Experimental test of the Crooks fluctuation theorem in a single nuclear spin

We experimentally test the Crooks fluctuation theorem in a quantum spin system. Our results show that the Crooks fluctuation theorem is valid for different speeds of the nonequilibrium processes and under various effective temperatures. Work is not an observable in quantum systems, which makes tests of quantum thermodynamic theorems challenging. In this work, we developed high-fidelity single-shot readouts of a single nuclear spin in diamond and implemented the two-point work measurement protocol, enabling a direct experimental test of the Crooks fluctuation theorem. Our results provide a quantum insight into fluctuations and the methods we developed can be utilized to study other quantum thermodynamic theorems

Zero-knowledge Proof Meets Machine Learning in Verifiability: A Survey

With the rapid advancement of artificial intelligence technology, the usage of machine learning models is gradually becoming part of our daily lives. High-quality models rely not only on efficient optimization algorithms but also on the training and learning processes built upon vast amounts of data and computational power. However, in practice, due to various challenges such as limited computational resources and data privacy concerns, users in need of models often cannot train machine learning models locally. This has led them to explore alternative approaches such as outsourced learning and federated learning. While these methods address the feasibility of model training effectively, they introduce concerns about the trustworthiness of the training process since computations are not performed locally. Similarly, there are trustworthiness issues associated with outsourced model inference. These two problems can be summarized as the trustworthiness problem of model computations: How can one verify that the results computed by other participants are derived according to the specified algorithm, model, and input data? To address this challenge, verifiable machine learning (VML) has emerged. This paper presents a comprehensive survey of zero-knowledge proof-based verifiable machine learning (ZKP-VML) technology. We first analyze the potential verifiability issues that may exist in different machine learning scenarios. Subsequently, we provide a formal definition of ZKP-VML. We then conduct a detailed analysis and classification of existing works based on their technical approaches. Finally, we discuss the key challenges and future directions in the field of ZKP-based VML

Experimental test of the Jarzynski equality in a single spin-1 system using high-fidelity single-shot readouts

The Jarzynski equality (JE), which connects the equilibrium free energy with non-equilibrium work statistics, plays a crucial role in quantum thermodynamics. Although practical quantum systems are usually multi-level systems, most tests of the JE were executed in two-level systems. A rigorous test of the JE by directly measuring the work distribution of a physical process in a high-dimensional quantum system remains elusive. Here, we report an experimental test of the JE in a single spin-1 system. We realized nondemolition projective measurement of this three-level system via cascading high-fidelity single-shot readouts and directly measured the work distribution utilizing the two-point measurement protocol. The validity of the JE was verified from the non-adiabatic to adiabatic zone and under different effective temperatures. Our work puts the JE on a solid experimental foundation and makes the NV center system a mature toolbox to perform advanced experiments of stochastic quantum thermodynamics

Experimental study on the principle of minimal work fluctuations

The central quantity in the celebrated quantum Jarzynski equality is $e^{-\beta W}$, where $W$ is work and $\beta$ is the inverse temperature. The impact of quantum randomness on the fluctuations of $e^{-\beta W}$ and hence on the predictive power of the Jarzynski estimator is an important problem. Working on a single nitrogen-vacancy center in diamond and riding on an implementation of two-point measurement of non-equilibrium work with single-shot readout, we have conducted a direct experimental investigation of the relationship between the fluctuations of $e^{-\beta W}$ and adiabaticity of non-equilibrium work protocols. It is observed that adiabatic processes minimize the variance of $e^{-\beta W}$, thus verifying an early theoretical concept, the so-called principle of minimal work fluctuations. Furthermore, it is experimentally demonstrated that shortcuts-to-adiabaticity control can be exploited to minimize the variance of $e^{-\beta W}$ in fast work protocols. Our work should stimulate further experimental studies of quantum effects on the bias and error in the estimates of free energy differences based on the Jarzynski equality

Third-order exceptional line in a nitrogen-vacancy spin system

The exceptional points (EPs) aroused from the non-Hermiticity bring rich phenomena, such as exceptional nodal topologies, unidirectional invisibility, single-mode lasing, sensitivity enhancement and energy harvesting. Isolated high-order EPs have been observed to exhibit richer topological characteristics and better performance in sensing over 2nd-order EPs. Recently, high-order EP geometries, such as lines or rings formed entirely by high order EPs, are predicted to provide richer phenomena and advantages over stand-alone high-order EPs. However, experimental exploration of high-order EP geometries is hitherto beyond reach due to the demand of more degrees of freedom in the Hamiltonian's parameter space or a higher level of symmetries. Here we report the observation of the third-order exceptional line (EL) at the atomic scale. By introducing multiple symmetries, the emergence of the third-order EL has been successfully realized with a single electron spin of nitrogen-vacancy center in diamond. Furthermore, the behaviors of the EP structure under different symmetries are systematically investigated. The symmetries are shown to play essential roles in the occurrence of high-order EPs and the related EP geometries. Our work opens a new avenue to explore high-order EP-related topological physics at the atomic scale and to the potential applications of high-order EPs in quantum technologies

