Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Determination: Hearing the Voices of Adults with Physical Disabilities.

Most current self-determination research focuses on adults with developmental disabilities but neglects adults with physical disabilities who depend on caregivers for many or most aspects of daily living. This study investigated the perceptions of 12 adults with physical disabilities related to their self-reported abilities and opportunities to practice self-determination, the obstacles they encountered and strategies they used to attain self-determination, and suggestions they made for facilitating self-determination in other individuals with physical disabilities. Interview results indicated that participants’ definitions of self-determination involved the importance of family, overcoming obstacles, and having the ability to persevere and attain goals. Facilitators of self-determination centered around four themes: (a) intrinsic factors; (b) support from families, individuals, and support networks; (c) opportunities; and (d) setting goals. Participants consistently recognized and identified the need to experience self-determination through various opportunities. Barriers to self-determination were grouped into two major categories: (a) internal barriers such as personal attributes and (b) external barriers such as financial issues, lack of accessibility to public facilities, and attitudinal and school-related hindrances. Discussion includes implications and
Improving the accuracy of Tagging Recommender System by Using Classification

Collaborative tagging system has become more and more popular and recently achieved widespread success due to flexibility and conceptual comprehensibility of tagging systems. Recommender system has the access to adopt tagging systems to achieve better performance. In this paper we consider that the items can be categorized into different classifications in which users show different interests. Here we adopt a two-step recommender method called TRSUC (Tagging Recommender Systems by Using Classification) which can be described as Inner-Class Recommender or Global Recommender in which we use tag as the intermediary entity between user and item. The experiment using MovieLens as dataset shows that we acquire better results than the recommender algorithms without classifying the items.
Instant Personalization via Clustering TV Viewing Patterns

Personal Television is here via the advent of a new class of devices called personal video recorders (PVRs). For a PVR to provide an enriched TV experience to the user, personalization is the key. One of the thorny problems facing a recommender system is that of cold-start: how does one capture the user preferences quickly and effectively and provide user-specific personalization "out-of-the-box"? To provide instant personalization, we propose a framework that allows a user to choose stereotypes, which reflect his/her TV viewing behavior closely, to seed their initial profiles and have a better "out-of-the-box" experience. The stereotypes have been derived by clustering TV viewing patterns of a sample set of 7 users who have been contributing their viewing histories to us for periods ranging from 5 months to 2 years. We conducted experiments by applying randomly chosen stereotypes to users in our sample set and measured the initial recommendation errors based on ground-truth data given by the users. The best initial errors were around 30%, which compared favorably with the best errors we have achieved to date from recommenders trained on user-specific data for a period of time.
Ions in the Brain: Normal Function, Seizures, and Stroke

PART I: IONS AND WATER IN THE BRAIN 1. The blood-brain barrier 2. The regulation of brain ions 3. Osmotic stress and the brain 4. The influence of ion concentrations on neuron function PART II: CEREBRAL SEIZURES 5. A primer of epileptiform seizures 6. Experimental seizures 7. Electrophysiology of seizures 8. Ions and seizures 9. Solving seizure mechanisms by simulations 10. Seizures, channels, genes 11. Mechanisms of action of antiepileptic drugs PART III: SPREADING DEPRESSION OF LEAO 12. Introduction to spreading depression: Extracellular electric signs 13. Ion fluxes during spreading depression 14. Membrane potential and input resistance during spreading depression 15. The mechanism of spreading depression 16. Solving the puzzle of spreading depression by computer simulation PART IV: PATHOLOGICAL BIOPHYSICS OF CEREBRAL HYPOXIA AND STROKE 17. Hypoxia, asphyxia and ischemia 18. Mechanism of early, reversible hypoxic synaptic failure 19. Irreversible hypoxic (ischemic) neuron injury
Hemodynamic Evaluation of the Patient with Portal Hypertension

