Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNA-27a Inhibits Cell Migration and Invasion of Fibroblast-Like Synoviocytes by Targeting Follistatin-Like Protein 1 in Rheumatoid Arthritis

Fibroblast-like synoviocytes (FLS) with aberrant expression of microRNA (miRNA) are critical pathogenic regulators in rheumatoid arthritis (RA). Previous studies have found that overexpression or silencing of miRNA can contribute to the development of miRNA-based therapeutics in arthritis models. In this study, we explored the effects of miR-27a on cell migration and invasion in cultured FLS from RA patients. We found that miR-27a was markedly downregulated in the serum, synovial tissue, and FLS of RA patients. Meanwhile, the expression of follistatin-like protein 1 (FSTL1) was upregulated, which suggests that FSTL1 plays a key role in RA development. The results of a Transwell assay showed that miR-27a inhibited FLS migration and invasion. However, miR-27a inhibition promoted the migration and invasion of FLS. In addition, the down-regulated expression of matrix metalloproteinases (MMP2, MMP9, and MMP13) and Rho family proteins (Rac1, Cdc42, and RhoA) was detected after treatment with miR-27a in RA-FLS by quantitative reverse transcription-PCR and western blot analysis. Then, a luciferase reporter assay validated that miR-27a targeted the 3-untranslated region (3′-UTR) of FSTL1. Moreover, miR-27a caused a significant decrease of FSTL1. In addition, the expression of TLR4 and NFκB was inhibited by miR-27a but increased by FSTL1 overexpression. In conclusion, we found that miR-27a inhibited cell migration and invasion of RA-FLS by targeting FSTL1 and restraining the TLR4/NFκB pathway.
Lycium barbarum Polysaccharide Prevents Focal Cerebral Ischemic Injury by Inhibiting Neuronal Apoptosis in Mice

Aims of the Study To investigate the neuroprotective effect of Lycium barbarum polysaccharide (LBP) on focal cerebral ischemic injury in mice and to explore its possible mechanism. Materials and Methods Male ICR mice were used to make the model of middle cerebral artery occlusion (MCAO) after intragastric administration with LBP (10, 20 and 40 mg/kg) and Nimodipine (0.4 mg/kg) for seven successive days. After 24 h of reperfusion, neurological scores were estimated and infarct volumes were measured by 2, 3, 5-triphenyltetrazolium chloride (TTC) staining. Morphological changes in ischemic brains were performed for hematoxylin-eosin (HE) staining. The number of apoptotic neurons was detected by TUNEL staining. The Bax, Bcl-2 protein expression and CytC, Caspase-3, -9 and cleaved PARP-1 activation were investigated by immunofluorescence and western-blot analysis. Results LBP (10, 20 and 40 mg/kg) treatment groups significantly reduced infract volume and neurological deficit scores. LBP also relieved neuronal morphological damage and attenuated the neuronal apoptosis. LBP at the dose of 40 mg/kg significantly suppressed overexpression of Bax, CytC, Caspase-3, -9 and cleaved PARP-1, and inhibited the reduction of Bcl-2 expression. Conclusions Based on these findings we propose that LBP protects against focal cerebral ischemic injury by attenuating the mitochondrial apoptosis pathway.
Content-Based Color Image Retrieval System Using Color Difference Features

In this paper, we propose a new color image retrieval scheme based on color features. The goal of this scheme is to effectively retrieve images similar to a query image in a color image database. In this scheme, a color image is first divided into three planes. Then the local features of the given image can be found by calculating the color difference of each plane. Thereafter, the color difference co-occurrence matrix (CDCOM) of each color image can be derived through these local features. The CDCOM is regarded as the global feature of the color image. Consequently, CDCOM is used to find images similar to the query image. Experiment results show that the proposed scheme can effectively retrieve the desired and similar images.
Improving Virtual Keyboards When All Finger Positions Are Known

Current virtual keyboards are known to be slower and less convenient than physical QWERTY keyboards because they simply imitate the traditional QWERTY keyboards on touchscreens. In order to improve virtual keyboards, we consider two reasonable assumptions based on the observation of skilled typists. First, the keys are already assigned to each finger for typing. Based on this assumption, we suggest restricting each finger to entering pre-allocated keys only. Second, non-touching fingers move in correlation with the touching finger because of the intrinsic structure of human hands. To verify of our assumptions, we conducted two experiments with skilled typists. In the first experiment, we statistically verified the second assumption. We then suggest a novel virtual keyboard using our observations. In the second experiment, we show that our suggested keyboard outperforms existing virtual keyboards.
An adaption of the schema theorem to various crossover and mutation operators for a music segmentation problem

