Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Analysis of Experiments

This chapter was contributed by Andrew Speedy, University of Oxford, UK. The objective is to assist researchers to compile and analyze data. To this end, use is made of one of the simpler statistics programs (MINITAB, Minitab Inc., Philadelphia, USA) as the model. More powerful statistical packages may be required for studies in plant and animal genetics and agricultural economics. But, in line with the general philosophy of this manual, it is considered that simplicity and ease of understanding are the principal attributes required of a computer program and, in this respect, Minitab has much to commend it and is therefore selected as the example. But obviously there are various other often more sophisticated statistical software packages available on the market.
Manipulating Large Corpora for Text Classification

In this paper, we address the problem of dealing with a large collection of data and propose a method for text classification which manipulates data using two well-known machine learning techniques, Naive Bayes(NB) and Support Vector Machines(SVMs). NB is based on the assumption of word independence in a text, which makes the computation of it far more efficient. SVMs, on the other hand, have the potential to handle large feature spaces, which makes it possible to produce better performance. The training data for SVMs are extracted using NB classifiers according to the category hierarchies, which makes it possible to reduce the amount of computation necessary for classification without sacrificing accuracy.
Iterative Term Weighting for Short Text Data

With the development of social media applications, short text mining is becoming more and more important. Due to the sparseness of short text data, both the feature correlation information (word co-occurrence) and data contiguity information (context information) are less reliable, thus most existing text mining methods which are designed to address regular text data are less efficient in short text mining tasks. According to our observation from analysis of discriminative term distribution in short text data, we found that discriminative terms distribute in a non-uniform way among different domains, while background words have a tendency to distribute uniformly. This observation can be measured by a suitably defined functional of a term's probability distribution over different domains. In this paper, we adopt this distribution as the weight of terms to address the sparseness problem of short text data. We evaluate our method on two datasets, and experimental results show that our method outperforms previous approaches which require information infusion, and a number of state-of-the-art clustering algorithms. Furthermore, our method can obtain a more coherent clustering result.
Using inter-lingual triggers for machine translation

In this paper, we present the idea of cross-lingual triggers. We exploit this formalism in order to build up a bilingual dictionary for machine translation. We describe the idea of cross-lingual triggers, the way to exploit and to make good use of them in order to produce a bilingual dictionary. We then compare it to ELRA and a free downloaded dictionaries. Finally, our dictionary is evaluated by comparing it to the one achieved by GIZA++ (which is an extension of the program GIZA) into an entire translation decoding process supplied by Pharaoh. The experiments showed that the obtained dictionary is well constructed and is suitable for machine translation. The experiments have been conducted on a parallel corpus of 19 million French words and of 17 million English words. Finally, the encouraging results allow us to put forward the concept of cross-lingual triggers which could have so many applications in machine translation.
Guessing secrets efficiently via list decoding

We consider the guessing secrets problem defined by Chung, Graham, and Leighton [CGL01]. This is a variant of the standard 20 questions game where the player has a set of k > 1 secrets from a universe of N possible secrets. The player is asked Boolean questions about the secret for each question, the player picks one of the k secrets adversarially, and answers according to this secret.We present an explicit set of O(log N) questions together with an efficient (i.e., poly(log N) time) algorithm to solve the guessing secrets problem for the case of 2 secrets. This answers the main algorithmic question left unanswered by [CGL01]. The main techniques we use are small ε-biased spaces and the notion of list decoding.We also establish bounds on the number of questions needed to solve the k-secrets game for k > 2, and discuss how list decoding can be used to get partial information about the secrets.
The Global Bio Grid at Virginia

The future of the life sciences will depend on distributed, large-scale, integrated, computational infrastructures, called Grids. Indeed, as observed recently by the National Research Council, "biology is becoming an information science". An interdisciplinary group of biologists, computer scientists, and clinicians at the University of Virginia have teamed up to implement this exciting vision and to make it a reality in the near future. The University of Virginia Center for Grid Research (CGR) was founded with the belief that the life sciences are the “killer application” for Grid computing, and with the commitment to transform life sciences research by providing the tools to Grid-enable the life sciences. The center has four specific objectives; we will: (1) Develop and deploy the Global Bio Grid (GBG), a data, computational, and algorithmic infrastructure for the life sciences; The GBG will provide a shared, secure infrastructure for collaboration and research across academic, government, and industrial institutions – and across the spectrum of life sciences applications. (2) Perform Research on dependable Grid and Service Oriented Architectures (SOA). Grid computing technology is still in its’ infancy and many problems remain. Particular areas that we will focus on are data access, security (confidentiality, data integrity, access control, policy negotiation), dependability (availability, SLA’s, policy languagues), and grid standards. (3) Develop new algorithms, tools, and techniques for hierarchical data integration and analysis. (4) Outreach to the life sciences community to both accelerate their science and to better understand their requirements and special needs. This technical report gives an overview of Grid computing, life sciences use cases for Grid, and the Global Bio Grid technical plan and status as of September, 2004.
Dynamic hosting management of web based applications over clouds

