Miracle-dz/UniFAR-FTUs huggingface dataset:
Inhibition of 3-Hydroxy-3-Methylglutaryl Coenzyme a (hmg co-A) Reductase in Liver Microsomes by Moringa Oleifera L. Polyphenols

Phytochemicals are the bioactive components present at micro level in our daily diet, especially the phenolic antioxidants, contribute to the prevention of cardiovascular and other degenerative diseases. Moringa oleifera (MO) leaves polyphenols effect on the activity of 3-hydroxy-3-methylglutaryl Coenzyme A (HMG CoA) reductase was studied using a spectrophotometric assay based on the stoichiometric formation of coenzyme A (SH) during the reduction of microsomal HMG CoA to mevalonate at different concentrations (200- 400 µg). Activity of HMG- CoA reductase was inhibited by MO polyphenols significantly (p<0.05) at the concentrations studied. The Coenzyme A released at the end of assay in the control was higher (18.87±0.12 n Moles) significantly than the MO polyphenol extract, which was dose dependent (14.69±0.07 to 10.26±0.33 n Moles). The results reveal the potency of the MO polyphenols in inhibiting the HMG- CoA reductase. Hence, the MO polyphenols can be explored for its role as a cholesterol lowering agent.
The Demand for Reinsurance: Theory and Empirical Tests

This paper investigates the valuation effects of reinsurance purchases in a contingent claims framework. The comparative statics of the model suggest that, other things equal, the demand for reinsurance will be greater, 1) the higher the firm's leverage, 2) the lower the correlation between the firm's investment returns and claims costs, 3) for firms which write "longer tail" lines of insurance, and 4) the more the firm concentrates its investments in tax- favored assets. These predictions are tested in an empirical analysis of the reinsurance behavior of U.S. property-liability insurance firms during the period 1980-1987. ‡ Acknowledgments. Earlier versions of this paper benefited substantially from helpful comments offered
Segmentation of accelerometer signals recorded during continuous treadmill walking

This paper describes a method for segmentation of triaxial accelerometer signals recorded during continuous treadmill walking. More specifically, we aim at detecting changes in speed and in incline by analyzing the accelerometer signals recorded on the shin or the waist of the walker. The raw accelerometer signals are transformed either in the time-frequency domain (with a Short-Time Fourier Transform) or in a specific features space (which emphasizes the characteristics of the gait). The transformed signals serve as inputs for change-point detection methods which output a number of estimated change times. Several change-point detection methods are tested, either parametric or non-parametric. In particular, a new change-point detection method is introduced, which takes into account the frequency structure of walking signals. The different signal representations and change-points detection methods are evaluated on a corpus of 24 subjects. An analysis of the obtained results is presented for the two considered sensors (waist and shin).
The establishment of polarity by hippocampal neurons in culture

By the end of the first week in culture, hippocampal neurons have established a single axon and several dendrites. These 2 classes of processes differ in their morphology, in their molecular composition, and in their synaptic polarity (Bartlett and Banker, 1984a, b; Caceres et al., 1984). We examined the events during the first week in culture that lead to the establishment of this characteristic form. Hippocampal cells were obtained from 18 d fetal rats, plated onto polylysine- treated coverslips, and maintained in a serum-free medium. The development of individual cells was followed by sequential photography at daily intervals until both axons and dendrites had been established; identification of the processes was confirmed by immunostaining for MAP2, a dendritic marker. Time-lapse video recording was used to follow the early stages of process formation. Hippocampal neurons acquired their characteristic form by a stereotyped sequence of developmental events. The cells first established several, apparently identical, short processes. After several hours, one of the short processes began to grow very rapidly; it became the axon. The remaining processes began to elongate a few days later and grew at a much slower rate. They became the cell's dendrites. Neurons that arose following mitosis in culture underwent this same sequence of developmental events. In a few instances, 2 processes from a cell exhibited the rapid growth typical of axons, but only one maintained this growth; the other retracted and became a dendrite. Axons branched primarily by the formation of collaterals, not by bifurcation of growth cones. As judged by light microscopy, processes are not specified as axons or dendrites when they arise. The first manifestation of neuronal polarity is the acquisition of axonal characteristics by one of the initial processes; subsequently the remaining processes become dendrites.
Reinforcement Learning by Construction of Hypothetical Targets

