Miracle-dz/UniFAR-FTUs huggingface dataset:
Diabetes Island: Preliminary Impact of a Virtual World Self-Care Educational Intervention for African Americans With Type 2 Diabetes

Background Diabetes is a serious worldwide public health challenge. The burden of diabetes, including prevalence and risk of complications, is greater for minorities, particularly African Americans. Internet-based immersive virtual worlds offer a unique opportunity to reach large and diverse populations with diabetes for self-management education and support. Objective The objective of the study was to examine the acceptability, usage, and preliminary outcome of a virtual world intervention, Diabetes Island, in low-income African Americans with type 2 diabetes. The main hypotheses were that the intervention would: (1) be perceived as acceptable and useful; and (2) improve diabetes self-care (eg, behaviors and barriers) and self-care related outcomes, including glycemic control (A1C), body mass index (BMI), and psychosocial factors (ie, empowerment and distress) over six months. Methods The evaluation of the intervention impact used a single-group repeated measures design, including three assessment time points: (1) baseline, (2) 3 month (mid intervention), and (3) 6 month (immediate post intervention). Participants were recruited from a university primary care clinic. A total of 41 participants enrolled in the 6 month intervention study. The intervention components included: (1) a study website for communication, feedback, and tracking; and (2) access to an immersive virtual world (Diabetes Island) through Second Life, where a variety of diabetes self-care education activities and resources were available. Outcome measures included A1C, BMI, self-care behaviors, barriers to adherence, eating habits, empowerment, and distress. In addition, acceptability and usage were examined. A series of mixed-effects analyses, with time as a single repeated measures factor, were performed to examine preliminary outcomes. Results The intervention study sample (N=41) characteristics were: (1) mean age of 55 years, (2) 71% (29/41) female, (3) 100% (41/41) African American, and (4) 76% (31/41) reported annual incomes below US $20,000. Significant changes over time in the expected direction were observed for BMI (P<.02); diabetes-related distress (P<.02); global (P<.01) and dietary (P<.01) environmental barriers to self-care; one physical activity subscale (P<.04); and one dietary intake (P<.01) subscale. The participant feedback regarding the intervention (eg, ease of use, interest, and perceived impact) was consistently positive. The usage patterns showed that the majority of participants logged in regularly during the first two months, and around half logged in each week on average across the six month period. Conclusions This study demonstrated promising initial results of an immersive virtual world approach to reaching underserved individuals with diabetes to deliver diabetes self-management education. This intervention model and method show promise and could be tailored for other populations. A large scale controlled trial is needed to further examine efficacy.
Fractional order disturbance observer for a run-of-mine ore milling circuit

Grinding mill circuits are hard to control with high performance due to poor modeling, large external disturbances, and uncertainties from internal couplings. This paper proposes a novel fractional order disturbance observer (FO-DOB) for a run-of-mine (ROM) ore milling circuit. A fractional order low pass filter (Q-filer) is used in the DOB to offer an additional degree of freedom in tuning for set-point tracking performance and disturbance rejection performance. A 3×3 linear time invariant MIMO plant model is used for evaluation of the performance gained over other commonly used controllers such as PID and MPC. The simulation results show that the FO-DOB scheme offers promising potential in real world ROM milling circuit implementations.
An Ensemble Kalman Filter Data Assimilation Scheme for Modeling the Wave Climate in Persian Gulf

