Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in Precision Medicine: Tailoring Individualized Therapies

The traditional bench-to-bedside pipeline involves using model systems and patient samples to provide insights into pathways deregulated in cancer. This discovery reveals new biomarkers and therapeutic targets, ultimately stratifying patients and informing cohort-based treatment options. Precision medicine (molecular profiling of individual tumors combined with established clinical-pathological parameters) reveals, in real-time, individual patient’s diagnostic and prognostic risk profile, informing tailored and tumor-specific treatment plans. Here we discuss advances in precision medicine presented at the Irish Association for Cancer Research Annual Meeting, highlighting examples where personalized medicine approaches have led to precision discovery in individual tumors, informing customized treatment programs.
Guidelines for evaluating grid connected PV system topologies

Several grid connected photovoltaic system topologies are used in existing installations. This paper proposes evaluation criteria for comparing and choosing topologies compatible with the user's demands. After presenting an overview of current architectures used in grid connected systems, five key points for comparison based on topology upgradeability, performance under shaded conditions, degraded mode operation, investment costs and ancillary service participation are discussed. The proposed method can be adapted to the user's particular needs and expectations of the photovoltaic plant.
Transcriptional Profiling of Endocrine Cerebro-Osteodysplasia Using Microarray and Next-Generation Sequencing

Background Transcriptome profiling of patterns of RNA expression is a powerful approach to identify networks of genes that play a role in disease. To date, most mRNA profiling of tissues has been accomplished using microarrays, but next-generation sequencing can offer a richer and more comprehensive picture. Methodology/Principal Findings ECO is a rare multi-system developmental disorder caused by a homozygous mutation in ICK encoding intestinal cell kinase. We performed gene expression profiling using both cDNA microarrays and next-generation mRNA sequencing (mRNA-seq) of skin fibroblasts from ECO-affected subjects. We then validated a subset of differentially expressed transcripts identified by each method using quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, we used gene ontology (GO) to identify critical pathways and processes that were abnormal according to each technical platform. Methodologically, mRNA-seq identifies a much larger number of differentially expressed genes with much better correlation to qRT-PCR results than the microarray (r2 = 0.794 and 0.137, respectively). Biologically, cDNA microarray identified functional pathways focused on anatomical structure and development, while the mRNA-seq platform identified a higher proportion of genes involved in cell division and DNA replication pathways. Conclusions/Significance Transcriptome profiling with mRNA-seq had greater sensitivity, range and accuracy than the microarray. The two platforms generated different but complementary hypotheses for further evaluation.
LFA‐1 (CD11a/CD18) triggers hydrogen peroxide production by canine neutrophils

The respiratory burst of neutrophils stimulated by chemotactic factors is markedly augmented by Mac‐1‐dependent adhesion such as the interaction of Mac‐1 (CD11b/CD18) with intercellular adhesion molecule‐1 (ICAM‐1; CD54) expressed on the surface of parenchymal cells (e.g., cardiac myocytes). In the current study, we evaluate the hypothesis that lymphocyte function‐associated antigen‐1 (LFA‐1; CD11a/CD18) can also trigger the respiratory burst in neutrophils. To isolate LFA‐1/ICAM‐1 interactions from Mac‐1/ICAM‐1 interactions, full‐length chimeric ICAM‐1 was developed and expressed in L cells with domains 1 and 2 from canine ICAM‐1 and domains 3–5 from human ICAM‐1 (C1,2;H3–5). We have shown that canine neutrophils do not bind to human ICAM‐1. We demonstrated that chimeric ICAM‐1 C1,2;H3–5 supported only LFA‐1‐dependent adhesion of canine neutrophils and that such adhesion triggered rapid onset of H2O2 production from canine neutrophils. The following seven experimental conditions distinguished LFA‐1‐dependent H2O2 production from Mac‐1‐dependent production: It did not require exogenous chemotactic stimulation; H2O2 release was more rapid, but the amount released was <40% of that mediated by Mac‐1 adhesion; it was inhibited by anti‐CD11a and anti‐ICAM‐1 antibodies; in contrast to that mediated by Mac‐1, it was not inhibited by anti‐CD11b antibody, neutrophil inhibitory factor (NIF), or cytochalasin B or H7. Thus, canine neutrophils seem to be able to utilize two members of the β2 integrin family to interact with ICAM‐1 and signal H2O2 production, with LFA‐1 at an early stage without prior chemotactic stimulation and Mac‐1 at a later stage requiring chemotactic stimulation.
Link and Node Protection using Hamiltonian p-Cycles found by Ant-like Agents

