Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of P311 in interleukin-1α-induced epithelial to myofibroblast transition in kidney tubular epithelial cells

Abstract Tubular epithelial-myofibroblast transition (TEMT) is an important process in renal tubulointerstitial fibrosis. Interleukin-1α (IL-1α) and transforming growth factor-β1 (TGF-β1) have been demonstrated to be key inducers of TEMT. In mouse embryonic fibroblast cells (NIH3T3), P311 protein induces phenotypic changes that are consistent to myofibroblast transformation. In the present study, we investigated the role of P311 gene and protein as well as potential mechanisms underlying TEMT in normal rat kidney tubular epithelial cells (NRK52E). Morphological and molecular changes were determined in NRK52E cells that were treated with IL-1α and/or P311 antibodies. The results showed that the NRK52E cells triggered by IL-1α became fibroblast-like cells, exhibiting hypertrophy of elongated and fusiform-shaped cells. IL-1α induced a time-dependent increase in P311 gene expression in NRK52E cells, with a peak time at 4 days. The expression levels of P311 gene were positively correlated with α-SMA and TGF-β1 gene expression levels. Anti-P311 antibody inhibited P311 and α-SMA expression in the presence of IL-1α. In contrast, anti-P311 antibody increased the expression of TGF-β1 gene in cells cultured with IL-1α. Therefore, P311 gene, together with α-SMA and TGF-β1 genes, was induced in the process of TEMT. P311 protein triggered by interleukin-1α may promote TEMT through a TGF-β1-independent pathway.
Questions to Improve Dialogue Flow and Speech Recognition in Spoken Dialogue Systems

Within human-machine conversation, clarification is vital and may consist of various forms, as it is may by due to many different effects on different levels of communication. In this paper, we present a strategy for detecting situations where a need for clarification exists in a natural spoken dialogue system. We define rule sets which enable us, via an anomaly analysis, to detect these critical situations. Through the use of such rule sets, we show that ist is possible to enhance the strategy in such a manner that more different situations are detected. In a user test, we evaluate the success of the strategy and show that strategies with explicit clarification improve the naturalness of human-machine interaction.
Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection

Bayesian On-line Changepoint Detection is extended to on-line model selection and non-stationary spatio-temporal processes. We propose spatially structured Vector Autoregressions (VARs) for modelling the process between changepoints (CPs) and give an upper bound on the approximation error of such models. The resulting algorithm performs prediction, model selection and CP detection on-line. Its time complexity is linear and its space complexity constant, and thus it is two orders of magnitudes faster than its closest competitor. In addition, it outperforms the state of the art for multivariate data.
Enhancing the development impact of migrant remittances and diaspora: the case of Viet Nam.

As most remittances either in cash or in kind are sent back to the migrants family members and relatives the most obvious impact of remittances is to support the subsistence and incomes of households in the places of origin. Remittances do not only increase the individual household income a part of them can also be channeled into investments and contribute to the growth of local economy. The use of remittances for private consumption may even stimulate demand which may create local markets and jobs for non-migrants. Although the proportion of total income from remittances may be less in poorer households the relative impact is likely to be greater. Among the poor a larger proportion of remittances may possibly be spent on consumption rather than on investment but remittances directly increase the household income of those families and amount in many cases to over 50 per cent of the total household income. (excerpt)
Civil Society Support: Is Community Development the Way Forward?

