Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulating Children's Null Subjects: An Early Language Generation Model

This paper reports work in progress on a sentence generation model which attempts to emulate certain language output patterns of children between the ages of one and one-half and three years. In particular, the model addresses the issue of why missing or phonetically "null" subjects appear as often as they do in the speech of young English-speaking children. It will also be used to examine why other patterns of output appear in the speech of children learning languages such as Italian and Chinese. Initial findings are that an output generator successfully approximates the null-subject output patterns found in English-speaking children by using a 'processing overload' metric alone; however, reference to several parameters related to discourse orientation and agreement morphology is necessary in order to account for the differing patterns of null arguments appearing cross-linguistically. Based on these findings, it is argued that the 'null-subject phenomenon' is due to the combined effects of limited processing capacity and early, accurate parameter setting.
Human-Robot Mutual Adaptation in Shared Autonomy

Shared autonomy integrates user input with robot autonomy in order to control a robot and help the user to complete a task. Our work aims to improve the performance of such a human-robot team: the robot tries to guide the human towards an effective strategy, sometimes against the human's own preference, while still retaining his trust. We achieve this through a principled human-robot mutual adaptation formalism. We integrate a bounded-memory adaptation model of the human into a partially observable stochastic decision model, which enables the robot to adapt to an adaptable human. When the human is adaptable, the robot guides the human towards a good strategy, maybe unknown to the human in advance. When the human is stubborn and not adaptable, the robot complies with the human's preference in order to retain their trust. In the shared autonomy setting, unlike many other common human-robot collaboration settings, only the robot actions can change the physical state of the world, and the human and robot goals are not fully observable. We address these challenges and show in a human subject experiment that the proposed mutual adaptation formalism improves human-robot team performance, while retaining a high level of user trust in the robot, compared to the common approach of having the robot strictly following participants' preference.
Women and Aging: Transcending the Myths

Aging in women has traditionally been defined by the menopause, however it is often social and economic changes which are more important to women. In Aging in Women Linda Gannon redresses the balance. From a feminist perspective, she critically reviews current research and provides a more comprehensive analysis of the psychological effects of life-span changes for older women. Some of the topics she explores include second careers, empty-nest, divorce, chronic illness, retirement and sexuality.
Discovering epistasis in large scale genetic association studies by exploiting graphics cards

Despite the enormous investments made in collecting DNA samples and generating germline variation data across thousands of individuals in modern genome-wide association studies (GWAS), progress has been frustratingly slow in explaining much of the heritability in common disease. Today's paradigm of testing independent hypotheses on each single nucleotide polymorphism (SNP) marker is unlikely to adequately reflect the complex biological processes in disease risk. Alternatively, modeling risk as an ensemble of SNPs that act in concert in a pathway, and/or interact non-additively on log risk for example, may be a more sensible way to approach gene mapping in modern studies. Implementing such analyzes genome-wide can quickly become intractable due to the fact that even modest size SNP panels on modern genotype arrays (500k markers) pose a combinatorial nightmare, require tens of billions of models to be tested for evidence of interaction. In this article, we provide an in-depth analysis of programs that have been developed to explicitly overcome these enormous computational barriers through the use of processors on graphics cards known as Graphics Processing Units (GPU). We include tutorials on GPU technology, which will convey why they are growing in appeal with today's numerical scientists. One obvious advantage is the impressive density of microprocessor cores that are available on only a single GPU. Whereas high end servers feature up to 24 Intel or AMD CPU cores, the latest GPU offerings from nVidia feature over 2600 cores. Each compute node may be outfitted with up to 4 GPU devices. Success on GPUs varies across problems. However, epistasis screens fare well due to the high degree of parallelism exposed in these problems. Papers that we review routinely report GPU speedups of over two orders of magnitude (>100x) over standard CPU implementations.
High-Resolution Imaging of Kidney Vascular Corrosion Casts with Nano-CT

