Due to their striking opticalp roperties, luminescent coordination polymers as sensors for the detection of hazardous species have drawn interest of researchers in consideration of the control of environmental pollution. In this work, the organic ligand 2-(4-((E)-2-(pyridine-2-yl)vinyl)styryl)pyridine (2-bpeb),w hich possesses al arge p-conjugated system, was employedt or eact with d 10 metal ions to obtain novel luminescentc oordination polymers. Three complexes [Cd(2-bpeb) 0.5 (CNA)(H 2 O)] (CP1), [Cd(2-bpeb) 0.5 (NDC)] (CP2) and [Zn(2-bpeb)(BDC)] (CP3)w ere synthesized successfully by introducing carboxylic acids of 4-carboxycinnamic acid (H 2 CNA), 2,6-naphthalene dicarboxylica cid (H 2 NDC) and 1,4benzenedicarboxylica cid (H 2 BDC) as auxiliary ligands. Because of the existence of the large p-conjugated system and d 10 metal ions, all of these coordinationp olymers exhibit striking fluorescencep roperties.I mpressively,a ll of them can functiona ss ensors for the detection of highly oxidizing anionsM nO 4 À and Cr 2 O 7 2À ,w ith an increased sensitivity for MnO 4 À .Supporting information and the ORCID identification number(s) for the author(s) of this article can be found under: https://doi.

Ball screw is a mechanical device widely used in mechanical field. The reverse clearance of ball screw will reduce its precision. In order to eliminate the reverse clearance, it is necessary to apply preload to the ball screw. It is very difficult to measure the preload in real time, and the data are large and time-consuming. By using machine learning method to predict and supervise preload, the changing trend of working condition of ball screw can be evaluated in advance, and the working precision of screw is controlled, which has important engineering significance. In this article, the relationship between the preload and the friction torque is obtained through theoretical derivation and experimental verification. Then, the support vector machine is used as a tool to model the friction torque of ball screw with the parameters of material, lubrication, and revolution, and predict the value and trend of preload to complete the supervision and prediction of the preload of the ball screw. By comparing the experimental results, it is proved that the support vector machine is feasible in predicting and supervising the attenuation of the preload of ball screw.