INTRAC is planning to hold an international conference in April 2005 on the theme of community development and civil society. Noticing changes in funding patterns in the international aid system and a growth of interest of multilateral and bilateral funders in grassroots community development initiatives, INTRAC plans to invite representatives from across the spectrum of civil society organizations and official funding bodies to present their own perspectives on the current state of community development. More specifically, INTRAC hopes to promote discussion of the link between development interventions at the grassroots and continuing efforts to strengthen civil society in developing and transition countries.
Ranolazine: an antianginal drug with antiarrhythmic properties

Ranolazine is an agent approved for the symptomatic treatment of chronic stable angina that inhibits the late inward sodium current (INaL). INaL amplitude is increased under several pathological conditions, including increased oxidative stress, myocardial ischemia, cardiac hypertrophy, heart failure, long-QT syndrome variant 3 and atrial fibrillation. Experimental and preliminary clinical evidence suggests that ranolazine may represent a new therapeutic strategy in the treatment of a broad spectrum of cardiac arrhythmias. This article reviews the role of the INaL and provides an update on experimental and clinical evidence supporting the efficacy and safety of ranolazine across a broad spectrum of arrhythmias.
Web User Profiling through Quiescent Semantic Analysis for Web Personalization

— Web personalization endorses the tailored Web pages or forecasts the personalized Web matters to Web users as per their particular observations. Fundamentally, user profile is generated for demonstrating particular user directional patterns derived from Web usage mining. This is done by corresponding the present active user session with the learned usage patterns. In this paper, a novel user profiling algorithm that makes use of usage patterns and a combined filtering approach is proposed. Firstly, similarity measure for Web user sessions is defined using cosine function of the user session over the quiescent semantic space. Then, the user sessions that exhibit similar navigational behaviors are clustered. The user profiles are viewed as the centroid of learned user session clusters. Whenever there is a fresh user session, the most corresponding user profile is chosen by determining distance between them. Then the top-N pages with the top support values are recommended. Experiments have been conducted on two data sets obtained from KDDCUP and RNSIT websites. The results show that the user profiles generated using the proposed method gives significant information for predicting and recommending the customized web pages for Web user.
Distribution-based Label Space Transformation for Multi-label Learning

Multi-label learning problems have manifested themselves in various machine learning applications. The key to successful multi-label learning algorithms lies in the exploration of inter-label correlations, which usually incur great computational cost. Another notable factor in multi-label learning is that the label vectors are usually extremely sparse, especially when the candidate label vocabulary is very large and only a few instances are assigned to each category. Recently, a label space transformation (LST) framework has been proposed targeting these challenges. However, current methods based on LST usually suffer from information loss in the label space dimension reduction process and fail to address the sparsity problem effectively. In this paper, we propose a distribution-based label space transformation (DLST) model. By defining the distribution based on the similarity of label vectors, a more comprehensive label structure can be captured. Then, by minimizing KL-divergence of two distributions, the information of the original label space can be approximately preserved in the latent space. Consequently, multi-label classifier trained using the dense latent codes yields better performance. The leverage of distribution enables DLST to fill out additional information about the label correlations. This endows DLST the capability to handle label set sparsity and training data sparsity in multi-label learning problems. With the optimal latent code, a kernel logistic regression function is learned for the mapping from feature space to the latent space. Then ML-KNN is employed to recover the original label vector from the transformed latent code. Extensive experiments on several benchmark datasets demonstrate that DLST not only achieves high classification performance but also is computationally more efficient.
Efficient search of the best warping window for Dynamic Time Warping

Time series classification maps time series to labels. The nearest neighbor algorithm (NN) using the Dynamic Time Warping (DTW) similarity measure is a leading algorithm for this task and a component of the current best ensemble classifiers for time series. However, NN-DTW is only a winning combination when its meta-parameter – its warping window – is learned from the training data. The warping window (WW) intuitively controls the amount of distortion allowed when comparing a pair of time series. With a training database of N time series of lengths L, a naive approach to learning the WW requires Θ(N·L) operations. This often results in NN-DTW requiring days for training on datasets containing a few thousand time series only. In this paper, we introduce FastWWSearch: an efficient and exact method to learn WW. We show on 86 datasets that our method is always faster than the state of the art, with at least one order of magnitude and up to 1000x speed-up.
The Role of Humor in Messaging about the MMR Vaccine

