Miracle-dz/UniFAR-FTUs huggingface dataset:
Ruthenium(III) Complexes of Heterocyclic Tridentate (ONN) Schiff Base: Synthesis, Characterization and its Biological Properties as an Antiradical and Antiproliferative Agent

The current work reports the synthesis, spectroscopic studies, antiradical and antiproliferative properties of four ruthenium(III) complexes of heterocyclic tridentate Schiff base bearing a simple 2′,4′-dihydroxyacetophenone functionality and ethylenediamine as the bridging ligand with RCHO moiety. The reaction of the tridentate ligands with RuCl3·3H2O lead to the formation of neutral complexes of the type [Ru(L)Cl2(H2O)] (where L = tridentate NNO ligands). The compounds were characterized by elemental analysis, UV-vis, conductivity measurements, FTIR spectroscopy and confirmed the proposed octahedral geometry around the Ru ion. The Ru(III) compounds showed antiradical potentials against 2,2-Diphenyl-1-Picrylhydrazyl (DPPH) and 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) radicals, with DPPH scavenging capability in the order: [(PAEBOD)RuCl2] > [(BZEBOD)RuCl2] > [(MOABOD)RuCl2] > [Vit. C] > [rutin] > [(METBOD)RuCl2], and ABTS radical in the order: [(PAEBOD)RuCl2] < [(MOABOD)RuCl2] < [(BZEBOD)RuCl2] < [(METBOD)RuCl2]. Furthermore, in vitro anti-proliferative activity was investigated against three human cancer cell lines: renal cancer cell (TK-10), melanoma cancer cell (UACC-62) and breast cancer cell (MCF-7) by SRB assay.
Expression of calcium–binding proteins in the diencephalon of the lizard Psammodromus algirus

This work is a study of the distribution pattern of calbindin–D28k, calretinin, and parvalbumin in the diencephalic alar plate of a reptile, the lizard Psammodromus algirus, by using the prosomeric model (Puelles [1995] Brain Behav Evol 46:319–337), which divides the alar plate of the diencephalon into the caudorostrally arranged pretectum (p1), dorsal thalamus plus epithalamus (p2), and ventral thalamus (p3). Calbindin and calretinin are more extensively expressed in the dorsal thalamus than in the neighboring alar regions, and therefore these calcium–binding proteins are particularly suitable markers for delimiting the dorsal thalamus/epithalamus complex from the ventral thalamus and the pretectum . Conversely, parvalbumin is more intensely expressed in the pretectum and ventral thalamus than in the dorsal thalamus/epithalamus complex. Within the dorsal thalamus , calcium–binding protein immunoreactivity reveals a three–tiered division. The pretectum displays the most intense expression of parvalbumin within the diencephalon. Virtually all nuclei in the three sectors of the pretectum (commissural, juxtacommissural, and precommissural) present strong to moderate expression of parvalbumin. We compare the distribution of calcium–binding proteins in the diencephalon of Psammodromus with other vertebrates, with mammals in particular, and suggest that the middle and ventral tiers of the reptilian dorsal thalamus may be comparable to nonspecific or plurimodal posterior/intralaminar thalamic nuclei in mammals, on the basis of the calcium–binding protein expression patterns, as well as the hodological and embryological data in the literature. J. Comp. Neurol. 427:67–92, 2000. © 2000 Wiley‐Liss, Inc.
Supervised Detection and Unsupervised Discovery of Pronunciation Error Patterns for Computer-Assisted Language Learning

Pronunciation error patterns (EPs) are patterns of mispronunciation frequently produced by language learners, and are usually different for different pairs of target and native languages. Accurate information of EPs can offer helpful feedbacks to the learners to improve their language skills. However, the major difficulty of EP detection comes from the fact that EPs are intrinsically similar to their corresponding canonical pronunciation, and different EPs corresponding to same canonical pronunciation are also intrinsically similar to each other. As a result, distinguishing EPs from their corresponding canonical pronunciation and between different EPs of the same phoneme is a difficult task-perhaps even more difficult than distinguishing between different phonemes in one language. On the other hand, the cost of deriving all EPs for each pair of target and native languages is high, usually requiring extensive expert knowledge or high-quality annotated data. Unsupervised EP discovery from a corpus of learner recordings would thus be an attractive addition to the field. In this paper, we propose new frameworks for both supervised EP detection and unsupervised EP discovery. For supervised EP detection, we use hierarchical multi-layer perceptrons (MLPs) as the EP classifiers to be integrated with the baseline using HMM/GMM in a two-pass Viterbi decoding architecture. Experimental results show that the new framework enhances the power of EP diagnosis. For unsupervised EP discovery we propose the first known framework, using the hierarchical agglomerative clustering (HAC) algorithm to explore sub-segmental variation within phoneme segments and produce fixed-length segment-level feature vectors in order to distinguish different EPs. We tested K-means (assuming a known number of EPs) and the Gaussian mixture model with the minimum description length principle (estimating an unknown number of EPs) for EP discovery. Preliminary experiments offered very encouraging results, although there is still a long way to go to approach the performance of human experts. We also propose to use the universal phoneme posteriorgram (UPP), derived from an MLP trained on corpora of mixed languages, as frame-level features in both supervised detection and unsupervised discovery of EPs. Experimental results show that using UPP not only achieves the best performance, but also is useful in analyzing the mispronunciation produced by language learners.
HOW COMPLEX ARE NEURONAL INTERACTIONS ?

