Miracle-dz/UniFAR-FTUs huggingface dataset:
Left Atrium in Heart Failure With Preserved Ejection Fraction: Structure, Function, and Significance

Cardiac remodeling is a fundamental part of the heart failure (HF) syndrome, representing a common response to various pathological stimuli that result in changes in the structural and functional properties of the heart. To date, most studies in HF have focused on ventricular remodeling, and much less emphasis has been placed on atrial structural and functional changes. Specifically, in the context of HF with preserved ejection fraction (HFpEF), more attention has recently been placed on the left atrial (LA) remodeling, which is now considered a potential therapeutic target and an end point for evaluation of novel therapies. In this review, we discuss the pathophysiologic and clinical implication of LA remodeling in HFpEF. Left atrium is a thin-walled structure located in the inflow path from the pulmonary veins to the left ventricle (LV) and is characterized by (a) main body with smooth walls that embryologically is developed from the outgrowth of the pulmonary veins and (b) by a finger-like trabeculated appendage, which is a remnant of the original embryonic left atrium.1 Distribution of atrial myocyte fibers is highly variable, but some components are relatively constant. In particular, the Bachmann’s bundle is the most superficial group of circumferential myofibers located close to the atrioventricular groove. In this bundle, the electric conduction from right to LA preferentially occurs. Other myocardial longitudinal fibres are likely responsible for upward motion of mitral annulus during atrial contraction. ### Mechanical Function The mechanical function of LA is usually defined by 3 phases of LA volume variations during the cardiac cycle. The reservoir phase takes place during ventricular systole when the LA collects blood coming from the pulmonary veins. This phase is mechanistically determined by LA relaxation and by LV contraction, which moves the mitral annulus toward the apex, resulting in increased LA volume.2 Atrial compliance allows chamber volume …
Normal Gentzen Deductions in the Classical Case

I define the notion of normality for deductions in a Gentzen system for the classical case; I prove the normalization theorem for this notion and I build two direct maps between normal Gentzen deductions and natural deductions in ∗-normal form, i.e., natural deductions in normal form that also satisfy other conditions. I give the proof of the “∗-normalization theorem”, i.e. I give a procedure for transforming a normal deduction of →Nc into a unique deduction in ∗-normal form.
Information Extraction from HTML: Application of a General Machine Learning Approach

Because the World Wide Web consists primarily of text, information extraction is central to any effort that would use the Web as a resource for knowledge discovery. We show how information extraction can be cast as a standard machine learning problem, and argue for the suitability of relational learning in solving it. The implementation of a general-purpose relational learner for information extraction, SRV, is described. In contrast with earlier learning systems for information extraction, SRV makes no assumptions about document structure and the kinds of information available for use in learning extraction patterns. Instead, structural and other information is supplied as input in the form of an extensible token-oriented feature set. We demonstrate the effectiveness of this approach by adapting SRV for use in learning extraction rules for a domain consisting of university course and research project pages sampled from the Web. Making SRV Web-ready only involves adding several simple HTML-specific features to its basic feature set.
Handbook of Research on P2P and Grid Systems for Service-oriented Computing: Models, Methodologies a

The Handbook of Research on P2P and Grid Systems for Service-Oriented Computing: Models, Methodologies, and Applications addresses the need for peer-to-peer computing and grid paradigms in delivering efficient service-oriented computing. This critical mass of the most sought after research serves as a collection of chapters facilitating a broad understanding of the subject matter useful to researchers and doctoral students working specifically in the deployment, implementation, and study of related topics including distributed computing, software engineering, Web services, and modeling of business processes.
Experimental evaluation of adaptive and robust schemes for robot manipulator control

Adaptive and robust control schemes are compared in tracking control of a robot manipulator. In adaptive control, we classify the adaptive control laws into three types and then investigate their tracking performances by experiment. In robust control, a two degree of freedom controller is examined. We demonstrate its strong disturbance rejection performance and robustness to parameter variation. Finally, we consider the advantages of both of the control schemes.
Undersampled MR Image Reconstruction with Data-Driven Tight Frame

Undersampled magnetic resonance image reconstruction employing sparsity regularization has fascinated many researchers in recent years under the support of compressed sensing theory. Nevertheless, most existing sparsity-regularized reconstruction methods either lack adaptability to capture the structure information or suffer from high computational load. With the aim of further improving image reconstruction accuracy without introducing too much computation, this paper proposes a data-driven tight frame magnetic image reconstruction (DDTF-MRI) method. By taking advantage of the efficiency and effectiveness of data-driven tight frame, DDTF-MRI trains an adaptive tight frame to sparsify the to-be-reconstructed MR image. Furthermore, a two-level Bregman iteration algorithm has been developed to solve the proposed model. The proposed method has been compared to two state-of-the-art methods on four datasets and encouraging performances have been achieved by DDTF-MRI.
Gesture as a predictor of language development in infants at high risk for autism spectrum disorders