Portal hypertension is a common syndrome that is characterized by a pathologic increase in portal venous pressure and by the formation of portosystemic collaterals that shunt part of the portal venous blood to the systemic circulation, bypassing the liver. Chronic liver disease is by far the most common cause of portal hypertension in Western countries. Parasitic infections, such as schistosomiasis, and idiopathic portal hypertension are common in other geographic areas.2," Massive gastrointestinal bleeding from ruptured esophageal and gastric varices is the main complication of portal hyperten~ion. ~ Other manifestations of the syndrome include ascites, hepatic encephalopathy, disturbances of the metabolism of drugs and endogenous compounds, bacteremia, splenomegaly, anemia, thrombocytopenia, and leukopenia. This article will review currently available
Algorithm for fault localization on a digital microfluidic biochip using particle swarm optimization technique

Commercial digital microfluidic biochip is facing an urge for design automation and test because of its complex multi-tasking paradigm. This work presents particle swarm optimization based technique for multiple fault detection in DMFB. The main objective of the algorithm is to localize the faults on a 2D biochip by circulation wash droplet, treated as the particle. PSO framework is modeled with the 2D biochip board as the search space for the particles. Multiple particles are generated from the reservoir and are circulated over the search space. Paths of the particles are guided by the velocity, which is decided upon previous knowledge of the particles' motion. The proposed work tries to find a time efficient procedure for fault localization with minimal number of particle encountered in the process. Simulation study shows that the process will enhance the reliability and accuracy in fault detection of the operational digital microfluidic biochips.
Effective framework for prediction of disease outcome using medical datasets: clustering and classification

The method of processing two algorithms within a single workflow, and hence the combined method, is called as hybrid computing. We propose a data mining framework comprising of two stages, namely clustering and classification. The first stage employs k-means algorithm on data and generates two clusters, namely cluster-0 and cluster-1. Instances in cluster-0 do not have disease symptoms and cluster-1 consists of instances with disease symptoms. The verification of valid grouping is then carried out by referring to the association of class labels in original datasets. Incorrectly classified instances are removed and remaining instances are used to build the classifier using C4.5 decision-tree algorithm with k-fold cross validation method. The framework was tested using eight datasets from the machine learning repository of the UCI. The proposed framework was evaluated for accuracy, sensitivity and specificity measures. Our framework obtained promising classification accuracy as compared to other methods found in the literature.
Automatic Detection of Name Disambiguation and Extracting Aliases for the Personal Name

An individual can be referred by multiple name aliases on the web. Extracting aliases of a name is important in information retrieval, sentiment analysis and name disambiguation. We propose a novel approach to find aliases of a given name using automatically extracted lexical pattern based approach. We exploit set of known names and their aliases as training data and extract lexical patterns that convey information related to aliases of names and extract large set of candidate aliases from text snippets returned by web search engine. We define numerous ranking scores to evaluate candidate aliases using three approaches: lexical pattern frequency, word co-occurrences in an anchor text and page counts on the web. We introduce notion of a word co-occurrence graph to represent mutual relations between words that appear in anchor text, words in anchor text are represented as nodes in the co-occurrence graph and edge is formed between nodes which link to the same url. The drawback of the existing method is the extracted alias names may be a original of some other person. So we introduce Email id extraction, by this we can overcome the problem. To construct a robust alias detection system, we integrate ranking scores through support vector machines using a single ranking function. Moreover, the aliases extracted using the proposed method are successfully utilized in information retrieval task to improve recall by 20 percent in a relation detection task.
A Microgrid Energy Management System and Risk Management Under an Electricity Market Environment

This paper presents a novel energy-management method for a microgrid that includes renewable energy, diesel generators, battery storage, and various loads. We assume that the microgrid takes part in a pool market and responds actively to the electricity price to maximize its profit by scheduling its controllable resources. To address various uncertainties, a risk-constrained scenario-based stochastic programming framework is proposed using the conditional value at risk method. The designed model is solved by two levels of stochastic optimization methods. One level of optimization is to submit optimal hourly bids to the day-ahead market under the forecast data. The other level of optimization is to determine the optimal scheduling using the scenario-based stochastic data of the uncertain resources. The proposed energy management system is not only beneficial for the microgrid and customers, but also applies the microgrid aggregator and virtual power plant. The results are shown to prove the validity of the proposed framework.
Voltage-Dependent Calcium Currents Are Enhanced in Nucleus of the Solitary Tract Neurons Isolated From Renal Wrap Hypertensive Rats

