Miracle-dz/UniFAR-FTUs huggingface dataset:
MAP-PF multi-mode tracking for over-the-horizon radar

Detection, localization, and tracking in over-the-horizon radar (OTHR) systems is a challenging problem due to the existence of multiple propagation paths, or modes, between the transmitter, target, and receiver. Traditional OTHR multi-target tracking techniques use three isolated processes: slant azimuth/range/Doppler estimation (detection), followed by association of detections to targets and mode paths, followed by fusion of associated slant detections or tracks into a single track in Earth coordinates for each target. In this paper, we use the Maximum a Posteriori Penalty Function (MAP-PF) approach to formulate the tracking problem as a MAP estimation problem operating directly on the radar array data. The result is a two-step estimation process similar to traditional methods, except the processes are coupled via the penalty function and the data association step is eliminated. In the azimuth/range/Doppler estimation process, the penalty function guides the estimator to look for detections at slant coordinates of possible mode paths for the current target state. In the track estimation process, the penalty function adaptively determines the influence of mode path estimates on the final track estimates. Performance is demonstrated on simulated OTHR data in a scenario with two ionospheric layers and four propagation modes.
Semaphorin 7a links nerve regeneration and inflammation in the cornea.

PURPOSE We determined Semaphorin 7a (Sema7a) localization and abundance in naive corneas and in corneas after nerve-transecting lamellar flap surgery, and determined the effect of Sema7a supplementation on corneal nerve regeneration and inflammation. METHODS Immunolocalization and Western blot analyses were performed to evaluate the abundance of Sema7a in naive corneas and corneas undergoing nerve regeneration after lamellar corneal surgery in thy1-YFP+ neurofluorescent mice. We used compartmental cultures of dissociated trigeminal ganglion cells to determine the effect of Sema7a exposure on neurite outgrowth in vitro. Finally, a Sema7a pellet was implanted under the corneal flap after lamellar transection surgery to determine the neuronal and inflammatory effects of Sema7a supplementation in vivo. RESULTS Sema7a was expressed in the corneal epithelium and stromal keratocytes, but was more abundant in the epithelium (74.3%) compared to the stroma (25.7%, P = 0.02). Sema7a expression was increased significantly in the cornea after lamellar corneal surgery and was localized to stromal cells near the regenerating nerve fronds. Exposure of trigeminal neurites to Sema7a (20 nM) in the side compartment increased neurite length significantly. The implanted Sema7a pellet increased significantly YFP+ inflammatory cell influx into the cornea as well as increased corneal nerve length. CONCLUSIONS Sema7a is expressed constitutively in the cornea, and potently stimulates nerve regeneration and inflammatory cell influx. Therefore, this immune semaphorin links nerve regeneration and inflammatory processes in the cornea.
Thermal Simulator Development: Non-Nuclear Testing of Space Fission Systems

Non-nuclear testing can be a valuable tool in the development of a space nuclear power system. At the NASA MSFC Early Flight Fission Test Facility (EFF-TF), highly designed electric heaters are used to simulate the heat from nuclear fuel to test space fission power and propulsion systems. To allow early utilization, nuclear system designs must be relatively simple, easy to fabricate, and easy to test using non-nuclear heaters to closely mimic heat from fission. In this test strategy, highly designed electric heaters are used to simulate the heat from nuclear fuel, allowing one to develop a significant understanding of individual components and integrated system operation without the cost, time and safety concerns associated with nuclear testing.
Measuring broadband radio channel parameters using a simple experimental set-up

A method is presented for measuring the main parameters required to estimate the capacity of the radio channel for wideband communications as the root mean square time delay and the coherence bandwidth. This method is based on the possibility of estimating the power delay profile from the knowledge of only the module of the transfer function of the channel in conjunction with the Hilbert transform. The major advantages of the method are first, the possibility to experimentally characterize the wideband channel performance by employing widely used and low cost instrumentation, and second the possibility to extend the technique to outdoor radio channels. The error associated to the approximated method is quantified, so that it can be used from an engineering point of view in the planning and development of wideband wireless communications systems.
GIS integration and interoperability based on GIS service chain

with the constantly enrichment of GIS Web Services, the most challenge we are facing now is how to dynamic combine those existing GIS Web Services to implement more complex tasks, thus to achieve the need of on-demand distributed geospatial information integration. This paper studies the key technology of distributed GIS Service Chain. First the paper proposes distributed GIS service chain integration architecture. Based on this integration architecture, key issues of GIS service chain integration are thoroughly studied. A prototype is implemented at the end of the paper. Keywords-GIS Service Chain; Distributed GIS Integration and Interoperability; Dynamic service choicing; visual Service composition
Performance of Single and Concatenated Sets of Mitochondrial Genes at Inferring Metazoan Relationships Relative to Full Mitogenome Data

