Spatial variation in aragonite saturation state and the influencing factors in Jiaozhou Bay, China

Both natural processes and human activities affect seawater calcium carbonate saturation state (Ωarag), while the mechanisms are still far from being clearly understood. This study analysed the seawater surface Ωarag during summer and winter in Jiaozhou Bay (JZB), China, based on two cruises observations performed in January and June 2017. The ranges of Ωarag values were 1.55~2.92 in summer and 1.62~2.15 in winter. Regression analyses were conducted to identify the drivers of the change of Ωarag distribution, and then the relative contributions of temperature, mixing processes and biological processes to the spatial differences in Ωarag were evaluated by introducing the difference between total alkalinity (TA) and dissolved inorganic carbon (DIC) as a proxy for Ωarag. The results showed that biological processes were the main factor affecting the spatial differences in Ωarag, with relative contributions of 70% in summer and 50% in winter. The contributions of temperature (25% in summer and 20% in winter) and the mixing processes (5% in summer and 30% in winter) were lower. The increasing urbanization in offshore areas can further worsen acidification, therefore environmental protection in both offshore and onshore is needed

Enhancing Large Language Model with Decomposed Reasoning for Emotion Cause Pair Extraction

Emotion-Cause Pair Extraction (ECPE) involves extracting clause pairs representing emotions and their causes in a document. Existing methods tend to overfit spurious correlations, such as positional bias in existing benchmark datasets, rather than capturing semantic features. Inspired by recent work, we explore leveraging large language model (LLM) to address ECPE task without additional training. Despite strong capabilities, LLMs suffer from uncontrollable outputs, resulting in mediocre performance. To address this, we introduce chain-of-thought to mimic human cognitive process and propose the Decomposed Emotion-Cause Chain (DECC) framework. Combining inducing inference and logical pruning, DECC guides LLMs to tackle ECPE task. We further enhance the framework by incorporating in-context learning. Experiment results demonstrate the strength of DECC compared to state-of-the-art supervised fine-tuning methods. Finally, we analyze the effectiveness of each component and the robustness of the method in various scenarios, including different LLM bases, rebalanced datasets, and multi-pair extraction.Comment: 13 pages, 5 figure

IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance

Among existing Neural Architecture Search methods, DARTS is known for its efficiency and simplicity. This approach applies continuous relaxation of network representation to construct a weight-sharing supernet and enables the identification of excellent subnets in just a few GPU days. However, performance collapse in DARTS results in deteriorating architectures filled with parameter-free operations and remains a great challenge to the robustness. To resolve this problem, we reveal that the fundamental reason is the biased estimation of the candidate importance in the search space through theoretical and experimental analysis, and more precisely select operations via information-based measurements. Furthermore, we demonstrate that the excessive concern over the supernet and inefficient utilization of data in bi-level optimization also account for suboptimal results. We adopt a more realistic objective focusing on the performance of subnets and simplify it with the help of the information-based measurements. Finally, we explain theoretically why progressively shrinking the width of the supernet is necessary and reduce the approximation error of optimal weights in DARTS. Our proposed method, named IS-DARTS, comprehensively improves DARTS and resolves the aforementioned problems. Extensive experiments on NAS-Bench-201 and DARTS-based search space demonstrate the effectiveness of IS-DARTS.Comment: accepted by AAAI2024, paper + supplementary, 11 page

Third-order intrinsic anomalous Hall effect with generalized semiclassical theory