In recent years, application and evaluation of the efficiency of different data assimilation methods has been a subject of interest in both wave hindcasting and forecasting systems. The main goal of the current study is to assess the efficiency of an ensemble Kalman filter (EnKF) data assimilation scheme in improving the wave simulation results in Persian Gulf. The so called region plays an important role in the oil and gas industry due to its Geographical and Morphological location and housing a large number of offshore platforms.A third generation wave model, SWAN, was employed in order to simulate the wave fields in the region. The three hours updated ECMWF wind data were used as the main driving force. The OpenDA toolbox, especially developed for efficient data assimilation purposes, was employed to smooth the chaotic nature of the non-linear wave simulation scheme. The OpenDA utilizes a number of methods that are based on Kalman filter algorithm but do not require the amount of computation efforts that are incurred by the classical filter algorithm. The EnKF is a variant of Kalman filter, where probability density function of a model state is represented by an ensemble of the model state.Two sets of records for significant wave heights and peak wave periods were used in the analysis process with EnKF to estimate the error covariance matrix. At analysis time, the forecast error covariance was computed by using the model forecasts ensembles. In overall and for the wave climate modeling, the initial conditions of the numerical model were updated using the improved system state, up to the current computing time level. This is achieved by incorporating the previous measurements into the Kalman filter algorithm. The model was then run into the future, driven by the new improved state conditions.The statistical results and diagrams showed that applying EnKF scheme leads to a noticeable improvement in significant wave heights. However, the accuracy of this technique was subjected to the location and number of observation stations and also ensemble size. With larger ensembles, results of error covariance estimation are more accurate but there is a limitation due to execution time of process and efficiency of the computations.Copyright © 2013 by ASME
A Practical and Scalable Tool to Find Overlaps between Sequences

The evolution of the next generation sequencing technology increases the demand for efficient solutions, in terms of space and time, for several bioinformatics problems. This paper presents a practical and easy-to-implement solution for one of these problems, namely, the all-pairs suffix-prefix problem, using a compact prefix tree. The paper demonstrates an efficient construction of this time-efficient and space-economical tree data structure. The paper presents techniques for parallel implementations of the proposed solution. Experimental evaluation indicates superior results in terms of space and time over existing solutions. Results also show that the proposed technique is highly scalable in a parallel execution environment.
Lyapunov Analysis of Sample-and-Hold Hybrid Feedbacks

For hybrid closed-loop systems arising from hybrid control of nonlinear systems, we show that the sample-and-hold implementation of the hybrid controller preserves (semiglobally and practically) the stability properties of the closed-loop system. We provide a general model for the hybrid closed-loop system where the hybrid controller is implemented digitally and it is interfaced to the nonlinear system through sample and hold devices. We model the sample device and the digital controller/hold device as single asynchronous hybrid systems with independent timing constants and data. The main result is established by means of a Lyapunov function for the hybrid closed-loop system resulting from the interconnection of its hybrid and nonlinear subsystems
Hydrous Phases and Water Transport in the Subducting Slab

Arc volcanoes are typically located 90–180 km above the surface of downgoing slabs, as shown by Wadati-Benioff deep seismic foci (Gill 1981; Tatsumi 1989). The intimate relationship between the dip angles of the subducting slab and the locations of volcanic arcs indicates that subduction zone magmatism is triggered by material input from the subducting slab (Tatsumi and Eggins 1995). The slab-derived components are thought to be aqueous fluids or H2O-rich partial melts of subducted oceanic crust. Therefore, knowledge of the stability of hydrous phases and the chemical and physical properties of aqueous fluids in downgoing slabs is essential to understand the material transport in subduction zones. In this section, I will review the stability of hydrous phases in downgoing peridotite, basalt and sediment systems, and the chemical and the wetting properties of aqueous fluids. Recent experimental studies indicate that 3–4 GPa, equivalent to 90–120 km depth, is a key pressure, where (1) the chemical compositions of silicate components dissolved in aqueous fluids equilibrated with mantle minerals approach the composition of mantle peridotite itself (Stalder et al. 2001; Mibe et al. 2002; Kawamoto et al. 2004), (2) the dihedral angle between olivine and aqueous fluids starts becoming smaller than 60° (Watson et al. 1990; Mibe et al. 1998, 1999), and (3) the immisciblity gap between peridotitic melts and aqueous fluids disappears and consequently hydrous minerals liberate supercritical aqueous fluids (Mibe et al. 2004a, 2006). The similarity between these pressures and the depths of downgoing slab underneath volcanic fronts, where the maximum numbers of volcanoes are formed, 124 ± 38 km (Gill 1981) or 112 ± 19 km (Tatsumi 1986), suggests that subduction zone magmatism can be triggered by the input of supercritical fluids from the downgoing peridotite and basalt. Many hydrous crystalline phases …
DKPro TC: A Java-based Framework for Supervised Learning Experiments on Textual Data

