Amplitude-robust metastructure with combined bistable and monostable mechanisms for simultaneously enhanced vibration suppression and energy harvesting

This Letter reports an amplitude-robust nonlinear dual-functional metastructure that combines bistable and monostable-hardening mechanisms in the local resonators for simultaneous energy harvesting and vibration suppression. The concept is verified by experiments using a primary beam with six pairs of piezoelectric cantilevered oscillators and numerical analyses using a fully coupled electromechanical model for varying base vibration acceleration and load resistance. The results show that the design offers a wide bandgap at high accelerations, attenuation of transmission peaks, and generation of power over a broad bandwidth, outperforming its linear, pure bistable, and pure monostable counterparts. The dual-functional capabilities are further quantitatively assessed by using a weighted index that reflects both the vibration and power generation behaviors. This study demonstrates opportunities in development of the smart nonlinear metastructures for simultaneous vibration suppression and energy harvesting

High-efficiency robust perovskite solar cells on ultrathin flexible substrates.

Wide applications of personal consumer electronics have triggered tremendous need for portable power sources featuring light-weight and mechanical flexibility. Perovskite solar cells offer a compelling combination of low-cost and high device performance. Here we demonstrate high-performance planar heterojunction perovskite solar cells constructed on highly flexible and ultrathin silver-mesh/conducting polymer substrates. The device performance is comparable to that of their counterparts on rigid glass/indium tin oxide substrates, reaching a power conversion efficiency of 14.0%, while the specific power (the ratio of power to device weight) reaches 1.96 kW kg(-1), given the fact that the device is constructed on a 57-μm-thick polyethylene terephthalate based substrate. The flexible device also demonstrates excellent robustness against mechanical deformation, retaining >95% of its original efficiency after 5,000 times fully bending. Our results confirmed that perovskite thin films are fully compatible with our flexible substrates, and are thus promising for future applications in flexible and bendable solar cells

Optimal design and control of permanent magnet assisted dual rotor motor

As high-performance motors, permanent magnet motors are widely used in a wide range of applications. It has become a consensus to mine reluctance torque in permanent magnet motors. The combination of permanent magnet motors and reluctance motors to generate higher output torque is one of the hotspots in motor research. A dual-rotor motor can be formed by connecting a coaxial connector or a concentric end disk, which can make the motor generate higher torque. However, although the motor torque has been improved, the cogging torque still affects the output torque of the motor. This paper describes a method to reduce the cogging torque of the permanent magnet rotor of the permanent magnet-assisted double rotor motor. By analyzing the motor power equation, it is concluded that the pole arc coefficient, the thickness of the magnetic steel, the length of the air gap, and the slot width of the stator have four influences on the teeth. For the parameters of the slot torque, the upper and lower limits of the parameter value are obtained according to the size of the motor. A certain parameter is taken as a fixed value, and the remaining parameters are uniformly valued. Use parametric scanning to determine the optimal value range of the parameter, and use Maxwell for parameterization. Simulation and analysis show that the cogging torque of the motor is reduced by 90% and the torque ripple is reduced by 50%. In order to simplify the motor control system, this paper designs a fuzzy controller based on granular functions, and the fuzzy rules of the fuzzy controller are to perform feature sampling and fit the response function, eliminating fuzzification and defuzzification, improving the response speed of fuzzy control, and simplifying the control system

Graph Transformer for Recommendation

This paper presents a novel approach to representation learning in recommender systems by integrating generative self-supervised learning with graph transformer architecture. We highlight the importance of high-quality data augmentation with relevant self-supervised pretext tasks for improving performance. Towards this end, we propose a new approach that automates the self-supervision augmentation process through a rationale-aware generative SSL that distills informative user-item interaction patterns. The proposed recommender with Graph TransFormer (GFormer) that offers parameterized collaborative rationale discovery for selective augmentation while preserving global-aware user-item relationships. In GFormer, we allow the rationale-aware SSL to inspire graph collaborative filtering with task-adaptive invariant rationalization in graph transformer. The experimental results reveal that our GFormer has the capability to consistently improve the performance over baselines on different datasets. Several in-depth experiments further investigate the invariant rationale-aware augmentation from various aspects. The source code for this work is publicly available at: https://github.com/HKUDS/GFormer.Comment: Accepted by SIGIR'202

