Miracle-dz/UniFAR-FTUs huggingface dataset:
Variability in clinical phenotype despite common chromosomal deletion in Smith-Magenis syndrome [del(17)(p11.2p11.2)]

Purpose This report delineates the phenotypic features in a cohort of 58 individuals with Smith-Magenis syndrome (SMS) and compares features of patients with the common microdeletion to those of patients with variable sized deletions, and the three previously reported patients who harbor a mutation in RAI1 (retinoic acid induced 1). Methods From December 1990 thru September 1999, 58 persons with SMS were enrolled in a 5-day multidisciplinary clinical protocol at the General Clinical Research Center (GCRC), Texas Children's Hospital. Each patient had a cytogenetically evident deletion in 17p11.2. Results Of the 51 patients in whom the molecular extent of the chromosomal deletion could be delineated by pulsed-field gel electrophoresis (PFGE) and/or fluorescent in situ hybridization (FISH), 39 (≈76%) had the common SMS deletion. Smaller or larger deletions were seen in ≈12% and ≈10% of patients, respectively, and 1 patient had a complex chromosomal rearrangement including a deletion in 17p11.2. Parent of origin was determined by polymorphic marker analysis in a subset of patients: maternal ≈43%, paternal ≈57%. All patients had impaired cognitive and adaptive functioning and had at least one objective measure of sleep disturbance. Other common features (seen in > 50% of patients) include short stature, ophthalmological, and otolaryngological anomalies, hearing impairment, abnormal EEG, and scoliosis. Cardiac and renal anomalies were seen in ≈45% and ≈19% of patients, respectively. There are no statistically significant differences in the incidence of these abnormalities in patients with the common deletion compared to those patients with smaller or larger sized deletions.Conclusions Despite a common deletion size in 76% of patients with SMS, the only constant objectively defined features among these patients are sleep disturbances, low adaptive functioning, and mental retardation. There is no pathognomonic clinical feature, no characteristic cardiovascular defect, renal anomaly, otolaryngological or ophthalmic abnormality in SMS.
ICA 512, an autoantigen of type I diabetes, is an intrinsic membrane protein of neurosecretory granules.

Islet cell autoantigen (ICA) 512 is a novel autoantigen of insulin‐dependent diabetes mellitus (IDDM) which is homologous to receptor‐type protein tyrosine phosphatases (++PTPases). We show that ICA 512 is an intrinsic membrane protein of secretory granules expressed in insulin‐producing pancreatic beta‐cells as well as in virtually all other peptide‐secreting endocrine cells and neurons containing neurosecretory granules. ICA 512 is cleaved at its luminal domain and, following exposure at the cell surface, recycles to the Golgi complex region and is sorted into newly formed secretory granules. By immunoprecipitation, anti‐ICA 512 autoantibodies were detected in 15/17 (88%) newly diagnosed IDDM patients, but not in 10/10 healthy subjects. These results suggest that tyrosine phosphorylation participates in some aspect of secretory granule function common to all neuroendocrine cells and that a subset of autoantibodies in IDDM is directed against an integral membrane protein of insulin‐containing granules.
Many-Objective Particle Swarm Optimization Using Two-Stage Strategy and Parallel Cell Coordinate System

It is a daunting challenge to balance the convergence and diversity of an approximate Pareto front in a many-objective optimization evolutionary algorithm. A novel algorithm, named many-objective particle swarm optimization with the two-stage strategy and parallel cell coordinate system (PCCS), is proposed in this paper to improve the comprehensive performance in terms of the convergence and diversity. In the proposed two-stage strategy, the convergence and diversity are separately emphasized at different stages by a single-objective optimizer and a many-objective optimizer, respectively. A PCCS is exploited to manage the diversity, such as maintaining a diverse archive, identifying the dominance resistant solutions, and selecting the diversified solutions. In addition, a leader group is used for selecting the global best solutions to balance the exploitation and exploration of a population. The experimental results illustrate that the proposed algorithm outperforms six chosen state-of-the-art designs in terms of the inverted generational distance and hypervolume over the DTLZ test suite.
Cell type specificity of neurovascular coupling in cerebral cortex