The nucleus of the solitary tract (NTS) is the central site of termination of baroreceptor afferents. We hypothesize that changes occur in voltage-gated calcium channels (VGCCs) within NTS neurons as a consequence of hypertension. Whole-cell patch-clamp recordings were obtained from adult normotensive (109±2 mm Hg; n=6 from 6 sham-operated and 31 nonsurgically treated) and hypertensive (158±6 mm Hg; n=24) rats. In some experiments, 4-(4-[dihexadecylamino]styryl)-N-methylpyridinium iodide was applied to the aortic nerve to visualize NTS neurons receiving baroreceptor synaptic contacts. Ba2+ currents (500 ms; −80 mV prepotential; 500 ms voltage steps in 5-mV increments to +15mV) peaked between −20 and −10 mV and were blocked by 100 &mgr;m of Cd2+. Peak VGCCs were not different comparing non-4-(4-[dihexadecylamino]styryl)-N-methylpyridinium iodide-labeled and 4-(4- [dihexadecylamino]styryl)-N-methylpyridinium iodide-labeled NTS neurons in hypertensive and normotensive rats. The peak VGCC was significantly greater in cells from hypertensive compared with normotensive rats for both non–DiA-labeled (P=0.02) and DiA-labeled (P=0.04) neurons. To separate high-voltage activated (HVA) and low-voltage activated (LVA) components of VGCCs, voltage ramps (−110 mV to +30 mV over 50 ms) were applied from a holding potential of −60 mV (LVA channels inactivated) and a holding potential of −100 mV (both LVA and HVA currents activated). HVA currents were subtracted from HVA+LVA currents to yield the LVA current. Peak LVA currents were not different between hypertensive (8.9±0.8 pA/pF) and normotensive (7.8±0.6 pA/pF) groups of NTS neurons (P=0.27). These results demonstrate that 4 weeks of renal wrap hypertension induce an increase in Ca2+ influx through HVA VGCCs in NTS neurons receiving arterial baroreceptor inputs.
Extracting Interest Tags for Non-famous Users in Social Network

Inferring interests of users in social network is important for many applications such as personalized search, recommender systems and online advertising. Most previous studies inferred users' interests based on text posted in social network, which is usually not related to their interests. In this paper, we propose a modified topic model, Bi-Labeled LDA with a term weighting scheme, to extract interest tags for users in social network. The proposed model utilize only users' relationship information without requirement for text information, and incorporates supervision into traditional LDA. Specifically, we introduce method to extract tags for non-famous user through their relationship with famous users in Twitter, and study why a non-famous user follows famous users simultaneously. Comparison with state-of-the-art methods on real dataset shows that our method is far more superior in terms of precision and recall of the extracted tag set, and also more applicable for many personalized applications. Besides, we find that a reasonable term weighting scheme can actually improve the performance further.
Speech Recognition by Wavelet Analysis

ABSTRACT In an effort to provide a more efficient representation of the speech signal, the application of the wavelet analysis is considered. This research presents an effective and robust method for extracting features for speech processing. Based on the time‐frequency multi‐resolution property of wavelet transform, the input speech signal is decomposed into various frequency channels. The major issues concerning the design of this Wavelet based speech recognition system are choosing optimal wavelets for speech signals, decomposition level in the DWT, selecting the feature vectors from the wavelet coefficients. More specifically automatic classification of various speech signals using the DWT is described and compared using different wavelets. Finally, wavelet based feature extraction system and its performance on an isolated word recognition problem are investigated. For the classification of the words, three layered feed forward network is used. General Terms
Recent Developments of Engineered Translational Machineries for the Incorporation of Non-Canonical Amino Acids into Polypeptides

