Studies on Gas-phase Cyclometalations of [ArNi(PPh3)n]+ (n = 1 or 2) by Electrospray Ionization Tandem Mass Spectrometry

Gas-phase cyclometalation of [ArNi(PPh3)n]+ (n = 1, 2) complexes have been studied by ESI-MS/MS. The electron-donating substituents of aromatic iodides in the para position were found to inhibit the cyclometalation process of losing ArH, while the electron-withdrawing substituents in the para position were found to enhance it. These results indicate that the cyclometalation process of losing ArH is favored by electron-deficient aromatic groups. In addition, the detailed dissociation pathways of the cationic nickel complexes were studied, and among these pathways, the process of aryl-aryl interchange was also found to proceed in ESI-MS/MS

An Interpretable Computer-Aided Diagnosis Method for Periodontitis From Panoramic Radiographs

Periodontitis is a prevalent and irreversible chronic inflammatory disease both in developed and developing countries, and affects about 20–50% of the global population. The tool for automatically diagnosing periodontitis is highly demanded to screen at-risk people for periodontitis and its early detection could prevent the onset of tooth loss, especially in local communities and health care settings with limited dental professionals. In the medical field, doctors need to understand and trust the decisions made by computational models and developing interpretable models is crucial for disease diagnosis. Based on these considerations, we propose an interpretable method called Deetal-Perio to predict the severity degree of periodontitis in dental panoramic radiographs. In our method, alveolar bone loss (ABL), the clinical hallmark for periodontitis diagnosis, could be interpreted as the key feature. To calculate ABL, we also propose a method for teeth numbering and segmentation. First, Deetal-Perio segments and indexes the individual tooth via Mask R-CNN combined with a novel calibration method. Next, Deetal-Perio segments the contour of the alveolar bone and calculates a ratio for individual tooth to represent ABL. Finally, Deetal-Perio predicts the severity degree of periodontitis given the ratios of all the teeth. The Macro F1-score and accuracy of the periodontitis prediction task in our method reach 0.894 and 0.896, respectively, on Suzhou data set, and 0.820 and 0.824, respectively on Zhongshan data set. The entire architecture could not only outperform state-of-the-art methods and show robustness on two data sets in both periodontitis prediction, and teeth numbering and segmentation tasks, but also be interpretable for doctors to understand the reason why Deetal-Perio works so well

SPatiotemporal-ENcoded acoustic radiation force imaging of focused ultrasound

Neuromodulation technology has provided novel therapeutic approaches for diseases caused by neural circuit dysfunction. Transcranial focused ultrasound (FU) is an emerging neuromodulation approach that combines noninvasiveness with relatively sharp focus, even in deep brain regions. It has numerous advantages such as high precision and good safety in neuromodulation, allowing for modulation of both peripheral and central nervous systems. To ensure accurate treatment targeting in FU neuromodulation, a magnetic resonance acoustic radiation force imaging (MR-ARFI) sequence is crucial for the visualization of the focal point. Currently, the commonly used 2D Spin Echo ARFI (2D SE-ARFI) sequence suffers from the long acquisition time, while the echo planar imaging ARFI (EPI-ARFI) sequence with a shorter acquisition time is vulnerable to the magnetic field inhomogeneities. To address these problems, we proposed a spatiotemporal-encoded acoustic radiation force imaging sequence (i.e., SE-SPEN-ARFI, shortened to SPEN-ARFI) in this study. The displacement at the focal spot obtained was highly consistent with that of the SE-ARFI sequence. Our research shows that SPEN-ARFI allows for rapid image acquisition and has less image distortions even under great field inhomogeneities. Therefore, a SPEN-ARFI sequence is a practical alternative for the treatment planning in ultrasound neuromodulation

Analysis and Suppression of Induced Voltage Pulsation in DC Winding of Five-Phase Wound-Field Switched Flux Machines

