Miracle-dz/UniFAR-FTUs huggingface dataset:
The Case Against Specialized Visual-Spatial Short-Term Memory

The dominant paradigm for understanding working memory, or the combination of the perceptual, attentional, and mnemonic processes needed for thinking, subdivides short-term memory (STM) according to whether memoranda are encoded in aural-verbal or visual formats. This traditional dissociation has been supported by examples of neuropsychological patients who seem to selectively lack STM for either aural-verbal, visual, or spatial memoranda, and by experimental research using dual-task methods. Though this evidence is the foundation of assumptions of modular STM systems, the case it makes for a specialized visual STM system is surprisingly weak. I identify the key evidence supporting a distinct verbal STM system—patients with apparent selective damage to verbal STM and the resilience of verbal short-term memories to general dual-task interference—and apply these benchmarks to neuropsychological and experimental investigations of visual-spatial STM. Contrary to the evidence on verbal STM, patients with apparent visual or spatial STM deficits tend to experience a wide range of additional deficits, making it difficult to conclude that a distinct short-term store was damaged. Consistently with this, a meta-analysis of dual-task visual-spatial STM research shows that robust dual-task costs are consistently observed regardless of the domain or sensory code of the secondary task. Together, this evidence suggests that positing a specialized visual STM system is not necessary.
Anatomical Correlates of Uncontrollable Laughter With Unilateral Subthalamic Deep Brain Stimulation in Parkinson’s Disease

Introduction Subthalamic nucleus deep brain stimulation (STN-DBS) is a well-established treatment for the management of motor complications in Parkinson’s disease. Uncontrollable laughter has been reported as a rare side effect of STN stimulation. The precise mechanism responsible for this unique phenomenon remains unclear. We examined in detail the DBS electrode position and stimulation parameters in two patients with uncontrollable laughter during programming after STN-DBS surgery and illustrated the anatomical correlates of the acute mood changes with STN stimulation. Case report Unilateral STN-DBS induced uncontrollable laughter with activation of the most ventral contacts in both patients. However, the location of the electrodes responsible for this adverse effect differed between the patients. In the first patient, the DBS lead was placed more inferiorly and medially within the STN. In the second patient, the DBS lead was implanted more anteriorly and inferiorly than initially planned at the level of the substantia nigra reticulata (SNr). Conclusion Unilateral STN-DBS can induce acute uncontrollable laughter with activation of electrodes located more anterior, medial, and inferior in relationship with the standard stereotactic STN target. We suggest that simulation of ventral and medial STN, surrounding limbic structures or the SNr, is the most plausible anatomical substrate responsible for this acute mood and behavioral change. Our findings provide insight into the complex functional neuroanatomical relationship of the STN and adjacent structures important for mood and behavior. DBS programming with more dorsal and lateral contacts within the STN should be entertained to minimize the emotional side effects.
Paediatric Hodgkin Lymphoma and Radiation Therapy: 3DCRT vs VMAT. A Case Report

Hodgkin Lymphoma (HL) is one of the most common cancers in young adult. Early stage Hodgkin disease has a good prognosis and high survival rates with modern therapeutic approaches. Clinical management of early stage HL involves two therapeutic options: one is combined modality therapy with abbreviated chemotherapy plus involved field radiation therapy (IFRT) and the other is chemotherapy alone. Combined modality ensures high cure rates but exposes young HL survivors to short-term and long-term complications such as cardiovascular and pulmonary disease and second malignancies especially in case of mediastinal involvement. Radiation therapy is crucial in the management of HL and has changed over the last decades. The introduction of new irradiation techniques such as Intensity modulated Radiation Therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT), the delivery of lower doses regimens and the reduction of field sizes from extended field radiotherapy (EFRT ) to involved field RT (IFRT) and involved –nodal RT (INRT) allow to choose the most effective and safest technique. We present a case report of a paediatric HL, stage II bulky mediastinal, already treated with different chemotherapy regimens containing bleomicyn and candidate to autologous transplantation in order to demonstrate which radiation technique is more effective and safer for lungs between 3D conformational therapy (3DCRT) and VMAT. VMAT seems safer for better lung sparing.
A Robust Controller for a Class of Front-end Buck-boost High Power Factor Rectifiers

This paper presents the application of variable structure control (VSC) to a high power factor correction SEPIC converter. VSC provides the advantages of simplicity of implementation and robustness leading to having an output, which is independent of input voltage, circuit parameters and/or output load. This controller is used to regulate both the output voltage and the input current waveform in order to get a near unity power factor via the selection of a proper switching function. An observer with adaptive parameter estimation is also designed to achieve current sensorless operation of the controller, and thus only two voltage measurements are needed. This leads to a smaller size and higher operational reliability of the converter. Analysis of the proposed controller and simulation results are reported. The results show a near unity power factor and a regulated 48 V output for a universal input voltage (90-260 V) and a 500 W output power
Using degree constrained gravity null-models to understand the structure of journeys' networks in bicycle sharing systems