Dynamic Application Hosting Management (DAHM) allows clouds to dynamically host applications in data centers at different locations based on: (i) spatio-temporal variation of energy price, (ii) data center computing and cooling energy efficiency, (iii) Virtual Machine (VM) migration cost for the applications, and (iv) any SLA violations due to migration overhead or network delay. DAHM is complementary to dynamic workload distribution problem and is modeled as mixed integer programming; online algorithms are developed to solve the problem. The algorithms are evaluated in a simulation study using realistic data and compared with performance-oriented application assignment, i.e., hosting the application at a data center whose delay is the least. Our simulations results indicate that DAHM can potentially save up to 20% cost while incurring only a nominal increase in SLA violations. The savings are obtained by exploiting the cost efficiency variation as well as reducing the total number of VMs employed to host applications.
SybilGuard: Defending Against Sybil Attacks via Social Networks

Peer-to-peer and other decentralized, distributed systems are known to be particularly vulnerable to sybil attacks. In a sybil attack, a malicious user obtains multiple fake identities and pretends to be multiple, distinct nodes in the system. By controlling a large fraction of the nodes in the system, the malicious user is able to ldquoout voterdquo the honest users in collaborative tasks such as Byzantine failure defenses. This paper presents SybilGuard, a novel protocol for limiting the corruptive influences of sybil attacks. Our protocol is based on the ldquosocial networkrdquo among user identities, where an edge between two identities indicates a human-established trust relationship. Malicious users can create many identities but few trust relationships. Thus, there is a disproportionately small ldquocutrdquo in the graph between the sybil nodes and the honest nodes. SybilGuard exploits this property to bound the number of identities a malicious user can create. We show the effectiveness of SybilGuard both analytically and experimentally.
Improving care-seeking for facility-based health services in a rural, resource-limited setting: Effects and potential of an mHealth project

The aim of this paper was to investigate the impact of a toll-free hotline and mobile messaging service on care-seeking behaviors. Due to the low uptake of the services, the treatment on the treated estimate is used. For maternal health, the intervention had a strong, positive impact on antenatal care initiation and skilled birth attendance. No effect was observed for postnatal check-ups, receiving the recommended four antenatal care visits and vitamin A uptake. A negative effect was observed on tetanus toxoid coverage. For child health, no change was seen in child immunization, and a significant decrease was observed for care-seeking for children with fever. Different factors are associated with care-seeking, which may explain in part the variations seen across care-seeking behaviors and possible influence of exogenous factors. Introduction of mHealth services for demand generation require attention to local health systems to ensure adequate supply and quality are available.
Dietary Patterns in High and Low Consumers of Meat in a Swedish Cohort Study

The objective was to examine relationships between meat and other food items which have been associated with higher risk of cancer in the colon and prostate in some epidemiological studies. The study was conducted as a population-based cohort study comprising 11648 subjects (4816 male and 6742 female) born between 1926 and 1945 and living in the city of Malmö, Sweden. Data on mean daily intake of foods and nutrients were assessed with a diet history method combining a 7-day menu book and a food frequency questionnaire. Increasing meat intake, expressed in quintiles and adjusted for energy, was associated with decreasing intakes of poultry, fish, fruits, bread, cereals and cheese in both sexes. Low negative correlations between meat intake and ascorbic acid (r= -0.11) and fiber (r= -0.16 to -0.20) were noted. The average intake of fat from meat out of total fat intake was 13.6% in men and 11.9% in women. No major associations were noted between meat and the cholesterol raising fatty acids C:12:0, C:14:0, C:160 nor for C:20:4 or its precursor C:18:2. In conclusion, our findings indicate that meat consumption is negatively associated with food groups rich in antioxidants and fiber and the positive covariance reported between meat and cancer and coronary heart disease might, therefore, not be directly linked to components in meat.
A Multipath Mitigation Localization Algorithm Based on MDS for Passive UHF RFID

Traditional localization algorithms are vulnerable in multipath environment for passive UHF RFID tag localization. To improve the localization accuracy, this letter proposes a robust algorithm named residual weighted multidimensional scaling (RWMDS) based on the multipath channel model. The RWMDS algorithm first utilizes reader-to-tag distances derived from received signal phase. To obtain the squared distance matrix required in the algorithm, the inter-tag distances are estimated using a few reference tags by establishing the relationship between inter-tag distance and phase information vectors measurement. Based on the modeling of ranging error in multipath environment, the RWMDS lgorithm can be applied to determine the estimated locations of the tags through a few iterations. Simulation results show that the RWMDS algorithm achieves higher localization accuracy than traditional algorithms in multipath environment.
Activin A and follistatin influence expression of somatostatin in the ciliary ganglion in vivo.

