Machine Learning Methods for Geotechnical Site Characterization and Scour Assessment

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Quasiexact posets and the moderate meet-continuity

The study of weak domains and quasicontinuous domains leads to the consideration of two types generalizations of domains. In the current paper, we define the weak way-below relation between two nonempty subsets of a poset and quasiexact posets. We prove some connections among quasiexact posets, quasicontinuous domains and weak domains. Furthermore, we introduce the weak way-below finitely determined topology and study its links to Scott topology and the weak way-below topology first considered by Mushburn. It is also proved that a dcpo is a domain if it is quasiexact and moderately meet continuous with the weak way-below relation weakly increasing

Improving Top- N

Recommender systems become increasingly significant in solving the information explosion problem. Data sparse is a main challenge in this area. Massive unrated items constitute missing data with only a few observed ratings. Most studies consider missing data as unknown information and only use observed data to learn models and generate recommendations. However, data are missing not at random. Part of missing data is due to the fact that users choose not to rate them. This part of missing data is negative examples of user preferences. Utilizing this information is expected to leverage the performance of recommendation algorithms. Unfortunately, negative examples are mixed with unlabeled positive examples in missing data, and they are hard to be distinguished. In this paper, we propose three schemes to utilize the negative examples in missing data. The schemes are then adapted with SVD++, which is a state-of-the-art matrix factorization recommendation approach, to generate recommendations. Experimental results on two real datasets show that our proposed approaches gain better top-N performance than the baseline ones on both accuracy and diversity

Adaptive Policy with Wait-kk Model for Simultaneous Translation

Simultaneous machine translation (SiMT) requires a robust read/write policy in conjunction with a high-quality translation model. Traditional methods rely on either a fixed wait-$k$ policy coupled with a standalone wait-$k$ translation model, or an adaptive policy jointly trained with the translation model. In this study, we propose a more flexible approach by decoupling the adaptive policy model from the translation model. Our motivation stems from the observation that a standalone multi-path wait-$k$ model performs competitively with adaptive policies utilized in state-of-the-art SiMT approaches. Specifically, we introduce DaP, a divergence-based adaptive policy, that makes read/write decisions for any translation model based on the potential divergence in translation distributions resulting from future information. DaP extends a frozen wait-$k$ model with lightweight parameters, and is both memory and computation efficient. Experimental results across various benchmarks demonstrate that our approach offers an improved trade-off between translation accuracy and latency, outperforming strong baselines.Comment: Accept to EMNLP 2023 main conference. 17 pages, 12 figures, 5 table

MUI-TARE: Multi-Agent Cooperative Exploration with Unknown Initial Position

Multi-agent exploration of a bounded 3D environment with unknown initial positions of agents is a challenging problem. It requires quickly exploring the environments as well as robustly merging the sub-maps built by the agents. We take the view that the existing approaches are either aggressive or conservative: Aggressive strategies merge two sub-maps built by different agents together when overlap is detected, which can lead to incorrect merging due to the false-positive detection of the overlap and is thus not robust. Conservative strategies direct one agent to revisit an excessive amount of the historical trajectory of another agent for verification before merging, which can lower the exploration efficiency due to the repeated exploration of the same space. To intelligently balance the robustness of sub-map merging and exploration efficiency, we develop a new approach for lidar-based multi-agent exploration, which can direct one agent to repeat another agent's trajectory in an \emph{adaptive} manner based on the quality indicator of the sub-map merging process. Additionally, our approach extends the recent single-agent hierarchical exploration strategy to multiple agents in a \emph{cooperative} manner by planning for agents with merged sub-maps together to further improve exploration efficiency. Our experiments show that our approach is up to 50\% more efficient than the baselines on average while merging sub-maps robustly.Comment: 8 pages, 8 figures, Submitted to IEEE RA

Ferroelectric memristor based on Pt/BiFeO3/Nb-doped SrTiO3 heterostructure

We report a continuously tunable resistive switching behavior in Pt/BiFeO₃/Nb-doped SrTiO₃ heterostructure for ferroelectric memristor application. The resistance of this memristor can be tuned up to 5 × 10⁵% by applying voltage pulses at room temperature, which exhibits excellent retention and anti-fatigue characteristics. The observed memristive behavior is attributed to the modulation effect of the ferroelectric polarization reversal on the width of depletion region and the height of potential barrier of the p-n junction formed at the BiFeO₃/Nb-doped SrTiO₃ interface.This work was supported by the National Natural Science Foundation of China (Grant Nos. 11074193 and 51132001). Q.L. and Y.L. acknowledge the support of the Australian Research Council (ARC) in the form of ARC Discovery Grants

Hemispherical Retina Emulated by Plasmonic Optoelectronic Memristors with All‐Optical Modulation for Neuromorphic Stereo Vision

