Lifeboat Foundation

The Driving Training Based Optimization (DTBO) algorithm, proposed by Mohammad Dehghani, is one of the novel metaheuristic algorithms which appeared in 2022⁸⁰. This algorithm is founded on the principle of learning to drive, which unfolds in three phases: selecting an instructor from the learners, receiving instructions from the instructor on driving techniques, and practicing newly learned techniques from the learner to enhance one’s driving abilities^81,82. In this work, DTBO algorithm is used, due to its effectiveness, which was confirmed by a comparative study⁸³ with other algorithms, including particle swarm optimization⁸⁴, Gravitational Search Algorithm (GSA)⁸⁵, teaching learning-based optimization, Gray Wolf Optimization (GWO)⁸⁶, Whale Optimization Algorithm (WOA)⁸⁷, and Reptile Search Algorithm (RSA)⁸⁸. The comparative study has been done using various kinds of benchmark functions, such as constrained, nonlinear and non-convex functions.

Lyapunov-based Model Predictive Control (LMPC) is a control approach integrating Lyapunov function as constraint in the optimization problem of MPC^89,90. This technique characterizes the region of the closed-loop stability, which makes it possible to define the operating conditions that maintain the system stability^91,92. Since its appearance, the LMPC method has been utilized extensively for controlling a various nonlinear systems, such as robotic systems⁹³, electrical systems⁹⁴, chemical processes⁹⁵, and wind power generation systems⁹⁰. In contrast to the LMPC, both the regular MPC and the NMPC lack explicit stability restrictions and can’t combine stability guarantees with interpretability, even with their increased flexibility.

The proposed method, named Lyapunov-based neural network model predictive control using metaheuristic optimization approach (LNNMPC-MOA), includes Lyapunov-based constraint in the optimization problem of the neural network model predictive control (NNMPC), which is solved by the DTBO algorithm. The suggested controller consists of two parts: the first is responsible for calculating predictions using a neural network model of the feedforward type, and the second is responsible to resolve the constrained nonlinear optimization problem using the DTBO algorithm. This technique is suggested to solve the nonlinear and non-convex optimization problem of the conventional NMPC, ensure on-line optimization in reasonable time thanks to their easy implementation and guaranty the stability using the Lyapunov function-based constraint. The efficiency of the proposed controller regarding to the accuracy, quickness and robustness is assessed by taking into account the speed control of a three-phase induction motor, and its stability is mathematically ensured using the Lyapunov function-based constraint. The acquired results are compared to those of NNMPC based on DTBO algorithm (NNMPC-DTBO), NNMPC using PSO algorithm (NNMPC-PSO), Fuzzy Logic controller optimized by TLBO (FLC-TLBO) and optimized PID controller using PSO algorithm (PID-PSO)⁹⁵.

In a major step for the international Deep Underground Neutrino Experiment (DUNE), scientists have detected the first neutrinos using a DUNE prototype particle detector at the U.S. Department of Energy’s Fermi National Accelerator Laboratory (Fermilab).

In the famous double-slit experiment, an interference pattern consisting of dark and bright bands emerges when a beam of light hits two narrow slits. The same effect has also been seen with particles such as electrons and protons, demonstrating the wave nature of propagating particles in quantum mechanics.

Microplastics are a global problem: they end up in rivers and oceans, they accumulate in living organisms and disrupt entire ecosystems. How tiny particles behave in a current is difficult to describe scientifically, especially in the case of thin fibers, which make up more than half of microplastic contamination in marine life-forms. In turbulent currents, it is almost impossible to predict their movement.

Since the first demonstration of the laser in the 1960s, laser spectroscopy has become an essential tool for studying the detailed structures and dynamics of atoms and molecules. Advances in laser technology have further enhanced its capabilities. There are two main types of laser spectroscopy: frequency comb-based laser spectroscopy and tunable continuous-wave (CW) laser spectroscopy.

In a major step for the international Deep Underground Neutrino Experiment, scientists have detected the first neutrinos using a DUNE prototype particle detector at the US Department of Energy’s Fermi National Accelerator Laboratory.

The prototype of a novel particle detection system for the international Deep Underground Neutrino Experiment successfully recorded its first accelerator neutrinos.

With the detection of a long-predicted “neutrino fog,” the search for particles of dark matter has entered a new age of both possibility and peril.

By Saima S. Iqbal

The decades-long search for dark matter could ultimately end in an impasse.

Helen Edwards was a particle physicist who led the design and construction of the Tevatron, a machine built to probe deeper into the atom than anyone had gone before.

Some experts believe that the future of fusion in the U.S. may be found in compact, spherical fusion vessels. A smaller tokamak is seen as a potentially more economical solution for fusion energy. The challenge lies in fitting all necessary components into a limited space. Recent research indicates that removing one key component used to heat the plasma could create the additional space required.

Scientists at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), the private company Tokamak Energy, and Kyushu University in Japan have proposed a design for a compact, spherical fusion pilot plant that heats the plasma using only microwaves. Typically, spherical tokamaks also use a massive coil of copper wire called a solenoid, located near the center of the vessel, to heat the plasma. Neutral beam injection, which involves applying beams of uncharged particles to the plasma, is often used as well. But much like a tiny kitchen is easier to design if it has fewer appliances, it would be simpler and more economical to make a compact tokamak if it has fewer heating systems.

The new approach eliminates ohmic heating, which is the same heating that happens in a toaster and is standard in tokamaks. “A compact, spherical tokamak plasma looks like a cored apple with a relatively small core, so one does not have the space for an ohmic heating coil,” said Masayuki Ono, a principal research physicist at PPPL and lead author of the paper detailing the new research. “If we don’t have to include an ohmic heating coil, we can probably design a machine that is easier and cheaper to build.”