Bicycle Sharing Systems are now ubiquitous in large cities around the world. In most of these systems, journeys' data can be extracted , providing rich information to better understand it. Recent works have used network based-machine learning, and in particular space-corrected node clustering, to analyse such datasets. In this paper, we show that spatial-null models used in previous methods have a systematic bias, and we propose a degree-contrained null-model to improve the results. We finally apply the proposed method on the BSS of a city.
Analysis of Social web data : A Review

Today social networking websites has evolved to become a source of various kind of information. This is because of the nature of these websites on which peoples comments and post their opinions on different types of topics i.e. they express positive or negative sentiments about any product that they use in daily life, complains and current issues etc. These sentiments help in getting information about various current trends and can be used further in deciding usefulness of some tasks, products and themes. Also social web data like twitter has a large amount of data that people post so it’s become important to work on efficient intelligent systems that can do data refinement, analysis of tasks intelligently and efficiently. This paper presents a comprehensive overview of past and current research on twitter sentiment analysis and identifies outstanding research questions for the future. Keywords— TASC (Topic Adaptive Sentiment Classification), Query term, RA (Rated Aspect), ESLAM (Emoticon Smoothed Language Model), LARA (Latent Aspect Rating Analysis)
In-situ X-ray Diffraction of Corrosion Products Formed on Iron Surfaces

In-situ X-ray diffraction measurements by synchrotron radiation and conventional X-ray source have been carried out for identifying constituent species of corrosion products, which were formed on the surface of a pure iron and an iron-5 mass% nickel alloy by reaction with aqueous solutions containing sodium chloride or sodium sulfate. A cell has been prepared for in-situ diffraction measurements of the corrosion products. Diffraction patterns from the corrosion products showed that major constituent species of the corrosion products was γ-FeOOH, and the fraction of minor species of α-FeOOH and Fe3O4 in the corrosion products depended on corrosion conditions, such as wetting and drying processes, anion species in aqueous solutions and nickel in the sample. An oxide scale thermally formed on the iron surface was also found to affect the formation of corrosion products.
PointProNets: Consolidation of Point Clouds with Convolutional Neural Networks

With the widespread use of 3D acquisition devices, there is an increasing need of consolidating captured noisy and sparse point cloud data for accurate representation of the underlying structures. There are numerous algorithms that rely on a variety of assumptions such as local smoothness to tackle this ill‐posed problem. However, such priors lead to loss of important features and geometric detail. Instead, we propose a novel data‐driven approach for point cloud consolidation via a convolutional neural network based technique. Our method takes a sparse and noisy point cloud as input, and produces a dense point cloud accurately representing the underlying surface by resolving ambiguities in geometry. The resulting point set can then be used to reconstruct accurate manifold surfaces and estimate surface properties. To achieve this, we propose a generative neural network architecture that can input and output point clouds, unlocking a powerful set of tools from the deep learning literature. We use this architecture to apply convolutional neural networks to local patches of geometry for high quality and efficient point cloud consolidation. This results in significantly more accurate surfaces, as we illustrate with a diversity of examples and comparisons to the state‐of‐the‐art.
Diverse involvement of EZH 2 in cancer epigenetics

EZH2 is the catalytic subunit of Polycomb Repressor Complex 2 (PRC2) which catalyzes methylation of histone H3 at lysine 27 (H3K27me) and mediates gene silencing of target genes via local chromatin reorganization. Numerous evidences show that EZH2 plays a critical role in cancer initiation, progression and metastasis, as well as in cancer stem cell biology. Indeed, EZH2 dysregulation alters gene expression programs in various cancer types. The molecular mechanisms responsible for EZH2 alteration appear to be diverse and depending on the type of cancer. Furthermore, accumulating evidences indicate that EZH2 could also act as a PRC2-independent transcriptional activator in cancer. In this review, we address the current understanding of the oncogenic role of EZH2, including the mechanisms of EZH2 dysregulation in cancer and progresses in therapeutic approaches targeting EZH2.
Extensional flow of nematic liquid crystal with an applied electric field

Systematic asymptotic methods are used to formulate a model for the extensional flow of a thin sheet of nematic liquid crystal. With no external body forces applied, the model is found to be equivalent to the so-called Trouton model for Newtonian sheets (and fibres), albeit with a modified ‘Trouton ratio’. However, with a symmetry-breaking electric field gradient applied, behaviour deviates from the Newtonian case, and the sheet can undergo finite-time breakup if a suitable destabilizing field is applied. Some simple exact solutions are presented to illustrate the results in certain idealized limits, as well as sample numerical results to the full model equations.
Examples of Sustainable Consumption: Review, Classification and Analysis

