Miracle-dz/UniFAR-FTUs huggingface dataset:
The “ram effect”: new insights into neural modulation of the gonadotropic axis by male odors and socio-sexual interactions

Reproduction in mammals is controlled by the hypothalamo-pituitary-gonadal (HPG) axis under the influence of external and internal factors such as photoperiod, stress, nutrition, and social interactions. Sheep are seasonal breeders and stop mating when day length is increasing (anestrus). However, interactions with a sexually active ram during this period can override the steroid negative feedback responsible for the anoestrus state, stimulate luteinizing hormone (LH) secretion and eventually reinstate cyclicity. This is known as the “ram effect” and research into the mechanisms underlying it is shedding new light on HPG axis regulation. The first step in the ram effect is increased LH pulsatile secretion in anestrus ewes exposed to a sexually active male or only to its fleece, the latter finding indicating a “pheromone-like” effect. Estradiol secretion increases in all ewes and this eventually induces a LH surge and ovulation, just as during the breeding season. An exception is a minority of ewes that exhibit a precocious LH surge (within 4 h) with no prior increase in estradiol. The main olfactory system and the cortical nucleus of the amygdala are critical brain structures in mediating the ram effect since it is blocked by their inactivation. Sexual experience is also important since activation (increased c-fos expression) in these and other regions is greatly reduced in sexually naïve ewes. In adult ewes kisspeptin neurons in both arcuate and preoptic regions and some preoptic GnRH neurons are activated 2 h after exposure to a ram. Exposure to rams also activates noradrenergic neurons in the locus coeruleus and A1 nucleus and increased noradrenalin release occurs in the posterior preoptic area. Pharmacological modulation of this system modifies LH secretion in response to the male or his odor. Together these results show that the ram effect can be a fruitful model to promote both a better understanding of the neural and hormonal regulation of the HPG axis in general and also the specific mechanisms by which male cues can overcome negative steroid feedback and trigger LH release and ovulatory cycles.
ReviewDeposition Diseases and 3 D Domain Swapping

Protein aggregation is a feature of both normal cellular assemblies and pathological protein depositions. Although the limited order of aggregates has often impeded their structural characterization, 3D domain swapping has been implicated in the formation of several protein aggregates. Here, we review known structures displaying 3D domain swapping in the context of amyloid and related fibrils, prion proteins, and macroscopic aggregates, and we discuss the possible involvement of domain swapping in protein deposition diseases.
Dissociable components of phonological and lexical–semantic short-term memory and their relation to impaired word production in aphasia

This study assesses the dissociability of phonological and lexical–semantic short-term memory (STM) in two aphasic patients, B.N. and T.M. , and explores the relationship between their STM deficits and their word production impairment. Picture naming performance suggests phonological language production impairment in B.N. and lexical–semantic language production impairment in T.M. On STM tasks, B.N. presented phonological STM impairment with preserved lexical–semantic STM, while T.M. presented the reverse profile. These results reveal a double dissociation between phonological and lexical–semantic STM capacities and suggest that our patients' STM impairment may be selectively related to their language production deficits.
Multiple Aspect Summarization Using Integer Linear Programming

Multi-document summarization involves many aspects of content selection and surface realization. The summaries must be informative, succinct, grammatical, and obey stylistic writing conventions. We present a method where such individual aspects are learned separately from data (without any hand-engineering) but optimized jointly using an integer linear programme. The ILP framework allows us to combine the decisions of the expert learners and to select and rewrite source content through a mixture of objective setting, soft and hard constraints. Experimental results on the TAC-08 data set show that our model achieves state-of-the-art performance using ROUGE and significantly improves the informativeness of the summaries.
Accuracy of magnetic resonance imaging for measuring maturing cartilage: A phantom study

OBJECTIVES: To evaluate the accuracy of magnetic resonance imaging measurements of cartilage tissue-mimicking phantoms and to determine a combination of magnetic resonance imaging parameters to optimize accuracy while minimizing scan time. METHOD: Edge dimensions from 4 rectangular agar phantoms ranging from 10.5 to 14.5 mm in length and 1.25 to 5.5 mm in width were independently measured by two readers using a steel ruler. Coronal T1 spin echo (T1 SE), fast spoiled gradient-recalled echo (FSPGR) and multiplanar gradient-recalled echo (GRE MPGR) sequences were used to obtain phantom images on a 1.5-T scanner. RESULTS: Inter- and intra-reader reliability were high for both direct measurements and for magnetic resonance imaging measurements of phantoms. Statistically significant differences were noted between the mean direct measurements and the mean magnetic resonance imaging measurements for phantom 1 when using a GRE MPGR sequence (512x512 pixels, 1.5-mm slice thickness, 5:49 min scan time), while borderline differences were noted for T1 SE sequences with the following parameters: 320x320 pixels, 1.5-mm slice thickness, 6:11 min scan time; 320x320 pixels, 4-mm slice thickness, 6:11 min scan time; and 512x512 pixels, 1.5-mm slice thickness, 9:48 min scan time. Borderline differences were also noted when using a FSPGR sequence with 512x512 pixels, a 1.5-mm slice thickness and a 3:36 min scan time. CONCLUSIONS: FSPGR sequences, regardless of the magnetic resonance imaging parameter combination used, provided accurate measurements. The GRE MPGR sequence using 512x512 pixels, a 1.5-mm slice thickness and a 5:49 min scan time and, to a lesser degree, all tested T1 SE sequences produced suboptimal accuracy when measuring the widest phantom.
Short-text domain specific key terms/phrases extraction using an n-gram model with wikipedia

