Miracle-dz/UniFAR-FTUs huggingface dataset:
An “In-Depth” Description of the Small Non-coding RNA Population of Schistosoma japonicum Schistosomulum

Parasitic flatworms of the genus Schistosoma are the causative agents of schistosomiasis, which afflicts more than 200 million people yearly in tropical regions of South America, Asia and Africa. A promising approach to the control of this and many other diseases involves the application of our understanding of small non-coding RNA function to the design of safe and effective means of treatment. In a previous study, we identified five conserved miRNAs from the adult stage of Schistosoma japonicum. Here, we applied Illumina Solexa high-throughput sequencing methods (deep sequencing) to investigate the small RNAs expressed in S. japonicum schistosomulum (3 weeks post-infection). This has allowed us to examine over four million sequence reads including both frequently and infrequently represented members of the RNA population. Thus we have identified 20 conserved miRNA families that have orthologs in well-studied model organisms and 16 miRNA that appear to be specific to Schistosoma. We have also observed minor amounts of heterogeneity in both 3′ and 5′ terminal positions of some miRNA as well as RNA fragments resulting from the processing of miRNA precursor. An investigation of the genomic arrangement of the 36 identified miRNA revealed that seven were tightly linked in two clusters. We also identified members of the small RNA population whose structure indicates that they are part of an endogenously derived RNA silencing pathway, as evidenced by their extensive complementarities with retrotransposon and retrovirus-related Pol polyprotein from transposon.
Information extraction from legal documents

Legal TRUTHS (TuRning Unstructured Texts to Helpful Structure) is a system that extracts relevant information from Philippine Supreme Court decisions, specifically on criminal cases. We describe here the processes involved in the development of Legal TRUTHS focusing on the issues relating to the domain and the geographical setting of the source documents, and the performance evaluation results are also presented. Pertinent information to be extracted for criminal cases such as the crime, the date and time of commission, the plaintiff, and the penalty were determined from a sample set of documents. Sections of these documents were identified for initial segmentation of the data. Automatic filtering of the data was involved in drawing out relevant information from the texts. From 25 training documents and also the same set for testing, performance showed over-all precision at 91.7%, recall at 99.5%, and F-measure at 95.6%. Testing on another 50 documents showed over-all precision at 84.3%, recall at 95.8%, and F-measure at 91.0%.
The Empirical Failure of the Expectations Hypothesis of the Term Structure of Bond Yields

Abstract This paper tests the expectations hypothesis (EH) using U.S. monthly data for bond yields spanning the 1952–2003 sample period and ranging in maturity from one month to 10 years. We apply the Lagrange multiplier test developed by Bekaert and Hodrick (2001) and extend it to increase the test power by introducing economic variables as conditioning information and by using more than two bond yields in the model and testing the EH jointly on more than one pair of yields. While the conventional bivariate procedure provides mixed results, the more powerful testing procedures suggest rejection of the EH throughout the maturity spectrum examined.
Reforma fiscal y bienestar en la economa de Mxico

En este trabajo se determina la estructura fiscal optima en un modelo de crecimiento endogeno de la economia de Mexico. El gasto publico seria financiado por un impuesto sobre la renta. Si los rendimientos del capital y el trabajo pueden ser tasados a distintos tipos impositivos, el impuesto optimo sobre los salarios seria nulo. Manteniendo constantes los parametros de gasto publico, el valor optimo del impuesto sobre el consumo es cero. La presencia de externalidades no parece justificar un subsidio a la educacion tan elevado como el estimado. Estos resultados se muestran relativamente robustos en el analisis de sensibilidad
Labeling the Network Traffic with Accurate Application Information

