Miracle-dz/UniFAR-FTUs huggingface dataset:
Lexical-Semantic Search Under Different Covert Verbal Fluency Tasks: An fMRI Study

Background: Verbal fluency is a measure of cognitive flexibility and word search strategies that is widely used to characterize impaired cognitive function. Despite the wealth of research on identifying and characterizing distinct aspects of verbal fluency, the anatomic and functional substrates of retrieval-related search and post-retrieval control processes still have not been fully elucidated. Methods: Twenty-one native English-speaking, healthy, right-handed, adult volunteers (mean age = 31 years; range = 21–45 years; 9 F) took part in a block-design functional Magnetic Resonance Imaging (fMRI) study of free recall, covert word generation tasks when guided by phonemic (P), semantic-category (C), and context-based fill-in–the-blank sentence completion (S) cues. General linear model (GLM), Independent Component Analysis (ICA), and psychophysiological interaction (PPI) were used to further characterize the neural substrate of verbal fluency as a function of retrieval cue type. Results: Common localized activations across P, C, and S tasks occurred in the bilateral superior and left inferior frontal gyrus, left anterior cingulate cortex, bilateral supplementary motor area (SMA), and left insula. Differential task activations were centered in the occipital, temporal and parietal regions as well as the thalamus and cerebellum. The context-based fluency task, i.e., the S task, elicited higher differential brain activity in a lateralized frontal-temporal network typically engaged in complex language processing. P and C tasks elicited activation in limited pathways mainly within the left frontal regions. ICA and PPI results of the S task suggested that brain regions distributed across both hemispheres, extending beyond classical language areas, are recruited for lexical-semantic access and retrieval during sentence completion. Conclusion: Study results support the hypothesis of overlapping, as well as distinct, neural networks for covert word generation when guided by different linguistic cues. The increased demand on word retrieval is met by the concurrent recruitment of classical as well as non-classical language-related brain regions forming a large cognitive neural network. The retrieval-related search and post-retrieval control processes that subserve verbal fluency, therefore, reverberates across distinct functional networks as determined by respective task demands.
From Opinion Lexicons to Sentiment Classification of Tweets and Vice Versa: A Transfer Learning Approach

Message-level and word-level polarity classification are two popular tasks in Twitter sentiment analysis. They have been commonly addressed by training supervised models from labelled data. The main limitation of these models is the high cost of data annotation. Transferring existing labels from a related problem domain is one possible solution for this problem. In this paper, we propose a simple model for transferring sentiment labels from words to tweets and vice versa by representing both tweets and words using feature vectors residing in the same feature space. Tweets are represented by standard NLP features such as unigrams and part-of-speech tags. Words are represented by averaging the vectors of the tweets in which they occur. We evaluate our approach in two transfer learning problems: 1) training a tweet-level polarity classifier from a polarity lexicon, and 2) inducing a polarity lexicon from a collection of polarity-annotated tweets. Our results show that the proposed approach can successfully classify words and tweets after transfer.
Mechanism of biosurfactant adsorption to oil/water interfaces from millisecond scale tensiometry measurements

Many biological molecules are by their nature amphiphilic and have the ability to act as surfactants, stabilizing interfaces between aqueous and immiscible oil phases. In this paper, we explore the adsorption kinetics of surfactin, a naturally occurring cyclic lipopeptide, at hexadecane/water interfaces and compare and contrast its adsorption behaviour with that of synthetic alkyl benzene sulfonate isomers, through direct measurements of changes in interfacial tension upon surfactant adsorption. We access millisecond time resolution in kinetic measurements by making use of droplet microfluidics to probe the interfacial tension of hexadecane droplets dispersed in a continuous water phase through monitoring their deformation when the droplets are exposed to shear flows in a microfluidic channel with regular corrugations. Our results reveal that surfactin rapidly adsorbs to the interface, thus the interfacial tension equilibrates within 300 ms, while the synthetic surfactants used undergo adsorption processes at an approximately one order of magnitude longer timescale. The approach presented may provide opportunities for understanding and modulating the adsorption mechanism of amphiphiles on a variety of interfaces in the context of life sciences and industrial applications.
Role of edaravone in managemant of septic peritonitis

