Miracle-dz/UniFAR-FTUs huggingface dataset:
Screen printing for the fabrication of organic light-emitting devices

Lower cost and high throughput printing techniques, such as screen printing, have a great promise in the fabrication of organic light-emitting devices. We investigate the effects of solution viscosity and screen mesh count on the printed layer thickness, and device performance. The results also demonstrate, for the first time to our knowledge, the use screen-printing to deposit an ultra-thin layers of less than 15nm with RMS surface roughness of less than 1.5 nm.
Effects of Emotional Context on Memory for Details: The Role of Attention

It was repeatedly demonstrated that a negative emotional context enhances memory for central details while impairing memory for peripheral information. This trade-off effect is assumed to result from attentional processes: a negative context seems to narrow attention to central information at the expense of more peripheral details, thus causing the differential effects in memory. However, this explanation has rarely been tested and previous findings were partly inconclusive. For the present experiment 13 negative and 13 neutral naturalistic, thematically driven picture stories were constructed to test the trade-off effect in an ecologically more valid setting as compared to previous studies. During an incidental encoding phase, eye movements were recorded as an index of overt attention. In a subsequent recognition phase, memory for central and peripheral details occurring in the picture stories was tested. Explicit affective ratings and autonomic responses validated the induction of emotion during encoding. Consistent with the emotional trade-off effect on memory, encoding context differentially affected recognition of central and peripheral details. However, contrary to the common assumption, the emotional trade-off effect on memory was not mediated by attentional processes. By contrast, results suggest that the relevance of attentional processing for later recognition memory depends on the centrality of information and the emotional context but not their interaction. Thus, central information was remembered well even when fixated very briefly whereas memory for peripheral information depended more on overt attention at encoding. Moreover, the influence of overt attention on memory for central and peripheral details seems to be much lower for an arousing as compared to a neutral context.
FRDC's Cross-lingual Entity Linking System at TAC 2013

In this paper, we present FRDC's system at participating in the cross-lingual entity linking (CLEL) tasks for the NIST Text Analysis Conference (TAC) Knowledge Base Population (KBP2013) track. We propose a joint approach for mention expansion, disambiguation, and clustering. In particular, we adopt a lexicon and rule based method for entity classification, a collaborative acronym expansion method and a heuristic combination ranking method that merged ListNet, SVM ranking with web search engine ranking. The results achieved in the TAC cross-lingual entity linking tasks show that our approach is competitive. Our best run achieves 0.655 in B^3+ F1 measure.
Extracellular matrix protein CCN1 regulates cardiomyocyte apoptosis in mice with stress-induced cardiac injury.

AIMS Expression of extracellular matrix protein CCN1 is induced in end-stage ischaemic cardiomyopathy in humans, and after cardiac ischaemia and reperfusion in experimental animal models. Despite its well-documented angiogenic activities, CCN1 increases the cytotoxicities of the tumour necrosis factor family cytokines, which promotes apoptosis in fibroblasts. We aimed to determine the physiological function of CCN1 in an injured heart. METHODS AND RESULTS To assess the function of CCN1 in vivo, knock-in mice carrying the apoptosis-defective mutant allele Ccn1-dm were tested in an isoproterenol (ISO)-induced myocardial injury model (100 mg/kg/day of sc injected ISO for 5 days). Compared with wild-type mice, Ccn1(dm/dm) mice were remarkably resistant to ISO-induced cardiac injury; they showed no post-treatment cardiomyocyte apoptosis or myocardial tissue damage. ISO cardiotoxicity was dependent on Fas ligand (FasL) and its downstream signalling. Using primary cultures of cardiomyocytes isolated from rats, we demonstrated that CCN1 sensitized FasL-mediated apoptosis by engaging its cell-surface receptor integrin α6β1 and up-regulating intracellular reactive oxygen species (ROS), which activated mitogen-activated protein kinase p38, and increased cell-surface Fas expression. CONCLUSION CCN1 is a critical pathophysiological regulator that mediates cardiomyocyte apoptosis during work-overload-induced cardiac injury. CCN1 increases cellular susceptibility to Fas-induced apoptosis by increasing ROS and cell-surface Fas expression.
Threadguide: profiler assisted application adaptation on CMP

