Miracle-dz/UniFAR-FTUs huggingface dataset:
Impairments in Brain Perfusion, Metabolites, Functional Connectivity, and Cognition in Severe Asymptomatic Carotid Stenosis Patients: An Integrated MRI Study

Carotid artery stenosis without transient ischemic attack (TIA) or stroke is considered as “asymptomatic. ” However, recent studies have demonstrated that these asymptomatic carotid artery stenosis (aCAS) patients had cognitive impairment in tests of executive function, psychomotor speed, and memory, indicating that “asymptomatic” carotid stenosis may not be truly asymptomatic. In this study, when 19 aCAS patients compared with 24 healthy controls, aCAS patients showed significantly poorer performance on global cognition, memory, and executive function. By utilizing an integrated MRI including pulsed arterial spin labeling (pASL) MRI, Proton MR Spectroscopy (MRS), and resting-state functional MRI (R-fMRI), we also found that aCAS patients suffered decreased cerebral blood flow (CBF) mainly in the Left Frontal Gyrus and had decreased NAA/Cr ratio in the left hippocampus and decreased connectivity to the posterior cingulate cortex (PCC) in the anterior part of default mode network (DMN).
Hybrid Wind Speed Prediction Based on a Self-Adaptive ARIMAX Model with an Exogenous WRF Simulation

Wind speed forecasting is difficult not only because of the influence of atmospheric dynamics but also for the impossibility of providing an accurate prediction with traditional statistical forecasting models that work by discovering an inner relationship within historical records. This paper develops a self-adaptive (SA) auto-regressive integrated moving average with exogenous variables (ARIMAX) model that is optimized very-short-term by the chaotic particle swarm optimization (CPSO) algorithm, known as the SA-ARIMA-CPSO approach, for wind speed prediction. The ARIMAX model chooses the wind speed result from the Weather Research and Forecasting (WRF) simulation as an exogenous input variable. Further, an SA strategy is applied to the ARIMAX process. When new information is available, the model process can be updated adaptively with parameters optimized by the CPSO algorithm. The proposed SA-ARIMA-CPSO approach enables the forecasting process to update training information and model parameters intelligently and adaptively. As tested using the 15-min wind speed data collected from a wind farm in Northern China, the improved method has the best performance compared with several other models.
Stirred vessel cultures of rat brain cells aggregates: Characterization of major metabolic pathways and cell population dynamics

We report a study on neural metabolism of long‐term three‐dimensional cultures of rat embryonic brain cells in stirred vessels. Our experimental setup was optimized to keep viable aggregate cultures with neuronal maintenance for up to 44 days. Results show that aggregate size and shape could be hydrodynamically controlled depending on the impeller design, avoiding necrotic centers or significant losses in cell viability. Aggregates were composed mainly of neurons until day 16, whereas an effective growth of the glial population was observed after day 21. Cell metabolic status was evaluated by quantification of several metabolites in the culture medium; amino acid metabolism was used as a marker of metabolic interrelationships between neural cell types. Furthermore, 13C‐NMR spectroscopy was used on day 31 to explore specific metabolic pathways: incubation with [1‐13C]glucose for 45 hr produced an increase in label incorporation in extracellular alanine, lactate, and glutamine, reflecting mainly astrocytic metabolism. The contribution of anaplerotic vs. oxidative pathways for glutamine synthesis was determined: a 92% reduction in the pyruvate carboxylase flux during the first 41 hr of incubation suggested a decrease in the need for replacing tricarboxylic acid cycle intermediates. We believe that our data corroborate the aggregating cultures as an attractive system to analyze brain cell metabolism being a valuable tool to model metabolic fluxes for in vitro brain diseases. © 2007 Wiley‐Liss, Inc.
Dynamic Social Networks Logic

We introduce a general framework for reasoning about dynamic processes within social networks, such as diffusion phenomena. First, we define the new Dynamic Social Networks Logic, a dynamic extension of standard hybrid modal logic. We then provide a complete axiomatization for this logic and give a terminating and complete tableau system for it. Finally, we show how to apply the framework to dynamic processes documented in social networks analysis.
Comparative phylogeography in marginal seas of the northwestern Pacific

