Miracle-dz/UniFAR-FTUs huggingface dataset:
Ocean mixing and ice-sheet control of seawater 234U/238U during the last deglaciation

Uranium in the deep sea The ratio of 234U to 238U in seawater underlies modern marine uranium-thorium geochronology, but it is difficult to establish the ratio precisely. Chen et al. report two 234U/238U records derived from deep-sea corals (see the Perspective by Yokoyama and Esat). The records reveal a number of important similarities to and differences from existing records of the past 30,000 years. Higher values during the most recent 10,000 years than during earlier glaciated conditions may reflect enhanced subglacial melting during deglaciation. Science, this issue p. 626; see also p. 550 The 234U/238U ratios of deep-sea corals illuminate glacially driven changes of the past 30,000 years. Seawater 234U/238U provides global-scale information about continental weathering and is vital for marine uranium-series geochronology. Existing evidence supports an increase in 234U/238U since the last glacial period, but the timing and amplitude of its variability has been poorly constrained. Here we report two seawater 234U/238U records based on well-preserved deep-sea corals from the low-latitude Atlantic and Pacific Oceans. The Atlantic 234U/238U started to increase before major sea-level rise and overshot the modern value by 3 per mil during the early deglaciation. Deglacial 234U/238U in the Pacific converged with that in the Atlantic after the abrupt resumption of Atlantic meridional overturning. We suggest that ocean mixing and early deglacial release of excess 234U from enhanced subglacial melting of the Northern Hemisphere ice sheets have driven the observed 234U/238U evolution.
A comparison of waveform fractal dimension algorithms

The fractal dimension of a waveform represents a powerful tool for transient detection. In particular, in analysis of electroencephalograms and electrocardiograms, this feature has been used to identify and distinguish specific states of physiologic function. A variety of algorithms are available for the computation of fractal dimension. In this study, the most common methods of estimating the fractal dimension of biomedical signals directly in the time domain (considering the time series as a geometric object) are analyzed and compared. The analysis is performed over both synthetic data and intracranial electroencephalogram data recorded during presurgical evaluation of individuals with epileptic seizures. The advantages and drawbacks of each technique are highlighted. The effects of window size, number of overlapping points, and signal-to-noise ratio are evaluated for each method. This study demonstrates that a careful selection of fractal dimension algorithm is required for specific applications.
Attaining Precedence-Based Communications in Secure IP Networks

Voice networks which support military operations require multi-level precedence based communications to ensure that critical voice calls and messages arrive at their destination, even at the expense of lower precedence calls. Multi-Level Precedence and Preemption (MLPP) is straight-forward to implement in circuit-switched systems, but military forces have now embraced the transition to converged IP networks. Given this transition, there is a requirement for the future US, NATO, and coalition networks to support precedence for both real-time/inelastic and elastic applications over an infrastructure incorporating an IPsec encrypted, cipher-text network core, over both fixed and disadvantaged networks. Authentication and authorization mechanisms must be provided that ensure only properly authorized users are permitted to use particular precedence levels. Particular challenges include: the impact of encryption on the call signaling; supporting voice calls over disadvantaged transmission links; achieving precedence for elastic traffic; and the planning, monitoring, and management across a Federation of Systems. This paper summarizes the issues and considers the solution space.
Guidelines for Developing Automated Quality Control Procedures for Brain Magnetic Resonance Images Acquired in Multi-Centre Clinical Trials

Automated quality control (QC) procedures are critical for efficiently obtaining precise quantitative brain imaging-based metrics of in vivo brain pathology. This is especially important for multi-centre clinical trials of therapeutics for neurological diseases, in which brain imaging-based metrics may be used to quantify therapeutic efficacy. While there are many different types of brain imaging methods (e.g. computed tomography, magnetic resonance imaging, positron emission tomography, etc.) that have been used to quantify different aspects of in vivo pathology (e.g. presence of tumours, brain atrophy, hydrocephalus, abnormalities in blood vessels or the extravasation of blood, the depletion of receptors available for the binding of an injected substance, abnormal brain metabolism, etc.), this Chapter will focus on the automated QC procedures required to use magnetic resonance (MR) images (MRI) to yield imaging-based metrics of in vivo brain tissue pathology. Magnetic resonance imaging is a powerful non-invasive technology that can provide in vivo images sensitive to normal and pathological brain tissue. Important strengths of MR imaging include its superior grey-matter (GM)/ white-matter (WM) tissue contrast, sensitivity to WM pathology and clinical feasibility of relatively high-resolution whole-brain imaging. In conventional brain MRI, the signal intensities arise from the different relaxation characteristics of protons in water molecules present in different brain environments following radio-frequency (RF) excitation when the brain is in a magnetic field. MRI acquisition sequences vary the timing and duration of RF excitation pulses and magnetic field gradients, yielding different contrasts (termed MRI modalities) that can highlight different aspects of brain anatomy and pathology. This is illustrated in Fig. 1 using 4 conventional imaging modalities, T1-weighed (T1w) and T1w 5 min after intravenous injection of a gadolinium (Gd) contrast agent (T1w+Gd), T2-weighted (T2w), proton density weighted (PDw), and fluid attenuated inversion recovery (FLAIR) image, which were all acquired from a patient with multiple sclerosis (MS), a neurological disease that affects the brain and spinal cord. The T1w image most clearly differentiates brain GM, WM and
Earthquake Brain: Altered Recognition and Misclassification of Facial Expressions Are Related to Trauma Exposure but Not Posttraumatic Stress Disorder

