Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Diversity and Population Structure Analysis of European Hexaploid Bread Wheat (Triticum aestivum L.) Varieties

Progress in plant breeding is facilitated by accurate information about genetic structure and diversity. Here, Diversity Array Technology (DArT) was used to characterize a population of 94 bread wheat (Triticum aestivum L.) varieties of mainly European origin. In total, 1,849 of 7,000 tested markers were polymorphic and could be used for population structure analysis. Two major subgroups of wheat varieties, GrI and GrII, were identified using the program STRUCTURE, and confirmed by principal component analysis (PCA). These subgroups were largely separated according to origin; GrI comprised varieties from Southern and Eastern Europe, whereas GrII contained mostly modern varieties from Western and Northern Europe. A large proportion of the markers contributing most to the genetic separation of the subgroups were located on chromosome 2D near the Reduced height 8 (Rht8) locus, and PCR-based genotyping suggested that breeding for the Rht8 allele had a major impact on subgroup separation. Consistently, analysis of linkage disequilibrium (LD) suggested that different selective pressures had acted on chromosome 2D in the two subgroups. Our data provides an overview of the allele composition of bread wheat varieties anchored to DArT markers, which will facilitate targeted combination of alleles following DArT-based QTL studies. In addition, the genetic diversity and distance data combined with specific Rht8 genotypes can now be used by breeders to guide selection of crossing parents.
A Comparison Study on Interest Rate Models of SHIBOR Based on MCMC Method

The main goal of this paper is to investigate the presence of jumps in Shanghai Inter-bank Offered Rate (SHIBOR), which is Chinese money market benchmark interest rate, and compare interest rate models of SHIBOR based on MCMC Method. Although SHIBOR has become an important interest rate, on which a lot of derivatives underlie, it is less studied. The Markov Chain Monte Carlo method is applied to analyze the interest rate models of SHIBOR, such as Vasicek model, Cox-Ingersoll-Ross model, CKLS model and CKLS jump diffusion model. The empirical results indicate that the CKLS model with generalized specification of volatility parameter is better than Cox-Ingersoll-Ross model and Vasicek model, but all these models are miss-specified. After introducing the jump factor, the model captures the jumps of 1-week SHIBOR rate well and passes the specification test. The estimates indicate the jump happens with a high probability everyday in the time period researched.
GLOBAL DYNAMICS OF A CHEMOSTATCOMPETITION MODEL WITH DISTRIBUTED

We study the global dynamics of n-species competition in a chemo-stat with distributed delay describing the time-lag involved in the conversion of nutrient to viable biomass. The delay phenomenon is modelled by the gamma distribution. The linear chain trick and a uctuation lemma are applied to obtain the global limiting behavior of the model. When each population can survive if it is cultured alone, we prove that at most one competitor survives. The winner is the population that has the smallest delayed break-even concentration, provided that the orders of the delay kernels are large and the mean delays modiied to include the washout rate (which we call the virtual mean delays) are bounded and close to each other, or the delay kernels modiied to include the washout factor (which we call the virtual delay kernels) are close in L 1-norm. Also, when the virtual mean delays are relatively small, it is shown that the predictions of the distributed delay model are identical with the predictions of the corresponding ODEs model without delay. However, since the delayed break-even concentrations are functions of the parameters appearing in the delay kernels, if the delays are suu-ciently large, the prediction of which competitor survives, given by the ODEs model, can diier from that given by the delay model.
Time slot-adding algorithm for improving bottleneck link throughput in IEEE 802.16j relay networks

IEEE 802.16j-based wireless relay networks adopt time division multiple access, where time slots are assigned to communication links as transmission opportunities. When we employ adaptive modulation and coding for data transmission on wireless links, the transmission bitrate is affected by the signal to interference and noise ratio. Therefore, algorithms that assign time slots to links are important for enhancing the performance of relay networks. When we employ relay networks to access backhaul networks, the bottleneck link is likely to be located near the gateway node, and dominates the performance of the relay network. In this paper, we propose a time slot-adding algorithm to improve bottleneck link throughput in IEEE 802.16j relay networks. Although we employ an existing method for the initial assignment of time slots to links in the network, we introduce novel algorithm to add more time slots to the bottleneck link. Performance evaluations confirm that the proposed method improves data transfer throuzhput by up to around 30%.
Proactive vs reactive approaches to failure resilient routing