Binocular stereo vision relies on imaging disparity between two hemispherical retinas, which is essential to acquire image information in three dimensional environment. Therefore, retinomorphic electronics with structural and functional similarities to biological eyes are always highly desired to develop stereo vision perception system. In this work, a hemispherical optoelectronic memristor array based on Ag-TiO2 nanoclusters/sodium alginate film is developed to realize binocular stereo vision. All-optical modulation induced by plasmonic thermal effect and optical excitation in Ag-TiO2 nanoclusters is exploited to realize in-pixel image sensing and storage. Wide field of view (FOV) and spatial angle detection are experimentally demonstrated owing to the device arrangement and incident-angle-dependent characteristics in hemispherical geometry. Furthermore, depth perception and motion detection based on binocular disparity have been realized by constructing two retinomorphic memristive arrays. The results demonstrated in this work provide a promising strategy to develop all-optically controlled memristor and promote the future development of binocular vision system with in-sensor architecture

Realizing 18.03% efficiency and good junction characteristics in organic solar cells via hydrogen-bonding interaction between glucose and ZnO electron transport layers

Electron transport layers (ETLs) with excellent electron extraction capability are essential for realizing high efficiency in organic solar cells (OSCs). A sol-gel-processed ZnO ETL is widely used in OSCs due to its high mobility and suitable work function. However, the existence of defects usually results in low photovoltaic performance during the operation of OSCs. In this work, glucose (Gl) was used to passivate free OH traps via hydrogen-bonding interaction and formed ZnO/Gl ETLs with ZnO, which exhibited improved electron extraction capability and reduced trap defect density. Thus, a champion efficiency of 18.03% was obtained in a PM6:Y6 light absorber-based cell, which is >11% higher than that of the reference cell (16.15%) with a pristine ZnO ETL. Impressive enhancements by >11% were also observed in different fullerene and non-fullerene light absorber-based cells relative to that of the reference cell. This study demonstrates a new strategy to design ETLs for realizing high efficiency in OSCs

Development and Validation of a New Method to Diagnose Apical Hypertrophic Cardiomyopathy By Gated Single-Photon Emission Computed Tomography Myocardial Perfusion Imaging

Aim The aim of this study is to develop and validate a new method to diagnose apical hypertrophic cardiomyopathy (AHCM) by the integral quantitative analysis of myocardial perfusion and wall thickening from gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). Patients and methods Twenty-two consecutive patients, who showed T wave inversion of at least 3 mm in precordial leads and sinus rhythm in ECG, were enrolled. All the patients underwent cardiac magnetic resonance (CMR), gated rest SPECT MPI and echocardiography. According to CMR diagnostic results, 13 patients were categorized as in the AHCM group and the remaining nine patients were categorized as in the non-AHCM group. Operators who were blinded to the CMR diagnosis independently performed the diagnosis by gated SPECT MPI. The regions of interest inside the apical hotspots on the perfusion polar map were drawn and the mean values of wall thickening in the drawn region of interests were calculated. Using MRI diagnosis as the gold standard, AHCM was diagnosed based on receiver operating characteristic analysis of the mean wall thickening in the apical perfusion hotspot. The area under curve, sensitivity, specificity, and accuracy of our method were 0.97, 100, 89, and 95%, respectively. Conclusion Our new method has high sensitivity, specificity, and accuracy against CMR diagnosis. It has great promise to become a clinical tool in the diagnosis of AHCM

Spatial Patterns of Leaf Carbon, Nitrogen, and Phosphorus Stoichiometry of Aquatic Macrophytes in the Arid Zone of Northwestern China

Ecological stoichiometry is a powerful indicator for understanding the adaptation of plants to environment. However, understanding of stoichiometric characteristics of leaf carbon (C%), nitrogen (N%), and phosphorus (P%) for aquatic macrophytes remains limited. In this study, 707 samples from 146 sites were collected to study the variations in leaf C%, N%, and P%, and tried to explore how different environmental conditions affect leaf C, N, and P stoichiometry. Results showed that the mean values of leaf C%, N%, P%, and N:P ratios were 39.95%, 2.12%, 0.14%, and 16.60% of macrophytes across the arid zone of northwestern China, respectively. And the mean values of leaf P% were lower than those from the Tibetan Plateau and eastern China, which maybe due to an adaptation strategy of the plants to the unique conditions in the arid zone in the long-term evolutionary process. The higher N:P ratios suggested that P was established as the limiting factor of the macrophytes communities in the arid zone of northwestern China. There were significant differences in leaf C%, N%, P%, and their ratios among different life forms. Our results also showed strong relationships between leaf N% and N:P ratios and longitude, leaf N%, P%, and N:P ratios and latitude, and leaf N% and P% and altitude, respectively. In addition, the results showed that pH can significantly influence leaf C%. Our results supported the temperature-plant physiology hypothesis owing to a negative relationship between leaf N% and P% of macrophytes and mean annual temperature in the arid zone of northwestern China. The different patterns of leaf stoichiometry between the arid zone of northwestern China and eastern China indicated that there were different physiological and ecological adaptability of macrophytes to environmental gradients in different climatic zones