Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of bilingual language proficiency on recall accuracy and semantic clustering in free recall output: evidence for shared semantic associations across languages

ABSTRACT Two experiments investigated how well bilinguals utilise long-standing semantic associations to encode and retrieve semantic clusters in verbal episodic memory. In Experiment 1, Spanish-English bilinguals (N = 128) studied and recalled word and picture sets. Word recall was equivalent in L1 and L2, picture recall was better in L1 than in L2, and the picture superiority effect was stronger in L1 than in L2. Semantic clustering in word and picture recall was equivalent in L1 and L2. In Experiment 2, Spanish-English bilinguals (N = 128) and English-speaking monolinguals (N = 128) studied and recalled word sequences that contained semantically related pairs. Data were analyzed using a multinomial processing tree approach, the pair-clustering model. Cluster formation was more likely for semantically organised than for randomly ordered word sequences. Probabilities of cluster formation, cluster retrieval, and retrieval of unclustered items did not differ across languages or language groups. Language proficiency has little if any impact on the utilisation of long-standing semantic associations, which are language-general.
Happy life expectancy and correlates of happiness among older adults in South Africa

ABSTRACT Objectives: This paper examines factors associated with happiness and to estimate happy life expectancy for older people in South Africa. Methods: The study uses data from the first wave of the Study on Ageing and Adult Health (SAGE) survey, which is a nationally representative population-based survey with a sample of 3,840 individuals aged 50 years and above. The Sullivan method and multivariate linear regression analysis were used in the analysis. Results: The prevalence of happiness was the same for men (55.5%) and women (55.4%) at the youngest of the age groups (50–59). However, this prevalence was higher in men than women across older ages. Women demonstrated longer life expectancy and happy life expectancy, but also unhappy life expectancy, compared to men, across all the ages. However, men had greater proportions of happy life expectancies compared to women. In multivariate analysis, wealth status, health, activity limitation, race and age were significantly associated with happiness among men and women. Conclusions: Gender disparities in happiness are demonstrated in this study. It is important to understand the factors that promote happiness in older people as this may point to areas that need intervention for improving overall quality of life.
Unsupervised Deep Context Prediction for Background Foreground Separation

In many advanced video based applications background modeling is a pre-processing step to eliminate redundant data, for instance in tracking or video surveillance applications. Over the past years background subtraction is usually based on low level or hand-crafted features such as raw color components, gradients, or local binary patterns. The background subtraction algorithms performance suffer in the presence of various challenges such as dynamic backgrounds, photometric variations, camera jitters, and shadows. To handle these challenges for the purpose of accurate background modeling we propose a unified framework based on the algorithm of image inpainting. It is an unsupervised visual feature learning hybrid Generative Adversarial algorithm based on context prediction. We have also presented the solution of random region inpainting by the fusion of center region inpaiting and random region inpainting with the help of poisson blending technique. Furthermore we also evaluated foreground object detection with the fusion of our proposed method and morphological operations. The comparison of our proposed method with 12 state-of-the-art methods shows its stability in the application of background estimation and foreground detection.
Random-Radius Ball Method for Estimating Closeness Centrality

In the analysis of real-world complex networks, identifying important vertices is one of the most fundamental operations. A variety of centrality measures have been proposed and extensively studied in various research areas. Many of distance-based centrality measures embrace some issues in treating disconnected networks, which are resolved by the recently emerged harmonic centrality. This paper focuses on a family of centrality measures including the harmonic centrality and its variants, and addresses their computational difficulty on very large graphs by presenting a new estimation algorithm named the random-radius ball (RRB) method. The RRB method is easy to implement, and a theoretical analysis, which includes the time complexity and error bounds, is also provided. The effectiveness of the RRB method over existing algorithms is demonstrated through experiments on real-world networks.
Determination of Median Lethal Concentration (LC50) and Behavioral Effects of Chlordecone in the Cichlid fish, Etroplus maculatus

The present study was aimed to investigate the median lethal concentration of chlordecone in the Cichlid fish, Etroplus maculatus and also its behavioral changes on the exposure to the environmental contaminant. Behavior is considered as a valid biomarker of pollution and also has high ecological significance, as it influences the fitness of the affected species. Different concentrations of chlordecone were exposed to the fish to evaluate the median lethal concentration at 96 h. The result showed that 35 μg/ L kill 50% of the animal, which is determined by the probit analysis. Behavioral changes such as reddening of eyes and fins, exopthalmia, slow movement and lethargy, hitting on the side walls were observed. Results from this study showed that the change in the behavior pattern due to chlordecone exposure was an ecologically relevant assessment for the effects of chlordecone on the test animal.
Generating High-Quality Surface Realizations Using Data Augmentation and Factored Sequence Models

