Improving the Resolution of Flexible Large-Area Tactile Sensors through Machine-Learning Perception.

Industrial robots are the main piece of equipment of intelligent manufacturing, and array-type tactile sensors are considered to be the core devices for their active sensing and understanding of the production environment. A great challenge for existing array-type tactile sensors is the wiring of sensing units in a limited area, the contradiction between a small number of sensing units and high resolution, and the deviation of the overall output pattern due to the difference in the performance of each sensing unit itself. Inspired by the human somatosensory processing hierarchy, we combine tactile sensors with artificial intelligence algorithms to simplify the sensor architecture while achieving tactile resolution capabilities far greater than the number of signal channels. The prepared 8-electrode carbon-based conductive network achieves high-precision identification of 32 regions with 97% classification accuracy assisted by a quadratic discriminant analysis algorithm. Notably, the output of the sensor remains unchanged after 13,000 cycles at 60 kPa, indicating its excellent durability performance. Moreover, the large-area skin-like continuous conductive network is simple to fabricate, cost-effective, and can be easily scaled up/down depending on the application. This work may address the increasing need for simple fabrication, rapid integration, and adaptable geometry tactile sensors for use in industrial robots.

Soil exposure is the major fluoride exposure pathways for residents from the high-fluoride karst region in Southwest China.

In the karst areas of southwest China, soil fluoride levels are higher than in China (478 mg kg-1) and world (200 mg kg-1). High levels of F in the environment might pose a health risk to humans. The comprehensive exposure risk must be studied in this area. Herein, samples of crops and soil were collected from Bijie City, a typical karst area in southwest China, to investigate the pollution level and evaluate the comprehensive F exposure risk. The single-factor index (PFw) and the geological accumulation index (Igeo) were used. The hazard index (HI) was applied to assess exposure risk from multiple exposure routes. The results revealed that there is considerable F contamination in soil and crops in the study area. Average soil total fluorine (Ft) was 1139.13 mg kg-1, and soil water soluble F (Fw) was 3.792 mg kg-1. In corn, rice, wheat, and potatoes, F contents were 1.167-9.585, 1.222-6.698, 1.587-9.976, and 1.797-9.143 mg kg-1, respectively. The mean values of HI were 4.45 and 2.42 for children and adults, respectively, > 1, showing potential health risk exists. Youngsters are at a greater exposure risk than adults. From the results of contribution ratios of different exposure routes for health risk, the major exposure risk was determined to be from soil exposure. Based on this, we suggest that risk managers mainly strive to control the soil fluoride level and implement the risk education and communication.

Co-exposure of potentially toxic elements in wheat grains reveals a probabilistic health risk in Southwestern Guizhou, China.

Bijie is located at a typical karst landform of Southwestern Guizhou, which presented high geological background values of potentially toxic elements (PTEs). Recently, whether PTE of wheat in Bijie is harmful to human health has aroused people's concern. To this end, the objectives of this study are to determine the concentrations of PTE [chromium (Cr), nickel (Ni), arsenic (As), lead (Pb), cadmium (Cd), and fluorine (F)] in wheat grains, identify contaminant sources, and evaluate the probabilistic risks to human beings. A total of 149 wheat grain samples collected from Bijie in Guizhou were determined using the inductively coupled plasma mass spectrometer (ICP-MS) and fluoride-ion electrode methods. The mean concentrations of Cr, Ni, As, Cd, Pb, and F were 3.250, 0.684, 0.055, 0.149, 0.039, and 4.539 mg/kg, respectively. All investigated PTEs met the standard limits established by the Food and Agriculture Organization except for Cr. For the source identification, Cr and Pb should be originated from industry activities, while Ni, As, and Cd might come from mixed sources, and F was possibly put down to the high geological background value. The non-carcinogenic and carcinogenic health risks were evaluated by the probabilistic approach (Monte Carlo simulation). The mean hazard quotient (HQ) values in the three populations were lower than the safety limit (1.0) with the exception of As (children: 1.03E+00). However, the mean hazard index (HI) values were all higher than 1.0 and followed the order: children (2.57E+00) > adult females (1.29E+00) > adult males (1.12E+00). In addition, the mean carcinogenic risk (CR) values for Cr, As, Pb, and Cd in three populations were all higher than 1E-06, which cannot be negligible. The mean threshold CR (TCR) values were decreased in the order of children (1.32E-02) > adult females (6.61E-03) > adult males (5.81E-03), respectively, all at unacceptable risk levels. Moreover, sensitivity analysis identified concentration factor (C W ) as the most crucial parameter that affects human health. These findings highlight that co-exposure of PTE in wheat grains revealed a probabilistic human health risk. Corresponding measures should be undertaken for controlling pollution sources and reducing the risks for the local populace.