Miracle-dz/UniFAR-FTUs huggingface dataset:
An Anytime Algorithm for Causal Inference

The Fast Casual Inference (FCI) algorithm searches for features common to observationally equivalent sets of causal directed acyclic graphs. It is correct in the large sample limit with probability one even if there is a possibility of hidden variables and selection bias. In the worst case, the number of conditional independence tests performed by the algorithm grows exponentially with the number of variables in the data set. This affects both the speed of the algorithm and the accuracy of the algorithm on small samples, because tests of independence conditional on large numbers of variables have very low power. In this paper, I prove that the FCI algorithm can be interrupted at any stage and asked for output. The output from the interrupted algorithm is still correct with probability one in the large sample limit, although possibly less informative (in the sense that it answers “Can’t tell” for a larger number of questions) than if the FCI algorithm had been allowed to continue uninterrupted.
A short review of ‘DGP spectroscopy’

In this paper we provide a short review of the main results developed in Charmousis et al (2006 Preprint hep-th/0604086). We focus on linearized vacuum perturbations about the self-accelerating branch of solutions in the DGP model. These are shown to contain a ghost in the spectrum for any value of the brane tension. We also comment on Deffayet et al (2006 Preprint hep-th/0607099), where some counter arguments have been presented.
IMPROVED SCIAMACHY WFDOAS TOTAL OZONE RETRIEVAL: STEPS TOWARDS HOMOGENISING LONG-TERM TOTAL OZONE DATASETS FROM GOME, SCIAMACHY, AND GOME2

Currently three European satellite spectrometers, GOME1/ERS2 (1995-present), SCIAMACHY/ENVISAT (2002-present), and GOME2 (2006-present) provide a near global decadal data set of total ozone covering more than a decade. This data are very valuable for the detection of recovery in stratospheric ozone as expected from the levelling off of stratospheric chlorine. In order to detect such a signal beyond the level of the large inter-annual variability is challenging and requires high accuracy in retrieved ozone with a stability to within one percent (relative bias) over a decade and absolute accuracy to within a few percent. A particular challenge will be to homogenise data sets from different instruments. In this paper we discuss important retrieval issues that are deemed important in order to avoid excessive homogenisation of multiple data sets (if homogenisation is understood as bias removal). The relevant issues discussed here are the choice of ozone cross-sections, the use of a-priori O3 profile climatologies, and level-1 spectral calibration.
On the convergence of linear passive complementarity systems

The notion of convergent systems is a powerful tool both in the analysis and synthesis of nonlinear systems. Sufficient conditions for convergence have been under investigation for smooth systems and for classes of non-smooth switching systems in the literature. In this paper, we look at a very particular class of non- smooth systems, namely complementarity systems. These systems have the capability of capturing the non-smooth dynamics of various interesting applications from different fields of engineering. The main contribution of this paper is to show that a linear complementarity system is convergent if the underlying linear dynamics possesses a certain positive realness property.
Phenotypic engineering of sperm-production rate confirms evolutionary predictions of sperm competition theory

Sperm production is a key male reproductive trait and an important parameter in sperm competition theory. Under sperm competition, paternity success is predicted to depend strongly on male allocation to sperm production. Furthermore, because sperm production is inherently costly, individuals should economize in sperm expenditure, and conditional adjustment of the copulation frequency according to their sperm availability may be expected. However, experimental studies showing effects of sperm production on mating behaviour and paternity success have so far been scarce, mainly because sperm production is difficult to manipulate directly in animals. Here, we used phenotypic engineering to manipulate sperm-production rate, by employing dose-dependent RNA interference (RNAi) of a spermatogenesis-specific gene, macbol1, in the free-living flatworm Macrostomum lignano. We demonstrate (i) that our novel dose-dependent RNAi approach allows us to induce high variability in sperm-production rate; (ii) that a reduced sperm-production rate is associated with a decreased copulation frequency, suggesting conditional adjustment of mating behaviour; and (iii) that both sperm production and copulation frequency are important determinants of paternity success in a competitive situation, as predicted by sperm competition theory. Our study clearly documents the potential of phenotypic engineering via dose-dependent RNAi to test quantitative predictions of evolutionary theory.
A methodology for selecting experiments to measure energy costs in smartphones

