Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonrelativistic Collisionless Shocks in Unmagnetized Electron-Ion Plasmas

We show that the Weibel-mediated collisionless shocks are driven at nonrelativistic propagation speed (0.1c < V < 0.45c) in unmagnetized electron-ion plasmas by performing two-dimensional particle-in-cell simulations. It is shown that the profiles of the number density and the mean velocity in the vicinity of the shock transition region, which are normalized by the respective upstream values, are almost independent of the upstream bulk velocity, i.e., the shock velocity. In particular, the width of the shock transition region is ~100 ion inertial lengths, independent of the shock velocity. For these shocks the energy density of the magnetic field generated by the Weibel-type instability within the shock transition region reaches typically 1%-2% of the upstream bulk kinetic energy density. This mechanism probably explains the robust formation of collisionless shocks, for example, driven by young supernova remnants, with no assumption of an external magnetic field in the universe.
Intracellular Movement of Green Fluorescent Protein–Tagged Phosphatidylinositol 3-Kinase in Response to Growth Factor Receptor Signaling

Phosphatidylinositol 3-kinase (PI 3-kinase) is a lipid kinase which has been implicated in mitogenesis, protein trafficking, inhibition of apoptosis, and integrin and actin functions. Here we show using a green fluorescent protein–tagged p85 subunit that phosphatidylinositol 3-kinase is distributed throughout the cytoplasm and is localized to focal adhesion complexes in resting NIH-3T3, A431, and MCF-7 cells. Ligand stimulation of an epidermal growth factor receptor/c-erbB-3 chimera expressed in these cells results in a redistribution of p85 to the cell membrane which is independent of the catalytic activity of the enzyme and the integrity of the actin cytoskeleton. The movement is, however, dependent on the phosphorylation status of the erbB-3 chimera. Using rhodamine-labeled epidermal growth factor we show that the phosphatidylinositol 3-kinase and the receptors colocalize in discrete patches on the cell surface. Low concentrations of ligand cause patching only at the periphery of the cells, whereas at high concentrations patches were seen over the whole cell surface. Using green fluorescent protein–tagged fragments of p85 we show that binding to the receptor requires the NH2-terminal part of the protein as well as its SH2 domains.
A study of time-varying cost parameter estimation methods in automated transportation systems based on mobile robots

Efficient control of systems based on automated guided vehicles requires accurate estimation of cost parameters such as speed, energy, task completion performance, et cetera. These parameters change along time, particularly in battery-operated robots. This work addresses the problem of on-line cost parameter identification and estimation which will be beneficial for proper control decisions of the individual mobile robots and for the system as a whole. Several filtering and estimation methods have been investigated with respect to travelling times, as they are considered key cost parameters. Results show that these parameters depend on the robot, the route and the moment, so they are linked to a particular robot, a region of the floor and a time period (or to a battery level). In fact, differences with static, pre-runtime travelling time computations, either heuristically or by characterization of real robots, are large enough to affect system's performance and overall productivity and efficiency.
Neural encoding of large-scale three-dimensional space—properties and constraints

How the brain represents represent large-scale, navigable space has been the topic of intensive investigation for several decades, resulting in the discovery that neurons in a complex network of cortical and subcortical brain regions co-operatively encode distance, direction, place, movement etc. using a variety of different sensory inputs. However, such studies have mainly been conducted in simple laboratory settings in which animals explore small, two-dimensional (i.e., flat) arenas. The real world, by contrast, is complex and three dimensional with hills, valleys, tunnels, branches, and—for species that can swim or fly—large volumetric spaces. Adding an additional dimension to space adds coding challenges, a primary reason for which is that several basic geometric properties are different in three dimensions. This article will explore the consequences of these challenges for the establishment of a functional three-dimensional metric map of space, one of which is that the brains of some species might have evolved to reduce the dimensionality of the representational space and thus sidestep some of these problems.
Information Rate of OFDM-Based Optical Wireless Communication Systems With Nonlinear Distortion

