941 research outputs found
GPT4Battery: An LLM-driven Framework for Adaptive State of Health Estimation of Raw Li-ion Batteries
State of health (SOH) is a crucial indicator for assessing the degradation
level of batteries that cannot be measured directly but requires estimation.
Accurate SOH estimation enhances detection, control, and feedback for Li-ion
batteries, allowing for safe and efficient energy management and guiding the
development of new-generation batteries. Despite the significant progress in
data-driven SOH estimation, the time and resource-consuming degradation
experiments for generating lifelong training data pose a challenge in
establishing one large model capable of handling diverse types of Li-ion
batteries, e.g., cross-chemistry, cross-manufacturer, and cross-capacity.
Hence, this paper utilizes the strong generalization capability of large
language model (LLM) to proposes a novel framework for adaptable SOH estimation
across diverse batteries. To match the real scenario where unlabeled data
sequentially arrives in use with distribution shifts, the proposed model is
modified by a test-time training technique to ensure estimation accuracy even
at the battery's end of life. The validation results demonstrate that the
proposed framework achieves state-of-the-art accuracy on four widely recognized
datasets collected from 62 batteries. Furthermore, we analyze the theoretical
challenges of cross-battery estimation and provide a quantitative explanation
of the effectiveness of our method
Traveling wave phenomena in a nonlocal dispersal predator-prey system with the Beddington-DeAngelis functional response and harvesting
This paper is devoted to studying the existence and nonexistence of traveling wave solution for a nonlocal dispersal delayed predator-prey system with the Beddington-DeAngelis functional response and harvesting. By constructing the suitable upper-lower solutions and applying Schauder\u27s fixed point theorem, we show that there exists a positive constant c∗ such that the system possesses a traveling wave solution for any given c\u3ec∗. Moreover, the asymptotic behavior of traveling wave solution at infinity is obtained by the contracting rectangles method. The existence of traveling wave solution for c=c∗ is established by means of Corduneanu\u27s theorem. The nonexistence of traveling wave solution in the case of
Intergenerational Test Generation for Natural Language Processing Applications
The development of modern NLP applications often relies on various benchmark
datasets containing plenty of manually labeled tests to evaluate performance.
While constructing datasets often costs many resources, the performance on the
held-out data may not properly reflect their capability in real-world
application scenarios and thus cause tremendous misunderstanding and monetary
loss. To alleviate this problem, in this paper, we propose an automated test
generation method for detecting erroneous behaviors of various NLP
applications. Our method is designed based on the sentence parsing process of
classic linguistics, and thus it is capable of assembling basic grammatical
elements and adjuncts into a grammatically correct test with proper oracle
information. We implement this method into NLPLego, which is designed to fully
exploit the potential of seed sentences to automate the test generation.
NLPLego disassembles the seed sentence into the template and adjuncts and then
generates new sentences by assembling context-appropriate adjuncts with the
template in a specific order. Unlike the taskspecific methods, the tests
generated by NLPLego have derivation relations and different degrees of
variation, which makes constructing appropriate metamorphic relations easier.
Thus, NLPLego is general, meaning it can meet the testing requirements of
various NLP applications. To validate NLPLego, we experiment with three common
NLP tasks, identifying failures in four state-of-art models. Given seed tests
from SQuAD 2.0, SST, and QQP, NLPLego successfully detects 1,732, 5301, and
261,879 incorrect behaviors with around 95.7% precision in three tasks,
respectively
Unveiling the nucleon tensor charge at Jefferson Lab: A study of the SoLID case
Future experiments at the Jefferson Lab 12 GeV upgrade, in particular, the
Solenoidal Large Intensity Device (SoLID), aim at a very precise data set in
the region where the partonic structure of the nucleon is dominated by the
valence quarks. One of the main goals is to constrain the quark transversity
distributions. We apply recent theoretical advances of the global QCD
extraction of the transversity distributions to study the impact of future
experimental data from the SoLID experiments. Especially, we develop a simple
strategy based on the Hessian matrix analysis that allows one to estimate the
uncertainties of the transversity quark distributions and their tensor charges
extracted from SoLID data simulation. We find that the SoLID measurements with
the proton and the effective neutron targets can improve the precision of the
u- and d-quark transversity distributions up to one order of magnitude in the
range 0.05 < x < 0.6.Comment: 11 pages, 3 figures, published on Physics Letters
Prognostic nomogram for bladder cancer with brain metastases: a National Cancer Database analysis.