Identification of the cellular players and molecular messengers that communicate neuronal activity to the vasculature driving cerebral hemodynamics is important for (1) the basic understanding of cerebrovascular regulation and (2) interpretation of functional Magnetic Resonance Imaging (fMRI) signals. Using a combination of optogenetic stimulation and 2-photon imaging in mice, we demonstrate that selective activation of cortical excitation and inhibition elicits distinct vascular responses and identify the vasoconstrictive mechanism as Neuropeptide Y (NPY) acting on Y1 receptors. The latter implies that task-related negative Blood Oxygenation Level Dependent (BOLD) fMRI signals in the cerebral cortex under normal physiological conditions may be mainly driven by the NPY-positive inhibitory neurons. Further, the NPY-Y1 pathway may offer a potential therapeutic target in cerebrovascular disease. DOI: http://dx.doi. org/10.7554/eLife.14315. 001
Cold vs. warm water route – sources for the upper limb of the AMOC revisited in a high-resolution ocean model

Abstract. The northward flow of the upper limb of the Atlantic Meridional Overturning Circulation (AMOC) is fed by waters entering the South Atlantic from the Indian Ocean mainly via the Agulhas Current (AC) system and by waters entering from the Pacific through Drake Passage (DP), commonly referred to as the warm and cold water routes, respectively. However, there is no final consensus on the relative importance of these two routes for the upper limb’s volume transport and thermohaline properties. In this study we revisited the AC and DP contributions by performing Lagrangian analyzes between the two source regions and the North Brazil Current (NBC) at 6° S in a realistically forced high-resolution (1/20°) ocean model. Our results agree with the prevailing conception that the AC contribution is the major source for the upper limb transport of the AMOC. However, they also suggest a non-negligible DP contribution of at least 40 %, which is substantially higher than estimates from previous Lagrangian studies with coarser resolution models, but now better matches estimates from Lagrangian observations. Moreover, idealized analyzes of decadal changes in the DP and AC contributions indicate that the ongoing increase in Agulhas leakage indeed may have evoked an increase in the AC contribution to the upper limb of the AMOC while the DP contribution decreased. In terms of thermohaline properties, our study highlights that the AC and DP contributions cannot be unambiguously distinguished by their temperature, as the commonly adopted terminology may imply, but rather by their salinity when entering the South Atlantic. During their transit towards the NBC the bulk of DP waters experiences a net density loss through a net warming, whereas the bulk of AC waters experiences a slight net density gain through a net increase in salinity. Notably, these density changes are nearly completely captured by those Lagrangian particle trajectories that reach the surface mixed layer at least once during their transit, which amount to 66 % and 49 % for DP and AC waters, respectively. This implies that more than half of the water masses supplying the upper limb of the AMOC are actually formed within the South Atlantic, and do not get their characteristic properties in the Pacific and Indian Oceans.
Handling Uncertain Tags in Visual Recognition

Gathering accurate training data for recognizing a set of attributes or tags on images or videos is a challenge. Obtaining labels via manual effort or from weakly-supervised data typically results in noisy training labels. We develop the FlipSVM, a novel algorithm for handling these noisy, structured labels. The FlipSVM models label noise by "flipping" labels on training examples. We show empirically that the FlipSVM is effective on images-and-attributes and video tagging datasets.
Relamination Styles in Collisional Orogens