In typically developing children, gesture use predates and predicts changes in language. Because language development is often delayed in later-born siblings of children with autism spectrum disorders (ASD) (who are at heightened biological risk for the disorder; heightened risk infants: HR), even those who are not eventually diagnosed with ASD, gesture may be one of the earliest indicators of later delays. To examine the pattern of gesture use and language development in HR infants, gesture referents for HR infants and low risk (LR) comparison infants were coded at 14 and 18 month home visits. HR infants who went on to receive either a language delay (LD) or ASD diagnosis exhibited less frequent gesture use and used gesture to indicate a smaller variety of referents than their typically developing peers at both 14 and 18 months. In comparison to LR infants, HR infants who went on to receive LD or ASD diagnoses also exhibited smaller increases in gesture use from 14 to 18 months. While there was a significant positive correlation between gesture frequency at 14 months and vocabulary size at 18 months for the HR group, HR infants that received eventual LD or ASD diagnoses converted a smaller proportion of gesture referents to words in later vocabulary than did LR infants. Taken together, these results suggest that early gesture use and its relationship to later language development differentiates HR infants who receive later LD or ASD diagnoses from typically developing infants, indicating that gesture may have the potential to be used as marker of language delays prior to the onset of speech.
Much More Social Studies through Children's Literature: A Collaborative Approach. Through Children's Literature.

Much More Social Studies Through Children's Literature: A . Sun, 12 May 2019 15:25:00 GMT "A participatory approach to elementary social studies teaching. Quality children's literature is the focal point for the hands-on, minds-on experiences that are presented in the 62 units linked to national standards. Much More Social Studies through Children's Literature: A . Sun, 05 May 2019 21:03:00 GMT The author also provides practical guidelines for collaborative ventures with school librarians, tips for integrating literature across the curriculum, lists of relevant web sites useful in social studies education, and an up-to-date section of annotated bibliographies of the best in children's social studies literature. All titles are linked to national social studies standards. A chapter on . www.newist. org Mon, 06 May 2019 21:23:00 GMT www.newist. org
Virtual Reality Simulation in Acquiring and Differentiating Basic Ophthalmic Microsurgical Skills

Objective: A virtual reality (VR) surgical simulator (EyeSi ophthalmosurgical simulator: VRMagic, Mannheim, Germany) was evaluated as a part-task training platform for differentiating and developing basic ophthalmic microsurgical skills. Methods: Surgical novice performance (residents, interns, and nonmicrosurgical ophthalmic staff) was compared with surgical expert performance (practicing ophthalmic microsurgeons) on a basic navigational microdexterity module provided with the EyeSi simulator. Results: Expert surgeons showed a greater initial facility with all microsurgical tasks. With repeated practice, novice surgeons showed sequential improvement in all performance scores, approaching but not equaling expert performance. Conclusion: VR simulator performance can be used as a gated, quantifiable performance goal to expert-level benchmarks. The EyeSi is a valid part-task training platform that may help develop novice surgeon dexterity to expert surgeon levels.
Extraction of Flat and Nested Data Records from Web Pages

This paper deals with studies the problem of identification and extraction of flat and nested data records from a given web page. With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, it is useful to mine such data regions and data records in order to extract information from such web pages to provide value-added services. Currently available automatic techniques to mine data regions and data records from web pages are still unsatisfactory because of their poor performance. In this paper, we propose a new method to identify and extract the data records from the web pages automatically. Given a page, the proposed technique first identifies the data region based on the visual clue information. It then extracts each record from the data region and identifies it whether it is a flat or nested record based on visual information -- the area covered by and the number of data items present in each record. The experimental results show that the proposed technique is effective and better than existing techniques.
Relational learning techniques for natural language information extraction