Abstract A vascular corrosion cast of an entire mouse kidney was scanned with a modular multiresolution X-ray nanotomography system. Using an isotropic voxel pitch of 0.5 μm, capillary systems such as the vasa recta, peritubular capillaries and glomeruli were clearly resolved. This represents a considerable improvement over corrosion casts scanned with microcomputed tomography systems. The resolving power of this system was clearly demonstrated by the unique observation of a dense, subcapsular mat of capillaries enveloping the entire outer surface of the cortical region. Resolution of glomerular capillaries was comparable to similar models derived from laser scanning confocal microscopy. The high-resolution, large field of view and the three-dimensional nature of the resulting data opens new possibilities for the use of corrosion casting in research.
Antiatherosclerotic Potential of Active Principle Isolated from Eugenia jambolana in Streptozotocin-Induced Diabetic Rats

The aim of the present study was to investigate the antiatherosclerotic effect of active principle (FIIc) isolated from aqueous fruit pulp extract of Eugenia jambolana. Crude aqueous extract of E. jambolana was subjected to purification using chromatographic techniques which yielded purified active compound (FIIc). Purity of FIIc was tested by HPLC. Phytochemical investigation of FIIc by NMR, IR, and UV spectra showed that the purified compound is α-hydroxy succinamic acid. The streptozotocin- (STZ-) induced diabetic rats were fed atherosclerotic (Ath) diet containing 1.5 mL olive oil containing 8 mg (3, 20,000 IU) vitamin D2 and 40 mg cholesterol for 5 consecutive days. The STZ-induced diabetic rats receiving Ath diet were orally administered FIIc at doses of 10, 15, and 20 mg/kg, and results were compared with reference drug, that is, glibenclamide (600 μg/mg) and healthy control. 30-day treatment with FIIc resulted in significant (P < .001) improvement in blood glucose, serum lipid profile, apolipoproteins (Apo A1 and apoB100), and endothelial dysfunction parameters. Histomorphological studies also confirmed biochemical findings. Our results showed that FIIc has protective effect on hyperglycemia-induced atherosclerosis.
Generative models for automatic recognition of human daily activities from a single triaxial accelerometer

In this work, we compare two generative models including Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) with Support Vector Machine (SVM) classifier for the recognition of six human daily activity (i.e., standing, walking, running, jumping, falling, sitting-down) from a single waist-worn tri-axial accelerometer signals through 4-fold cross-validation and testing on a total of thirteen subjects, achieving an average recognition accuracy of 96.43% and 98.21% in the first experiment and 95.51% and 98.72% in the second, respectively. The results demonstrate that both HMM and GMM are not only able to learn but also capable of generalization while the former outperformed the latter in the recognition of daily activities from a single waist worn tri-axial accelerometer. In addition, these two generative models enable the assessment of human activities based on acceleration signals with varying lengths.
Alveolar macrophage gene expression is altered in the setting of alcohol use disorders.

BACKGROUND Alcohol use disorders (AUDs) are associated with an increased susceptibility to a variety of common and devastating pulmonary diseases including community- and hospital-acquired pneumonias, as well as the acute respiratory distress syndrome (ARDS). Alveolar macrophages play an important role in preventing the development of these disorders through maintaining lung sterility and resolving lung inflammation. Although alcohol exposure has been associated with aberrant alveolar macrophage function in animal models, the clinical relevance of these observations in humans is not established. Therefore, we sought to determine the effects of AUDs on human alveolar macrophage gene expression. METHODS Whole genome microarray analysis was performed on alveolar macrophages obtained by bronchoalveolar lavage from a test cohort of subjects with AUDs (n = 7), and controls (n = 7) who were pair-matched on age, gender, and smoking. Probe set expression differences in this cohort were validated by real-time reverse transcription-polymerase chain reaction (RT RT-PCR). Functional analysis with web-based bioinformatics tools was utilized with microarray data to assess differentially expressed candidate genes (p < 0.01) based on alcohol consumption. Alveolar macrophage mRNA samples from a second cohort of subjects with AUDs (n = 7) and controls (n = 7) were used to confirm gene expression differences related to AUDs. RESULTS In both the test and the confirmatory cohorts, AUDs were associated with upregulation of alveolar macrophage gene expression related to apoptosis, including perforin-1, granzyme A, and CXCR4 (fusin). Pathways governing the regulation of progression through cell cycle and immune response were also affected, as was upregulation of gene expression for mitochondrial superoxide dismutase. Overall, 12 genes' expression was affected by AUDs independent of smoking. CONCLUSIONS Alcohol use disorders are associated with unique changes in human alveolar macrophage gene expression. Novel therapies targeting alveolar macrophage gene expression in the setting of AUDs may prove to be clinically useful in limiting susceptibility for pulmonary disorders in these individuals.
Meaningful Measures of the Current Account