Smartphones equipped with latest applications and features are the reality of the modern telecommunication world. Researchers have studied the energy consumption in smartphones while running some network related applications (NRAs) but they have neither fully covered the wide pool of NRAs nor provided a methodology to measure the energy consumption in smartphones. In this paper, we identified the most popular NRAs and configurable parameters which can impact the energy consumption while running these NRAs. We further propose a methodology to measure the energy consumption in smartphones while conducting a feasible set of experiments. We present a measurement bench for measuring the energy consumption in smartphones. We conducted selected experiments on latest smartphones (BB 9700, Nokia E71, HTC Nexus One and HTC HD2) to support our methodology. Our methodology evaluates the impact of configurable parameters and NRAs on energy consumption and provide a base to compare the energy consumption across smartphones.
A q-weighted version of the Robinson-Schensted algorithm

We introduce a q-weighted version of the Robinson-Schensted (column insertion) algorithm which is closely connected to q Whittaker functions (or Macdonald polynomials with t=0) and reduces to the usual Robinson-Schensted algorithm when q=0. The q-insertion algorithm is `randomised', or `quantum', in the sense that when inserting a positive integer into a tableau, the output is a distribution of weights on a particular set of tableaux which includes the output which would have been obtained via the usual column insertion algorithm. There is also a notion of recording tableau in this setting. We show that the distribution of weights of the pair of tableaux obtained when one applies the q-insertion algorithm to a random word or permutation takes a particularly simple form and is closely related to q-Whittaker functions. In the case $0\le q<1$, the q-insertion algorithm applied to a random word also provides a new framework for solving the q-TASEP interacting particle system introduced (in the language of q-bosons) by Sasamoto and Wadati (1998) and yields formulas which are equivalent to some of those recently obtained by Borodin and Corwin (2011) via a stochastic evolution on discrete Gelfand-Tsetlin patterns (or semistandard tableaux) which is coupled to the q-TASEP. We show that the sequence of P-tableaux obtained when one applies the q-insertion algorithm to a random word defines another, quite different, evolution on semistandard tableaux which is also coupled to the q-TASEP.
Towards Conceptualizing a Neural Systems-Based Anatomy of Attention-Deficit/Hyperactivity Disorder

Convergent data from neuroimaging, neuropsychological, genetic and neurochemical studies in attention-deficit/hyperactivity disorder (ADHD) have implicated dysfunction of the dorsolateral prefrontal cortex (DLPFC) and dorsal anterior cingulate cortex (dACC), which form the cortical arm of the frontostriatal network supporting executive functions. Furthermore, besides the DLPFC and dACC, structural and functional imaging studies have shown abnormalities in key brain regions within distributed cortical networks supporting attention. The conceptualization of neural systems biology in ADHD aims at the understanding of what organizing principles have been altered during development within the brain of a person with ADHD.Characterizing these neural systems using neuroimaging could be critical for the description of structural endophenotypes, and may provide the capability of in vivo categorization and correlation with behavior and genes.
Analysis of Genetic Diversity in Crop Plants—Salient Statistical Tools and Considerations