Background and Aims: Sepsis is a complex rapidly progressive infectious disease that remain a major cause of morbidity and mortality in surgical patients and trauma victims. Edaravone a novel free radical scavenger was approved in 2001 in Japan for treatment of acute cerebral and myocardial infarction. Hence, in this work we attempt to evaluate its role in cases of septic peritonitis (SP). Material and Methods: This is a prospective randomized observer-blinded study carried out in surgical Intensive Care Unit (ICU) after approval by Hospital Ethical Committee. After admission to ICU patients were randomly divided into two groups of thirty patients each-Group (C): Control group managed according to the routine protocol of sepsis and Group (E): Edaravone treated SP managed according to the routine protocol of sepsis + edaravone at dose of 30 mg/12 h intravenous infusion for 2 weeks. All patients were monitored for invasive blood pressure, central venous pressure, heart rate, temperature, urine output, total fluid balance, and routine investigation. Blood sample was taken weekly for 2 weeks to measure the following parameters: Nuclear transcription factor kappa B activity (NFKB), mitogen-activated protein kinase (MAPK), heat shock protein 72 (HSP 72) and total antioxidant capacity (TAC). Results: There was significant decrease (P < 0.05) in serum level of NFKB, MAPK in Group E in comparison with Group C. While serum level of HSP 72 and TAC showed significant increase (P < 0.05) in Group E compared with Group C with better outcome. Conclusion: SP treatment with edaravone could significantly improve the inflammatory and oxidative states with better patient outcomes.
Learning the Reward Model of Dialogue POMDPs from Data

Spoken language communication between human and machines has become a challenge in research and technology. In particular, enabling the health care robots with spoken language interface is of great attention. Recently due to uncertainty characterizing dialogues, there has been interest for modelling the dialogue manager of spoken dialogue systems using Partially Observable Markov Decision Processes (POMDPs). In this context, we would like to learn the reward model of dialogue POMDPs from expert’s data. In a previous paper, we used an unsupervised learning method for learning the states, as well as the transition and observation functions of the dialogue POMDPs based on human-human dialogues. Continuing our objective of learning the components of dialogue POMDPs from data, here we introduce a novel inverse re-inforcement learning (IRL) algorithm for learning the reward function of the dialogue POMDP model. Based on the introduced method, and from an available corpus of data, we construct a dialogue POMDP. Then, the learned dialogue policies, based on the learned POMDP, are evaluated. Our empirical evaluation shows that the performance of the learned POMDP is higher than expert performance in non, low, and medium noise levels, but the high noise level. At the end, current limitations and future directions are addressed.
Tumor suppressor genes promote rhabdomyosarcoma progression in p53 heterozygous, HER-2/neu transgenic mice

Human sarcomas arise suddenly, thus preempting the study of preneoplastic and early neoplastic lesions. To explore the natural history of these tumors we studied male mice carrying a heterozygous deletion of p53 and an activated HER-2/neu transgene (BALB-p53Neu mice), that develop urethral rhabdomyosarcomas with nearly full penetrance and early onset (4 months of age). Among genes prominently upregulated in preneoplastic tissue, and more highly expressed in tumors, we found the insulin-like growth factor 2 (Igf2) and tumor suppressors, p19Arf and p21Cip1. In urethral tissues of male mice p53 was less expressed than in female mice, whereas HER-2/neu was more expressed, a combination not found in other skeletal muscles of the same mice that could contribute to the anatomic and sexual specificity of BALB-p53Neu rhabdomyosarcoma. Upregulation of p19Arf and p21Cip1 was additively determined by HER-2/neu activation and by p53 inactivation. Silencing of p19Arf or p21Cip1 in rhabdomyosarcoma cell lines can inhibit cell growth and motility, thus suggesting that these genes can contribute to growth autonomy and malignancy of tumor cells. In vivo injection of gene-silenced cells highlighted selective variations in organ-specific metastatic ability, indicating that overexpression of p19Arf and p21Cip1 controlled both tumor cell-intrinsic properties and microenvironmental interactions. The onset of pelvic rhabdomyosarcoma in BALB-p53Neu male mice is triggered by the coincidental overexpression of HER-2/neu and hypoexpression of the residual p53 allele, that foster p53 loss, Igf2 autocriny and overexpression of p19Arf and p21Cip1, a phenotype that could provide novel potential targets for cancer prevention and therapy.
Application of Random Forest in Predicting Fault-Prone Classes