Since the conventional current account uses cash flow accounting, it is potentially devoid of economic meaning. Assessing foreign assets at market values and including expected transfers from abroad, this paper reports two measures of the external surplus that are grounded in economic theory. The first measure is the aggregate generational current account, annual differences in the sum of net foreign assets across all current and future generations. The second measure is the generational profile of net foreign assets in a benchmark year. These ideas are implemented with data from Korea. Copyright 1997 by Blackwell Publishing Ltd.
Autism assessment through a small humanoid robot

Children affected by Autism Spectrum Disorder (ASD) show early impairment in Joint Attention and Imitation. We propose in this paper to explore their behaviors through the use of a small humanoid robot. A small set of activities have been developed to elicit such behaviors as part of the standard Early Start Denver Model treatment. Results shown statistically relevant differences between the behaviors of children affected by ASD and typical development groups.
Mechanisms of Copper Ion Mediated Huntington's Disease Progression

Huntington's disease (HD) is caused by a dominant polyglutamine expansion within the N-terminus of huntingtin protein and results in oxidative stress, energetic insufficiency and striatal degeneration. Copper and iron are increased in the striata of HD patients, but the role of these metals in HD pathogenesis is unknown. We found, using inductively-coupled-plasma mass spectroscopy, that elevations of copper and iron found in human HD brain are reiterated in the brains of affected HD transgenic mice. Increased brain copper correlated with decreased levels of the copper export protein, amyloid precursor protein. We hypothesized that increased amounts of copper bound to low affinity sites could contribute to pro-oxidant activities and neurodegeneration. We focused on two proteins: huntingtin, because of its centrality to HD, and lactate dehydrogenase (LDH), because of its documented sensitivity to copper, necessity for normoxic brain energy metabolism and evidence for altered lactate metabolism in HD brain. The first 171 amino acids of wild-type huntingtin, and its glutamine expanded mutant form, interacted with copper, but not iron. N171 reduced Cu2+ in vitro in a 1∶1 copper∶protein stoichiometry indicating that this fragment is very redox active. Further, copper promoted and metal chelation inhibited aggregation of cell-free huntingtin. We found decreased LDH activity, but not protein, and increased lactate levels in HD transgenic mouse brain. The LDH inhibitor oxamate resulted in neurodegeneration when delivered intra-striatially to healthy mice, indicating that LDH inhibition is relevant to neurodegeneration in HD. Our findings support a role of pro-oxidant copper-protein interactions in HD progression and offer a novel target for pharmacotherapeutics.
Structural Diversity and Homophily: A Study Across More than One Hundred Large-Scale Networks

Understanding the ways in which local network structures are formed and organized is a fundamental problem in network science. A widely recognized organizing principle is structural homophily, which suggests that people with more common neighbors are more likely to connect with each other. However, what influence the diverse structures formed by common neighbors have on link formation is much less well understood. To explore this problem, we begin by formally defining the structural diversity of common neighborhoods. Using a collection of 116 large-scale networks---the biggest with over 60 million nodes and 1.8 billion edges---we then leverage this definition to develop a unique network signature, which we use to uncover several distinct network superfamilies not discoverable by conventional methods. We demonstrate that structural diversity has a significant impact on link existence, and we discover striking cases where it violates the principle of homophily. Our findings suggest that structural diversity is an intrinsic network property, giving rise to potential advances in the pursuit of theories of link formation and network evolution.
Relationship between impulsivity and obsession types in obsessive-compulsive disorder