Accurate network traffic classification is crucial for network management and has received widespread attention in the last few years. However, there is not a reliable and widely accepted validation technique for verifying these classification approaches. The main reason is that there are not public traffic traces with accurate application information. In order to address the above problem, this paper presents a new technique, which uses the Network Driver Interface Specification (NDIS) Hook and the Socket Hook to label the packets with the corresponding application on the basis of the user host. The socket hook can capture the packets and gain the related information of the captured packet and send the gained information to the memory. The NDIS Hook can capture the packet and change the header information of the IP packet. Then, these marked packets are sent to the Internet and collected at the boundary gateway.
On the Irreducible Components of the Form Ring and an Application to Intersection Cycles

Let A be a commutative Noetherian ring and I an ideal in A. We characterize algebraically when all the minimal primes of the associated graded ring G I A contract to minimal primes of A/I. This, applied to intersection theory, means that there are no embedded distinguished varieties of intersection. The characterization is in terms of the analytic spread of certain localizations of I, the symbolic Rees algebra, and the normalization of the Rees algebra, and extends results of Huneke, Vasconcelos, and Martí-Farré.
Design of strictly positive real systems using constant output feedback

The authors present a linear matrix inequality (LMI) approach to the strictly positive real (SPR) synthesis problem: find an output feedback K such that the closed loop system T(s) is SPR. The authors establish that if no such constant output feedback K exists, then no dynamic output feedback with a proper transfer matrix exists to make the closed-loop system SPR. The existence of K to guarantee the SPR property of the closed-loop system is used to develop an adaptive control scheme that can stabilize any system of arbitrary unknown order and unknown parameters.
Geometric phases and criticality in spin systems

A general formalism of the relation between geometric phases produced by circularly evolving interacting spin systems and their criticality behaviour is presented. This opens up the way for the use of geometric phases as a tool to probe regions of criticality without having to undergo a quantum phase transition. As a concrete example, a spin-1/2 chain with XY interactions is considered and the corresponding geometric phases are analysed. Finally, a generalization of these results to the case of an arbitrary spin system is presented.
Accuracy of bleeding scores for patients presenting with myocardial infarction: a meta-analysis of 9 studies and 13 759 patients

Introduction Due to its negative impact on prognosis, a clear assessment of bleeding risk for patients presenting with acute coronary syndrome (ACS) remains crucial. Different risk scores have been proposed and compared, although with inconsistent results. Aim We performed a meta-analysis to evaluate the accuracy of different bleeding risk scores for ACS patients. Material and methods All studies externally validating risk scores for bleeding for patients presenting with ACS were included in the present review. Accuracy of risk scores for external validation cohorts to predict major bleeding in patients with ACS was the primary end point. Sensitivity analysis was performed according to clinical presentation (ST segment elevation myocardial infarction (STEMI) and non-ST segment elevation myocardial infarction (NSTEMI)). Results Nine studies and 13 759 patients were included. CRUSADE, ACUITY, ACTION and GRACE were the scores externally validated. The rate of in-hospital major bleeding was 7.80% (5.5–9.2), 2.05% (1.5–3.0) being related to access and 2.70% (1.7–4.0) needing transfusions. When evaluating all ACS patients, ACTION, CRUSADE and ACUITY performed similarly (AUC 0.75: 0.72–0.79; 0.71: 0.64–0.80 and 0.71: 0.63–0.77 respectively) when compared to GRACE (0.66; 0.64–0.67, all confidence intervals 95%). When appraising only STEMI patients, all the scores performed similarly, while CRUSADE was the only one externally validated for NSTEMI. For ACTION and ACUITY, accuracy increased for radial access patients, while no differences were found for CRUSADE. Conclusions ACTION, CRUSADE and ACUITY perform similarly to predict risk of bleeding in ACS patients. The CRUSADE score is the only one externally validated for NSTEMI, while accuracy of the scores increased with radial access.
Mapping Temporal Horizons: Analysis of Collective Future and Past related Attention in Twitter

