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A large amount of Cr2O72− and glyphosate (GLYP) discharge cause serious water pollution. In this paper, two new MOFs (Zn‐DPIA and Cd‐DPIA) were synthesized, which have excellent selectivity and sensitivity in the detection of Cr2O72− and GLYP. The detection limits (LODs) of Zn‐DPIA sensing Cr2O72− and GLYP were 1.37 and 1.92 μM, respectively, and the LODs of Cd‐DPIA sensing Cr2O72− and GLYP were 1.19 and 1.42 μM, respectively. Cr2O72− and GLYP detection based on Zn‐DPIA and Cd‐DPIA in tap water is highly reliable based on high recovery rates (97% to 106% and 95% to 103%), indicating that Zn‐DPIA and Cd‐DPIA have practical application prospects. [ABSTRACT FROM AUTHOR]

The vibration of downhole drilling tools is important to the drilling process, which needs to be measured in real time. Here, a self-powered vibration sensor for downhole drilling tools based on a hybrid electromagnetic–triboelectric nanogenerator is proposed in this research. The sensor has high reliability because the triboelectric nanogenerator (TENG) and the electromagnetic generator (EMG) parts of the sensor can be used as vibration sensors alone, and it may also supply power to other micro-power measurements while drilling instruments when the TENG and the EMG are used in parallel to increase the output power. Test results show that for the TENG part, the maximum output voltage, current, and power are 14 V, 5.2 µA, and 3.2 µW, respectively, with a 1 MΩ resistance in series, and for the EMG part, they are 1.22 V, 33 µA, and 21.8 mW, respectively, with a 10 Ω resistance in series. Further tests show that the measurement range of both the TENG and EMG is 0–11 Hz, the measurement error of both is less than ±5%, and both can work normally in the temperature range of less than 250 °C. In addition, this research also builds a wireless vibration data transmission system based on the sensor, which shows the potential for use in the wireless sensing field. [ABSTRACT FROM AUTHOR]

We put forward a multimode slotted nanobeam cavity (MM-SPCNC) supporting both air and dielectric modes through a specific design of band properties. Dual-parameter detection is realized by jointly measuring the resonance wavelength shifts of both air and dielectric modes. The proposed sensor is robust against external interference and shows higher sensitivity compared with other dual-parameter sensors. The maximum external interference ranges of the proposed sensor are 4.82×10−6 and 0.05 for refractive index (RI) and temperature (T), respectively, which indicates that the sensor can effectively resist against external interference. The RI and T sensitivities of the fundamental air mode are 421 nm/RIU and 58 pm/K respectively, whereas those of the fundamental dielectric mode are 706 nm/RIU and 46 pm/K respectively. The proposed sensor thus represents a promising candidate for future multifunctional and lab-on-chip sensing applications. [ABSTRACT FROM AUTHOR]

Here, we synthesized a novel three-dimensional cadmium-based MOF (Cd-DPNA). It has high selectivity and sensitivity to the biomarker (DPA) of Bacillus anthracis, which provides a new idea for the detection of DPA by MOF-based fluorescence sensing method. [Display omitted] • 3D Cd-DPNA was successfully synthesized and characterized. • The fluorescence intensity of Cd-DPNA is quenched by adding DPA. • The low detection limit of Cd-DPNA for DPA is 3.04 μM. • Cd-DPNA detects DPA with very high selectivity, excellent recyclability and rapid response. • In the actual sample detection, Cd-DPNA has high detection accuracy and has potential for practical application. Anthracnose caused by Bacillus anthracis is an acute infectious disease that has the greatest impact on grazing livestock and wild ungulates, and poses a serious threat to human health. Therefore, it is of great research significance and application value to develop a fluorescent sensor that can detect the markers of Bacillus anthracis. Based on this, a three-dimensional Cd-based MOF (Cd-DNPA) was synthesized by solvothermal method. It is worth noting that it exhibits high selectivity and high sensitivity to 2,6-pyridine dicarboxylic acid (DPA), the calculated Ksv is 2.3686 × 103 M−1, the detection limit (LOD) is as low as 3.04 μM. In addition, the sensor can be detected in actual samples, and the recovery value is 98% −103%, indicating that it has the potential for practical application. [ABSTRACT FROM AUTHOR]

