Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Algorithm Uncertainty Principles

Previously, Bennet and Feynman asked if Heisenberg's uncertainty principle puts a limitation on a quantum computer (Quantum Mechanical Computers, Richard P. Feynman, Foundations of Physics, Vol. 16, No. 6, p597-531, 1986). Feynman's answer was negative. In this paper, we will revisit the same question for the discrete time Fourier transform uncertainty principle. We will show that the discrete time Fourier transform uncertainty principle plays a fundamental role in showing that Shor's type of quantum algorithms has efficient running time and conclude that the discrete time uncertainty principle is an aid in our current formulation and understanding of Shor's type of quantum algorithms. It turns out that for these algorithms, the probability of measuring an element in some set $T$ (at the end of the algorithm) can be written in terms of the time-limiting and band-limiting operators from finite Fourier analysis. Associated with these operators is the finite Fourier transform uncertainty principle. The uncertainty principle provides a lower bound for the above probability. We will derive lower bounds for these types of probabilities in general. We will call these lower bounds quantum algorithm uncertainty principles or QAUP. QAUP are important because they give us some sense of the probability of measuring something desirable. We will use these lower bounds to derive Shor's factoring and discrete log algorithms.
SUPERCONDUCTING MAGNETS FOR USE INSIDE THE HERA EP INTERACTION REGIONS

For the HERA luminosity upgrade, superconducting magnets will be inserted inside the existing H1 and ZEUS experimental detectors. These magnets enable earlier separation of the electron and proton colliding beams than the original HERA design and provide additional interaction region (IR) focusing. Design and production of such magnets is challenging due to detector space limitations, interaction with detector solenoidal fields, large inner synchrotron radiation apertures and stringent field quality requirements. We plan to direct wind ≈1 mm cable in dipole, quadrupole, skew dipole and skew quadrupole circuits as discussed in this paper. Recent magnetic field measurements of a short prototype magnet, for quantifying ramp rate effects, are also presented here.
A framework toward a self-organizing and self-healing certificate authority group in a Content Addressable Network

Public-key provision in on Internet scale is crucial for securing peer-to-peer (P2P) applications. This paper proposes a framework for a self-organizing and self-healing certificate authority (CA) in a Content Addressable Network (CAN) that can provide certificates without a centralized Trusted Third Party (TTP). In our framework, a CA group is initialized by bootstrapping nodes and then grows to a mature state by itself. Based on our group management policies, the membership in the CA group is dynamic and has a uniform distribution over the P2P community. Meanwhile, the honest majority of the CA group is maintained by a Byzantine agreement algorithm, and all shares of the CA group are refreshed gradually and continuously. A security analysis shows that the framework enables key registration and certificate issue with resistance to man-in-the-middle (MITM), collusion, and node impersonation attacks.
Of microtubules and memory: implications for microtubule dynamics in dendrites and spines

Microtubules (MTs) are cytoskeletal polymers composed of repeating subunits of tubulin that are ubiquitously expressed in eukaryotic cells. They undergo a stochastic process of polymerization and depolymerization from their plus ends termed dynamic instability. MT dynamics is an ongoing process in all cell types and has been the target for the development of several useful anticancer drugs, which compromise rapidly dividing cells. Recent studies also suggest that MT dynamics may be particularly important in neurons, which develop a highly polarized morphology, consisting of a single axon and multiple dendrites that persist throughout adulthood. MTs are especially dynamic in dendrites and have recently been shown to polymerize directly into dendritic spines, the postsynaptic compartment of excitatory neurons in the CNS. These transient polymerization events into dendritic spines have been demonstrated to play important roles in synaptic plasticity in cultured neurons. Recent studies also suggest that MT dynamics in the adult brain function in the essential process of learning and memory and may be compromised in degenerative diseases, such as Alzheimer’s disease. This raises the possibility of targeting MT dynamics in the design of new therapeutic agents.
A Vision for Apple Orchard Systems of the Future