Protection cycles is a well know dependability measure and commonly applied in SDH networks with ring topologies. Applying protection cycles (known as p-cycles) in meshed network has recently been shown to provide good protection against failures in both network links and nodes. Upcoming optical burst and packet switched networks will require node protection. Increasing the density of meshing in such networks and applying p-cycle protection may prove more cost efficient than traditional protection by standby node redundancy. Swarm intelligence is a distributed system construction concept which has shown promising results when applied to problems within the area of network and operational management. Swarm Intelligence systems are fully distributed (without central components) have high redundancy, are adaptable, and can find near optimal solutions to NP-hard problems. This paper describes a new swarm intelligence system based on the CE-ant algorithm developed by Helvik and Wittner. The system is capable of finding near optimal Hamiltonian cycles in meshed networks with respect to the amount of spare capacity on the links in the cycle. Early results from simulations indicate that the new system has a promising ability to find good candidate p-cycles.
Statistical Physics, Mixtures of Distributions, and the EM Algorithm

We show that there are strong relationships between approaches to optmization and learning based on statistical physics or mixtures of experts. In particular, the EM algorithm can be interpreted as converging either to a local maximum of the mixtures model or to a saddle point solution to the statistical physics system. An advantage of the statistical physics approach is that it naturally gives rise to a heuristic continuation method, deterministic annealing, for finding good solutions.
Lipreading Using Profile Versus Frontal Views

Visual information from a speaker's mouth region is known to improve automatic speech recognition robustness. However, the vast majority of audio-visual automatic speech recognition (AVASR) studies assume frontal images of the speaker's face. In contrast, this paper investigates extracting visual speech information from the speaker's profile view, and, to our knowledge, constitutes the first real attempt to attack this problem. As with any AVASR system, the overall recognition performance depends heavily on the visual front end. This is especially the case with profile-view data, as the facial features are heavily compacted compared to the frontal scenario. In this paper, we particularly describe our visual front end approach, and report experiments on a multi-subject, small-vocabulary, bimodal, multi-sensory database that contains synchronously captured audio with frontal and profile face video. Our experiments show that AVASR is possible from profile views with moderate performance degradation compared to frontal video data
Adaptive control of nonlinear teleoperation systems with varying asymmetric time delays

In this paper, a new adaptive control design method for nonlinear telerobotic systems with varying asymmetric time delays is presented. Using the proposed controller, it is possible to synchronize the state behavior of the local and the remote robots. While prior art on adaptive teleoperation has addressed stability in such systems only for constant delays, we guarantee asymptotic stability in the presence of delays that may be time-varying and/or unequal in the forward and backward directions. Using the proposed controller, asymptotic stability of the bilateral teleoperation system subject to any bounded varying delay with a bounded rate of variation can be guaranteed. The proposed controller also has the ability to cope with parameter variations in the dynamics of the local and the remote robots. To study the transparency of the closed-loop teleoperation system, we prove that the position and velocity errors between the local and the remote manipulators converge to zero asymptotically. To show the efficiency of the proposed controller, simulation results on a pair of two-degree-of-freedom manipulators with varying time delays in the communication channel are presented.
TaxoMap in the OAEI 2007 Alignment Contest

An automatic address assignment system has a plurality of I/O devices coupled to a bus. Each device contains a unique machine-readable identifier which is used to select the device for address assignment. The identifier is a binary bit string. Each bit position in the bit string is selected by the host in a serial manner with the host specifying which binary value is being solicited. All devices whose identifier digit matches the solicited value respond positively and remain in contention for address assignment. The other devices will not respond and drop out of contention for address assignment until the sequence is restarted from the first bit. After the bit sequence is completed, the address for that device is bused to the device, and the sequence is restarted from the first bit until all devices have been assigned an address.
Syndicated Loan Spreads and the Composition of the Syndicate

The past decade has seen significant changes in the structure of the corporate lending market, with non-bank institutional investors playing larger roles than they historically have played. These non-bank institutional lenders typically have higher required rates of return than banks, but invest in the same loan facilities. We hypothesize that non-bank institutional lenders invest in loan facilities that would not otherwise be filled by banks, so that the arranger has to offer a higher spread to attract the non-bank institution. In a sample of 20,031 leveraged loan facilities originated between 1997 and 2007, we find that, loan facilities including a non-bank institution in their syndicates have higher spreads than otherwise identical bank-only facilities. Contrary to risk-based explanations of this finding, non-bank facilities are priced with premiums relative to bank-only facilities of the same loan package. These premiums for non-bank facilities are substantially larger when a hedge or private equity fund is one of the syndicate members. Consistent with the notion that firms are willing to pay spread premiums when loan facilities are particularly important to the firm, we find that firms spend the capital raised by loan facilities priced at a premium faster than other loan facilities, especially when the premium is associated with a non-bank institutional investor.
Domain-specific classification methods for disfluency detection

