Miracle-dz/UniFAR-FTUs huggingface dataset:
Pharmacokinetics and pharmacodynamics of febuxostat under fasting conditions in healthy individuals

The aim of the present study was to investigate the pharmacokinetic and pharmacodynamic characteristics of febuxostat following the administration of single and multiple oral doses under fasting conditions to healthy individuals. Thirty-six healthy subjects were randomly divided into three groups, each containing 12 subjects (six male and six female) as follows: Group A, treated with a single oral dose of febuxostat (40 mg); group B, treated with a single oral dose of febuxostat (80 mg) followed by multiple oral doses of febuxostat for 7 days; and group C, treated with a single oral dose of febuxostat (120 mg). Blood samples were collected, and the plasma drug levels and serum uric acid (UA) concentrations were determined by clinical laboratory testing. Febuxostat displayed a linear pharmacokinetic profile for oral doses of 40 to 120 mg. Drug accumulation was not detected following multiple oral doses. When febuxostat was administered as single doses of 40, 80 and 120 mg, the 24-h UA concentration (UA24) values displayed a linear correlation with the dosage. The relationship between UA24 and the three single dose levels (40, 80 and 120 mg) was analyzed. The difference in UA24 between every single dose was significant (P<0.05). After 3 and 7 days of dosing, reductions of 46.67 and 52.69%, respectively, were observed in UA24. On day 7 of dosing, the mean reduction in the UA concentration was 51.83±7.00%. This study demonstrates that febuxostat reduces serum UA concentrations in a dose-linear manner.
SCTP Extension for EGPRS/WLAN Handover Data

Multistreaming and multihoming SCTP features give better performance than TCP for the transport of signaling in wired networks. More recently, some solutions have been defined for wireless environment (Xing et al., 2002), mobile SCTP (mSCTP) is a wireless extension that was proposed to take benefit from the multihoming feature for hand off. In this paper we use SCTP's multihoming feature and define a new type of control chunk in order to retrieve radio information from mobile and to use this information to improve the performance of SCTP in handoff situation. We propose modifications of the SCTP congestion control algorithms to take into account information sent by mobile to the network (GGSN) via QoS_Measurement_Chunk. This new mechanism is useful to perform inter RAT handover for data. The example studied here is between EGPRS and WLAN. The results obtained are compared with the standard SCTP and present an improvement of performance especially in terms of throughput
Learning to Aggregate Information for Sequential Inferences

We consider the problem of training a binary sequential classifier under an error rate constraint. It is well known that for known densities, accumulating the likelihood ratio statistics is time optimal under a fixed error rate constraint. For the case of unknown densities, we formulate the learning for sequential detection problem as a constrained density ratio estimation problem. Specifically, we show that the problem can be posed as a convex optimization problem using a Reproducing Kernel Hilbert Space representation for the log-density ratio function. The proposed binary sequential classifier is tested on synthetic data set and UC Irvine human activity recognition data set, together with previous approaches for density ratio estimation. Our empirical results show that the classifier trained through the proposed technique achieves smaller average sampling cost than previous classifiers proposed in the literature for the same error rate.
1 On-line EM with Weight-Based Forgetting

In the on-line version of the EM algorithm introduced by Sato and Ishii (2000), a timedependent discount factor is introduced for forgetting the effect of the old posterior values obtained with an earlier, inaccurate estimator. In their approach, forgetting is uniformly applied to the estimators of each mixture component depending exclusively on time, irrespective of the weight attributed to each unit for the observed sample. This causes an excessive forgetting in the less frequently sampled regions. To address this problem we propose a modification of the algorithm that involves a weight-dependent forgetting, different for each mixture component, in which old observations are forgotten according to the actual weight of the new samples used to replace older values. A comparison of the time-dependent versus the weight-dependent approach shows that the last one improves the accuracy of the approximation and exhibits a much greater stability.
Molecular Cues Guiding Matrix Stiffness in Liver Fibrosis