We present DKPro TC, a framework for supervised learning experiments on textual data. The main goal of DKPro TC is to enable researchers to focus on the actual research task behind the learning problem and let the framework handle the rest. It enables rapid prototyping of experiments by relying on an easy-to-use workflow engine and standardized document preprocessing based on the Apache Unstructured Information Management Architecture (Ferrucci and Lally, 2004). It ships with standard feature extraction modules, while at the same time allowing the user to add customized extractors. The extensive reporting and logging facilities make DKPro TC experiments fully replicable.
The Path through Math: Course Sequences and Academic Performance at the Intersection of Race‐Ethnicity and Gender

Using new national data from Adolescent Health and Academic Achievement (AHAA), this article examines high school math patterns for students of different race‐ethnicity and gender. Compared with white males, African American and Latino males receive lower returns from taking Algebra I during their freshman year, reaching lower levels of the math course sequence when they begin in the same position. This pattern is not explained by academic performance, and, furthermore, African American males receive less benefit from high math grades. Lower returns are not observed for minority female students, suggesting that more attention to racial‐ethnic inequality in math among male students is needed.
The Black Hole-to-Bulge Mass Relation in Active Galactic Nuclei

The masses of the central black holes in active galactic nuclei (AGNs) can be estimated using the broad emission lines as a probe of the virial mass inside the broad-line region (BLR). Using reverberation mapping to determine the size of the BLR and the width of the variable component of the line profile Hβ line, it is possible to find quite accurate virial mass estimates for AGNs with adequate data. Compiling a sample of AGNs with reliable central masses and bulge magnitudes, we find an average black hole-to-bulge mass ratio of 10-3.5, a factor of 20 less than the value found for normal galaxies and for bright quasars. This lower ratio is more consistent with the black hole mass density predicted from quasar light and agrees with the value found for our Galaxy. We argue that the black hole-to-bulge mass ratio actually has a significantly larger range than indicated by massive black holes detected in normal galaxies (using stellar dynamics) and in bright quasars—which may be biased toward larger black holes—and derive a scenario of black hole growth that explains the observed distribution.
Genetic Dissection of Sympatric Populations of Brown Planthopper, Nilaparvata lugens (Stål), Using DALP-PCR Molecular Markers

Direct amplified length polymorphism (DALP) combines the advantages of a high-resolution fingerprint method and also characterizing the genetic polymorphisms. This molecular method was also found to be useful in brown planthopper, Nilaparvata lugens species complex for the analysis of genetic polymorphisms. A total of 11 populations of Nilaparvata spp. were collected from 6 locations from Malaysia. Two sympatric populations of brown planthopper, N. lugens, one from rice and the other from a weed grass (Leersia hexandra), were collected from each of five locations. N. bakeri was used as an out group. Three oligonucleotide primer pairs, DALP231/DALPR′5, DALP234/DALPR′5, and DALP235/DALPR′5 were applied in this study. The unweighted pair group method with arithmetic mean (UPGMA) dendrogram based on genetic distances for the 11 populations of Nilaparvata spp. revealed that populations belonging to the same species and the same host type clustered together irrespective of their geographical localities of capture. The populations of N. lugens formed into two distinct clusters, one was insects with high esterase activities usually captured from rice and the other was with low esterase activities usually captured from L. hexandra. N. bakeri, an out group, was the most isolated group. Analyses of principal components, molecular variance, and robustness also supported greatly to the findings of cluster analysis.
Crucial function of vertebrate glutaredoxin 3 (PICOT) in iron homeostasis and hemoglobin maturation

