4-Tosyl-1-oxa-4-aza­spiro­[4.5]deca-6,9-dien-8-one

In the mol­ecule of the title compound, C15H15NO4S, the two six-membered rings are almost parallel to each other [dihedral angle = 1.87 (9)°] and perpendicular to the mean plane through the five-membered ring [dihedral angles of 89.98 (10) and 89.04 (10)°]. The crystal structure is stabilized by inter­molecular C—H⋯O hydrogen-bonding inter­actions

Validity of the “Streitberger” Needle in a Chinese Population with Acupuncture: A Randomized, Single-Blinded, and Crossover Pilot Study

We studied the validity of a “Streitberger” needle as a valid approach in a Chinese population with experience of acupuncture. Volunteers were recruited from students of the School of Acupuncture and Moxibustion, Guangzhou University of Chinese Medicine. Sixty students receiving education in acupuncture theory and experience in practical acupuncture were tested in study determining whether needling with the placebo needle felt any different from conventional acupuncture. Outcomes included measures of penetration sensation, VAS ratings, and Deqi sensation questionnaire. As a result, needle penetration, VAS ratings for either needle and Deqi sensation were not significantly different between two kinds of needles. Our findings show that the use of “Streitberger” needle is credible in a Chinese population with acupuncture experience

Modeling and performance analysis of marine DTN networks with Nodes-cluster in an ad hoc sub-net

The marine communication environment is complex and changeable, and the sea wireless infrastructure is few. The delay tolerant network is proposed and applied in ocean environment. We use the ships to store, carry and forward the messages, so as to solve the problem that the communication links are broken frequently and the message cannot be transmitted due to the movement of the nodes. Under the environment of MATLAB, the random motion trajectory of a fishing vessel in the South China Sea is modeled and simulated. A mobile Ad hoc network is formed between ship and ship, and the base station of the land mobile communication network is connected with the marine radio transmitting point through optical fiber. Data is generated according to Poisson distribution in a heterogeneous network at sea and the data transmission uses the flooding mechanism. Taking into account the limited capacity of the wireless transmission point of the sea, we introduced a forwarding-time-limited mechanism. The performance of it is analyzed in the delayed network at sea, and the effects of the survival time, the number of fishing vessels and the coverage of the wireless network on data delivery are compared. The simulation results show that increasing the survival time of the data and the coverage of the wireless network can improve the data delivery ratio, reduce the network transmission delay, and improve the performance of the maritime wireless communication network

Multilevel leapfrogging initialization for quantum approximate optimization algorithm

The quantum approximate optimization algorithm (QAOA) is a prospective hybrid quantum-classical algorithm widely used to solve combinatorial optimization problems. However, the external parameter optimization required in QAOA tends to consume extensive resources to find the optimal parameters of the parameterized quantum circuit, which may be the bottleneck of QAOA. To meet this challenge, we first propose multilevel leapfrogging learning (M-Leap) that can be extended to quantum reinforcement learning, quantum circuit design, and other domains. M-Leap incrementally increases the circuit depth during optimization and predicts the initial parameters at level $p+r$ ($r>1$) based on the optimized parameters at level $p$, cutting down the optimization rounds. Then, we propose a multilevel leapfrogging-interpolation strategy (MLI) for initializing optimizations by combining M-Leap with the interpolation technique. We benchmark its performance on the Maxcut problem. Compared with the Interpolation-based strategy (INTERP), MLI cuts down at least half the number of rounds of optimization for the classical outer learning loop. Remarkably, the simulation results demonstrate that the running time of MLI is 1/3 of INTERP when MLI gets quasi-optimal solutions. In addition, we present the greedy-MLI strategy by introducing multi-start, which is an extension of MLI. The simulation results show that greedy-MLI can get a higher average performance than the remaining two methods. With their efficiency to find the quasi-optima in a fraction of costs, our methods may shed light in other quantum algorithms