Tissue and matrix stiffness affect cell properties during morphogenesis, cell growth, differentiation, and migration and are altered in the tissue remodeling following injury and the pathological progression. However, detailed molecular mechanisms underlying alterations of stiffness in vivo are still poorly understood. Recent engineering technologies have developed powerful techniques to characterize the mechanical properties of cell and matrix at nanoscale levels. Extracellular matrix (ECM) influences mechanical tension and activation of pathogenic signaling during the development of chronic fibrotic diseases. In this short review, we will focus on the present knowledge of the mechanisms of how ECM stiffness is regulated during the development of liver fibrosis and the molecules involved in ECM stiffness as a potential therapeutic target for liver fibrosis.
Investigating the Use of Liquisolid Compacts Technique to Minimize the Influence of pH Variations on Loratadine Release

Loratadine is a class II water-insoluble drug and its dissolution rate and, consequently, absorption are dependent on the gastrointestinal pH. The resulting very high variability in bioavailability and related inter- and intra-subject absorption variations present a major challenge that hinders the realization of an effective and uniform therapy. Among the several techniques that have been used to minimize pH dependency of dissolution rate, liquisolid compacts technique can be suggested as a promising solution. In this study, it was hypothesized that the formulation of loratadine using liquisolid compacts technique may reduce the effect of pH variation on the drug dissolution rate. Solubilities of loratadine in propylene glycol, Tween 80, and polyethylene glycol 400 were first measured and propylene glycol was selected as for producing the highest solubility among the tested solvents. Several liquisolid tablet formulations containing various ratios of drug: propylene glycol (5%, 10%, and 20% w/w) were prepared. The ratio of microcrystalline cellulose (carrier) to silica (coating powder material) was kept constant in all formulations. The dissolution behavior of loratadine from liquisolid compacts was investigated in several buffered media with different pH values (pH 1.2, 2.5, and 5). The results showed that the drug release rates produced by liquisolid compacts were significantly higher and less affected by pH variation compared with conventionally made (direct compression) and commercial (Clarityn) tablets. In conclusion, liquisolid compacts technique may be used as a tool to minimize the effects of pH variation on the dissolution rate of drugs with poor water solubility.
Inhibition of Bax-Induced Cytochrome c Release from Neural Cell and Brain Mitochondria by Dibucaine and Propranolol

BH3 (Bcl-2 homology 3)-only proteins of the Bcl-2 family activate Bax or Bak during apoptosis to promote the release of pro-death factors sequestered in the mitochondrial intermembrane space. Previous results demonstrated that a synthetic BH3 peptide mimics the ability of the BH3-only protein Bid to promote Bax insertion and cytochrome c (cyt c) release from neural cell mitochondria. However, the BH3 peptide was deficient in promoting cyt c release from mitochondria without associated Bax, such as adult rat brain mitochondria. This study tested the hypothesis that the amphiphilic membrane-active cationic drugs dibucaine and propranolol block BH3 peptide-initiated cytc efflux by preventing the integration of Bax into the mitochondrial outer membrane. BH3 peptide-initiated release of cytc from GT1-7 neural cell mitochondria was inhibited by dibucaine and propranolol at concentrations of 100–300 μm. Recombinant Bax (100 nm) alone did not release cyt c from adult rat brain mitochondria; however, when BH3 peptide or caspase-8 cleaved Bid (cBid) was added, robust cyt c release was achieved that was inhibited completely by 200 μm dibucaine or propranolol. These drugs at similar concentrations also inhibited release of entrapped 10 kDa dextrans from protein-free liposomes treated with Bax and cBid. Contrary to the hypothesis that dibucaine and propranolol act by inhibiting the insertion of Bax into the mitochondrial outer membrane, membrane insertion of Bax was not inhibited in mitochondria or liposomes, indicating a mechanism of drug action downstream from this event. These results suggest that dibucaine and propranolol inhibit Bax-induced permeability changes through a direct interaction with the lipid membrane and present a novel target for the development of neuroprotective, antiapoptotic therapeutics.
Identifying Personal Health Information Using Support Vector Machines