Chip Multiprocessors (CMP) are there to stay in everyday computing -- starting from large scale server to mobile handheld devices. The challenge in designing a system with CMP is to utilize the processor resources optimally so that the power and performance goals are met. In this paper we present Threadguide, a framework for application adaptation augmenting mircoarchitectual support in CMP. The hardware assisted methodology collects runtime information from the program to annotate the code in appropriate locations. In subsequent passes compiler generate more refined code (thereby adapting the application) that distributes the workload across available processors and takes decisions to manage total energy to meet the power budget. The hardware is non-intrusive to the processor pipeline and does not hinder the execution of the processor. We show that with minimum hardware real estate (as low as a kilobyte) and energy overhead (less than 1% of dynamic energy), proposed scheme saves up to 18% in energy-delay product (EDP).
Real-time measurement of flows classified according to their application

In the management of Internet Protocol networks, the number of flows is an important performance metric because it has useful applications in areas such as port scan detection, denial-of-service detection, and traffic analysis. Real-time counting of flows is particularly important because network operators can take immediate actions against detected network anomalies or performance degradation. This paper presents a method that enables real-time counting of flows classified by application. More useful information for network management can be obtained by counting classified flows. For example, the proposed method is helpful in determining the type of attacks or victim services for attack detection. The algorithm for counting classified flows is developed using the timestamp vector algorithm. This paper first explores a naïve method that has as many timestamp vector mechanisms as the application classes. However, this method is disadvantageous because it consumes very large memory space. To avoid this problem, a new method that considerably decreases memory consumption is proposed. In addition, the paper also investigates a method for improving measurement accuracy. The effectiveness of the proposed method is evaluated for real-world network data.
eural networks to predict earthquakes in Chile

A new earthquake prediction system is presented in this work. This method, based on the application of artificial neural networks, has been used to predict earthquakes in Chile, one of the countries with larger seismic activity. The input values are related to the b-value, the Bath’s law, and the Omori–Utsu’s law, parameters that are strongly correlated with seismicity, as shown in solid previous works. Two kind of prediction are provided in this study: The probability that an earthquake of magnitude larger than a threshold value happens, and the probability that an earthquake of a limited magnitude interval might occur, both during the next five days in the areas analyzed. For the four Chile’s seismic regions examined, with epicenters placed on meshes with dimensions varying from 0.5◦ × 0.5◦ to 1◦ × 1◦, a prototype of rtificial neural networks eismic risk ime series neuronal network is presented. The prototypes predict an earthquake every time the probability of an earthquake of magnitude larger than a threshold is sufficiently high. The threshold values have been adjusted with the aim of obtaining as few false positives as possible. The accuracy of the method has been assessed in retrospective experiments by means of statistical tests and compared with well-known machine learning classifiers. The high success rate achieved supports the suitability of applying soft d po computing in this field an
An Empirical Test of Bootstrapping as a Method for Assessing Confidence in Phylogenetic Analysis

Bootstrapping is a common method for assessing confidence in phylogenetic anal? yses. Although bootstrapping was first applied in phylogenetics to assess the repeatability of a given result, bootstrap results are commonly interpreted as a measure of the probability that a phylogenetic estimate represents the true phylogeny. Here we use computer simulations and a laboratory-generated phylogeny to test bootstrapping results of parsimony analyses, both as measures of repeatability (i.e., the probability of repeating a result given a new sample of characters) and accuracy (i.e., the probability that a result represents the true phylogeny). Our results indicate that any given bootstrap proportion provides an unbiased but highly imprecise measure of repeatability, unless the actual probability of replicating the relevant result is nearly one. The imprecision of the estimate is great enough to render the estimate virtually useless as a measure of repeatability. Under conditions thought to be typical of most phylogenetic analyses, however, bootstrap proportions in majority-rule consensus trees provide biased but highly con? servative estimates of the probability of correctly inferring the corresponding clades. Specifically, under conditions of equal rates of change, symmetric phylogenies, and internodal change of 70% usually correspond to a probability of >95% that the corresponding dade is real. However, under conditions of very high rates of internodal change (approaching randomization of the characters among taxa) or highly unequal rates of change among taxa, bootstrap proportions >50% are overestimates of accuracy. (Boot? strapping; accuracy; repeatability; phylogeny; parsimony; precision; statistical analyses; simu? lations.)
Secure group identity authentication based on non-perfect secret sharing scheme