In this paper, a piecewise polynomial function is proposed as a generalized model for the nonlinear transfer characteristic of the transmitter for optical wireless communications (OWC). The two general multicarrier modulation formats for OWC based on orthogonal frequency-division multiplexing (OFDM), direct-current-biased optical OFDM (DCO-OFDM) and asymmetrically clipped optical OFDM (ACO-OFDM), are studied. The nonlinear distortion of the electrical signal-to-noise ratio (SNR) at the receiver is derived in closed form, and it is verified by means of a Monte Carlo simulation. This flexible and accurate model allows for the application of pre-distortion and linearization of the dynamic range of the transmitter between points of minimum and maximum radiated optical power. Through scaling and DC-biasing the transmitted signal is optimally conditioned in accord with the optical power constraints of the transmitter front-end, i.e., minimum, average and maximum radiated optical power. The mutual information of the optimized optical OFDM (O-OFDM) schemes is presented as a measure of the capacity of these OWC systems under an average electrical power constraint. When the additional DC bias power is neglected, DCO-OFDM is shown to achieve the Shannon capacity when the optimization is employed, while ACO-OFDM exhibits a 3-dB gap which grows with higher information rate targets. When the DC bias power is counted towards the signal power, DCO-OFDM outperforms ACO-OFDM for the majority of average optical power levels with the increase of the information rate target or the dynamic range. The results can be considered as a lower bound on the O-OFDM system capacity.
Eliminating error with older eyewitnesses using the elimination lineup

Older eyewitnesses have difficulty saying the perpetrator is not present in a lineup where the perpetrator is in fact absent. In this study a lineup technique called the elimination lineup was used to see whether it could help seniors. Younger (N=62, ages 18-58) and older adults (N=30, ages 61-94) were assessed using four different lineup conditions: the traditional simultaneous technique and the elimination technique with the perpetrator present or absent. Participants watched a video of either an older or a younger man driving then answered questions about the video, completed a driving behaviour survey, and looked at a photo lineup to potentially identify the driver. Older participants performed better with the elimination lineup than the simultaneous lineup if the driver was absent and similar to younger participants on the elimination lineup if the driver was present. This demonstrates the elimination lineup may be a better alternative for older eyewitnesses.
Solving the Langford problem in parallel

In this paper, the parallel resolution of the Langford problem is studied. Two different approaches are developed. First, an explicit construction of all the solutions is done using a shared memory. The application associated to this approach is written in C using the standard OpenMP library. Second, a parallelization of the algebraic method introduced by Godfrey is proposed. The application is taking advantage of MPI and has revealed efficient up to 128 processors. This solution opens up some new perspectives such as solving the already resolved instances of the problem more quickly and solving the next two open instances of the problem in a near future.
Biochemical effects and therapeutic potential of tunicamycin in murine L1210 leukemia.

Tunicamycin, an antibiotic which specifically inhibits the dolichol-mediated synthesis of glycoproteins, significantly decreased the incorporation of tritiated D-mannose and D-glucosamine into L1210 ascites leukemia cell glycoproteins at concentrations which affected the biosynthesis of proteins minimally. Mice receiving inoculations of L1210 cells pretreated with 10 microM tunicamycin in vitro survived nearly twice as long as did mice receiving implants of untreated tumor cells. A nonlethal dose of X-irradiation (350 rads) to mice 24 hr prior to receiving their inoculation of tunicamycin-treated L1210 cells prevented this increase in life span. Thirty-eight % of the long-term surviving mice which received 1 X 10(5) L1210 cells pretreated with 10 microM tunicamycin in vitro were then resistant to a subsequent challenge with 10(6) untreated L1210 ascites cells. Direct i.p. administration of tunicamycin to mice resulted in potent liver toxicity (50% lethal dose, 2.0 mg/kg) which obviated any therapeutic efficacy when administered to L1210 ascites tumor-bearing mice. The administration of nontoxic levels of D-mannose prior to the administration of tunicamycin decreased the toxicity of the antibiotic in vivo and, when combined with D-mannose in vitro, exhibited cytotoxic additivity in terms of the inhibition of L1210 leukemic cell growth. A therapeutic regimen incorporating a 24-hr infusion of the sugar prior to multiple administrations of tunicamycin gave evidence of a small therapeutic response in terms of the survival of tumor-bearing mice. These results suggest that tunicamycin, an inhibitor of glycoprotein biosynthesis, might be able to alter tumor cell growth and immunogenicity provided that host liver toxicity is diminished.
Constituents from the Stems of Malaysian Uncaria tomentosa