This work presents state of the art results in reconstruction of surface realizations from obfuscated text. We identify the lack of sufficient training data as the major obstacle to training high-performing models, and solve this issue by generating large amounts of synthetic training data. We also propose preprocessing techniques which make the structure contained in the input features more accessible to sequence models. Our models were ranked first on all evaluation metrics in the English portion of the 2018 Surface Realization shared task.
Sonographic median nerve change after steroid injection for carpal tunnel syndrome

Introduction: The sonographic changes of the median nerve after steroid injection for carpal tunnel syndrome (CTS) still require investigation. Methods: Sixty‐two patients with CTS were included. The Boston Carpal Tunnel Questionnaire was administered, and ultrasonographic examinations were performed before and at 2, 6, and 12 weeks after steroid injection. At 12 weeks, general improvement was scored on a 6‐point Likert scale. Results: After treatment, the cross‐sectional area (CSA) of the median nerve was significantly reduced at 2‐, 6‐, and 12‐week follow‐ups (for each, P < 0.001, analysis of variance). The “significant improvement” group (n = 39) had a significantly greater reduction in the CSA at the carpal tunnel inlet (P = 0.014) and CSA in the proximal carpal tunnel (P = 0.003) compared with the “little/no improvement” group (n = 23). Discussion: Sonographic measurement of CSA may be considered complementary to the standard clinical evaluation in monitoring of treatment response in patients with CTS. Muscle Nerve 58: 402–406, 2018
Eukaryotic Translation Elongation Factor 1-Alpha 1 Inhibits p53 and p73 Dependent Apoptosis and Chemotherapy Sensitivity

The p53 family of transcription factors is a key regulator of cell proliferation and death. In this report we identify the eukaryotic translation elongation factor 1-alpha 1 (eEF1A1) to be a novel p53 and p73 interacting protein. Previous studies have demonstrated that eEF1A1 has translation-independent roles in cancer. We report that overexpression of eEF1A1 specifically inhibits p53-, p73- and chemotherapy-induced apoptosis resulting in chemoresistance. Short-interfering RNA-mediated silencing of eEF1A1 increases chemosensitivity in cell lines bearing wild type p53, but not in p53 null cells. Furthermore, silencing of eEF1A1 partially rescues the chemoresistance observed in response to p53 or p73 knockdown, suggesting that eEF1A1 is a negative regulator of the pro-apoptotic function of p53 and p73. Thus, in the context of p53-family signaling, eEF1A1 has anti-apoptotic properties. These findings identify a novel mechanism of regulation of the p53 family of proteins by eEF1A1 providing additional insight into potential targets to sensitize tumors to chemotherapy.
A Development of Travel Itinerary Planning Application using Traveling Salesman Problem and K-Means Clustering Approach

In this paper, an algorithm for making travel itinerary using traveling salesman problem (TSP) and k-means clustering technique is proposed. We employ the algorithm to develop a web based application that can help travelers to plan their travel itinerary. The developed application should be able to provide an optimal itinerary recommendation in terms of distance and travel time. We use initial assumption that the traveler has determined all the tourist destinations he/she wants to visit and also the number of days he/she will stay in the region. Our approach consists of two steps, macro grouping using k-means and micro tour arrangement using TSP. Yogyakarta city, one of the tourist city in Indonesia, is used as an example to illustrate how the proposed algorithm can help travelers make their itinerary. This approach works well in small to medium number points of interest. However, the application still need many improvements such as to make it run faster and to handle the additional constraints that exist when creating an itinerary.
Post-glacial recolonization of European biota

Population structure is the result of both present processes and past history. Molecular markers are proving of great value in describing the former, and it is important to similarly determine the latter in order to understand their respective contributions. The study of palaeo-climates has also advanced significantly, and in particular that of the Pleistocene ice ages, which modified species ranges considerably. The last ice age and rapid post-glacial colonization of Europe is summarized. Possible population genetic consequences of expansion northward from southern refugia, and those of remaining in these mountainous regions are discussed. A series of recent case studies are detailed where DNA sequence information has been used to describe species genetic variation and subdivision across Europe. These include a grasshopper, the hedgehog, oak trees, the common beech, the black alder, the brown bear, newts, shrews, water vole, silver fir and house mice. These molecular data confirm southern peninsulas of Europe as major ice age refugia, and in most cases demonstrate that genetically distinct taxa emerged from them. They can thus define genomic differences and so greatly augment previous fossil data. The refugial genomes contributed differently in various species to the re-colonization of Europe, with three broad patterns described as paradigms‘grasshopper’, ‘hedgehog’ and ‘bear’. These different expansion patterns produced clusters of hybrid zones where they made contact, and it is argued that many species genomes may be further cryptically subdivided. A reduction in diversity from southern to northern Europe in the extent of allelic variation and species subdivision is seen; this is attributed to rapid expansion northward and the varied topography of southern refugia allowing populations to diverge through several ice ages. The differences in DNA sequence indicate that some species have been diverging in refugial regions for a few ice ages at most, whilst distinct lineages in other species suggest much more ancient separation.
Association Between Autophagy and Neurodegenerative Diseases

