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For practical brain–machine interfaces (BMIs), electroencephalography (EEG) and near-infrared spectroscopy (NIRS) are the only current methods that are non-invasive and available in non-laboratory environments. However, the use of EEG and NIRS involves certain inherent problems. EEG signals are generally a mixture of neural activity from broad areas, some of which may not be related to the task targeted by BMI, hence impairing BMI performance. NIRS has an inherent time delay as it measures blood flow, which therefore detracts from practical real-time BMI utility. To try to improve real environment EEG–NIRS-based BMIs, we propose here a novel methodology in which the subjects' mental states are decoded from cortical currents estimated from EEG, with the help of information from NIRS. Using a Variational Bayesian Multimodal EncephaloGraphy (VBMEG) methodology, we incorporated a novel form of NIRS-based prior to capture event related desynchronization from isolated current sources on the cortical surface. Then, we applied a Bayesian logistic regression technique to decode subjects' mental states from further sparsified current sources. Applying our methodology to a spatial attention task, we found our EEG–NIRS-based decoder exhibited significant performance improvement over decoding methods based on EEG sensor signals alone. The advancement of our methodology, decoding from current sources sparsely isolated on the cortex, was also supported by neuroscientific considerations; intraparietal sulcus, a region known to be involved in spatial attention, was a key responsible region in our task. These results suggest that our methodology is not only a practical option for EEG–NIRS-based BMI applications, but also a potential tool to investigate brain activity in non-laboratory and naturalistic environments. •Portable multi-modal imaging (NIRS and EEG) was used for decoding spatial attention.•Cortical currents estimated from EEG–NIRS explained the validity of classifiers.•The accuracy was best available among non-invasive portable devices.•This research has potential to study brain activities in naturalistic conditions.

Making several simultaneous measurements with different kinds of sensors at the same location in a solution is difficult because of crosstalk between the sensors. In addition, because the conditions at different locations in plant beds differ, in situ measurements in agriculture need to be done in small localized areas. We have fabricated a multimodal sensor on a small Si chip in which a pH sensor was integrated with electrical conductivity (EC) and temperature sensors. An ISFET with a Si3N4 membrane was used for the pH sensor. For the EC sensor, the electrical conductivity between platinum electrodes was measured, and the temperature sensor was a p-n junction diode. These are some of the most important measurements required for controlling the conditions in plant beds. The multimodal sensor can be inserted into a plant bed for in situ monitoring. To confirm the absence of crosstalk between the sensors, we made simultaneous measurements of pH, EC, and temperature of a pH buffer solution in a plant bed. When the solution was diluted with hot or cold water, the real time measurements showed changes to the EC and temperature, but no change in pH. We also demonstrated that our sensor was capable of simultaneous in situ measurements in rock wool without being affected by crosstalk.

Film cooling technology is of great significance to enhance the performance of aero-engines and extend service life. With the increasing requirements for film cooling efficiency, researchers and engineers have carried out a lot of work on the precision and digital measurement of cooling holes. Based on the above, this paper outlines the importance and principles of film cooling technology and reviews the evolution of cooling holes. Also, this paper details the traditional measurement methods of the cooling hole used in current engineering scenarios with their limitations and categorizes digital measurement methods into five main types, including probing measurement technology, optical measurement technology, infrared imaging technology, computer tomography (CT) scanning technology, and composite measurement technology. The five types of methods and integrated automated measurement platforms are also analyzed. Finally, through a generalize and analysis of cooling hole measurement methods, this paper points out technical challenges and future trends, providing a reference and guidance for forward researches.

This study presents a photonic integrated optical sensor based on a dual-polarization microring resonator with angular gratings on a silicon-on-insulator (SOI) waveguide, enabling simultaneous and precise refractive index (RI) and temperature measurements. Due to the distinct energy distributions for transverse electric (TE) and transverse magnetic (TM) modes in SOI waveguides, these modes show distinct sensitivity responses to the variation in ambient RI and temperature. Simultaneous measurements of both temperature and RI are enabled by exciting both these transverse modes in the microring resonator structure. Furthermore, incorporating angular gratings into the microring resonator’s inner sidewall extends the temperature measurement range by mitigating free spectral range limitations. This work presents a novel approach to dual-polarization microring resonators with angular gratings, offering an enhanced temperature measurement range and detection limit in optical sensing applications requiring an extended temperature range. The proposed structure is able to yield a simulated temperature measurement range of approximately 35 nm with a detection limit as low as 2.99×10−5. The achieved temperature sensitivity is 334 pm/°C and RI sensitivity is 13.33 nm/RIU for the TE0 mode, while the TM0 mode exhibits a temperature sensitivity of 260 pm/°C and an RI sensitivity of 76.66 nm/RIU.

In this research, we proposed and experimentally verified a compact all-fiber sensor that can measure refractive index (RI) and temperature simultaneously. Two segments of hollow-core fiber (HCF) are connected to the two ends of the four-core fiber (FCF) as a beam splitter and a coupler, and then spliced with two sections of single-mode fibers (lead-in and lead-out SMF), respectively. The two hollow-core fibers can excite the higher-order modes of the four-core fiber and recouple the core modes and higher-order modes into the outgoing single-mode fiber, thereby forming inter-mode interference. The different response sensitivities of two interference dips to RI and temperature manifest that the proposed structure can achieve simultaneous measurement. From the experimental results, it can be seen that the maximum sensitivity of the sensor to RI and temperature is 275.30 nm/RIU and 94.4 pm/°C, respectively. When the wavelength resolution is 0.02 nm, the RI and temperature resolutions of the sensor are 7.74 × 10−5 RIU and 0.335 °C. The proposed dual-parameter optical sensor has the advantages of high sensitivities, good repeatability, simple fabrication, and structure. In addition, it has potential application value in multi-parameter simultaneous measurement.

