DES14X3taz: A Type I Superluminous Supernova Showing a Luminous, Rapidly Cooling Initial Pre-peak Bump

We present DES14X3taz, a new hydrogen-poor superluminous supernova (SLSN-I) discovered by the Dark Energy Survey (DES) supernova program, with additional photometric data provided by the Survey Using DECam for Superluminous Supernovae. Spectra obtained using Optical System for Imaging and low-Intermediate-Resolution Integrated Spectroscopy on the Gran Telescopio CANARIAS show DES14X3taz is an SLSN-I at z = 0.608. Multi-color photometry reveals a double-peaked light curve: a blue and relatively bright initial peak that fades rapidly prior to the slower rise of the main light curve. Our multi-color photometry allows us, for the first time, to show that the initial peak cools from 22,000 to 8000 K over 15 rest-frame days, and is faster and brighter than any published core-collapse supernova, reaching 30% of the bolometric luminosity of the main peak. No physical 56Ni-powered model can fit this initial peak. We show that a shock-cooling model followed by a magnetar driving the second phase of the light curve can adequately explain the entire light curve of DES14X3taz. Models involving the shock-cooling of extended circumstellar material at a distance of 400  are preferred over the cooling of shock-heated surface layers of a stellar envelope. We compare DES14X3taz to the few double-peaked SLSN-I events in the literature. Although the rise times and characteristics of these initial peaks differ, there exists the tantalizing possibility that they can be explained by one physical interpretation.

Evaluation of an alternative spectroscopic approach for aflatoxin analysis: Comparative analysis of food and feed samples with UPLC-MS/MS

Increasing research has highlighted the effects of changing climates on the occurrence and prevalence of toxigenic Aspergillus species producing aflatoxins. There is concern of the toxicological effects to human health and animal productivity following acute and chronic exposure that may affect the future ability to provide safe and sufficient food globally. Considerable research has focused on the detection of these toxins, based on the physicochemical and biochemical properties of the aflatoxin compounds, in agricultural products for human and animal consumption. As improvements in food security continue more regulations for acceptable levels of aflatoxins have arisen globally; the most stringent in Europe. These regulations are important for developing countries as aflatoxin occurrence is high significantly effecting international trade and the economy. In developed countries analytical approaches have become highly sophisticated, capable of attaining results with high precision and accuracy, suitable for regulatory laboratories. Regrettably, many countries that are affected by aflatoxin contamination do not have resources for high tech HPLC and MS instrumentation and require more affordable, yet robust equally accurate alternatives that may be used by producers, processors and traders in emerging economies. It is especially important that those companies wishing to exploit the opportunities offered by lucrative but highly regulated markets in the developed world, have access to analytical methods that will ensure that their exports meet their customers quality and safety requirements.

This work evaluates the ToxiMet system as an alternative approach to UPLC–MS/MS for the detection and determination of aflatoxins relative to current European regulatory standards. Four commodities: rice grain, maize cracked and flour, peanut paste and dried distillers grains were analysed for natural aflatoxin contamination. For B1 and total aflatoxins determination the qualitative correlation, above or below the regulatory limit, was good for all commodities with the exception of the dried distillers grain samples for B1 for which no calibration existed. For B1 the quantitative R² correlations were 0.92, 0.92, 0.88 (<250 μg/kg) and 0.7 for rice, maize, peanuts and dried distillers grain samples respectively whereas for total aflatoxins the quantitative correlation was 0.92, 0.94, 0.88 and 0.91. The ToxiMet system could be used as an alternative for aflatoxin analysis for current legislation but some consideration should be given to aflatoxin M1 regulatory levels for these commodities considering the high levels detected in this study especially for maize and peanuts

The Outer Solar Systems Origins Survey. I. Design and First-quarter Discoveries

We report the discovery, tracking, and detection circumstances for 85 trans-Neptunian objects (TNOs) from the first 42 deg2 of the Outer Solar System Origins Survey. This ongoing r-band solar system survey uses the 0.9 deg2 field of view MegaPrime camera on the 3.6 m Canada–France–Hawaii Telescope. Our orbital elements for these TNOs are precise to a fractional semimajor axis uncertainty <0.1%. We achieve this precision in just two oppositions, as compared to the normal three to five oppositions, via a dense observing cadence and innovative astrometric technique. These discoveries are free of ephemeris bias, a first for large trans-Neptunian surveys. We also provide the necessary information to enable models of TNO orbital distributions to be tested against our TNO sample. We confirm the existence of a cold "kernel" of objects within the main cold classical Kuiper Belt and infer the existence of an extension of the "stirred" cold classical Kuiper Belt to at least several au beyond the 2:1 mean motion resonance with Neptune. We find that the population model of Petit et al. remains a plausible representation of the Kuiper Belt. The full survey, to be completed in 2017, will provide an exquisitely characterized sample of important resonant TNO populations, ideal for testing models of giant planet migration during the early history of the solar system.

