Miracle-dz/UniFAR-FTUs huggingface dataset:
An energy-dispersive technique to measure x-ray coherent scattering form factors of amorphous materials

The material-dependent x-ray scattering properties of amorphous substances such as tissues and phantom materials used in imaging are determined by their scattering form factors, measured as a function of the momentum transfer argument, x. Incoherent scattering form factors, Finc, are calculable for all values of x while coherent scattering form factors, Fcoh, cannot be calculated except at large x because of their dependence on long-range order. As a result, measuring Fcoh is very important to the developing field of x-ray scatter imaging. Previous measurements of Fcoh, based on crystallographic techniques, have shown significant variability, as these techniques are not optimal for amorphous materials. We have developed an energy-dispersive technique that uses a polychromatic x-ray beam and an energy-sensitive detector. We show that Fcoh can be measured directly, with no scaling parameters, by computing the ratio of two spectra: the first, measured at a given scattering angle and the second, the direct transmission spectrum with no scattering. Experiments have been constructed on this principle and used to measure Fcoh for water and polyethylene to explore the reliability of the technique. A 121 kVp x-ray spectrum and seven different scattering angles between 1.67 and 15.09° were used, resulting in a measurable range of x between 0.5 and 9.5 nm−1. These are the first measurements of Fcoh made without the need for a scaling factor. Resolution in x varies between 10% for small scattering angles and 2% for large scattering angles. Accuracy in Fcoh is shown to be strongly dependent on the precision of the experimental geometry and varies between 5% and 15%. Comparison with previous published measurements for water shows values of the average absolute relative difference between 8% and 14%.
Fully covered self-expandable metal stent in the treatment of postsurgical colorectal diseases: outcome in 29 patients

Background: Self-expandable metal stent (SEMS) placement is a minimally invasive treatment for palliation of malignant colorectal strictures and as a bridge to surgery. However, the use of SEMS for benign colorectal diseases is controversial. The purpose of this retrospective study is to evaluate the efficacy and safety of fully covered SEMS (FCSEMS) placement in postsurgical colorectal diseases. Methods: From 2008 to 2014, 29 patients with 32 FCSEMS deployment procedures were evaluated. The indications for stent placement were: 17 anastomotic strictures (3/17 presented complete closure of the anastomosis); four anastomotic leaks; seven strictures associated with anastomotic leak; and one rectum-vagina fistula. Results: Clinical success was achieved in 18 out of 29 patients (62.1%) being symptom-free at an average of 19 months. In the remaining 11 patients (37.9%), a different treatment was needed: four patients required multiple endoscopic dilations, 4 patients colostomy confection, one patient definitive ileostomy and three patients revisional surgery. The FCSEMS were kept in place for a mean period of 34 (range: 6–65) days. Major complications occurred in 12 out of 29 patients (41.4%) and consisted of stent migration. Minor complications included two cases of transient fever, eight cases of abdominal or rectal pain, and one case of tenesmus. Conclusion: FCSEMS are considered a possible therapeutic option for treatment of postsurgical strictures and leaks. However, their efficacy in guaranteeing long-term anastomotic patency and leak closure is moderate. A major complication is migration. The use of FCSEMS for colonic postsurgical pathologies should be carefully evaluated for each patient.
Recovering Implicit Information

This paper describes the SDC PUNDIT, (Prolog UNDerstands Integrated Text), system for processing natural language messages. PUNDIT, written in Prolog, is a highly modular system consisting of distinct syntactic, semantic and pragmatics components. Each component draws on one or more sets of data, including a lexicon, a broad-coverage grammar of English, semantic verb decompositions, rules mapping between syntactic and semantic constituents, and a domain model.This paper discusses the communication between the syntactic, semantic and pragmatic modules that is necessary for making implicit linguistic information explicit. The key is letting syntax and semantics recognize missing linguistic entities as implicit entities, so that they can be labelled as such, and reference resolution can be directed to find specific referents for the entities. In this way the task of making implicit linguistic information explicit becomes a subset of the tasks performed by reference resolution. The success of this approach is dependent on marking missing syntactic constituents as elided and missing semantic roles as ESSENTIAL so that reference resolution can know when to look for referents.
Effects of smoked substance abuse on nonspecific airway hyperresponsiveness.