We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision. We observe a phenomenon that part detectors emerge within CNN trained to classify attributes from uncropped face images, without any explicit part supervision. The observation motivates a new method for finding faces through scoring facial parts responses by their spatial structure and arrangement. The scoring mechanism is data-driven, and carefully formulated considering challenging cases where faces are only partially visible. This consideration allows our network to detect faces under severe occlusion and unconstrained pose variations. Our method achieves promising performance on popular benchmarks including FDDB, PASCAL Faces, AFW, and WIDER FACE. [ABSTRACT FROM AUTHOR]

Recently, 3D object detection by point cloud data processing has been applied to robotics and autonomous driving because of the popularity of the LiDAR sensors. Point cloud data contain the depth and geometric space information of an object as compared with the 2D images, and achieve high precision for classification and location. In the traditional processing of point cloud data, the disorder and sparsity of the points are significant problems. In addition, the traditional detector can only support processing a limited number of point clouds. Thus, it is difficult to detect objects using a large number of point clouds. However, the previous methods need to sample the point cloud data into a coarser type, so they cannot avoid the loss of information and the accuracy is affected, as seen in in PV-RCNN. In this paper, we propose a multiscale feature fusion detector called multiscale region proposal networks (MS-RPNs), which can provide multiscale prediction results for difficult category objects. Meanwhile, our method can improve the detection accuracy for smaller objects with the optimal processing of the multiscale feature extraction module. The efficiency and accuracy of the multiscale region proposal network on the KITTI 3D object detection datasets was evaluated using numerous experiments. [ABSTRACT FROM AUTHOR]

• A three-dimensional inverse opal WO 3 sensor modified by MOF derived ZnO@Au nanopartilces is synthesized for H 2 S detection. • The heterojunctions, and the effective encapsulated of small sized Au NPs lead to the outstanding gas sensing performance. • The improved conductivity and the higher negative charge of O can contribute to the excellent selectivity. • The designed sensor can be applied to distinguish the abnormal H 2 S concentration in the simulated exhaled breath environment. Sensitive and selective determination of H 2 S in human exhalation is essential for understanding some physiological and pathological processes. However, effective detection of H 2 S at ppb level remains a challenge. In this work, three-dimensional inverse opal (3DIO) WO 3 structure modified with metal-organic framework (MOF) derived ZnO@Au nanoparticles (NPs) were designed and fabricated for trace H 2 S detection. The ordered macroporous structure of 3DIO, n-n heterojunctions between WO 3 and ZnO, and effective encapsulated of small-sized Au NPs benefited to the sensing performance. Compared to pristine 3DIO WO 3 sensor, the response of MOF derived 3DIO WO 3 /ZnO@Au sensor enhanced 6.5-folds (175 to 10 ppm H 2 S), the optimal working temperature dramatically decreased to 170 °C, and the actual detection limit extended to 50 ppb with a response of 8.5. The good selectivity and long-term stability of the sensor were also identified. The theoretical simulation indicated that improved conductivity, higher negative charge of O, and increased adsorption energies contributed to the excellent selectivity. Furthermore, the proposed sensor could distinguish the trace H 2 S concentration change in the exhaled breath environment. This work demonstrates an example of a simple and versatile method for high performance H 2 S gas sensor design, which is promising for exhaled breath biomarker determination. [ABSTRACT FROM AUTHOR]

To realize early fire identification in cotton harvesting operations, a mid-infrared carbon monoxide (CO) sensor system was developed. To match the broadband light source with a 15° divergence angle, a multipass gas cell (MPGC) with an effective path length of 180 cm was designed to improve sensor sensitivity, leading to a limit of detection (LoD) of 0.83 parts-per-million by volume (ppmv). A damping module with springs at the bottom and front/back sides was fabricated, which can effectively reduce the vibration intensity by >80%. The sensor system can operate normally from −40 °C to 85 °C by stabilizing the temperature of the optical module through heating or cooling as well as using automotive electronic components. An adaptive early fire identification algorithm based on a dual-parameter threshold alarming method was proposed to avoid false and missing alarms. Field deployments on a harvester verified the good practicability of the sensor system. [ABSTRACT FROM AUTHOR]