Outbreaks of vaccine-preventable diseases have increased due, in part, to misconceptions about vaccine safety (Kennedy et al., 2011). Extant literature has examined various messages designed to correct false beliefs about vaccination risks and to urge parents to vaccinate their children. The present study is designed to contribute to this literature by drawing on the broader research and theory on resistance to persuasion and correcting false beliefs. We examine the effects of a humorous (vs. non-humorous) message about the importance of the measles, mumps, and rubella vaccine on parents’ vaccine hesitancy. Results revealed that compared to a more serious message, a satirical message reduced reactance and led to greater perceptions of measles severity, which reduced vaccine hesitancy. Practical and theoretical implications are discussed.
[The manifestation of videonystamography in the patients with posterior circulation ischemia vertigo].

Objective:To investigate the changes of vedionystamography(VNG)in patients with posterior circulation ischemia vertigo(PCIV). Method:Fifty patients who complained of vertigo and imbalance with PCI were selected as experimental group for testing of visual nystamography(VNG). Thirty normal subjects were chosen as control group.The result was analyzed.Result:The results of VNG in PCIV group and the control group were compared.The abnormal ratio were as follows:(4%,0;P>0.05)for Spontaneous nystagmus,(68%,10%;P<0.01)for Saccade Test,(42.0%,6.7%;P<0.01)for Tracking Test,(44%,0;P<0.01)for Optokinetic Test,(78%,10%;P<0.01)for Positional Test,respectively.The intensity of positional nystagmus in those patients was(4.12±3.46)°/s,which was much higher than that of the control group(P<0.01). One or more abnormal findings for visual-oculomotor system examination were shown in 37 patients(74%). Conclusion:Both vestibular central and peripheral system can be involved in PCIV.VNG test has clinical significance in differential diagnosis and lesion location.The abnormal ratio of visual nystamography in PCIV group reaches 92%(46/50). These results suggest that VNG be used as an important accessory diagnostic tool for patients with PCIV.
Molecular Aspects of Glucose-6-Phosphate Dehydrogenase Deficiency in Iran

1. Department of Laboratory Sciences, Faculty of Medicine, Islamic Azad University, Tehran Medical Branch, Tehran, Iran 2. Department of Pathology, Zanjan University of Medical Sciences, Zanjan, Iran 3. Department of Hematology, Thalassemia and Hemoglobinopathy Research Center, Jundi Shapur University of Medical Sciences, Ahvaz, Iran 4. Department of Hematology, Division of Laboratory Hematology and Blood Banking, Tabriz University of Medical Sciences, Tabriz, Iran
Assessment of Cortical Interruptions in the Finger Joints of Patients With Rheumatoid Arthritis Using HR‐pQCT, Radiography, and MRI

Small cortical interruptions may be the first sign of an erosion, and more interruptions can be found in patients with rheumatoid arthritis (RA) compared with healthy subjects. First, we compared the number and size of interruptions in patients with RA with healthy subjects using high‐resolution peripheral quantitative CT (HR‐pQCT). Second, we investigated the association between structural damage and inflammatory markers on conventional radiography (CR) and MRI with interruptions on HR‐pQCT. Third, the added value of HR‐pQCT over CR and MRI was investigated. The finger joints of 39 patients with RA and 38 healthy subjects were examined through CR, MRI, and HR‐pQCT. CRs were scored using the Sharp/Van der Heijde method. MRI images were analyzed for the presence of erosions, bone marrow edema, and synovitis. HR‐pQCT images were analyzed for the number, surface area, and volume of interruptions using a semiautomated algorithm. Descriptives were calculated and associations were tested using generalized estimating equations. Significantly more interruptions and both a larger surface area and the volume of interruptions were detected in the metacarpophalangeal joints of patients with RA compared with healthy subjects (median, 2.0, 1.42 mm2, and 0.48 mm3 versus 1.0, 0.69 mm2, and 0.23 mm3, respectively; all p < 0.01). Findings on CR and MRI were significantly associated with more and larger interruptions on HR‐pQCT (prevalence ratios [PRs] ranging from 1.03 to 7.74; all p < 0.01) in all subjects, and were consistent in patients with RA alone. Having RA was significantly associated with more and larger interruptions on HR‐pQCT (PRs, 2.33 to 5.39; all p < 0.01), also after adjustment for findings on CR or MRI. More and larger cortical interruptions were found in the finger joints of patients with RA versus healthy subjects, also after adjustment for findings on CR or MRI, implying that HR‐pQCT imaging may be of value in addition to CR and MRI for the evaluation of structural damage in patients with RA. © 2018 The Authors. Journal of Bone and Mineral Research Published by Wiley Periodicals Inc.
Possible Role of Phthalate in the Pathogenesis of Endometriosis: In Vitro, Animal, and Human Data.