Uncaria tomentosa (Willd. ex Schult.) DC. is well known as a medicinal plant that has been used for various treatments. This tropical vine grows up to 30 m tall and commonly found in natural forest. It has hook-like thorns that resemble the claws of a cat. The leaves are elliptic with a smooth edge, and grow in opposite whorls of two. Although there has not been any literature found on the availability of this species locally, we have discovered it in several parts of Peninsular Malaysia. A preliminary investigation of the stems of the plant has yielded three compounds, scopoletin, isopteropodine along with s-sitosterol. The structures of the isolated compounds were characterized by analysis of spectral characteristics (mostly 1D, 2D NMR and mass spectrometry) and comparison with literature.
Improving Spam Blacklisting Through Dynamic Thresholding and Speculative Aggregation

Unsolicited bulk e-mail (UBE) or spam constitutes a significant fraction of all e-mail connection attempts and routinely frustrates users, consumes resources, and serves as an infection vector for malicious software. In an effort to scalably and effectively reduce the impact of these e-mails, e-mail system designers have increasingly turned to blacklisting. Blacklisting (blackholing, block listing) is a form of course-grained, reputation-based, dynamic policy enforcement in which real-time feeds of spam sending hosts are sent to networks so that the e-mail from these hosts may be rejected. Unfortunately, current spam blacklist services are highly inaccurate and exhibit both false positives and significant false negatives. In this paper, we explore the root causes of blacklist inaccuracy and show that the trend toward stealthier spam exacerbates the existing tension between false positives and false negatives when assigning spamming IP reputation. We argue that to relieve this tension, global aggregation and reputation assignment should be replaced with local aggregation and reputation assignment, utilizing preexisting global spam collection, with the addition of local usage, policy, and reachability information. We propose two specific techniques based on this premise, dynamic thresholding and speculative aggregation, whose goal is to improve the accuracy of blacklist generation. We evaluate the performance and accuracy of these solutions in the context of our own deployment consisting of 2.5 million production e-mails and 14 million e-mails from spamtraps deployed in 11 domains over a month-long period. We show that the proposed approaches significantly improve the false positive and false negative rates when compared to existing approaches.
Dust and gas in the local environments of gamma-ray bursts

From spectral analysis on the XRT/UVOT Spectral Energy Distribution (SED) on a sample of Swift GRBs we determine the host galaxy hydrogen column density, N-H,N-X, and visual dust-extinction, AV. All but one GRBs have host galaxy dust properties that are most consistent with an SMC or LMC dust extinction law, with a range in AV from 0.11 +/- 0.07 to 0.88(-0.20)(+0.23) mags, although selection effects distort the true AV distribution. We estimate that GR13s with no afterglow detected blueward of 5500 angstrom to have an average rest-frame extinction almost seven times the average in our sample. This may help account for the similar to 1/3 of GRBs observed by Swift that have no afterglow detected by UVOT.
Regularization : Problen 1 s and Pro 111 ises