The schema theorem provides theoretical background for the effectiveness of genetic algorithms and serves as a formal model to explain their success. It describes the functionality of genetic algorithms under very restrictive limitations of a canonical genetic algorithm which applies a binary alphabet, individuals of equal length, fitness-proportional selection, single-point crossover, and gene-wise mutation. Applications of genetic algorithms, however, are often based on noncanonical variations and, therefore, are not verified by the theory of the traditional theorem. This paper describes the adaption of the theorem for various other crossover and mutation operators focusing on the application of genetic algorithms to a music segmentation problem.
Virtual Surrounding Face Geocasting with Guaranteed Message Delivery for Ad Hoc and Sensor Networks

Geocasting in wireless sensor networks and ad hoc networks is the delivery of a message from a source to all the nodes in a given geographical region. The objectives of a geocasting protocol are two-folds: guaranteed message delivery and low transmission cost. Most of the existing protocols do not guarantee message delivery, and those that do incur a high transmission costs. In this paper, we introduce the idea of a virtual surrounding face (VSF), and present a geocasting protocol based on VSF. By using mathematical analyses and simulation studies, we show that the proposed protocol guarantees message delivery and has a significant lower transmission cost than the existing approaches.
Comparative safety, immunogenicity, and efficacy of several anti‐H5N1 influenza experimental vaccines in a mouse and chicken models (Testing of killed and live H5 vaccine)

Please cite this paper as: Gambaryan et al. (2011) Comparative safety, immunogenicity, and efficacy of several anti‐H5N1 influenza experimental vaccines in a mouse and chicken models. Parallel testing of killed and live H5 vaccine. Influenza and Other Respiratory Viruses 6(3), 188–195.
GLOBALLY OPTIMAL PERFORMANCE OF FEEDBACK CONTROL SYSTEMS WITH LIMITED COMMUNICATION OVER NOISY CHANNELS

A discrete time stochastic feedback control system consisting of a non-linear plant, a sensor, a controller, and a noisy communication channel between the sensor and the controller is considered. The sensor has limited memory and at each time, it transmits an encoded symbol over the channel and updates its memory. The controller receives a noise-corrupted copy of the transmitted symbol. It generates a control action based on all its past observations and all its past actions. This control action action is fed back to the plant. At each time instant the system incurs an instantaneous cost depending on the state of the plant and the control action. The objective is to choose encoding, memory update and control strategies to minimize: an expected total cost over a finite horizon, or an expected discounted cost over an infinite horizon, or an average cost per unit time over an infinite horizon. A solution methodology to obtain a sequential decomposition of the global optimization problem is developed. This solution methodology is extended to the case when the sensor makes an imperfect observation of the state of the plant.
Does a Better Education Make for Better Managers? An Empirical Examination of CEO Educational Quality and Firm Performance

This paper represents the first attempt, to our knowledge, to empirically examine the relationship between the quality of Chief Executive Officer (CEO) education and firm performance. This is an important question as many papers in the management literature have postulated that managers with higher educational attainment will be more adaptive and innovative, and more likely to possess other characteristics that may improve firm performance. We find four results in our analysis. First, using the mean entrance scores as proxies for the prestige of undergraduate and graduate programs, we find no evidence that firms with CEOs from more prestigious schools perform better than firms with CEOs from less prestigious schools. Second, we find that firms managed by CEOs with MBA or law degrees perform no better than firms with CEOs without graduate degrees. Third, we find some limited evidence that firms led by CEOs with non-MBA, non-law graduate degrees have slightly better risk-adjusted market performance than other firms. Fourth, we find that compensation is somewhat higher for CEOs who attended more prestigious schools.
Information Assurance in the SQoS Network

In the SQoS network as introduced in [1] and [2], the border router in every autonomous system (AS) provides customized security mechanisms to the incoming packets. Some serious problems have been recently raised particularly when there are one or more compromised routers that attempt to modify, delete, or fabricate any part or the whole packet into the SQoS network. The compromised router can either passively or actively perform the malicious activities against the forwarding packets. The SQoS network does not explicitly specify the method to detect whether the data contained in the packets have been tampered by the compromised routers or by the end host itself. We deliberate the threats and propose several methods to detect both the malicious routers and end hosts such that SQoS information and payload are authentic and integrity-protected.
Inception: Towards a Nested Cloud Architecture

Despite the increasing popularity of Infrastructure-as-aservice (IaaS) clouds, providers have been very slow in adopting a large number of innovative technologies, such as live VM migration, dynamic resource management, and VM replication. In this paper, we argue that the reasons are not only technical but also fundamental, due to lack of transparency and conflict of interest between providers and customers. We present our vision inception, a nested IaaS cloud architecture to overcome this impasse. Inception clouds are built entirely on top of the resources acquired from today’s clouds, and provide nested VMs to end users. We discuss the benefits, use cases, and challenges of inception clouds, and present our network design and prototype implementation.
Estimation of the false negative fraction of a diagnostic kit through Bayesian regression model averaging