Dealing with network failures effectively is a major operational challenge for Internet service providers. Commonly deployed link state routing protocols such as OSPF react to link failures through global (i.e., network-wide) link state advertisements and routing table recomputations, causing significant forwarding discontinuity after a failure. The drawback with these protocols is that they need to trade off routing stability and forwarding continuity. To improve failure resiliency without jeopardizing routing stability, we propose a proactive local rerouting based approach called failure insensitive routing (FIR). The proposed approach prepares for failures using interface-specific forwarding, and upon a failure, suppresses the link state advertisement and instead triggers local rerouting using a backwarding table. In this paper, we prove that when no more than one link failure notification is suppressed, FIR always finds a loop-free path to a destination if one such path exists. We also formally analyze routing stability and network availability under both proactive and reactive approaches, and show that FIR provides better stability and availability than OSPF.
COGNITIVE RADIO NETWORK TOMOGRAPHY OF SPECTRUM MAP USING LEARNING AND RANDOM SET THEORY

Cognitive radio network tomography identifies transmission opportunities by actively or passively obtaining link-level or network-level information, to enable networking cognitive radios. Beyond the spectrum holes, radio resource with location information that is known as spectrum map, can easily facilitate network functions such as multi-hop cooperative routing. However, it is not feasible to construct the spectrum map by dynamic placing a large number of cooperative sensors, but we need to complete spectrum map even with locations without sensors. To overcome this challenge, in this paper, we propose a twostep procedure using learning and random set theory to infer the radio resource at a specific location without direct observation from sensors, which can be used to construct and consummate the spectrum map. We utilize the spatial correlation among sensors to retrieve the spectrum map, especially in the locations that sensors existed previously. Yielding a reduced number of required sensors, our proposed scheme can realize multi-hop cognitive radio networking functions of CRN with complete spectrum map information.
Data-Driven Detection of Malicious Document

Malcode hidden in otherwise normal appearing public documents provide both convenient and stealthy means for attackers to penetrate systems. By exploiting the ubiquitous and object-oriented approach of modern document applications and formats, malcode can reach third-party applications that may harbor exploitable vulnerabilities otherwise unreachable by network-level service attacks: by clicking a web link of any arbitrary website or even inserting media such as CD-ROMS and USB drives, a target system can be infected when a document is opened, effectively bypassing all the network firewalls and sensors. To protect against this stealthy threat, this thesis investigates the ability to detect embedded malcode in Word documents using two techniques: static content analysis using statistical models of typical document content and run-time dynamic tests. The first approach parses Word documents into its constituent objects and identifies the “sections” of the binary file content of those objects. The Anagram sensor introduced for network packet anomaly detection and an Entropy analysis technique are applied for this purpose. The second approach uses a series of dynamic tests on diverse platforms to open a document and execute its embedded malcode in diverse environments forcing the malcode to behave abnormally leading to its detection. The intent of such code to do harm is detected by observing unexpected changes it makes to the underlying platforms when it is able to execute. In addition to simply observing the system, a few techniques used to monitor virtual machines and detect anomaly are proposed in this document. A formal study using thousands of infected Word documents gathered from the wild has been performed, and several deficiencies of both approaches are identified, representing both challenges in addressing the problem and opportunities for follow on research. This document presents a twenty-four month research program for developing the major components of the proposed approaches, including a hybrid system that applies both techniques and for completing the experiments and evaluations.
Testing real convergence in the ECOWAS countries in presence of heterogeneous long-run growths: A panel data study

In this paper, we examine the issue of β convergence of per-capita GDP in the ECOWAS countries under the assumption of parameter heterogeneity. We apply panel data techniques to an error-correction model that allow us to take into account latent heterogeneities across the countries. In comparison with the standard growth equations, the novelty comes from the fact that the slopes of the long-run growth equations are assumed to differ across the countries. If the economic structures are truly heterogeneous, then using average-based estimators yields results that are more robust than those derived from pooled-based estimators. The results suggest opportunities for policymakers to achieve real convergence through more coordinated policies Outline
Characterization of resistance to Synchytrium endobioticum in cultivated potato accessions from the collection of Vavilov Institute of Plant Industry

With 7 figures and 1 table Abstract The causal agent of potato wart (Synchytrium endobioticum) is an obligate parasitic chytrid fungus. It is included as a quarantine pathogen in 55 countries, with losses in susceptible cultivars reaching 50–100%. The aim of our study was to characterize the resistance to S. endobioticum pathotype 1 in cultivated potatoes from a well-characterized subset of the Vavilov Institute of Plant Industry collection and to determine whether this resistance is associated with cultivated potato species taxonomy, with ploidy, with geographic distance or with a molecular marker Nl25-1400 proposed for molecular screening for resistance to pathotype 1 of S. endobioticum. Within the diversity of 52 landrace genotypes, our work shows a lack of such predictive associations with wart resistance. High intraspecific variation of wart diseases resistance allows the selection of extremely resistant and susceptible genotypes available for future genetic and breeding studies.
Implementation of a Parallel and Pipelined Watershed Algorithm on FPGA