Objectives The study investigated facial expression recognition (FER) in posttraumatic stress disorder (PTSD) caused by exposure to earthquakes, and in particular whether people with this condition showed a bias toward interpreting facial expressions as threat-related emotions (i.e., as anger, fear, or disgust). The study included a trauma-exposed control group who had been similarly exposed to the earthquakes but had not developed PTSD. We hypothesized that individuals with PTSD would have increased sensitivity to threat-related facial emotions compared with the trauma-exposed control group. This would be shown by increased accuracy in recognition of threat-related emotions and the misinterpretation of neutral expressions to these emotions (i.e., misidentifying them as anger, fear, or disgust). The availability of a group of healthy controls from a previous study who had been tested on a similar task before the earthquakes allowed a further non-exposed comparison. Method Twenty-eight individuals with PTSD (71% female, mean age 42.8 years) and 89 earthquake-exposed controls (66% female, mean age 50.1 years) completed an FER task, which featured six basic emotions. Further comparisons were made with 50 non-exposed controls (64% female, mean age 38.5 years) who had been tested before the earthquakes. Results There was no difference in sensitivity to threat-related facial expressions (as measured by accuracy in recognition of threat-related facial expressions and the misinterpretation of neutral expressions as threatening) in individuals with PTSD compared with similarly earthquake-exposed controls. Supplementary comparison with an historical, non-exposed control group showed that both earthquake-exposed groups had increased accuracy for the identification of all facial emotions and showed a bias in the misclassification of neutral facial expressions to the threat-related emotions of anger and disgust. Conclusion These findings suggest that it is exposure to earthquakes and repeated aftershocks, rather than the presence of PTSD that affects FER accuracy and misinterpretation. The importance of these biases in both PTSD and trauma-exposed controls needs further exploration and is an area for future research.
Obesity correlates with increased blood pressures in urban native American youth

Although obesity is a growing problem with Native American youth living on reservations, little research has been conducted examining the prevalence of obesity and correlations between age, body composition, dietary intake, and blood pressures (BP) for urban Native youth. The purpose of this study was to investigate the relationship of these variables in urban Native American youth. Height and weight were measured for 155 Native American youth, age 5–18 years, and the body mass index (BMI) was calculated and classified into percentile categories. Skinfold thicknesses at the biceps, triceps, suprailiac, and subscapular sites, arm and waist circumferences, and systolic (SBP) and diastolic (DBP) blood pressures were also measured. There was a high proportion of obesity (>95 percentile) for youth in all age groups. The prevalence was 38% for the 5–10‐year‐olds and 45% for the 11–18‐year‐olds youth. There were no significant correlations between SBP and DBP and dietary variables. Mean SBP and DBP increased with increasing BMI percentiles. Stepwise regression analyses showed that waist circumference, age, and BMI were strong predictors for SBP, while waist circumference and age were predictors for DBP in the total sample. The findings suggest that overweight/obesity is very prevalent among urban Native American youth and the increased adiposity is associated with increased SBP and DBP. Am. J. Hum. Biol. 15:78–90, 2003. © 2002 Wiley‐Liss, Inc.
Design and implementation of multilanguage name card reader on Android platform

In recent years, the rapid development of smartphone subscribers has played an important role in the trend of moving applications from computers to mobile devices. There are thousands of new mobile applications uploaded in the online stores daily in many fields like education, entertainment, healthcare, etc. This paper describes the design and implementation of multilanguage name card reader on Android platform which is the most popular mobile operating system. We use the built-in camera of smartphone to capture name card image or load available image from memory. This image will be rectified by using several image processing techniques before converted to characters by using Tesseract OCR engine. We define the templates of information for pattern matching and use Google application programming interface (API) to extract full name, mobile number, and email address to fill in the new contact importing form.
Electron Microscopic Examination of Corynebacterium ovis