“Orchards of the future will likely be 10-11 feet tall and with very narrow canopies that can be maintained by mechanical side-wall shearing to reduce labor costs and to improve fruit quality and harvested and pruned with harvest assist platforms. We expect such orchards to have very high yields (1500 bu/acre) with uniformly high fruit quality. We propose that such future orchards can be managed with significantly less total annual labor hours. ” There has been a steady increase in tree planting density over the last 50 years from 40 trees/acre to in some cases more than 3,000 trees/acre. Since the beginning of this planting system revolution growers in NY State have progressively moved from multiple leader trees on seedling rootstocks at 40 trees/ acre to the central leader system on semi-dwar f ing rootstocks at 200 trees/acre, to the slender spindle system on fully dwarfing roots to ck s a t 6 0 0 t re e s / a c re , to small central leader trees on M.9/MM.111 interstem root systems at 400 trees/acre to the vertical axis system on dwarfing rootstocks at 500 trees/acre, to the super spindle system on dwarfing rootstocks at 2,200 trees/acre to the tall spindle system at 1,000 trees/acre. In this article we would like to present a vision for the orchards of the next 20 years.
Evolutionary robotics and SAGA: The case for hill crawling and tournament selection

This paper will look at an evolutionary approach to robotics; partly at pragmatic issues, but primarily at theoretical issues associated with the evolutionary algorithms which are appropriate. Genetic Algorithms are not suitable in their usual form for the evolution of cognitive structures, which must be in an incremental fashion. SAGA | Species Adaptation Genetic Algorithms | is a conceptual framework for extending GAs to variable length genotypes, where evolution allows a species of individuals to evolve from simple to more complex. In the context of species evolutionthe metaphor of hill-crawling as opposed to hill-climbing is introduced, and appropriate mutation rates discussed. On both pragmatic and theoretical grounds, it will be suggested that there are good reasons for using Tournament Selection in evolutionary robotics.
articu-A juvenile cf. Edmontosaurus annectens (Ornithischia, Hadrosauridae) femur documents a previously unreported intermediate growth stage for this taxon

: A nearly complete, but isolated, femur of a small hadrosaurid from the Hell Creek Formation of Montana is tentatively referred to Edmontosaurus annectens . At 28 cm long, the element can be classified as likely that from an ‘early juvenile’ individual, approximately 24% of the maximum known femur length for this species. Specimens from this size range and age class have not been described previously for E. annectens . Notable trends with increasing body size include increasingly distinct separation of the femoral head and greater trochanter, relative increase in the size of the cranial trochanter, a slight reduction in the relative breadth of the fourth trochanter, and a relative increase in the prominence of the cranial intercondylar groove. The gross profile of the femoral shaft is fairly consistent between the smallest and largest individuals. Although an ontogenetic change from relatively symmetrical to an asymmetrical shape in the fourth trochanter has been suggested previously, the new juvenile specimen shows an asymmetric fourth trochanter. Thus, there may not be a consistent ontogenetic pattern in trochanteric morphology. An isometric relationship between femoral circumference and femoral length is confirmed for Edmontosaurus . Overall ontogenetic trends in the femur of Edmontosaurus are concordant with patterns seen in other Hadrosauridae, supporting a fairly conserved pattern of development for this element within the clade.
Predictions of Physicochemical Properties of Ionic Liquids with DFT

Nowadays, density functional theory (DFT)-based high-throughput computational approach is becoming more efficient and, thus, attractive for finding advanced materials for electrochemical applications. In this work, we illustrate how theoretical models, computational methods, and informatics techniques can be put together to form a simple DFT-based throughput computational workflow for predicting physicochemical properties of room-temperature ionic liquids. The developed workflow has been used for screening a set of 48 ionic pairs and for analyzing the gathered data. The predicted relative electrochemical stabilities, ionic charges and dynamic properties of the investigated ionic liquids are discussed in the light of their potential practical applications.
Mining GPS data to augment road models

