Miracle-dz/UniFAR-FTUs huggingface dataset:
APOE Genotypes Associate With Cognitive Performance but Not Cerebral Structure: Diabetes Heart Study MIND

OBJECTIVE Dementia is a debilitating illness with a disproportionate burden in patients with type 2 diabetes (T2D). Among the contributors, genetic variation at the apolipoprotein E locus (APOE) is posited to convey a strong effect. This study compared and contrasted the association of APOE with cognitive performance and cerebral structure in the setting of T2D. RESEARCH DESIGN AND METHODS European Americans from the Diabetes Heart Study (DHS) MIND (n = 754) and African Americans from the African American (AA)-DHS MIND (n = 517) were examined. The cognitive battery assessed executive function, memory, and global cognition, and brain MRI was performed. RESULTS In European Americans and African Americans, the APOE E4 risk haplotype group was associated with poorer performance on the modified Mini-Mental Status Examination (P < 0.017), a measure of global cognition. In contrast to the literature, the APOE E2 haplotype group, which was overrepresented in these participants with T2D, was associated with poorer Rey Auditory Verbal Learning Test performance (P < 0.032). Nominal associations between APOE haplotype groups and MRI-determined cerebral structure were observed. CONCLUSIONS Compared with APOE E3 carriers, E2 and E4 carriers performed worse in the cognitive domains of memory and global cognition. Identification of genetic contributors remains critical to understanding new pathways to prevent and treat dementia in the setting of T2D.
Emotion Mining Techniques in Social Networking Sites

In today’s scenario social networking sites are a part and parcel of our lives that are hard to be avoided by anyone. These SNS are contributing in bringing people together from various communities of similar interest at a single collaborated destination. This not only helps people in sharing their views, experiences, likes and dislikes regarding a common topic of interest. Moreover most of the active and vibrant users have a great impact on influencing others views and thoughts. Such an impact can be negative as well as positive depending upon the conveyer and receptor’s ability to think and understand and these factors effect on how a person react to a particular situation and there by influence others.
The Co-activator CREB-binding Protein Participates in Enhancer-dependent Activities of Bicoid*

Bicoid (Bcd) is a transcriptional activator required for early embryonic patterning in Drosophila. Despite extensive studies, it currently remains unclear how Bcd activates transcription and what proteins participate in its activation process. In this report, we describe experiments to analyze the role of the Drosophila co-activator dCBP in Bcd-mediated activation. In Drosophila S2 cells, the Bcd activity is increased by the co-transfection of plasmids expressing dCBP and reduced by double-stranded RNA-mediated interference against dCBP. We further show that Bcd and dCBP can interact with each other and that Bcd-interacting domains of dCBP can cause dominant negative effects on Bcd activity in S2 cells. Our comparison of two Bcd-responsive enhancers, hunchback (hb) and knirps (kni), reveals a differential role of dCBP in facilitating Bcd activation. A dCBP mutant defective in its histone acetyltransferase activity exhibits a reduced, but not abolished, co-activator function for Bcd. Our chromatin immunoprecipitation experiments show that dCBP can increase not only the occupancy of Bcd itself at the enhancers but also the recruitment of general transcription factors to the promoter. Together, these experiments suggest that dCBP is an enhancer-dependent co-activator of Bcd, facilitating its activation through multiple mechanisms.
Neutrophil gelatinase-associated lipocalin and acute kidney injury after cardiac surgery: the effect of baseline renal function on diagnostic performance.

BACKGROUND AND OBJECTIVES Neutrophil gelatinase-associated lipocalin (NGAL) is rapidly released by renal tubules after injury, potentially allowing early identification of acute kidney injury (AKI) after cardiac surgery. However, the diagnostic performance of NGAL has varied widely in clinical studies, and it remains unknown what factors modify the relationship between NGAL and AKI. We hypothesized the relationship between urinary NGAL and AKI would vary with baseline renal function, allowing a stratified analysis to improve diagnostic performance of this novel biomarker. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS We performed a prospective observational study in 426 adult cardiac surgical patients. Urinary NGAL was serially determined, commencing preoperatively and continuing 24 hours postoperatively. AKI was defined as increase in serum creatinine from baseline by either >50% or >0.3 mg/dl within 48 hours postoperatively. Patients were stratified by baseline estimated GFR (eGFR). NGAL levels were compared between patients with and without AKI and diagnostic characteristics determined according to baseline eGFR. RESULTS In patients with baseline eGFR >or=60 ml/min, urinary NGAL was higher at all postoperative time points in patients who developed AKI compared with those who did not. In patients with baseline eGFR <60 ml/min, urinary NGAL did not differ at any time between those who did and those who did not develop AKI. Postoperative NGAL best identified AKI in patients with baseline eGFR 90 to 120 ml/min. CONCLUSIONS The relationship between urinary NGAL and AKI after cardiac surgery varies with baseline renal function, with optimal discriminatory performance in patients with normal preoperative function.
CW technique for measurement of linewidth enhancement factor: application to 735-nm tensile-strained GaAsP quantum-well lasers