Previous data suggest that regular tobacco smoking may lead to nonspecific airway hyperresponsiveness (AHR) independent of airway obstruction, possibly because of effects on bronchial inflammation or mucosal permeability. Little is known concerning the effects on AHR of other widely smoked substances besides tobacco such as marijuana or cocaine. The smoke of both marijuana and cocaine contains respiratory irritants that elicit cough and produce abnormalities in airway dynamics and bronchial mucosal histopathology in habitual smokers. Therefore, regular smoking of one or both of these illicit substances could cause AHR or augment the AHR associated with tobacco smoking. The present study examined the influence of habitual smoking of marijuana, cocaine, and/or tobacco on nonspecific AHR in 542 (456 male) healthy participants (mean age, 34.8 +/- 6.8 SD yr) in an ongoing cohort study of the pulmonary effects of habitual smoking of illicit substances. Subjects with a history of intravenous drug abuse, significant occupational exposures, asthma, or recent upper respiratory tract infection were excluded. Inhalation challenge studies were performed using solutions of diluent and methacholine chloride (1.25 to 25 mg/ml) aerosolized by a DeVilbiss no. 646 nebulizer attached to a breath-activated dosimeter inhaled by three to five inspiratory capacity breaths. Positive responses to methacholine were defined by > or = 20% or > or = 10% declines in FEV1 from the postdiluent control value after inhalation of each concentration of methacholine. Participants were categorized by smoking status (nonsmoking and smoking of marijuana, cocaine, and/or tobacco alone and in combination); most analyses were performed in men and women separately. (ABSTRACT TRUNCATED AT 250 WORDS)
A Latent Variable Approach to Study Gene–Environment Interactions in the Presence of Multiple Correlated Exposures

Summary Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene–environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene–environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case–control G × E studies, we use the assumption of gene–environment (G‐E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G‐E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G‐E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade‐off between the most restrictive to most flexible form of G‐E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro‐Toxicants Study of lead exposure, iron metabolism genes, and birth weight.
Monetary policy with incomplete exchange rate pass-through

The central bank's optimal reaction to foreign and domestic shocks is analyzed in an inflation targeting model allowing for incomplete exchange rate pass-through. Limited pass-through is incorporated through nominal rigidities in an aggregate supply-aggregate demand model derived from some microfoundations. Three main results are obtained. First, the results suggest that the interest rate response to foreign shocks is smaller when pass-through is low. Second, the inflation-output variability trade-off becomes more favourable as pass-through decreases. Third, lower pass-through, that is larger nominal rigidity, leads to higher exchange rate volatility. With exogenous nominal price stickiness, part of the required relative price adjustment is provided through larger movements in the endogenously determined exchange rate.
Performance Evaluation of Polyol Esters from Palm Oil as a Lubricant for Bentonite Suspension Drilling Fluid

This study evaluated the potential use of three polyol esters (POEs) derived from palm oil as a lubricant in bentonite suspension drilling fluid. Three different POEs were investigated, which are pentaerythritol ester (PEE), trimethylolpropane ester (TMPE), and neopentylglycol ester (NPGE). It was revealed that POEs reduced the coefficient of friction (COF) in bentonite suspension by more than 80%. However, TMPE and NPGE undesirably caused foaming and altered the gel texture of the suspension. PEE showed the best performance as it produced the highest lubricity and the lowest effect on the suspension texture. The decrease of COF might increase the drilling efficiency and prevent the lubricity-related drilling problems. The findings of this investigation will be used for future applications of POE from palm oil in wider mud formulation.
Self-Optimisation of Antenna Beam Tilting in LTE Networks

This paper introduces a novel technique for self-optimisation of antenna down-tilting. The proposed solution consists of two phases. During the first phase, which needs to be performed quickly, a method based on the Golden Section Search (GSS) algorithm is used to find a near-optimal tilt angle. Then, in the next step, the tilt angle value is fine-tuned through frequent explorations of the near-optimal region. Additionally, the solution benefits from self-healing properties by responding to the failure of a neighbouring cell. In this case, the algorithm is adapted to find a new optimal point upon failure detection. The result shows fast convergence and close-to-optimum performance (93.8% on average) of the proposed algorithm. The overall solution is fully distributed and is 3GPP complaint.
Ieee Signal Processing Magazine Special Issue Bayesian Nonparametric Methods for Learning Markov Switching Processes

Markov switching processes, such as the hidden Markov model (HMM) and switching linear dy-namical system (SLDS), are often used to describe rich dynamical phenomena. They describe complex behavior via repeated returns to a set of simpler models: imagine a person alternating between walking, running, and jumping behaviors, or a stock index switching between regimes of high and low volatility. Classical approaches to identification and estimation of these models assume a fixed, pre-specified number of dynamical models. We instead examine Bayesian nonparametric approaches that define a prior on Markov switching processes with an unbounded number of potential model parameters (i.e., Markov modes). By leveraging stochastic processes such as the beta and Dirichlet process, these methods allow the data to drive the complexity of the learned model, while still permitting efficient inference algorithms. They also lead to generalizations which discover and model dynamical behaviors shared among multiple related time series.
Magnetic iron oxide nanoparticles as T1 contrast agents for magnetic resonance imaging

