Non-Autoregressive Machine Translation with Auxiliary Regularization

As a new neural machine translation approach, Non-Autoregressive machine Translation (NAT) has attracted attention recently due to its high efficiency in inference. However, the high efficiency has come at the cost of not capturing the sequential dependency on the target side of translation, which causes NAT to suffer from two kinds of translation errors: 1) repeated translations (due to indistinguishable adjacent decoder hidden states), and 2) incomplete translations (due to incomplete transfer of source side information via the decoder hidden states). In this paper, we propose to address these two problems by improving the quality of decoder hidden representations via two auxiliary regularization terms in the training process of an NAT model. First, to make the hidden states more distinguishable, we regularize the similarity between consecutive hidden states based on the corresponding target tokens. Second, to force the hidden states to contain all the information in the source sentence, we leverage the dual nature of translation tasks (e.g., English to German and German to English) and minimize a backward reconstruction error to ensure that the hidden states of the NAT decoder are able to recover the source side sentence. Extensive experiments conducted on several benchmark datasets show that both regularization strategies are effective and can alleviate the issues of repeated translations and incomplete translations in NAT models. The accuracy of NAT models is therefore improved significantly over the state-of-the-art NAT models with even better efficiency for inference.Comment: AAAI 201

A Stabilized, Intrinsically Safe, 10% Efficient, Solar-Driven Water-Splitting Cell Incorporating Earth-Abundant Electrocatalysts with Steady-State pH Gradients and Product Separation Enabled by a Bipolar Membrane

An efficient, stable, and intrinsically safe solar water-splitting device is demonstrated using a III–V tandem junction photoanode, an acid-stable, earth-abundant hydrogen evolution catalyst, and a bipolar membrane. The integrated photoelectrochemical cell operates under a steady-state pH gradient and achieves ≈10% solar-to-hydrogen conversion efficiency, >100 h of stability in a large (>1 cm^2) photoactive area in relation to most previous reports

Scanning droplet cell for high throughput electrochemical and photoelectrochemical measurements

High throughput electrochemical techniques are widely applied in material discovery and optimization. For many applications, the most desirable electrochemical characterization requires a three-electrode cell under potentiostat control. In high throughput screening, a material library is explored by either employing an array of such cells, or rastering a single cell over the library. To attain this latter capability with unprecedented throughput, we have developed a highly integrated, compact scanning droplet cell that is optimized for rapid electrochemical and photoeletrochemical measurements. Using this cell, we screened a quaternary oxide library as (photo)electrocatalysts for the oxygen evolution (water splitting) reaction. High quality electrochemical measurements were carried out and key electrocatalytic properties were identified for each of 5456 samples with a throughput of 4 s per sample

Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot.

A rehabilitation robot plays an important role in relieving the therapists' burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles' good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM's nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions

Solar-Driven Reduction of 1 atm of CO_2 to Formate at 10% Energy-Conversion Efficiency by Use of a TiO_2-Protected III–V Tandem Photoanode in Conjunction with a Bipolar Membrane and a Pd/C Cathode

A solar-driven CO_2 reduction (CO_2R) cell was constructed, consisting of a tandem GaAs/InGaP/TiO_2/Ni photoanode in 1.0 M KOH(aq) (pH = 13.7) to facilitate the oxygen-evolution reaction (OER), a Pd/C nanoparticle-coated Ti mesh cathode in 2.8 M KHCO_3(aq) (pH = 8.0) to perform the CO_2R reaction, and a bipolar membrane to allow for steady-state operation of the catholyte and anolyte at different bulk pH values. At the operational current density of 8.5 mA cm^(–2), in 2.8 M KHCO_3(aq), the cathode exhibited 94% Faradaic efficiency for the reduction of 1 atm of CO_2(g) to formate. The anode exhibited a 320 ± 7 mV overpotential for the OER in 1.0 M KOH(aq), and the bipolar membrane exhibited ∼480 mV voltage loss with minimal product crossovers and >90 and >95% selectivity for protons and hydroxide ions, respectively. The bipolar membrane facilitated coupling between two electrodes and electrolytes, one for the CO_2R reaction and one for the OER, that typically operate at mutually different pH values and produced a lower total cell overvoltage than known single-electrolyte CO_2R systems while exhibiting ∼10% solar-to-fuels energy-conversion efficiency

A Monolithically Integrated, Intrinsically Safe, 10% Efficient, Solar-Driven Water-Splitting System Based on Active, Stable Earth-Abundant Electrocatalysts in Conjunction with Tandem III-V Light Absorbers Protected by Amorphous TiO_2 Films

A monolithically integrated device consisting of a tandem-junction GaAs/InGaP photoanode coated by an amorphous TiO_2 stabilization layer, in conjunction with Ni-based, earth-abundant active electrocatalysts for the hydrogen-evolution and oxygen-evolution reactions, was used to effect unassisted, solar-driven water splitting in 1.0 M KOH(aq). When connected to a Ni-Mo-coated counterelectrode in a two-electrode cell configuration, the TiO_2-protected III-V tandem device exhibited a solar-to-hydrogen conversion efficiency, η_(STH), of 10.5% under 1 sun illumination, with stable performance for > 40 h of continuous operation at an efficiency of η_(STH) >10%. The protected tandem device also formed the basis for a monolithically integrated, intrinsically safe solar-hydrogen prototype system (1 cm^2) driven by a NiMo/GaAs/InGaP/TiO_2/Ni structure. The intrinsically safe system exhibited a hydrogen production rate of 0.81 μL s^(-1) and a solar-to-hydrogen conversion efficiency of 8.6% under 1 sun illumination in 1.0 M KOH(aq), with minimal product gas crossover while allowing for beneficial collection of separate streams of H_2(g) and O_2(g)

MS-NHHO: A Swarm Intelligence Optimization Algorithm Incorporating Cognitive Science for Malicious Traffic Detection

The diversification of attacks jeopardizes cyberspace's normal operation. This paper proposes a new Harris Hawks Optimization Based on Multiple Strategies (MS-NHHO), inspired by humans' limited cognitive load, collective decision-making, and dynamic learning mechanisms for processing complex information. This paper utilizes the elite chaos reverse learning strategy to improve the algorithm's convergence speed and population diversity. Then, the dynamic adaptive weights are introduced into the escape energy decline mechanism to improve the algorithm's global exploration and local exploitation ability. Finally, the Gaussian random walk strategy enhances the algorithm's anti-stagnation ability. The experimental results confirm the usefulness of the three optimization strategies. Meanwhile, MS-NHHO exhibits satisfactory performance in terms of computational cost, detection performance, and efficiency in several scenarios

A Comprehensive Review of Chinese Herbal Formulations for the Treatment of Atopic Dermatitis

Atopic dermatitis (AD) is a common, chronic, and relapsing inflammatory skin disorder characterized by skin irritation and intense pruritus, which significantly impairs the quality of patients’ life. Traditional Chinese medicine (TCM) has a long history in the treatment of atopic dermatitis, especially in preventing disease recurrence, minimizing adverse reactions and alleviating disease burden. In this paper, we reviewed the clinical anti-AD efficacy of Chinese herbal formulae from the perspective of AD mechanisms. Following assessment indicators were used: SCORing Atopic Dermatitis (SCORAD), erythema intensity, skin quality of life index (DLQI), pruritus intensity and frequency, transdermal dehydration (TEWL), and AD-mediated chemokine expression levels as index formulae. We also summarize the pharmacological effects of single herbs in the formulae. In conclusion, TCM has significant clinical efficacy for patients of all ages, both as a standalone treatment and in combination with other therapies