Abstract Objective: Impulsivity is an important aspect of obsessive-compulsive disorder (OCD) which is classified under a new heading in DSM-5 with other impulsivity related disorders like trichotillomania. Due to its heterogeneous nature, different obsessions may be linked to varying impulsivity profiles. Aim of this study was to investigate the impulsivity traits and their relationship with obsession types by comparing OCD subjects who display sexual, religious and aggressive obsessions or other obsessions to healthy controls. Methods: Outpatients with OCD (n = 146) and healthy controls (n = 80) were evaluated with Sociodemographic Data Form, SCID-I, SCID non-patient version, Yale-Brown Obsessive Compulsive Scale (Y-BOCS) and Barratt Impulsiveness Scale (BIS-11). Results: BIS-11 attention scores of the OCD group were significantly higher than healthy subjects. In patients with sexual, aggressive, religious obsessions, BIS-11 attention scores were significantly higher than those who have other obsession types and that of controls. Conclusions: Higher levels of attentional impulsivity, particularly in patients suffering from sexual, aggressive or religious obsessions suggest a common diathesis for a dysfunction in neural correlates corresponding to these symptoms. The results of our study may promote further studies conducted with more advanced and objective neuropsychometric tests evaluating features of the clinical course, neurobiology and the response to OCD treatment.
Practical evaluation of security for quantum key distribution

Many papers have proven the security of quantum key distribution (QKD) systems in the asymptotic framework. The degree of the security has not been discussed in the finite coding-length framework, sufficiently. However, to guarantee any implemented QKD system required, it is needed to evaluate a protocol with a finite coding length. For this purpose, we derive a tight upper bound of the eavesdropper's information. This bound is better than existing bounds. We also obtain the exponential rate of the eavesdropper's information. Further, we approximate our bound by using the normal distribution.
Solving Flexible Multi-objective JSP Problem Using A Improved Genetic Algorithm

Genetic algorithm is a combinatorial optimization problem solving in the field of search algorithm, because of its versatility and robustness, it has been widely used in various fields of science. However, there are some defects in traditional genetic algorithm . for its shortcomings, this paper proposed an improved genetic algorithm for multi-objective Flexible JSP (job shop scheduling) problem . The algorithm construct the initial solution based on judging similarity strategy and immune mechanisms, proposed a self-adaptation cross and mutation operator, and using simulated annealing algorithm strategy combined with immune mechanisms in the selection operator, the experiment proof shows that, the improved genetic algorithm can improve the performance.
Data-driven curvature for real-time line drawing of dynamic scenes

This article presents a method for real-time line drawing of deforming objects. Object-space line drawing algorithms for many types of curves, including suggestive contours, highlights, ridges, and valleys, rely on surface curvature and curvature derivatives. Unfortunately, these curvatures and their derivatives cannot be computed in real-time for animated, deforming objects. In a preprocessing step, our method learns the mapping from a low-dimensional set of animation parameters (e.g., joint angles) to surface curvatures for a deforming 3D mesh. The learned model can then accurately and efficiently predict curvatures and their derivatives, enabling real-time object-space rendering of suggestive contours and other such curves. This represents an order-of-magnitude speedup over the fastest existing algorithm capable of estimating curvatures and their derivatives accurately enough for many different types of line drawings. The learned model can generalize to novel animation sequences and is also very compact, typically requiring a few megabytes of storage at runtime. We demonstrate our method for various types of animated objects, including skeleton-based characters, cloth simulation, and blend-shape facial animation, using a variety of nonphotorealistic rendering styles. An important component of our system is the use of dimensionality reduction for differential mesh data. We show that Independent Component Analysis (ICA) yields localized basis functions, and gives superior generalization performance to that of Principal Component Analysis (PCA).
Minimal credential disclosure in trust negotiations