Genetic code expansion and reprogramming methodologies allow us to incorporate non-canonical amino acids (ncAAs) bearing various functional groups, such as fluorescent groups, bioorthogonal functional groups, and post-translational modifications, into a desired position or multiple positions in polypeptides both in vitro and in vivo. In order to efficiently incorporate a wide range of ncAAs, several methodologies have been developed, such as orthogonal aminoacyl-tRNA-synthetase (AARS)–tRNA pairs, aminoacylation ribozymes, frame-shift suppression of quadruplet codons, and engineered ribosomes. More recently, it has been reported that an engineered translation system specifically utilizes an artificially built genetic code and functions orthogonally to naturally occurring counterpart. In this review we summarize recent advances in the field of ribosomal polypeptide synthesis containing ncAAs.
Synergistic Effect of Thrombin and CD40 Ligand on Endothelial Matrix Metalloproteinase-10 Expression and Microparticle Generation In Vitro and In Vivo

Objective—Thrombin induces CD40 ligand (CD40L) and matrix metalloproteinases (MMPs) under inflammatory/prothrombotic conditions. Thrombin and CD40L could modulate endothelial MMP-10 expression in vitro and in vivo. Methods and Results—Human endothelial cells were stimulated with thrombin (0.1–10 U/mL), CD40L (0.25–1 &mgr;g/mL), or their combination (thrombin/CD40L) to assess MMP-10 expression and microparticle generation. Thrombin/CD40L elicited higher MMP-10 mRNA (5-fold; P<0.001) and protein levels (4.5-fold; P<0.001) than either stimulus alone. This effect was mimicked by a protease-activated receptor-1 agonist and antagonized by hirudin, a-protease-activated receptor-1, &agr;-CD40L, and &agr;-CD40 antibodies. The synergistic effect was dependent on p38 mitogen-activated protein kinase and c-Jun N-terminal kinase-1 pathways. Thrombin also upregulated the expression of CD40 in endothelial cell surface increasing its availability, thereby favoring its synergistic effects with CD40L. In mice, thrombin/CD40L further increased the aortic MMP-10 expression. Septic patients with systemic inflammation and enhanced thrombin generation (n=60) exhibited increased MMP-10 and soluble CD40L levels associated with adverse clinical outcome. Endothelial and systemic activation by thrombin/CD40L and lipopolysaccharide also increased microparticles harboring MMP-10 and CD40L. Conclusion—Thrombin/CD40L elicited a strong synergistic effect on endothelial MMP-10 expression and microparticles containing MMP-10 in vitro and in vivo, which may represent a new link between inflammation/thrombosis with prognostic implications.
Classroom Discussion and Threaded Electronic Discussion: Learning In Two Arenas

Classroom discussion is an important teaching strategy because of its relation to the development of participatory citizenship, critical thinking, Discussion is particularly relevant in social studies education because of the mandate to prepare students for participatory democracy. Sev-have examined the distinctive nature of discussion itself. Those studies indicate that there are various types of discussion that vary in purpose, content, and format. In this article the author begins a look at two general " types " of discussion in schools: classroom discussion¾where face-to-face verbal interactions occur among students and teacher¾and threaded electronic discussion¾where the interactions occur electronically and asynchro-nously by way of a computer. Interest in this topic stems from the possibility that threaded discussions may be a promising format for discussing public issues in the classroom. Merry Merryfield (2000) provided several advantages that threaded discussions have over other electronic discussion formats (e.g., list serves, chat rooms). Merryfield suggested that threaded discussions are advantageous because they are linked to a course homepage, the instructor can control the structure of the discussions, and the " postings " provide a searchable database of student comments and interactions. While electronic threaded discussions are not commonplace in social studies classrooms, the technology needed to facilitate such discussions is not new or expensive. Still, examples of students engaging in threaded electronic discussions are hard to find in schools.
A repeat-dose thorough QT study of inhaled fluticasone furoate/vilanterol combination in healthy subjects