Reg;ularization is becoming a popular framework for describing and solving many ill-posed problems of computer vision. Of course, a generalized framework h; only useful if it provides additional insights or benefits unavailable without it. This paper discllsses some of the benefits promised by the regula.rization framework. Additionally, as a mathematical paradigm for vision, regularization presents many difficulties for the vision researcher, and some of these difficulties are discussed in this paper. The paper then discusses the lack of development of most of the "promises of regularization" theory, and gives a. brief look as some of the promises which have been realized. In the context of smooth surface reconstruction, the paper addresses one of t.he most difficult problems with the use of regularization: the problem of determining an appropriate fu nctional class, norm, and regularization stabilizing functional. I n particular, results are discussed from an experiment which subjectively orders various functional classes and stabilizing functionals for a regularization-based formulation of the surface reconstruction problem. The conclusions drawn include the fact that there exist non-traditional formulations of this regularization problem which provide better results. The paper concludes with a brief mention of two more general frameworks and their relationship to regularization.
WinPop 2.5: Software for representing population genetics phenomena

The curriculum for genetics courses is shifting from a classical to a more molecular genetics focus, increasing the importance of subjects such as population genetics. Population genetics is a computational and statistical field that requires a good understanding of the nature of stochastic events. It is a difficult field for biology students with a limited mathematical background and there is a need for visualisation tools to facilitate understanding by the use of practical examples. WinPop provides students and researchers with a visual tool to allow the simulation and representation of population genetics phenomena. WinPop is a user-friendly software meant for use in population genetics courses and basic research. WinPop 2.5 contains six different modules that represent and simulate population genetics models. Genotype and allele frequencies are calculated under the different models: panmixia, genetic drift, assortative matings, selection, gene flow and mutation. The program's interface presents information in Cartesian graphics and isosceles triangular coordinate systems, allowing the user to save graphical and textual data output from the simulations. WinPop is developed in Visual Basic 6.0 and uses Windows 95 and higher. WinPop 2.5 can be downloaded from http://www.genedrift. org/winpop.php.
Target Acquisition, Localization, and Surveillance Using a Fixed-Wing Mini-UAV and Gimbaled Camera

Target acquisition and continuous surveillance using fixed-wing UAVs is a difficult task due to the many degrees of freedom inherent in aircraft and gimbaled cameras. Mini-UAVs further complicate the problem by introducing severe restrictions on the size and weight of electro-optical sensor assemblies. We present a field-tested mini-UAV gimbal mechanism and flightpath generation algorithm as well as a human-UAV interaction scheme in which the operator manually flies the UAV to produce an estimate of the target position, then allows the aircraft to fly itself and control the gimbal while the operator re fines or moves the target position as required.
Estimated stocks of circumpolar permafrost carbon with quantified uncertainty ranges and identified data gaps

Soils and other unconsolidated deposits in the northern circumpolar permafrost region store large amounts of soil organic carbon (SOC). This SOC is potentially vulnerable to remobilization following soil warming and permafrost thaw, but SOC stock estimates were poorly constrained and quantitative error estimates were lacking. This study presents revised estimates of permafrost SOC stocks, including quantitative uncertainty estimates, in the 0–3 m depth range in soils as well as for sediments deeper than 3 m in deltaic deposits of major rivers and in the Yedoma region of Siberia and Alaska. Revised estimates are based on significantly larger databases compared to previous studies. Despite this there is evidence of significant remaining regional data gaps. Estimates remain particularly poorly constrained for soils in the High Arctic region and physiographic regions with thin sedimentary overburden (mountains, highlands and plateaus) as well as for deposits below 3 m depth in deltas and the Yedoma region. While some components of the revised SOC stocks are similar in magnitude to those previously reported for this region, there are substantial differences in other components, including the fraction of perennially frozen SOC. Upscaled based on regional soil maps, estimated permafrost region SOC stocks are 217 ± 12 and 472 ± 27 Pg for the 0–0.3 and 0–1 m soil depths, respectively (±95% confidence intervals). Storage of SOC in 0–3 m of soils is estimated to 1035 ± 150 Pg. Of this, 34 ± 16 Pg C is stored in poorly developed soils of the High Arctic. Based on generalized calculations, storage of SOC below 3 m of surface soils in deltaic alluvium of major Arctic rivers is estimated as 91 ± 52 Pg. In the Yedoma region, estimated SOC stocks below 3 m depth are 181 ± 54 Pg, of which 74 ± 20 Pg is stored in intact Yedoma (late Pleistocene ice- and organic-rich silty sediments) with the remainder in refrozen thermokarst deposits. Total estimated SOC storage for the permafrost region is ∼1300 Pg with an uncertainty range of ∼1100 to 1500 Pg. Of this, ∼500 Pg is in non-permafrost soils, seasonally thawed in the active layer or in deeper taliks, while ∼800 Pg is perennially frozen. This represents a substantial ∼300 Pg lowering of the estimated perennially frozen SOC stock compared to previous estimates.
Signal-power integrity and EMI analysis for singlechip and multi-chip-module applications