During continental collision, a part of the lower‐plate material can be subducted, emplaced at the base of the upper plate, and eventually incorporated into its crust. This mechanism of continental‐crust transformation is called relamination, and it has been invoked to explain occurrences of high‐pressure felsic rocks in different structural positions of several orogenic systems. In the present study we reproduced relamination during continental collision in a thermomechanical numerical model. We performed a parametric study and distinguished three main types of evolution regarding the fate of the subducted continental crust: (i) return along the plate interface in a subduction channel or wedge, (ii) flow at the bottom of the upper‐plate lithosphere and subsequent translithospheric exhumation near the arc or in the back‐arc region (“sublithospheric relamination”), and (iii) nearly horizontal flow directly into the upper‐plate crust (“intracrustal relamination”). Sublithospheric relamination is preferred for relatively quick convergence of thin continental plates. An important factor for the development of sublithospheric relamination is melting of the subducted material, which weakens the lithosphere and opens a path for the exhumation of the relaminant. In contrast, a thick and strong overriding plate typically leads to exhumation near the plate interface. If the overriding plate is too thin or weak, intracrustal relamination occurs. We show that each of these evolution types has its counterpart in nature: (i) the Alps and the Caledonides, (ii) the Himalayan‐Tibetan system and the European Variscides, and (iii) pre‐Cambrian ultrahot orogens.
Interactive Systems Based on Electrical Muscle Stimulation

Electrical muscle stimulation (EMS) has been used since the 1960s in rehabilitative medicine to regenerate lost motor functions, but in recent years researchers have started to explore new EMS applications including guided training, muscle-propelled force feedback for more immersive virtual experiences, and novel forms of information access. The authors analyze the interactive potential of EMS and compare it to more traditional mechanical actuation. The web extra at https://youtu.be/YA0mv9X9Ncw demonstrates Muscle-plotter, an interactive system that combines EMS with a motion-tracking digital pen.
Visual search and selective attention

Visual search is a key paradigm in attention research that has proved to be a test bed for competing theories of selective attention. The starting point for most current theories of visual search has been Treisman's “feature integration theory” of visual attention (e.g., Treisman & Gelade, 1980). A number of key issues that have been raised in attempts to test this theory are still pertinent questions of research today: (1) The role and (mode of) function of bottom-up and top-down mechanisms in controlling or “guiding” visual search; (2) in particular, the role and function of implicit and explicit memory mechanisms; (3) the implementation of these mechanisms in the brain; and (4) the simulation of visual search processes in computational or, respectively, neurocomputational (network) models. This paper provides a review of the experimental work and the—often conflicting—theoretical positions on these thematic issues, and goes on to introduce a set of papers by distinguished experts in fields designed to provide solutions to these issues.
Moving Object Graphs and Layer Extraction from Image Sequences

We describe a new approach to extracting layered representations from image sequences based on moving object graphs(MOGs). A MOG is a form of region adjacency graph which links together local motion segmentations corresponding to distinct moving regions in the scene, typically either foreground objects or the background. The local motion segmentations are obtained by fusing colour segmentations with block motion estimates and the MOGs link segmentations with consistent spatial and motion properties. Linking MOGs across frames then allows temporal consistency to be imposed and layers to be extracted. The approach provides a flexible framework within which to combine local and global constraints both spatially and temporally, enabling robust motion segmentation and layer extraction. Results of experiments on real sequences illustrate that the approach is effective.
Deep Syntactic Structures for String-to-Tree Translation

A state-of-the-art syntax-based Statistical Machine Translation (SMT) model, string-to-tree translation model (Galley et al., 2004; Galley et al., 2006; Chiang et al., 2009), is to construct a number of parse trees of the target language by ‘parsing’ a source language sentence making use of a bilingual translation grammar. Given a set of parallel sentences for training, optimal word alignments for every sentence pairs are first derived by using GIZA++ (Och and Ney, 2003). Then, a syntactic parser is used to parse the target sentences into trees. A source sentence, a target parse tree, and the alignment between the source and target words form an ‘aligned treestring pair’. In order to split a tree into tree fragments yet obeying the constraints from the word alignment, algorithms proposed by Galley et al. (2004; 2006) are the de facto standard for extracting minimal and composed tree-string translation rules from the aligned tree-string pairs. n-gram language model (LM) integrated CKY algorithm (Huang and Chiang, 2005; Chiang, 2007) is popularly used for decoding. Tree-string translation rules are binarized (Zhang et al., 2006) into Chomsky normal forms before been used by the CKY algorithm. Figure 1 illustrates the training and testing process of Japanese string to English tree translation. For simplicity, similar example is used for both translation rule extracting and decoding. During training, suppose we are given an aligned tree-string pair, GHKM algorithm (Galley et al., 2004) is first applied for minimal rule extraction. During testing, given a Japanese sentence, we try to build a number x0 は x1 x0 x1 x1 を x0
A Multifunctional 3D Co-Culture System for Studies of Mammary Tissue Morphogenesis and Stem Cell Biology