To ensure personnel safety and prevent serious accidents, it is crucial to monitor parameters such as temperature, pressure, and gas composition concentrations in confined spaces. This study proposes a multi-parameter simultaneous inversion algorithm based on tunable diode laser absorption spectroscopy (TDLAS). The algorithm integrates the Levenberg–Marquardt (L-M) fitting method, single-line thermometry and manometry methods, spectral separation, and alternating iteration techniques, with an adaptive feedback mechanism adding to enhance convergence stability. Through this approach, simultaneous inversion of H2O, CO2, CO, and O2 concentrations, temperature, and pressure was successfully achieved. Simulation results demonstrated that the measurement accuracy meets practical requirements. This study provides an effective monitoring method for multi-parameter detection in confined spaces within conventional environments and lays a foundation for expanding the application scope of TDLAS technology.

Near-infrared spectroscopy (NIRS) is commonly used for studying human brain function. However, several studies have shown that superficial hemodynamic changes such as skin blood flow can affect the prefrontal NIRS hemoglobin (Hb) signals. To examine the criterion-related validity of prefrontal NIRS-Hb signals, we focused on the functional signals during a working memory (WM) task and investigated their similarity with blood-oxygen-level-dependent (BOLD) signals simultaneously measured by functional magnetic resonance imaging (fMRI). We also measured the skin blood flow with a laser Doppler flowmeter (LDF) at the same time to examine the effect of superficial hemodynamic changes on the NIRS-Hb signals. Correlation analysis demonstrated that temporal changes in the prefrontal NIRS-Hb signals in the activation area were significantly correlated with the BOLD signals in the gray matter rather than those in the soft tissue or the LDF signals. While care must be taken when comparing the NIRS-Hb signal with the extracranial BOLD or LDF signals, these results suggest that the NIRS-Hb signal mainly reflects hemodynamic changes in the gray matter. Moreover, the amplitudes of the task-related responses of the NIRS-Hb signals were significantly correlated with the BOLD signals in the gray matter across participants, which means participants with a stronger NIRS-Hb response showed a stronger BOLD response. These results thus provide supportive evidence that NIRS can be used to measure hemodynamic signals originating from prefrontal cortex activation. •Simultaneous NIRS, fMRI and LDF measurements to validate prefrontal NIRS signals•Significant correlation between NIRS and BOLD signals from the prefrontal cortex•Higher NIRS correlation with brain BOLD signal than with extracranial signals•Task-related signal amplitudes of NIRS were proportional to those of fMRI.•Validity of prefrontal NIRS signals was supported by comparable fMRI results.

Simultaneous measurements of transcriptomic and epigenomic profiles in the same individual cells provide an unprecedented opportunity to understand cell fates. However, effective approaches for the integrative analysis of such data are lacking. Here, we present a single-cell aggregation and integration (scAI) method to deconvolute cellular heterogeneity from parallel transcriptomic and epigenomic profiles. Through iterative learning, scAI aggregates sparse epigenomic signals in similar cells learned in an unsupervised manner, allowing coherent fusion with transcriptomic measurements. Simulation studies and applications to three real datasets demonstrate its capability of dissecting cellular heterogeneity within both transcriptomic and epigenomic layers and understanding transcriptional regulatory mechanisms.

This article presents a long-period fiber-grating sensor based on a congruent quasi-helical structure (CQH-LPFG) with the two-parameter measurement of both temperature and curvature. The CQH-LPFG sensor was manufactured using a high-frequency CO2 laser, and an innovative quasi-helical structure was introduced into the two-parameter measurement of the temperature and curvature of the optical fiber sensor with excellent results. The experiment and analysis demonstrate that the curvature sensitivities of the three resonance peaks in the 1440 nm to 1540 nm transmission spectrum were 11.88 nm/m−1, 8.05 nm/m−1, and 11.11 nm/m−1, and the curvature varied ranging from 0.156 m−1 to 0.494 m−1. The three resonance peaks showed temperature responsivities of 29.87 pm/°C, 24.65 pm/°C, and 36.85 pm/°C, respectively, and the linear fit was of excellent quality. In the case of measuring both curvature and temperature changes simultaneously, the resonant peak wavelength of the CQH-LPFG sensor was demodulated through matrix analysis, with dip A and dip C providing superior simultaneous measurements. These features make it a promising candidate for applications such as engineering machinery and the health inspection of buildings.

In this work, a simple side-polish plastic optical fiber (POF)-based surface plasmon resonance (SPR) sensor is proposed and demonstrated for simultaneous measurement of refractive index (RI) and liquid level. The effects of side-polish depths on the sensing performance were studied. The experimental results show that the SPR peak wavelength will be changed as the RI changes, and the SPR peak intensity will be changed with the liquid level variation. By monitoring the changes in peak wavelength and intensity, the RI and liquid level can be detected simultaneously. Experimental results show that an RI sensitivity of 2008.58 nm/RIU can be reached at an RI of 1.39. This sensor has the advantages of simple structure and low cost, which has a good prospect in the field of biochemical sensing.