Downhole vibration is important for the judgment of the drilling tool conditions and the formulation of drilling technology. To meet the demand of downhole drilling tools acceleration measurement, this research proposes a self-powered acceleration sensor with two working modes based on the triboelectric nanogenerator, namely, mode A, which is based on the voltage response acceleration trend and mode B, which judges the acceleration based on the output pulses. Test results show that the acceleration measurement range is 0–11 m/s2, the maximum output voltage amplitude can reach 15.3 V, the working environment temperature is less than 250 °C, the working environment humidity is less than 90%, and long-time working has almost no effect on the output voltage of the sensor. In addition, since the sensor will generate electrical energy during the vibration process, the power generation performance of the sensor has been tested. And the results show that the maximum output power of the sensor is 0.18 µW when a 1000 MΩ load is connected in series. Compared to traditional downhole sensors, the sensor is more flexible, because it can work normally at high temperatures and has the potential for being self-powered. [ABSTRACT FROM AUTHOR]

• A novel four-channel-based sensor structure was presented for methane measurement. • A LS-FTF denoising algorithm was adopted to suppress the optical and electrical noise. • Numerical simulations were carried out and sensor calibration and stability test were performed. • The proposed structure shows an enhanced performance for improving sensor sensitivity. By incorporating two wide-band mid-infrared (MIR) incandescence light sources and two dual-channel pyroelectric detectors, a new four-channel-based mid-infrared gas sensor is presented for the measurement of methane (CH 4) mole fractions. A least-square fast transverse filtering (LS-FTF) self-adaptive denoising algorithm was proposed to improve the robustness, stability, and noise immunity performance of the sensor. Numerical simulations were carried out to validate the function of the LS-FTF algorithm by introducing interference with different frequencies in the simulation. Sensor calibration and stability test were performed for the self-adaptive sensor using standard or diluted CH 4 samples. With the intrinsic noise considered only, an Allan deviation of ∼ 207 parts per million by volume (ppmv) with a ∼ 3 s averaging time was obtained with no filter (NF) structure. Using self-adaptive filtering (SAF), the Allan deviation was decreased to ∼162 ppmv with the same averaging time. Noise with different modulation frequencies was imposed on the detection channel to validate the denoising performance of the four-channel structure. The reported four-channel-based sensor using LS-FTF technique shows an enhanced denoising performance as compared to the two or three-channel-based sensor structure. [ABSTRACT FROM AUTHOR]

Recently, many noncontact sensors are intended for facilities that require hygiene to be considered. However, there is a problem in that noncontact sensors could malfunction unintentionally. In addition, there is a demerit in that noncontact sensor is not possible to perform complicated operations with one sensor because it would be limited to the simple operation of turning on when hold hand over it. In this paper, we examine the principle of a noncontact sensor that responds only to the action of waving in front of the sensor as an intentional action and does not malfunction. Additionally, since there are large and small hand waving methods, hand waving alone could be used for multiple signals. Experiments show that the proposed system is to realize not only the states of ON and OFF but also various operations with a single noncontact button. [ABSTRACT FROM AUTHOR]

The schematic diagram of the sensor system structure, which includes a gas pretreatment module, a CO 2 sensor module, a CO sensor module, and a monitoring platform module. [Display omitted] • Asensor system was developed for early fire detection and location. • Early fire detection was determined by concentration ratio. • A mobile early fire location method was presented using PSO algorithm. • Experiment verified the function of early fire detection and location. In order to realize early fire detection and location, a mid-infrared carbon monoxide (CO) and carbon dioxide (CO 2) dual-gas sensor system was developed, which mainly includes a gas pretreatment module, a CO 2 sensor module, a CO sensor module, and a laptop monitoring platform. CO 2 and CO absorption lines located at 4.26 μm and 4.66 μm, respectively, were selected to ensure good selectivity of the sensor system. A series of experiments were carried out to evaluate the sensor performance. The 10–90% response time of the CO and CO 2 sensor modules was measured to be ∼ 30 s at a flow rate of 1 L/min, and the limits of detection (LoD) of CO 2 and CO were assessed to be 5.66 parts per million by volume (ppmv) and 0.94 ppmv, respectively, when the averaging time was 0.25 s. According to the correlation between CO 2 and CO concentration in the early fire stage, a method of early fire detection was studied and proposed using the normalized concentration ratio between CO and CO 2 (C (CO)/ C (CO 2)) as the key alarm parameter. Based on gas turbulent diffusion (GTD) model combined with particle swarm optimization (PSO) algorithm, a mobile early fire location method was presented. Correlative experiment results verified that the reported sensor system has a good performance for early fire detection and location. [ABSTRACT FROM AUTHOR]