21,754 research outputs found
nab-paclitaxel/carboplatin induction in squamous NSCLC: Longitudinal quality of life while on chemotherapy
Pathogenic mycobacteria achieve cellular persistence by inhibiting the Niemann-Pick Type C disease cellular pathway [version 1; referees: 2 approved, 2 approved with reservations]
AAVrh10 gene therapy ameliorates central and peripheral nervous system disease in canine globoid cell leukodystrophy (Krabbe disease)
A new glucocerebrosidase chaperone reduces α-synuclein and glycolipid levels in iPSC-derived dopaminergic neurons from patients with gaucher disease and parkinsonism
Clinical outcomes of EUS-guided drainage of debris-containing pancreatic pseudocysts: A large multicenter study
Quantum properties and dynamics of X states
X states are a broad class of two-qubit density matrices that generalize many
states of interest in the literature. In this work, we give a comprehensive
account of various quantum properties of these states, such as entanglement,
negativity, quantum discord and other related quantities. Moreover, we discuss
the transformations that preserve their structure both in terms of continuous
time evolution and discrete quantum processes.Comment: 13 page
Normalization of hepatic homeostasis in the Npc1nmf164 mouse model of Niemann-Pick type C disease treated with the histone deacetylase inhibitor vorinostat
Fuzzy logic control for energy saving in autonomous electric vehicles
Limited battery capacity and excessive battery dimensions have been two major limiting factors in the rapid advancement of electric vehicles. An alternative to increasing battery capacities is to use better: intelligent control techniques which save energy on-board while preserving the performance that will extend the range with the same or even smaller battery capacity and dimensions. In this paper, we present a Type-2 Fuzzy Logic Controller (Type-2 FLC) as the speed controller, acting as the Driver Model Controller (DMC) in Autonomous Electric Vehicles (AEV). The DMC is implemented using realtime control hardware and tested on a scaled down version of a back to back connected brushless DC motor setup where the actual vehicle dynamics are modelled with a Hardware-In-the-Loop (HIL) system. Using the minimization of the Integral Absolute Error (IAE) has been the control design criteria and the performance is compared against Type-1 Fuzzy Logic and Proportional Integral Derivative DMCs. Particle swarm optimization is used in the control design. Comparisons on energy consumption and maximum power demand have been carried out using HIL system for NEDC and ARTEMIS drive cycles. Experimental results show that Type-2 FLC saves energy by a substantial amount while simultaneously achieving the best IAE of the control strategies tested
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