In this report, we gather what could be seen as examples of sustainable consumption. The intention of the report is to help policy makers identify promising policy measures and strategies to reduce environmental and social impacts. We also would like to point to promising research directed at developing policies, tools, and evaluation methods for sustainable consumption. In order to fruitfully organize and present sustainable consumption examples, we group and classify these examples. A number of prior issues have to be addressed, most urgently the definition of sustainable consumption. We define sustainable consumption through a framework that can be used to analyse the social and environmental impacts of household consumption. In this framework, measures directed toward consumption are distinguished from those targeting production.A more in-depth study of examples of sustainable consumption could yield insights in how these examples work, how well they are accepted, and how/to what degree they can be replicated. In the appendix, we proposed a detailed study to develop social science methods to evaluate acceptance and take into account the rebound effect.
OpenLensFlare: an open-source, lens flare designing and rendering framework

Lens flare rendering in computer games has always been lacking. While physically motivated solutions based on real camera systems exist, their inherent complexity makes them inappropriate for widespread use. Developers are not trained to work with these complicated imaging systems, and even if they were, artists and designers prefer intuitive parameters over these complicated optical system descriptions. More support is needed to start adopting to these advanced models, and to show that with an appropriate tool the situation can be vastly improved. This paper describes OpenLensFlare, an open-source C++ framework for rendering convincing physically-based lens flare effects. Additionally, a supporting optical system editor is also provided, which is capable of producing and visualizing optical systems and showing an example usage of the run-time library. Together, these two systems can be used to replace the existing naive algorithms, with small effort and low integration complexity.
Fibrolytic Rumen Bacteria: Their Ecology and Functions

Among rumen microbes, bacteria play important roles in the biological degradation of plant fiber due to their large biomass and high activity. To maximize the utilization of fiber components such as cellulose and hemicellulose by ruminant animals, the ecology and functions of rumen bacteria should be understood in detail. Recent genome sequencing analyses of representative fibrolytic bacterial species revealed that the number and variety of enzymes for plant fiber digestion clearly differ between Fibrobacter succinogenes and Ruminococcus flavefaciens. Therefore, the mechanism of plant fiber digestion is also thought to differ between these two species. Ecology of individual fibrolytic bacterial species has been investigated using pure cultures and electron microscopy. Recent advances in molecular biology techniques complement the disadvantages of conventional techniques and allow accurate evaluation of the ecology of specific bacteria in mixed culture, even in situ and in vivo. Molecular monitoring of fibrolytic bacterial species in the rumen indicated the predominance of F. succinogenes. Nutritive interactions between fibrolytic and non-fibrolytic bacteria are important in maintaining and promoting fibrolytic activity, mainly in terms of crossfeeding of metabolites. Recent 16S rDNA-based analyses suggest that presently recognized fibrolytic species such as F. succinogenes and two Ruminococcus species with fibrolytic activity may represent only a small proportion of the total fibrolytic population and that uncultured bacteria may be responsible for fiber digestion in the rumen. Therefore, characterization of these unidentified bacteria is important to fully understand the physiology and ecology of fiber digestion. To achieve this, a combination of conventional and modern techniques could be useful.
Isolated Ovarian Metastasis in a Woman with Prior History of Superficial Bladder Cancer

C l i n M e d International Library Citation: Mahoney K, Gupta M, Patnaik A (2015) Isolated Ovarian Metastasis in a Woman with Prior History of Superficial Bladder Cancer. Clin Med Rev Case Rep 2:064. doi. org/10.23937/2378-3656/1410064 Received: March 16, 2015: Accepted: October 09, 2015: Published: October 12, 2015 Copyright: © 2015 Mahoney K. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Clinical Medical Reviews and Case Reports ISSN: 2378-3656 Volume 2 | Issue 10 DOI: 10.23937/2378-3656/1410064
Reinforcement Learning for Heterogeneous Teams with PALO Bounds

We introduce reinforcement learning for heterogeneous teams in which rewards for an agent are additively factored into local costs, stimuli unique to each agent, and global rewards, those shared by all agents in the domain. Motivating domains include coordination of varied robotic platforms, which incur different costs for the same action, but share an overall goal. We present two templates for learning in this setting with factored rewards: a generalization of Perkins' Monte Carlo exploring starts for POMDPs to canonical MPOMDPs, with a single policy mapping joint observations of all agents to joint actions (MCES-MP); and another with each agent individually mapping joint observations to their own action (MCES-FMP). We use probably approximately local optimal (PALO) bounds to analyze sample complexity, instantiating these templates to PALO learning. We promote sample efficiency by including a policy space pruning technique, and evaluate the approaches on three domains of heterogeneous agents demonstrating that MCES-FMP yields improved policies in less samples compared to MCES-MP and a previous benchmark.
A unified multi-soft-body dynamic model for underwater soft robots

