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Fingerprints and finger veins are widely used in security identification in many fields due to their uniqueness and identifiability. However, their privacy issues are often criticized. This article summarizes several approaches that combine federated learning with fingerprint and finger vein recognition to solve privacy issues. One of the frameworks for fingerprint recognition, Federated Learning-Fingerprint Recognition, uses sparse representation techniques such as the Discrete Cosine Transform for data preprocessing. The framework also references the ResNet18 model and reservoir sampling so that each client can participate in training fairly. As for finger vein recognition, the Federated Learning-based Finger Vein authentication framework allows clients to share model weights to solve the data island problem and divide client data into shared and personalized parts to ensure privacy. This paper also points out its challenges, such as poor interpretability and applicability, and provides optimization solutions. For example, the interpretability issue can be solved by implementing an expert system. The expert system uses its robust knowledge base and inference engine to track model behavior and derive reasonable explanations. Transfer learning can also eliminate the applicability issue. It transfers the knowledge gained from training clients with concentrated data to clients with sparse data. In summary, this article comprehensively reviews the methods of federated learning in fingerprint and finger vein, respectively, and discusses the shortcomings and prospects.

Given fault false alarm and fault control failure caused by the decrease of fault identification accuracy and fault delay of Switched Reluctance Motor (SRM) power converter in complex working conditions, a method based on the Interactive Multi-Model (IMM) algorithm was proposed in this paper. Besides, the corresponding equivalent circuit models were established according to the different working states of the SRM power converter. The Kalman filter was employed to estimate the state of the model, and the fault detection and location were realized depending on the residual signal. Additionally, a transition probability correction function of the IMM was constructed using the difference of the n-th order to suppress the influence of external disturbance on the fault diagnosis accuracy. Concurrently, a model jump threshold was introduced to reduce delay when the matched model was switched, so as to realize the rapid separation of faults and effective fault control. The simulation and experiment results demonstrate that the IMM algorithm based on low delay anti-interference can effectively reduce the influence of complex working conditions, improve the anti-interference ability of SRM power converter fault diagnosis, and identify fault information accurately and quickly.

The intrinsic antiferromagnetic topological insulator MnBi 2 Te 4 provides an ideal platform for exploring exotic topological quantum phenomena. Recently, the Chern insulator and axion insulator phases have been realized in few-layer MnBi 2 Te 4 devices at low magnetic field regime. However, the fate of MnBi 2 Te 4 in high magnetic field has never been explored in experiment. In this work, we report transport studies of exfoliated MnBi 2 Te 4 flakes in pulsed magnetic fields up to 61.5 T. In the high-field limit, the Chern insulator phase with Chern number C  = −1 evolves into a robust zero Hall resistance plateau state. Nonlocal transport measurements and theoretical calculations demonstrate that the charge transport in the zero Hall plateau state is conducted by two counter-propagating edge states that arise from the combined effects of Landau levels and large Zeeman effect in strong magnetic fields. Our result demonstrates the intricate interplay among intrinsic magnetic order, external magnetic field, and nontrivial band topology in MnBi 2 Te 4 . The antiferromagnetic topological insulator MnBi 2 Te 4 exhibits Chern and axion insulator phases at low magnetic field; however, its behaviour in high magnetic field has remained unexplored. Here, using transport measurements at high magnetic field, the authors report a zero Hall plateau composed of two counter-propagating edge channels.

New strategies with high antimicrobial efficacy against multidrug-resistant bacteria are urgently desired. Herein, we describe a smart triple-functional nanostructure, namely TRIDENT (Thermo-Responsive-Inspired Drug-Delivery Nano-Transporter), for reliable bacterial eradication. The robust antibacterial effectiveness is attributed to the integrated fluorescence monitoring and synergistic chemo-photothermal killing. We notice that temperature rises generated by near-infrared irradiation did not only melt the nanotransporter via a phase change mechanism, but also irreversibly damaged bacterial membranes to facilitate imipenem permeation, thus interfering with cell wall biosynthesis and eventually leading to rapid bacterial death. Both in vitro and in vivo evidence demonstrate that even low doses of imipenem-encapsulated TRIDENT could eradicate clinical methicillin-resistant Staphylococcus aureus , whereas imipenem alone had limited effect. Due to rapid recovery of infected sites and good biosafety we envision a universal antimicrobial platform to fight against multidrug-resistant or extremely drug-resistant bacteria. Antibiotic resistance is a major global health challenge. Here, the authors report on a thermoresponsive delivery system for combined photothermal and antibiotic delivery with fluorescent tracking abilities and demonstrate application against antibiotic resistant bacteria in vitro and in vivo.