A fundamental goal of systems neuroscience is to understand how the collective dynamics of neurons encode sensory information and guide behavior. To answer this important question one needs to uncover the network of underlying neuronal interactions. Whereas advances in technology during the last several decades made it possible to record neural activity simultaneously from a large number of network elements, these techniques do not provide information about the physical connectivity between the elements being recorded. Thus, neuroscientists are challenged to solve the inverse problem: inferring interactions between network elements from the recorded signals that arise from the network connectivity structure. Here, we review studies that address the problem of reconstructing network interactions from high-dimensional datasets generated by modern techniques, and focus on the emerging theoretical models capable of capturing the dominant network interactions of any order. These models are beginning to shed light on the structure and complexity of neuronal interactions. 87 How Complex Are NeurAl INterACtIoNs?
Realistic Dynamic Facial Textures from a Single Image Using GANs

We present a novel method to realistically puppeteer and animate a face from a single RGB image using a source video sequence. We begin by fitting a multilinear PCA model to obtain the 3D geometry and a single texture of the target face. In order for the animation to be realistic, however, we need dynamic per-frame textures that capture subtle wrinkles and deformations corresponding to the animated facial expressions. This problem is highly undercon-strained, as dynamic textures cannot be obtained directly from a single image. Furthermore, if the target face has a closed mouth, it is not possible to obtain actual images of the mouth interior. To address this issue, we train a Deep Generative Network that can infer realistic per-frame texture deformations, including the mouth interior, of the target identity using the per-frame source textures and the single target texture. By retargeting the PCA expression geometry from the source, as well as using the newly inferred texture, we can both animate the face and perform video face replacement on the source video using the target appearance.
Study of CCN3 (NOV) and DDR1 in normal melanocytes and vitiligo skin

Abstract: We have hypothesised that melanocytes disappear in vitiligo because they are weakly attached to the epidermal basal membrane (melanocytorrhagy). In the epidermis, attachment of melanocytes to collagen IV is mediated through DDR1, which is under the control of CCN3. DDR1 genetic variants have been associated with vitiligo in patients of different ethnic origin. In vitro studies have shown that inhibition of CCN3 induces the detachment of melanocytes. We have studied in parallel the expression of CCN3 and DDR1 in lesional and perilesional skin of patients with vitiligo and the impact of the silencing of CCN3 and DDR1 in normal human melanocytes on their behaviour in epidermal reconstructs. Our in vivo study provides evidence of a dysregulation of the DDR1–CCN3 interaction in vitiligo skin as melanocytes remaining in perilesional skin did not express CCN3. Expression of DDR1 was decreased in lesional versus perilesional vitiligo skin in the majority of patients, and the expression of collagen IV was found decreased in all patients. Silencing of CCN3 in melanocytes induced a significant inhibition of cell adhesion to collagen IV whereas melanocytes transduced with shDDR1 still adhered well on collagen IV and did not increase melanocyte loss in epidermal reconstructs as compared with normal melanocytes. Melanocyte detachment was observed but not in all reconstructs using CCN3 silenced melanocytes. Overall, our study confirms that a downregulation of CCN3 is implicated in melanocyte adhesion in part through DDR1. In vitiligo skin, the interaction of CCN3 with other molecules, such as TGFβ and CCN2, needs to be addressed.
On the analytical evaluation of closed-loop power-control error statistics in DS-CDMA cellular systems

