Anomaly Detection Based on Mining Six Local Data Features and BP Neural Network

Key performance indicators (KPIs) are time series with the format of (timestamp, value). The accuracy of KPIs anomaly detection is far beyond our initial expectations sometimes. The reasons include the unbalanced distribution between the normal data and the anomalies as well as the existence of many different types of the KPIs data curves. In this paper, we propose a new anomaly detection model based on mining six local data features as the input of back-propagation (BP) neural network. By means of vectorization description on a normalized dataset innovatively, the local geometric characteristics of one time series curve could be well described in a precise mathematical way. Differing from some traditional statistics data characteristics describing the entire variation situation of one sequence, the six mined local data features give a subtle insight of local dynamics by describing the local monotonicity, the local convexity/concavity, the local inflection property and peaks distribution of one KPI time series. In order to demonstrate the validity of the proposed model, we applied our method on 14 classical KPIs time series datasets. Numerical results show that the new given scheme achieves an average F1-score over 90%. Comparison results show that the proposed model detects the anomaly more precisely

A Novel Low-Cost GNSS Solution for the Real-Time Deformation Monitoring of Cable Saddle Pushing: A Case Study of Guojiatuo Suspension Bridge

Extreme loadings, a hostile environment and dangerous operation lead to the unsafe state of bridges under construction, especially large-span bridges. Global Navigation Satellite Systems (GNSS) tend to be the best choice for real-time deformation monitoring due to the significant advantage of automation, continuation, all-weather operation and high precision. Unfortunately, the traditional geodetic GNSS instrument with its high price and large volume is limited in its applications. Hence, we design and develop low-cost GNSS equipment by simplifying the monitoring module. The performance of the proposed solution is evaluated through an experimental dynamic scenario, proving its ability to track abrupt deformation down to 3–5 mm. We take Chongqing Guojiatuo Suspension Bridge in China as a case study. We build a real-time low-cost GNSS monitoring cloud platform. The low-cost bridge GNSS monitoring stations are located at the top of the south and north towers, midspan upstream and downstream respectively and the reference station is located in the stable zone 400 m away from the bridge management buildings. We conducted a detailed experimental assessment of low-cost GNSS on 5 April and a real-time deformation detection experiment of the towers and main cables during the dynamic cable saddle pushing process on 26 February 2022. In the static experiment, the standard deviation of the residual using the multi-GNSS solution is 2 mm in the horizontal direction and 5 mm in the vertical direction. The multi-GNSS solution significantly outperforms the BDS/GPS single system. The dynamic experiment shows that, compared with the movement measured by the robotic total station, the horizontal error of the south tower and north tower measured by low-cost GNSS is below 0.005 m and 0.008 m respectively. This study highlights the potential of low-cost GNSS solutions for Structural Health Monitoring (SHM) applications

A Novel Low-Cost GNSS Solution for the Real-Time Deformation Monitoring of Cable Saddle Pushing: A Case Study of Guojiatuo Suspension Bridge

Extreme loadings, a hostile environment and dangerous operation lead to the unsafe state of bridges under construction, especially large-span bridges. Global Navigation Satellite Systems (GNSS) tend to be the best choice for real-time deformation monitoring due to the significant advantage of automation, continuation, all-weather operation and high precision. Unfortunately, the traditional geodetic GNSS instrument with its high price and large volume is limited in its applications. Hence, we design and develop low-cost GNSS equipment by simplifying the monitoring module. The performance of the proposed solution is evaluated through an experimental dynamic scenario, proving its ability to track abrupt deformation down to 3–5 mm. We take Chongqing Guojiatuo Suspension Bridge in China as a case study. We build a real-time low-cost GNSS monitoring cloud platform. The low-cost bridge GNSS monitoring stations are located at the top of the south and north towers, midspan upstream and downstream respectively and the reference station is located in the stable zone 400 m away from the bridge management buildings. We conducted a detailed experimental assessment of low-cost GNSS on 5 April and a real-time deformation detection experiment of the towers and main cables during the dynamic cable saddle pushing process on 26 February 2022. In the static experiment, the standard deviation of the residual using the multi-GNSS solution is 2 mm in the horizontal direction and 5 mm in the vertical direction. The multi-GNSS solution significantly outperforms the BDS/GPS single system. The dynamic experiment shows that, compared with the movement measured by the robotic total station, the horizontal error of the south tower and north tower measured by low-cost GNSS is below 0.005 m and 0.008 m respectively. This study highlights the potential of low-cost GNSS solutions for Structural Health Monitoring (SHM) applications