The recent growth of online information available in the form of natural language documents creates a greater need for computing systems with the ability to process those documents to simplify access to the information. One type of processing appropriate for many tasks is information extraction, a type of text skimming that retrieves speci c types of information from text. Although information extraction systems have existed for two decades, these systems have generally been built by hand and contain domain speci c information, making them di cult to port to other domains. A few researchers have begun to apply machine learning to information extraction tasks, but most of this work has involved applying learning to pieces of a much larger system. This paper presents a novel rule representation speci c to natural language and a learning system, Rapier, which learns information extraction rules. Rapier takes pairs of documents and lled templates indicating the information to be extracted and learns patterns to extract llers for the slots in the template. This proposal presents initial results on a small corpus of computer-related job postings with a preliminary version of Rapier. Future research will involve several enhancements to Rapier as well as more thorough testing on several domains and extension to additional natural language processing tasks. We intend to extend the rule representation and algorithm to allow for more types of constraints than are currently supported. We also plan to incorporate active learning, or sample selection, methods, speci cally query by committee, into Rapier. These methods have the potential to substantially reduce the amount of annotation required. We will explore the issue of distinguishing relevant and irrelevant messages, since currently Rapier only extracts from the any messages given to it, assuming that all are relevant. We also intend to run much larger tests with Rapier on multiple domains including the terrorism domain from the third and fourth Message Uncderstanding Conferences, which will allow comparison against other systems. Finally, we plan to demonstrate the generality of Rapier`s representation and algorithm by applying it to other natural language processing tasks such as word sense disambiguation.
A framework for fusion methods and rendering techniques of multimodal volume data

Many different direct volume rendering methods have been developed to visualize 3D scalar fields on uniform rectilinear grids. However, little work has been done on rendering simultaneously various properties of the same 3D region measured with different registration devices or at different instants of time. The demand for this type of visualization is rapidly increasing in scientific applications such as medicine in which the visual integration of multiple modalities allows a better comprehension of the anatomy and a perception of its relationships with activity. This paper presents different strategies of direct multimodal volume rendering (DMVR). It is restricted to voxel models with a known 3D rigid alignment transformation. The paper evaluates at which steps of the rendering pipeline the data fusion must be realized in order to accomplish the desired visual integration and to provide fast re‐renders when some fusion parameters are modified. In addition, it analyses how existing monomodal visualization algorithms can be extended to multiple datasets and it compares their efficiency and their computational cost. Copyright © 2004 John Wiley & Sons, Ltd.
Characterization of Dynamic SRAM Stability in 45 nm CMOS

Optimization of SRAM yield using dynamic stability metrics has been evaluated in the past to ensure continued scaling of bitcell size and supply voltage in future technology nodes. Various dynamic stability metrics have been proposed but they have not been used in practical failure analysis and compared with conventional static margins. This work compares static and dynamic metrics to identify expected correlations. A dynamic stability characterization architecture using pulsed word-lines is implemented in 45 nm CMOS to identify sources of variability, and their impact on SRAM stability. Static read margins were observed to overestimate failures by 10-100 X while static write margins failed to predict outliers in critical writeability. Critical writeability was demonstrated to exhibit an enhanced sensitivity to process variations, random telegraph noise (RTN), and negative bias temperature instability (NBTI), compared to static write margins.
Swarm Intelligence: Ant-Based Robot Path Planning

In this paper we proposed a novel algorithm Ant-based Robot Path Planning (ARPP) based on Ant Colony System (ACS) to mimic a swarm of ants to find the globally optimal path for autonomous mobile robots. Visibility graph was used as both the roadmap and construction graph in ARPP. Although the near-optimums were readily available by ARPP, it is hard to find the optimality; therefore we proposed the special ARPP (S-ARPP) algorithm as its supplement. Experimental results show S-ARPP outperforms ARPP for higher qualities of the global-best path it found, and a flexible trade-off between satisfactory solutions and the number of iterations was also easily available to meet the certain needs.
Reactive Oxygen Species Scavenging by Catalase Is Important for Female Lutzomyia longipalpis Fecundity and Mortality

The phlebotomine sand fly Lutzomyia longipalpis is the most important vector of American visceral leishmaniasis (AVL), the disseminated and most serious form of the disease in Central and South America. In the natural environment, most female L. longipalpis are thought to survive for less than 10 days and will feed on blood only once or twice during their lifetime. Successful transmission of parasites occurs when a Leishmania-infected female sand fly feeds on a new host. Knowledge of factors affecting sand fly longevity that lead to a reduction in lifespan could result in a decrease in parasite transmission. Catalase has been found to play a major role in survival and fecundity in many insect species. It is a strong antioxidant enzyme that breaks down toxic reactive oxygen species (ROS). Ovarian catalase was found to accumulate in the developing sand fly oocyte from 12 to 48 hours after blood feeding. Catalase expression in ovaries as well as oocyte numbers was found to decrease with age. This reduction was not found in flies when fed on the antioxidant ascorbic acid in the sugar meal, a condition that increased mortality and activation of the prophenoloxidase cascade. RNA interference was used to silence catalase gene expression in female Lu. longipalpis. Depletion of catalase led to a significant increase of mortality and a reduction in the number of developing oocytes produced after blood feeding. These results demonstrate the central role that catalase and ROS play in the longevity and fecundity of phlebotomine sand flies.
28nm FDSOI technology platform for high-speed low-voltage digital applications