Molecular Characterization of Reduced Susceptibility to Biocides in Clinical Isolates of Acinetobacter baumannii

Active efflux is regarded as a common mechanism for antibiotic and biocide resistance. However, the role of many drug efflux pumps in biocide resistance in Acinetobacter baumannii remains unknown. Using biocide-resistant A. baumannii clinical isolates, we investigated the incidence of 11 known/putative antimicrobial resistance efflux pump genes (adeB, adeG, adeJ, adeT1, adeT2, amvA, abeD, abeM, qacE, qacEΔ1, and aceI) and triclosan target gene fabI through PCR and DNA sequencing. Reverse transcriptase quantitative PCR was conducted to assess the correlation between the efflux pump gene expression and the reduced susceptibility to triclosan or chlorhexidine. The A. baumannii isolates displayed high levels of reduced susceptibility to triclosan, chlorhexidine, benzalkonium, hydrogen peroxide, and ethanol. Most tested isolates were resistant to multiple antibiotics. Efflux resistance genes were widely distributed and generally expressed in A. baumannii. Although no clear relation was established between efflux pump gene expression and antibiotic resistance or reduced biocide susceptibility, triclosan non-susceptible isolates displayed relatively increased expression of adeB and adeJ whereas chlorhexidine non-susceptible isolates had increased abeM and fabI gene expression. Increased expression of adeJ and abeM was also demonstrated in multiple antibiotic resistant isolates. Exposure of isolates to subinhibitory concentrations of triclosan or chlorhexidine induced gene expression of adeB, adeG, adeJ and fabI, and adeB, respectively. A point mutation in FabI, Gly95Ser, was observed in only one triclosan-resistant isolate. Multiple sequence types with the major clone complex, CC92, were identified in high level triclosan-resistant isolates. Overall, this study showed the high prevalence of antibiotic and biocide resistance as well as the complexity of intertwined resistance mechanisms in clinical isolates of A. baumannii, which highlights the importance of antimicrobial stewardship and resistance surveillance in clinics

Genomic regions, cellular components and gene regulatory basis underlying pod length variations in cowpea (V. unguiculata L. Walp).

Cowpea (V. unguiculata L. Walp) is a climate resilient legume crop important for food security. Cultivated cowpea (V. unguiculata L) generally comprises the bushy, short-podded grain cowpea dominant in Africa and the climbing, long-podded vegetable cowpea popular in Asia. How selection has contributed to the diversification of the two types of cowpea remains largely unknown. In the current study, a novel genotyping assay for over 50 000 SNPs was employed to delineate genomic regions governing pod length. Major, minor and epistatic QTLs were identified through QTL mapping. Seventy-two SNPs associated with pod length were detected by genome-wide association studies (GWAS). Population stratification analysis revealed subdivision among a cowpea germplasm collection consisting of 299 accessions, which is consistent with pod length groups. Genomic scan for selective signals suggested that domestication of vegetable cowpea was accompanied by selection of multiple traits including pod length, while the further improvement process was featured by selection of pod length primarily. Pod growth kinetics assay demonstrated that more durable cell proliferation rather than cell elongation or enlargement was the main reason for longer pods. Transcriptomic analysis suggested the involvement of sugar, gibberellin and nutritional signalling in regulation of pod length. This study establishes the basis for map-based cloning of pod length genes in cowpea and for marker-assisted selection of this trait in breeding programmes

Algorithm of face anti-spoofing based on pseudo-negative features generation

IntroductionDespite advancements in face anti-spoofing technology, attackers continue to pose challenges with their evolving deceptive methods. This is primarily due to the increased complexity of their attacks, coupled with a diversity in presentation modes, acquisition devices, and prosthetic materials. Furthermore, the scarcity of negative sample data exacerbates the situation by causing domain shift issues and impeding robust generalization. Hence, there is a pressing need for more effective cross-domain approaches to bolster the model’s capability to generalize across different scenarios.MethodsThis method improves the effectiveness of face anti-spoofing systems by analyzing pseudo-negative sample features, expanding the training dataset, and boosting cross-domain generalization. By generating pseudo-negative features with a new algorithm and aligning these features with the use of KL divergence loss, we enrich the negative sample dataset, aiding the training of a more robust feature classifier and broadening the range of attacks that the system can defend against.ResultsThrough experiments on four public datasets (MSU-MFSD, OULU-NPU, Replay-Attack, and CASIA-FASD), we assess the model’s performance within and across datasets by controlling variables. Our method delivers positive results in multiple experiments, including those conducted on smaller datasets.DiscussionThrough controlled experiments, we demonstrate the effectiveness of our method. Furthermore, our approach consistently yields favorable results in both intra-dataset and cross-dataset evaluations, thereby highlighting its excellent generalization capabilities. The superior performance on small datasets further underscores our method’s remarkable ability to handle unseen data beyond the training set

