Miracle-dz/UniFAR-FTUs huggingface dataset:
Proposal of Dynamic FEC Controls with Population Estimation Methods for Delay Tolerant Networks

In case of local areas, there are possibilities to isolate from other areas after earthquakes. Besides, the network diversity between urban and local area might cause the future problems of health or public services by information networks. The DTN (Delay Tolerant Networks) is considered to be one of the effective methods, and there are previous researches to improve the DTN routings. However, the current rapid developments of mobile devices such as data storages or broadband wireless networks have made the efficiency different as the previous researches. Therefore, we propose the Enhanced Media Coordinate System for DTN to the architecture in order to provide the Data Triage, Node Selection based on its Territory, and Dynamic FEC (Forward Error Correction). In this paper, the proposed Dynamic FEC with population estimation is especially explained, and the results of the computational simulation by the GIS map of a Japanese coastal town are reported. Then, the results are discussed for the future studies of DTN for Disaster Information Network System in local areas.
Failure to demonstrate long-lived MHC saturation both in vitro and in vivo. Implications for therapeutic potential of MHC-blocking peptides.

Peptides that bind with high affinity to class II MHC molecules can inhibit T cell activation both in vitro and in vivo. Thus, they have been suggested as potential therapeutic agents for MHC-associated autoimmune diseases. We have constructed nonnatural peptides with high affinity for certain disease-associated MHC alleles. More specifically, a particular peptide, designated as CY-760.50, was found to have a high binding affinity for DR1, slow dissociation kinetics after binding to MHC, and prolonged stability in human serum. However, when the ability of this peptide to block peptide presentation to an influenza hemagglutinin 307-319 peptide-specific, DR1-restricted T cell clone was examined, it was found that MHC blockade could only be achieved when high concentrations of peptide were present along with Ag in the fluid phase. Thus, pretreatment of APC with MHC class II blocker, followed by removal of unbound blocker, did not result in saturation of MHC molecules, because practically immediate reacquisition of Ag-presenting capacity was observed after removal of fluid phase blocker. The pharmacokinetic behavior and the duration of blocking activity of CY-760.50 were also examined in vivo, taking advantage of the fact that the mouse MHC class II molecule I-Ab also bound CY-760.50 with high affinity. CY-760.50 administered i.v. to C57BL/6 mice was rapidly cleared from the circulation and virtually undetectable in the serum 10 min after injection. This fast clearance rate was paralleled by a similarly short duration of the MHC blockade effect. These in vivo results have implications concerning the biology of peptide-MHC interactions, and suggest that MHC blockade may not be feasible as a therapeutic approach unless effective concentrations of inhibitor can be maintained over extended periods of time in the extracellular fluids.
The analysis and measurement of FSS radome for antenna RCS reduction

This paper investigates the application of bandpass FSS radome with an enclosed antenna to reduce its backward RCS outside of its operating band. A planar array antenna covered with FSS radome is designed and constructed. In order to study the effects of a dielectric embedded FSS on an enclosed antenna pattern, we adopt the ray tracing technique to compute the near field pattern of the antenna-FSS configuration, from which the transmission coefficient and the far field patterns can be calculated. The results show that the backward RCS of antenna array with FSS radome has dramatically reduced than the common antenna array at out of operating band.
Jointly Identifying Predicates, Arguments and Senses using Markov Logic

In this paper we present a Markov Logic Network for Semantic Role Labelling that jointly performs predicate identification, frame disambiguation, argument identification and argument classification for all predicates in a sentence. Empirically we find that our approach is competitive: our best model would appear on par with the best entry in the CoNLL 2008 shared task open track, and at the 4th place of the closed track---right behind the systems that use significantly better parsers to generate their input features. Moreover, we observe that by fully capturing the complete SRL pipeline in a single probabilistic model we can achieve significant improvements over more isolated systems, in particular for out-of-domain data. Finally, we show that despite the joint approach, our system is still efficient.
Unique Metabolic Features of Stem Cells, Cardiomyocytes, and Their Progenitors