Finding domain specific key terms/phrases from a given set of documents is a challenging task. A domain may be defined as an area of interest over a collection of documents which may not be explicitly defined but implicitly observable in those documents. When considering a collection of documents related to academic research, examples of key terms/phrases may be Information Retrieval", "Marine Biology", etc. In this paper a technique for extracting important key terms/phrases in a considered topical domain is proposed using external evidence from the titles of Wikipedia articles and the Wikipedia category graph. We performed some experiments over the document collection of Web sites of different post-graduate schools. Our preliminary evaluations show promising results for the detection of domain specific key terms/phrases from the given set of domain focused Web pages.
A multiphase Cahn--Hilliard--Darcy model for tumour growth with necrosis

We derive a Cahn–Hilliard–Darcy model to describe multiphase tumour growth taking interactions with multiple chemical species into account as well as the simultaneous occurrence of proliferating, quiescent and necrotic regions. A multitude of phenomena such as nutrient diffusion and consumption, angiogenesis, hypoxia, blood vessel growth, and inhibition by toxic agents, which are released for example by the necrotic cells, are included. A new feature of the modelling approach is that a volume-averaged velocity is used, which dramatically simplifies the resulting equations. With the help of formally matched asymptotic analysis we develop new sharp interface models. Finite element numerical computations are performed and in particular the effects of necrosis on tumour growth are investigated numerically. In particular, for certain modelling choices, we obtain some form of focal and patchy necrotic growth that have been observed in experiments.
Regime Switching in Stock Market Returns

In this paper, we use an extension of Hamilton's (1989) Markov switching techniques to describe and analyze stock market returns. Using new tests, we find very strong evidence of switching behaviour. A major innovation of our work is to use a multivariate specification which allows us to examine whether the price-dividend ratio has marginal predictive power for stock market returns after accounting for state-dependent switching. We find strong evidence of predictability. The response of returns to the past price-dividend ratio is strongly asymmetric - about four times larger in the low-return state than in the high-return state. A second innovation in our work is to allow the probability of transitions from one regime to another to depend on economic variables.
York University at TREC 2013: Contextual Suggestion Track

This paper presents our participation in the Contextual Suggestion Track of TREC 2013. The goal of this track is to investigate search techniques for complex information needs that are highly dependent on context and user interests. To achieve this goal, we propose a semantic user profile modeling for personalized place recommendation. For the semantic user profile model construction, we construct a place ontology based on the Open Directory Project (ODP), a hierarchical ontology scheme for organizing websites. Previously rated attractions by the user are mapped to the place ontology where we represent positive and negative preferences under each place type. For a new user context represented by geographic coordinates, we rerank the top 50 suggestions returned by Google places API using the user profile.
Automatic Named Entity Set Expansion Using Semantic Rules and Wrappers for Unary Relations

Named Entity Set Expansion is the task from a set given a small number of named entities in same type finds a more complete Named Entity set. Two famous Named Entity expansion systems using the web are Google Sets and Boo! Wa! In this paper, we proposed an approach using Vietnamese semantic rule combined with wrappers for unary relations to expand a given set of Vietnamese Named Entities. Our model using the results which are provided by Google search engine in Vietnam, consists of six main phases. We did the experiments for many times to choose the rank method that gave the best results is Page Rank, and mixing coefficient is 0.6. Experimental results showed that the feasible approach with average precision is 96.4% with 5 first entities and 92.6% with 10 first entities.
Defeasible Rules in Content Selection and Text Structuring