Vertebrate glutaredoxin 3 (PICOT) is essential for the maturation of the heme cofactor of hemoglobin through its essential functions in iron homeostasis. The data suggest an evolutionarily conserved role of cytosolic monothiol multidomain Grxs in cellular iron metabolism pathways.
Social negative bootstrapping for visual categorization

To learn classifiers for many visual categories, obtaining labeled training examples in an efficient way is crucial. Since a classifier tends to misclassify negative examples which are visually similar to positive examples, inclusion of such informative negatives should be stressed in the learning process. However, they are unlikely to be hit by random sampling, the de facto standard in literature. In this paper, we go beyond random sampling by introducing a novel social negative bootstrapping approach. Given a visual category and a few positive examples, the proposed approach adaptively and iteratively harvests informative negatives from a large amount of social-tagged images. To label negative examples without human interaction, we design an effective virtual labeling procedure based on simple tag reasoning. Virtual labeling, in combination with adaptive sampling, enables us to select the most misclassified negatives as the informative samples. Learning from the positive set and the informative negative sets results in visual classifiers with higher accuracy. Experiments on two present-day image benchmarks employing 650K virtually labeled negative examples show the viability of the proposed approach. On a popular visual categorization benchmark our precision at 20 increases by 34%, compared to baselines trained on randomly sampled negatives. We achieve more accurate visual categorization without the need of manually labeling any negatives.
Machine listening techniques as a complement to video image analysis in forensics

Video is now one of the major sources of information for forensics. However, video documents can be originating from various recording devices (CCTV, mobile devices, etc.) with inconsistent quality and can sometimes be recorded in challenging light or motion conditions. Therefore, the amount of information that can be extracted relying solely on video image can vary to a great extent. Most of the videos however generally include audio recording as well. Machine listening can then become a valuable complement to video image analysis in challenging scenarios. In this paper, the authors present a brief overview of some machine listening techniques and their application to the analysis of video documents for forensics. The applicability of these techniques to forensics problems is then discussed in the light of machine listening system performances.
Lentiviral Vector Mediated Delivery of RHBDD1 shRNA down Regulated the Proliferation of Human Glioblastoma Cells

Rhomboid domain containing 1 (RHBDD1) gene, a new member of rhomboid family of proteins is highly responsible for the regulation of apoptosis by cleaving pro-apoptotic Bcl-2 family protein BIK. Therefore, the higher expression levels of RHBDD1 in cancer tissues may have a direct influence on cancer progression by arresting apoptosis. With this background this study was focused to find out the effect of RHBDD1 silencing on the progression of human brain glioblastoma cells, U251 and U87MG. The results indicated that both cell lines show a higher expression level of RHBDD1 and RNA interference (RNA) mediated gene silencing successfully down regulated the RHBDD1 gene expression. As a result of RHBDD1 silencing the proliferation of both cell types was reduced by over 50%, 5 days after silencing. Moreover the colony formation was completely inhibited and there were no cells present following two week RHBDD1 gene silencing. The cell proliferation was inhibited as a result of cell cycle arrest due to RHBDD1 absence. Therefore, these results clearly indicate that, RHBDD1 is essential for the progression of glioblastoma cells and silencing of it is resulting in significant inhibition of cell cycle progression and cell proliferation. Collectively, this study shows that RHBDD1 gene engineering could be used as an effective tool in malignant brain tumor therapy.
Estimation of Extreme Sea Levels in a Tide-Dominated Environment Using Short Data Records