Studies on the stem cell niche and the efficacy of cancer therapeutics require complex multicellular structures and interactions between different cell types and extracellular matrix (ECM) in three dimensional (3D) space. We have engineered a 3D in vitro model of mammary gland that encompasses a defined, porous collagen/hyaluronic acid (HA) scaffold forming a physiologically relevant foundation for epithelial and adipocyte co-culture. Polarized ductal and acinar structures form within this scaffold recapitulating normal tissue morphology in the absence of reconstituted basement membrane (rBM) hydrogel. Furthermore, organoid developmental outcome can be controlled by the ratio of collagen to HA, with a higher HA concentration favouring acinar morphological development. Importantly, this culture system recapitulates the stem cell niche as primary mammary stem cells form complex organoids, emphasising the utility of this approach for developmental and tumorigenic studies using genetically altered animals or human biopsy material, and for screening cancer therapeutics for personalised medicine.
Eye contact detection in humans from birth

Making eye contact is the most powerful mode of establishing a communicative link between humans. During their first year of life, infants learn rapidly that the looking behaviors of others conveys significant information. Two experiments were carried out to demonstrate special sensitivity to direct eye contact from birth. The first experiment tested the ability of 2- to 5-day-old newborns to discriminate between direct and averted gaze. In the second experiment, we measured 4-month-old infants' brain electric activity to assess neural processing of faces when accompanied by direct (as opposed to averted) eye gaze. The results show that, from birth, human infants prefer to look at faces that engage them in mutual gaze and that, from an early age, healthy babies show enhanced neural processing of direct gaze. The exceptionally early sensitivity to mutual gaze demonstrated in these studies is arguably the major foundation for the later development of social skills.
Declining phosphorus as a potential driver for the onset of Didymosphenia geminata mats in North American rivers

Didymosphenia geminata is a stalk‐forming diatom capable of creating thick benthic mats in low‐nutrient streams. There are two hypotheses to explain the rapid worldwide increase in occurrence of nuisance D. geminata mats: (a) Cells are spread among rivers and across broad ecoregions through natural and anthropogenic vectors, or (2) pre‐existing D. geminata populations are forming mats in response to changing environmental conditions within the habitat. Low phosphorus (P) concentrations are a major trigger for stalk production by D. geminata cells. Although the environmental change hypothesis is gaining support among researchers, long‐term data sets demonstrating declining P concentrations prior to reported mat formation have been essentially absent from the literature. Here, we present long‐term datasets for two case studies for which long‐term P and D. geminata data coincide: the Matapedia River in Eastern Canada and the Kootenai River below Libby Dam in Montana, United States. Both rivers had declining P levels over time. However, there was a 2‐ and 20‐year lag time, respectively, between mat development and reaching the previously proposed average 2 μg/L soluble reactive P threshold for development. Although the Matapedia River provides some support of the environmental change hypothesis, the Kootenai River data set suggests other environmental factors may play a role in mat development. The data presented do not rule out the environmental change hypothesis but do suggest there may be conditions in addition to low P that must be met for mats to form and the environmental change hypothesis can likely be refined to include more parameters to better understand and mitigate the influence of mats.
A case study in distributed control: Elastically interconnected seesaw-cart systems

As the main contribution of the paper, we present a network of electro-mechanical systems as a suitable platform for education, testing and verification of real-life implementation of decentralised and distributed control solutions. The overall system (network) consists of a set of elastically interconnected seesaw-chart systems. Additionally, suitable, control oriented, structured model of the system's dynamics is derived and presented. Results of a case study in distributed control are presented, together with comparison with achievable centralized control behaviour.
A Factored Functional Dependency Transformation of the English Penn Treebank for Probabilistic Surface Generation