The maturation of marine phylogeography depends on integration of comparative information across different regions globally. The northwestern Pacific, characterized by unique tectonic setting, however, is still underrepresented. This study seeks to highlight its phylogeographical history based on the available population data, focusing on three seas: the East China Sea (ECS), the South China Sea (SCS) and the Sea of Japan (SOJ). We first conducted a literature survey to evaluate current research efforts and then reanalysed the population structure, historical demography and genealogy for two selections of studies (namely ‘the ECS category’ and ‘the multiple‐sea category’) to elucidate the evolutionary processes within and across the seas, respectively. For the ECS category, the meta‐analyses revealed most studies displayed a shallow phylogeny, indicating a single origin from the sea. Significant population structure was commonplace, particularly in molluck and crustacean studies, with proportions of 89% and 80%, respectively. Nearly all studies selected showed signals of population expansion: the times estimated were closely linked to a period of ~120–140 Kya rather than the last glacial maximum. For the latter category, divergent intraspecific lineages appeared among seas and overlapped in the adjacent regions, a pattern implying each sea had served as an independent refugium during glaciations. The genetic splits, however, were estimated to arise from separate events dating from late Miocene to middle Pleistocene. As phylogeography is still in its infancy in the region, more effort is needed to test and complement the general rules abstracted here. Finally, challenges and prospects were discussed to accelerate further research.
BZP-‘Party pills’, populism and prohibition: Exploring global debates in a New Zealand context

In New Zealand, the debates surrounding legal highs have been developing for approximately a decade. New Zealand’s historical grappling with the problem of legal highs reflects a global problem in addressing the issues related to new psychoactive substances. The focus of this article is the prohibition of BZP-based party pills under the Misuse of Drugs (Classification of BZP) Amendment Act, 2008 (hereafter the 2008 Act). This article reports on a qualitative study of the banning of BZP-based party pills in New Zealand, using thematic analysis of the discourses contained in the 2007 Parliamentary Bill readings of the 2008 Act. Six key themes were identified from the bill readings: prohibition is not an effective way to deal with drug use; BZP has a ‘gateway effect’; availability and accessibility means young people can access BZP-PPs too readily; young people are at risk; BZP has contributed to establishing a pill popping culture in New Zealand; and BZP has the potential for harm/has a moderate risk of harm. The thematic analysis revealed that evidence was often not fully represented in parliamentary debates, and that many of the concerns raised about BZPPs could have been dealt with through regulation rather than prohibition. A punitive moral populism aimed at drug use and drug users was also identified, driven by fears of drug using groups, and the symbolism associated with drug use.
Landcover classification with self-taught learning on archetypal dictionaries

This paper introduces archetypal dictionaries for a self-taught learning framework for the application of landcover classification. Self-taught learning, an unsupervised representation learning method, is exploited to learn low-dimensional and discriminative higher-level features, which are used as input into a classification algorithm. Experiments are conducted using a multi-spectral Landsat 5 TM image of a study area in the north of Novo Progresso located in South America. Our results confirm that self-taught learning with archetypal dictionaries provide features, which can be used as input into a linear logistic regression classifier. The obtained classification accuracies are comparable to kernel-based classifier using the original features.
Reverse Taxonomy for Elucidating Diversity of Insect-Associated Nematodes: A Case Study with Termites