This paper describes an implementation of a parallel and pipelined watershed algorithm on FPGA. In the algorithm, pixels in a given image are repeatedly scanned from top-left to bottom-right, and then from bottom-right to top-left. Because of these simplified memory accesses, N pixels in a given image can be processed in parallel by reading N lines at the same time. However, N is limited by the number of external memory banks that store image data. In our implementation, in order to achieve high performance using an FPGA with limited number of external memory banks, (1) a given image is divided to K regions, (2) several of them are cached on the FPGA, (3) the watershed algorithm is applied on those regions, and (4) the next (or previous) region is loaded to the FPGA during the computation to hide the loading time. In our current implementation on XC2V6000, up to 32 pixels can be processed in parallel. The performance for 512 × 512 pixel images is about 3-4 msec, which is fast enough for real-time applications.
Molecular Characterization of Chronic Lymphocytic Leukemia Patients with a High Number of Losses in 13q14

Background Patients with chronic lymphocytic leukemia and 13q deletion as their only FISH abnormality could have a different outcome depending on the number of cells displaying this aberration. Thus, cases with a high number of 13q- cells (13q-H) had both shorter overall survival and time to first therapy. The goal of the study was to analyze the genetic profile of 13q-H patients. Design and Methods: A total of 102 samples were studied, 32 of which served as a validation cohort and five were healthy donors. Results Chronic lymphocytic leukemia patients with higher percentages of 13q- cells (>80%) showed a different level of gene expression as compared to patients with lower percentages (<80%, 13q-L). This deregulation affected genes involved in apoptosis and proliferation (BCR and NFkB signaling), leading to increased proliferation and decreased apoptosis in 13q-H patients. Deregulation of several microRNAs, such as miR-15a, miR-155, miR-29a and miR-223, was also observed in these patients. In addition, our study also suggests that the gene expression pattern of 13q-H cases could be similar to the patients with 11q- or 17p-. Conclusions This study provides new evidence regarding the heterogeneity of 13q deletion in chronic lymphocytic leukemia patients, showing that apoptosis, proliferation as well as miRNA regulation are involved in cases with higher percentages of 13q- cells.
PriFi: using a multiple alignment of related sequences to find primers for amplification of homologs

Using a comparative approach, the web program PriFi () designs pairs of primers useful for PCR amplification of genomic DNA in species where prior sequence information is not available. The program works with an alignment of DNA sequences from phylogenetically related species and outputs a list of possibly degenerate primer pairs fulfilling a number of criteria, such that the primers have a maximal probability of amplifying orthologous sequences in other phylogenetically related species. Operating on a genome-wide scale, PriFi automates the first steps of a procedure for developing general markers serving as common anchor loci across species. To accommodate users with special preferences, configuration settings and criteria can be customized.
The Recently Identified P2Y-Like Receptor GPR17 Is a Sensor of Brain Damage and a New Target for Brain Repair

Deciphering the mechanisms regulating the generation of new neurons and new oligodendrocytes, the myelinating cells of the central nervous system, is of paramount importance to address new strategies to replace endogenous damaged cells in the adult brain and foster repair in neurodegenerative diseases. Upon brain injury, the extracellular concentrations of nucleotides and cysteinyl-leukotrienes (cysLTs), two families of endogenous signaling molecules, are markedly increased at the site of damage, suggesting that they may act as “danger signals” to alert responses to tissue damage and start repair. Here we show that, in brain telencephalon, GPR17, a recently deorphanized receptor for both uracil nucleotides and cysLTs (e.g., UDP-glucose and LTD4), is normally present on neurons and on a subset of parenchymal quiescent oligodendrocyte precursor cells. We also show that induction of brain injury using an established focal ischemia model in the rodent induces profound spatiotemporal-dependent changes of GPR17. In the lesioned area, we observed an early and transient up-regulation of GPR17 in neurons expressing the cellular stress marker heat shock protein 70. Magnetic Resonance Imaging in living mice showed that the in vivo pharmacological or biotechnological knock down of GPR17 markedly prevents brain infarct evolution, suggesting GPR17 as a mediator of neuronal death at this early ischemic stage. At later times after ischemia, GPR17 immuno-labeling appeared on microglia/macrophages infiltrating the lesioned area to indicate that GPR17 may also acts as a player in the remodeling of brain circuitries by microglia. At this later stage, parenchymal GPR17+ oligodendrocyte progenitors started proliferating in the peri-injured area, suggesting initiation of remyelination. To confirm a specific role for GPR17 in oligodendrocyte differentiation, the in vitro exposure of cortical pre-oligodendrocytes to the GPR17 endogenous ligands UDP-glucose and LTD4 promoted the expression of myelin basic protein, confirming progression toward mature oligodendrocytes. Thus, GPR17 may act as a “sensor” that is activated upon brain injury on several embryonically distinct cell types, and may play a key role in both inducing neuronal death inside the ischemic core and in orchestrating the local remodeling/repair response. Specifically, we suggest GPR17 as a novel target for therapeutic manipulation to foster repair of demyelinating wounds, the types of lesions that also occur in patients with multiple sclerosis.
Contractual and Organizational Structure with Reciprocal Agents

