Differential Structure of Inductive Proximity Sensor.

The inductive proximity sensor (IPS) is applicable to displacement measurements in the aviation field due to its non-mechanical contact, safety, and durability. IPS can increase reliability of position detection and decrease maintenance cost of the system effectively in aircraft applications. Nevertheless, the specialty in the aviation field proposes many restrictions and requirements on the application of IPS, including the temperature drift effect of the resistance component of the IPS sensing coil. Moreover, reliability requirements of aircrafts restrict the use of computational-intensive algorithms and avoid the use of process control components. Furthermore, the environment of airborne electronic equipment restricts measurements driven by large current and proposes strict requirements on emission tests of radio frequency (RF) energy. For these reasons, a differential structured IPS measurement method is proposed in this paper. This measurement method inherits the numerical separation of the resistance and inductance components of the IPS sensing coil to improve the temperature adaptation of the IPS. The computational complexity is decreased by combining the dimension-reduced look-up table method to prevent the use of process control components. The proposed differential structured IPS is equipped with a differential structure of distant and nearby sensing coils to increase the detection accuracy. The small electric current pulse excitation decreases the RF energy emission. Verification results demonstrate that the differential structured IPS realizes the numerical decoupling calculation of the vector impedance of the sensing coil by using 61 look-up table units. The measuring sensitivity increased from 135.5 least significant bits (LSB)/0.10 mm of a single-sensing-coil structured IPS to 1201.4 LSB/0.10 mm, and the linear approximation distance error decreased from 99.376 µm to -3.240 µm. The proposed differential structured IPS method has evident comparative advantages compared with similar measuring techniques.

Effect of dexmedetomidine on rats with convulsive status epilepticus and association with activation of cholinergic anti-inflammatory pathway.

Convulsive status epilepticus (CSE) is a neurological disease with contraction and extension of limbs, leading to damage of hippocampus and cognition. This study aimed to explore the effects of dexmedetomidine (DEX) on the cognitive function and neuroinflammation in CSE rats. All rats were divided into control group, CSE group and DEX group. Morris water maze test was used to measure cognitive function. Acute hippocampal slices were made to detect long-term potentiation (LTP). Immunohistochemistry was used to determine the expression of α7-nicotinic acetylcholine receptor (α7-nAChR) and interleukin-1ß (IL-1ß). Enzyme-linked immunosorbent assay (ELISA) was used to measure serum levels of IL-1ß, tumor necrosis factor-α (TNF-α), S-100ß and brain-derived neurotrophic factor (BDNF). Our results showed that DEX improved the memory damage caused by CSE. DEX reduced seizure severity and increased the amplitudes and sustainable time of LTP, and also inhibited the hippocampal expression of α7-nAChR and IL-1ß in CSE rats. DEX treatment decreased serum IL-1ß, TNF-α and S-100ß levels and increased BDNF levels. The effects of DEX on seizure severity and LTP could be simulated by nicotine or attenuated by concurrent α-bungarotoxin (α-BGT) treatment. In conclusions, DEX significantly improved spatial cognitive dysfunction, reduced seizure severity and increased LTP in CSE rats. Improvements by DEX were closely related to enhancement of cholinergic anti-inflammatory pathway.

Dimension-Reduced Analog-Digital Mixed Measurement Method of Inductive Proximity Sensor.

Inductive proximity sensors (IPSs) present a unique no-contact advantage. They are widely preferred for displacement measurement in various industrial fields (e.g., aviation and aerospace), and they are improved continuously. When the inductance and resistance components of the IPS sensing core are separated, the influence of temperature drift on measurement can be eliminated. The complexity of online computation of component separation can be reduced using a two-dimensional look-up table method. However, this method exhibits disadvantages, such as large capacity of the look-up table, dependency on precision measurement of sensing core parameter, and nonlinear distribution of measurement resolution. This study aims to overcome these disadvantages by examining the nonlinear relationship between the response of the sensing core and the ambient temperature, and proposes a dimension-reduced measurement method. The proposed method extracts the characteristics of the response curves at two temperatures and calculates the characteristics of the response curves at any temperature using a linear approximation. The look-up table capacity is less than 0.37% of the two-dimensional look-up table capacity (condensed) under the same condition; dimension reduction enables the construction of a complete look-up table directly by calibration procedures and avoids precise measurement on sensing core parameters; the calibration procedures establish uniform mapping of the distribution of measurement resolution. The experiment shows that, when the measurement ranges are 0-6, 0-5, and 0-4 mm, the maximum measurement errors are 0.140, 0.065, and 0.040 mm, respectively, under temperature ranging from 20 ∘ C to 110 ∘ C. This study extends the measurement range from 0-5 mm to 0-7 mm and improves the measurement accuracy over 0.1 mm (50% at 5 mm) compared with the two-dimensional look-up table method. Therefore, the proposed method not only inherits the advantages of the original method but also achieves the above-mentioned expected capacity improvements effectively.