An identity authentication method based on the non-perfect secret sharing scheme using MIX-SPLIT algorithm is proposed in this paper. In this method, the face image of a user is employed to get his biometric hashing code. Every user is given a permutation key which is used to produce random permutation. The sharing secrets are gained by MIX-SPLIT algorithm and they are as secure as the one time key. A group of authorized users can access the confidential files by combining their sharing secrets. The experimental results show that the proposed method is effective and practical.
Choroidal neovascularization reduced by targeted drug delivery with cationic liposome-encapsulated paclitaxel or targeted photodynamic therapy with verteporfin encapsulated in cationic liposomes

Purpose Intravitreal antivascular endothelial growth factor (anti-VEGF) application has revolutionized the treatment of choroidal neovascularization (CNV), a hallmark of wet age-related macular degeneration. However, additional treatment options are desirable as not all CNV lesions respond to anti-VEGF injections. Here, we assessed the feasibility of targeted delivery of cationic liposome-encapsulated paclitaxel (EndoTAG-1) in treating CNV. Furthermore, we investigated whether a new formulation of verteporfin encapsulated in cationic liposomes (CL-VTP) enhances the effect of photodynamic therapy (PDT). Methods EndoTAG-1, LipoSPA, and CL-VTP were produced by encapsulating paclitaxel, succinyl-paclitaxel, or verteporfin in cationic liposomes (CL). Mice underwent argon laser coagulations at day 0 (D0) to induce CNV. EndoTAG-1 and LipoSPA were injected into the tail vein at D1, D3, D5, D7, and D9. Taxol, CL, or trehalose buffer alone was injected in control animals. At D10, all animals were perfused with fluorescein isothiocyanate (FITC)-dextran. Flatmounts comprising the retinal pigment epithelium, choroid, and sclera were prepared for quantifying the CNV by measuring the area of lesions perfused with FITC-dextran. For PDT, mice received an injection with CL-VTP or Visudyne at D10. One eye was treated with PDT while the other served as a control. Evaluation of RPE-choroid-scleral and retinal flatmounts was performed at D12, D14, or D17. Perfusion with FITC-dextran and tetramethylrhodamine-5-(and 6)-isothiocyanate-lectin staining was used to distinguish between perfused and non-perfused choroidal vessels. Results EndoTAG-1 or LipoSPA significantly reduced CNV size to 15% compared to trehalose controls. The mean CNV area of mice treated with CL was reduced (though not significantly) to about one-half of the value of the trehalose control group. The same was observed for paclitaxel. Thus, the reduction in the CNV size between treatment with CL and treatment with EndoTAG-1 or LipoSPA was 40%, which was not significant. PDT using either CL-VTP or Visudyne reduced CNV size to 65% (D17) of trehalose control size. CNV size was further diminished to 56% with Visudyne and 53% with CL-VTP when PDT was repeated twice. Most importantly, PDT-associated retinal damage was less pronounced using CL-VTP compared to Visudyne. Conclusions Systemic intravenous injection of paclitaxel (EndoTAG-1)- or succinyl-paclitaxel (LipoSPA)-loaded CL had a significant antiangiogenic effect in a CNV mouse model. PDT with CL-VTP was as effective as Visudyne in neovascular obliteration but induced less tissue damage. Our data suggest that systemic application of cationic liposome formulations may serve to treat ocular neovascular diseases. This approach may reduce the need for intraocular injections and may benefit patients with neovascular lesions irresponsive to anti-VEGF treatment.
EasiRA: A hybrid rate adaptation scheme for 802.11 mobile wireless access networks