The linear intrinsic anomalous Hall effect (IAHE) and second-order IAHE have been intensively investigated in time-reversal broken systems. However, as one of the important members of the nonlinear Hall family, the investigation of third-order IAHE remains absent due to the lack of an appropriate theoretical approach, although the third-order extrinsic AHE has been studied within the framework of first- and second-order semiclassical theory. Herein, we generalize the semiclassical theory for Bloch electrons under the uniform electric field up to the third-order using wavepacket method and based on which we predict that the third-order IAHE can also occur in time-reversal broken systems. Same as the second-order IAHE, we find the band geometric quantity, the second-order field-dependent Berry curvature arising from the second-order field-induced positional shift, plays a pivotal role to observe this effect. Moreover, with symmetry analysis, we find that the third-order IAHE, as the leading contribution, is supported by 15 time-reversal broken 3D magnetic point groups (MPGs), corresponding to a wide class of antiferromagnetic (AFM) materials. Guided by the symmetry arguments, a two-band model is chosen to demonstrate the generalized theory. Furthermore, the generalized third-order semiclassical theory depends only on the properties of Bloch bands, implying that it can also be employed to explore the IAHE in realistic AFM materials, by combining with first-principles calculations.Comment: 1 figur

Topiramate inhibits the proliferation of bladder cancer cells via PI3K/AKTR signaling pathway

Purpose: To explore new treatment options for bladder cancer (BC) based on topiramate (TPM).Methods: The MTT assay and flow cytometry were used to determine the effect of topiramate on partial growth-related malignant phenotype of BC cells. Expression levels of apoptosis-related biomarkers and signaling pathway-related factors were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. In vivo experiments were conducted to investigate the role of TPM on tumor growth in mice with bladder cancer.Results: The MTT results showed that topiramate blocked the growth of BC cells (p < 0.05). Growth inhibition was positively correlated with TPM concentration. Flow cytometry results revealed that bladder cancer cell apoptosis rose with increase in TPM concentration, while the mRNAs of apoptosisassociated factors Bcl-2 and Mcl-1 were down-regulated in a concentration-based manner by TPM (p < 0.05). Western blot assay indicated that Bax and Caspase-3 proteins were up-regulated, and the higher the concentration of TPM, the more significant the protein expression levels (p < 0.05).Conclusion: Topiramate (TPM) slows down the rate of growth of BC cells and accelerates their rate of apoptosis through the regulation of P13K/AKT/mTOR signaling pathway. Thus, the compound has potentials for development as an anti-bladder cancer agent

Electrochemical migration of Sn and Sn solder alloys: a review

Sn and Sn solder alloys in microelectronics are the most susceptible to suffer from electrochemical migration (ECM) which significantly compromises the reliability of electronics. This topic has attracted more and more attention from researchers since the miniaturization of electronics and the explosive increase in their usage have largely increased the risk of ECM. This article first presents an introductory overview of the ECM basic processes including electrolyte layer formation, dissolution of metal, ion transport and deposition of metal ions. Then, the article provides the major development in the field of ECM of Sn and Sn solder alloys in recent decades, including the recent advances and discoveries, current debates and significant gaps. The reactions at the anode and cathode, the mechanisms of precipitates formation and dendrites growth are summarized. The influencing factors including alloy elements (Pb, Ag, Cu, Zn, etc.), contaminants (chlorides, sulfates, flux residues, etc.) and electric field (bias voltage and spacing) on the ECM of Sn and Sn alloys are highlighted. In addition, the possible strategies such as alloy elements, inhibitor and pulsed or AC voltage for the inhibition of the ECM of Sn and Sn solder alloys have also been reviewed

Acoustic emission source location method and experimental verification for structures containing unknown empty areas

Acoustic emission (AE) localization plays an important role in the prediction and control of potential hazardous sources in complex structures. However, existing location methods have less discussion on the presence of unknown empty areas. This paper proposes an AE source location method for structures containing unknown empty areas (SUEA). Firstly, this method identifies the shape, size, and location of empty areas in the unknown region by exciting the active AE sources and using the collected AE arrivals. Then, the unknown AE source can be located considering the identified empty areas. The lead break experiments were performed to verify the effectiveness and accuracy of the proposed method. Five specimens were selected containing empty areas with different positions, shapes, and sizes. Results show the average location accuracy of the SUEA increased by 78% compared to the results of the existing method. It can provide a more accurate solution for locating AE sources in complex structures containing unknown empty areas such as tunnels, bridges, railroads, and caves in practical engineering