Background The molecular operational taxonomic unit (MOTU) has recently been applied to microbial and microscopic animal biodiversity surveys. However, in many cases, some of the MOTUs cannot be definitively tied to any of the taxonomic groups in current databases. To surmount these limitations, the concept of “reverse taxonomy” has been proposed, i.e. to primarily list the MOTUs with morphological information, and then identify and/or describe them at genus/species level using subsamples or by re-isolating the target organisms. Nevertheless, the application of “reverse taxonomy” has not been sufficiently evaluated. Therefore, the practical applicability of “reverse taxonomy” is tested using termite-associated nematodes as a model system for phoretic/parasitic organisms which have high habitat specificity and a potential handle (their termite host species) for re-isolation attempts. Methodology Forty-eight species (from 298 colonies) of termites collected from the American tropics and subtropics were examined for their nematode associates using the reverse taxonomy method and culturing attempts (morphological identification and further sequencing efforts). The survey yielded 51 sequence types ( = MOTUs) belonging to 19 tentatively identified genera. Within these, four were identified based on molecular data with preliminary morphological observation, and an additional seven were identified or characterized from successful culturing, leaving eight genera unidentified. Conclusions That 1/3 of the genera were not successfully identified suggests deficiencies in the depth of available sequences in the database and biological characters, i.e. usually isolated as phoretic/parasitic stages which are not available for morphological identification, and too many undiscovered lineages of nematodes. Although there still is the issue of culturability of nematodes, culturing attempts could help to make reverse taxonomy methods more effective. However, expansion of the database, i.e., production of more DNA barcodes tied to biological information by finding and characterizing additional new and known lineages, is necessary for analyzing functional diversity.
Non-intrusive GMM-based speech quality measurement

We propose a non-intrusive speech quality measurement algorithm based on using Gaussian-mixture probability models of features of undegraded speech signals as an artificial reference model of "clean" speech behaviour. The consistency between the features of the test speech signal and the reference model serves as an indicator of speech quality. Consistency measures are calculated and mapped to an objective speech quality score using a multivariate adaptive regression splines function. Simulation results show that the proposed method offers accurate and yet low-complexity measurement of speech quality.
Using hybrid models to predict blood pressure reactivity to unsupported back based on anthropometric characteristics

Accurate blood pressure (BP) measurement is essential in epidemiological studies, screening programmes, and research studies as well as in clinical practice for the early detection and prevention of high BP-related risks such as coronary heart disease, stroke, and kidney failure. Posture of the participant plays a vital role in accurate measurement of BP. Guidelines on measurement of BP contain recommendations on the position of the back of the participants by advising that they should sit with supported back to avoid spuriously high readings. In this work, principal component analysis (PCA) is fused with forward stepwise regression (SWR), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and the least squares support vector machine (LS-SVM) model for the prediction of BP reactivity to an unsupported back in normotensive and hypertensive participants. PCA is used to remove multi-collinearity among anthropometric predictor variables and to select a subset of components, termed ‘principal components’ (PCs), from the original dataset. The selected PCs are fed into the proposed models for modeling and testing. The evaluation of the performance of the constructed models, using appropriate statistical indices, shows clearly that a PCA-based LS-SVM (PCA-LS-SVM) model is a promising approach for the prediction of BP reactivity in comparison to others. This assessment demonstrates the importance and advantages posed by hybrid models for the prediction of variables in biomedical research studies.
Denaturing high‐performance liquid chromatography (DHPLC)‐based prenatal diagnosis for tuberous sclerosis

Tuberous sclerosis (TSC) is a frequent autosomal‐dominant condition (affecting 1 in 6000 individuals) caused by various mutations in either the hamartin (TSC1) or the tuberin gene (TSC2). This allelic and non‐allelic heterogeneity makes genetic counseling and prenatal diagnosis difficult, especially as a significant proportion of TSC cases are due to de novo mutations. For this reason the identification of the disease causing mutation is mandatory for accurate counseling, yet current mutation detection methods such as single‐strand conformation polymorphism (SSCP) or denaturing gradient gel electrophoresis (DGGE) are labor intensive with limited detection efficiency. Denaturing high‐performance liquid chromatography (DHPLC) is a high‐throughput, semi‐automated mutation detection system with a reported mutation detection rate close to 100% for PCR fragments of up to 800 bp. We used a recently described DHPLC assay allowing the efficient detection of mutations in TSC1 to analyze the DNA extracted from a chorion villus sample in order to perform a prenatal diagnosis for TSC. The fetus was found not to have inherited the deleterious mutation and the DHPLC diagnosis was confirmed by haplotype analysis. This represents the first DHPLC‐based prenatal diagnosis of a genetic disease. Copyright © 2001 John Wiley & Sons, Ltd.
Mechanobehavioral Scores in Women with and without TMJ Disc Displacement

