototype implementation of our labeling/comparison algorithm and provide examples of its application. In particular, we apply the approach to detect trends in the evolution of a software system.
On vertex stability of complete k-partite graphs

Let \(H\) be any graph. We say that graph \(G\) is \(H\)-stable if \(G-u\) contains a subgraph isomorphic to \(H\) for an arbitrary chosen \(u\in V(G)\). We characterize all \(H\)-stable graphs of minimal size where \(H\) is any complete \(k\)-partite graph. Thus, we generalize the results of Dudek and Żak regarding complete bipartite graphs.
Host and Network Monitoring Feature Extraction Feature AnalysisAnomaly Detection EnsembleResponse Actions Target System Modeling

Lateral movement-based attacks are increasingly leading to compromises in large private and government networks, often resulting in information exfiltration or service disruption. Such attacks are often slow and stealthy and usually evade existing security products. To enable effective detection of such attacks, we present a new approach based on graph-based modeling of the security state of the target system and correlation of diverse indicators of anomalous host behavior. We believe that irrespective of the specific attack vectors used, attackers typically establish a command and control channel to operate, and move in the target system to escalate their privileges and reach sensitive areas. Accordingly, we identify important features of command and control and lateral movement activities and extract them from internal and external communication traffic. Driven by the analysis of the features, we propose the use of multiple anomaly detection techniques to identify compromised hosts. These methods include Principal Component Analysis, kmeans clustering, and Median Absolute Deviation-based outlier detection. We evaluate the accuracy of identifying compromised hosts by using injected attack traffic in a real enterprise network dataset, for various attack communication models. Our results show that the proposed approach can detect infected hosts with high accuracy and a low false positive rate.