CONTEXT Although phthalates were shown to have several negative effects on reproductive function in animals, its role in the pathogenesis of endometriosis remains to be elucidated. OBJECTIVE We aimed to investigate the in vitro and in vivo effects of di-(2-ethylhexyl)-phthalate (DEHP) and to compare the urinary levels of several phthalate metabolites between women with and without endometriosis. DESIGN For experimental studies, we used endometrial cell culture and nonobese diabetic/severe combined immunodeficiency (NOD/SCID) mouse models. We also performed a prospective case-control study for human sample analyses. SETTING The study was conducted at an academic center. MAIN OUTCOME MEASURES The activities of matrix metalloproteinase (MMP)-2 and 9, cellular invasiveness, phosphorylation of extracellular signal-regulated kinase (Erk), and expression of p21-activated kinase 4 were analyzed in endometrial cells treated with DEHP. The implant size was compared between NOD/SCID mice fed with and without DEHP. Urinary concentrations of several phthalate metabolites were compared between women with and without endometriosis. RESULTS In vitro treatment of endometrial cells with DEHP led to significant increases of MMP-2 and 9 activities, cellular invasiveness, Erk phosphorylation, and p21-activated kinase 4 expression. The size of the endometrial implant was significantly larger in the NOD/SCID mice fed with DEHP compared with those fed with vehicle. The urinary concentration of mono (2-ethyl-5-hydroxyhexyl) phthalate, mono (2-ethyl-5-oxohexyl) phthalate, and mono (2-ethyl-5-carboxyphentyl) phthalate were significantly higher in women with endometriosis compared with controls. CONCLUSION These findings strongly suggest that exposure to phthalate may lead to establishment of endometriosis by enhancing invasive and proliferative activities of endometrial cells.
ShiftRoute: Achieving Location Privacy for Map Services on Smartphones

Map services, e.g., Google Maps, are gaining popularity for vehicle navigation. However, map service users have to provide sensitive information like precise geographic locations or detailed addresses, which are susceptible to accidental leakage or even data mining in the future. We find existing general-purposed location privacy protection mechanisms (LPPMs) not effective, when applied to map service on smartphones. This paper presents ShiftRoute, a new LPPM specially designed for map services on smartphones. ShiftRoute enables smartphone users to query a route between two endpoints on the map, without revealing any meaningful location information. The basic idea is to strategically shift the endpoints to nearby ones, such that: 1) the semantic meanings encoded in these endpoints (e.g., their addresses) change much, i.e., location privacy is largely protected; 2) the routes returned by map services change little, i.e., service usability is preserved. Specifically, we design a protocol to allow a mobile client to retrieve point of interests (POIs) close to the original endpoints, and an algorithm that selects shifted endpoints from these POIs, that achieves the privacy property of geo-indistinguishability. We implement an application of ShiftRoute on Android, and conduct experiments with real traces from a production map service. Experimental results show that ShiftRoute strikes a good tradeoff between location privacy and service usability.
A fast and flexible architecture for very large word n-gram datasets