(1) Background: Macrosomia is prevalent in China and worldwide. The current method of predicting macrosomia is ultrasonography. We aimed to develop new predictive models for recognizing macrosomia using a random forest model to improve the sensitivity and specificity of macrosomia prediction; (2) Methods: Based on the Shandong Multi-Center Healthcare Big Data Platform, we collected the prenatal examination and delivery data from June 2017 to May 2018 in Jinan, including the macrosomia and normal-weight newborns. We constructed a random forest model and a logistic regression model for predicting macrosomia. We compared the validity and predictive value of these two methods and the traditional method; (3) Results: 405 macrosomia cases and 3855 normal-weight newborns fit the selection criteria and 405 pairs of macrosomia and control cases were brought into the random forest model and logistic regression model. On the basis of the average decrease of the Gini coefficient, the order of influencing factors was: interspinal diameter, transverse outlet, intercristal diameter, sacral external diameter, pre-pregnancy body mass index, age, the number of pregnancies, and the parity. The sensitivity, specificity, and area under curve were 91.7%, 91.7%, and 95.3% for the random forest model, and 56.2%, 82.6%, and 72.0% for logistic regression model, respectively; the sensitivity and specificity were 29.6% and 97.5% for the ultrasound; (4) Conclusions: A random forest model based on the maternal information can be used to predict macrosomia accurately during pregnancy, which provides a scientific basis for developing rapid screening and diagnosis tools for macrosomia.

Flowering plants have evolved numerous intraspecific and interspecific prezygotic reproductive barriers to prevent production of unfavourable offspring 1 . Within a species, self-incompatibility (SI) is a widely utilized mechanism that rejects self-pollen 2 , 3 to avoid inbreeding depression. Interspecific barriers restrain breeding between species and often follow the SI × self-compatible (SC) rule, that is, interspecific pollen is unilaterally incompatible (UI) on SI pistils but unilaterally compatible (UC) on SC pistils 1 , 4 – 6 . The molecular mechanisms underlying SI, UI, SC and UC and their interconnections in the Brassicaceae remain unclear. Here we demonstrate that the SI pollen determinant S -locus cysteine-rich protein/ S -locus protein 11 (SCR/SP11) 2 , 3 or a signal from UI pollen binds to the SI female determinant S -locus receptor kinase (SRK) 2 , 3 , recruits FERONIA (FER) 7 – 9 and activates FER-mediated reactive oxygen species production in SI stigmas 10 , 11 to reject incompatible pollen. For compatible responses, diverged pollen coat protein B-class 12 – 14 from SC and UC pollen differentially trigger nitric oxide, nitrosate FER to suppress reactive oxygen species in SC stigmas to facilitate pollen growth in an intraspecies-preferential manner, maintaining species integrity. Our results show that SRK and FER integrate mechanisms underlying intraspecific and interspecific barriers and offer paths to achieve distant breeding in Brassicaceae crops. A signalling mechanism ensuring intraspecies and interspecies reproductive barriers in flowering plants is uncovered.

The quantum anomalous Hall effect in layered antiferromagnet MnBi 2 Te 4 harbors a rich interplay between magnetism and topology, holding a significant promise for low-power electronic devices and topological antiferromagnetic spintronics. In recent years, MnBi 2 Te 4 has garnered considerable attention as the only known material to exhibit the antiferromagnetic quantum anomalous Hall effect. However, this field faces significant challenges as the quantization at zero magnetic field depending critically on fabricating high-quality devices. In this article, we introduce a straightforward yet effective method to mitigate the detrimental effect of the standard fabrication on MnBi 2 Te 4 by depositing an AlO x layer on the surface before fabrication. Optical contrast and magnetotransport measurements on over 50 MnBi 2 Te 4 demonstrate that AlO x can effectively preserve the pristine states of the devices. Surprisingly, we find this simple method can significantly enhance the anomalous Hall effect towards quantization, which resolves a longstanding challenge in the field of MnBi 2 Te 4 . Scaling relation analysis further reveals the intrinsic mechanism of anomalous Hall effect dominated by Berry curvature at various magnetic configuration. By tuning the gate voltage, we uncover a gate independent magnetism in odd-layer MnBi 2 Te 4 devices. Our experiments not only pave the way for the fabrication of high-quality dissipationless transport devices, but also advance the investigation of exotic topological quantum phenomena in 2D materials. The challenges in reliably reproducing the quantum anomalous Hall effect have emerged as a major bottleneck for MnBi 2 Te 4 . Here, the authors develop a fabrication method to address this, paving the way for the fabrication of high-quality dissipationless topological transport devices.