Ultrasmall iron oxide nanoparticles have recently attracted much attention as T1 (positive) contrast agents for magnetic resonance imaging to serve as safer alternatives to gadolinium-based T1 contrast agents. This review will discuss several key aspects regarding this newly developed contrast agent, including synthetic strategies, parameters affecting T1 signal (e.g., size, surface, and environment), and emerging applications. The integration with other imaging modalities will be discussed as well, such as dual T1/T2 imaging, positron emission tomography, and computed tomography. Finally, perspectives and outlook about the future development and concerns will be included.
“I Can/Should Look Like a Media Figure”: The Association Between Direct and Indirect Media Exposure and Teens’ Sexualizing Appearance Behaviors

Prior research has examined the influence of media exposure on adolescents’ sexualized self-concept, but engagement in sexualizing appearance behaviors remains understudied, especially among a younger age group (i.e., early adolescents). This three-wave panel study among 971 nine- to 14-year-olds (Mage = 12.99, SD = 1.03) showed that discussing media content with friends (i.e., indirect media exposure) was indirectly related to sexualizing appearance behaviors through perceived attainability of the appearance ideal. Direct media exposure was not significantly related to sexualizing appearance behaviors, nor to perceived pressure or perceived attainability. Direct and indirect media exposure influenced boys and girls in similar ways, although the model showed a better fit among the girls. In addition, reward sensitivity did not moderate the examined relations.
Molecular pathology of Alzheimer neurofibrillary

The most characteristic brain lesion of Alzheimer disease is the accumulation of paired helical filaments (PHF) in the affected neurons. Based on solubility in detergents there are two general populations of PHF, the readily soluble (PHF I) and the sparingly soluble (PHF 11) types. The major polypeptides of PHF are the microtubule associated protein tau. Tau in PHF is present in abnormally phosphorylated forms. In addition to the PHF, the abnormal tau is also present in unpolymerized form in the AD brain. Small amounts of ubiquitin (%) are associated with PHF I1 but neither with PHF I nor with the unpolymerized abnormally phosphorylated tau in AD brain. Furthermore, the pretangle neurons can readily be immunolabeled for abnormally phosphorylated tau but not for ubiquitin. The level of tau in neocortex is several-fold higher than in AD aged control cases, but this increase is in the form of the abnormally phosphorylated protein. The microtubule associated proteins from AD brain do not promote the assembly of microtubules in vitro, whereas the in vitro dephosphorylated PHF polypeptides stimulate the binding of GTP to the exchangeable site of tubulin and the assembly of microtubules. In vitro the phosphate groups in PHF are less accessible than those of tau to alkaline phosphatase. It is suggested that a defect in the protein phosphorylation/dephosphorylation system leads to hyperphosphory-lation of tau. The altered tau contributes to a microtubule assembly defect and consequently compromises the axoplasmic flow and leads to neuronal degeneration.
An improved array interpolation approach to DOA estimation in correlated signal environments

Many popular direction-of-arrival (DOA) estimators rely on the fact that the array response vector of the array is Vandermonde, for example, that of a uniform linear array (ULA). Array interpolation is a preprocessing technique to transform the array response vector of a planar array of arbitrary geometry to that of a ULA over an angular sector. While good approximation within the target sector is attained in the existing array interpolation approaches, the response of the interpolated array in the out-of-sector region is at best partially controlled. Accordingly, out-of-sector signals, especially those highly correlated with the in-sector signals, can degrade significantly the performance of DOA estimators (e.g., MUSIC with spatial smoothing) that rely on the Vandermonde form to work correctly. In this paper, we propose an improved array interpolation approach that takes into account the array response over the full azimuth. We present also numerical examples to demonstrate the shortcomings of the existing approaches and the effectiveness of our proposal.
A Storage Model with a Two-State Random Environment

Motivated by queues with service interruptions, we consider an infinite-capacity storage model with a two-state random environment. The environment alternates between “up” and “down” states. In the down state, the content increases according to one stochastic process; in the up state, the content decreases according to another stochastic process. We describe the steady-state behavior of this system under assumptions on the component stochastic elements. For the special case of deterministic linear flow during the up and down states, we show that the steady-state content is directly related to the steady-state workload or virtual waiting time in an associated G/G/1 queue, thus supplementing the results of D. P. Gaver, Jr., and R. G. Miller, Jr. (1962), R. G. Miller, Jr. (1963) and H. Chen and D. D. Yao (1992).
Potential

