Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome Engineering of Drosophila with the CRISPR RNA-Guided Cas9 Nuclease

We have adapted a bacterial CRISPR RNA/Cas9 system to precisely engineer the Drosophila genome and report that Cas9-mediated genomic modifications are efficiently transmitted through the germline. This RNA-guided Cas9 system can be rapidly programmed to generate targeted alleles for probing gene function in Drosophila.
N ov 2 00 5 Single-particle dynamics of the Anderson model : a two-self-energy description within the numerical renormalization group approach

Single-particle dynamics of the Anderson model: a two-self-energy description within the numerical renormalization group approach. Abstract. Single-particle dynamics of the Anderson impurity model are studied using both the numerical renormalization group (NRG) method and the local moment approach (LMA). It is shown that a 'two-self-energy' description of dynamics inherent to the LMA, as well as a conventional 'single-self-energy' description, arise within NRG; each yielding correctly the same local single-particle spectrum. Explicit NRG results are obtained for the broken symmetry spectral constituents arising in a two-self-energy description, and the total spectrum. These are also compared to analytical results obtained from the LMA as implemented in practice. Very good agreement between the two is found, essentially on all relevant energy scales from the high-energy Hubbard satellites to the low-energy Kondo resonance.
Supramolecular Organization of the Respiratory Chain in Neurospora crassa Mitochondria

ABSTRACT The existence of specific respiratory supercomplexes in mitochondria of most organisms has gained much momentum. However, its functional significance is still poorly understood. The availability of many deletion mutants in complex I (NADH:ubiquinone oxidoreductase) of Neurospora crassa, distinctly affected in the assembly process, offers unique opportunities to analyze the biogenesis of respiratory supercomplexes. Herein, we describe the role of complex I in assembly of respiratory complexes and supercomplexes as suggested by blue and colorless native polyacrylamide gel electrophoresis and mass spectrometry analyses of mildly solubilized mitochondria from the wild type and eight deletion mutants. As an important refinement of the fungal respirasome model, we found that the standard respiratory chain of N. crassa comprises putative complex I dimers in addition to I-III-IV and III-IV supercomplexes. Three Neurospora mutants able to assemble a complete complex I, lacking only the disrupted subunit, have respiratory supercomplexes, in particular I-III-IV supercomplexes and complex I dimers, like the wild-type strain. Furthermore, we were able to detect the I-III-IV supercomplexes in the nuo51 mutant with no overall enzymatic activity, representing the first example of inactive respirasomes. In addition, III-IV supercomplexes were also present in strains lacking an assembled complex I, namely, in four membrane arm subunit mutants as well as in the peripheral arm nuo30.4 mutant. In membrane arm mutants, high-molecular-mass species of the 30.4-kDa peripheral arm subunit comigrating with III-IV supercomplexes and/or the prohibitin complex were detected. The data presented herein suggest that the biogenesis of complex I is linked with its assembly into supercomplexes.
Modelling Estimates of Norovirus Disease in Patients with Chronic Medical Conditions

Background The burden of disease due to norovirus infection has been well described in the general United States population, but studies of norovirus occurrence among persons with chronic medical conditions have been limited mostly to the immunocompromised. We assessed the impact of norovirus gastroenteritis on health care utilization in US subjects with a range of chronic medical conditions. Methods We performed a retrospective cohort study using MarketScan data from July 2002 to December 2013, comparing the rates of emergency department visits, outpatient visits and hospitalizations among patients with chronic conditions (renal, cardiovascular, respiratory, immunocompromising, gastrointestinal, hepatic/pancreatic and neurological conditions and diabetes) with those in a healthy population. We estimated the rates of these outcomes due to norovirus gastroenteritis using an indirect modelling approach whereby cases of gastroenteritis of unknown cause and not attributed to a range of other causes were assumed to be due to norovirus. Results Hospitalization rates for norovirus gastroenteritis were higher in all of the risk groups analyzed compared with data in otherwise healthy subjects, ranging from 3.2 per 10,000 person-years in persons with chronic respiratory conditions, to 23.1 per 10,000 person-years in persons with chronic renal conditions, compared to 2.1 per 10,000 among persons without chronic conditions. Over 51% of all norovirus hospitalizations occurred in the 37% of the population with some form of chronic medical condition. Outpatient visits for norovirus gastroenteritis were also increased in persons with chronic gastrointestinal or immunocompromising conditions. Conclusion Norovirus gastroenteritis leads to significantly higher rates of healthcare utilization in patients with a chronic medical condition compared to patients without any such condition.
P) Reactions: a Survey of the Relativistic Plane Wave Impulse Approximation