Corynebacterium ovis (C. pseudotuberculosis) was examined by electron microscopy after being subjected to various methods of fixation. The organism exhibited a fine structure similar to other corynebacterial species in the appearance of its cell wall, plasma membrane, nuclear apparatus, cytoplasmic matrix, wealth and complexity of intracytoplasmic membrane systems, and polyphosphate granules. An outstanding structural feature was the existence of an electron-dense, floccular layer external to the cell wall which both ligroin and acetone-methanol extractions demonstrated to be the previously postulated surface lipid of this organism. The only variations in structure evident between virulent and attenuated strains was a quantitative difference in the thickness and appearance of the surface lipid. The observation of this layer provided a basis for explaining the surface properties of C. ovis, with particular respect to its clumping capacity in suspension, the waxiness of its growth on solid media, and its ability to grow as a pellicle on suitable liquid media. The variation in the visible amount of surface lipid between the virulent and avirulent strains adequately explained the divergence of these three surface properties between the strains.
Good Articles ?-How Wikis Work

Wikis are websites to develop content collaboratively. The question arises to what extent the reputation of participants influences the quality of wiki sites. We analyze the impact of author reputation using the example of Wikipedia. We extend previous research by considering a set of different reputation metrics and a new model for aggregating reputation values. Since anonymous authors tend to have a lower reputation, we also quantify the level of participation of anonymous authors as an indicator for the reputation of the crowd. Our analysis finds out that reputation matters, but strongly depends on the used reputation metric and therefore on the corresponding author characteristics. The study shows that the experience of authors in the development of high-quality articles is highly relevant whereas the number of edits and the quality of contributions are of lower importance. Finally, our investigation proves the open editing model and the self-healing mechanism of wikis.
Classification of biological signals using linear and nonlinear features

This paper investigates the characterization ability of linear and nonlinear features and proposes combining such features in order to improve the classification of biological signals, in particular single-trial electroencephalogram (EEG) and electrocardiogram (ECG) data. For this purpose, three data sets composed of ECG, epileptic EEG and finger-movement EEG were utilized. The characterization ability of seven nonlinear features namely the approximate entropy, largest Lyapunov exponents, correlation dimension, nonlinear prediction error, Hurst exponent, higher order autocovariance and asymmetry due to time reversal are compared with two linear features namely the autoregressive (AR) reflection coefficients and AR model coefficients. The features were tested by their ability to differentiate between different classes of data using a linear discriminant analysis (LDA) method with tenfold cross-validation. The class separability of combined linear and nonlinear features was assessed using sequential floating forward search with linear discriminant analysis method (SFFS-LDA). The results demonstrated that linear and nonlinear features on their own provided comparable results for the ECG data set and the finger-movement EEG data set whilst the linear features provided a better class separability compared to nonlinear features for the epileptic EEG data set. Combining linear and nonlinear features demonstrated a significant improvement in the class separability for all of the data sets where an average improvement of 20.56% was obtained with the ECG data set, 7.45% with finger-movement data set and 6.62% with the epileptic EEG data set. Overall results suggest that the use of combined linear and nonlinear feature sets would be a better approach for the characterization and classification of biological signals such as EEG and ECG.
Identification and characterization of clustered genes for thermostable xylan-degrading enzymes, beta-xylosidase and xylanase, of Bacillus stearothermophilus 21

Bacillus stearothermophilus 21 is a gram-positive, facultative thermophilic aerobe that can utilize xylan as a sole source of carbon. We isolated this strain from soil, purified its extracellular xylanase and beta-xylosidase, and analyzed the two-step degradation of xylan by these enzymes (T. Nanmori, T. Watanabe, R. Shinke, A. Kohno, and Y. Kawamura, J. Bacteriol. 172:6669-6672, 1990). An Escherichia coli transformant carrying a 4.2-kbp chromosomal segment of this bacterium as a recombinant plasmid was isolated. It excreted active beta-xylosidase and xylanase into the culture medium. The plasmid was introduced into UV-sensitive E. coli CSR603, and its protein products were analyzed by the maxicell method. Proteins harboring beta-xylosidase and xylanase activities were identified, and their molecular masses were estimated by sodium dodecyl sulfate-polyarylamide gel electrophoresis to be 75 and 40 kDa, respectively. The values were identical to those of proteins prepared from cells of B. stearothermophilus 21. The genes for both enzymes were encoded in a 3.4-kbp PstI fragment derived from the 4.2-kbp chromosomal segment. The nucleotide sequence of the 4.2-kbp segment was accordingly determined. The beta-xylosidase gene (xylA) is located upstream of the xylanase gene (xynA) with a possible promoter and a Shine-Dalgarno sequence. The latter gene is preceded by two possible promoters and a Shine-Dalgarno sequence that are located within the 3'-terminal coding region of the former. The two genes thus appear to be, at least partly, expressed independently, which was experimentally confirmed in E. coli by deletion analysis. (ABSTRACT TRUNCATED AT 250 WORDS)
Size Ratio Can Highly Predict Rupture Risk in Intracranial Small (<5 mm) Aneurysms