For the first time, a full platform using FDSOI technology is presented. This work demonstrates 32% and 84% speed boost at 1.0V and 0.6V respectively, without adding process complexity compared to standard bulk technology. We show how memory access time can be significantly reduced thanks to high Iread, by keeping competitive leakage values. Yield of ~14Mb SRAM cells is demonstrated, allowing to measure for the first time Vmin of SRAM arrays.
Out-of-the-box strategy for Rich Speech Retrieval MediaEval 2011

Evaluation tracks oer valuable opportunities to measure scientic and technological advances. Spinque approaches challenges as the MediaEval Rich Speech Recognition task with the additional goal of developing solutions that can easily transferred from academic labs to industry. The system used during this evaluation was obtained with minimal eort and no manual optimisation and yet it provides a reasonably good baseline to improve upon. More importantly, it is by nature an extensible approach, based on the concept of declarative search strategies, rather than an ad-hoc search system.
Brain-derived Neurotrophic Factor Promotes Survival and Chemoprotection of Human Neuroblastoma Cells*

Brain-derived neurotrophic factor (BDNF) promotes neuronal survival and protection against neuronal damage. We addressed whether BDNF might promote survival and chemoprotection in neuroblastoma (NB) using a drug-sensitive human NB cell line. All-trans-retinoic acid (ATRA) induces a striking phenotypic differentiation of NB1643 cells, and exogenous BDNF treatment promotes survival of these differentiated cells. ATRA induces TRKB expression, and exogenous BDNF stimulates both autophosphorylation of TRKB and induction of the immediate early gene, FOS, in these cells.BDNF mRNA is expressed in NB1643 cells. Because the time course of TRKB induction closely parallels phenotypic differentiation of these cells, it seems probable that ATRA induces differentiation of NB1643 cells by establishing an autocrine loop involving BDNF and TRKB. Exogenous BDNF treatment resulted in a further increase in neurite outgrowth, which again suggests that an autocrine loop is involved in differentiation of NB1643 cells in response to ATRA. We then tested whether BDNF might afford drug resistance in NB and found that BDNF does indeed protect in this NB model against cisplatin, a DNA-damaging agent actually used in the treatment of NB.
Interneurons Differentially Contribute to Spontaneous Network Activity in the Developing Hippocampus Dependent on Their Embryonic Lineage

Spontaneously generated network activity is a hallmark of developing neural circuits, and plays an important role in the formation of synaptic connections. In the rodent hippocampus, this activity is observed in vitro as giant depolarizing potentials (GDPs) during the first postnatal week. Interneurons importantly contribute to GDPs, due to the depolarizing actions of GABA early in development. While they are highly diverse, cortical interneurons can be segregated into two distinct groups based on their embryonic lineage from either the medial or caudal ganglionic eminences (MGE and CGE). There is evidence suggesting CGE-derived interneurons are important for GDP generation; however, their contribution relative to those from the MGE has never been directly tested. Here, we optogenetically inhibited either MGE- or CGE-derived interneurons in a region-specific manner in mouse neonatal hippocampus in vitro. In CA1, where interneurons are the primary source of recurrent excitation, we found that those from the MGE strongly and preferentially contributed to GDP generation. Furthermore, in dual whole-cell patch recordings in neonatal CA1, MGE interneurons formed synaptic connections to and from neighboring pyramidal cells at a much higher rate than those from the CGE. These MGE interneurons were commonly perisomatic targeting, in contrast to those from the CGE, which were dendrite targeting. Finally, inhibiting MGE interneurons in CA1 suppressed GDPs in CA3 and vice versa; conversely, they could also trigger GDPs in CA1 that propagated to CA3 and vice versa. Our data demonstrate a key role for MGE-derived interneurons in both generating and coordinating GDPs across the hippocampus. SIGNIFICANCE STATEMENT During nervous system development, immature circuits internally generate rhythmic patterns of electrical activity that promote the establishment of synaptic connections. Immature interneurons are excitatory rather than inhibitory and actively contribute to the generation of these spontaneous network events, referred to as giant depolarizing potentials (GDPs) in the hippocampus. Interneurons can be generally separated into two distinct groups based on their origin in the embryo from the medial or caudal ganglionic eminences (MGE and CGE). Here we show that MGE interneurons play a dominant role in generating GDPs compared with their CGE counterparts. They accomplish this due to their high synaptic connectivity within the local circuitry. Finally, they can control network activity across large regions of the developing hippocampus.