Empirically, compensation systems generate substantial effort despite weak monetary incentives. We consider reciprocal motivations as a source of incentives. We solve for the optimal contract in the basic principal-agent problem and show that reciprocal motivations and explicit performance-based pay are substitutes. A firm endogenously determines the mix of the two sources of incentives to best induce effort from the agent. Analyzing extended versions of the model allows us to examine how organizational structure impacts the effectiveness of reciprocity and to derive specific empirical predictions. We use the UK-WERS workplace compensation data set to confirm the predictions of our extended model.
Energetically Optimal Action Potentials

Most action potentials in the nervous system take on the form of strong, rapid, and brief voltage deflections known as spikes, in stark contrast to other action potentials, such as in the heart, that are characterized by broad voltage plateaus. We derive the shape of the neuronal action potential from first principles, by postulating that action potential generation is strongly constrained by the brain's need to minimize energy expenditure. For a given height of an action potential, the least energy is consumed when the underlying currents obey the bang-bang principle: the currents giving rise to the spike should be intense, yet short-lived, yielding spikes with sharp onsets and offsets. Energy optimality predicts features in the biophysics that are not per se required for producing the characteristic neuronal action potential: sodium currents should be extraordinarily powerful and inactivate with voltage; both potassium and sodium currents should have kinetics that have a bell-shaped voltage-dependence; and the cooperative action of multiple 'gates' should start the flow of current.
Attention Diversion Improves Response Inhibition of Immediate Reward, But Only When it Is Beneficial: An fMRI Study

Deficits of self-control are associated with a number of mental state disorders. The ability to direct attention away from an alluring stimulus appears to aid inhibition of an impulsive response. However, further functional imaging research is required to assess the impact of shifts in attention on self-regulating processes. We varied the level of attentional disengagement in an functional magnetic resonance imaging (fMRI)-based Go/No-go task to probe whether diversion of attention away from alluring stimuli facilitates response inhibition. We used the attention-grabbing characteristic of faces to exogenously direct attention away from stimuli and investigated the relative importance of attention and response inhibition mechanisms under different delayed reward scenarios [i.e., where forgoing an immediate reward ($1) led to a higher ($10) or no payoff in the future]. We found that diverting attention improved response inhibition performance, but only when resistance to an alluring stimulus led to delayed reward. Region of interest analyses indicated significant increased activity in posterior right inferior frontal gyrus during successful No-go trials for delayed reward trials compared to no delayed reward trials, and significant reduction in activity in the superior temporal gyri and left caudate in contexts of high attentional diversion. Our findings imply that strategies that increase the perceived benefits of response inhibition might assist individuals in abstaining from problematic impulsive behaviors.
Dynamic heterogeneous data processing in IaaS cloud

The integration of framework in cloud computing companies makes the customers easy to access and deploy their programs. Currently used processing frameworks are static and homogeneous in nature. So the initially allocated computing resources may be inadequate for big parts of the submitted job which increases processing time and cost. Nephele, a first data processing framework utilize the dynamic resource allocation offered by IaaS clouds in task scheduling and execution. Different types of virtual machines can be assigned to a particular task of a processing job which is automatically instantiated and terminated during job execution. Nephele with Mapreduce concept is existed but Mapreduce perform well among homogeneous datasets. Mapreduce merge is the alternative to Mapreduce in processing heterogeneous data relations. In proposed system, Mapreduce merge in Nephele to process data relationships among heterogeneous datasets is illustrated. Based on this new framework extended evaluations of Map reduce inspired processing jobs on an IaaS cloud system is performed. Finally, the results are compared to Map reduce merge inspired jobs on an IaaS cloud system.
Ultrastructural Study of Electron Dense Deposits in Renal Tubular Basement Membrane: Prevalence and Relationship to Epithelial Atrophy

Abstract This study reports the prevalence of immune deposits associated with the proximal and distal tubules in a series of routine renal biopsies received in our department during a single calendar year. From 87 cases, 65 (74%) were found to have glomerular immune deposits by immunofluorescence. Tubular immune deposits were found in 12 cases (18%), 3 of which had no glomerular deposits. By transmission electron microscopy (EM), 58 cases (66%) were found to have deposits of granular or vesicular material associated with the tubular basement membranes (TBM). Finely granular electron dense deposits appeared to correspond to the immune deposits seen by immunofluorescence microscopy (IF) and may be a sensitive marker of immune deposition.