There are available metrics for predicting fault prone classes, which may help software organizations for planning and performing testing activities. This may be possible due to proper allocation of resources on fault prone parts of the design and code of the software. Hence, importance and usefulness of such metrics is understandable, but empirical validation of these metrics is always a great challenge. Random forest (RF) algorithm has been successfully applied for solving regression and classification problems in many applications. This paper evaluates the capability of RF algorithm in predicting fault prone software classes using open source software. The results indicate that the prediction performance of random forest is good. However, similar types of studies are required to be carried out in order to establish the acceptability of the RF model.
Is podocyte shape controlled by the dystroglycan complex?

Alpha- and beta-dystroglycan were detected at the base of foot processes of human glomeruli by immunoelectron microscopy. Perfusion of isolated rat kidneys with the polycationic compound protamine sulfate was found to induce rapid (i.e. within 15 min) flattening of foot processes in an energy- and actin-dependent fashion. Here we provide evidence that (i) glomeruli possess large amounts of a specifically composed complex; (ii) this complex may undergo changes in human glomerular disease; and (iii) flattening of foot processes is directly associated with dissociation of laminin-dystroglycan complexes.
Analysis of Interior-Point Paths

Infeasible-interior-point paths are the main tools in interior-point methods for solving many kinds of optimization problems. These paths are usually parametrized by a penalty-parameter r ↓ 0 and further parameters describing their off-centrality and infeasiblilty. Starting with an early result of C. Witzgall et al. [12] in linear programming, this paper gives an overview on results concerning the existence of these paths, their analyticity and the limiting behavior of their derivatives as r ↓ 0, and this also for degenerate problems in the areas of linear programming, linear complementarity problems, and semi-definte programming.
NEAR-ULTRAVIOLET EXCESS IN SLOWLY ACCRETING T TAURI STARS: LIMITS IMPOSED BY CHROMOSPHERIC EMISSION

Young stars surrounded by disks with very low mass accretion rates are likely in the final stages of inner disk evolution and therefore particularly interesting to study. We present ultraviolet (UV) observations of the ∼5–9 Myr old stars RECX-1 and RECX-11, obtained with the Cosmic Origins Spectrograph and Space Telescope Imaging Spectrograph on the Hubble Space Telescope, as well as optical and near-infrared spectroscopic observations. The two stars have similar levels of near-UV emission, although spectroscopic evidence indicates that RECX-11 is accreting and RECX-1 is not. The line profiles of Hα and He i λ10830 in RECX-11 show both broad and narrow redshifted absorption components that vary with time, revealing the complexity of the accretion flows. We show that accretion indicators commonly used to measure mass accretion rates, e.g., U-band excess luminosity or the Ca ii triplet line luminosity, are unreliable for low accretors, at least in the middle K spectral range. Using RECX-1 as a template for the intrinsic level of photospheric and chromospheric emission, we determine an upper limit of 3 × 10−10 M☉ yr−1 for RECX-11. At this low accretion rate, recent photoevaporation models predict that an inner hole should have developed in the disk. However, the spectral energy distribution of RECX-11 shows fluxes comparable to the median of Taurus in the near-infrared, indicating that substantial dust remains. Fluorescent H2 emission lines formed in the innermost disk are observed in RECX-11, showing that gas is present in the inner disk, along with the dust.
Cooperative Spectrum Sensing in Cognitive Radio Networks Using Multidimensional Correlations