Autophagy is a phylogenetically conserved mechanism that controls the degradation of subcellular constituents, including misfolded proteins, and damaged organelles. The progression of many neurodegenerative diseases is thought to be driven by the aggregation of misfolded proteins; therefore, autophagic activity is thought to affect disease severity to some extent. In some neurodegenerative diseases, the suppression of autophagic activity accelerates disease progression. Given that the induction of autophagy can potentially mitigate disease severity, various autophagy-inducing compounds have been developed and their efficacy has been evaluated in several rodent models of neurodegenerative diseases.
A Cell Surface Aggregation-Promoting Factor from Lactobacillus gasseri Contributes to Inhibition of Trichomonas vaginalis Adhesion to Human Vaginal Ectocervical Cells

Trichomoniasis, a prevalent sexually transmitted infection, is commonly symptomatic in women. The causative agent is Trichomonas vaginalis, an extracellular protozoan parasite. ABSTRACT Trichomoniasis, a prevalent sexually transmitted infection, is commonly symptomatic in women. The causative agent is Trichomonas vaginalis, an extracellular protozoan parasite. The host-protective mechanisms and molecules of vaginal lactobacilli that counteract this pathogen are largely unknown. This study examines the inhibition promoted by Lactobacillus gasseri against the adhesion of T. vaginalis to host cells, a critical virulence aspect of this pathogen. We observed that the vaginal strain L. gasseri ATCC 9857 is highly inhibitory by various contact-dependent mechanisms and that surface proteins are largely responsible for this inhibitory phenotype. We found that the aggregation-promoting factor APF-2 from these bacteria significantly contributes to inhibition of the adhesion of T. vaginalis to human vaginal ectocervical cells. Understanding the molecules and mechanisms used by lactobacilli to protect the host against T. vaginalis might help in the development of novel and specific therapeutic strategies that take advantage of the natural microbiota.
In Vivo and In Vitro Effects of a ClpP-Activating Antibiotic against Vancomycin-Resistant Enterococci

Antibiotics with novel bactericidal mechanisms of action are urgently needed. The antibiotic acyldepsipeptide 4 (ADEP4) activates the ClpP protease and causes cells to self-digest. ABSTRACT Antibiotics with novel bactericidal mechanisms of action are urgently needed. The antibiotic acyldepsipeptide 4 (ADEP4) activates the ClpP protease and causes cells to self-digest. The effects of ADEP4 and ClpP activation have not been characterized sufficiently for the enterococci, which are important pathogens known for high levels of acquired and intrinsic antibiotic resistance. In the present study, ADEP4 was found to be potently active against both Enterococcus faecalis and Enterococcus faecium, with MIC90s of 0.016 μg/ml and 0.031 μg/ml, respectively. ClpP purified from E. faecium was found to bind ADEP4 in a surface plasmon resonance analysis, and ClpP activation by ADEP4 was demonstrated biochemically with a β-casein digestion assay. In addition, E. faecium ClpP was crystallized in the presence of ADEP4, revealing ADEP4 binding to ClpP in the activated state. These results confirm that the anti-enterococcal activity of ADEP4 occurs through ClpP activation. In killing curve assays, ADEP4 was found to be bactericidal against stationary-phase vancomycin-resistant E. faecalis (VRE) strain V583, and resistance development was prevented when ADEP4 was combined with multiple classes of approved antibiotics. ADEP4 in combination with partnering antibiotics also eradicated mature VRE biofilms within 72 h of treatment. Biofilm killing with ADEP4 antibiotic combinations was superior to that with the clinically used combinations ampicillin-gentamicin and ampicillin-daptomycin. In a murine peritoneal septicemia model, ADEP4 alone was as effective as ampicillin. ADEP4 coadministered with ampicillin was significantly more effective than either drug alone. These data suggest that ClpP-activating antibiotics may be useful for treating enterococcal infections.
First tooth, first visit, zero cavities: a review of the evidence as it applies to Ireland.