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

Large Language Models (LLMs), like ChatGPT, have demonstrated vast potential but also introduce challenges related to content constraints and potential misuse. Our study investigates three key research questions: (1) the number of different prompt types that can jailbreak LLMs, (2) the effectiveness of jailbreak prompts in circumventing LLM constraints, and (3) the resilience of ChatGPT against these jailbreak prompts. Initially, we develop a classification model to analyze the distribution of existing prompts, identifying ten distinct patterns and three categories of jailbreak prompts. Subsequently, we assess the jailbreak capability of prompts with ChatGPT versions 3.5 and 4.0, utilizing a dataset of 3,120 jailbreak questions across eight prohibited scenarios. Finally, we evaluate the resistance of ChatGPT against jailbreak prompts, finding that the prompts can consistently evade the restrictions in 40 use-case scenarios. The study underscores the importance of prompt structures in jailbreaking LLMs and discusses the challenges of robust jailbreak prompt generation and prevention

Evolving Walkability of Major Cities in the People's Republic of China

Context: Walkability is an important element for assessing urban sustainability. There are increased concerns that more cities in the People's Republic of China (PRC) have become less walkable. Objectives: We aim to develop a composite walkability index. We intend to use it to evaluate the spatio-temporal evolution of the walkability of PRC cities in the context of the rapid urbanization. Methods: We developed a comprehensive walkability index that integrates five aspects of the urban built environment: dwelling density, street connectivity, land-use mix, access to public transit, and elevation variation. Using Shanghai, Hangzhou, Chongqing, and Lanzhou as cases, we evaluated the spatio-temporal patterns and changes of walkability in the context of rapid urban expansion. Results: All four cities expanded their urban land from 1990 to 2010, but that there was a higher expansion rate in 2000-2010 than in 1990-2000. For inner cities, Shanghai had the highest average walkability index, whereas Lanzhou held the lowest. In 2000-2010, however, the inner cities of Hangzhou, Chongqing, and Lanzhou and the entire cities of Shanghai and Chongqing increased their walkability index, whereas the inner city of Shanghai had decreased walkability. Furthermore, while inner cities of Shanghai and Hangzhou experienced decreased or stable walkability, inner cities of Lanzhou and Chongqing enjoyed moderate to high increases in walkability. Conclusions: The spatiotemporal changes in walkability seem to be directly associated with governmental policies at both central and local levels. The walkability index method can be widely implemented for any urban landscape because of its comprehensiveness, simplicity, and flexibility

Method to Evaluate the Kinetics of Bainite Transformation in Low-Temperature Nanobainitic Steel Using Thermal Dilatation Curve Analysis

The aim of this work was to develop a method to evaluate the kinetics of bainite transformation by theoretical deduction and thermal dilatation curve analysis. A Gleeble-3500 thermomechanical simulator and dilatometer (DIL805A) were employed to study the isothermal transformation in deformed (360 ∘ C , 600 ∘ C , and 860 ∘ C ) and undeformed conditions. The thermal dilatation information during isothermal transformation was recorded, and the dilatation curves were well smoothed. By taking a derivative of the dilation curve with respect to the transformation time, the peak time of transformation rate (PTTR) was obtained, which can serve as the essence of isothermal transformation time. The relative change of length ( Δ L / L ) due to phase transformation was theoretically deduced, and the effect of temperature was taken into consideration. Combing experimental data, the volume fraction of bainite in isothermal transformation was calculated. Making a graph of volume fraction versus PTTR was a good method to evaluate the kinetics of bainitic transformation clearly and concisely which facilitated optimization of the preparation technique for low-temperature nanobainitic steel