Miracle-dz/UniFAR-FTUs huggingface dataset:
Proceedings of the Fourth Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies

This paper provides an overview of current progress in the technological advances and the use of deep brain stimulation (DBS) to treat neurological and neuropsychiatric disorders, as presented by participants of the Fourth Annual DBS Think Tank, which was convened in March 2016 in conjunction with the Center for Movement Disorders and Neurorestoration at the University of Florida, Gainesveille FL, USA. The Think Tank discussions first focused on policy and advocacy in DBS research and clinical practice, formation of registries, and issues involving the use of DBS in the treatment of Tourette Syndrome. Next, advances in the use of neuroimaging and electrochemical markers to enhance DBS specificity were addressed. Updates on ongoing use and developments of DBS for the treatment of Parkinson's disease, essential tremor, Alzheimer's disease, depression, post-traumatic stress disorder, obesity, addiction were presented, and progress toward innovation(s) in closed-loop applications were discussed. Each section of these proceedings provides updates and highlights of new information as presented at this year's international Think Tank, with a view toward current and near future advancement of the field.
Verifying Linear Temporal Logic Properties in UML/OCL Class Diagrams Using Filmstripping

Testing system behavior in real world applications often requires analyzing properties over multiple system states to ensure that operations do not interfere with each other in ways that are not desired. In UML class diagrams, behavior is specified using operations with pre-and postconditions, which alone are not sufficient to formulate temporal properties spanning multiple system states and, thus, require additional description means. For this purpose, multiple extensions of OCL with linear temporal logic (LTL) exist, which provide a formalism to describe temporal properties. Using so-called filmstrip models, this paper provides formal semantics for OCL enhanced by LTL through a translation into standard OCL on the basis of class diagrams and enables verifying these temporal properties using existing model checking tools.
Development of Layer I Neurons in the Primate Cerebral Cortex

Layer I, which plays an important role in the development of the cerebral cortex, expands in size and diversity in primates. We found that, unlike in rodents, in the macaque monkey, neurons of this layer are generated during the entire 2 month period of corticogenesis, within the middle of the 165-d-long gestation. The large, classical Cajal–Retzius cells, immunoreactive to reelin and calretinin but not to GABA, are generated first [embryonic day 38 (E38)–E50], with the peak of [3H]thymidine ([3H]TdR) labeling at E43. Ultrastructural analysis revealed that processes of these cells form a stereotyped, rectangular network oriented parallel to the pial surface. Genesis of smaller, GABAergic neurons begins slightly later (E43), reaches a peak of [3H]TdR labeling between E54 and E70, and continues until the completion of corticogenesis (E94). These late-generated layer I cells are imported from outside sources such as the olfactory primordium and ganglionic eminence and via a massive subpial granular layer that may also supply some GABAergic interneurons to the subjacent cortical plate. The ratio of large-to-small layer I neurons changes differentially, indicating that each class is produced and/or eliminated at a different rate and suggesting that their roles in primates are diverse.
A problem solving environment for remote sensing data processing

A huge quantity of Earth observation and geospatial data is produced daily by numerous satellites launched by several worldwide space agencies. The processing of remote sensing data requires several steps, some of which are computationally intensive. The extraction of prominent information from remote sensing data requires a coordinated use of many applications and algorithms. Sharing computational resources among different scientists represents the sole way to approach the problem in order to achieve good performance. We describe a problem solving environment for remote sensing data processing layered on grid technologies. The proposed architecture allows sharing resources among different organizations taking into account each access policy defined by the owner of the resource.
Human carcinoma-associated mesenchymal stem cells promote ovarian cancer chemotherapy resistance via a BMP4/HH signaling loop