Recently, growing attention has been directed toward stem cell metabolism, with the key observation that the plasticity of stem cells also reflects the plasticity of their energy substrate metabolism. There seems to be a clear link between the self-renewal state of stem cells, in which cells proliferate without differentiation, and the activity of specific metabolic pathways. Differentiation is accompanied by a shift from anaerobic glycolysis to mitochondrial respiration. This metabolic switch of differentiating stem cells is required to cover the energy demands of the different organ-specific cell types. Among other metabolic signatures, amino acid and carbohydrate metabolism is most prominent in undifferentiated embryonic stem cells, whereas the fatty acid metabolic signature is unique in cardiomyocytes derived from embryonic stem cells. Identifying the specific metabolic pathways involved in pluripotency and differentiation is critical for further progress in the field of developmental biology and regenerative medicine. The recently generated knowledge on metabolic key processes may help to generate mature stem cell–derived somatic cells for therapeutic applications without the requirement of genetic manipulation. In the present review, the literature about metabolic features of stem cells and their cardiovascular cell derivatives as well as the specific metabolic gene signatures differentiating between stem and differentiated cells are summarized and discussed.
TREC-5 Ad Hoc Retrieval Using K Nearest-Neighbors Re-Scoring

AA. focus on improving on baseline results obtained from another search engine by means of automatic query expansion. They call the specific formula used for query expansion Knn re-scoring, where Knn stands for K nearest-neighbors. The first-pass ranking is done using Okapi system's basic scoring formula. The documents are theen rescored using the same formula with the top-ranked K documents as queries, weighted according to their first-pass scores. The formula is motivated by viewing the rescoring process as a Markov process. This approach improves the precision outside the topK retrieved documents. They have implemented a query expansion scheme using all the words and some of the bigrams in the topK documents
Measuring independence of datasets

Approximating pairwise, or k-wise, independence with sublinear memory is of considerable importance in the data stream model. In the streaming model the joint distribution is given by a stream of k-tuples, with the goal of testing correlations among the components measured over the entire stream. Indyk and McGregor (SODA 08) recently gave exciting new results for measuring pairwise independence in this model. Statistical distance is one of the most fundamental metrics for measuring the similarity of two distributions, and it has been a metric of choice in many papers that discuss distribution closeness. For pairwise independence, the Indyk and McGregor methods provide log{n}-approximation under statistical distance between the joint and product distributions in the streaming model. Indyk and McGregor leave, as their main open question, the problem of improving their log n-approximation for the statistical distance metric. In this paper we solve the main open problem posed by Indyk and McGregor for the statistical distance for pairwise independence and extend this result to any constant k. In particular, we present an algorithm that computes an (ε, δ)-approximation of the statistical distance between the joint and product distributions defined by a stream of k-tuples. Our algorithm requires O((1/ε log(nm/δ))(30+k)k) memory and a single pass over the data stream.
Knowledge Reposiory as Entity Similarity Computing Enabler

With the adoption of Semantic Web technologies, knowledge based applications are nowadays common. They rely on the use of numerous and varied knowledge organization systems. This raises the problem of the interoperability of the underlying models in particular for data integration purpose. We present in this paper an approach based on an ontology server and providing functionalities including ontology matching and change detection. The evaluation of the matching approach using standard measure of recall/precision/F-measure shows results which outperform in certain contexts current available systems which are able to process large data set.
Dynamic Programming for Partially Observable Stochastic Games

We develop an exact dynamic programming algorithm for partially observable stochastic games (POSGs). The algorithm is a synthesis of dynamic programming for partially observable Markov decision processes (POMDPs) and iterated elimination or dominated strategies in normal form games. We prove that when applied to finite-horizon POSGs, the algorithm iteratively eliminates very weakly dominated strategies without first forming a normal form representation of the game. For the special case in which agents share the same payoffs, the algorithm can be used to find an optimal solution. We present preliminary empirical results and discuss ways to further exploit POMDP theory in solving POSGs.
Persistent cognitive decline in older hospitalized patients in Taiwan.

AIM This paper is a report of a study conducted to determine the prevalence and predictors of persistent and transient cognitive decline in older hospitalized patients over 6 months after hospital discharge. BACKGROUND Cognitive decline occurs in 16-35.5% of older hospitalized patients, but this decline may be persistent rather than transient. Distinguishing persistent from transient cognitive decline is clinically useful. METHODS For this prospective cohort study, 291 older patients were recruited from five medical and surgical units at a tertiary medical centre in Taiwan between 2004 and 2006. Participants were assessed for cognitive status by scores on the Mini-Mental State Examination at admission, discharge, 3 and 6 months postdischarge. Persistent cognitive decline was defined as continuing score reduction and > or =3-point reduction 6 months postdischarge. Transient decline was defined as > or = 3-point reduction at some stage, with a total decline < 3 points 6 months postdischarge. Findings. The cognitive status of the majority of participants (57.4%, n = 167) decreased > or =3 points during follow-up. Of these decliners, 59 (35.3%) had persistent cognitive decline, with an average 5.32-point reduction 6 months postdischarge. Forty-six (27.5%) participants experienced transient cognitive decline. After multiple adjustments in logistic regression analysis, persistent decline was predicted by no in-hospital functional decline (OR = 0.16, P = 0.002), more re-admissions after discharge (OR = 2.42, P = 0.020), and older age (OR = 1.09, P = 0.048). CONCLUSION A new perspective is needed on discharge planning on patients at risk for persistent cognitive decline. Nurses can oversee the delivery of care, identify cognitive decline, refer patients, and educate families on strategies to enhance cognitive functioning for their aging relatives.
A Computer Tournament of Adaptive Decision Making: Two-Person Iterated Games of Limited Information