BACKGROUND: This study aimed to establish and validate a nomogram for predicting brain metastasis in patients with bladder cancer (BCa) and assess various treatment modalities using a primary cohort comprising 234 patients with clinicopathologically-confirmed BCa from 2004 to 2015 in the National Cancer Database.
METHODS: Machine learning method and Cox model were used for nomogram construction. For BCa patients with brain metastasis, surgery of the primary site, chemotherapy, radiation therapy, palliative care, brain confinement of metastatic sites, and the Charlson/Deyo Score were predictive features identified for building the nomogram.
RESULTS: For the original 169 patients considered in the model, the areas under the receiver operating characteristic curve (AUC) were 0.823 (95% CI 0.758-0.889, P \u3c 0.001) and 0.854 (95% CI 0.785-0.924, P \u3c 0.001) for 0.5- and 1-year overall survival respectively. In the validation cohort, the nomogram displayed similar AUCs of 0.838 (95% CI 0.738-0.937, P \u3c 0.001) and 0.809 (95% CI 0.680-0.939, P \u3c 0.001), respectively. The high and low risk groups had median survivals of 1.91 and 5.09 months for the training cohort and 1.68 and 8.05 months for the validation set, respectively (both P \u3c 0.0001).
CONCLUSIONS: Our prognostic nomogram provides a useful tool for overall survival prediction as well as assessing the risk and optimal treatment for BCa patients with brain metastasis
Power Allocation Strategies for Secure Spatial Modulation
In this paper, power allocation (PA) strategies in secure spatial modulation networks, are investigated under the total power constraint. Considering that there is no closed-form expression for secrecy rate (SR), an approximate closed-form expression of SR is derived as an efficient metric to optimize PA factor, which can greatly reduce the computation complexity. Based on this expression, a convex optimization (CO) method of maximizing SR (Max-SR) is proposed accordingly. Furthermore, a method of maximizing the product of signal-to-leakage and noise ratio (SLNR) and artificial noise-to-leakage and noise ratio (Max-P-SAN) is proposed to provide an analytic solution for PA factor with extremely low complexity. Simulation results demonstrate that the SR performance of the proposed CO method is close to that of the optimal PA strategy with exhaustive search, and is better than that of Max-P-SAN in the high signal-to-noise ratio (SNR) region. However, in the low and medium SNR regions, the proposed Max-P-SAN slightly outperforms the proposed CO scheme in terms of SR performance
Effects of Excitation Angle on Air-Puff-Stimulated Surface Acoustic Wave-Based Optical Coherence Elastography (SAW-OCE)
Increased stiffness of tissues has been recognised as a diagnostic feature of pathologies. Tissue stiffness characterisation usually involves the detection of tissue response from mechanical stimulation. Air-puff optical coherence elastography (OCE) can generate impulse surface acoustic waves (SAWs) on tissue surface without contact and evaluate the mechanical properties of tissue. This study endeavours to explore the optimal excitation angle for air-puff OCE, a parameter that lacks standardisation at present, by investigating the relationship between the frequency bandwidth and peak-to-peak signal-to-noise ratio (SNR) of SAWs for different excitation angles (relative to the normal surface) of air-puff on the sample, from 5° to 85°, with an interval of 5° applied on the phantom. Due to the unevenness of human hands, 20°, 45° and 70° angles were employed for human skin (10 healthy adults). The results show that a smaller excitation angle could produce higher wave frequency bandwidth; a 5° angle generated an SAW with 1747 Hz frequency bandwidth, while an 85° angle produced an SAW with 1205 Hz. Significant differences were not shown in peak-to-peak SNR comparison between 5° and 65° on the phantom, but between 65° and 85° at the excitation position, a reduction of 48.6% was observed. Furthermore, the group velocity of the SAWs was used to evaluate the bulk Young’s modulus of the human tissue. The outcomes could provide essential guidance for air-puff-based elastography studies in clinical applications and future tissue research.<br/
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