Speech disﬂuencies are very common in our everyday life and considerably affect NLP systems, which makes systems that can detect or even repair them highly desirable. Previous research achieved good results in the ﬁeld of disﬂuency detection but only in subsets of the disﬂuency types. The aim of this study was to develop a technology that is able to cope with a broad ﬁeld of disﬂuency types. A thorough investigation of our corpus led us to a detection design where basic rule-matching techniques are complemented with machine learning and N-gram based approaches. In this paper, we describe the different detection techniques, each specialized on its own disﬂuency domain and the results we gained.
What causes asymmetric price transmission in agro-food sector? : meta-analysis perspective

There now exists a large literature on price transmission in agro-food sectors. However, a great majority of empirical studies focus on the existence of asymmetry and, by and large, do not allow investigating the reason for its presence or absence. This is in sharp contrast to the theoretical literature that provides a number of explanations for why we should expect (a)symmetry. In response to this, this paper tries to uncover the reasons for asymmetric price transmission in the agro-food chain. To do so, we use meta-analysis drawing on the existing studies from this area. Our focus is on the organizational and institutional characteristics of the agro-food supply chain. Our findings suggest that asymmetric price transmission in farm-retail relationship is more likely to occur in sectors/countries with more fragmented farm structure, higher governmental support and more restrictive regulations on price controls in retail sector. On the other hand, more restrictive regulations on entry barriers in retail sector and relative importance of the sector in question tend to promote symmetric farm-retail price transmission. The latter is also more likely in the presence of strong processing industry.
Multi-Scale Probabilistic Dithering for Suppressing Banding Artifacts in Digital Images

A method is proposed for reducing the visibility of "banding artifacts," i.e. false contours resulting from color quantization in digital images. The method performs a multi-scale analysis on the neighborhood of each pixel, determines the presence and scale of banding artifacts, and probabilistically dithers (perturbs) the color of the pixel. The overall effect is to "break down" the false contours making them less visible. The proposed method may be used to reduce banding artifacts at the same bit depth as the input image or at higher bit depths. The banding detection mechanism ensures that artifact-free regions remain unaffected during the process.
A Robust Test for Two‐Stage Design in Genome‐Wide Association Studies

Summary A two‐stage design is cost‐effective for genome‐wide association studies (GWAS) testing hundreds of thousands of single nucleotide polymorphisms (SNPs). In this design, each SNP is genotyped in stage 1 using a fraction of case–control samples. Top‐ranked SNPs are selected and genotyped in stage 2 using additional samples. A joint analysis, combining statistics from both stages, is applied in the second stage. Follow‐up studies can be regarded as a two‐stage design. Once some potential SNPs are identified, independent samples are further genotyped and analyzed separately or jointly with previous data to confirm the findings. When the underlying genetic model is known, an asymptotically optimal trend test (TT) can be used at each analysis. In practice, however, genetic models for SNPs with true associations are usually unknown. In this case, the existing methods for analysis of the two‐stage design and follow‐up studies are not robust across different genetic models. We propose a simple robust procedure with genetic model selection to the two‐stage GWAS. Our results show that, if the optimal TT has about 80% power when the genetic model is known, then the existing methods for analysis of the two‐stage design have minimum powers about 20% across the four common genetic models (when the true model is unknown), while our robust procedure has minimum powers about 70% across the same genetic models. The results can be also applied to follow‐up and replication studies with a joint analysis.
The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding

MOTIVATION Receptor-ligand interactions play an important role in controlling many biological systems. One prominent example is the binding of peptides to the major histocompatibility complex (MHC) molecules controlling the onset of cellular immune responses. Thousands of MHC allelic versions exist, making determination of the binding specificity for each variant experimentally infeasible. Here, we present a method that can extrapolate from variants with known binding specificity to those where no experimental data are available. RESULTS For each position in the peptide ligand, we extracted the polymorphic pocket residues in MHC molecules that are in close proximity to the peptide residue. For MHC molecules with known specificities, we established a library of pocket-residues and corresponding binding specificities. The binding specificity for a novel MHC molecule is calculated as the average of the specificities of MHC molecules in this library weighted by the similarity of their pocket-residues to the query. This PickPocket method is demonstrated to accurately predict MHC-peptide binding for a broad range of MHC alleles, including human and non-human species. In contrast to neural network-based pan-specific methods, PickPocket was shown to be robust both when data is scarce and when the similarity to MHC molecules with characterized binding specificity is low. A consensus method combining the PickPocket and NetMHCpan methods was shown to achieve superior predictive performance. This study demonstrates how integration of diverse algorithmic approaches can lead to improved prediction. The method may also be used for making ligand-binding predictions for other types of receptors where many variants exist.
Under Consideration for Publication in Theory and Practice of Logic Programming Polytool: Polynomial Interpretations as a Basis for Termination Analysis of Logic Programs