The issue of factorization within the context of coincidence quasi–elastic electron scattering is reviewed. Using a relativistic formalism for the entire reaction mechanism and restricting ourselves to the case of plane waves for the outgoing proton, we discuss the meaning of factorization in the cross section and the role of the small components of the bound nucleon wave function.
Multi-Modal and Multi-Temporal Data Fusion: Outcome of the 2012 GRSS Data Fusion Contest

The 2012 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society (GRSS) aimed at investigating the potential use of very high spatial resolution (VHR) multi-modal/multi-temporal image fusion. Three different types of data sets, including spaceborne multi-spectral, spaceborne synthetic aperture radar (SAR), and airborne light detection and ranging (LiDAR) data collected over the downtown San Francisco area were distributed during the Contest. This paper highlights the three awarded research contributions which investigate (i) a new metric to assess urban density (UD) from multi-spectral and LiDAR data, (ii) simulation-based techniques to jointly use SAR and LiDAR data for image interpretation and change detection, and (iii) radiosity methods to improve surface reflectance retrievals of optical data in complex illumination environments. In particular, they demonstrate the usefulness of LiDAR data when fused with optical or SAR data. We believe these interesting investigations will stimulate further research in the related areas.
How Much of the Dynamics of Fixed Income Options can be Explained by their Underlying Assets ? The Brazilian

In general, derivatives are not redundant instruments. They usually carry some type of information independent of their underlying assets prices. Connections between derivatives prices and their respective underlying assets prices are interesting because they inform the degree of completeness of the market as a whole. In this paper, we propose to test the ability of a multi-factor affine model to price and hedge options, when it has been estimated based only on the underlying market data. Adopting the Brazilian ID-Futures market, we estimate how much of the information carried on its corresponding option market (IDI options) is explained by only the sources of uncertainty of the primary market. Our empirical results suggest that the Brazilian fixed income market is incomplete. We conclude then proposing a dynamic term structure model which is a promising candidate to reconcile theory to the obtained empirical results.
Eigentree-SIFT – a Hierarchical Space-Partitioning Approach for Indexing and Description of Local Image Features

In this work, we investigate a new approach to the description of scaleinvariant local image features. We take as point of departure the PCASIFT approach, an improvement on the well-known Scale-Invariant Feature Transform (SIFT). Analogous to the eigenspace of features being the basis for PCA, we design an “eigentree” that hierarchically partitions the feature space, allowing the eigenvectors to iteratively re-adapt to local clusters of data. Each terminal node in the tree then corresponds to a sub-cluster of data, and the features in such a terminal set are described by projection onto the eigenvectors along their path up the tree, combined with traditional PCA, to make for a constant number of descriptor elements. Through a series of tests, we find that, by wise design of the eigentree, PCA-SIFT can be outperformed, both in the rate of correct matches between test features and training features, and in terms of indexing speed. Egenträds-SIFT: Beskrivning och indexering av lokala särdrag i bilder genom hierarkisk partitionering av särdragsrummet
Determining Relative Importance and Best Settings for Genetic Algorithm Control Parameters