We present a procedure for determining the linewidth enhancement factor (/spl alpha/ parameter) in semiconductor lasers under continuous-wave (CW) operation. It is based on the measurement of the amplified spontaneous emission spectra, with a proper correction of thermal effects. The method is applied to 735-nm tensile strained GaAsP-AlGaAs quantum-well lasers and it is validated by comparing CW results, after correcting thermal effects, with pulsed measurements. The results show a low value of the /spl alpha/ parameter attributed to the tensile strain.
Effect of medicinal and aromatic plants on rumen fermentation, protozoa population and methanogenesis in vitro.

The potential of tannins from 21 medicinal and aromatic plant leaves as antimethanogenic additives in ruminant feeds was investigated. The effect of tannin from these leaves on rumen fermentation parameters, protozoa population and methanogenesis was studied by incubating the samples [200 mg dry matter (DM)] without and with polyethylene glycol (PEG)-6000 (400 mg DM) as a tannin binder during 24-h incubation in the in vitro Hohenheim gas method. Based on the methane percentage estimated in the total gas produced, methane production in millilitre was calculated [methane volume (ml) = methane % × total gas produced (ml) in 24 h]. In the samples, crude protein and neutral detergent fibre (g/kg DM) ranged from 113 to 172 and from 352 to 444 respectively. The total phenol (TP; g/kg DM) content was highest in Terminalia chebula (274) followed by Hemigraphis colorata (71) and Sapindus laurifolia (51) respectively. In the remaining samples, it was <43 g/kg DM. Activity of tannins, as represented by the increase in gas volume on addition of PEG, ranged from 0 to 133%, with the highest being recorded in T. chebula. The per cent increase in methane on PEG addition was 0 for Ammi majus, Aristolochia indica, Cascabela thevetia, Ipomea nil and Lantana camara, illustrating that tannins present in these samples had no effect on methane concentration. The PEG addition increased the total protozoa count by >50% in A. indica and C. thevetica. One of the important findings of our study was that of the 21 samples screened, Entodinia population increased in 12 with PEG as compared to 7 where Holotricha increased, indicating higher susceptibility of Entodinia to tannin. There was no increase in the protozoa population with PEG when incubating Cardiospermum halicacabum, Clerodendrum inerme, Dioscorea floribunda, Nerium oleander and Selastras paniculatus, which strongly suggested that methane suppression recorded in these samples was not because of a defaunating effect of their tannins per se. The fermentation pattern reflected increased total volatile fatty acid (TVFA) concentration from 0 to 28.3% with PEG addition among the leaves. Our results confirmed further observations that methanogenesis in vitro is not essentially related to density of protozoa population. Secondly, medicinal and aromatic plants such as C. inerme, Gymnema sylvestre and Sapindus laurifolia containing tannins appear to have a potential to suppress in vitro methanogenesis.
Carbon sources utilized by virulent Treponema pallidum

Carbon sources utilized by virulent Treponema pallidum organisms extracted from infected rabbit tissue have been investigated. Utilization of 14C-labeled compounds by T. pallidum was monitored by degradation of these compounds to 14CO2. Experiments have consistently shown that of 22 carbon sources examined, [14C]glucose and [14C]pyruvate are selectively degraded to 14CO2 under the experimental conditions employed. When [1-14C]pyruvate, [2-14C]pyruvate, and [3-14C]pyruvate are tested, virulent T. pallidum preferentially degrade and release the carboxyl group as 14CO2. End product analyses indicate that CO2 and acetate are the major products of pyruvate degradation by T. pallidum.
Reliability Of Arm Wingate Anaerobic Testing In Persons With Complete Paraplegia

Abstract Background: Accurate, reliable assessment of upper extremity muscular power in persons with paraplegia caused by spinal cord injury (SCI) would provide an objective indication of their ability to generate the forces necessary for the performance of daily activities. Wingate Anaerobic Testing (WAnT) consists of a 30-second sprint test on a cycle ergometer and has been used widely in both athletic and research settings. Purpose: To examine test-retest reliability of arm WAnT performance in persons with complete SCI and paraplegia. Methods: Forty-three participants with thoracic-level paraplegia (T2 through T12) performed 2 trials of arm WAnT with 2 to 7 days between each trial. Testing was performed using a Monarch 834E ergometer with participants seated in their wheelchairs. Participants were directed to crank at maximal pace for 30 seconds against a resistance load equivalent to 3.5% of their body mass. The SMI OptoSensor 2000 system was used to determine values of peak power (Ppeak), mean power (Pmean), minimum power, and rate of fatigue, which were compared between trials using 1-way analysis of variance for repeated measures. Coeffi cients of determination (r2) were calculated between trials for Ppeak and Pmean. Results: No significant diffe rence was found between trials for any of the power output variables. Regression analysis ind icat ed that Ppeak and Pmean were closely associated between the 2 trials (r2= 0.92 and 0.94, respectively). Conclusion: Arm WAnT is a reliable measurement tool for the assessment of upper extremity muscular power in persons with complete paraplegia.
Comments on Picture thresholding using an iterative selection method