Mitochondrial (mt) genes are some of the most popular and widely-utilized genetic loci in phylogenetic studies of metazoan taxa. However, their linked nature has raised questions on whether using the entire mitogenome for phylogenetics is overkill (at best) or pseudoreplication (at worst). Moreover, no studies have addressed the comparative phylogenetic utility of mitochondrial genes across individual lineages within the entire Metazoa. To comment on the phylogenetic utility of individual mt genes as well as concatenated subsets of genes, we analyzed mitogenomic data from 1865 metazoan taxa in 372 separate lineages spanning genera to subphyla. Specifically, phylogenies inferred from these datasets were statistically compared to ones generated from all 13 mt protein-coding (PC) genes (i.e., the “supergene” set) to determine which single genes performed “best” at, and the minimum number of genes required to, recover the “supergene” topology. Surprisingly, the popular marker COX1 performed poorest, while ND5, ND4, and ND2 were most likely to reproduce the “supergene” topology. Averaged across all lineages, the longest ∼2 mt PC genes were sufficient to recreate the “supergene” topology, although this average increased to ∼5 genes for datasets with 40 or more taxa. Furthermore, concatenation of the three “best” performing mt PC genes outperformed that of the three longest mt PC genes (i.e, ND5, COX1, and ND4). Taken together, while not all mt PC genes are equally interchangeable in phylogenetic studies of the metazoans, some subset can serve as a proxy for the 13 mt PC genes. However, the exact number and identity of these genes is specific to the lineage in question and cannot be applied indiscriminately across the Metazoa.
Moving south: effects of water temperatures on the larval development of invasive cane toads (Rhinella marina) in cool‐temperate Australia

Abstract The distributional limits of many ectothermic species are set by thermal tolerances of early‐developmental stages in the life history; embryos and larvae often are less able to buffer environmental variation than are conspecific adults. In pond‐breeding amphibians, for example, cold water may constrain viability of eggs and larvae, even if adults can find suitable thermal conditions in terrestrial niches. Invasive species provide robust model systems for exploring these questions, because we can quantify thermal challenges at the expanding range edge (from field surveys) and larval responses to thermal conditions (in the laboratory). Our studies on invasive cane toads (Rhinella marina) at the southern (cool‐climate) edge of their expanding range in Australia show that available ponds often average around 20°C during the breeding period, 10°C lower than in many areas of the toads’ native range, or in the Australian tropics. Our laboratory experiments showed that cane toad eggs and larvae cannot develop successfully at 16°C, but hatching success and larval survival rates were higher at 20°C than in warmer conditions. Lower temperatures slowed growth rates, increasing the duration of tadpole life, but also increased metamorph body mass. Water temperature also influenced metamorph body shape (high temperatures reduced relative limb length, head width, and body mass) and locomotor performance (increased speed from intermediate temperatures, longer hops from high temperatures). In combination with previous studies, our data suggest that lower water temperatures may enhance rather than reduce recruitment of cane toads, at least in areas where pond temperatures reach or exceed 20°C. That condition is fulfilled over a wide area of southern Australia, suggesting that the continuing expansion of this invasive species is unlikely to be curtailed by the impacts of relatively low water temperatures on the viability of early life‐history stages.
HMC at SemEval-2016 Task 11: Identifying Complex Words Using Depth-limited Decision Trees

We present two systems created for SemEval2016s Task 11: Complex Word Identification. Our two systems, a regression tree and decision tree, were trained with a word’s unigram and lemma word counts, average ageof-acquisition, and a measure of concreteness. The systems ranked 5th and 6th, respectively, on the test set by G-score (the harmonic mean between accuracy and recall). With the regression tree’s predictions earning a G-score of 0.766, and the decision tree’s earning 0.765, the two systems scored within 1 percent of the score of the best-performing system in the task.
Decision making guided by emotion

A computational architecture is presented, in which “swift and fuzzy” emotional channels guide a “slow and precise” decision-making channel. Reported neurobiological studies first provide hints on the representation of both emotional and cognitive dimensions across brain structures, mediated by the neuromodulation system. The related model is based on Guided Propagation Networks, the inner flows of which can be guided through modulation. A key-channel of this model grows from a few emotional cues, and is aimed at anticipating the consequences of on-going possible actions. Current experimental results of a computer simulation show the integrated contribution of several emotional influences, as well as issues of accidental all-out emotions.
The Effect of Linkage Disequilibrium and Family Relationships on the Reliability of Genomic Prediction