This paper makes two main contributions: (1) we define an experiment design and analysis approach that can be adapted to determine relative importance and best settings for control parameters in any evolutionary computation algorithm and (2) we determine the relative importance and best settings for the control parameters of a classic genetic algorithm (GA). We plan to use these control settings to parameterize a GA applied to steer a population of cloud-computing simulators into behavioral directions that reveal degraded performance and system collapse. Such a method could serve as a design tool, empowering system engineers to identify and mitigate low-probability, costly failure scenarios. In the existing GA literature, we uncovered conflicting opinions and evidence regarding key GA control parameters, and the best settings to adopt. Consequently, we designed and executed an experiment to determine the relative importance and best settings for seven GA control parameters, when applied across a set of numeric optimization problems drawn from the literature. This paper describes our experiment design, analysis methods and results. We found that crossover most significantly influences GA success, followed by mutation rate and reboot point, with population size ranking third. Elite selection and selection method ranked fourth, while precision used within the chromosome to represent numerical values had least influence. Our findings are robust over 60 numeric optimization problems.
Advances in Proactive Road Safety Planning

There are two main transportation engineering approaches to improving road safety: reactive and proactive. The traditional reactive approach consists of implementing the necessary improvements to existing hazardous (black-spot) sites in order to improve safety at these sites. The proactive approach is a collision prevention approach that tries to prevent unsafe road conditions from occurring in the first place. While the traditional reactive approach has proven to be very successful, it requires that a significant collision history exist before any action is taken to address the road safety problem. Moreover, retrofitting countermeasures in reaction to problems in existing road networks can be costly. Therefore, there is a need for transportation professionals to take a proactive approach that addresses road safety problems before they are allowed to emerge. There is a growing appreciation in the road safety community for the need to implement a more proactive approach to road safety. Geometric design guides in many countries now present explicit relationships between road design decisions and safety consequences, moving road engineering away from reliance on minimum standards without regard to safety. The focus of this paper is on proactive engineering initiatives that can be employed to improve road safety. An overview of emerging trends in proactive road safety planning will be provided. These emerging trends include: the use of safety conscious planning models, the explicit evaluation of safety in road design, and the automated safety analysis of video data.
Insensitive Modification of Subspace Information Criterion for Least Mean Squares Learning

The least mean squares (LMS) algorithm is widely applied in the machine learning community. Insensitive Modification of Subspace Information Criterion (IMSIC) is one of the model selection methods, which is defined on an unbiased estimator of the generalization error-Subspace Information Criterion(SIC). In this paper, we will give the method of selecting LMS learning models by IMSIC.
On the Trade-Off Between Accuracy and Delay in Cooperative UWB Localization: Performance Bounds and Scaling Laws

Ultra-wide bandwidth (UWB) systems allow for accurate positioning in environments where global navigation satellite systems may fail, especially when complemented with cooperative processing. While cooperative UWB has led to centimeter-level accuracies, the communication overhead is often neglected. We quantify how accuracy and delay trade off in a wide variety of operation conditions. We also derive the asymptotic scaling of accuracy and delay, indicating that, in some conditions, standard cooperation offers the worst possible tradeoff. Both avenues lead to the same conclusion: indiscriminately targeting increased accuracy incurs a significant delay penalty. Simple countermeasures can be taken to reduce this penalty and obtain a meaningful accuracy/delay trade-off.
Spectroscopy of Globular Clusters in the Fornax Dwarf Galaxy

We present low-resolution, integrated Keck spectra of the five globular clusters (GCs) of the Fornax dwarf spheroidal galaxy. We find a tentative age spread among the clusters, with the GC H5 younger by 2–3 Gyr than the others. The clusters generally appear to be very metal-poor ([Fe/H] ∼ -1.8), with the cluster H4 slightly more metal-rich at [Fe/H] = -1.5. We speculate that cluster H4 is similar to the Galactic GC Ruprecht 106, which lacks the [α/Fe] enhancement typical among metal-poor GCs in the Milky Way. High-resolution spectroscopy of individual cluster and field stars will be needed to sort out the surprisingly complex history of GC formation and evolution in this galaxy.
An Iterative List-Based Multiuser Detector for Overloaded Receivers in a Rayleigh Fading Channel