Many advanced safety and navigation applications in vehicles require accurate, detailed digital maps, but manual lane measurements are expensive and time-consuming, making automated techniques desirable. This paper describes a data-mining approach to map refinement, using position traces that come from Global Positioning System receivers with differential corrections. The computed lane models enable safety applications, such as lanekeeping, and convenience applications, such as lane-changing advice. Experiments show that, starting from a baseline map that is commercially available, our lane models predict a vehicle’s lane with high accuracy from a small number of passes over a particular road segment. Multiple position traces are a powerful new source of data that enables cheap, automated methods of inducing lane models, as well as other geographic knowledge, like traffic signals and elevations, and potentially impacts any geographic information system with a need to relate to actual behavior.
Large Area Covering LiDAR Height Models – Problems and Solution

The company BIMTAS, belonging to the Greater Istanbul Municipality, generates a digital height model (DHM) for the area of the Greater Istanbul Municipality with a Riegl LSMQ680i full waveform laser scanner with 400kHz and a used field of view of +/-30°. A precise absolute orientation requires ground control points (GCP), presented by height values of gable roofs to allow also an improvement of horizontal shifts. Because of the very high number of flight lines it is not possible to have GCP for any flight line, so sub-blocks of approximately 10 flight lines have been combined by 3D-transformation based on height points on planes. These sub-blocks have been transformed to the GCP. The varying overlap of neighbored LiDAR-strips in the range of 40% allows a three-dimensional transformation of neighbored, but if 10 strips of a sub-block are transformed together this may lead to unfavorable error propagation. The sub-blocks are only shifted to control point groups with points on inclined roofs and on the ground. Nevertheless a check of the transformed LiDAR-strips by check points results in a vertical accuracy of better as 5cm. Another possibility of joining overlapping LiDAR-strips is a filtering of the point cloud, eliminating points on vegetation and at building limits. Such a transformation uses quite more corresponding points as the method based just on planes and is robust also in areas only with few and not well distributed buildings. The result of transformation is on a similar level. In addition to the original digital surface models (DSM) also DHM with the points of the bare ground have been generated. The major problem of the LiDAR-points is the data amount. With a density of 16 points/m2 a single strips has approximately 500 million ground points, exceeding the capacity of several programs.
Possibility of Ultra High-Energy Cosmic Rays from the Giant Flare in Soft Gamma Repeater 1806−20

On 2004 December 27, a giant flare from the soft gamma repeater 1806$-$20 was observed. The radiation mechanism of the initial peak of the flare would be controversial. In this letter we point out that very high-energy cosmic rays would be produced in the case that the flare was caused by internal shocks, as is usually considered for gamma-ray bursts. The highest energy of cosmic rays can reach $10^{19}$ eV, if the Lorentz factor of the shocks is sufficiently high. Future observations of cosmic rays will inform us about the mechanism of the giant flare.
On the Power of Adaptivity in Matrix Completion and Approximation

We consider the related tasks of matrix completion and matrix approximation from missing data and propose adaptive sampling procedures for both problems. We show that adaptive sampling allows one to eliminate standard incoherence assumptions on the matrix row space that are necessary for passive sampling procedures. For exact recovery of a low-rank matrix, our algorithm judiciously selects a few columns to observe in full and, with few additional measurements, projects the remaining columns onto their span. This algorithm exactly recovers an $n \times n$ rank $r$ matrix using $O(nr\mu_0 \log^2(r))$ observations, where $\mu_0$ is a coherence parameter on the column space of the matrix. In addition to completely eliminating any row space assumptions that have pervaded the literature, this algorithm enjoys a better sample complexity than any existing matrix completion algorithm. To certify that this improvement is due to adaptive sampling, we establish that row space coherence is necessary for passive sampling algorithms to achieve non-trivial sample complexity bounds. For constructing a low-rank approximation to a high-rank input matrix, we propose a simple algorithm that thresholds the singular values of a zero-filled version of the input matrix. The algorithm computes an approximation that is nearly as good as the best rank-$r$ approximation using $O(nr\mu \log^2(n))$ samples, where $\mu$ is a slightly different coherence parameter on the matrix columns. Again we eliminate assumptions on the row space.
Inverse KKT Motion Optimization : A Newton Method to Efficiently Extract Task Spaces and Cost Parameters from Demonstrations