The tumor microenvironment is critical to cancer growth and therapy resistance. We previously characterized human ovarian carcinoma-associated mesenchymal stem cells (CA-MSCs). CA-MSCs are multi-potent cells that can differentiate into tumor microenvironment components including fibroblasts, myofibroblasts and adipocytes. We previously reported CA-MSCs, compared to normal MSCs, express high levels of BMP proteins and promote tumor growth by increasing numbers of cancer stem-like cells (CSCs). We demonstrate here that ovarian tumor cell-secreted Hedgehog (HH) induces CA-MSC BMP4 expression. CA-MSC-derived BMP4 reciprocally increases ovarian tumor cell HH expression indicating a positive feedback loop. Interruption of this loop with a HH pathway inhibitor or BMP4 blocking antibody decreases CA-MSC-derived BMP4 and tumor-derived HH preventing enrichment of CSCs and reversing chemotherapy resistance. The impact of HH inhibition was only seen in CA-MSC-containing tumors, indicating the importance of a humanized stroma. These results are reciprocal to findings in pancreatic and bladder cancer, suggesting HH signaling effects are tumor tissue specific warranting careful investigation in each tumor type. Collectively, we define a critical positive feedback loop between CA-MSC-derived BMP4 and ovarian tumor cell-secreted HH and present evidence for the further investigation of HH as a clinical target in ovarian cancer.
A GeSbTe phase-change memory cell featuring a tungsten heater electrode for low-power, highly stable, and short-read-cycle operations

This paper presents a GeSbTe memory cell with a tungsten heater electrode. The cell has the lowest reset current (50 /spl mu/A) ever reported for a phase-change memory device. The factors responsible for re-amorphization, which increased the instability of crystallization are shown. The GeSbTe cell in this work offers a read-time within 2 nsec, which allows 200 MHz-chip operation with negligible effects of read disturbance.
Simulation Analysis on Strength of Bucket Tooth with Various Soil

This paper applies large-scale finite element software ANSYS and the module of LS-DYNA to establish the solid model of bucket teeth, and according to Smoothed Particle Hydrodynamics Method (SPH) establishes the soil constitutive model. Emulating the process that bucket teeth excavate soil of three different grade ruggedness coefficients obtains the stress and statistical value of bucket tooth point; Simulation results show that: the stress concentration of bucket teeth point is more serious. When the ruggedness coefficient is0.6< f <1.0, the corresponding maximum stress is 197 ~ 309MPa, which meets the strength requirement . The damage is caused by the fatigue failure.
Study on Lüders Deformation in Welded Mild Steel Using Infrared Thermography and Digital Image Correlation

Studies on characterizing heterogeneous deformations in many materials under different loading conditions using imaging NDE techniques like Infrared thermography (IRT) and Digital image correlation (DIC) began in the last decade and have been reported by many researchers. This work aims in experimental investigation of one such heterogeneous deformation namely Lüders band phenomenon in welded IS 2062 E250-B mild steel during monotonic, uniaxial tensile testing using IRT and DIC. Also attempt has been made to study the generation of pre-yield microstrain in welded material. An understanding of nucleation and propagation of Lüders band in welded specimen is made based on temperature and strain changes.
BUILD-3: a randomized, controlled trial of bosentan in idiopathic pulmonary fibrosis.

RATIONALE A previous trial of bosentan in idiopathic pulmonary fibrosis (IPF) showed a trend to delayed IPF worsening or death. Also, improvements in some measures of dyspnea and health-related quality of life were observed. OBJECTIVES To demonstrate that bosentan delays IPF worsening or death. METHODS Prospective, randomized (2:1), double-blind, placebo-controlled, event-driven, parallel-group, morbidity-mortality trial of bosentan in adults with IPF of less than 3 years' duration, confirmed by surgical lung biopsy, and without extensive honeycombing on high-resolution computed tomography. The primary endpoint was time to IPF worsening (a confirmed decrease from baseline in FVC ≥ 10% and diffusing capacity of the lung for carbon monoxide ≥ 15%, or acute exacerbation of IPF) or death up to End of Study. Effects of bosentan on health-related quality of life, dyspnea, and the safety and tolerability of bosentan were investigated. MEASUREMENTS AND MAIN RESULTS Six hundred sixteen patients were randomized to bosentan (n=407) or placebo (=209). No significant difference between treatment groups was observed in the primary endpoint analysis (hazard ratio, 0.85; 95% confidence interval, 0.66-1.10; P=0.2110). No treatment effects were observed on health-related quality of life or dyspnea. Some effects of bosentan treatment were observed in changes from baseline to 1 year in FVC and diffusing capacity of the lung for carbon monoxide. The safety profile for bosentan was similar to that observed in other trials. CONCLUSIONS The primary objective in the Bosentan Use in Interstitial Lung Disease-3 trial was not met. Bosentan was well tolerated. Clinical trial registered with www.clinicaltrials. gov (NCT 00391443).
Implementation of an On-Demand Routing Protocol for Wireless Sensor Networks