Knowledge about germplasm diversity and genetic relationships among breeding materials could be an invaluable aid in crop improvement strategies. A number of methods are currently available for analysis of genetic diversity in germplasm accessions, breeding lines, and populations. These methods have relied on pedigree data, morphological data, agronomic performance data, biochemical data, and more recently molecular (DNA-based) data. For reasonably accurate and unbiased estimates of genetic diversity, adequate attention has to be devoted to (i) sampling strategies; (ii) utilization of various data sets on the basis of the understanding of their strengths and constraints; (iii) choice of genetic distance measure(s), clustering procedures, and other multivariate methods in analyses of data; and (iv) objective determination of genetic relationships. Judicious combination and utilization of statistical tools and techniques, such as bootstrapping, is vital for addressing complex issues related to data analysis and interpretation of results from different types of data sets, particularly through clustering procedures. This review focuses on application of statistical tools and techniques in analysis of genetic diversity at the intraspecific level in crop plants.
On Optimizing Overlay Topologies for Search in Unstructured Peer-to-Peer Networks

Unstructured peer-to-peer (P2P) file-sharing networks are popular in the mass market. As the peers participating in unstructured networks interconnect randomly, they rely on flooding query messages to discover objects of interest and thus introduce remarkable network traffic. Empirical measurement studies indicate that the peers in P2P networks have similar preferences, and have recently proposed unstructured P2P networks that organize participating peers by exploiting their similarity. The resultant networks may not perform searches efficiently and effectively because existing overlay topology construction algorithms often create unstructured P2P networks without performance guarantees. Thus, we propose a novel overlay formation algorithm for unstructured P2P networks. Based on the file sharing pattern exhibiting the power-law property, our proposal is unique in that it poses rigorous performance guarantees. Theoretical performance results conclude that in a constant probability, 1) searching an object in our proposed network efficiently takes O(lnc N) hops (where c is a small constant), and 2) the search progressively and effectively exploits the similarity of peers. In addition, the success ratio of discovering an object approximates 100 percent. We validate our theoretical analysis and compare our proposal to competing algorithms in simulations. Based on the simulation results, our proposal clearly outperforms the competing algorithms in terms of 1) the hop count of routing a query message, 2) the successful ratio of resolving a query, 3) the number of messages required for resolving a query, and 4) the message overhead for maintaining and formatting the overlay.
Error-constrained COUNT query evaluation in relational databases

In thk paper, we discuss the problem of estimating a COUNT(E) query having a guaranteed error bound with a certain confidence level, where E is an arbitrary relational algebra (RA) expression with Select, Join and Intersection operations. Such a~ estimate is useful in query optimization as well as in real-time databases as it takes significantly less time to obtain compared with evaluating COUNT(E) completely. To guarantee the desired error bound with the given confidence level, we use double sampling (or two-phase sampling) where in the first stage preliminary information is obtained from a small pilot sample taken from the input relations. And then, the sample size for the second stage is deter-
The Unit Histogram Concept for Scarce Statistical Information

The new unit histogram concept is described as increasing with one order of magnitude the amount of statistical information extracted from experimental data. The new statistical technology is particularly suited for very scarce population samples, when it dramatically increases the information extracted from the available data. Otherwise, existing features of the population would remain inaccessible. The method could prove useful also for signal processing, when a high level of accuracy in detail rendition is required. The efficiency of the method is demonstrated in examples of experimental measurement of the combustion heat delivered by rocket propellants. Populations as small as of six readings, where the regular statistics is useless, are successfully processed and characterized.
Chern-Simons orbital magnetoelectric coupling in generic insulators

We present a Wannier-based method to calculate the Chern-Simons orbital magnetoelectric coupling in the framework of first-principles density-functional theory. In view of recent developments in connection with strong ${\mathbb{Z}}_{2}$ topological insulators, we anticipate that the Chern-Simons contribution to the magnetoelectric coupling could, in special cases, be as large or larger than the total magnetoelectric coupling in known magnetoelectrics, such as Cr${}_{2}$O${}_{3}$. The results of our calculations for the ordinary magnetoelectrics Cr${}_{2}$O${}_{3}$, BiFeO${}_{3}$, and GdAlO${}_{3}$ confirm that the Chern-Simons contribution is quite small in these cases. On the other hand, we show that, if the spatial-inversion and time-reversal symmetries of the ${\mathbb{Z}}_{2}$ topological insulator Bi${}_{2}$Se${}_{3}$ are broken by hand, large induced changes appear in the Chern-Simons magnetoelectric coupling.
Crystal structure of the DdrB/ssDNA complex from Deinococcus radiodurans reveals a DNA binding surface involving higher-order oligomeric states