Assessment of Construction Workers’ Spontaneous Mental Fatigue Based on Non-Invasive and Multimodal In-Ear EEG Sensors

Construction activities are often conducted in outdoor and harsh environments and involve long working hours and physical and mental labor, which can lead to significant mental fatigue among workers. This study introduces a novel and non-invasive method for monitoring and assessing mental fatigue in construction workers. Based on cognitive neuroscience theory, we analyzed the neurophysiological mapping of spontaneous mental fatigue and developed multimodal in-ear sensors specifically designed for construction workers. These sensors enable real-time and continuous integration of neurophysiological signals. A cognitive experiment was conducted to validate the proposed mental fatigue assessment method. Results demonstrated that all selected supervised classification models can accurately identify mental fatigue by using the recorded neurophysiological data, with evaluation metrics exceeding 80%. The long short-term memory model achieved an average accuracy of 92.437%. This study offers a theoretical framework and a practical approach for assessing the mental fatigue of on-site workers and provides a basis for the proactive management of occupational health and safety on construction sites

Ternary composite phase change materials (PCMs) towards low phase separation and supercooling: eutectic behaviors and application

Salt hydrates have been used as phase change materials (PCMs) for various types of Thermal Energy Storage (TES) especially for cold storage. In this project, a novel composite phase change material (PCM) consisted of mixed solution of inorganic salt and organic salt was developed and characterized. Firstly, the PCM solutions containing sodium formate, potassium chloride and water with various weight percentage were evaluated to understand their solidification temperature, melting temperature, the supercooling degree and the latent heat. Then a PCM with mass fractions at weight percentages of 22%/12%/66% with better performance was selected for further study to restrain the supercooling. Different gelling agents and nucleate agents were employed in this PCM. The results show that the addition of 0.6 wt% xanthan gum can effectively prevent the phase separation and leakage, while 0.6 wt% of nano-TiO2 is the best nucleating agent since the supercooling can be reduced to 2.6 °C, which is 67.9% lower than that of the original PCM without any nucleating agent. Finally, the novel PCM was tested for frozen food storage application, in which the food temperature could be maintained below -18 °C for over 10 hours in the insulated box. This indicated the suitability of developed PCM for frozen food storage and transportation

Cryo-EM structures of lipopolysaccharide transporter LptB2FGC in lipopolysaccharide or AMP-PNP-bound states reveal its transport mechanism

Lipopolysaccharides (LPS) of Gram-negative bacteria are critical for the defence against cytotoxic substances and must be transported from the inner membrane (IM) to the outer membrane (OM) through a bridge formed by seven membrane proteins (LptBFGCADE). The IM component LptB2FG powers the process through a yet unclarified mechanism. Here we report three high-resolution cryo-EM structures of LptB2FG alone and complexed with LptC (LptB2FGC), trapped in either the LPS- or AMP-PNP-bound state. The structures reveal conformational changes between these states and substrate binding with or without LptC. We identify two functional transmembrane arginine-containing loops interacting with the bound AMP-PNP and elucidate allosteric communications between the domains. AMP-PNP binding induces an inward rotation and shift of the transmembrane helices of LptFG and LptC to tighten the cavity, with the closure of two lateral gates, to eventually expel LPS into the bridge. Functional assays reveal the functionality of the LptF and LptG periplasmic domains. Our findings shed light on the LPS transport mechanism

Genomic Analyses Reveal Mutational Signatures and Frequently Altered Genes in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets

Trunk Borer Identification Based on Convolutional Neural Networks

The trunk borer is a great danger to forests because of its strong concealment, long lag and great destructiveness. In order to improve the early monitoring ability of trunk borers, the representative Agrilus planipennis Fairmaire was selected as the research object. The convolutional neural network named TrunkNet was designed to identify the activity sounds of Agrilus planipennis Fairmaire larvae. The activity sounds were recorded as vibration signals in audio form. The detector was used to collect the activity sounds of Agrilus planipennis Fairmaire larvae in the wood segments and some typical outdoor noise. The vibration signal pulse duration is short, random and high energy. TrunkNet was designed to train and identify vibration signals of Agrilus planipennis Fairmaire. Over the course of the experiment, the test accuracy of TrunkNet was 96.89%, while MobileNet_V2, ResNet18 and VGGish showed 84.27%, 79.37% and 70.85% accuracy, respectively. TrunkNet based on the convolutional neural network can provide technical support for the automatic monitoring and early warning of the stealthy tree trunk borers. The work of this study is limited to a single pest. The experiment will further focus on the applicability of the network to other pests in the future