This paper outlines a number of ways in which defeasible rules can contribute to the content selection and discourse structuring components of a text generation system. We suggest that, for certain types of descriptive text, the characterisation of discourse struc-turing mechanisms as operations on or involving defeasible rules provides an attractive framework for addressing important issues in content selection/structuring. We describe an architecture which incorporates defeasible rules into a systemic model of generation, and illustrate its use in the description of objects in a museum gallery. While defeasible rules are traditionally used in theorem-proving applications, to make predictions about the consequences of known facts, we are here concerned with three separate issues: (i) how such rules may need to be expressed by the NLG system in order to achieve its goals; (ii) how their interaction with facts about particular objects enables the use of valuable coherence relations; and (iii) how they are relevant in taking account of the system's user model.
Three-fluid plasmas in star formation II. Momentum transfer rate coefficients

Context. The charged component of the insterstellar medium consists of atomic and molecular ions, electrons, and charged dust grains, coupled to the local Galactic magnetic field. Collisions between neutral particles (mostly atomic or molecular hydrogen) and charged species, and between the charged species themselves, affect the magnetohydrodynamical behaviour of the medium and the dissipation of electric currents. Aims. The friction force due to elastic collisions between particles of different species in the multi-component interstellar plasma is a nonlinear function of the temperature of each species and the Mach number of the relative drift velocity. The aim of this paper is to provide an accurate and, as far as possible, complete set of momentum transfer rate coefficients for magnetohydrodynamical studies of the interstellar medium. Methods. Momentum transfer rates are derived from available experimental data and theoretical calculations of cross sections within the classic approach developed by Boltzmann and Langevin for a wide range of values of the temperature and the drift velocity. Results. Accurate numerical values for momentum transfer rates are obtained and fitted to simple analytical formulae expressing the dependence of the results on the gas temperature and the relative drift velocity. The often used polarization approximation is in satisfactory agreement with our results only for collisions between H2 and molecular ions (HCO + ,H + ). For other kinds of collisions, the polarization approximation fails by large factors, and must be replaced by more accurate expressions.
Fast and highly anisotropic thermal transport through vertically aligned carbon nanotube arrays

This letter reports on fast and highly anisotropic thermal transport through millimeter-tall, vertically aligned carbon nanotube arrays (VANTAs) synthesized by chemical vapor deposition on Si substrates. Thermal diffusivity measurements were performed for both longitudinal and transverse to the nanotube alignment direction, with longitudinal values as large as 2.1±0.2cm2∕s and anisotropy ratios as large as 72. Longitudinal thermal conductivities of 15.3±1.8W∕(mK) for porous 8±1vol% VANTAs in air and 5.5±0.7W∕(mK) for epoxy-infiltrated VANTAs already exceed those of phase-changing thermal interface materials used in microelectronics. Data suggest that further improvements are possible through optimization of density and defects in the arrays.
Effects of Magnitude and Phase Distortion in 8-PSK Systems on Error Vector Magnitude Measurements

This work investigates the effects of magnitude and/or phase distortions, in 8-Phase Shift Keying (8-PSK) systems, due to Gaussian bandpass noise. Analytical expressions are derived to compute the performance of the distorted 8-PSK signals in terms of error vector magnitude (EVM), symbol error rate (SER) and Es/No. The results show that the same value of EVM may result in different SER values depending on the type of distortion. Simulations are carried out to confirm the results of the derived expressions.
Probabilistic non-negative matrix factorisation and extensions

Matrix factorisation models have had an explosive growth in popularity in the last decade. It has become popular due to its usefulness in clustering and missing values prediction. We review the main literature for matrix factorisation, focusing on nonnegative matrix factorisation and probabilistic approaches. We also consider several extensions: matrix tri-factorisation, Tensor factorisation, Tucker decomposition, and data fusion.
Multi-Bernoulli filter based sensor selection with limited sensing range for multi-target tracking

In this paper, we consider a sensor network with limited sensing range and present a sensor selection algorithm for multi-target tracking problem. The proposed algorithm is based on the multi-Bernoulli filtering and a collection of sub-selection problems for individual target. A sub-selection problem for each target is investigated under the framework of partially observed Markov decision process. Each sub-selection problem is solved using a combination of information theoretic method and limited sensing range. Numerical studies validate the effectiveness of our method for multi-target tracking scenario in a sensor network.
Ece437 Project Report Wavelet{domain Statistical Modeling Using Hmms

Wavelet{based techniques has long been known in signal/image processing literature, and applied into various applications such as denoising and compression. As a separate framework, hidden Markov model (HMM) has been widely used to provide formal statistical models. This projects follows the paper by M. Crouse et al 1], trying to make the connection between these two separate concepts. The wavelet representation of a signal often has the properties of clustering and persistence across scales. By investigating these properties we develop a wavelet{domain HMM to model the wavelet coeecients. An eecient Expectation Maximization (EM) algorithm is developed for tting the HMMs to observational wavelet coeecients. After the model is obtained, we can use this model into the framework of signal estimation, and many other applications as well.
MicroRNA-497 impairs the growth of chemoresistant neuroblastoma cells by targeting cell cycle, survival and vascular permeability genes