In modelling we usually endeavour to find a single ‘best’ model that explains the relationship between independent and dependent variables. Selection of a single model fails to take into account the prior uncertainty in the model space. The Bayesian model averaging (BMA) approach tackles this problem by considering the set of all possible models. We apply BMA approach to the estimation of the false negative fraction (FNF) in a particular case of a two‐stage multiple screening test for bowel cancer. We find that after taking model uncertainty into consideration the estimate of the FNF obtained is largely dependent on the covariance structure of the priors. Results obtained when the Zellner g‐prior for the prior variance is used is largely influenced by the magnitude of g. Copyright © 2005 John Wiley & Sons, Ltd.
Semi-Supervised Learning for Asymmetric Graphs through Reach and Distance Diffusion

Semi-supervised learning algorithms are an indispensable tool when labeled examples are scarce and there are many unlabeled examples [Blum and Chawla 2001, Zhu et. al. 2003]. With graph-based methods, entities (examples) correspond to nodes in a graph and edges correspond to related entities. The graph structure is used to infer implicit pairwise affinity values (kernel) which are used to compute the learned labels. Two powerful techniques to define such a kernel are "symmetric" spectral methods and Personalized Page Rank (PPR). With spectral methods, labels can be scalably learned using Jacobi iterations, but an inherent limiting issue is that they are applicable to (undirected) graphs, whereas often, such as with like, follow, or hyperlinks, relations between entities are inherently asymmetric. PPR naturally works with directed graphs but even with state of the art techniques does not scale when we want to learn billions of labels. Aiming at both high scalability and handling of directed relations, we propose here and kernels. Our design is inspired by models for influence diffusion in social networks, formalized and spawned from the seminal work of [Kempe, Kleinberg, and Tardos 2003]. These models apply with directed interactions and are naturally suited for asymmetry. We tailor these models to define a natural asymmetric "kernel" and design highly scalable algorithms for parameter setting and label learning.
EEG-FMRI integration using a partially constrained tensor factorization

Simultaneous EEG-fMRI recording provides great opportunity to study the relationship between synchronous neuronal activity in EEG and blood oxygenation level dependent (BOLD) in fMRI. In this paper a novel semi-blind technique using PARAFAC2 is proposed to investigate the correlation between post-movement beta rebound (PMBR) in beta band and BOLD. In this method, the instantaneous power of EEG in beta band representing the PMBR is calculated and used as a constraint for PARAFAC2 to detect the fMRI voxels activated during PMBR. The results confirm that the proposed method effectively detects the area in the brain which is responsible for beta rebound. The results are compared with those of general linear model (GLM) that completely relies on the predefined fMRI time-course.
Specificity in Mother-Toddler Language-Play Relations Across the Second Year

Relations among specific aspects of language (comprehension and production, semantics and utterance length) and relations between language and symbolic play were evaluated when children were 13 and 20 months of age. The contributions of maternal stimulation to toddler performance and whether associations among toddler abilities might be explained by maternal behaviors were also examined. Although measures of toddler language covaried, language-play associations in toddlers were specific to semantic aspects of language. Associations between mother and toddler behaviors emerged and tended to be specific: Maternal language related to toddler language, and maternal play related to toddler play. Moreover, relations among toddler abilities maintained after maternal influences were partialed. The multidimensional structure of language and specificities in languageplay associations were discussed with reference to models of early representational development.
Improving adaptive skin color segmentation by incorporating results from face detection

The visual tracking of human faces is a basic functionality needed for human-machine interfaces. This paper describes an approach that explores the combined use of adaptive skin color segmentation and face detection for improved face tracking on a mobile robot. To cope with inhomogeneous lighting within a single image, the color of each tracked image region is modeled with an individual, unimodal Gaussian. Face detection is performed locally on all segmented skin-colored regions. If a face is detected, the appropriate color model is updated with the image pixels in an elliptical area around the face position. Updating is restricted to pixels that are contained in a global skin color distribution obtained off-line. The presented method allows us to track faces that undergo changes in lighting conditions while at the same time providing information about the attention of the user, i.e. whether the user looks at the robot. This forms the basis for developing more sophisticated human-machine interfaces capable of dealing with unrestricted environments.
Surfactant proteins in pulmonary alveolar proteinosis in adults