The proof of Kontsevich's periodicity conjecture on noncommutative birational transformations

For an arbitrary associative unital ring RR, let J1J1 and J2J2 be the following noncommutative, birational, partly defined involutions on the set M3(R)M3(R) of 3×33×3 matrices over RR: J1(M)=M−1J1(M)=M−1 (the usual matrix inverse) and J2(M)jk=(Mkj)−1J2(M)jk=(Mkj)−1 (the transpose of the Hadamard inverse).

We prove the surprising conjecture by Kontsevich that (J2∘J1)3(J2∘J1)3 is the identity map modulo the DiagL×DiagRDiagL×DiagR action (D1,D2)(M)=D−11MD2(D1,D2)(M)=D1−1MD2 of pairs of invertible diagonal matrices. That is, we show that, for each MM in the domain where (J2∘J1)3(J2∘J1)3 is defined, there are invertible diagonal 3×33×3 matrices D1=D1(M)D1=D1(M) and D2=D2(M)D2=D2(M) such that (J2∘J1)3(M)=D−11MD2(J2∘J1)3(M)=D1−1MD2.

Efficient and Selectable Production of Reactive Species Using a Nanosecond Pulsed Discharge in Gas Bubbles in Liquid

A plasma gas bubble-in-liquid method for high production of selectable reactive species using a nanosecond pulse generator has been developed. The gas of choice is fed through a hollow needle in a point-to-plate bubble discharge, enabling improved selection of reactive species. The increased interface reactions, between the gas-plasma and water through bubbles, give higher productivity. H₂O₂ was the predominant species produced using Ar plasma, while predominantly  and NO₂ were generated using air plasma, in good agreement with the observed emission spectra. This method has nearly 100% selectivity for H₂O₂, with seven times higher production, and 92% selectivity for , with nearly twice the production, compared with a plasma above the water.

OFDM-based schemes for next generation wireless systems

The purpose of this study is to investigate two candidate waveforms for next generation wireless systems, filtered Orthogonal Frequency Division Multiplexing (f-OFDM) and Unified Filtered Multi-Carrier (UFMC). The evaluation is done based on the power spectral density analysis of the signal and performance measurements in synchronous and asynchronous transmission. In f-OFDM we implement a soft truncated filter with length 1/3 of OFDM symbol. In UFMC we use the Dolph-Chebyshev filter, limited to the length of zero padding (ZP). The simulation results demonstrates that both waveforms have a better spectral behaviour compared with conventional OFDM. However, the induced inter-symbol interference (ISI) caused by the filter in f-OFDM, and the inter-carrier interference (ICI) induced in UFMC due to cyclic prefix (CP) reduction , should be kept under control. In addition, in a synchronous transmission case with ideal parameters, f-OFDM and UFMC appear to have similar performance with OFDM. When carrier frequency offset (CFO) is imposed in the transmission, UFMC outperforms OFDM and f-OFDM.

Preventing encrypted traffic analysis

Many existing encrypted Internet protocols leak information through packet sizes and timing. Though seemingly innocuous, prior work has shown that such leakage can be used to recover part or all of the plaintext being encrypted. The prevalence of encrypted protocols as the underpinning of such critical services as e-commerce, remote login, and anonymity networks and the increasing feasibility of attacks on these services represent a considerable risk to communications security. Existing mechanisms for preventing traffic analysis focus on re-routing and padding. These prevention techniques have considerable resource and overhead requirements. Furthermore, padding is easily detectable and, in some cases, can introduce its own vulnerabilities. To address these shortcomings, we propose embedding real traffic in synthetically generated encrypted cover traffic. Novel to our approach is our use of realistic network protocol behavior models to generate cover traffic. The observable traffic we generate also has the benefit of being indistinguishable from other real encrypted traffic further thwarting an adversary's ability to target attacks. In this dissertation, we introduce the design of a proxy system called TrafficMimic that implements realistic cover traffic tunneling and can be used alone or integrated with the Tor anonymity system. We describe the cover traffic generation process including the subtleties of implementing a secure traffic generator. We show that TrafficMimic cover traffic can fool a complex protocol classification attack with 91% of the accuracy of real traffic. TrafficMimic cover traffic is also not detected by a binary classification attack specifically designed to detect TrafficMimic. We evaluate the performance of tunneling with independent cover traffic models and find that they are comparable, and, in some cases, more efficient than generic constant-rate defenses. We then use simulation and analytic modeling to understand the performance of cover traffic tunneling more deeply. We find that we can take measurements from real or simulated traffic with no tunneling and use them to estimate parameters for an accurate analytic model of the performance impact of cover traffic tunneling. Once validated, we use this model to better understand how delay, bandwidth, tunnel slowdown, and stability affect cover traffic tunneling. Finally, we take the insights from our simulation study and develop several biasing techniques that we can use to match the cover traffic to the real traffic while simultaneously bounding external information leakage. We study these bias methods using simulation and evaluate their security using a Bayesian inference attack. We find that we can safely improve performance with biasing while preventing both traffic analysis and defense detection attacks. We then apply these biasing methods to the real TrafficMimic implementation and evaluate it on the Internet. We find that biasing can provide 3-5x improvement in bandwidth for bulk transfers and 2.5-9.5x speedup for Web browsing over tunneling without biasing.

Host and Network Optimizations for Performance Enhancement and Energy Efficiency in Data Center Networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.