Being the first intrinsic antiferromagnetic (AFM) topological insulator (TI), MnBi 2 Te 4 is argued to be a topological axion state in its even-layer form due to the antiparallel magnetization between the top and bottom layers. Here we combine both transport and scanning microwave impedance microscopy (sMIM) to investigate such axion state in atomically thin MnBi 2 Te 4 with even-layer thickness at zero magnetic field. While transport measurements show a zero Hall plateau signaturing the axion state, sMIM uncovers an unexpected edge state raising questions regarding the nature of the “axion state”. Based on our model calculation, we propose that the edge state of even-layer MnBi 2 Te 4 at zero field is derived from gapped helical edge states of the quantum spin Hall effect with time-reversal-symmetry breaking, when a crossover from a three-dimensional TI MnBi 2 Te 4 to a two-dimensional TI occurs. Our finding thus signifies the richness of topological phases in MnB 2 Te 4 that has yet to be fully explored. Previous work has reported an axion insulator state in a layered topological antiferromagnet MnBi 2 Te 4 evidenced by a zero Hall plateau. Here, in addition to the zero Hall plateau, the authors identify edge states in transport measurements at zero field which challenge the axion insulator interpretation.

Lightweight object detection algorithms play a paramount role in unmanned aerial vehicles (UAVs) remote sensing. However, UAV remote sensing requires target detection algorithms to have higher inference speeds and greater accuracy in detection. At present, most lightweight object detection algorithms have achieved fast inference speed, but their detection precision is not satisfactory. Consequently, this paper presents a refined iteration of the lightweight object detection algorithm to address the above issues. The MobileNetV3 based on the efficient channel attention (ECA) module is used as the backbone network of the model. In addition, the focal and efficient intersection over union (FocalEIoU) is used to improve the regression performance of the algorithm and reduce the false-negative rate. Furthermore, the entire model is pruned using the convolution kernel pruning method. After pruning, model parameters and floating-point operations (FLOPs) on VisDrone and DIOR datasets are reduced to 1.2 M and 1.5 M and 6.2 G and 6.5 G, respectively. The pruned model achieves 49 frames per second (FPS) and 44 FPS inference speeds on Jetson AGX Xavier for VisDrone and DIOR datasets, respectively. To fully exploit the performance of the pruned model, a plug-and-play structural re-parameterization fine-tuning method is proposed. The experimental results show that this fine-tuned method improves mAP@0.5 and mAP@0.5:0.95 by 0.4% on the VisDrone dataset and increases mAP@0.5:0.95 by 0.5% on the DIOR dataset. The proposed algorithm outperforms other mainstream lightweight object detection algorithms (except for FLOPs higher than SSDLite and mAP@0.5 Below YOLOv7 Tiny) in terms of parameters, FLOPs, mAP@0.5, and mAP@0.5:0.95. Furthermore, practical validation tests have also demonstrated that the proposed algorithm significantly reduces instances of missed detection and duplicate detection.

The van der Waals antiferromagnetic topological insulator MnBi 2 Te 4 represents a promising platform for exploring the layer-dependent magnetism and topological states of matter. Recently observed discrepancies between magnetic and transport properties have aroused controversies concerning the topological nature of MnBi 2 Te 4 in the ground state. In this article, we demonstrate that fabrication can induce mismatched even-odd layer dependent magnetotransport in few-layer MnBi 2 Te 4 . We perform a comprehensive study of the magnetotransport properties in 6- and 7-septuple-layer MnBi 2 Te 4 , and reveal that both even- and odd-number-layer device can show zero Hall plateau phenomena in zero magnetic field. Importantly, a statistical survey of the optical contrast in more than 200 MnBi 2 Te 4 flakes reveals that the zero Hall plateau in odd-number-layer devices arises from the reduction of the effective thickness during the fabrication, a factor that was rarely noticed in previous studies of 2D materials. Our finding not only provides an explanation to the controversies regarding the discrepancy of the even-odd layer dependent magnetotransport in MnBi 2 Te 4 , but also highlights the critical issues concerning the fabrication and characterization of 2D material devices. MnBi2Te4 is an antiferromagnetic topological insulator. This combination of magnetic ordering and topological properties has resulted in intense interest, however, like many van der Waals materials, experimental results are hampered by fabrication difficulties. Here, Li, Wang, Lian et al. show that the fabrication process itself can result in mismatched thickness dependence of magneto-transport measurements. ‘