The ability of Deinococcus radiodurans to recover from extensive DNA damage is due in part to its ability to efficiently repair its genome, even following severe fragmentation by hundreds of double-strand breaks. The single-strand annealing pathway plays an important role early during the recovery process, making use of a protein, DdrB, shown to greatly stimulate ssDNA annealing. Here, we report the structure of DdrB bound to ssDNA to 2.3 Å. Pentameric DdrB was found to assemble into higher-order structures that coat ssDNA. To gain further mechanistic insight into the protein's function, a number of point mutants were generated altering both DNA binding and higher order oligomerization. This work not only identifies higher-order DdrB associations but also suggests the presence of an extended DNA binding surface running along the ‘top’ surface of a DdrB pentamer and continuing down between two individual subunits of the ring structure. Together this work sheds new insight into possible mechanisms for DdrB function in which higher-order assemblies of DdrB pentamers assist in the pairing of complementary ssDNA using an extended DNA binding surface.
Characterization of Large Scale Functional Brain Networks During Ketamine-Medetomidine Anesthetic Induction

Several experiments evidence that specialized brain regions functionally interact and reveal that the brain processes and integrates information in a specific and structured manner. Networks can be used to model brain functional activities constituting a way to characterize and quantify this structured form of organization. Reports state that different physiological states or even diseases that affect the central nervous system may be associated to alterations on those networks, that might reflect in graphs of different architectures. However, the relation of their structure to different states or conditions of the organism is not well comprehended. Thus, experiments that involve the estimation of functional neural networks of subjects exposed to different controlled conditions are of great relevance. Within this context, this research has sought to model large scale functional brain networks during an anesthetic induction process. The experiment was based on intra-cranial recordings of neural activities of an old world macaque of the species Macaca fuscata. Neural activity was recorded during a Ketamine-Medetomidine anesthetic induction process. Networks were serially estimated in time intervals of five seconds. Changes were observed in various networks properties within about one and a half minutes after the administration of the anesthetics. These changes reveal the occurrence of a transition on the networks architecture. During general anesthesia a reduction in the functional connectivity and network integration capabilities were verified in both local and global levels. It was also observed that the brain shifted to a highly specific and dynamic state. The results bring empirical evidence and report the relation of the induced state of anesthesia to properties of functional networks, thus, they contribute for the elucidation of some new aspects of neural correlates of consciousness.
Design and Applications of A Smooth Mobility Model for Mobile Ad Hoc Networks

Existing mobility models used in the simulation tools have two major limitations. First, these models invoke unrealistic moving behaviors, such as sudden stop and sharp turn during the simulation. Hence, the study of mobile ad-hoc networks (MANETs) based on these models could lead to wrong conclusions. Second, because the node speed and direction do not change within each movement, they are insufficient to mimic the minute moving behaviors of mobile users. Therefore, we design a novel smooth mobility model, which can characterize the real-life moving behaviors of mobile users in accordance with the physical law of a smooth motion. Moreover, we apply the smooth model to evaluate the routing performance and network connectivity of MANETs. Compared with the most commonly used mobility model, random waypoint (RWP) model, we find that the routing performance and network connectivity evaluation based on the RWP model is over optimistic. To demonstrate the applications of the smooth model, we present the easy adaptation of the smooth model to group mobility and geographic restrictions
Is Enhanced Recovery the New Standard of Care in Microsurgical Breast Reconstruction?