Cartilage fatigue may be a factor in the precocious development of degenerative changes in the temporomandibular joint (TMJ). This cross-sectional study estimated potential for cartilage fatigue via TMJ energy densities (ED) and jaw muscle duty factors (DF), which were combined to calculate mechanobehavioral scores (MBS) in women with (+) and without (–) bilateral TMJ disc displacement (DD). All subjects gave informed consent to participate and were examined using Diagnostic Criteria (DC) for Temporomandibular Disorders (TMD) and magnetic resonance (MR) and computed tomography (CT) images. Forty-seven subjects were categorized into +DD (n = 29) and –DD (n = 18) groups. Dynamic stereometry (MR images combined with jaw-tracking data) characterized individual-specific data of TMJ stress-field mechanics to determine ED (ED = W/Q mJ/mm3, where W = work done, Q = volume of cartilage) during 10 symmetrical jaw-closing cycles with a 20-N mandibular right canine load. Subjects were trained to record masseter and temporalis electromyography over 3 days and 3 nights. Root mean square electromyography/bite-force calibrations determined subject-specific masseter and temporalis muscle activities per 20-N bite-force (T20 N, µV), which defined thresholds. Muscle DF (DF = % duration of muscle activity/total recording time) were determined for a range of thresholds, and MBS (ED2 × DF) were calculated. Intergroup differences in ED, DF, and MBS were assessed via analyses of variance with Bonferroni and Tukey honest significant difference post hoc tests. Average ED for contralateral TMJs was significantly larger (P = 0.012) by 1.4-fold in +DD compared to –DD subjects. Average DF were significantly larger (all P < 0.01) for +DD compared to –DD subjects by 1.7-, 2.5-, and 1.9-fold for day, night, and overall, respectively. Daytime MBS were significantly larger (all P < 0.04) by up to 8.5-fold in +DD compared to –DD subjects. Significantly larger ED, DF, and MBS were shown in women with compared to women without bilateral TMJ DD.
An analytical model for S-ALOHA performance evaluation in M2M networks

The S-ALOHA (i.e. slotted-ALOHA) protocol is recently regaining interest in Lower Power Wide Area Networks (LPWAN) handling M2M traffic. Despite intensive studies since the birth of S-ALOHA, the special features of M2M traffic and requirements highlight the importance of analytical models taking into account performance-affecting factors and giving a thorough performance evaluation. Fulfilling this necessity is the main focus of this paper: we jointly consider the impact of capture effect, diversity of transmit power levels with imperfect power control. We propose a low-complexity but still accurate analytical model capable of evaluating S-ALOHA in terms of packet loss rate, throughput, energy-efficiency and average number of transmissions. The proposed model is able to facilitate dimensioning and design of S-ALOHA based LPWAN. The comparison between simulation and analytical results confirms the accuracy of our proposed model. The design guides about S-ALOHA based LPWAN deduced from our model are: the imperfect power control can be positive with capture effect and appropriate transmit power diversity strategy. The transmit power diversity strategy should be determined by jointly considering network charges level, power control precision and SINR threshold to achieve optimal performance of S-ALOHA.
Annotating Noun Argument Structure for NomBank

When complete, NomBank will provide annotation of noun arguments in Penn Treebank II (PTB). In PropBank, University of Pennsylvania annotators provide similar information for verbs. Given nominalization/verb mappings, the combination of NomBank and PropBank allows for generalization of arguments across parts of speech. This paper describes our annotation task including factors which make assigning role labels to noun arguments a challenging task.
Calcium Channel Blockers and Outcomes in Older Patients With Heart Failure and Preserved Ejection Fraction