Rate adaptation, which adapts transmission bit rate according to current wireless link conditions, is a fundamental mechanism used by link-layer protocols to improve the performance of 802.11 wireless access networks in terms of throughput. However, rate adaptation faces to severe challenges due to more and more congested and dynamic wireless links. In this paper, we design a hybrid rate adaptation scheme, called EasiRA, for 802.11 mobile wireless access networks. It has following three features. First, it combines the sensor-hints and protocol-hints information together to estimate current link status. Second, EasiRA exploits environmental signal strength information obtained by a 802.15. 4-based radio to help distinguish the causes of packet losses and adjust the thresholds of the protocol-hints. Finally, EasiRA uses both random and deterministic rate increase or decrease schemes to combat the dynamic and unpredictable characteristics of wireless links. Simulation results show that EasiRA consistently outperforms the existing rate adaptation schemes, namely CARA, Minstrel and RapidSample, particularly in relatively high dynamic scenario.
The relationship between thyroid function and estimated glomerular filtration rate in patients with chronic kidney disease.

BACKGROUND Recent studies have shown an increasing risk of hypothyroidism with incrementally lower estimated glomerular filtration rate (eGFR) in cohorts comprised of patients with normal to mildly impaired kidney function. We sought to confirm these findings in a nationally representative cohort of Veterans Affairs patients with moderate-to-severe chronic kidney disease (CKD). METHODS This study examined the association between kidney function and hypothyroidism among 461 607 veterans with Stage 3 to 5 CKD who underwent repeated measurements of serum creatinine and thyrotropin (TSH) at identical time points between October 2004 and September 2006. Kidney function was defined by eGFR using the Chronic Kidney Disease Epidemiology Collaboration formula. In primary analyses, the association between eGFR and hypothyroidism (defined as serum TSH > 5 mIU/L and/or receipt of thyroid hormone supplementation) was estimated using multivariable random effects logistic regression. In secondary analyses, the association between eGFR and serum TSH level was estimated using multivariable random effects linear regression. RESULTS At baseline, 68.9, 25.5, 5.3 and 0.3% of patients had Stage 3A, 3B, 4 and 5 CKD, respectively. For every 10 mL/min/1.73 m(2) lower eGFR, there was an 18% higher risk of hypothyroidism: adjusted odds ratio 1.18 [95% confidence interval (CI) 1.17-1.20, P < 0.001]. In secondary analyses, we observed that a 10 mL/min/1.73 m(2) lower eGFR was associated with a 0.11 mIU/L higher serum TSH (95% CI 0.10-0.11 mIU/L higher serum TSH, P < 0.001). CONCLUSIONS In a nationally representative cohort of patients with moderate-to-severe CKD, there is an inverse association between eGFR and risk of hypothyroidism.
Semiotic Methods for Enterprise Design and IT Applications

Investment in information technology (or IT) does not necessarily bring improvement in business performance. One important cause of this is the divorce between the design of the IT systems and business organisations. An approach of organisational semiotics, based on the understanding of organisations as systems of social norms emphasises the central role of the people, their responsibility and the organisation in the analysis and design of IT applications. Business organisations are analysed as systems of meanings, intentional communication and interpretation that create knowledge, which sooner or later leads to action. Effective methods for organisational analysis and systems design (MEASUR) have been developed on the basis of this theory. However, to make these methods ready for practical, industrial use, they need further work, especially the creation of supporting aids and tools. The recently established research project, SEDITA, addresses these issues and invites collaboration both within business and research institutions. Keyword: Organisation, semiotics, information systems, requirements engineering, systems analysis and design, MEASUR, methodology, semantics, ontology, pragmatics, knowledge. “The method of science is the method of bold conjectures and ingenious and severe attempts to refute them” Sir Karl Popper, Objective Knowledge, p.81
A model presented for classification ECG signals base on Case-Based Reasoning