T.W. Ridler and E.S. Calvard (ibid., vol.SMC-8, p.630-2, Aug. 1978) presented a method of picture thresholding that was further mathematically developed by H.J. Trussel (ibid., vol.SMC-9, p.311, 1979). The principle of this method is to evaluate the unique threshold T for any image with a bimodal histogram. The present paper reinterprets the procedure as an algorithm designed to optimize the conversion of a multiple gray-level picture to a bimodel picture while maintaining as closely as possible the average luminance of the picture. >
GenderMag: A Method for Evaluating Software's Gender Inclusiveness

In recent years, research into gender differences has established that individual differences in how people problem-solve often cluster by gender. Research also shows that these differences have direct implications for software that aims to support users' problem-solving activities, and that much of this software is more supportive of problem-solving processes favored (statistically) more by males than by females. However, there is almost no work considering how software practitioners—such as User Experience (UX) professionals or software developers—can find gender-inclusiveness issues like these in their software. To address this gap, we devised the GenderMag method for evaluating problem-solving software from a gender-inclusiveness perspective. The method includes a set of faceted personas that bring five facets of gender difference research to life, and embeds use of the personas into a concrete process through a gender-specialized Cognitive Walkthrough. Our empirical results show that a variety of practitioners who design software—without needing any background in gender research—were able to use the GenderMag method to find gender-inclusiveness issues in problem-solving software. Our results also show that the issues the practitioners found were real and fixable. This work is the first systematic method to find gender-inclusiveness issues in software, so that practitioners can design and produce problem-solving software that is more usable by everyone.
A new approach to the differential diagnosis of human malignant melanomas

In an attempt to improve the diagnosis of melanotic tumors, we have compared the diagnosis obtained by histological examination of 216 skin tumors and their metastases with that obtained by using a conjunction of four techniques: tissue culture, cytoenzymology, in situ electron microscopy and 5‐S‐cysteinyl‐dopa (5‐S‐CD) assay. In 46 cases the final diagnosis as determined by one or more of these tests differed from the initial histological diagnosis, but was confirmed by repeat histological examination. We conclude that this method presents a valuable new approach to the differential diagnosis of human malignant melanoma.
Thread-level parallel execution in co-designed virtual machines

Virtual machine technology is becoming more important as the use of non-heterogeneous computer networks have become more widespread. However, the runtime performance of an application running on a virtual machine is significantly below that of the same application running as a native executable on a given platform. Previous work shows that a hardware/software co-designed virtual machine can provide a performance improvement. This paper describes research work to further improve the performance of the co-designed virtual machine by adding thread-level parallel execution. The design put forward adds the functionality to support independent scheduling of threads in the hardware and software partitions of the co-designed virtual machine. A prototype of the design, based on the Java virtual machine, utilizing software simulation has been constructed and tested. The results of this testing show that the design is feasible when there is sufficient communication bandwidth available between the partitions.
Registration of Neuroimaging Data: Implementation and Clinical Applications

Image registration brings images into a form in which each voxel corresponds to a predetermined anatomic entity and is necessary for comparisons of data across scans. lntrasubject registration is a matter of translating and rotating one image volume into correspondence with another. lntersubject registration is more difficult because it requires the removal of individual anatomy dependence from the data. This article describes, with the help of clinical examples, automated methods for intrasubject registration of scans within and between modalities, and intersubject registration used for registering a three‐dimensional brain atlas with a patient's brain scan.
The Effect of Retrospective Sampling on Estimates of Prediction Error for Multifactor Dimensionality Reduction

The standard in genetic association studies of complex diseases is replication and validation of positive results, with an emphasis on assessing the predictive value of associations. In response to this need, a number of analytical approaches have been developed to identify predictive models that account for complex genetic etiologies. Multifactor Dimensionality Reduction (MDR) is a commonly used, highly successful method designed to evaluate potential gene‐gene interactions. MDR relies on classification error in a cross‐validation framework to rank and evaluate potentially predictive models. Previous work has demonstrated the high power of MDR, but has not considered the accuracy and variance of the MDR prediction error estimate. Currently, we evaluate the bias and variance of the MDR error estimate as both a retrospective and prospective estimator and show that MDR can both underestimate and overestimate error. We argue that a prospective error estimate is necessary if MDR models are used for prediction, and propose a bootstrap resampling estimate, integrating population prevalence, to accurately estimate prospective error. We demonstrate that this bootstrap estimate is preferable for prediction to the error estimate currently produced by MDR. While demonstrated with MDR, the proposed estimation is applicable to all data‐mining methods that use similar estimates.
Genome Sequence of Riemerella anatipestifer Strain RCAD0122, a Multidrug-Resistant Isolate from Ducks