A unified formulation that accounts for the dynamics of a general class of aquatic multi-body, soft-structured robots is presented. The formulation is based on a Cosserat formalism where the description of the ensemble of geometrical entities, such as shells and beams, gives rise to a multi-soft-body system capable of simulating both manipulation and locomotion. Conceived as an advanced tool for a priori hardware development, n-degree-of-freedom dynamics analysis and control design of underwater, soft, multi-body, vehicles, the model is validated against aquatic locomotion experiments of an octopus-inspired soft unmanned underwater robot. Upon validation, the general applicability of the model is demonstrated by predicting the self-propulsion dynamics of a diverse range of new viable combinations of multi-soft-body aquatic system.
Detection for Improving Coreference Resolution in Russian Texts : A Machine Learning Approach

Coreference resolution task is a well-known NLP application that was proven helpful for all high-level NLP applications: machine translation, summarization, and others. Mention detection is the sub-task of detecting the discourse status of each noun phrase, classifying it as a discourse-new, singleton (mentioned only once) or discourse-old occurrence. It has been shown that this task applied to a coreference resolution system may increase its overall performance. So, we decided to adapt current approaches for English language into Russian. We present some quality results of experiments regarding classifiers for mention detection and their application into the coreference resolution task in Russian languages.
Two Remarks on Eventown and Oddtown Problems

A family $\mathcal A$ of subsets of an $n$-element set is called an eventown (resp., oddtown) if all its sets have even (resp., odd) size and all pairwise intersections have even size. Using tools from linear algebra, it was shown by Berlekamp and Graver that the maximum size of an eventown is $2^{\left\lfloor n/2\right\rfloor}$. On the other hand (somewhat surprisingly), it was proven by Berlekamp that oddtowns have size at most $n$. Over the last four decades, many extensions of this even/oddtown problem have been studied. In this paper we present new results on two such extensions. First, extending a result of Vu, we show that a $k$-wise eventown (i.e., intersections of $k$ sets are even) has for $k \geq 3$ a unique extremal configuration and obtain a stability result for this problem. Next we improve some known bounds for the defect version of an $\ell$-oddtown problem. In this problem we consider sets of size $\not\equiv 0 \pmod \ell$ where $\ell$ is a prime number (not necessarily 2) and allow a few.
Discriminative boundary detection for model-based heart segmentation in CT images

Segmentation of organs in medical images can be successfully performed with deformable models. Most approaches combine a boundary detection step with some smoothness or shape constraint. An objective function for the model deformation is thus established from two terms: the first one attracts the surface model to the detected boundaries while the second one keeps the surface smooth or close to expected shapes. In this work, we assign locally varying boundary detection functions to all parts of the surface model. These functions combine an edge detector with local image analysis in order to accept or reject possible edge candidates. The goal is to optimize the discrimination between the wanted and misleading boundaries. We present a method to automatically learn from a representative set of 3D training images which features are optimal at each position of the surface model. The basic idea is to simulate the boundary detection for the given 3D images and to select those features that minimize the distance between the detected position and the desired object boundary. The approach is experimentally evaluated for the complex task of full-heart segmentation in CT images. A cyclic cross-evaluation on 25 cardiac CT images shows that the optimized feature training and selection enables robust, fully automatic heart segmentation with a mean error well below 1 mm. Comparing this approach to simpler training schemes that use the same basic formalism to accept or reject edges shows the importance of the discriminative optimization.
E-VIEW-alation – a Large-scale Evaluation Study of Association Measures for Collocation Identification

Statistical association measures (AM) play an important role in the automatic extraction of collocations and multiword expressions from corpora, but many parameters governing their performance are still poorly understood. Systematic evaluation studies have produced conflicting recommendations for an optimal AM, and little attention has been paid to other parameters such as the underlying corpus, the size of the co-occurrence context, or the application of a frequency threshold. Our paper presents the results of a large-scale evaluation study covering 13 corpora, eight context sizes, four frequency thresholds, and 20 AMs against two different gold standards of lexical collocations. While the optimal choice of an AM depends strongly on the particular gold standard used, other parameters prove much more robust: (i) small co-occurrence contexts are better than larger spans, and the best results are usually obtained from syntactic dependencies; (ii) corpus quality is more important than sheer size, but large Web corpora prove to be a valid substitute for the British National Corpus; (iii) frequency thresholds seem to be unnecessary in most situations, as the statistical AMs successfully weed out rare and unreliable candidates; (iv) there is little interaction between the choice of AM and the other parameters. In order to provide complete evidence for our observations to readers, we created an interactive Web-based application that allows users to manipulate all evaluation parameters and dynamically updates evaluation graphs and summaries.