A general approach to delayed reinforcement learning by the use of supervised training algorithms is proposed. The approach is monolithic, direct and involves minor modifications to any supervised learning algorithm. Each connection has two weight change registers, one for eventual success and one for eventual failure, and the network is trained on self-generated hypothetical target vectors. The method is a close, but more general, relative to selective bootstrap adaption and is tested on an abstract model of the Link Allocation problem in Asynchronous Transfer Mode (ATM) telecommunication networks.
Walk to Language: Creating Language Development Opportunities for ELL and Non-ELL Kindergarten Students

A staggering number of students begin school with lagging English language skills, which may impact a child’s future achievement in reading and writing. This challenge is disproportionately high for students living in poverty and/or students that are learning English as a second language. The purpose of this research is to measure the impact of an instructional model utilized for kindergarten students, Walk to Language, on English language development and on English language arts skills. This model is unique in that it simultaneously addresses the language development needs of English language learners (ELL) and non-ELL, many of which are students of color. An ex post facto quantitative research design was utilized to evaluate data from a Pacific Northwest school district pilot of the model. The study included 67 kindergarten students from a school participating in the pilot as a treatment group and 96 students from a control group within the district. Results indicated significantly higher scores for native English speaking students in language skills from the treatment group (p = .04). This finding supports the hypothesis that non-ELL students would benefit from language instruction. The control group made significantly higher growth on sentence dictation (p = .001) and on the English Language Proficiency Assessment 21 (ELPA 21) reading sub-scores (p = .04) than treatment students. These
Test of Choice Set Misspecification for Discrete Models of Consumer Choice

We develop and evaluate a test of choice set misspecification for a multinomial logit choice model. This test determines whether the choice set designated by the researcher mistakenly assigns relevant substitutes to the numeraire good. We develop this test by generalizing the traditional McFadden-type conditional logit model to evaluate whether the traditional model is conditioned on an overly restrictive set of substitution possibilities. The test has a convenient feature: while it requires information on potentially relevant, but omitted, substitute goods, it does not require the researcher to observe consumers choices among these omitted potential substitutes if they select the numeraire good (which contains these omitted substitutes). A comparison of the traditional multinomial logit choice model and our more general model suggests that choice set misspecification may produce biased parameters that distort welfare estimates to a consequential extent.
Efficient exact edit similarity query processing with the asymmetric signature scheme

Given a query string Q, an edit similarity search finds all strings in a database whose edit distance with Q is no more than a given threshold t. Most existing method answering edit similarity queries rely on a signature scheme to generate candidates given the query string. We observe that the number of signatures generated by existing methods is far greater than the lower bound, and this results in high query time and index space complexities. In this paper, we show that the minimum signature size lower bound is t +1. We then propose asymmetric signature schemes that achieve this lower bound. We develop efficient query processing algorithms based on the new scheme. Several dynamic programming-based candidate pruning methods are also developed to further speed up the performance. We have conducted a comprehensive experimental study involving nine state-of-the-art algorithms. The experiment results clearly demonstrate the efficiency of our methods.
Web Spambot Detection Based on Web Navigation Behaviour

Web robots have been widely used for various beneficial and malicious activities. Web spambots are a type of web robot that spreads spam content throughout the web by typically targeting Web 2.0 applications. They are intelligently designed to replicate human behaviour in order to bypass system checks. Spam content not only wastes valuable resources but can also mislead users to unsolicited websites and award undeserved search engine rankings to spammers’ campaign websites. While most of the research in anti-spam filtering focuses on the identification of spam content on the web, only a few have investigated the origin of spam content, hence identification and detection of web spambots still remains an open area of research. In this paper, we describe an automated supervised machine learning solution which utilises web navigation behaviour to detect web spambots. We propose a new feature set (referred to as an action set) as a representation of user behaviour to differentiate web spambots from human users. Our experimental results show that our solution achieves a 96.24% accuracy in classifying web spambots.
New Aggregate and Source-Specific Pork Import Demand Elasticity for Japan: Implications to U.S. Exports

The authors estimate aggregate and source-specific import demand elasticities for pork in Japan using a two-stage model that has two important advantages over other models: it allows substitution between domestic and imported products, and it avoids econometric problems in generating source-specific parameters. Pork imports into Japan are constrained by high protection and the strong preference Japanese consumers have for domestic pork. U.S. pork is inexpensive in Japan, but because food safety and quality drive pork demand in Japan, U.S. pork's comparatively low price may not be providing a market advantage. However, U.S. pork exports to Japan have performed well over the past three years, suggesting that the U.S. may have benefited from disease challenges in Taiwan and the E.U. or that the U.S. is learning to meet Japanese consumer demands more effectively.
The attentional blink and task switching within and across modalities