ABSTRACT Riemerella anatipestifer is an important pathogenic bacterium in waterfowl and other avian species. We present here the genome sequence of R. anatipestifer RCAD0122, a multidrug-resistant strain isolated from infected ducks. The isolate contains at least nine types of antibiotic resistance-associated genes.
Invited Paper - Even the Rich Can Make Themselves Poor: A Critical Examination of IV Methods in Marketing Applications

Marketing is a field that is rich in data. Our data is of high quality, often at a highly disaggregate level, and there is considerable variation in the key variables for which estimates of effects on outcomes such as sales and profits are desired. The recognition that, in some general sense, marketing variables are set by firms on the basis of information not always observable by the researcher has led to concerns regarding endogeneity and widespread pressure to implement instrumental variables methods in marketing problems. The instruments used in our empirical literature are rarely valid and the IV methods used can have poor sampling properties, including substantial finite sample bias and large sampling errors. Given the problems with IV methods, a convincing argument must be made that there is a first order endogeneity problem and that we have strong and valid instruments before these methods should be used. If strong and valid instruments are not available, then researchers need to look toward supplementing the information available to them. For example, if there are concerns about unobservable advertising or promotional variables, then the researcher is much better off measuring these variables rather than using instruments such as lagged marketing variables that are clearly invalid. Ultimately, only randomized variation in marketing variables with proper implementation and large samples can be argued to be a valid instrument without further assumptions.
How strong is the case for the adoption of problem-based learning in physiotherapy education in the United Kingdom?

Despite its use in medical and health education in several countries, problem-based learning (PBL) has to date not been adopted in undergraduate physiotherapy education in the UK. Most of these physiotherapy curricula incorporate many of the educationally desirable features found in PBL.The question is whether the evidence for PBL is strong enough to justify the costs involved in adopting it on such programmes. The strength of the evidence for PBL was reviewed in relation to required graduate attributes and several aspects of learning theory. Overall the findings were equivocal. The evidence suggests that PBL is preferential to traditional curricular design, but does not seem to meet all the requirements of medical and health education. Adoption of PBL would be positive, but its processes and outcomes may be no more successful than those of other curricular designs that incorporate the same sound educational design features. Comparative research in this area is needed.
A Hidden Markov Model-based approach for recognizing swimmer's behaviors in swimming pool

This paper employs a HMM (Hidden Markov Model) methodology to recognize some specific-behaviors of a swimmer in the swimming pool. In this study, a swimmer's behavior is composed of a series of the static image-frames. For each frame, a Convexity-Structure is used to enclose the swimmer's shape after segmenting the swimmer-blob. A codebook is created for mapping a swimmer-blob into one of 6 feature blob-types during training and recognition stage. Consequently, the time-sequential blobs are converted to a feature-vector sequence and transformed into a symbolic-sequence by the existed codebook. Thus a learned HMM can be obtained by this symbolic-sequence from a given specific-behavior and used to recognize a swimmer's behavior which is normal or abnormal. Four different swimming styles (Backstroke, Breaststroke, Freestyle, and Butterfly) are examined. An average recognition rate of 90% is obtained.
Fuzzy C means integrated with spatial information and contrast enhancement for segmentation of MR brain images

This paper proposes a fully automated method for MR brain image segmentation into Gray Matter, White Matter and Cerebro‐spinal Fluid. It is an extension of Fuzzy C Means Clustering Algorithm which overcomes its drawbacks, of sensitivity to noise and inhomogeneity. In the conventional FCM, the membership function is computed based on the Euclidean distance between the pixel and the cluster center. It does not take into consideration the spatial correlation among the neighboring pixels. This means that the membership values of adjacent pixels belonging to the same cluster may not have the same range of membership value due to the contamination of noise and hence misclassified. Hence, in the proposed method, the membership function is convolved with mean filter and thus the local spatial information is incorporated in the clustering process. The method further includes pixel re‐labeling and contrast enhancement using non‐linear mapping to improve the segmentation accuracy. The proposed method is applied to both simulated and real T1‐weighted MR brain images from BrainWeb and IBSR database. Experiments show that there is an increase in segmentation accuracy of around 30% over the conventional methods and 6% over the state of the art methods.