Background and Purpose— Management strategies for unruptured intracranial aneurysms (UIAs) are controversial. This study aimed to identify surrogate parameters that highly predict the rupture risk of small (<5 mm) UIAs. Methods— Radiological data were collected from 854 patients with aneurysmal subarachnoid hemorrhages who were enrolled in the Sapporo SAH Study. They had a total of 854 ruptured intracranial aneurysms and 180 UIAs. The size, aneurysm-to-vessel size ratio, and distribution were precisely compared between ruptured intracranial aneurysms and UIAs. Results— For all aneurysms, the size was significantly larger in ruptured intracranial aneurysms (7.0±1.3 mm) than in the UIAs (3.7±1.2 mm; P<0.001). Size ratio was also significantly higher in ruptured intracranial aneurysms (4.3±1.9) than in the UIAs (2.2±1.6; P<0.001). Multivariate logistic analysis showed that size and size ratio were correlated with aneurysm rupture. However, in small aneurysms, multivariate logistic regression revealed that only size ratio was associated with ruptured aneurysms (P=0.008; odds ratio, 9.1). There were no significant differences in size or aneurysm location. A receiver operating characteristic analysis was performed for size ratio in small aneurysms, and the threshold separating ruptured and unruptured groups was 3.12 and the area under the curve was 0.801. Conclusions— This study revealed that the size ratio, and not the absolute size, may highly predict the risk of rupture in small UIAs. Size ratio measurements are very simple and provide useful information for determining treatment and follow-up strategies for patients with small UIAs.
Model-based respiratory motion compensation for emission tomography image reconstruction

In emission tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations, imprecise diagnosis, impairing of fusion with other modalities, etc. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested, which lead to improvements over the spatial activity distribution in lungs lesions, but which have the disadvantages of requiring additional instrumentation or the need of discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion compensation directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the maximum likelihood expectation maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data.
The estimation of D-region electron densities from riometer data

Abstract. At high latitude the hard electron precipitation associated with auroral activity is a major source of ionization for the D-region, one consequence being the absorption of radio waves. Direct measurements of the D-region electron density are not readily available, however. This paper investigates the relationship between the electron density at altitudes between 100 and 70 km and the total radio absorption observed with a riometer, with a view to using the latter to predict the former. Tables are given of the median electron density corresponding to 1 dB absorption at 27.6 MHz for each hour of the day, and it is shown that at certain heights the estimates will be accurate to within a factor of 1.6 on 50% of the occasions. A systematic variation with time of day is probably associated with a progressive hardening of the typical electron spectrum during the morning hours. There is also evidence for a seasonal effect possibly due to seasonal variations of the mesosphere. Key words. Ionosphere (auroral ionosphere) – Radio science (ionospheric propagation; instruments and techniques)
Method of selecting training sets to build compact and efficient language model

For statistical language model training, target task matched corpora are required. However, training corpora sometimes include both target task matched and unmatched sentences. In such a case, training set selection is effective for both model size reduction and model performance improvement. In this paper, training set selection method for statistical language model training is described. The method provides two advantages for training a language model. One is its capacity to improve the language model performance, and the other is its capacity to reduce computational loads for the language model. The method has four steps. 1) Sentence clustering is applied to all available corpora. 2) Language models are trained on each cluster. 3) Perplexity on the development set is calculated using the language models. 4) For the final language model training, we use the clusters whose language models yield low perplexities. The experimental results we obtained indicate the language model trained on the data selected by our method gives lower perplexity on an open test set than a language model trained on all available corpora.
Error Performance Analysis of Clipped Alamouti Space-Time Coded OFDM Systems

In this paper we investigate the performance of clipped Alamouti space-time coded (STC) orthogonal frequency division multiplexing (OFDM) systems. The high peaks in STC-OFDM signals are clipped to limit the peak-to-average power ratio (PAPR). In STC-OFDM and OFDM, clipping can achieve significant PAPR reduction while maintaining a low symbol error rate (SER). Previous studies on OFDM have concluded that the effect of channel fading on clipping noise must be considered for an accurate error performance analysis. We extend this further to incorporate STC-OFDM systems and jointly study the impact of channel fading and receiver combining on clipping noise. At the STC-OFDM receiver, effective clipping noise governing the signal-to-noise ratio has different characteristics compared to the same for OFDM. Simulations indicate that STC-OFDM is more sensitive to clipping effects than OFDM. The theoretical and simulated SER are also compared for clipped STC-OFDM.