1‑D “Platinum Wire” Stacking Structure Built of Platinum(II) Diimine Bis(σ-acetylide) Units with Luminescence in the NIR Region

A square-planar platinum­(II) complex, Pt­(DiBrbpy)­(CCC₆H₄Et-4)₂ (<b>1</b>) (DiBrbpy = 4,4-dibromo-2,2′-bipyridine), and crystals of its three solvated forms, namely, <b>1</b>·DMSO, <b>1</b>·1/2­(CH₃CN), and <b>1</b>·1/8­(CH₂Cl₂), were developed and characterized. <b>1</b>·DMSO and <b>1</b>·1/2­(CH₃CN) contain quasi-dimeric and dimeric structures with luminescence in the visible range, whereas <b>1</b>·1/8­(CH₂Cl₂) exhibits NIR luminescence at 1022 nm due to its intrinsic 1-D “platinum wire” stacking structure with strong Pt–Pt interactions. <b>1</b>·1/8­(CH₂Cl₂) represents the first compound based on platinum­(II) diimine bis­(σ-acetylide) molecular units with the NIR luminescence beyond 1000 nm. <b>1</b> selectively responds to DMSO and CH₃CN by changing its color and luminescence property and the three solvated forms can be reversibly converted to each other upon exposure to corresponding solvent vapors. Their desolvated forms, namely <b>1a</b>, <b>1b</b>, and <b>1c</b>, obtained after heating <b>1</b>·DMSO, <b>1</b>·1/2­(CH₃CN), and <b>1</b>·1/8­(CH₂Cl₂), respectively, can also be restored to the original solvated forms upon exposure to corresponding solvent vapors. <b>1a</b> and <b>1b</b> emit NIR luminescence peaked at 998 and 1018 nm respectively, suggesting indirect synthetic methods as powerful alternatives to achieve NIR luminescence with long wavelength. In contrast, <b>1c</b> exhibits a red luminescence with a broad unstructured emission band centered at 667 nm. All the responses to organic solvent vapors and heating are due to the structural transformations which result in the conversion of the lowest energy excited states between ³MLCT/³LLCT and ³MMLCT in solid-state as supported by time-dependent density functional theory (TD-DFT) calculations

Synuclein impairs trafficking and signaling of BDNF in a mouse model of Parkinson's disease.

Recent studies have demonstrated that hyperphosphorylation of tau protein plays a role in neuronal toxicities of α-synuclein (ASYN) in neurodegenerative disease such as familial Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and Parkinson's disease. Using a transgenic mouse model of Parkinson's disease (PD) that expresses GFP-ASYN driven by the PDGF-β promoter, we investigated how accumulation of ASYN impacted axonal function. We found that retrograde axonal trafficking of brain-derived neurotrophic factor (BDNF) in DIV7 cultures of E18 cortical neurons was markedly impaired at the embryonic stage, even though hyperphosphorylation of tau was not detectable in these neurons at this stage. Interestingly, we found that overexpressed ASYN interacted with dynein and induced a significant increase in the activated levels of small Rab GTPases such as Rab5 and Rab7, both key regulators of endocytic processes. Furthermore, expression of ASYN resulted in neuronal atrophy in DIV7 cortical cultures of either from E18 transgenic mouse model or from rat E18 embryos that were transiently transfected with ASYN-GFP for 72 hrs. Our studies suggest that excessive ASYN likely alters endocytic pathways leading to axonal dysfunction in embryonic cortical neurons in PD mouse models