40 Gbit/s Transparent Network Based on Wavelength-Selective Optical Cross Connect

This paper discusses a 40-Gbit/s transparent optical network focusing on the optical transport performance. We show 1200-km transmission with two WSOXC' sspaced by 400 km. In addition, network control issues are briefly addressed.

Transparent micropatterned conductive films based on highlyordered nanowire network

Transparent conductive films that are based on nanowire networks are essential to construct flexible,wearable,and even stretchable electronics.However,large-scale precise micropatterning,especially with regard to the controllability of the organizing orientation of nanowires,is a critical challenge.Herein,we proposed a liquid film rupture self-assembly approach for manufacturing transparent conductive films with microstructure arrays based on a highly ordered nanowire network.The large-scale microstructure conductive films were fabricated through air-liquid interface self-assembly and liquid film rupture self-assembly.Six typical micropattern morphologies,including square,hexagon,circle,serpentine,etc.,were prepared to reveal the universal applicability of the proposed approach.The homogeneity and controllability of this approach were verified for multiple assemblies.With the assembly cycles increasing,the optical transmittance decreases slightly.In addition,theoretical model analysis is carried out,and the analytical formula of the speed of the film moving with the surface tension and the density of the liquid film is presented.Finally,the feasibility of this approach for piezoresistive strain sensors is verified.This fabrication approach demonstrated a cost-effective and efficient method for precisely arranging nanowires,which is useful in transparent and wearable applications.

Performance Monitoring in Transparent Reconfigurable WDM Networks

This paper classifies and surveys different approaches proposed for performance monitoring, in particular the optical signal-to-noise ratio (OSNR) monitoring, in transparent reconfigurable WDM networks. Some considerations for future monitoring schemes are discussed.

All-optical integrated support for multicast and burst amplification in transparent optical network

A novel scalable and integrated design that supports optical multicast and burst amplification is proposed and demonstrated experimentally. The powers of incoming signals can be tuned to optimize the results of burst amplification and replication. Experimental results also show that erbium-doped optical Fiber amplication （EDFA） transients can be suppressed to an equally low level regardless of the burst parameters. Extended structure designs are further proposed to satisfy the need of mass replication of multicast signals.

Transparent open-box learning network and artificial neural network predictions of bubble-point pressure compared

The transparent open box(TOB)learning network algorithm offers an alternative approach to the lack of transparency provided by most machine-learning algorithms.It provides the exact calculations and relationships among the underlying input variables of the datasets to which it is applied.It also has the capability to achieve credible and auditable levels of prediction accuracy to complex,non-linear datasets,typical of those encountered in the oil and gas sector,highlighting the potential for underfitting and overfitting.The algorithm is applied here to predict bubble-point pressure from a published PVT dataset of 166 data records involving four easy-tomeasure variables(reservoir temperature,gas-oil ratio,oil gravity,gas density relative to air)with uneven,and in parts,sparse data coverage.The TOB network demonstrates high-prediction accuracy for this complex system,although it predictions applied to the full dataset are outperformed by an artificial neural network(ANN).However,the performance of the TOB algorithm reveals the risk of overfitting in the sparse areas of the dataset and achieves a prediction performance that matches the ANN algorithm where the underlying data population is adequate.The high levels of transparency and its inhibitions to overfitting enable the TOB learning network to provide complementary information about the underlying dataset to that provided by traditional machine learning algorithms.This makes them suitable for application in parallel with neural-network algorithms,to overcome their black-box tendencies,and for benchmarking the prediction performance of other machine learning algorithms.

Two-dimensional gain cross-grating based on spatial modulation of active Raman gain

Based on the spatial modulation of active Raman gain,a two-dimensional gain cross-grating is theoretically proposed.As the probe field propagates along the z direction and passes through the intersectant region of the two orthogonal standingwave fields in the x-y plane,it can be effectively diffracted into the high-order directions,and the zero-order diffraction intensity is amplified at the same time.In comparison with the two-dimensional electromagnetically induced cross-grating based on electromagnetically induced transparency,the two-dimensional gain cross-grating has much higher diffraction intensities in the first-order and the high-order directions.Hence,it is more suitable to be utilized as all-optical switching and routing in optical networking and communication.