In this paper, a global Chip-Package-PCB Co-Design and Co-Verification methodology is successfully applied to Single-Chip Down-converter circuit and Multi-Chip-Module in transmit mode. Full-wave electromagnetic and thermal Co-Analysis approach is adopted to investigate impact of critical RF couplings, power dissipation and grounding strategies on systemlevel performances. The Single-Chip down-converter circuit shows 43dB conversion gain, with 6.5dB noise figure and output IP3 of 18dBm. The MCM design demonstrates 35dBm output IP3, 25dBm output CP1, with 45dB image rejection with 25dB voltage gain for a dissipated power of 2.2W.
Test Data Generation from UML State Machine Diagrams using GAs

Automatic test data generation helps testers to validate software against user requirements more easily. Test data can be generated from many sources; for example, experience of testers, source program, or software specification. Selecting a proper test data set is a decision making task. Testers have to decide what test data that they should use, and a heuristic technique is needed to solve this problem automatically. In this paper, we propose a framework for generating test data from software specifications. The selected specification is Unified Modeling Language (UML) state machine diagram. UML state machine diagram describes a system in term of state which can be changed when there is an action occurring in the system. The generated test data is a sequence of these actions. These sequences of action help testers to know how they should test the system. The quality of generated test data is measured by the number of transitions which is fired using the test data. The more transitions test data can fire, the better quality of test data is. The number of coverage transitions is also used as a feedback for a heuristic search for a better test set. Genetic algorithms (GAs) are selected for searching the best test data. Our experimental results show that the proposed GA-based approach can work well for generating test data for some types of UML state machine diagrams.
The semantics of personalised web accessibility assessment

This paper presents SAAF, a Semantic Accessibility Assessment Framework for personalised Web accessibility assessment procedures. We define four domains as a way to decouple general accessibility concepts and semantics (e.g., disabilities, device descriptions) from technology or assessment specific concepts. We leverage personalised Web accessibility by transforming questions such as "is this Web site accessible to me? " into rich-semantics queries on SAAF and integrate it into a Web accessibility evaluator.
Sequential Boolean function learning by classifier system

Classi f ier systems have been used extens ive ly to learn categor izat ions from examples in some important area of research in machine learning. A classi f ier system consists of an assor tment of rulel ike hypotheses known as classif iers. The per formance of such a system improves over t ime as better (those having more strength ) tend to prepondera te and dr ive out the weaker ones, i.e., those whose per formance is detr imental to the system as a whole. Strengths are reinforced by feedback from the env i ronment depending on system performance. Classi f ier systems were f irst proposed by Hol land (1976). Since then they have been appl ied in d iverse domains by researchers , e.g., Wilson (1985 a,b), Goldberg (1985), Booker (1985). In this paper, this important tool is used in a machine learning application, namely, for the purpose of learning a sequent ia l boolean function. Classi f ier systems have been used to learn boolean combinator ia l funct ions successful ly (Wilson, 1986). But thus far no research has been made in learning sequential boolean functions, a very important category in the f ield of digital logic. This paper shows that the classi f ier systems can be used to learn sequent ia l problems as well, and, as combinator ia l problems have al ready been solved using them, they can be used to learn almost any digital logic function.