An important developmental question concerns whether neurotransmitter phenotype is an inherent property of neurons or is influenced by target tissues. This issue can be addressed in the avian ciliary ganglion (CG) which contains two cholinergic populations, ciliary and choroid neurons, that differentially express the peptide cotransmitter, somatostatin. The present study tests the hypothesis that differences in the level of expression of activin A and its endogenous inhibitor follistatin in CG neuron target tissues are responsible for selective expression of somatostatin in choroid neurons. Intraocular injection of activin A or follistatin (300 ng injected at E10/E11) in cultured embryos resulted in a 39% increase or a 23% decrease, respectively, in somatostatin-positive neurons relative to controls. Chorioallantoic membrane application of follistatin (1 microgram daily from E7 to E13) reduced somatostatin positive neurons by 54%. Neuron number, size, and target tissue morphology were unaffected by these treatments. Together with our previous studies, these data suggest that activin A and follistatin are target-derived molecules that regulate neuropeptide phenotype in the ciliary ganglion.
A new interleaved series input parallel output zero-voltage-switching forward converter

A new interleaved soft-switching forward converter is proposed in this paper. Two active-clamp forward converters are connected in series input and parallel output structure to share the input voltage and output current. The output capacitance of switches and the resonant inductance are utilized to realize the resonance at the transition interval of switches such that the zero-voltage-switching (ZVS) operation for all switches can be achieved. The current-doubler rectifier with ripple current cancellation is used to reduce the current stress of the transformer secondary winding. The interleaved PWM operation also diminishes the current ripple in the output capacitor to reduce the size of the output filter. All these features make the proposed converter suitable for high input voltage, high output current and high efficiency applications. The operating principles, steady-state analysis and design considerations of the proposed converter are presented. Finally, experimental results based on a 240 W (12V/20A) prototype are provided to verify the effectiveness of the proposed converter.
How does the ECB target in ‡ ation ?

The announced primary objective of the European Central Bank is price stability. While no restrictive reference is given to how the goal should be reached, such a mandate can be thought as a concern to stabilize some relevant macroeconomic aggregates. Accordingly, we frame ECB monetary policy in a general set up that allows policy makers to weight di¤erently positive and negative deviations of in‡ation and output gaps. The empirical analysis on aggregated Euro area data indicates that ECB monetary policy can be characterized by a nonlinear policy rule. While the objective of price stability is symmetric, the one on real activity is not in that output contractions require larger policy responses. Moreover, the actual Euro interest rate highly commoves with the counterfactual rate that the Bundesbank would have followed if charged to set policy rates for the Euro area. JEL Classi.cation: E52, E58.
Consensus Phylogenetic trees of Fifteen Prokaryotic Aminoacyl-tRNA Synthetase Polypeptides based on Euclidean Geometry of All-Pairs Distances and Concatenation

Background Most molecular phylogenetic trees depict the relative closeness or the extent of similarity among a set of taxa based on comparison of sequences of homologous genes or proteins. Since the tree topology for individual monogenic traits varies among the same set of organisms and does not overlap taxonomic hierarchy, hence there is a need to generate multidimensional phylogenetic trees. Results Phylogenetic trees were constructed for 119 prokaryotes representing 2 phyla under Archaea and 11 phyla under Bacteria after comparing multiple sequence alignments for 15 different aminoacyl-tRNA synthetase polypeptides. The topology of Neighbor Joining (NJ) trees for individual tRNA synthetase polypeptides varied substantially. We use Euclidean geometry to estimate all-pairs distances in order to construct phylogenetic trees. Further, we used a novel “Taxonomic fidelity” algorithm to estimate clade by clade similarity between the phylogenetic tree and the taxonomic tree. We find that, as compared to trees for individual tRNA synthetase polypeptides and rDNA sequences, the topology of our Euclidean tree and that for aligned and concatenated sequences of 15 proteins are closer to the taxonomic trees and offer the best consensus. We have also aligned sequences after concatenation, and find that by changing the order of sequence joining prior to alignment, the tree topologies vary. In contrast, changing the types of polypeptides in the grouping for Euclidean trees does not affect the tree topologies. Conclusions We show that a consensus phylogenetic tree of 15 polypeptides from 14 aminoacyl-tRNA synthetases for 119 prokaryotes using Euclidean geometry exhibits better taxonomic fidelity than trees for individual tRNA synthetase polypeptides as well as 16S rDNA. We have also examined Euclidean N-dimensional trees for 15 tRNA synthetase polypeptides which give the same topology as that constructed after amalgamating 3-dimensional Euclidean trees for groups of 3 polypeptides. Euclidean N-dimensional trees offer a reliable future to multi-genic molecular phylogenetics.
Evaluation of pre-existent immunity in patients with primary breast cancer: molecular and cellular assays to quantify antigen-specific T lymphocytes in peripheral blood mononuclear cells.

