Accurately detect the residues of organophosphate pesticides (OPs) in food and environment is critical to our daily lives. In this study, we developed a novel acetylcholinesterase (AChE) biosensor based on Au-Tb alloy nanospheres (NSs) for rapid and sensitive detection of OPs for the first time. Au-Tb alloy NSs that with good conductivity and biocompatibility were produced with a mild hydrothermal. SR717 Under optimal conditions, the AChE biosensor was obtained by a simple assembly process, with a big linear range (10-13-10-7M) and the limit of detection was 2.51 × 10-14M for the determination of methyl parathion. Moreover, the determination of methyl parathion with the prepared biosensor presented a high sensitivity, outstanding repeatability and superior stability compared with other reported biosensors. Through the determination of tap water and Yanming lake samples, it was proved that the modified biosensor with satisfactory recoveries (96.76%-108.6%), and are realizable in the determination of OPs in real samples.Legged locomotion enables robotic platforms to traverse on rough terrain, which is quite challenging for other locomotion types, such as in wheeled and tracked systems. However, this benefit-moving robustly on rough terrain-comes with an inherent drawback due to the higher cost of transport in legged robots. The ultimate need for energy efficiency motivated the utilization of passive dynamics in legged locomotion. Nevertheless, a handicap in passive dynamic walking is the fragile basin of attraction that limits the locomotion capabilities of such systems. There have been various extensions to overcome such limitations by incorporating additional actuators and active control approaches at the expense of compromising the benefits of passivity. Here, we present a novel actuation and control framework, enabling efficient and sustained bipedal locomotion on significantly rough terrain. The proposed approach reinforces the passive dynamics by intermittent active feedback control within a bio-inspired compliant ankle actuation framework. Specifically, we use once-per-step energy regulation to adjust the spring precompression of the compliant ankle based on the liftoff instants-when the toe liftoffs from the ground-of the locomotion. Our results show that the proposed approach achieves highly efficient (with a cost of transport of 0.086) sustained locomotion on rough terrain, withstanding height variations up to 15% of the leg length. We provide theoretical and numerical analysis to demonstrate the performance of our approach, including systematic comparisons with the recent and state-of-the-art techniques in the literature.Colorful indoor organic photovoltaics (OPVs) have attracted considerable attention in recent years for their autonomous function in internet-of-things (IoT) devices. In this study, a solution-processed TiO2layer in a metal-oxide-metal (MOM) color filter electrode is used for light energy recycling in P3HTICBA-based indoor OPVs. The MOM electrode allows for tuning of the optical cavity mode to maximize photocurrent production by modulating the thickness of the TiO2layer in the sandwich structure. This approach preserves the OPVs' optoelectronic properties without damaging the photoactive layer and enables them to display a suitable range of vivid colors. The optimized MOM-OPVs demonstrated an excellent power conversion efficiency (PCE) of 8.8% ± 0.2%, which is approximately 20% higher than that of reference opaque OPVs under 1000 lx light emitting diode illumination. This can be attributed to the high photocurrent density due to the nonresonant light reflected from metals into the photoactive layer. Additionally, the proposed MOM-OPVs exhibited high external quantum efficiency and large parasitic shunt resistances, leading to improved fill factor and PCE values. Thus, the study's MOM electrode provides excellent feasibility for realizing colorful and efficient indoor OPVs for IoT applications.Plasmonic nanostructures, of which gold nanoparticles are the most elementary example, owe their unique properties to localized surface plasmons (LSP), the modes of free electron oscillation. LSP alter significantly electromagnetic field in the nanostructure neighborhood (i.e., near-field), which can modify the electric dipole transition rates in organic emitters. This study aims at investigating the influence of Au@SiO2core-shell nanoparticles on the photophysics of porphyrins covalently attached to the nanoparticles surface. Guided by theoretical predictions, three sets of gold nanoparticles of different sizes were coated with a silica layer of similar thickness. The outer silica surface was functionalized with either free-basemeso-tetraphenylporphyrin or its zinc complex. Absorption and emission bands of porphyrin overlap in energy with a gold nanoparticle LSP resonance that provides the field enhancement. Silica separates the emitters from the gold surface, while the gold core size tunes the energy of the LSP resonance. The signatures of weak-coupling regime have been observed. Apart from modified emission profiles and shortened S1lifetimes, Q band part intensity of the excitation spectra significantly increased with respect to the Soret band. The results were explained using classical transfer matrix simulations and electronic states kinetics, taking into account the photophysical properties of each chromophore. The calculations could reasonably well predict and explain the experimental outcomes. The discrepancies between the two were discussed.Objective. There is emerging evidence that analysing the entropy and complexity of biomedical signals can detect underlying changes in physiology which may be reflective of disease pathology. This approach can be used even when only short recordings of biomedical signals are available. This study aimed to determine whether entropy and complexity measures can detect differences between subjects with Parkinsons disease and healthy controls (HCs).Approach. A method based on a diagram of entropy versus complexity, named complexity-entropy plane, was used to re-analyse a dataset of cerebral haemodynamic signals from subjects with Parkinsons disease and HCs obtained under poikilocapnic conditions. A probability distribution for a set of ordinal patterns, designed to capture regularities in a time series, was computed from each signal under analysis. Four types of entropy and ten types of complexity measures were estimated from these distributions. Mean values of entropy and complexity were compared and their classification power was assessed by evaluating the best linear separator on the corresponding complexity-entropy planes.