STATEMENT OF THE PROBLEM There is increasing evidence that the first oral health visit should occur before 12 months of age. Anecdotally, most children in Ireland are not seen at an optimal age. PURPOSE OF THE STUDY To review the benefits, on both an individual and population basis, of children receiving oral healthcare before 12 months of age, and to apply the appropriate available evidence to the current oral health landscape in Ireland. RESULTS From an individual perspective, there is published evidence of the benefits of infants attending a dentist before the age of 12 months. These benefits include the opportunity to risk assess the child, provide tailored oral health education and institute preventive care. From an oral health promotion perspective, there are additional benefits of providing population level programmes for children at an early age. CONCLUSIONS Introduction of the first dental visit by 12 months of age should be firmly on the health agenda here in Ireland.
Learning Latent Sentiment Scopes for Entity-Level Sentiment Analysis

In this paper, we focus on the task of extracting named entities together with their associated sentiment information in a joint manner. Our key observation in such an entity-level sentiment analysis (a.k.a. targeted sentiment analysis) task is that there exists a sentiment scope within which each named entity is embedded, which largely decides the sentiment information associated with the entity. However, such sentiment scopes are typically not explicitly annotated in the data, and their lengths can be unbounded. Motivated by this, unlike traditional approaches that cast this problem as a simple sequence labeling task, we propose a novel approach that can explicitly model the latent sentiment scopes. Our experiments on the standard datasets demonstrate that our approach is able to achieve better results compared to existing approaches based on conventional conditional random fields (CRFs) and a more recent work based on neural networks.
Seeing through obfuscation : interactive detection and removal of opaque predicates

A program can be obfuscated to impede analysis of its inner workings or data while retaining its original functionality. The effectiveness of software obfuscation depends highly on the technique used, on the program that is being obfuscated and on the type of secret that is being hidden. Yet, under the right circumstances, an obfuscated program can require a considerably larger amount of time and effort to analyse than its non-obfuscated counterpart. Different methods of obfuscation provide protection against different kinds of attackers. The focus of this thesis is on control-flow obfuscation and specifically on one method of control-flow obfuscation: the insertion of opaque predicates. While control-flow obfuscation techniques were originally mostly intended to protect against manual analysis, upcoming automated software testing and analysis techniques such as symbolic execution have created a new challenge for obfuscators. Several automated deobfuscators make use of such analysis techniques [22] [6]. However, some of these automated deobfuscation techniques are either not available in (easy-to-use) tools or are limited to a very specific type of obfuscation and lack versatility. This thesis gives an overview of the current state-of-the-art in opaque predicates and control-flow obfuscation in general, showing that for some of these obfuscations, little to no automated deobfuscation tools are available, at least not outside the realm of academic proofs-of-concept. It describes an attempt at partly filling this gap by the creation of an IDA Pro plugin called Drop, which implements an advanced opaque-predicate detection algorithm (Ming et al. [22]) in a versatile manner. We show that Drop is able to detect and remove invariant and contextual opaque predicates in both artificial and non-artificial environments. Additionally, we show that the ability for an analyst to provide interactive input during the deobfuscation process can be rather useful in various scenarios, and the ability to provide a specific type of constraint on program arguments can even help detect and reverse an otherwise very strong type of control-flow obfuscation: input-invariant opaque predicates.
Altered Whole-Brain Structural Covariance of the Hippocampal Subfields in Subcortical Vascular Mild Cognitive Impairment and Amnestic Mild Cognitive Impairment Patients

The hippocampus plays important roles in memory processing. However, the hippocampus is not a homogeneous structure, which consists of several subfields. The hippocampal subfields are differently affected by many neurodegenerative diseases, especially mild cognitive impairment (MCI). Amnestic mild cognitive impairment (aMCI) and subcortical vascular mild cognitive impairment (svMCI) are the two subtypes of MCI. aMCI is characterized by episodic memory loss, and svMCI is characterized by extensive white matter hyperintensities and multiple lacunar infarctions on magnetic resonance imaging. The primary cognitive impairment in svMCI is executive function, attention, and semantic memory. Some variations or disconnections within specific large-scale brain networks have been observed in aMCI and svMCI patients. The aim of this study was to investigate abnormalities in structural covariance networks (SCNs) between hippocampal subfields and the whole cerebral cortex in aMCI and svMCI patients, and whether these abnormalities are different between the two groups. Automated segmentation of hippocampal subfields was performed with FreeSurfer 5.3, and we selected five hippocampal subfields as the seeds of SCN analysis: CA1, CA2/3, CA4/dentate gyrus (DG), subiculum, and presubiculum. SCNs were constructed based on these hippocampal subfield seeds for each group. Significant correlations between hippocampal subfields, fusiform gyrus (FFG), and entorhinal cortex (ERC) in gray matter volume were found in each group. We also compared the differences in the strength of structural covariance between any two groups. In the aMCI group, compared to the normal controls (NC) group, we observed an increased association between the left CA1/CA4/DG/subiculum and the left temporal pole. Additionally, the hippocampal subfields (bilateral CA1, left CA2/3) significantly covaried with the orbitofrontal cortex in the svMCI group compared to the NC group. In the aMCI group compared to the svMCI group, we observed decreased association between hippocampal subfields and the right FFG, while we also observed an increased association between the bilateral subiculum/presubiculum and bilateral ERC. These findings provide new evidence that there is altered whole-brain structural covariance of the hippocampal subfields in svMCI and aMCI patients and provide insights to the pathological mechanisms of different MCI subtypes.