In this paper, a multidimensional-correlation-based sensing scheduling algorithm, (CORN)2, is developed for cognitive radio networks to minimize energy consumption. A sensing quality metric is defined as a measure of the correctness of spectral availability information based on the fact that spectrum sensing information at a given space and time can represent spectrum information at a different point in space and time. The scheduling algorithm is shown to achieve a cost of sensing (e.g., energy consumption, sensing duration) arbitrarily close to the possible minimum, while meeting the sensing quality requirements. To this end, (CORN)2 utilizes a novel sensing deficiency virtual queue concept and exploits the correlation between spectrum measurements of a particular secondary user and its collaborating neighbors. The proposed algorithm is proved to achieve a distributed and arbitrarily close to optimal solution under certain, easily satisfied assumptions. Furthermore, a distributed Selective-(CORN)2 (S-(CORN)2) is introduced by extending the distributed algorithm to allow secondary users to select collaboration neighbors in densely populated cognitive radio networks. In addition to the theoretically proved performance guarantees, the algorithms are evaluated through simulations.
Transactional information systems: theory, algorithms, and the practice of concurrency control and recovery

Transactional Information Systems is the long-awaited, comprehensive work from leading scientists in the transaction processing field. Weikum and Vossen begin with a broad look at the role of transactional technology in today's economic and scientific endeavors, then delve into critical issues faced by all practitioners, presenting today's most effective techniques for controlling concurrent access by multiple clients, recovering from system failures, and coordinating distributed transactions. The authors emphasize formal models that are easily applied across fields, that promise to remain valid as current technologies evolve, and that lend themselves to generalization and extension in the development of new classes of network-centric, functionally rich applications. This book's purpose and achievement is the presentation of the foundations of transactional systems as well as the practical aspects of the field what will help you meet today's challenges. * Provides the most advanced coverage of the topic available anywhere--along with the database background required for you to make full use of this material. * Explores transaction processing both generically as a broadly applicable set of information technology practices and specifically as a group of techniques for meeting the goals of your enterprise. * Contains information essential to developers of Web-based e-Commerce functionality--and a wide range of more "traditional" applications. * Details the algorithms underlying core transaction processing functionality. Table of Contents PART ONE - BACKGROUND AND MOTIVATION Chapter 1 What Is It All About? Chapter 2 Computational Models PART TWO - CONCURRENCY CONTROL Chapter 3 Concurrency Control: Notions of Correctness for the Page Model Chapter 4 Concurrency Control Algorithms Chapter 5 Multiversion Concurrency Control Chapter 6 Concurrency Control on Objects: Notions of Correctness Chapter 7 Concurrency Control Algorithms on Objects Chapter 8 Concurrency Control on Relational Databases Chapter 9 Concurrency Control on Search Structures Chapter 10 Implementation and Pragmatic Issues PART THREE - RECOVERY Chapter 11 Transaction Recovery Chapter 12 Crash Recovery: Notion of Correctness Chapter 13 Page Model Crash Recovery Algorithms Chapter 14 Object Model Crash Recovery Chapter 15 Special Issues of Recovery Chapter 16 Media Recovery Chapter 17 Application Recovery PART FOUR - COORDINATION OF DISTRIBUTED TRANSACTIONS Chapter 18 Distributed Concurrency Control Chapter 19 Distributed Transaction Recovery PART FIVE - APPLICATIONS AND FUTURE PERSPECTIVES Chapter 20 What Is Next?
PulseNet: the molecular subtyping network for foodborne bacterial disease surveillance, United States.