We explore the use of Support Vector Machines to recognize personal health information in medical discharge summaries. In addition to the basic token level features, we use entities recognized by an information extraction system designed for newswire text, plus a set of rules that incorporate entity-specific knowledge. The results on the unseen test dataset show that the SVM model can be easily adapted to a new domain with minimal work and achieve good performance (0.9869, the weighted F measure). The proposed new features also contribute to improving the accuracy of entity identification.
Fuzzy expert system for automatic wavelet shrinkage procedure selection for noise suppression

Signal processing is an indispensable issue of several technical areas. Wavelet shrinkage, i.e. thresholding in the wavelet coefficient domain, has been successfully used for signal and image noise removal problems. Although, the selection of the suitable wavelet threshold procedure is still a challenging task, because the applied method has significant impact on the result. Furthermore, the specific choice of wavelet, decomposition level and threshold rule, etc., allows a wide variability of the shrinkage method. This paper presents a new supervisory fuzzy expert system for automatic wavelet shrinkage method selection for noise suppression of unknown signals. Simulation results show efficient performance of the system.
Security Analysis of Geoencryption : A Case Study Using Loran

The term “geoencryption” or “location-based encryption” refer to a security algorithm that limits the access or decryption of information content to specified locations and/or times. The algorithm does not replace any of the conventional cryptographic algorithms, but instead adds an additional layer of security. Loran is chosen as a case study to implement geoencryption due to its many properties that are beneficial to this protocol. Loran’s stationary transmitters result in many location dependent parameters. Low frequency and high power signal can reach places like urban canyons and indoor environments. Enhanced Loran can provide a data channel useful for geoencryption. In order to evaluate the effectiveness of Loran for geoencryption we need to perform two tasks: 1) build a testbed to implement geoencryption protocol, and 2) examine the performance and security of the system. The prototype of geoencryption demonstration was built and further refinements are needed. To accomplish the second task, a threat model is developed and analyzed using the testbed built in the first task. In this threat model we discussed false positives and false negatives of the system. The signal to noise ratio (SNR) provides as an important metric to judge the performance analysis. This paper describes the work on analyzing system performance using the designed threat model. In addition, some data collections were done using the geoencryption testbed. This paper also provides a comparison on the experimental results and analytical results.
Siim Technical Report Refutable Inductive Inference of Recursive Functions Refutable Inductive Inference of Recursive Functions

Learning of recursive functions refutably informally means that for every recursive function, the learning machine has either to learn this function or to refute it, that is to signal that it is not able to learn it. Three modi of making precise the notion of refuting are considered. We show that the corresponding types of learning refutably are of strictly increasing power, where already the most stringent of them turns out to be of remarkable topological and algorith-mical richness. Furthermore, all these types are closed under union, though in diierent strengths. Also, these types are shown to be diierent with respect to their intrinsic complexity; two of them do not contain function classes that are \most diicult" to learn, while the third one does. Moreover, we present several characterizations for these types of learning refutably. Some of these characterizations make clear where the refuting ability of the corresponding learning machines comes from and how it can be realized, in general. For learning with anomalies refutably, we show that several results from standard learning without refutation stand refutably. From this we derive some hierarchies for refutable learning. Finally, we prove that in general one cannot trade stricter refutability constraints for more liberal learning criteria.
SHARED DEMOCRACY AND PUBLIC SUPPORT FOR WAR : CAUSAL MECHANISMS