Background: At present, there are limited data available regarding the use and feasibility of enhanced recovery pathways for patients undergoing microsurgical breast reconstruction. The authors sought to assess patient outcomes before and after the introduction of an enhanced recovery pathway that was adopted at a single cancer center. Methods: A multidisciplinary enhanced recovery pathway was developed for patients undergoing deep inferior epigastric perforator or free transverse rectus abdominis myocutaneous flap breast reconstruction. Core elements of the enhanced recovery pathway included substituting intravenous patient-controlled analgesia with ketorolac and transversus abdominis plane blocks using liposomal bupivacaine, as well as intraoperative goal-directed fluid management. Patients who underwent surgery between April and August of 2015 using the enhanced recovery pathway were compared with a historical control cohort. The primary endpoints were hospital length of stay and total postoperative opioid consumption. Results: In total, 91 consecutive patients were analyzed (enhanced recovery pathway, n = 42; pre–enhanced recovery pathway, n = 49). Mean hospital length of stay was significantly shorter in the enhanced recovery pathway group than in the pre–enhanced recovery pathway group (4.0 days versus 5.0 days; p < 0.0001). Total postoperative morphine equivalent consumption was also lower in the enhanced recovery pathway group (46.0 mg versus 70.5 mg; p = 0.003). There was no difference in the incidence of 30-day complications between the groups (p = 0.6). Conclusion: The adoption of an enhanced recovery pathway for deep inferior epigastric perforator and transverse rectus abdominis myocutaneous flap reconstruction by multiple surgeons significantly decreased opioid consumption and reduced length of stay by 1 day. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.
Compressed Multiple-Row Storage Format

A new format for storing sparse matrices is proposed for efficient sparse matrix-vector (SpMV) product calculation on modern throughput-oriented computer architectures. This format extends the standard compressed row storage (CRS) format and is easily convertible to and from it without any memory overhead. Computational performance of an SpMV kernel for the new format is determined for over 140 sparse matrices on two Fermi-class graphics processing units (GPUs) and the efficiency of the kernel, which peaks at 36 and 25 GFLOPS at single and double precision, respectively, is compared with that of five existing generic algorithms and industrial implementations. The efficiency of the new format is also measured as a function of the mean (μ) and of the standard deviation (σ) of the number of matrix nonzero elements per row. The largest speedup is found for matrices with μ & 20 and μ & σ & 1.5 and can be as high as 43%.
Measuring the Strength of Interaction between the Ebola Fusion Peptide and Lipid Rafts: Implications for Membrane Fusion and Virus Infection

The Ebola fusion peptide (EBO16) is a hydrophobic domain that belongs to the GP2 membrane fusion protein of the Ebola virus. It adopts a helical structure in the presence of mimetic membranes that is stabilized by the presence of an aromatic-aromatic interaction established by Trp8 and Phe12. In spite of its infectious cycle becoming better understood recently, several steps still remain unclear, a lacuna that makes it difficult to develop strategies to block infection. In order to gain insight into the mechanism of membrane fusion, we probed the structure, function and energetics of EBO16 and its mutant W8A, in the absence or presence of different lipid membranes, including isolated domain-resistant membranes (DRM), a good experimental model for lipid rafts. The depletion of cholesterol from living mammalian cells reduced the ability of EBO16 to induce lipid mixing. On the other hand, EBO16 was structurally sensitive to interaction with lipid rafts (DRMs), but the same was not observed for W8A mutant. In agreement with these data, W8A showed a poor ability to promote membrane aggregation in comparison to EBO16. Single molecule AFM experiments showed a high affinity force pattern for the interaction of EBO16 and DRM, which seems to be a complex energetic event as observed by the calorimetric profile. Our study is the first to show a strong correlation between the initial step of Ebola virus infection and cholesterol, thus providing a rationale for Ebola virus proteins being co-localized with lipid-raft domains. In all, the results show how small fusion peptide sequences have evolved to adopt highly specific and strong interactions with membrane domains. Such features suggest these processes are excellent targets for therapeutic and vaccine approaches to viral diseases.