The secure release of identity attributes is a key enabler for electronic business interactions. Users should have the maximum control possible over the release of their identity attributes and should state under which conditions these attributes can be disclosed. Moreover, users should disclose only the identity attributes that are actually required for the transactions at hand. In this paper we present an approach for the controlled release of identity attributes that addresses such requirements. The approach is based on the integration of trust negotiation and minimal credential disclosure techniques. Trust negotiation supports selective and incremental disclosure of identity attributes, while minimal credential disclosure guarantees that only the attributes necessary to complete the on-line interactions are disclosed.
Age‐associated alterations in hippocampal and basal forebrain nuclear factor kappa B activity

Age‐related cognitive deficits are often associated with loss of cholinergic activity within the neurotrophin‐dependent cholinergic neurons that project from the basal forebrain to the hippocampus. The cause of reduced cholinergic function is unknown, but alterations in transcription factor‐signaling pathways causing altered gene expression may cause decreased specific tissue function, resulting in loss of cholinergic activity. We measured transcription factor Nuclear Factor kappa B by electrophoretic mobility shift assay and Western analysis in young and aged rat brain tissues and report that basal levels of Nuclear Factor kappa B DNA‐binding activity increase in the hippocampus and basal forebrain with age to significantly higher levels at 30 months of age. This age‐associated increase in binding activity is associated with increased translocation of p65 to the nucleus. These data show an age‐associated alteration in Nuclear Factor kappa B signal transduction pathways that may contribute to age‐associated decreases in specific tissue function. J. Neurosci. Res. 48:580–587, 1997. © 1997 Wiley‐Liss Inc.
NEMS by multilayer sidewall transfer lithography

This paper reports an extension of a recently demonstrated technique to fabricate nano-electro-mechanical systems (NEMS) using sidewall transfer lithography (STL). The process uses three pattern transfer steps. Each step only requires optical lithography, making the method suitable for low-cost, wafer scale fabrication. The first two involve STL and are used to form nanoscale features such as suspension beams. These may now intersect, breaking an important restriction of single-layer STL NEMS. The third involves conventional lithography and is used to form microscale features such as anchors. Current nanoscale features have a width of 100 nm and an aspect ratio of 50 : 1. The new process should allow mass parallel fabrication of complex NEMS.
Levels of Leydig cell autophagy regulate the fertility of male naked mole-rats

Fertility is abolished in nonbreeding males in colonies of natal naked mole-rats (NMRs). Although spermatogenesis occurs in both breeding and nonbreeding male NMRs, the mechanisms underlying the differences in fertility between breeders and nonbreeders remain unexplored. In this study, a significant decrease in autophagy was observed in Leydig cells of the testis from nonbreeding male NMRs. This alteration was visualised as a significant decrease in the levels of autophagy-related gene 7 (Atg7), Atg5, microtubule-associated protein 1A/B light chain 3 (LC3-II/I) and the number of autophagosomes and an increase in P62 levels using Western blotting analyses. Furthermore, monodansylcadaverine (MDC) staining and Western blot analyses revealed that testosterone production decreased in nonbreeding male NMR Leydig cells, this decrease was associated with a reduction in autophagy. Primary Leydig cells from breeding and nonbreeding male NMRs were processed to investigate the effect of an autophagy inhibitor (3-MA, 3-methyladenine) or an autophagy activator (rapamycin) on testosterone production. Rapamycin induced an increase in testosterone production in NMR Leydig cells, whereas 3-MA had the opposite effect. Consequently, spermatogenesis, the weight of the testis, and androgen levels were dramatically reduced in nonbreeding male NMRs. While rapamycin treatment restored the fertility of nonbreeding male NMRs. Based on these results, inadequate autophagy correlates with a decrease in steroid production in nonbreeding male NMR Leydig cells, which may ultimately influence the spermatogenesis and fertilities of these animals.