The attentional blink (AB) is a robust deficit obtained for a second visual target (T2) appearing within 200 600 ms of a correctly identified first target (T1). In most AB studies both targets appear among distractors in a rapid serial visual presentation (RSVP), and a key variable is the lag or SOA between the two targets. In the present chapter we review research bearing on the basis for the AB deficit and related deficits, including cross-modal versions of the AB procedure and tasks that require a task switch (a switch in target criterion) between T1 and T2. We conclude that the standard AB deficit is restricted to visual targets and can be distinguished from an additional deficit that results from a task switch between T1 and T2. The latter effect is found with cross-modal and auditory stimuli as well as visual stimuli, and is additive with the AB effect (when both targets are visual). We propose that the standard AB effect occurs at a different stage of processing than the more central taskswitching deficit and shows features that distinguish it from the latter. The visual AB effect represents a limit in the speed with which visual targets — which are vulnerable to masking — can be consolidated into working memory or awareness: A second target may be lost while queuing for access to the consolidation process. We review studies that show a clear dissociation between AB and task-switching deficits, consistent with complementary findings of Allport and Hsieh (this volume) on criterion shifting in RSVP target search. The evidence suggests that there are multiple bottlenecks in processing which individually or together limit performance when two target stimuli must be processed close in time.
Approach to Selecting Best Development Set for Phrase-Based Statistical Machine Translation

In phrase-based statistical machine translation system, the parameters of model are usually obtained from minimum error rate training (MERT) on the development set. So the development set has a great influence on the performance of the translation system. Generally, more development set will achieve more effective and robust parameters but consume much more time on MERT process. In this paper, we propose two methods to select sentences from the large development set, based on the phrase and the sentence structure respectively. The experimental results show that our methods can get better translation performance than the baseline system on the compact development set by using a state-of-the-art SMT system.
Document clustering based on time series

This paper presents a novel document clustering algorithm that represents documents as a time series of words. Document clustering is very important due to the fact that it permits us to group them based on some certain criteria, especially nowadays when a large number of articles are available. The timed series representation of the document instead of the vector model permits us to consider a new algorithm for the computation of the distance between documents: dynamic time warping. This novel representation together with the dynamic time warping algorithm represents the foundation for computing the similarity and the clustering of the documents. The clustering algorithm used is hierarchical clustering. This novel clustering method of texts is applied on named entities and on the parts of speech of the words that compose the documents. As test data we are using the Reuters corpus of newspaper articles.
Uniform Generalization, Concentration, and Adaptive Learning

One fundamental goal in any learning algorithm is to mitigate its risk for overfitting. Mathematically, this requires that the learning algorithm enjoys a small generalization risk, which is defined either in expectation or in probability. Both types of generalization are commonly used in the literature. For instance, generalization in expectation has been used to analyze algorithms, such as ridge regression and SGD, whereas generalization in probability is used in the VC theory, among others. Recently, a third notion of generalization has been studied, called uniform generalization, which requires that the generalization risk vanishes uniformly in expectation across all bounded parametric losses. It has been shown that uniform generalization is, in fact, equivalent to an information-theoretic stability constraint, and that it recovers classical results in learning theory. It is achievable under various settings, such as sample compression schemes, finite hypothesis spaces, finite domains, and differential privacy. However, the relationship between uniform generalization and concentration remained unknown. In this paper, we answer this question by proving that, while a generalization in expectation does not imply a generalization in probability, a uniform generalization in expectation does imply concentration. We establish a chain rule for the uniform generalization risk of the composition of hypotheses and use it to derive a large deviation bound. Finally, we prove that the bound is tight.
Resource allocation and scheduling in MIMO-OFDMA with time-varying channel and bursty arrivals

A cross-layer resource allocation and scheduling scheme in the downlink of MIMO-OFDMA systems is proposed to provide quality of service (QoS) guarantees to real-time traffics and non-real-time traffics in case of heavy-traffic. The proposed algorithm aims to maximize the efficient system throughput with the constraints of packet error rate, delay, packets dropping rate and buffer size. At the medium access control (MAC) layer, the proposed algorithm dynamically assigns subcarriers to the highest priority user based on the channel state information (CSI) and the queue state information (QSI). After initial subcarrier assignment, the subcarrier re-assignment is applied to approve the system performance. At the physical (PHY) layer, a low complexity rate-and-power adaptation scheme is used to the predetermined subcarriers. It is demonstrated in the numerical results that the proposed algorithm significantly improves the system performance in terms of system throughput and packet loss rate.
La temporalité, un facteur déterminant des conduites addictives