One of the most striking findings in political science is the democratic peace: the absence of war between democracies. Some authors attempt to explain this phenomenon by highlighting the role of public opinion. They observe that democratic leaders are beholden to voters and argue that voters oppose war because of its human and financial costs. This logic predicts that democracies should behave peacefully in general, but history shows that democracies avoid war primarily in their relations with other democracies. In this article we investigate not whether democratic publics are averse to war in general, but whether they are especially reluctant to fight other democracies. We embedded experiments in public opinion polls in the United States and the United Kingdom and found that individuals are substantially less supportive of military strikes against democracies than against otherwise identical autocracies. Moreover, our experiments suggest that shared democracy pacifies the public primarily by changing perceptions of threat and morality, not by raising expectations of costs or failure. These findings shed light on a debate of enduring importance to scholars and policy makers.
IR-IITBHU at TREC 2016 Open Search Track: Retrieving documents using Divergence From Randomness model in Terrier

In our participation at TREC 2016 Open Search Track which focuses on ad-hoc scienti(cid:28)c literature search, we used Terrier, a modular and a scalable Information Retrieval framework as a tool to rank documents. The organizers provided live data as documents, queries and user interactions from real search engine that were available through Living Lab API framework. The data was then converted into TREC format to be used in Terrier. We used Divergence from Randomness (DFR) model, speci(cid:28)cally, the Inverse expected document frequency model for randomness, the ratio of two Bernoulli’s processes for (cid:28)rst normalisation, and normalisation 2 for term frequency normalization with natural logarithm, i.e. , In_expC2 model to rank the available documents in response to a set of queries. Al-together we submit 391 runs for sites CiteSeerX and SSOAR to the Open Search Track via the Living Lab API framework. We received an ‘out-come’ of 0.72 for test queries and 0.62 for train queries of site CiteSeerX at the end of Round 3 Test Period where, the (cid:16)outcome(cid:17) is computed as: #wins / (#wins + #losses). A ‘win’ occurs when the participant achieves more clicks on his documents than those of the site and ‘loss’ otherwise. Complete relevance judgments is awaited at the moment. We look forward to getting the users’ feedback and work further with them.
Structure of the human telomere in Na+ solution: an antiparallel (2+2) G-quadruplex scaffold reveals additional diversity

Single-stranded DNA overhangs at the ends of human telomeric repeats are capable of adopting four-stranded G-quadruplex structures, which could serve as potential anticancer targets. Out of the five reported intramolecular human telomeric G-quadruplex structures, four were formed in the presence of K+ ions and only one in the presence of Na+ ions, leading often to a perception that this structural polymorphism occurs exclusively in the presence of K+ but not Na+. Here we present the structure of a new antiparallel (2+2) G-quadruplex formed by a derivative of a 27-nt human telomeric sequence in Na+ solution, which comprises a novel core arrangement distinct from the known topologies. This structure complements the previously elucidated basket-type human telomeric G-quadruplex to serve as reference structures in Na+-containing environment. These structures, together with the coexistence of other conformations in Na+ solution as observed by nuclear magnetic resonance spectroscopy, establish the polymorphic nature of human telomeric repeats beyond the influence of K+ ions.
Point of View Species and Phylogenetic Nomenclature

Species and Phylogenetic Nomenclature NICO CELLINESE1,∗ , DAVID A. BAUM2, AND BRENT D. MISHLER3 1Florida Museum of Natural History, University of Florida, 354 Dickinson Hall, Gainesville, FL 32611-7800; 2Department of Botany, University of Wisconsin-Madison, 430 Lincoln Drive, Madison, WI 53706, USA; and 3University and Jepson Herbaria and Department of Integrative Biology, University of California, Berkeley, CA 94720, USA; ∗Correspondence to be sent to: Florida Museum of Natural History, University of Florida, 354 Dickinson Hall, Gainesville, FL 32611-7800, USA; E-mail: ncellinese@flmnh.ufl. edu.
Mechanism Design for Personalized Recommender Systems