AIMS This study was designed as a thorough QT (TQT) study to evaluate the effects of fluticasone furoate(FF)/vilanterol (VI) in healthy subjects. Supportive data from a TQT study conducted with FF are also presented. METHODS This was a randomized, placebo-and positive-controlled, double-dummy, double-blind, four-way crossover study, in which healthy subjects (n = 85) were randomized to 7 days of once-daily treatment of FF/VI (200/25 or 800/100 μg) or placebo or single-dose oral moxifloxacin (single-blind, 400 mg). In the supportive TQT study, subjects (n = 40) were randomized to single-dose inhaled FF(4000 μg), oral moxifloxacin (400 mg) or placebo. RESULTS There was a lack of effect of FF/VI (200/25 μg) on QTcF (Fridericia's correction); all time-matched mean differences from baseline relative to placebo (0–24 h) were <5 ms, with upper 90% confidence intervals (CI) of <10 ms. At 800/100 μg, FF/VI had no significant clinicaleffect on QTcF except at 30 min postdose when the 90% CI was >10 ms [mean (90% CI), 9.6 ms (7.2, 12.0)]. No effect on QTci (individually corrected) was observed at either strength of FF/VI, with mean time-matched treatment differences <5 ms at all time points [upper 90% CIs <10 ms (0–24 h)]. Assay sensitivity was confirmed; moxifloxacin prolonged QTcF and QTci, with time-matched mean differences from baseline relative toplacebo of >10 ms (1–8 h postdose). CONCLUSIONS Repeat once-daily dosing of FF/VI (200/25 μg), which is the highest therapeutic strength used in phase III studies, is not associated with QTc prolongation in healthy subjects. Supratherapeutic strength FF/VI (800/100 μg) demonstrated a small transient effect on QTcF but not on QTci.
Residue cache: A low-energy low-area L2 cache architecture via compression and partial hits

L2 cache memories are being adopted in the embedded systems for high performance, which, however, increases energy consumption due to their large sizes. We propose a low-energy low-area L2 cache architecture, which performs as well as the conventional L2 cache architecture with 53% less area and around 40% less energy consumption. This architecture consists of an L2 cache and a small cache called residue cache. L2 and residue cache lines are half sized of the conventional L2 cache lines. Well compressed conventional L2 cache lines are stored only in the L2 cache while other poorly compressed lines are stored in both the L2 and residue caches. Although many conventional L2 cache lines are not fully captured by the residue cache, most accesses to them do not incur misses because not all their words are needed immediately, which are termed as partial hits in this paper. The residue cache architecture consumes much lower energy and area than conventional L2 cache architectures, and can be combined synergistically with other schemes such as the line distillation and ZCA. The residue cache architecture is also shown to perform well on a 4-way superscalar processor typically used in high performance systems.
OLI image atmospheric correction sensitivity to altitude, visibility and acquisition geometry

Atmospheric effects can damage surface information extraction from satellite images and correction using physically based models is a way to minimize these effects. This paper presents a sensitivity analysis of atmospheric correction of an OLI image using a base case from which the surface altitude, horizontal visibility and viewing geometry were varied. Results show that viewing geometry, target altitude and horizontal visibility affects the ground reflectance retrieval, mainly in the visible bands. Atmospheric effects decreased from the backscattering to the forward scattering while it decreased as target altitude increased. It is concluded that the use of average values of these correction parameters can be a problem when performing the atmospheric correction. It is recommended that care should be taken when using average values and preferably use correction that takes into account the within image variations of these parameters.
Anomaly Detection in Text: The Value of Domain Knowledge

We consider the problem of detecting anomalies from text data. Our hypothesis is that as with classical anomaly detection algorithms, domain-speciﬁc features are more important than the linguistic features. We employ the use of ﬁrst-order logic and demonstrate the effectiveness of useful domain knowledge in two domains. Our results show that the domain-speciﬁc features are more predictive and that the relational learning methods exhibit superior performance.