Inverse Optimal Control (IOC) assumes that demonstrations are the solution to an optimal control problem with unknown underlying costs, and extracts parameters of these underlying costs. Inverse KKT motion optimization assumes that the demonstrations fulfill the Karush-Kuhn-Tucker conditions of an unknown underlying constrained optimization problem, and extracts parameters of this underlying problem. We propose the latter to extract the relevant task spaces and cost parameters from demonstrations of skills that involve contacts. The aim of this approach is to push learning from demonstration to more complex manipulation scenarios that include the interaction with objects and therefore the realization of contacts/constraints within the motion. We introduce the novel approach and present first results on simulation and real robots.
FARM : Feature-Assisted Aggregate Route Mining in Trajectory Data

An aggregate route of a set of trajectories is the representative movement direction of the set. Existing solutions address the problem of finding representative routes by finding clusters in the data with minimum intra-cluster deviation and then deriving a simplified trajectory to represent each cluster. However, existing similarity measures for trajectories are not discriminative and are sensitive to noise. This paper presents FARM, a framework for extracting aggregate routes from trajectory data. FARM first transforms the trajectories into a feature space. Next, it applies spectral clustering to find clusters in the feature space. Finally, we find a representative route for each cluster obtained. Experimental studies demonstrate the effectiveness of the proposed method.
Multiscale and directional transform for denoising Medical Images

In medical images, noise suppression is a particularly delicate and difficult task. A trade off between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. The main properties of a good image denoising model are that it will remove noise while preserving edges and contours. This paper proposes a new denoising technique called Contourlet transform. This method of contourlets has been used extensively for denoising medical image. It provides a flexible multi resolution, local and directional image expansion. The contourlet transform is realized efficiently via double iterated filter bank structure where the Laplacian Pyramid (LP) filter in the first stage is used to capture the point discontinuities, and then followed by a directional filter bank (DFB) to link the point discontinuities. In this paper, we evaluate Contourlets denoising procedures using medical test images corrupted with additive Gaussian noise,salt&pepper noise, multiplicative noise and compare the performance with FBP,Wavelets, in terms of the peak-signal-to-noise ratio (PSNR) as a measure of the quality of denoising.Expermental results shows that the contourlet transform outperforms the other two techniques. Keywords— Contourlets, Denoising, FBP, Laplacian Pyramid (LP), Tomography, Wavelets.
Detection of Primary User in Cognitive Radio Using Bayesian Approach

Using cognitive radios (CRs), the secondary users (SUs) is allowed to use the spectrum originally allocated to primary users (PUs) as long as the primary users are not using it temporarily. This operation is called opportunistic spectrum access (OSA). To avoid interference to the primary users, the SUs have to perform spectrum sensing before their attempts to transmit over the spectrum. In this paper we use energy detector, Bayesian detector and Approximate Bayesian detector for digitally modulated primary user to maximize the spectrum utilization, without prior information of transmitted sequence of the primary signals. We provide the performance analysis of the suboptimal detectors in terms of probabilities of detection and false alarm. In spectrum utilization and secondary user's throughput performance of the Bayesian and approximate Bayesian detector are better when compared with the energy detector. For the performance estimation we use MATLAB simulation environment.
Insecticide-Treated Nets for the Prevention of Malaria in Pregnancy: A Systematic Review of Randomised Controlled Trials