Early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through appropriate treatment; thus classifying cardiac signals will be helped to immediate diagnosing of heart beat type in cardiac patients. The present paper utilizes the case base reasoning (CBR) for classification of ECG signals. Four types of ECG beats (normal beat, congestive heart failure beat, ventricular tachyarrhythmia beat and atrial fibrillation beat) obtained from the PhysioBank database was classified by the proposed CBR model. The main purpose of this article is classifying heart signals and diagnosing the type of heart beat in cardiac patients that in proposed CBR (Case Base Reasoning) system, Training and testing data for diagnosing and classifying types of heart beat have been used. The evaluation results from the model are shown that the proposed model has high accuracy in classifying heart signals and helps to clinical decisions for diagnosing the type of heart beat in cardiac patients which indeed has high impact on diagnosing the type of heart beat aided computer.
Nano-liposomal dry powder inhaler of tacrolimus: Preparation, characterization, and pulmonary pharmacokinetics

The studies were undertaken to evaluate feasibility of pulmonary delivery of liposomaly encapsulated tacrolimus dry powder inhaler for prolonged drug retention in lungs as rescue therapy to prevent refractory rejection of lungs after transplantation. Tacrolimus encapsulated liposomes were prepared by thin film evaporation technique and liposomal dispersion was passed through high pressure homogenizer. Tacrolimus nano-liposomes (NLs) were separated by centrifugation and characterized. NLs were dispersed in phosphate buffer saline (PBS) pH 7.4 containing different additives like lactose, sucrose, and trehalose, and L-leucine as antiadherent. The dispersion was spray dried and spray dried powders were characterized. In vitro and in vivo pulmonary deposition was performed using Andersen Cascade Impactor and intratracheal instillation in rats respectively. NLs were found to have average size of 140 nm, 96% ± 1.5% drug entrapment, and zeta potential of 1.107 mV. Trehalose based formulation was found to have low density, good flowability, particle size of 9.46 ± 0.8 μm, maximum fine particle fraction (FPF) of 71.1 ± 2.5%, mean mass aerodynamic diameter (MMAD) 2.2 ± 0.1 μm, and geometric standard deviation (GSD) 1.7 ± 0.2. Developed formulations were found to have in vitro prolonged drug release up to 18 hours, following Higuchi’s Controlled Release model. In vivo studies revealed maximal residence of tacrolimus within lungs of 24 hours, suggesting slow clearance from the lungs. The investigation provides a practical approach for direct delivery of tacrolimus encapsulated in NLs for controlled and prolonged retention at the site of action. It may play a promising role as rescue therapy in reducing the risk of acute rejection and chronic rejection.
An improved approach to reinforcement learning in Computer Go

Monte-Carlo Tree Search (MCTS) has revolutionized, Computer Go, with programs based on the algorithm, achieving a level of play that previously seemed decades away. , However, since the technique involves constructing a search tree, its performance tends to degrade in larger state spaces. Dyna-2, is a hybrid approach that attempts to overcome this shortcoming, by combining Monte-Carlo methods with state abstraction. While, not competitive with the strongest MCTS-based programs, the, Dyna-2-based program RLGO achieved the highest ever rating, by a traditional program on the 9×9 Computer Go Server. Plain, Dyna-2 uses _-greedy exploration and a flat learning rate, but we, show that the performance of the algorithm can be significantly, improved by making some relatively minor adjustments to this, configuration. Our strongest modified program achieved an Elo, rating 289 points higher than the original in head-to-head play, equivalent to an expected win rate of 84%.
Bounded Delay in Byzantine-Tolerant State Machine Replication

The paper proposes a new state machine replication protocol for the partially synchronous system model with Byzantine faults. The algorithm, called BFT-Mencius, guarantees that the latency of updates initiated by correct processes is eventually upper-bounded, even in the presence of Byzantine processes. BFTMencius is based on a new communication primitive, Abortable Timely Announced Broadcast (ATAB), and does not use signatures. We evaluate the performance of BFT-Mencius in cluster settings, and show that it provides bounded latency and good throughput, being comparable to the state-of-the-art algorithms such as PBFT and Spinning in fault-free configurations and outperforming them under performance attacks by Byzantine processes.