We consider a wireless communication system where multiple co-channel users transmit data via a synchronous, frequency-flat Rayleigh fading channel. The receiver employs an antenna array. The paper develops an iterative list multiuser detector for overloaded applications where the number of transmitted signals exceeds the number of receive antennas. The receiver uses a linear preprocessor to reduce co-channel interference followed by a multiuser detector with an iterative groupwise symbol detection algorithm that extracts a list of the most likely user symbols. Simulation results show that the proposed detector provides good complexity-performance trade offs.
Trophic cascade facilitates coral recruitment in a marine reserve

Reduced fishing pressure and weak predator–prey interactions within marine reserves can create trophic cascades that increase the number of grazing fishes and reduce the coverage of macroalgae on coral reefs. Here, we show that the impacts of reserves extend beyond trophic cascades and enhance the process of coral recruitment. Increased fish grazing, primarily driven by reduced fishing, was strongly negatively correlated with macroalgal cover and resulted in a 2-fold increase in the density of coral recruits within a Bahamian reef system. Our conclusions are robust because four alternative hypotheses that may generate a spurious correlation between grazing and coral recruitment were tested and rejected. Grazing appears to influence the density and community structure of coral recruits, but no detectable influence was found on the overall size-frequency distribution, community structure, or cover of corals. We interpret this absence of pattern in the adult coral community as symptomatic of the impact of a recent disturbance event that masks the recovery trajectories of individual reefs. Marine reserves are not a panacea for conservation but can facilitate the recovery of corals from disturbance and may help sustain the biodiversity of organisms that depend on a complex three-dimensional coral habitat.
Clinical Applications of Transcranial Magnetic Stimulation in Pediatric Neurology

Noninvasive brain stimulation is now an accepted technique that is used as a diagnostic aid and in the treatment of neuropsychiatric disorders in adults, and is being increasingly used in children. In this review, we will discuss the basic principles and safety of one noninvasive brain stimulation method, transcranial magnetic stimulation. Improvements in the spatial accuracy of transcranial magnetic stimulation are described in the context of image-guided transcranial magnetic stimulation. The article describes and provides examples of the current clinical applications of transcranial magnetic stimulation in children as an aid in the diagnosis and treatment of neuropsychiatric disorders and discusses future potential applications. Transcranial magnetic stimulation is a noninvasive tool that is safe for use in children and adolescents for functional mapping and treatment, and for many children it aids in the preoperative evaluation and the risk-benefit decision making.
Differential expression of HIF-1 in glioblastoma multiforme and anaplastic astrocytoma

Hypoxia is an important factor mediating tumor progression and therapeutic resistance, in part through proteome changes mediated by the transcription factor hypoxia-inducible factor (HIF)-1. Since glioblastoma multiforme is the epitome of a highly aggressive tumor entity, while lower-grade astrocytomas often show a prolonged clinical course, a profound difference in the extent of hypoxic tissue areas and corresponding magnitude of HIF-1 activity may exist between these entities. In this study, to address this question, serial sections of 11 glioblastomas and 10 anaplastic astrocytomas were immunostained for HIF-1α, glucose transporter (GLUT)-1, carbonic anhydrase (CA) IX (i.e., hypoxia-related markers), Ki67 (proliferation), phosphorylated ribosomal protein S6 [p-rpS6; mammalian target of rapamycin (mTOR) activity] and CD34 (microvascular endothelium). Digital scans of whole tumor sections were registered to achieve geometric correspondence for subsequent morphometric operations. HIF-1α-, GLUT-1- and CA IX-positive staining was found in all 11 glioblastomas, showing a preferential expression in tissue areas adjacent to necroses. A considerable spatial overlap between GLUT-1 and CA IX, and a colocalization of these proteins with areas of enlarged mean diffusion distances were observed. Conversely, 8 of the 10 anaplastic astrocytomas were completely negative for hypoxia-related markers. The glioblastomas also showed significantly greater heterogeneity of intercapillary distances, larger diffusion-limited tissue fractions, significantly higher mTOR activity and a trend for higher proliferation rates. Microregionally, mTOR and proliferation showed a significant spatial overlap with areas of shorter mean diffusion distances. In conclusion, diffusion-limited hypoxia, leading to the expression of hypoxia-related markers is a pivotal element of the glioblastoma phenotype and may be driven by dysregulated growth and proliferation in normoxic subregions.
Reducing cross-group traffic with a cooperative streaming architecture