We present our experiences in implementing and validating the on-demand EYES Source Routing protocol (ESR) in a real wireless sensor network (WSN) environment. ESR has a fast recovery mechanism relying on MAC layer feedback to overcome frequent network topology changes resulting from node mobility and unreliability. A geographically restricted directional flooding scheme reduces energy consumption in the route re-establishment. ESR is implemented in our WSN environment consisting of EYES sensor node prototypes using the Lightweight Medium Access Control protocol (LMAC) on top of the AmbientRT operating system. We describe the key design and implementation features of our protocol and report experiment results of ESR and Ad hoc On-demand Distance Vector protocol (AODV), a conventional routing protocol for ad hoc networks.
Accurate and Efficient PSD Computation in Mixed-Signal Circuits: A Time-Domain Approach

The aim of this brief is twofold. On one side, the time-domain technique presented by Vasudevan to obtain the average and instantaneous power-spectral density of electrical variables in analog circuits characterized by (non)stationary noise sources is rigorously extended to the wide class of analog mixed-signal circuits modeled as hybrid dynamical systems. On the other side, an efficient numerical implementation is proposed to overcome the computational effort required by the original approach. The reliability of the method is first tested through the analog ring oscillator analyzed by Vasudevan. A fractional delta-sigma phase-locked loop with dithering is then simulated and the obtained results are partially validated through experimental measurements.
Development, importance, and effect of a ground truth correction for the Moon Mineralogy Mapper reflectance data set

We evaluate the effect and importance of a ground truth correction for the Moon Mineralogy Mapper (M3) level 2 (reflectance) data set. This correction is derived from extensive laboratory characterizations of mature feldspathic lunar soils and is designed to improve the accuracy of 1 µm absorption features in M3 reflectance data. To evaluate the correction, the band strength across a subset of the feldspathic highlands terrane (FHT) is analyzed with M3 imaging spectroscopy data. Using M3 reflectance data and derived products, we find significant differences in band strength and shape between M3 observations collected over identical terrain but under different observational and operational conditions. The ground truth correction minimizes these differences in 1 µm band strengths and also brings the 1 µm band strengths measured with M3 data into closer agreement with laboratory measurements of lunar soil samples. Although the FHT region studied was found to have very low band strengths, the M3 ground truth correction results in overall stronger absorption features for all mature soils relative to uncorrected level 2 (reflectance) data for the same region. These differences between M3 data collected under different operational conditions and the effects of the ground truth correction, while minor in appearance, can have significant implications for interpretations of any regional soil analyses with M3 data that rely on absolute 1 µm absorption feature strength. The M3 ground truth correction corrects only wavelengths below ~1500 nm, and comparisons between corrected and uncorrected wavelengths must be done with caution.
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?

Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-dimensional datasets is challenging, since the search space is exponential in the number of dimensions and the volume of patterns can be huge. Many of the state-of-the-art techniques rely upon the use of prefix trees (e.g. FP-trees) which allow nodes to be shared among common prefix paths. However, the scalability of such techniques may be limited when handling high dimensional datasets. The purpose of this paper is to analyse the behaviour of mining frequent itemsets when instead of a tree data structure, a canonical directed acyclic graph namely Zero Suppressed Binary Decision Diagram (ZBDD) is used. Due to its compactness and ability to promote node reuse, ZBDD has proven very effective in other areas of computer science, such as boolean SAT solvers. In this paper, we show how ZBDDs can be used to mine frequent itemsets (and their common varieties). We also introduce a weighted variant of ZBDD which allows a more efficient mining algorithm to be developed. We provide an experimental study concentrating on high dimensional biological datasets, and identify indicative situations where a ZBDD technology can be superior over the prefix tree based technique.
Modeling Mode I Cracking Failure in Asphalt Binder by Using Nonconserved Phase-Field Model

AbstractCracking failure in asphalt binder in winter has always been one of the most serious problems in pavement structures. Classical fracture mechanics is the most widely used method to analyze the initiation and propagation of cracks. In this paper, a new modeling and computational tool—namely, the phase-field method—is proposed for modeling the Mode I cracking failure in asphalt binder. This method describes the microstructure using a phase-field variable that assumes 1 in the intact solid and −1 in the crack region. The fracture toughness is modeled as the surface energy stored in the diffuse interface between the intact solid and crack void. To account for the growth of cracks, a nonconserved Allen-Cahn equation is adopted to evolve the phase-field variable. The energy-based formulation of the phase-field method handles the competition between the growth of surface energy and release of elastic energy in a natural way: the crack propagation is a result of the energy minimization in the direction of.
Quality-oriented Rate Control and Resource Allocation in Time-Varying OFDMA Networks

In this paper, we propose a resource management scheme for on-demand video streaming in orthogonal frequency-division multiple access (OFDMA) networks with both time-varying channels and a user's personalized quality requirement. We design a user quality satisfaction model to evaluate the degree of the user quality satisfaction with respect to his/her personalized quality requirement. To perform the dynamic resource management, we propose a joint rate control (RC) associated with the quality adjustment at the application layer and resource allocation (RA) associated with the power allocation and subcarrier assignment at the physical layer. By using the Lyapunov optimization technique, we develop a joint RC and RA (JRCRA) algorithm to maximize the time-averaged quality satisfaction of all users (QSAU). We show that the QSAU achieved by the JRCRA algorithm without any prior knowledge of the channel statistics can arbitrarily attain the optimal QSAU achieved by the algorithm with a complete knowledge of the channel statistics. Simulation results verify the advantages of the proposed JRCRA algorithm.
Chapter 14: A Comparative Study of ICA Based Approaches for Separation of Components in Functional MRI Sequences

This paper prepares a review of ICA based approaches that are used for separation of components in functional MRI sequences. In previous works, the FastICA and the Infomax algorithms are investigated in more details; therefore, in this paper we focus on methods such as "radical ICA", "SDD ICA", "Erica" and "Evd" for separation purposes. This comparative study provides reliable framework for brain researchers to choose appropriate ICA based method for their special investigation purposes.
Correlated Cascades: Compete or Cooperate

In real world social networks, there are multiple cascades which are rarely independent. They usually compete or cooperate with each other. Motivated by the reinforcement theory in sociology we leverage the fact that adoption of a user to any behavior is modeled by the aggregation of behaviors of its neighbors. We use a multidimensional marked Hawkes process to model users product adoption and consequently spread of cascades in social networks. The resulting inference problem is proved to be convex and is solved in parallel by using the barrier method. The advantage of the proposed model is twofold; it models correlated cascades and also learns the latent diffusion network. Experimental results on synthetic and two real datasets gathered from Twitter, URL shortening and music streaming services, illustrate the superior performance of the proposed model over the alternatives.
A Path-based Transfer Model for Machine Translation

We propose a path-based transfer model for machine translation. The model is trained with a word-aligned parallel corpus where the source language sentences are parsed. The training algorithm extracts a set of transfer rules and their probabilities from the training corpus. A rule translates a path in the source language dependency tree into a fragment in the target dependency tree. The problem of finding the most probable translation becomes a graph-theoretic problem of finding the minimum path covering of the source language dependency tree.
Nonlinear terahertz spectroscopy