Microblogging platforms such as Twitter have recently received much attention as great sources for live web sensing, real-time event detection and opinion analysis. Previous works usually assumed that tweets mainly describe "what's happening now". However, a large portion of tweets contains time expressions that refer to time frames within the past or the future. Such messages often reflect expectations or memories of social media users. In this work we investigate how microblogging users collectively refer to time. In particular, we analyze half a year long portion of Japanese and four months long collection of US tweets and we quantify collective temporal attention of users as well as other related temporal characteristics. This kind of knowledge is helpful in the context of growing interest for detection and prediction of important events within social media. The exploratory analysis we perform is possible thanks to the development of visual analytics framework for robust overview and easy detection of various regularities in the past and future-oriented thinking of Twitter users. We believe that the visualizations we provide and the findings we outline can be also valuable for sociologists and computer scientists to test and refine their models about time in natural language.
Involvement of heterophilic trans‐interaction of Necl‐5/Tage4/PVR/CD155 with nectin‐3 in formation of nectin‐ and cadherin‐based adherens junctions

Nectins, Ca2+‐independent immunoglobulin (Ig)‐like cell–cell adhesion molecules and cadherins, Ca2+‐dependent cell–cell adhesion molecules, are associated through their respective cytoplasmic tail‐binding proteins, afadin and catenins and play roles in formation of adherens junctions (AJs) in epithelial cells and fibroblasts. Nectin‐like molecule‐5 (Necl‐5) is a Ca2+‐independent Ig‐like molecule which does not homophilically trans‐interact, but heterophilically trans‐interacts with nectin‐3, one member of the nectin family. Necl‐5 does not directly bind afadin and therefore is not associated with cadherins. Necl‐5 regulates cell motility and proliferation in cooperation with integrins and growth factor receptors, when it does not interact with nectin‐3. We studied here a role of the heterophilic trans‐interaction of Necl‐5 with nectin‐3 in cell–cell adhesion using L cells stably expressing Necl‐5, nectin‐3 and E‐cadherin (Necl‐5‐nectin‐3‐EL cells). Afadin, E‐cadherin and catenins were recruited to the nectin‐3 side, but not to the Necl‐5 side, of the contact sites formed by the heterophilic trans‐interaction between Necl‐5 and nectin‐3. The anti‐Necl‐5 monoclonal antibody, which specifically inhibited the heterophilic trans‐interaction of Necl‐5 with nectin‐3, inhibited the formation of the E‐cadherin‐based AJs in Necl‐5‐nectin‐3‐EL cells. These results indicate that Necl‐5 plays roles not only in cell motility and proliferation but also in cell–cell adhesion in cooperation with nectin‐3.
The Evolution of Anatomic Anterior Cruciate Ligament Reconstruction

Anterior cruciate ligament reconstruction has evolved significantly since the early 1900’s, back when an emphasis was placed on repair and not reconstruction. Over the past century, the technique has evolved from intra-articular non anatomic reconstruction, to extra articular reconstruction, back to intra articular (performed arthroscopically), to now, the advent of anatomic insertion site restoration. This review will aim to illustrate the changes that have occurred, describing the rational for this process, based upon anatomical, radiological, biomechanical and clinical studies, all of which have aimed to improve patient function following ACL injury.
VaccineImmunogenicity of a Pulsed Dendritic Cell Self-Tumor Antigen Enhances the Linkage of Foreign Carrier Protein to a

The unique Ag-presenting capabilities of dendritic cells (DCs) make them attractive vehicles for the delivery of therapeutic cancer vaccines. While tumor Ag-pulsed DC vaccination has shown promising results in a variety of murine tumor models and early clinical trials, the optimal form of tumor Ag for use in DC pulsing has not been determined. We have studied DC vaccination using alternative forms of a soluble protein tumor Ag, the tumor-speciﬁc Ig idiotype (Id) expressed by a murine B cell lymphoma. Vaccination of mice with Id-pulsed DCs was able to induce anti-Id Abs only when the Id was modiﬁed to constitute a hapten-carrier system. DCs pulsed with Id proteins modiﬁed to include foreign constant regions, foreign constant regions plus GM-CSF, or linkage to keyhole limpet hemocyanin (KLH) carrier protein were increasingly potent in their ability to elicit anti-Id Abs. Vaccination with Id-KLH-pulsed DCs induced tumor-protective immunity superior to that obtained with Id-KLH plus a chemical adjuvant, and protection was not dependent upon effector T cells. Rather, protection was associated with the induction of high titers of anti-Id Abs of the IgG2a subclass, characteristic of a Th1 response. These ﬁndings have implications for the design of therapeutic Ag-pulsed DC vaccines for cancer immunotherapy in humans. The Journal of Immunology, 2000, 164: 4797–4803.
JAFA: a protein function annotation meta-server