Strategic behaviour from sellers on e-commerce websites, such as faking transactions and manipulating the recommendation scores through artificial reviews, have been among the most notorious obstacles that prevent websites from maximizing the efficiency of their recommendations. Previous approaches have focused almost exclusively on machine learning-related techniques to detect and penalize such behaviour. In this paper, we tackle the problem from a different perspective, using the approach of the field of mechanism design. We put forward a game model tailored for the setting at hand and aim to construct truthful mechanisms, i.e. mechanisms that do not provide incentives for dishonest reputation-augmenting actions, that guarantee good recommendations in the worst-case. For the setting with two agents, we propose a truthful mechanism that is optimal in terms of social efficiency. For the general case of m agents, we prove both lower and upper bound results on the effciency of truthful mechanisms and propose truthful mechanisms that yield significantly better results, when compared to an existing mechanism from a leading e-commerce site on real data.
A user profiling component with the aid of user ontologies

What follows is a contribution to the field of user modeling for adaptive teaching and learning programs especially in the medical field. The paper outlines existing approaches to the problem of extracting user information in a form that can be exploited by adaptive software. We focus initially on the so-called stereotyping method, which allocates users into classes adaptively, reflecting characteristics such as physical data, social background, and computer experience. The user classifications of the stereotyping method are however ad hoc and unprincipled, and they can be exploited by the adaptive system only after a large number of trials by various kinds of users. We argue that the remedy is to create a database of user ontologies from which readymade taxonomies can be derived in such a way as to enable associated software to support a variety of different types of users.
Clustering e-Banking Customer using Data Mining and Marketing Segmentation

In Thailand e-banking has been offered by various financial institutes including Thai commercial banks and government banks. However, e-banking in Thailand is not widely used and accepted as in other countries. Accordingly, the study of e-banking is scantly due to the limitation of data confidentiality. This study uses data mining techniques to analyse historical data of e-banking usages from a commercial bank in Thailand. These techniques including SOMS, K-Mean algorithm and marketing techniques-RFM analysis are used to segment customers into groups according to their personal profiles and e-banking usages. Then Apriori algorithm is applied to detect the relationships within features of e-banking services. Typically, results of this study are presented and can be used to generate new service packages which are customised to each segment of e-banking users.
Reporting Quality of Social and Psychological Intervention Trials: A Systematic Review of Reporting Guidelines and Trial Publications

Background Previous reviews show that reporting guidelines have improved the quality of trial reports in medicine, yet existing guidelines may not be fully suited for social and psychological intervention trials. Objective/Design We conducted a two-part study that reviewed (1) reporting guidelines for and (2) the reporting quality of social and psychological intervention trials. Data Sources (1) To identify reporting guidelines, we systematically searched multiple electronic databases and reporting guideline registries. (2) To identify trials, we hand-searched 40 journals with the 10 highest impact factors in clinical psychology, criminology, education, and social work. Eligibility (1) Reporting guidelines consisted of articles introducing a checklist of reporting standards relevant to social and psychological intervention trials. (2) Trials reported randomised experiments of complex interventions with psychological, social, or health outcomes. Results (1) We identified 19 reporting guidelines that yielded 147 reporting standards relevant to social and psychological interventions. Social and behavioural science guidelines included 89 standards not found in CONSORT guidelines. However, CONSORT guidelines used more recommended techniques for development and dissemination compared to other guidelines. (2) Our review of trials (n = 239) revealed that many standards were poorly reported, such as identification as a randomised trial in titles (20% reported the information) and abstracts (55%); information about blinding (15%), sequence generation (23%), and allocation concealment (17%); and details about actual delivery of experimental (43%) and control interventions (34%), participant uptake (25%), and service environment (28%). Only 11 of 40 journals referenced reporting guidelines in “Instructions to Authors. ” Conclusion Existing reporting guidelines have important limitations in content, development, and/or dissemination. Important details are routinely missing from trial publications; most leading journals in social and behavioural sciences do not ask authors to follow reporting standards. Findings demonstrate a need to develop a CONSORT extension with updated standards for social and psychological intervention trials.