PulseNet, the national molecular subtyping network for foodborne disease surveillance, was established by the Centers for Disease Control and Prevention and several state health department laboratories to facilitate subtyping bacterial foodborne pathogens for epidemiologic purposes. PulseNet, which began in 1996 with 10 laboratories typing a single pathogen (Escherichia coli O157:H7), now includes 46 state and 2 local public health laboratories and the food safety laboratories of the U.S. Food and Drug Administration and the U.S. Department of Agriculture. Four foodborne pathogens (E. coli O157:H7; nontyphoidal Salmonella serotypes, Listeria monocytogenes and Shigella) are being subtyped, and other bacterial, viral, and parasitic organisms will be added soon.
Identifiability and Stability in Blind Deconvolution Under Minimal Assumptions

Blind deconvolution (BD) arises in many applications. Without assumptions on the signal and the filter, BD does not admit a unique solution. In practice, subspace or sparsity assumptions have shown the ability to reduce the search space and yield the unique solution. However, existing theoretical analysis on uniqueness in BD is rather limited. In an earlier paper, we provided the first algebraic sample complexities for BD that hold for Lebesgue almost all bases or frames. We showed that for BD of a pair of vectors in <inline-formula> <tex-math notation="LaTeX">$ \mathbb {C}^{n}$ </tex-math></inline-formula>, with subspace constraints of dimensions <inline-formula> <tex-math notation="LaTeX">$m_{1}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$m_{2}$ </tex-math></inline-formula>, respectively, a sample complexity of <inline-formula> <tex-math notation="LaTeX">$n\geq m_{1}m_{2}$ </tex-math></inline-formula> is sufficient. This result is suboptimal, since the number of degrees of freedom is merely <inline-formula> <tex-math notation="LaTeX">$m_{1}+m_{2}-1$ </tex-math></inline-formula>. We provided analogous results, with similar suboptimality, for BD with sparsity or mixed subspace and sparsity constraints. In this paper, taking advantage of the recent progress on the information-theoretic limits of unique low-rank matrix recovery, we finally bridge this gap, and derive an optimal sample complexity result for BD with generic bases or frames. We show that for BD of an arbitrary pair (respectively, all pairs) of vectors in <inline-formula> <tex-math notation="LaTeX">$ \mathbb {C} ^{n}$ </tex-math></inline-formula>, with sparsity constraints of sparsity levels <inline-formula> <tex-math notation="LaTeX">$s_{1}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$s_{2}$ </tex-math></inline-formula>, a sample complexity of <inline-formula> <tex-math notation="LaTeX">$n > s_{1}+s_{2}$ </tex-math></inline-formula> [respectively, <inline-formula> <tex-math notation="LaTeX">$n > 2(s_{1}+s_{2})$ </tex-math></inline-formula>] is sufficient. We also present analogous results for BD with subspace constraints or mixed constraints, with the subspace dimension replacing the sparsity level. Last but not least, in all the above scenarios, if the bases or frames follow a probabilistic distribution specified in this paper, the recovery is not only unique, but also stable against small perturbations in the measurements, under the same sample complexities.
IgG4-related systemic sclerosing disease: a diagnosis to be considered

IgG4-related systemic sclerosing disease is a chronic autoimmune disorder with diverse clinical presentation. We report a 56-year-old patient who has presented with obstructive jaundice, bulky pancreas and mesenteric lymph node mass. He was later diagnosed to have IgG4-sclerosing disease involving pancreas, small bowel mesentery, common bile duct, liver, gallbladder and submandibular salivary glands and has required multiple surgical interventions. IgG4-related systemic sclerosing disease appears to be more commonly encountered than it was once thought and needs considered in patients presenting with pancreatitis of no obvious underlying cause. Although the disease is primarily managed by medical therapy, there is a role for surgical intervention in order to obtain tissue for diagnosis, exclude other possible neoplastic aetiology and to manage disease-related complications.
Effects of multi-link failures on low priority traffic in MPLS-TE networks

Packet (MPLS-TE) over optical transport networks offer a two-phase restoration procedure against single and multiple concurrent equipment failures, i.e., a relatively faster restoration scheme at the MPLS layer and a relatively slower restoration scheme at the optical layer. This two-phase procedure can be leveraged to efficiently handle network recovery from a disaster-type scenario, while accounting for the traffic assigned priorities. This paper investigates the effects of this two-phase restoration procedure on the low priority traffic performance during and after network recovery.