This paper proposes an analytical study that aims at evaluating the power-control error statistics in wireless direct-sequence code-division multiple-access (DS-CDMA) cellular systems based on an ideal variable step closed-loop power-control scheme. In particular, the cumulative distribution function and the correlation coefficient of the power-control error are derived through a first-order Taylor expansion of the received signal envelope. A novel power-control scheme that exploits the autocorrelation properties of the fading is also proposed, and its performance is analyzed in terms of power-control error statistics. Rayleigh and Rice frequency-selective channel models, which involve the use of a diversity RAKE receiver at the base station, have been taken into account. The proposed analytical approach specifically applies to CDMA systems. A method that aims at estimating the capacity of a DS-CDMA cellular network is also given.
Privacy Preserving ID3 over Horizontally, Vertically and Grid Partitioned Data

We consider privacy preserving decision tree induction via ID3 in the case where the training data is horizontally or vertically distributed. Furthermore, we consider the same problem in the case where the data is both horizontally and vertically distributed, a situation we refer to as grid partitioned data. We give an algorithm for privacy preserving ID3 over horizontally partitioned data involving more than two parties. For grid partitioned data, we discuss two different evaluation methods for preserving privacy ID3, namely, first merging horizontally and developing vertically or first merging vertically and next developing horizontally. Next to introducing privacy preserving data mining over grid-partitioned data, the main contribution of this paper is that we show, by means of a complexity analysis that the former evaluation method is the more efficient.
The burden of premature mortality of epilepsy in high‐income countries: A systematic review from the Mortality Task Force of the International League Against Epilepsy

Since previous reviews of epidemiologic studies of premature mortality among people with epilepsy were completed several years ago, a large body of new evidence about this subject has been published. We aim to update prior reviews of mortality in epilepsy and to reevaluate and quantify the risks, potential risk factors, and causes of these deaths. We systematically searched the Medline and Embase databases to identify published reports describing mortality risks in cohorts and populations of people with epilepsy. We reviewed relevant reports and applied criteria to identify those studies likely to accurately quantify these risks in representative populations. From these we extracted and summarized the reported data. All population‐based studies reported an increased risk of premature mortality among people with epilepsy compared to general populations. Standard mortality ratios are especially high among people with epilepsy aged <50 years, among those whose epilepsy is categorized as structural/metabolic, those whose seizures do not fully remit under treatment, and those with convulsive seizures. Among deaths directly attributable to epilepsy or seizures, important immediate causes include sudden unexpected death in epilepsy (SUDEP), status epilepticus, unintentional injuries, and suicide. Epilepsy‐associated premature mortality imposes a significant public health burden, and many of the specific causes of death are potentially preventable. These require increased attention from healthcare providers, researchers, and public health professionals.
Re-considering neighborhood-based collaborative filtering parameters in the context of new data

The Movielens dataset and the Herlocker et al. study of 1999 have been very influential in collaborative filtering. Yet, the age of both invites re-examining their applicability. We use Netflix challenge data to re-visit the prior results. In particular, we re-evaluate the parameters of Herlocker et al.'s method on two critical factors: measuring similarity between users and normalizing the ratings of the users. We find that normalization plays a significant role and that Pearson Correlation is not necessarily the best similarity metric.
A pragmatic procedure to support the user-centric evaluation of recommender systems

As recommender systems are increasingly deployed in the real world, they are not merely tested offline for precision and coverage, but also "online" with test users to ensure good user experience. The user evaluation of recommenders is however complex and resource-consuming. We introduce a pragmatic procedure to evaluate recommender systems for experience products with test users, within industry constraints on time and budget. Researchers and practitioners can employ our approach to gain a comprehensive understanding of the user experience with their systems.
Treatment of advanced solid tumours with NSAIDs: Correlation of quantitative monitoring of circulating tumour cells and positron emission tomography-computed tomography imaging

The detection and characterisation of tumour-derived circulating epithelial tumor cells (CETCs) or circulating tumor cells (CTCs) have been a main focus of basic oncological research over previous years. Numerous studies in the past decade have shown that CTCs are a promising tool for the estimation of the risk for metastatic relapse. The present observational study describes treatment results using tumour imaging and the quantification of CTCs. A group of 14 patients with advanced carcinomas was followed during their anticancer treatments. CTC numbers were serially detected and treatment success was estimated by positron emission tomography-computed tomography. A connection was found between tumour remission and a decreasing CTC count in 83%, a connection between stable disease and stable CTC numbers in 78% and a connection between progressive disease (PD) and an increase in CTC count in 50% of cases. In the patients with PD, an incomplete response was observed affecting the CTCs, but not the solid region of the tumour. As a result of this study, it may be concluded that patients with solid tumours benefit from serial quantification of CTCs in addition to imaging, as this combination of techniques provides a more sensitive result than imaging alone.
A weighted estimating equation for linear regression with missing covariate data