Our goal is to study the feasibility of porting termination analysis techniques developed for one programming paradigm to another paradigm. In this paper, we show how to adapt termination analysis techniques based on polynomial interpretations-very well known in the context of term rewrite systems (TRSs)-to obtain new (non-transformational) termination analysis techniques for definite logic programs (LPs). This leads to an approach that can be seen as a direct generalization of the traditional techniques in termination analysis of LPs, where linear norms and level mappings are used. Our extension generalizes these to arbitrary polynomials. We extend a number of standard concepts and results on termination analysis to the context of polynomial interpretations. We also propose a constraint-based approach for automatically generating polynomial interpretations that satisfy the termination conditions. Based on this approach, we implemented a new tool, called Polytool, for automatic termination analysis of LPs.
Physical and functional link of the leukemia-associated factors AML 1 and PML

The AML1-CBF transcription factor complex is the most frequent target of specific chromosome translocations in acute myeloid leukemia (AML). The promyelocytic leukemia (PML) gene is also frequently involved in AML-associated translocation. Here we report that a specific isoform PML I forms a complex with AML1. PML I was able to recruit AML1 and coactivator p300 in PML nuclear bodies and enhance the AML1-mediated transcription in the presence of p300. A specific C-terminal region of PML I and a Cterminal region of AML1 were found to be required for both their association and colocalization in the nuclear bodies. Overexpression of PML I stimulates myeloid cells to differentiate. These results suggest that PML I could act as a mediator for AML1 and its coactivator p300/CBP to assemble into functional complexes and, consequently, activate AML1-dependent transcription and myeloid cell differentiation. (Blood. 2005;105:292-300)
A re-optimization dynamic shortest path algorithm for vehicle navigation

The traffic congestion changes over time in the real transportation network, and the vehicle navigation is a real-time processing. Both the accuracy and time performance of navigation algorithm are important. To respond rapidly to transportation network changes, this paper proposes two new dynamic shortest path algorithms based on the re-optimization method. The algorithms take full advantage of the previous search results, thus they take relatively few computing time to obtain the optimal solution. Experimental results demonstrate that the proposed algorithms can be applied to vehicle navigation in the transportation network with dynamic variation of the travel times on arcs and runs much faster than the traditional Dijkstra algorithm.
SelD homolog from Drosophila lacking selenide-dependent monoselenophosphate synthetase activity.

The isolation and molecular characterization of an invertebrate gene that encodes a homolog of the human selenophosphate synthetase 1 is described. This Drosophila gene, termed selD-like, is located in the cytogenetic interval 50 D/E on the right arm of chromosome 2. It is expressed ubiquitously throughout embryogenesis and found to be highly enriched in the developing gut and in the nervous system of the embryo. The SelD-like from Drosophila was purified after expression in Escherichia coli. The purified protein does not catalyze the selenide-dependent ATP hydrolysis reaction and its gene does not complement a selD lesion in E. coli. These results and the fact that selD-like possesses an arginine residue at the position of the essential Cys17 (E. coli nomenclature) indicate that the Drosophila gene exerts a function different from that of the classical selenophosphate synthetases. Two classes of SelD proteins can therefore be differentiated. The class I proteins contain a cysteine or selenocysteine residue in the active site and display selenide-dependent selenophosphate synthetase activity. Class II proteins, including Drosophila selD-like and human selenophosphate synthetase 1 are devoid of this activity and they possess other amino acids in position 17.
Redox Regulation of Nonmuscle Myosin Heavy Chain during Integrin Engagement

On the basis of our findings reporting that cell adhesion induces the generation of reactive oxygen species (ROS) after integrin engagement, we were interested in identifying redox-regulated proteins during this process. Mass spectrometry analysis led us to identify nonmuscle myosin heavy chain (nmMHC) as a target of ROS. Our results show that, while nmMHC is reduced in detached/rounded cells, it turns towards an oxidized state in adherent/spread cells due to the integrin-engaged ROS machinery. The functional role of nmMHC redox regulation is suggested by the redox sensitivity of its association with actin, suggesting a role of nmMHC oxidation in cytoskeleton movement. Analysis of muscle MHC (mMHC) redox state during muscle differentiation, a process linked to a great and stable decrease of ROS content, shows that the protein does not undergo a redox control. Hence, we propose that the redox regulation of MHC in nonprofessional muscle cells is mandatory for actin binding during dynamic cytoskeleton rearrangement, but it is dispensable for static and highly organized cytoskeletal contractile architecture in differentiating myotubes.