A new method for estimating extreme sea levels from short sea-level records in a tide-dominated environment is presented. A short sea-level record is first decomposed into its constituent components such as tide, mean level of the sea, and storm surge. Monte Carlo simulations are then incorporated into an empirical simulation technique to randomly recombine the components to produce an annual series of sea levels at high tide from which the annual maximum is selected. The yearly simulation is repeated many thousands of times to yield robust statistics on extreme values. Comparison of the method with the traditional extreme-value analysis of annual maximum sea levels for a 33-year record shows that the methods give similar results. The method is likely to be most useful for estimation of extreme sea levels at locations where the available sea-level record is short (<15 years) and where the various sea-level components can be assumed to be largely independent.
Improving LSB steganalysis using marginal and joint probabilistic distributions

The goal of steganalysis is to search for the presence of hidden information in numerical contents. This paper is based on a previous LSB steganalysis scheme for digital images that estimates the size of the hidden message. The accuracy of this algorithm is first outlined, then the limits are presented in order to introduce some solutions based on texture processing: analysis of histograms and coocurrence matrices are presented and their uses, to improve steganalysis using segmentation, is proposed.
Casting Shadows in Real Time

Shadows are crucial for enhancing realism and provide important visual cues. In recent years, many important contributions have been made both for hard shadows and soft shadows. Often spurred by the tremendous increase of computational power and capabilities of graphics hardware, much progress has been made concerning visual quality and speed, making high-quality real-time shadows a reachable goal. But with the growing wealth of available choices, it is particularly dicult to pick the right solution and assess shortcomings. Because currently there is no ultimate approach available, algorithms should be selected in accordance to the context in which shadows are produced. The possibilities range across a wide spectrum; from very approximate but really ecient to slower but accurate, adapted only to smaller or only to larger sources, addressing directional lights or positional lights, or involving GPU- or CPU-heavy computations. This course tries to serve as a guide to better understand limitations and failure cases, advantages and disadvantages, and suitability of the algorithms for dierent application scenarios. We will focus on real-time to interactive solutions but also discuss oine approaches if needed for a better understanding. In the future, we will provide you with more information via the course webpage: http://www.mpi-inf.mpg. de/resources/ShadowCourse/.
Optimal bidding strategies in dynamic auctions with budget constraints

We consider the problem of a bidder with limited budget competing in a series of second-price auctions. A motivating example is that of sponsored search auctions, where advertisers bid in a sequence of repeated generalized second price auctions. To characterize the optimal bidding strategy, we formulate the problem as a discounted Markov Decision Process, and provide explicit solutions when the bidder is involved in a large number of auctions.
Ponderosa pine mortality following fire in northern Arizona

Sampling of 1367 trees was conducted in the Side wildfire (4 May 1996), Bridger-Knoll wildfire (20 June 1996) and Dauber prescribed fire (9 September 1995) in northern Arizona ponderosa pine forests (Pinus ponderosa). Tree mortality was assessed for 3 years after each fire. Three-year post-fire mortality was 32.4% in the Side wildfire, 18.0% in the Dauber prescribed fire, and 13.9% in the Bridger-Knoll wildfire. In the Dauber and Side fires, 95% and 94% of 3-year post-fire mortality occurred by year 2, versus 76% in the Bridger-Knoll wildfire. Compared with trees that lived for 3 years after fire, dead trees in all fires had more crown scorch, crown consumption, bole scorch, ground char, and bark beetle attacks. Logistic regression models were used to provide insight on factors associated with tree mortality after fire. A model using total crown damage by fire (scorch + consumption) and bole char severity as independent variables was the best two-variable model for predicting individual tree mortality for all fires. The amount of total crown damage associated with the onset of tree mortality decreased as bole char severity increased. Models using diameter at breast height (dbh) and crown volume damage suggested that tree mortality decreased as dbh increased in the Dauber prescribed fire where trees were smallest, and tree mortality increased as dbh increased in the Side and Bridger-Knoll wildfires where trees were largest. Moreover, a U-shaped dbh–mortality distribution for all fires suggested higher mortality for the smallest and largest trees compared with intermediate-size trees. We concluded that tree mortality is strongly influenced by interaction between crown damage and bole char severity, and differences in resistance to fire among different-sized trees can vary among sites.