Polarization Analysis of p̄ Produced in pA Collisions

A quite simple procedure for the generation of a polarized antiproton beam could be worked out if antiprotons are produced with some polarization. In order to investigate this possibility measurements of the polarization of produced antiprotons have been started at a CERN/PS test beam. The polarization will be determined from the asymmetry of the elastic antiproton scattering at a liquid hydrogen target in the CNI region for which the analyzing power is well known. The data are under analysis and an additional measurement is done in 2018. Details on the experiment and the ongoing data analysis will be given

Acoustic Diagnostics of Electrical Origin Fault Modes with Readily Available Consumer-Grade Sensors

Acoustic diagnostics, traditionally associated with mechanical fault modes, can potentially solve a wider range of monitoring applications. Typically, fault modes are induced purposefully by the researcher through physical component damage whilst the system is shutdown. This paper presents low-cost real-time fault diagnostics of a previously unreported acute electrical origin fault that manifests sporadically during system operation with no triggering intervention. A suitability study into acoustic measurements from readily available consumer-grade sensors for low-cost real-time diagnostics of audible faults, and a brief overview of the theory and configuration of the wavelet packet transform (including optimal wavelet selection methods) and empirical mode decomposition processing algorithms is also included. The example electrical origin fault studied here is an unpredictable current instability arising with the PWM-controller of a BrushLess DC motor. Experimental trials positively detect 99.9 % of the 1160 resultant high-bandwidth torque transients using acoustic measurements from a USB microphone and a smartphone. While the use of acoustic techniques for detecting emerging electrical origin faults remains largely unexplored, the techniques demonstrated here can be readily adopted for the prevention of catastrophic failure of drive and power electronic components

Using jasmonates and salicylates to reduce losses within the fruit supply chain

The fresh produce industry is constantly growing, due to increasing consumer demand. The shelf-life of some fruit, however, is relatively short, limited by microbial contamination or visual, textural and nutritional quality loss. Thus, techniques for reducing undesired microbial contamination, spoilage and decay, as well as maintaining product’s visual, textural and nutritional quality are in high demand at all steps within the supply chain. The postharvest use of signalling molecules, i.e. jasmonates and salicylates seems to have unexplored potential. The focus of this review is on the effects of treatment with jasmonates and salicylates on the fresh produce quality, defined by decay incidence and severity, chilling injury, maintenance of texture, visual quality, taste and aroma, and nutritional content. Postharvest treatments with jasmonates and salicylates have the ability to reduce decay by increasing fruit resistance to diseases and reducing chilling injury in numerous products. These treatments also possess the ability to improve other quality characteristics, i.e. appearance, texture maintenance and nutritional content. Furthermore, they can easily be combined with other treatments, e.g. heat treatment, ultrasound treatment. A good understanding of all the benefits and limitations related to the postharvest use of jasmonates and salicylates is needed, and relevant information has been reviewed in this paper

Back to Massey: Impressively fast, scalable and tight security evaluation tools

None of the existing rank estimation algorithms can scale to large cryptographic keys, such as 4096-bit (512 bytes) RSA keys. In this paper, we present the first solution to estimate the guessing entropy of arbitrarily large keys, based on mathematical bounds, resulting in the fastest and most scalable security evaluation tool to date. Our bounds can be computed within a fraction of a second, with no memory overhead, and provide a margin of only a few bits for a full 128-bit AES key

Poly-Logarithmic Side Channel Rank Estimation via Exponential Sampling

Rank estimation is an important tool for a side-channel evaluations laboratories. It allows estimating the remaining security after an attack has been performed, quantified as the time complexity and the memory consumption required to brute force the key given the leakages as probability distributions over $d$ subkeys (usually key bytes). These estimations are particularly useful where the key is not reachable with exhaustive search. We propose ESrank, the first rank estimation algorithm that enjoys provable poly-logarithmic time- and space-complexity, which also achieves excellent practical performance. Our main idea is to use exponential sampling to drastically reduce the algorithm\u27s complexity. Importantly, ESrank is simple to build from scratch, and requires no algorithmic tools beyond a sorting function. After rigorously bounding the accuracy, time and space complexities, we evaluated the performance of ESrank on a real SCA data corpus, and compared it to the currently-best histogram-based algorithm. We show that ESrank gives excellent rank estimation (with roughly a 1-bit margin between lower and upper bounds), with a performance that is on-par with the Histogram algorithm: a run-time of under 1 second on a standard laptop using 6.5 MB RAM