Acknowledgments: We are indebted to a number of people for help on this paper. Beau Keogh provided essential programming support. Jonathan Bendor, James Kuklinski, Gary Miller, Robert Pahre, Buddy Peyton, and the attendees at a seminar at the University of Illinois at which early portions of this research were presented provided useful comments, as did our discussant Thomas Hammond and attendees at a panel of the Midwest Political Science Association’s annual meeting in Chicago, 2003. Author’s names are listed in alphabetical order.
A Novel Approach of Obtaining Features Using Wavelet Based Image Fusion and Harris Corner Detection

In this paper we proposed a method of corner detection for obtaining features which is required for tracking and recognizing objects from a fused image. Image fusion is a combination of information gathered from different images which is useful for extraction of more numbers of features from Multibiometric systems, useful for the purpose of biometric recognition and identification. Image fusion is carried out using wavelet based alpha blending technique.
MMSE decoding for analog joint source channel coding using monte carlo importance sampling

We investigate the performance of a discrete-time all-analog-processing joint source-channel coding system for the transmission of i.i. d. Gaussian sources over additive white Gaussian noise (AWGN) channels. At the encoder, samples of an i.i. d. source are grouped and mapped into a channel symbol using a space-filling curve. Different from previous work in the literature, MMSE instead of ML decoding is considered, and we focus on both high and low channel SNR regions. In order to reduce complexity, Monte Carlo importance sampling is applied in the decoding process. The main contribution of this paper is to show that for a wide range of rates the proposed system presents a performance very close to the theoretical limits, even at low SNR, as long as the curve parameters are properly optimized.
Engineering Attenuated Virulence of a Theileria annulata–Infected Macrophage

Live attenuated vaccines are used to combat tropical theileriosis in North Africa, the Middle East, India, and China. The attenuation process is empirical and occurs only after many months, sometimes years, of in vitro culture of virulent clinical isolates. During this extensive culturing, attenuated lines lose their vaccine potential. To circumvent this we engineered the rapid ablation of the host cell transcription factor c-Jun, and within only 3 weeks the line engineered for loss of c-Jun activation displayed in vitro correlates of attenuation such as loss of adhesion, reduced MMP9 gelatinase activity, and diminished capacity to traverse Matrigel. Specific ablation of a single infected host cell virulence trait (c-Jun) induced a complete failure of Theileria annulata–transformed macrophages to disseminate, whereas virulent macrophages disseminated to the kidneys, spleen, and lungs of Rag2/γC mice. Thus, in this heterologous mouse model loss of c-Jun expression led to ablation of dissemination of T. annulata–infected and transformed macrophages. The generation of Theileria-infected macrophages genetically engineered for ablation of a specific host cell virulence trait now makes possible experimental vaccination of calves to address how loss of macrophage dissemination impacts the disease pathology of tropical theileriosis.
Coming to grips with the objects we grasp: detecting interactions with efficient wrist-worn sensors

The use of a wrist-worn sensor that is able to read nearby RFID tags and the wearer's gestures has been suggested frequently as a way to both detect the objects we interact with and to identify the interaction. Making such a prototype feasible for longer-term deployments is far from solved however, as plenty of challenges remain in the hardware, embedded algorithms, and the overall design of such a bracelet-like device. This paper presents several of the challenges that emerged during the development of a functioning prototype that is able to sense interaction data for several days. We focus in particular on RFID tag reading range optimization, efficient data logging methods, meaningful evaluation techniques, and long-term deployments.
Genome-Wide Association Implicates Candidate Genes Conferring Resistance to Maize Rough Dwarf Disease in Maize