Our recent development of a simple and reliable method to generate terahertz (THz) pulses with high intensities (equivalent to high electric field amplitudes) has paved the way for nonlinear optics in the THz regime. We present experiments on bulk n-type GaAs which give new insights into phenomena like Bloch oscillations and Zener tunneling in bulk semiconductors. Another novel development in this field is two-dimensional THz spectroscopy. Here, we present first experiments on intersubband transitions in GaAs/AlGaAs quantum wells.
Inhibition of nuclear protein import by nonhydrolyzable analogues of GTP and identification of the small GTPase Ran/TC4 as an essential transport factor [published erratum appears in J Cell Biol 1994 Jan;124(1-2):217]

We have investigated a possible involvement of GTPases in nuclear protein import using an in vitro transport system involving digitonin- permeabilized cells supplemented with exogenous cytosol. Transport in this system was measured with a novel ELISA-based assay that allows rapid quantitative analysis. GTP gamma S and other nonhydrolyzable analogues of GTP were found to rapidly inhibit the rate of in vitro nuclear import. Transport inhibition by GTP gamma S was dependent on the concentrations of permeabilized cells and cytosol, and was strongly enhanced by a cytosolic factor(s). The predominant cytosolic component responsible for this inhibition was found in a 20-30-kD fraction in molecular sieving chromatography. Furthermore, a component(s) of this 20-30-kD fraction was itself required for efficient nuclear import. Biochemical complementation with bacterially expressed protein demonstrated that this essential GTP gamma S-sensitive transport factor was Ran/TC4, a previously described GTPase of the Ras superfamily found in both nucleus and cytoplasm. Ran/TC4 and its guanine nucleotide release protein RCC1 have previously been implicated in DNA replication, cell cycle checkpoint control, and RNA synthesis, processing and export. Our results suggest that Ran/TC4 serves to integrate nuclear protein import with these other nuclear activities.
Moderators of remission with interpersonal counselling or drug treatment in primary care patients with depression: randomised controlled trial.

BACKGROUND Despite depressive disorders being very common there has been little research to guide primary care physicians on the choice of treatment for patients with mild to moderate depression. AIMS To evaluate the efficacy of interpersonal counselling compared with selective serotonin reuptake inhibitors (SSRIs), in primary care attenders with major depression and to identify moderators of treatment outcome. METHOD A randomised controlled trial in nine centres (DEPICS, Australian New Zealand Clinical Trials Registry number: ACTRN12608000479303). The primary outcome was remission of the depressive episode (defined as a Hamilton Rating Scale for Depression score ≤7 at 2 months). Daily functioning was assessed using the Work and Social Adjustment Scale. Logistic regression models were used to identify moderators of treatment outcome. RESULTS The percentage of patients who achieved remission at 2 months was significantly higher in the interpersonal counselling group compared with the SSRI group (58.7% v. 45.1%, P = 0.021). Five moderators of treatment outcome were found: depression severity, functional impairment, anxiety comorbidity, previous depressive episodes and smoking habit. CONCLUSIONS We identified some patient characteristics predicting a differential outcome with pharmacological and psychological interventions. Should our results be confirmed in future studies, these characteristics will help clinicians to define criteria for first-line treatment of depression targeted to patients' characteristics.
Scaling in Stock Market Data: Stable Laws and Beyond

The concepts of scale invariance, self-similarity and scaling have been fruitfully applied to the study of price fluctuations in financial markets. After a brief review of the properties of stable Levy distributions and their applications to market data we indicate the shortcomings of such models and describe the truncated Levy flight as an alternative model for price movements. Furthermore, studying the dependence structure of the price increments shows that while their autocorrelation function decreases rapidly to zero, the correlation of their squares and absolute values shows a slow power law decay, indicating persistence in the scale of fluctuations, a property which can be related to the anomalous scaling of the kurtosis. In the last section we review, in the light of these empirical facts, recent attempts to draw analogies between scaling in financial markets and in turbulent flows.