Context: some studies suggest that temporality is an important determinant in psychoactive substance use. The objective of our study is to determine the psychometric properties of two temporality measures and to compare them. Both measures were then linked to potentially addictive behaviours: use of alcohol, tobacco, cannabis and internet. We also wanted to examine the developmental differences by comparing secondary school and university students. Methods: after obtaining informed consent, French secondary school (n = 256) and university students (n = 263) completed a series of self- evaluations. Results: temporality measures were partially validated. Both measures correlated significantly with certain addiction-risk behaviours. Discussion: in clinical practice, these results support an association between the relationship with time and addiction-risk behaviours. This may contribute to the development of intervention modalities in users during prevention campaigns or care programmes.
User-guided pedestrian and object removal

Street-level image collections now exist for a number of locations around the world. While the focus is on capturing streets and buildings, pedestrians are commonly captured. Pedestrian faces are identified and blurred in different system to address privacy concerns but leave their possibly identifiable bodies intact. In this paper, we present a user-guided approach to fully remove pedestrians and undesirable scene objects. Both are fully removed given a user created removal mask with our system's gui and using successive image frames with an image inpainting-inspired approach.
N400 congruency effects from emblematic gesture probes following sentence primes

Emblematic gesture pictures were presented to subjects as probes in relation to semantically congruent and incongruent sentences to investigate if there is a similar cognitive processing network for congruity as there is with words. Subjects had to perform a simple discrimination task while undergoing EEG recordings. The ERPs elicited by semantically incongruent gestures produced larger N400 and possibly N300 components. While the N400 is indicative of semantic processing showing that emblematic gestures are lexicalized, the N300 likely reflects the cognitive processing of picture stimuli.
Understanding the Promise: A Typology of State and Local College Promise Programs

Over the past decade, but especially in the past few years, programs with a promise label have been advanced at the local, state, and federal levels. To advance understanding of the design, implementation, and impact of the many different versions of emerging programs, policymakers, practitioners, and researchers need an organizing framework. To address this knowledge need, this study uses descriptive and cluster analyses of 289 programs that meet the following criteria: have a primary goal of increasing higher education attainment, promise a financial award to eligible students, have some “place” requirement, and focus on the traditional college-age population. Results suggest that state- versus non-state sponsorship, financial award structure (e.g., first/last dollar), type of postsecondary educational institutions at which the award may be used, and eligibility criteria (universal vs. merit or need) are important differentiators among programs. The results provide a foundation for future research on college promise programs.
Neural correlates of dual‐task practice benefit on motor learning: a repetitive transcranial magnetic stimulation study

Dual‐task practice has been previously shown to enhance motor learning when both primary and secondary tasks engage similar cognitive processes. In the present study, participants practiced a finger sequence task with the non‐dominant hand under a single‐task condition (i.e. without a probe task) or a dual‐task condition in which a probe choice reaction time (CRT) task was presented during the preparation phase (before movement onset) of the finger task. It was hypothesised that by engaging similar ‘planning’ processes, the dual‐task condition may facilitate the activation of shared ‘planning’ circuitry that includes dorsal premotor cortex (dPM), an important neural substrate for CRT task performance and movement preparation. Repetitive transcranial magnetic stimulation (rTMS; 1 Hz) was applied to the contralateral dPM immediately following practice. Motor learning was assessed by a retention test conducted ~ 24 h after practice. Consistent with our previous results, the dual‐task condition enhanced learning compared with the single‐task condition. rTMS applied to dPM attenuated the dual‐task practice benefit on motor learning. In contrast, rTMS to M1 did not attenuate the dual‐task practice benefit, suggesting the rTMS effect was specific to dPM. Our findings suggest a unique role of dPM in mediating the dual‐task practice effect on motor learning.
The study on the Effect of virtual current distribution in an electromagnetic flow meter with bubble

Electromagnetic flow meters are widely used in multiphase flow measurements in recent years. In this paper, a simulation model is established to study the Effects of virtual current distribution in an Electromagnetic Flow Meter which exist a spherical non-conductive body in the Fluid by using ANSYS. Furthermore, the characteristics of virtual current distribution and the flow meter errors by changes the size of bubble are discussed. For application, the results provide a possible way to estimate errors of the flow meter caused by multiphase flow.