Pulmonary alveolar proteinosis (PAP) is a rare disorder characterised histologically by an intra-alveolar accumulation of fine granular eosinophilic and periodic acid-Schiff positive material. In a retrospective study, the composition of the intra-alveolarly accumulated material of adult patients with PAP was analysed by means of immunohistochemistry and Western blotting. In patients with PAP, the current authors found an intra-alveolar accumulation of surfactant protein (SP)-A, precursors of SP-B, SP-B, variable amounts of mono-, di-, and oligomeric SP-C forms, as well as SP-D. Only in one patient was a precursor of SP-C detected. By means of immuno-electron microscopy, the current authors identified not only transport vesicles labelled for precursors of SP-B and SP-C, but also transport vesicles containing either precursors of SP-B or SP-C in type-II pneumocytes in normal human lungs. It is concluded that pulmonary alveolar proteinosis in adults is characterised by an intra-alveolar accumulation of surfactant protein A, precursors of surfactant protein B, and surfactant proteins B, C and D. The current data provide evidence that not only an impairment of surfactant clearance by alveolar macrophages, but also an abnormal secretion of transport vesicles containing precursors of surfactant protein B (but not surfactant protein C) and an insufficient palmitoylation of surfactant protein C, which may lead to the formation of di- and oligomeric surfactant protein C forms, play a role in the pathogenesis of pulmonary alveolar proteinosis.
Concentrated Announcements on Clustered Data: An Event Study on Biotechnology Stocks

In spring 2000, three events—two political statements by Bill Clinton and Tony Blair and a breakthrough announcement by Celera Genomics—had a major impact on biotechnology stocks. We analyze their effects over a comprehensive set of biopharmaceutical companies, using a composite return-generating model with an industry-specific patent-based factor. Our results show that stocks can be clustered according to their responsiveness to political and scientific events. Furthermore, we emphasize different impacts on the market value of intangible assets for each cluster, suggesting that growth options are valued with different criteria for therapeutics, and technology-based subsectors.
The Effect of Self-Construal and Argumentativeness on English Writing by Korean College Students

This study investigated whether and how the interplay between independent-interdependent self-construal and argumentativeness tendency of Korean college students affects their behaviors of English argumentative writing. Participants were 71 undergraduate students who took English skills development courses at intermediate levels. The dependent variables included (a) the students’ choices of certain writing features that have been suggested as conceptually associated with individualist and collectivist values and (b) the overall argumentation quality in the students’ English argumentative essays. Correlation and ANOVA results revealed no substantial impact of the writers’ orientations in self-construal and levels of argumentativeness on the occurrences of certain writing features and the overall argumentation qualities in their writing. The study results suggested that for beginning/intermediate L2 writers, their psychological dispositions may not exert as significant influences on their English writing as might be expected. The study results were further discussed in reference to L2 writers’ developmental statuses and relevant situational constraints. Further research is warranted for assessing the proportional effects of developmental status, psychological disposition, and contextual constraints on L2 writing. Suggestions for further investigation are presented as well as study limitations.
The impact of increasing demand visibility on production and inventory control efficiency

Information sharing practices such as vendor‐managed inventory (VMI) give manufacturers access to more accurate demand information, e.g. customer sales data, than before. The value of this type of information sharing has been established in many studies. However, most of the research has focused on the ideal situation of the manufacturer having access to information from all downstream parties. In practice, this is rarely the case. In this paper, discrete‐event simulation is used to examine how a manufacturer can combine traditional order data available from non‐VMI customers with sales data available from VMI customers in its production and inventory control and what impact this has on the manufacturer's operational efficiency. The simulation model is based on a real‐life VMI implementation and uses actual demand and product data. The key finding is that even for products with stable demand a partial improvement of demand visibility can improve production and inventory control efficiency, but that the value of visibility greatly depends on the target products’ replenishment frequencies and the production planning cycle employed by the manufacturer.
Town Crier: An Authenticated Data Feed for Smart Contracts

Smart contracts are programs that execute autonomously on blockchains. Their key envisioned uses (e.g. financial instruments) require them to consume data from outside the blockchain (e.g. stock quotes). Trustworthy data feeds that support a broad range of data requests will thus be critical to smart contract ecosystems. We present an authenticated data feed system called Town Crier (TC). TC acts as a bridge between smart contracts and existing web sites, which are already commonly trusted for non-blockchain applications. It combines a blockchain front end with a trusted hardware back end to scrape HTTPS-enabled websites and serve source-authenticated data to relying smart contracts. TC also supports confidentiality. It enables private data requests with encrypted parameters. Additionally, in a generalization that executes smart-contract logic within TC, the system permits secure use of user credentials to scrape access-controlled online data sources. We describe TC's design principles and architecture and report on an implementation that uses Intel's recently introduced Software Guard Extensions (SGX) to furnish data to the Ethereum smart contract system. We formally model TC and define and prove its basic security properties in the Universal Composibility (UC) framework. Our results include definitions and techniques of general interest relating to resource consumption (Ethereum's "gas" fee system) and TCB minimization. We also report on experiments with three example applications. We plan to launch TC soon as an online public service.