Abstract This paper presents TrendStream, a versatile architecture for very large word n-gram datasets. Designed for speed, flexibility, and portability, TrendStream uses a novel trie-based architecture, features lossless compression, and provides optimization for both speed and memory use. In addition to literal queries, it also supports fast pattern matching searches (with wildcards or regular expressions), on the same data structure, without any additional indexing. Language models are updateable directly in the compiled binary format, allowing rapid encoding of existing tabulated collections, incremental generation of n-gram models from streaming text, and merging of encoded compiled files. This architecture offers flexible choices for loading and memory utilization: fast memory-mapping of a multi-gigabyte model, or on-demand partial data loading with very modest memory requirements. The implemented system runs successfully on several different platforms, under different operating systems, even when the n-gram model file is much larger than available memory. Experimental evaluation results are presented with the Google Web1T collection and the Gigaword corpus.
An Analysis of Financial Literacy and Household Saving among Fishermen in Indonesia

Financial literacy literatures suggested that people in many countries were financially illiterate. Even though financial literacy had quoted mostly in many research, this concept rarely examined on the population group of fishermen. The purpose of this study was to examine their personal financial literacy and the relationship between the financial literacy and household saving. The data for this study were gathered during January-June 2014 through questionnaires, conveniently distributed to a population group of fishermen in the age of 25 to 50 years old in Regency of Brebes, Tegal and Pekalongan, Central Java, Indonesia. Variables used in this study were financial literate and household saving. Results from 258 samples confirm that financial literacy was positively related to household saving. Eighty five percent of fishermen were illiterate and most of them had no saving account. We also find that financial inclusion played a crucial role to fishermen in saving their money. The results of this study suggested for policy makers to increase financial literacy of fishermen by implementing various financial education programs and financial inclusion by adding geographic penetration of banks and credit availability. DOI: 10.5901/mjss.2015. v6n5s5p216
Economic Growth and Electricity Consumption in Emerging Countries of Europa: An Ardl Analysis

Abstract The structure of energy intensity is not only important for the economists but also for the policymakers since it contributes to the policy debate on the link between energy use and economic growth and co-movement of the energy supply and growth policies. This study estimates the causal relationship between energy consumption and economic growth at per capita and aggregate levels for some transition countries in Europe; Albania, Belarus, Bulgaria, Czech Republic, Hungary, Lithuania, Poland, Romania and Slovakia. The study also presents the income elasticities of total energy demand by using the ARDL (Auto Regressive Distributed Lag) method.
ECAD functionality suitable for web-based optimised automated product variant generation

Product variant generation is fundamentally different in Electrical Computer-Aided Design (ECAD) rather than Mechanical Computer-Aided Design (MCAD). The difference lies in the logical relationships between ECAD components. It is not straightforward to select a previous product design to aid product variant generation. Therefore, a new methodology suitable for web-based delivery to support ECAD product variant design is described. Part of the methodology proposed is based on fuzzy logic to select previous ECAD designs from a database of case bases. An additional cost engineering module is proposed to provide the functionality of cost optimisation of the subset of the designs fulfilling a predefined criteria list. The other parts of the methodology have been fully implemented to allow automatic generation of designs in software.
Identifying RNA N6-Methyladenosine Sites in Escherichia coli Genome

N6-methyladenosine (m6A) plays important roles in a branch of biological and physiological processes. Accurate identification of m6A sites is especially helpful for understanding their biological functions. Since the wet-lab techniques are still expensive and time-consuming, it's urgent to develop computational methods to identify m6A sites from primary RNA sequences. Although there are some computational methods for identifying m6A sites, no methods whatsoever are available for detecting m6A sites in microbial genomes. In this study, we developed a computational method for identifying m6A sites in Escherichia coli genome. The accuracies obtained by the proposed method are >90% in both 10-fold cross-validation test and independent dataset test, indicating that the proposed method holds the high potential to become a useful tool for the identification of m6A sites in microbial genomes.