Although the concept of genomic selection relies on linkage disequilibrium (LD) between quantitative trait loci and markers, reliability of genomic predictions is strongly influenced by family relationships. In this study, we investigated the effects of LD and family relationships on reliability of genomic predictions and the potential of deterministic formulas to predict reliability using population parameters in populations with complex family structures. Five groups of selection candidates were simulated by taking different information sources from the reference population into account: (1) allele frequencies, (2) LD pattern, (3) haplotypes, (4) haploid chromosomes, and (5) individuals from the reference population, thereby having real family relationships with reference individuals. Reliabilities were predicted using genomic relationships among 529 reference individuals and their relationships with selection candidates and with a deterministic formula where the number of effective chromosome segments (Me) was estimated based on genomic and additive relationship matrices for each scenario. At a heritability of 0.6, reliabilities based on genomic relationships were 0.002 ± 0.0001 (allele frequencies), 0.022 ± 0.001 (LD pattern), 0.018 ± 0.001 (haplotypes), 0.100 ± 0.008 (haploid chromosomes), and 0.318 ± 0.077 (family relationships). At a heritability of 0.1, relative differences among groups were similar. For all scenarios, reliabilities were similar to predictions with a deterministic formula using estimated Me. So, reliabilities can be predicted accurately using empirically estimated Me and level of relationship with reference individuals has a much higher effect on the reliability than linkage disequilibrium per se. Furthermore, accumulated length of shared haplotypes is more important in determining the reliability of genomic prediction than the individual shared haplotype length.
SNR investigation of beam forming in IS-95 CDMA base station receiver

This paper presents analytical derivations and simulation results for signal-to-noise ratio (SNR) when a linear array antenna is used in a CDMA base station with beam forming (BF) algorithms. The roles of two design factors effecting performance, the direction selectivity of an array antenna and the direction-of-arrival (DOA) accuracy in the BF algorithm, are examined not only for SNR but also to determine the robustness of a BF algorithm due to error factors of spatial scattering of radio waves and DOA. From the study, it is found that there is a trade-off between the SNR and the robustness with respect to these design factors. The trade-off can be used to achieve an economical implementation of the BIT in the CDMA system, which does not have severely deteriorated SNR performance while ensuring its robustness to the error factors.
An Overview of Statistical Language Model Adaptation

Speech recognition performance is severely a ected when the lexical, syntactic, or semantic characteristics of the discourse in the training and recognition tasks di er. The aim of language model adaptation is to exploit speci c, albeit limited, knowledge about the recognition task to compensate for this mismatch. More generally, an adaptive language model seeks to maintain an adequate representation of the current task domain under changing conditions involving potential variations in vocabulary, syntax, content, and style. This paper presents an overview of the major approaches proposed to address this issue, and o ers some perspectives regarding their comparative merits and associated trade-o s.
Output Grouping Method Based on a Similarity of Boolean Functions

A method allowing us to efficiently group the multi -output Boolean function outputs is presented in this paper. Some kind of decomposition is usually involved in the logic synthesis process. Here the circuit has to be repeatedly divi ded nto subcircuits, until these subcircuits becom e technological library elements or technology-depend ent components, in general. Our output-grouping method can be used to compute which functions of a set of Boolean functions could share most of logic. This idea can be exploited in single-level decomposition, where a two-level multi-output circuit is divided into several standalone blocks, while retaining their two-level natur e. The total size of these circuits should be kept min i al. After such single-level decomposition the circuits are further processed by a common synthesi s process. Obtained results are shown in this paper, for a set of s andard MCNC and ISCAS benchmarks. Two general problems to be solved were considered f or tests: an output-grouping based decomposition and a parity predictor synthesis, whi ch is used in an on-line diagnostic design.
Past, present and future of brain stimulation

Recent technological advances including brain imaging (higher resolution in space and time), miniaturization of integrated circuits (nanotechnologies), and acceleration of computation speed (Moore’s Law), combined with interpenetration between neuroscience, mathematics, and physics have led to the development of more biologically plausible computational models and novel therapeutic strategies. Today, mathematical models of irreversible medical conditions such as Parkinson’s disease (PD) are developed and parameterised based on clinical data. How do these evolutions have a bearing on deep brain stimulation (DBS) of patients with PD? We review how the idea of DBS, a standard therapeutic strategy used to attenuate neurological symptoms (motor, psychiatric), has emerged from past experimental and clinical observations, and present how, over the last decade, computational models based on different approaches (phase oscillator models, spiking neuron network models, population-based models) have started to shed light onto DBS mechanisms. Finally, we explore a new mathematical modelling approach based on neural field equations to optimize mechanisms of brain stimulation and achieve finer control of targeted neuronal populations. We conclude that neuroscience and mathematics are crucial partners in exploring brain stimulation and this partnership should also include other domains such as signal processing, control theory and ethics.
Traditional vs Agile development a comparison using chaos theory