With the high number of sequences and structures streaming in from genomic projects, there is a need for more powerful and sophisticated annotation tools. Most problematic of the annotation efforts is predicting gene and protein function. Over the past few years there has been considerable progress in automated protein function prediction, using a diverse set of methods. Nevertheless, no single method reports all the information possible, and molecular biologists resort to ‘shopping around’ using different methods: a cumbersome and time-consuming practice. Here we present the Joined Assembly of Function Annotations, or JAFA server. JAFA queries several function prediction servers with a protein sequence and assembles the returned predictions in a legible, non-redundant format. In this manner, JAFA combines the predictions of several servers to provide a comprehensive view of what are the predicted functions of the proteins. JAFA also offers its own output, and the individual programs' predictions for further processing. JAFA is available for use from .
On Data Importance Analysis

Accidents of information leakage and insider threats by malicious employee are major issues in enterprise IT system. Data importance analysis methods can resolve this issue, the importance of data is automatically analyzed by the method and confirms whether the operation suits the security policy for the level of importance of the data. Insider threads are also protected by analyzing data importance and data flows. A mechanism to ascertain data importance via automatic analysis is useful for avoiding human error. The mechanism finds the appropriate category for user sent data in terms of data importance, highly secret, important, and unclassified. In this paper, we presented an analysis method and discussed its application. It will apply to information leakage by both human error and insider threads. The method is a combination of data diagnosis and data categorization, and it can analyze whether the transaction to send the data compiles with the security policy.
3 Morphological-Rank-Linear Models for Financial Time Series Forecasting

The financial time series forecasting is considered a rather difficult problem, due to the many complex features frequently present in such time series (irregularities, volatility, trends and noise). Several approaches have been studied for the development of predictive models able to predict time series, based on its past and present data. In the attempt to solve the time series prediction problem, a wide number of linear statistical models were proposed. Among them, the popular linear statistical approach based on Auto Regressive Integrated Moving Average (ARIMA) models [1] is one of the most common choices. However, since the ARIMA models are linear and most real world applications involve nonlinear problems, this can introduce an accuracy limitation of the generated forecasting models. In the attempt to overcome linear statistical models limitations, other nonlinear statistical approaches have been developed, such as the bilinear models [2], the threshold autoregressive models [3], the exponential autoregressive models [4], the general state dependent models [5], amongst others. The drawbacks of those nonlinear statistical models are the high mathematical complexity associated with them (resulting in many situations in similar performances to the linear models) and the need, most of the time, of a problem dependent specialist to validate the predictions generated by the model, limiting the development of an automatic forecast system [6]. Alternately, Artificial Neural Networks (ANNs) based approaches have been applied for nonlinear modeling of time series in the last two decades [7-14]. However, in order to define a solution to a given problem, ANNs require the setting up of a series of system parameters, some of them are not always easy to determine. The ANN topology, the number of processing units, the algorithm for ANN training (and its corresponding variables) are just some of the parameters that require definition. In addition to those, in the particular case of time series forecasting, another crucial element necessary to determine is the relevant time lags to represent the series [15]. In this context, evolutionary approaches for the definition of neural network parameters have produced interesting results [16{20]. Some of these works have focused on the evolution of the network weights whereas others aimed at evolving the network architecture.
“ Object-Oriented and Internet-Based Technologies ” White Paper Ercatons : Thing-oriented Programming