PURPOSE Breast cancers are known to frequently (over)express several well-characterized tumor-associated antigens (TAAs) such as carcinoembryonic antigen, MUC-1, Her-2/neu, and cancer/testis antigens such as NY-ESO-1, SSX-2, and members of the MAGE family. Whereas in melanoma patients, the detection of pre-existing T cell responses to tumor-associated differentiation antigens was a rationale to initiate several vaccination strategies, little is known thus far concerning tumor-specific immunity in breast cancer patients. The objectives of our study were (a) to modify and compare different immunodiagnostic T cell assays with regard to their suitability for clinical applications and (b) to determine endogenous TAA-specific T cell immunity of breast cancer patients at the time point of primary diagnosis. EXPERIMENTAL DESIGN Using MUC-1- and Her-2/neu-derived HLA-A*0201-restricted peptides as model antigens, we analyzed antigen-dependent IFN-gamma release of T cells by enzyme-linked immunospot (ELISpot) assay, intracellular cytokine flow cytometry (CytoSpot), and quantitative real-time PCR. As an assay independent of T cell function, we performed tetramer staining. RESULTS In our hands, the quantitative real-time PCR method is most sensitive and a feasible screening test to perform an "immunological staging" of cancer patients. By doing this, we detected in 7 of 13 (54%) of HLA-A*0201(+) breast cancer patients a pre-existent specific cellular immune response to at least one of the investigated TAAs (MUC-1, Her-2/neu, carcinoembryonic antigen, NY-ESO-1, and SSX-2). Four of 21 patients (19%) were found to have a significant Her-2/neu-specific T cell response as defined by a stimulation index >/==" BORDER="0"> 2 (range, 10-88). CONCLUSIONS Although the clinical relevance of endogenous TAA-specific immunity remains unclear, our findings suggest that patients with primary breast cancer can mount a T cell immune response to their tumor that might be beneficially enhanced by TAA-dependent vaccination strategies in the adjuvant situation.
Mitochondria to nucleus stress signaling

Mitochondrial genetic and metabolic stress causes activation of calcineurin (Cn), NFAT, ATF2, and NFκB/Rel factors, which collectively alter the expression of an array of nuclear genes. We demonstrate here that mitochondrial stress–induced activation of NFκB/Rel factors involves inactivation of IκBβ through Cn-mediated dephosphorylation. Phosphorylated IκBβ is a substrate for Cn phosphatase, which was inhibited by FK506 and RII peptide. Chemical cross-linking and coimmunoprecipitation show that NFκB/Rel factor–bound IκBβ forms a ternary complex with Cn under in vitro and in vivo conditions that was sensitive to FK506. Results show that phosphorylation at S313 and S315 from the COOH-terminal PEST domain of IκBβ is critical for binding to Cn. Mutations at S313/S315 of IκBβ abolished Cn binding, inhibited Cn-mediated increase of Rel proteins in the nucleus, and had a dominant-negative effect on the mitochondrial stress–induced expression of RyR1 and cathepsin L genes. Our results show the distinctive nature of mitochondrial stress–induced NFκB/Rel activation, which is independent of IKKα and IKKβ kinases and affects gene target(s) that are different from cytokine and TNFα-induced stress signaling. The results provide new insights into the role of Cn as a critical link between Ca2+ signaling and NFκB/Rel activation.
A Holonic Control Architecture for a Heterogeneous Multi-Objective Smart Micro-Grid

Designing the control infrastructure of future ``smart'' power grids is a challenging task. Such grids will integrate a wide variety of heterogeneous producers and consumers that are unpredictable and operate at various scales. Smart grids will need to control these in order to attain global objectives at the macro-level, while also taking into account local objectives and private interests at the micro-level. This paper proposes a holonic control architecture to help meet these requirements. We show how this architecture can integrate heterogeneous control solutions, including - when applicable - existing state-of-the-art solutions for the smart grid. To better illustrate the utility of this generic architecture we exemplify its use via a proof-of-concept implementation, integrating some basic control solutions. We show how this sample holonic controller can manage a grid simulator in several scenarios. Obtained results support our belief that the proposed architecture can facilitate the development of control solutions addressing the aforementioned challenges.