Cooperative approaches, such as P2P networks, have demonstrated their effectiveness in video delivery. However, with underlay structure considered, it is still possible to further improve traffic efficiency. In this paper, we discuss the problem of localizing the traffic traversal across peer groups, which are partitioned according to underlay characteristics. We first provide three concrete examples to demonstrate this common challenge, which we theoretically formulate afterwards. Finally, we propose a ring overlay approach, which performs excellently to solve the problem, while tolerating peer dynamics and supporting peer heterogeneity.
Medication adherence and knowledge of older patients with and without multidose drug dispensing.

OBJECTIVE we compared the self-reported medication adherence and knowledge of older patients receiving their drugs via multidose drug dispensing (MDD users) with patients receiving manually dispensed drugs (non-MDD users). METHODS MDD users (≥ 65 years, ≥ 5 oral chronic drugs) were randomly selected from eight Dutch community pharmacies. Non-MDD users (≥ 5 oral chronic drugs) were matched on age and gender. Medication adherence was assessed by using the Medication Adherence Reporting Scale (MARS) and medication knowledge by asking the indication of drugs. Cognitive function was measured with Mini-Mental State Examination (MMSE) for a sub selection of patients. RESULTS the percentage of patients being adherent to all drugs was higher for MDD users (n = 119, 81%) compared with non-MDD users (n = 96, 58%, P < 0.001). The percentage of patients with adequate knowledge was lower for MDD users (40%) compared with non-MDD users (79%, P < 0.001). The differences in adherence were independent of knowledge and MMSE scores. CONCLUSION this study shows that older patients receiving their drugs via MDD reported a higher medication adherence compared with patients receiving manually dispensed drugs, despite a lower knowledge and lower cognitive function among patients receiving MDD.
Learning Algorithms from Natural Proofs

Based on Hastad's (1986) circuit lower bounds, Linial, Mansour, and Nisan (1993) gave a quasipolytime learning algorithm for AC0 (constant-depth circuits with AND, OR, and NOT gates), in the PAC model over the uniform distribution. It was an open question to get a learning algorithm (of any kind) for the class of AC0[p] circuits (constant-depth, with AND, OR, NOT, and MODp gates for a prime p). Our main result is a quasipolytime learning algorithm for AC0[p] in the PAC model over the uniform distribution with membership queries. This algorithm is an application of a general connection we show to hold between natural proofs (in the sense of Razborov and Rudich (1997)) and learning algorithms. We argue that a natural proof of a circuit lower bound against any (sufficiently powerful) circuit class yields a learning algorithm for the same circuit class. As the lower bounds against AC0[p] by Razborov (1987) and Smolensky (1987) are natural, we obtain our learning algorithm for AC0[p].
Changing Roles: Dynamic Role Assignment

Modeling roles as sets of normative behavior that agents can assume has been found to be a useful development technique. An important characteristic of real-world agent systems is that the roles played by an agent may change over time. These changes can be of several different kinds. We describe an illustrative application where such role changes are important, analyze and classify the various kinds of role changes over time that may occur, and show how this analysis is useful in developing a more formal description of the application.
Fabrication and Characterization of Micro Opto-electronic Sensor

Tunneling junction is the basic structure of photoconductive semiconductor switch (PCSS) and single electric transistor (SET). In order to get ultra high speed PCSS, photo lithography and AFM nano oxidation methods are combined to fabricate micro metal (Ti)-insulator (TiOx)-metal (Ti) tunneling junction (MIM) type PCSS. Multi-junctions structure is tried to enhance the PCSS’s photoelectric efficiency. The I-V characteristics, such as effect of TiOx wire width on tunneling and effect of TiOx wire’s number on Tunneling of the tunneling junctions, are studied and analyzed in this paper. The results indicate that there is a clear exponential relationship between tunneling current and bias voltage and that different TiOx wire width and different numbers of TiOx wires induce different tunneling phenomena.