Linear regression is one of the most popular statistical techniques. In linear regression analysis, missing covariate data occur often. A recent approach to analyse such data is a weighted estimating equation. With weighted estimating equations, the contribution to the estimating equation from a complete observation is weighted by the inverse ‘probability of being observed’. In this paper, we propose a weighted estimating equation in which we wrongly assume that the missing covariates are multivariate normal, but still produces consistent estimates as long as the probability of being observed is correctly modelled. In simulations, these weighted estimating equations appear to be highly efficient when compared to the most efficient weighted estimating equation as proposed by Robins et al. and Lipsitz et al. However, these weighted estimating equations, in which we wrongly assume that the missing covariates are multivariate normal, are much less computationally intensive than the weighted estimating equations given by Lipsitz et al. We compare the weighted estimating equations proposed in this paper to the efficient weighted estimating equations via an example and a simulation study. We only consider missing data which are missing at random; non‐ignorably missing data are not addressed in this paper. Copyright © 2002 John Wiley & Sons, Ltd.
Return to Learning After a Concussion and Compliance With Recommendations for Cognitive Rest

Objective:To determine the compliance of schools and school nurses in the United States with national recommendations for cognitive rest in students who sustain a concussion. Design:Cross-sectional questionnaire based. Participants:Members of the National Association of School Nurses working at the high school level. Intervention:A questionnaire, developed by the authors and based on recommendations for cognitive rest, was electronically distributed 3 times during the 2012 to 2013 academic year. Main Outcome Measures:Self-reported responses were collected regarding demographics and compliance of schools and school nurses with recommendations for the management of the postconcussion student, including the presence of specific guidelines for individualized care and the responsibility of the nurse for the prevention, detection, and management of concussions. Results:Analysis was performed on 1033 completed questionnaires (36% usable response rate). Fifty-three percent of schools have guidelines to assist students when returning to school after a concussion. These guidelines include extension of assignment deadlines (87%), rest periods during the school day (84%), postponement or staggering of tests (75%), reduced workload (73%), and accommodation for light or noise sensitivity (64%). Sixty-six percent of nurses in our sample have had special training in the recognition and management of concussions. Nurses reported involvement in the following roles: identifying suspected concussions (80%), providing emotional support for recovering students dealing with concussion-related depression (59%), and guiding the student's postconcussion graduated academic and activity re-entry process (58%). Conclusions:We detected a wide variability in compliance of schools and school nurses with national recommendations for cognitive rest. Clinical Relevance:Ensuring that schools have policies established for a student's return to learning, having specific guidelines to provide an individualized approach to return to learning based on postconcussion signs/symptoms, training school nurses in the recognition and management of concussions, and involving school nurses in the re-entry process are identified areas for improvement. Schools in the United States should be aware of these recommendations to guide a student's postconcussion graduated academic re-entry process.
Gender and Heritage Spanish Bilingual Grammars: A Study of Code-mixed Determiner Phrases and Copula Constructions

The study examined heritage speaker grammars and to what extent they diverge with respect to grammatical gender from adult L2 learners. Results from a preference task involving code-mixed Determiner Phrases (DPs) and code-mixed copula constructions show a difference between these two types of operations. Heritage speakers patterned with the control group of L1 Spanish/L2 English speakers for the copula/agreement constructions but differed from the control group for the DP conditions. We argue that it may be the case that the two operations (concord versus agreement) are processed differently by heritage speakers and people raised monolingually. If this idea is on the right track, then it can be assumed that it is processing and not different underlying representations that are the cause of the differences among the groups.
Pediatric Dosing and Body Size in Biotherapeutics

Although pediatric doses for biotherapeutics are often based on patients' body weight (mg/kg) or body surface area (mg/m2), linear body size dose adjustment is highly empirical. Growth and maturity are also important factors that affect the absorption, distribution, metabolism and excretion (ADME) of biologics in pediatrics. The complexity of the factors involved in pediatric pharmacokinetics lends to the reconsideration of body size based dose adjustment. A proper dosing adjustment for pediatrics should also provide less intersubject variability in the pharmacokinetics and/or pharmacodynamics of the product compared with no dose adjustment. Biological proteins and peptides generally share the same pharmacokinetic principle with small molecules, but the underlying mechanism can be very different. Here, pediatric and adult pharmacokinetic parameters are compared and summarized for selected biotherapeutics. The effect of body size on the pediatric pharmacokinetics for these biological products is discussed in the current review.