Background Protection from malaria with insecticide-treated bednets (ITNs) during pregnancy is widely advocated, but evidence of benefit has been inconsistent. We undertook a systematic review of randomised trials. Methods and Findings Three cluster-randomised and two individually randomised trials met the inclusion criteria; four from Africa (n = 6,418) and one from Thailand (n = 223). In Africa, ITNs compared to no nets increased mean birth weight by 55 g (95% confidence interval [CI] 21–88), reduced low birth weight by 23% (relative risk [RR] 0.77, 95% CI 0.61–0.98), and reduced miscarriages/stillbirths by 33% (RR 0.67, 0.47–0.97) in the first few pregnancies. Placental parasitaemia was reduced by 23% in all gravidae (RR 0.77, 0.66–0.90). The effects were apparent in the cluster-randomised trials and the one individually randomised trial in Africa. The trial in Thailand, which randomised individuals to ITNs or untreated nets, showed reductions in anaemia and fetal loss in all gravidae, but not reductions in clinical malaria or low birth weight. Conclusions ITNs used throughout pregnancy or from mid-pregnancy onwards have a beneficial impact on pregnancy outcome in malaria-endemic Africa in the first few pregnancies. The potential impact of ITNs in pregnant women and their newborns in malaria regions outside Africa requires further research.
Complete Genome Sequence of Phytopathogenic Pectobacterium atrosepticum Bacteriophage Peat1

ABSTRACT Pectobacterium atrosepticum is a common phytopathogen causing significant economic losses worldwide. To develop a biocontrol strategy for this blackleg pathogen of solanaceous plants, P. atrosepticum bacteriophage Peat1 was isolated and its genome completely sequenced. Interestingly, morphological and sequence analyses of the 45,633-bp genome revealed that phage Peat1 is a member of the family Podoviridae and most closely resembles the Klebsiella pneumoniae bacteriophage KP34. This is the first published complete genome sequence of a phytopathogenic P. atrosepticum bacteriophage, and details provide important information for the development of biocontrol by advancing our understanding of phage-phytopathogen interactions.
Class A β-Lactamases as Versatile Scaffolds to Create Hybrid Enzymes: Applications from Basic Research to Medicine

Designing hybrid proteins is a major aspect of protein engineering and covers a very wide range of applications from basic research to medical applications. This review focuses on the use of class A β-lactamases as versatile scaffolds to design hybrid enzymes (referred to as β-lactamase hybrid proteins, BHPs) in which an exogenous peptide, protein or fragment thereof is inserted at various permissive positions. We discuss how BHPs can be specifically designed to create bifunctional proteins, to produce and to characterize proteins that are otherwise difficult to express, to determine the epitope of specific antibodies, to generate antibodies against nonimmunogenic epitopes, and to better understand the structure/function relationship of proteins.
Antiproton tagging and vertex fitting in a Timepix 3 detector The AEgIS collaboration

Studies of antimatter are important for understanding our universe at a fundamental level. There are still unsolved problems, such as the matter-antimatter asymmetry in the universe. The AEgIS experiment at CERN aims at measuring the gravitational fall of antihydrogen in order to determine the gravitational force on antimatter. The proposed method will make use of a positionsensitive detector to measure the annihilation point of antihydrogen. Such a detector must be able to tag the antiproton, measure its time of arrival and reconstruct its annihilation point with high precision in the vertical direction. This work explores a new method for tagging antiprotons and reconstructing their annihilation point. Antiprotons from the Antiproton Decelerator at CERN were used to obtain data on direct annihilations on the surface of a silicon pixel sensor with Timepix3 readout. These data were used to develop and verify a detector response model for annihilation of antiprotons in this detector. Using this model and the antiproton data it is shown that a tagging efficiency of 50 ± 10% and a vertical position resolution of 22 ± 0.5 μm can be obtained.
Monitoring of Network Traffic based on Queuing Theory

Network traffic monitoring is an important way for network performance analysis and monitor. The present article explores how to build the basic model of network traffic analysis based on Queuing Theory. In the present work, two queuing models (M/M/1): ((C+1)/FCFS) and (M/M/2): ((C+1)/FCFS) have been applied to determine the forecast way for the stable congestion rate of the network traffic. Using this we can obtain the network traffic forecasting ways and the stable congestion rate formula. Combining the general network traffic monitor parameters, we can realize the estimation and monitor process for the network traffic rationally.