This paper describes a featurized functional dependency corpus automatically derived from the Penn Treebank. Each word in the corpus is associated with over three dozen features describing the functional syntactic structure of a sentence as well as some shallow morphology. The corpus was created for use in probabilistic surface generation, but could also be useful as a resource for the study of English and the development of other NLP applications.
FIR Filter for Adaptive Equalization in PRML Read Channels

A novel design of FIR filter for adaptive equalization in PRML read channels is presented. Two aspects of a design are considered: architecture level and implementation. The realization of this FIR structure introduces new architectural solutions. Those solutions are exploiting beneficial properties of both conventional FIR architectures, which allows for low computation latency at high operating frequencies, and ease of trading between parallel and pipelined structure. The implementation of this FIR structure uses the channel noise property knowledge to determine acceptable level of truncation/rounding and applies optimal automated special-purpose multiplication method to further minimize overall latency of the filter.
Naive Bayes as a Satis cing Model

We report on an empirical study of supervised learning algorithms that induce models to resolve the meaning of ambiguous words in text. We nd that the Naive Bayesian classi er is as accurate as several more sophisticated methods. This is a surprising result since Naive Bayes makes simplifying assumptions about disambiguation that are not realistic. However, our results correspond to a growing body of evidence that Naive Bayes acts as a satis cing model in a wide range of domains. We suggest that bias variance decompositions of classi cation error can be used to identify and develop satis cing models.
Extracting Semantic Entities and Events from Sports Tweets

Large volumes of user-generated content on practically every major issue and event are being created on the microblogging site Twitter. This content can be combined and processed to detect events, entities and popular moods to feed various knowledge- intensive practical applications. On the downside, these content items are very noisy and highly informal, making it difficult to extract sense out of the stream. In this paper, we exploit various approaches to detect the named entities and significant micro-events from users' tweets during a live sports event. Here we describe how combining linguistic features with background knowledge and the use of Twitter- specific features can achieve high, precise detection results (f-measure = 87%) in different datasets. A study was conducted on tweets from cricket matches in the ICC World Cup in order to augment the event- related non-textual media with collective intelligence.
Using Semantic Graphs and Word Sense Disambiguation Techniques to Improve Text Summarization

espanolEn este trabajo se presenta un metodo para la generacion automatica de resumenes basado en grafos semanticos. El sistema utiliza conceptos y relaciones de WordNet para construir un grafo que representa el documento, asi como un algoritmo de clustering basado en la conectividad para descubrir los distintos temas tratados en el. La seleccion de oraciones para el resumen se realiza en funcion de la presencia en las oraciones de los conceptos mas representativos del documento. Los experimentos realizados demuestran que el enfoque propuesto obtiene resultados significativamente mejores que otros sistemas evaluados bajo las mismas condiciones experimentales. Asimismo, el sistema puede ser facilmente adaptado para trabajar con documentos de diferentes dominios, sin mas que modificar la base de conocimiento y el metodo para identificar conceptos en el texto. Finalmente, este trabajo tambien estudia el efecto de la ambiguedad lexica en la generacion de resumenes. EnglishThis paper presents a semantic graph-based method for extractive summarization. The summarizer uses WordNet concepts and relations to produce a semantic graph that represents the document, and a degree-based clustering algorithm is used to discover different themes or topics within the text. The selection of sentences for the summary is based on the presence in them of the most representative concepts for each topic. The method has proven to be an efficient approach to the identification of salient concepts and topics in free text. In a test on the DUC data for single document summarization, our system achieves significantly better results than previous approaches based on terms and mere syntactic information. Besides, the system can be easily ported to other domains, as it only requires modifying the knowledge base and the method for concept annotation. In addition, we address the problem of word ambiguity in semantic approaches to automatic summarization.