Despite multimodal therapies, a high percentage of high-risk neuroblastoma (NB) become refractory to current treatments, most of which interfere with cell cycle and DNA synthesis or function, activating the DNA damage response (DDR). In cancer, this process is frequently altered by deregulated expression or function of several genes which contribute to multidrug resistance (MDR). MicroRNAs are outstanding candidates for therapy since a single microRNA can modulate the expression of multiple genes of the same or different pathways, thus hindering the development of resistance mechanisms by the tumor. We found several genes implicated in the MDR to be overexpressed in high-risk NB which could be targeted by microRNAs simultaneously. Our functional screening identified several of those microRNAs that reduced proliferation of chemoresistant NB cell lines, the best of which was miR-497. Low expression of miR-497 correlated with poor patient outcome. The overexpression of miR-497 reduced the proliferation of multiple chemoresistant NB cell lines and induced apoptosis in MYCN-amplified cell lines. Moreover, the conditional expression of miR-497 in NB xenografts reduced tumor growth and inhibited vascular permeabilization. MiR-497 targets multiple genes related to the DDR, cell cycle, survival and angiogenesis, which renders this molecule a promising candidate for NB therapy.
The catecholamine system in health and disease —Relation to tyrosine 3-monooxygenase and other catecholamine-synthesizing enzymes—

Catecholamines [dopamine, noradrenaline (norepinephrine), and adrenaline (epinephrine); CAs] are neurotransmitters in the central and peripheral nervous systems as well as hormones in the endocrine system. CAs in the brain play a central role in versatile functions as slow-acting neurotransmitters functioning in synaptic neurotransmission, modulating the effects of fast-acting neurotransmitters such as glutamate and γ-aminobutyric acid (GABA). In this review, I focus on recent advances in the biochemistry and molecular biology of the CA system in humans in health and disease, especially in neuropsychiatric diseases such as Parkinson’s disease (PD), in relation to the biosynthesis of CAs regulated by a pteridine-dependent monooxygenase, tyrosine 3-monooxygenase (tyrosine hydroxylase, TH) and its pteridine cofactor, tetrahydrobiopterin (BH4).
Optimal Loop-Shaping in the Cepstral Domain for Active Noise Canceling Headsets

Simple active noise-canceling systems (such as noise canceling headphones) use a feedback mechanism whereby the signal recorded by microphone placed near the loudspeaker is phase-inverted and sent back through the loudspeaker via a feedback filter. Such systems can be implemented using analog circuitry, are fairly inexpensive, and achieve reasonably good performance at low frequencies (below 500 Hz). The feedback filter is designed to achieve a high gain at low-frequencies (for best noise reduction) while maintaining closed-loop stability under various conditions. To design the feedback filter, fairly ad-hoc techniques were traditionally used under the broad denomination of "loop-shaping" until the advent in the 80's of optimal Hinfin algorithms. The design technique outlined in this paper shares the intuitive approach of traditional loop-shaping methods, but removes most of the guess-work while producing optimal filters that guarantee closed-loop stability. The main idea is to represent the filter in the cepstral domain, where gain and phase constraints take a convenient linear form, and use linear programming to design the optimal feedback filter
The Structural Dynamics of U.S. Output and Inflation: What Explains the Changes?

We examine the dynamics of US output and inflation using a structural time varying coefficient VAR. We show that there are changes in the volatility of both variables and in the persistence of inflation. Technology shocks explain changes in output volatility, while a combination of technology, demand and monetary shocks explain variations in the persistence and volatility of inflation. We detect changes over time in the transmission of technology shocks and in the variance of technology and of monetary policy shocks. Hours and labor productivity always increase in response to technology shocks.
Does a Drama-Inspired ‘Mirroring’ Exercise Enhance Mathematical Learning?

Learning from complex instructional materials typically requires sustained attention, but many learners — both children and adults — may find their minds ‘wandering’ when learning. Drama educators have argued that ‘mirroring’ exercises, where students in pairs or groups mirror each other's movements, improve attention; but, to date, evidence for this claim is anecdotal. This exploratory study investigated the effects of a prelearning mirroring intervention on mathematical performance from the perspective of cognitive load theory. Twenty-six university students engaged in a mindful and embodied mirroring activity before learning a rapid mental mathematics strategy. Effects on learning were evaluated using two mathematical problem-solving tests completed after learning the maths strategy. Compared to the non-mirroring condition, students in the mirroring condition solved subsequent test problems more quickly than those in the control condition. Initial evidence thus suggests a mirroring intervention may enhance the quality of learning during mathematics.