Agile software development describes those methods with iterative and incremental development. This development method came into view to overcome the drawbacks of traditional development methods. Although agile development methods have become very popular since the introduction of the Agile Manifesto in 2001, however, there is an ongoing debate about the strengths and weakness of these methods in comparison with traditional ones. In this paper, a new dimension for the comparison between the two methods is presented. We postulate that, since both methods are based mainly on human activity, the two methods can be modeled using Chaos Theory. Source codes that are produced by the two methods in subsequent versions are characterized by a set of software metrics. Modeling and analysis of these metrics are performed using the Chaos Theory. Initial results show that the metrics sequences of both methods are chaotic sequences. Furthermore, agile methods produce more chaotic metrics sequences. However, is being chaotic a good or a bad feature? We argue that sometimes being chaotic is not a weakness, on the contrary, it is a strength.
The facial neural crest controls fore- and midbrain patterning by regulating Foxg1 expression through Smad1 activity

The facial neural crest (FNC), a pluripotent embryonic structure forming craniofacial structures, controls the activity of brain organisers and stimulates cerebrum growth. To understand how the FNC conveys its trophic effect, we have studied the role of Smad1, which encodes an intracellular transducer, to which multiple signalling pathways converge, in the regulation of Foxg1. Foxg1 is a transcription factor essential for telencephalic specification, the mutation of which leads to microcephaly and mental retardation. Smad1 silencing, based on RNA interference (RNAi), was performed in pre-migratory FNC cells. Soon after electroporation of RNAi molecules, Smad1 inactivation abolished the expression of Foxg1 in the chick telencephalon, resulting in dramatic microcephaly and partial holoprosencephaly. In addition, the depletion of Foxg1 activity altered the expression Otx2 and Foxa2 in di/mesencephalic neuroepithelium. However, when mutated forms of Smad1 mediating Fgf and Wnt signalling were transfected into FNC cells, these defects were overcome. We also show that, downstream of Smad1 activity, Dkk1, a Wnt antagonist produced by the FNC, initiated the specification of the telencephalon by regulating Foxg1 activity. Additionally, the activity of Cerberus in FNC-derived mesenchyme synergised with Dkk1 to control Foxg1 expression and maintain the balance between Otx2 and Foxa2.
Damage classification of concrete structures based on grey level co-occurrence matrix using Haar\'s discrete wavelet transform

A novel method for recognition, characterization, and quantification of deterioration in bridge components and laboratory concrete samples is presented in this paper. The proposed scheme is based on grey level co-occurrence matrix texture analysis using Haar`s discrete wavelet transform on concrete imagery. Each image is described by a subset of band-filtered images containing wavelet coefficients, and then reconstructed images are employed in characterizing the texture, using grey level co-occurrence matrices, of the different types and degrees of damage: map-cracking, spalling and steel corrosion. A comparative study was conducted to evaluate the efficiency of the supervised maximum likelihood and unsupervised K-means classification techniques, in order to classify and quantify the deterioration and its extent. Experimental results show both methods are relatively effective in characterizing and quantifying damage; however, the supervised technique produced more accurate results, with overall classification accuracies ranging from 76.8% to 79.1%.
Kinase Screening in Pichia pastoris Identified Promising Targets Involved in Cell Growth and Alcohol Oxidase 1 Promoter (PAOX1) Regulation

As one of the most commonly used eukaryotic recombinant protein expression systems, P. pastoris relies heavily on the AOX1 promoter (PAOX1), which is strongly induced by methanol but strictly repressed by glycerol and glucose. However, the complicated signaling pathways involved in PAOX1 regulation when supplemented with different carbon sources are poorly understood. Here we constructed a kinase deletion library in P. pastoris and identified 27 mutants which showed peculiar phenotypes in cell growth or PAOX1 regulation. We analyzed both annotations and possible functions of these 27 targets, and then focused on the MAP kinase Hog1. In order to locate its potential downstream components, we performed the phosphoproteome analysis on glycerol cultured WT and Δhog1 strains and identified 157 differentially phosphorylated proteins. Our results identified important kinases involved in P. pastoris cell growth and PAOX1 regulation, which could serve as valuable targets for further mechanistic studies.
Sensitivity Analysis of Server Virtualized System Availability

Server virtualization is a technology used in many enterprise systems to reduce operation and acquisition costs, and increase the availability of their critical services. Virtualized systems may be even more complex than traditional nonvirtualized systems; thus, the quantitative assessment of system availability is even more difficult. In this paper, we propose a sensitivity analysis approach to find the parameters that deserve more attention for improving the availability of systems. Our analysis is based on Markov reward models, and suggests that host failure rate is the most important parameter when the measure of interest is the system mean time to failure. For capacity oriented availability, the failure rate of applications was found to be another major concern. The results of both analyses were cross-validated by varying each parameter in isolation, and checking the corresponding change in the measure of interest. A cost-based optimization method helps to highlight the parameter that should have higher priority in system enhancement.