Traces of past human life activities can be seen in cultural remains such as artifacts, features and ecofacs. The cultural remains found today are also referred to as archaeological resources. We have to explore the potential of these archaeological traces or remains so that we can bring them back as a learning resource. Banyuwangi Regency is rich in archaeological heritage that can be used as an alternative source of learning from existing books. This study tries to analyze these relics and present them into the history learning of senior high schools in Banyuwangi. The results show that the archaeological remains in Banyuwangi are very complete from prehistoric times to modern history. However, the history teacher at senior high school did not explore these relics with various obstacles, ranging from difficulties in integrating materials and financial problems which were large enough to invite students to places that had archaeological remains. This study provides an overview of the subject matter that can be integrated according to the 2013 curriculum and the findings of archaeological remains in Banyuwangi as a learning resource.
A Low-Power Noise Reduction Technique for Broadband CMOS Low-Noise Amplifiers

A broadband input matching technique for low noise amplifiers (LNAs) is presented which exploits an active feedback network to achieve better noise performance. The presented matching scheme is compared to the common-gate and conventional noise canceling structures. The noise performance of the presented technique is similar to that of the conventional noise canceling technique with much less power consumption. In contrast to the traditional noise cancellation circuit, the proposed LNA does not degrade the linearity and its IIP3 is similar to the simple common-gate LNA. The proposed technique is applied to an LNA operating in 2~6.5 GHz bandwidth. The circuit is designed in a 0.18 μm RF CMOS technology with a 1.8 V power supply. This LNA achieves an IIP3 of +5.4 dBm, 17 dB voltage gain, and 2.5 dB noise figure while consuming 7.6 mW power. KeywordsUltra wideband (UWB), low noise amplifier, noise cancellation, low power.
Transcranial passive acoustic mapping with hemispherical sparse arrays using CT-based skull-specific aberration corrections: a simulation study

The feasibility of transcranial passive acoustic mapping with hemispherical sparse arrays (30 cm diameter, 16 to 1372 elements, 2.48 mm receiver diameter) using CT-based aberration corrections was investigated via numerical simulations. A multi-layered ray acoustic transcranial ultrasound propagation model based on CT-derived skull morphology was developed. By incorporating skull-specific aberration corrections into a conventional passive beamforming algorithm (Norton and Won 2000 IEEE Trans. Geosci. Remote Sens. 38 1337–43), simulated acoustic source fields representing the emissions from acoustically-stimulated microbubbles were spatially mapped through three digitized human skulls, with the transskull reconstructions closely matching the water-path control images. Image quality was quantified based on main lobe beamwidths, peak sidelobe ratio, and image signal-to-noise ratio. The effects on the resulting image quality of the source’s emission frequency and location within the skull cavity, the array sparsity and element configuration, the receiver element sensitivity, and the specific skull morphology were all investigated. The system’s resolution capabilities were also estimated for various degrees of array sparsity. Passive imaging of acoustic sources through an intact skull was shown possible with sparse hemispherical imaging arrays. This technique may be useful for the monitoring and control of transcranial focused ultrasound (FUS) treatments, particularly non-thermal, cavitation-mediated applications such as FUS-induced blood–brain barrier disruption or sonothrombolysis, for which no real-time monitoring techniques currently exist.
Efficient and Parsimonious Agnostic Active Learning

We develop a new active learning algorithm for the streaming setting satisfying three important properties: 1) It provably works for any classifier representation and classification problem including those with severe noise. 2) It is efficiently implementable with an ERM oracle. 3) It is more aggressive than all previous approaches satisfying 1 and 2. To do this, we create an algorithm based on a newly defined optimization problem and analyze it. We also conduct the first experimental analysis of all efficient agnostic active learning algorithms, evaluating their strengths and weaknesses in different settings.
New method to determine the base resistance of bipolar transistors

A new method to determine the base resistance of bipolar transistors under forward-bias conditions is presented. Using special transistor structures, the total base resistance has been directly measured and then separated into its components, the external and internal base resistances. The sheet resistance for the internal base region can be estimated for a base-emitter voltage range of practical interest. An accurate estimation of the base resistance of advanced bipolar transistors under high-forward-bias conditions is demonstrated. <<ETX>>
A proportional assist ventilator to unload respiratory muscles experimentally during exercise in humans

What is the central question of this study? Can a modern proportional assist ventilator (PAV) function sufficiently well to unload the respiratory muscles during exercise? What is the main finding and its importance? A PAV can be constructed with contemporary hardware and software and be used at all exercise intensities to unload the respiratory muscles by up to 70%. Previously, PAVs have allowed researchers to address many fundamental physiological problems in clinical and healthy populations, but those versions are no longer functional or available. We describe the creation of a PAV that permits researchers to use it as an experimental tool.