Background—Little is known about associations of calcium channel blockers (CCBs) with outcomes in patients with heart failure and preserved ejection fraction (EF). Methods and Results—Of the 10 570 hospitalized patients with heart failure and preserved EF, ≥65 years, EF ≥40%, in the Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF; 2003–2004), linked to Medicare data (through December 31, 2008), 7514 had no prior history of CCB use. Of these, 815 (11%) patients received new discharge prescriptions for CCBs. Propensity scores for CCB initiation, calculated for each of the 7514 patients, were used to assemble a matched cohort of 1620 (810 pairs) patients (mean age, 80 years; mean EF, 56%; 65% women; 10% black) receiving and not receiving CCBs, balanced on 114 baseline characteristics. The primary composite end point of all-cause mortality or heart failure hospitalization occurred in 82% and 81% of patients receiving and not receiving CCBs (hazard ratio for CCBs, 1.03; 95% confidence interval, 0.92–1.14). Hazard ratios (95% confidence intervals) for all-cause mortality, heart failure hospitalization, and all-cause hospitalization were 1.05 (0.94–1.18), 1.05 (0.91–1.21), and 1.03 (0.93–1.14), respectively. Similar associations were observed when we categorized patients into those receiving amlodipine and nonamlodipine CCBs. Among 7514 prematch patients, multivariable-adjusted and propensity-adjusted hazard ratios (95% confidence interval) for primary composite end point were 1.03 (0.95–1.12) and 1.02 (0.94–1.11), respectively. Conclusions—In hospitalized older patients with heart failure, new discharge prescriptions for CCBs had no associations with composite or individual end points of mortality or heart failure hospitalization, regardless of the class of CCBs.
Neuronal Nitric Oxide Synthase in Neural Stem Cells Induces Neuronal Fate Commitment via the Inhibition of Histone Deacetylase 2

Active adult neurogenesis produces new functional neurons, which replace the lost ones and contribute to brain repair. Promoting neurogenesis may offer a therapeutic strategy for human diseases associated with neurodegeneration. Here, we report that endogenous neuronal nitric oxide synthase (nNOS) for neural stem cells (NSCs) or progenitors positively regulates neurogenesis. nNOS repression exhibits significantly decreased neuronal differentiation and nNOS upregulation promotes neurons production from NSCs. Using a quantitative approach, we show that instructive effect, that is instruction of NSCs to adopt a neuronal fate, contributes to the favorable effect of endogenous nNOS on neurogenesis. Furthermore, nNOS-mediated instruction of neuronal fate commitment is predominantly due to the reduction of histone deacetylase 2 (HDAC2) expression and enzymatic activity. Further investigation will be needed to test whether HDAC2 can serve as a new target for therapeutic intervention of neurodegenerative disorders.
High-Power Cycloconverter for Mining Applications: Practical Recommendations for Operation, Protection, and Compensation

This paper presents practical aspects related with the operation, compensation, and protection of high-power cycloconverters used in the mining industry. Practical recommendations related with startup, compensation requirements, operational characteristics, and unexpected shutdown process are described. Fuseless characteristics of modern cycloconverters are also discussed. Relevant current waveforms associated with the operation of a 20-MW synchronous motor semiautogenous grinding mill drive are presented, as well as current and voltage waveforms under fault operating conditions.
Decision-Making Involvement Scale for Individuals With Dementia and Family Caregivers

This report describes the development and preliminary psychometric properties of the Decision-Making Involvement Scale for individuals with dementia and family caregivers. Data were collected from 217 individuals with dementia and their respective caregivers. Principal axis factor analysis, Kendall τ, and Pearson correlations were used to determine the Decision-Making Involvement Scale's psychometric properties, mean differences of caregiver and individual with dementia, and the relationship between scores of Decision-Making Involvement Scale and measures of well-being. Analyses support a reliable, 1-factor solution of the Decision-Making Involvement Scale for both individuals with dementia and caregivers. Socio-demographic, impairment, and well-being variables are differentially related to the perceptions of how involved the individual with dementia is in decision making. The Decision-Making Involvement Scale provides useful information about daily decision making of an individual with dementia, and it shows promise as a means for understanding the relationship between decision-making involvement and well-being of individuals with dementia and caregivers.