In wound-field (WF) switched flux (SF) (WFSF) machines, the DC winding induced voltage pulsation causes current ripple in the DC winding and challenges the DC power source, and deteriorates the control performance. In this paper, the induced voltage pulsation in DC winding of five-phase WFSF machines is analyzed and its reduction methods are proposed. The cycles per electric period of the open-circuit and armature reaction induced voltage pulsation in DC winding are derived analytically. Modifying the airgap permeance by optimizing the rotor pole arc or chamfering the rotor pole surface, and axial pairing of rotor segments having rotor pole with different arcs are used to suppress the induced voltage pulsation in DC winding, with >90% average torque maintained. Finite element results show that, by optimizing the rotor pole arc, the peak-to-peak value of the induced voltage pulsation in DC winding can be effectively suppressed to 59.59%, 30.67%, 29.99% and 43.35% for the 10-stator-pole five-phase WFSF machines with 8-, 9-, 11- and 12-rotor-pole rotors, respectively. By applying rotor pole surface shaping, the induced voltage pulsation in DC winding peak-to-peak value can be effectively suppressed to 61.76%, 45.47% and 40.21% for the 8-, 9- and 12-rotor-pole machines, respectively, while by applying axial pairing, it can be suppressed to 46.89%, 7.16%, 15.64% and 12.04%, respectively. The 10-stator-pole/12-rotor-pole WFSF machines having the original rotor, optimized rotor, chamfered rotor and axial paired rotor are prototyped and the experiments validate the analytical and finite element results

Application of Blockchain Hierarchical Model in the Realm of Rural Green Credit Investigation

In order to realize the application research of blockchain technology in the field of green credit investigation, the current paper adopts the method of a blockchain hierarchical model to study the rural green credit. With regard to the realm of rural green credit investigation, this paper sorts out the characteristics of credit data in China’s countryside by countryside credit investigation and determines the major problems and in rural green credit investigation of financial inclusion. Subsequently, the authors put forward a blockchain hierarchical model, which not only has reinforced the advantages in original blockchain dedicated to agriculture, rural areas and rural residents, such as traceability and immutability, but also has transformed the decentralization into disintermediation and changed the single-layered P2P network into a multilayered structure based on China’s rural financial environment. Finally, the authors collect and extract the proper credit investigation data on the rural internet to assess the application value of the model by investigating its practical applicability in reality and problems that may occur during the application of the model. Results show that private credit information has an important impact on the prediction accuracy, and the blockchain hierarchical model is helpful to ensure the reliability and security of rural green credit data

Underwater Radiated Noise Prediction Method of Cabin Structures under Hybrid Excitation

Aiming at the engineering limitations of traditional ship vibration online monitoring and noise prediction methods, this paper proposes a method for online monitoring and underwater radiation noise prediction of cabin structures’ vibration and noise under hybrid excitation of sound and force. The method first constructs the condition test model; based on OTPA technology, the “acoustic-vibration” transfer function between sound and vibration monitoring points in the cabin and the “acoustic/vibration-acoustic” transmission network inside and outside the cabin structure are obtained. Secondly, based on the “acoustic-vibration” transfer function, the online vibration and sound monitoring data are decoupled and processed to obtain the modified vibration and sound monitoring data. Finally, the near-field radiation noise on the conformal hologram surface outside the cabin is predicted based on the “acoustic/vibration-acoustic” transmission network, and the far-field radiation noise of the cabin structure is predicted by the wave superposition method. In this paper, the contribution law of external radiation noise and the coupling characteristics of the monitoring information under the hybrid excitation of sound and force are analyzed theoretically, and the decoupling method of coupling information is also studied. This method makes up for the problem of missing underwater radiation noise caused by sound excitation in traditional vibration monitoring, and it can effectively improve the prediction accuracy of underwater radiation noise. The effectiveness of the method is further verified by the tank model experiments

A Five-Level RF-PWM Method with Third and Fifth Harmonic Elimination for All-Digital Transmitters

An appropriate pulse-coding algorithm is the key to achieving an efficient switched-mode power amplification in all-digital transmitters. A five-level RF-PWM method with third and fifth harmonic elimination is proposed to relax the requirements of the filter and to reduce the control complexity of the SMPA for all-digital transmitters. By controlling the pulse width and the center position of three-level sub-pulses, third and fifth harmonic elimination is achieved. Meanwhile, the control complexity of the SMPA is reduced by the decrease in the output-signal-level number. Finally, the feasibility of the method is verified by simulation. For the 16QAM signal with a carrier frequency of 200 MHz, the proposed method can achieve third harmonic suppression of −46.24 dBc and fifth harmonic suppression of −54.05 dBc when coding efficiency reaches 77.51%