Thing-oriented programming (TP) is an emerging programming model which overcomes some of the limitations of current practice in software development in general and of object-oriented programming (OOP) in particular. Ercatons provide an implementation of the model. TP does not describe a new programming language. The so-called “ercato virtual machine” or “ercato engine” implements the ideas discussed and has been used to validate the concepts described here. Thing-oriented programming is centered around the concept of a “Thing”. A thing in an executing software system is bound to behave like an object does in our real world. Software objects do not. Aspect-oriented programming (AOP) or extreme programming methods (XP) provide no exception. This fact is traced back to be the root why current software development often fails to meet our expectations. TP should then be able to provide the means to make software development achieve what other engineering disciplines have achieved a long time ago: that projects are deterministic (completed in time and effort scales sub-linearly with size). This paper is a revised version of the original paper published in the conference proceedings of the Net.ObjectDays 2004 conference, by Springer Verlag LNCS 3263.
Full-Time Supervision based Bidirectional RNN for Factoid Question Answering

Recently, bidirectional recurrent neural network (BRNN) has been widely used for question answering (QA) tasks with promising performance. However, most existing BRNN models extract the information of questions and answers by directly using a pooling operation to generate the representation for loss or similarity calculation. Hence, these existing models don't put supervision (loss or similarity calculation) at every time step, which will lose some useful information. In this paper, we propose a novel BRNN model called full-time supervision based BRNN (FTS-BRNN), which can put supervision at every time step. Experiments on the factoid QA task show that our FTS-BRNN can outperform other baselines to achieve the state-of-the-art accuracy.
Stability of Chitosan—A Challenge for Pharmaceutical and Biomedical Applications

Chitosan—one of the natural multifunctional polymers—due to its unique and versatile biological properties is regarded as a useful compound in medical and pharmaceutical technology. Recently, considerable research effort has been made in order to develop safe and efficient chitosan products. However, the problem of poor stability of chitosan-based systems restricts its practical applicability; thus, it has become a great challenge to establish sufficient shelf-life for chitosan formulations. Improved stability can be assessed by controlling the environmental factors, manipulating processing conditions (e.g., temperature), introducing a proper stabilizing compound, developing chitosan blends with another polymer, or modifying the chitosan structure using chemical or ionic agents. This review covers the influence of internal, environmental, and processing factors on the long-term stability of chitosan products. The aim of this paper is also to highlight the latest developments which enable the physicochemical properties of chitosan-based applications to be preserved upon storage.
How Well Does a Monetary Dynamic Equilibrium Model Account for Chilean Data

The purpose of this paper is to figure out how well a money-in-the-utility-function model with a Taylor rule can match Chilean data, specially some monetary stylized facts. A dynamic stochastic general equilibrium model is formulated, solved and calibrated to evaluate its ability to replicate the main features of the Chilean economy in the 1986-2000 period. In particular, it focuses on a possible explanation to what the empirical literature calls the "price puzzle", the co-movement between interest rate and inflation. The solution of the model is adequately achieved through a perturbation method (second-order approximation). A positive transitory policy interest rate shock causes: (1) a temporary (non-significant) decline in output, (2) a decrease in real money balances, and (3) a temporary increase in the inflation rate. These findings are relatively consistent with those obtained from impulse-response functions estimated for Chile. Therefore, the theoretical model proposed is able to explain and reproduce the co-movement between interest rate and inflation. This relationship is caused by a Fisher effect and strengthened by the presence of a Taylor rule that depends positively on inflation deviation from its steady state equilibrium.
Half-Bridge LLC Resonant Converter Design Using FSFR-Series Fairchild Power Switch (FPSTM)

The effort to obtain ever-increasing power density of switched-mode power supply has been limited by the size of passive components. Operation at higher frequencies considerably reduces the size of passive components, such as transformers and filters; however, switching losses have been an obstacle to high-frequency operation. To reduce switching losses and allow high-frequency operation, resonant switching techniques have been developed. These techniques process power in a sinusoidal manner and the switching devices are softly commutated. Therefore, the switching losses and noise can be dramatically reduced [1-7].