Hough Transform Proposal and Simulations for Particle Track Recognition for LHC Phase-II Upgrade.

In the near future, LHC experiments will continue future upgrades by overcoming the technological obsolescence of the detectors and the readout capabilities. Therefore, after the conclusion of a data collection period, CERN will have to face a long shutdown to improve overall performance, by updating the experiments, and implementing more advanced technologies and infrastructures. In particular, the largest LHC experiment, i.e., ATLAS, will upgrade parts of the detector, the trigger, and the data acquisition system. In addition, the ATLAS experiment will complete the implementation of new strategies, algorithms for data handling, and transmission to the final storage apparatus. This paper presents an overview of an upgrade planned for the second half of this decade for the ATLAS experiment. In particular, we show a study of a novel pattern recognition algorithm used in the trigger system, which is a device designed to provide the information needed to select physical events from unnecessary background data. The idea is to use a well known mathematical transform, the Hough transform, as the algorithm for the detection of particle trajectories. The effectiveness of the algorithm has already been validated in the past, regardless of particle physics applications, to recognize generic shapes within images. On the contrary, here, we first propose a software emulation tool, and a subsequent hardware implementation of the Hough transform, for particle physics applications. Until now, the Hough transform has never been implemented on electronics in particle physics experiments, and since a hardware implementation would provide benefits in terms of overall Latency, we complete the studies by comparing the simulated data with a physical system implemented on a Xilinx hardware accelerator (FELIX-II card). In more detail, we have implemented a low-abstraction RTL design of the Hough transform on Xilinx UltraScale+ FPGAs as target devices for filtering applications.

Identification and molecular characterization of the high-affinity copper transporters family in Solanum lycopersicum.

Copper (Cu) plays a key role as cofactor in the plant proteins participating in essential cellular processes, such as electron transport and free radical scavenging. Despite high-affinity Cu transporters (COPTs) being key participants in Cu homeostasis maintenance, very little is known about COPTs in tomato (Solanum lycopersicum) even though it is the most consumed fruit worldwide and this crop is susceptible to suboptimal Cu conditions. In this study, a six-member family of COPT (SlCOPT1-6) was identified and characterized. SlCOPTs have a conserved architecture consisting of three transmembrane domains and ß-strains. However, the presence of essential methionine residues, a methionine-enriched amino-terminal region, an Mx3Mx12Gx3G Cu-binding motif and a cysteine rich carboxy-terminal region, all required for their functionality, is more variable among members. Accordingly, functional complementation assays in yeast indicate that SlCOPT1 and SlCOPT2 are able to transport Cu inside the cell, while SlCOPT3 and SlCOPT5 are only partially functional. In addition, protein interaction network analyses reveal the connection between SlCOPTs and Cu PIB-type ATPases, other metal transporters, and proteins related to the peroxisome. Gene expression analyses uncover organ-dependency, fruit vasculature tissue specialization and ripening-dependent gene expression profiles, as well as different response to Cu deficiency or toxicity in an organ-dependent manner.

Recent developments in automatic scoring of rodent sleep.

Sleep research carried out on rat and mouse model led to the publication of more than 5000 papers in the last 15 years, of which more than 500 in 2014. Wake-sleep scoring represents a crucial step of the work performed in pre- clinical sleep laboratories; it is a time consuming task and a potential source of errors affecting research outcomes. Several algorithms have been developed to perform automatic sleep scoring. Automatic scoring can accelerate the work of researchers substantially. Moreover, the use of sleep scoring algorithms facilitates the direct comparison of the results produced in different laboratories, with clear advantages from the viewpoint of the advancement of science and reduction of the number of animals used for research. The intent of this review is to provide the readers with the last developments in scoring in rodent sleep and to stress about the need of a cross-lab and cross-species validated algorithm.

SCOPRISM: a new algorithm for automatic sleep scoring in mice.

BACKGROUND: Scoring of wake-sleep states by trained investigators is a time-consuming task in many sleep experiments. We aimed to validate SCOPRISM, a new open-source algorithm for sleep scoring based on automatic graphical clustering of epoch distribution. METHODS: We recorded sleep and blood pressure signals of 36 orexin-deficient, 7 leptin knock-out, and 43 wild-type control mice in the PRISM laboratory. Additional groups of mice (n=14) and rats (n=6) recorded in independent labs were used to validate the algorithm across laboratories. RESULTS: The overall accuracy, specificity and sensitivity values of SCOPRISM (97%, 95%, and 94%, respectively) on PRISM lab data were similar to those calculated between human scorers (98%, 98%, and 94%, respectively). Using SCOPRISM, we replicated the main sleep and sleep-dependent cardiovascular findings of our previous studies. Finally, the cross-laboratory analyses showed that the SCOPRISM algorithm performed well on mouse and rat data. COMPARISON WITH EXISTING METHODS: SCOPRISM performed similarly or even better than recently reported algorithms. SCOPRISM is a very simple algorithm, extensively (cross)validated and with the possibility to evaluate its efficacy following a quick and easy visual flow chart. CONCLUSIONS: We validated SCOPRISM, a new, automated and open-source algorithm for sleep scoring on a large population of mice, including different mutant strains and on subgroups of mice and rats recorded by independent labs. This algorithm should help accelerate basic research on sleep and integrative physiology in rodents.