Maize rough dwarf disease (MRDD) is a destructive viral disease in China, which results in 20–30% of the maize yield losses in affected areas and even as high as 100% in severely infected fields. Understanding the genetic basis of resistance will provide important insights for maize breeding program. In this study, a diverse maize population comprising of 527 inbred lines was evaluated in four environments and a genome-wide association study (GWAS) was undertaken with over 556000 SNP markers. Fifteen candidate genes associated with MRDD resistance were identified, including ten genes with annotated protein encoding functions. The homologous of nine candidate genes were predicted to relate to plant defense in different species based on published results. Significant correlation (R2 = 0.79) between the MRDD severity and the number of resistance alleles was observed. Consequently, we have broadened the resistant germplasm to MRDD and identified a number of resistance alleles by GWAS. The results in present study also imply the candidate genes in defense pathway play an important role in resistance to MRDD in maize.
Group Exporting from manufacturing firms in Sub-Saharan Africa GPRG-WPS-036

The poor performance of many African economies has been associated with low growth of exports in general and of manufacturing exports in particular. In this paper we draw on micro evidence of manufacturing firms in five African countries Kenya, Ghana, Tanzania, South Africa and Nigeria to investigate the causes of poor exporting performance. We exploit a data set which has a much longer panel dimension than has been used before to assess the relative importance of self-selection based on efficiency and firm size as determinants of export participation. We show that firm size is a robust determinant of the decision to export. It is not a proxy for efficiency, for capital intensity, for sector or for time-invariant unobservables. In contrast the evidence for self-selection into exporting is very weak. Finally our use of a longer run panel than has been available before has allowed us to separate out the roles of ownership and skills as possible determinants of participation in exporting. We find that both foreign ownership and skills are significant determinants of exporting. This paper draws on data collected as part of the Regional Program on Enterprise Development (RPED), organised by the World Bank and funded by the Belgian, British, Canadian, Dutch, French and Swedish governments. Extensions to this data for Ghana were collected by a team from the Centre for the Study of African Economies, Oxford and the Ghana Statistical Office (GSO), Accra over a period from 1992 to 2003. The surveys have been funded by the Department for International Development of the UK government. The Kenyan, Nigerian and Tanzanian data collection was funded by both DFID and UNIDO. Work on this project was funded by the Economic and Social Research Council of the UK as part of the Global Poverty Research Group. We are greatly indebted to numerous collaborators for enabling this comparative data to be assembled.
Reporting standards for transjugular intrahepatic portosystemic shunts.

IN the last 5 years, the transjugular intrahepatic portosystemic shunt (TIPS) procedure has become widely disseminated. The number of interventional radiologists who are creating shunts has steadily increased as the procedure has become an accepted method of reducing portal vein pressure (1–28). Although the optimal technique for shunt creation continues to evolve, shunts can routinely be created in more than 93% of patients (5,8,13, 14,18,29). Accordingly, significant attention is now directed to the collection and reporting of prospective, standardized controlled data regarding the safety, efficacy, and patency of TIPS. The purpose of this document is to aid this process by recommending standards for reporting of TIPS data. At present, the most accepted indication for TIPS is for the treatment of recurrent variceal hemorrhage that is refractory or not amenable to endoscopic therapy. Other indications are being evaluated, such as refractory ascites. It is too early to reach a consensus on reporting standards addressing all uses of TIPS. Future addenda to this document will discuss other uses of TIPS as they become more established.
High-Quality Binary Protein Interaction Map of the Yeast Interactome Network

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a “second-generation” high-quality, high-throughput Y2H data set covering ∼20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.
Stochastic Convex Optimization

For supervised classification problems, it is well known that learnability is equivalent to uniform convergence of the empirical risks and thus to learnability by empirical minimization. Inspired by recent regret bounds for online convex optimization, we study stochastic convex optimization, and uncover a surprisingly different situation in the more general setting: although the stochastic convex optimization problem is learnable (e.g. using online-to-batch conversions), no uniform convergence holds in the general case, and empirical minimization might fail. Rather then being a difference between online methods and a global minimization approach, we show that the key ingredient is strong convexity and regularization. Our results demonstrate that the celebrated theorem of Alon et al on the equivalence of learnability and uniform convergence does not extend to Vapnik’s General Setting of Learning, that in the General Setting considering only empirical minimization is not enough, and that despite Vanpnik’s result on the equivalence of strict consistency and uniform convergence, uniform convergence is only a sufficient, but not necessary, condition for meaningful non-trivial learnability.