Tracking of enriched dialog states for flexible conversational information access

Dialog state tracking (DST) is a crucial component in a task-oriented dialog system for conversational information access. A common practice in current dialog systems is to define the dialog state by a set of slot-value pairs. Such representation of dialog states and the slot-filling based DST have been widely employed, but suffer from three drawbacks. (1) The dialog state can contain only a single value for a slot, and (2) can contain only users' affirmative preference over the values for a slot. (3) Current task-based dialog systems mainly focus on the searching task, while the enquiring task is also very common in practice. The above observations motivate us to enrich current representation of dialog states and collect a brand new dialog dataset about movies, based upon which we build a new DST, called enriched DST (EDST), for flexible accessing movie information. The EDST supports the searching task, the enquiring task and their mixed task. We show that the new EDST method not only achieves good results on Iqiyi dataset, but also outperforms other state-of-the-art DST methods on the traditional dialog datasets, WOZ2.0 and DSTC2.Comment: 5 pages, 2 figures, accepted by ICASSP201

A Continuum Model for Dislocation Climb

Dislocation climb plays an important role in understanding plastic deformation of metallic materials at high temperature. In this paper, we present a continuum formulation for dislocation climb velocity based on densities of dislocations. The obtained continuum formulation is an accurate approximation of the Green's function based discrete dislocation dynamics method (Gu et al. J. Mech. Phys. Solids 83:319-337, 2015). The continuum dislocation climb formulation has the advantage of accounting for both the long-range effect of vacancy bulk diffusion and that of the Peach-Koehler climb force, and the two longrange effects are canceled into a short-range effect (integral with fast-decaying kernel) and in some special cases, a completely local effect. This significantly simplifies the calculation in the Green's function based discrete dislocation dynamics method, in which a linear system has to be solved over the entire system for the long-range effect of vacancy diffusion and the long-range Peach-Koehler climb force has to be calculated. This obtained continuum dislocation climb velocity can be applied in any available continuum dislocation dynamics frameworks. We also present numerical validations for this continuum climb velocity and simulation examples for implementation in continuum dislocation dynamics frameworks

TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs

Sparse convolution plays a pivotal role in emerging workloads, including point cloud processing in AR/VR, autonomous driving, and graph understanding in recommendation systems. Since the computation pattern is sparse and irregular, specialized high-performance kernels are required. Existing GPU libraries offer two dataflow types for sparse convolution. The gather-GEMM-scatter dataflow is easy to implement but not optimal in performance, while the dataflows with overlapped computation and memory access (e.g.implicit GEMM) are highly performant but have very high engineering costs. In this paper, we introduce TorchSparse++, a new GPU library that achieves the best of both worlds. We create a highly efficient Sparse Kernel Generator that generates performant sparse convolution kernels at less than one-tenth of the engineering cost of the current state-of-the-art system. On top of this, we design the Sparse Autotuner, which extends the design space of existing sparse convolution libraries and searches for the best dataflow configurations for training and inference workloads. Consequently, TorchSparse++ achieves 2.9x, 3.3x, 2.2x and 1.7x measured end-to-end speedup on an NVIDIA A100 GPU over state-of-the-art MinkowskiEngine, SpConv 1.2, TorchSparse and SpConv v2 in inference; and is 1.2-1.3x faster than SpConv v2 in mixed precision training across seven representative autonomous driving benchmarks. It also seamlessly supports graph convolutions, achieving 2.6-7.6x faster inference speed compared with state-of-the-art graph deep learning libraries.Comment: MICRO 2023; Haotian Tang and Shang Yang contributed equally to this projec

Revisiting Pairing-friendly Curves with Embedding Degrees 10 and 14

Since 2015, there has been a significant decrease in the asymptotic complexity of computing discrete logarithms in finite fields. As a result, the key sizes of many mainstream pairing-friendly curves have to be updated to maintain the desired security level. In PKC\u2720, Guillevic conducted a comprehensive assessment of the security of a series of pairing-friendly curves with embedding degrees ranging from $9$ to $17$. In this paper, we focus on pairing-friendly curves with embedding degrees of 10 and 14. First, we extend the optimized formula of the optimal pairing on BW13-310, a 128-bit secure curve with a prime $p$ in 310 bits and embedding degree $13$, to our target curves. This generalization allows us to compute the optimal pairing in approximately $\log r/2\varphi(k)$ Miller iterations, where $r$ and $k$ are the order of pairing groups and the embedding degree respectively. Second, we develop optimized algorithms for cofactor multiplication for $\mathbb{G}_1$ and $\mathbb{G}_2$, as well as subgroup membership testing for $\mathbb{G}_2$ on these curves. Based on these theoretical results a new 128-bit secure curve emerges: BW14-351. Finally, we provide detailed performance comparisons between BW14-351 and other popular curves on a 64-bit platform in terms of pairing computation, hashing to $\mathbb{G}_1$ and $\mathbb{G}_2$, group exponentiations and subgroup membership testings. Our results demonstrate that BW14-351 is a strong candidate for building pairing-based cryptographic protocols

Simultaneous treatment of phosphorus and fluoride wastewater using acid-modified iron-loaded electrode capacitive deionization: Preparation and performance

Here, capacitive deionization technology (CDI) using modified activated carbon fiber felt (ACF) electrodes was proposed to provide a new strategy for the challenge of simultaneous phosphorus and fluoride wastewater treatment. The acid-modified iron-loaded ACF (A@Fe-ACF) was obtained by modifying ACF through a two-step impregnation method. After the modification, the oxygen-containing functional groups on ACF increased and provided more adsorption sites. The electron transfer efficiency on the A@Fe-ACF was increased by introducing Fe and synergistically promoted the adsorption of phosphorus and fluorine. Results showed that the removal efficiencies of total phosphorus (TP) and total fluorine (TF) in wastewater reached 89.4% and 85% under optimal conditions (voltage intensity 1.5 V, pH 7, plate spacing 1 cm), while the adsorption mechanism of phosphorus and fluorine was dominated by chemical adsorption. Meanwhile, A@Fe-ACF electrode has good recyclability and stability after five cycles

SdPI, The First Functionally Characterized Kunitz-Type Trypsin Inhibitor from Scorpion Venom

Background: Kunitz-type venom peptides have been isolated from a wide variety of venomous animals. They usually have protease inhibitory activity or potassium channel blocking activity, which by virtue of the effects on predator animals are essential for the survival of venomous animals. However, no Kunitz-type peptides from scorpion venom have been functionally characterized. Principal Findings: A new Kunitz-type venom peptide gene precursor, SdPI, was cloned and characterized from a venom gland cDNA library of the scorpion Lychas mucronatus. It codes for a signal peptide of 21 residues and a mature peptide of 59 residues. The mature SdPI peptide possesses a unique cysteine framework reticulated by three disulfide bridges, different from all reported Kunitz-type proteins. The recombinant SdPI peptide was functionally expressed. It showed trypsin inhibitory activity with high potency (Ki = 1.6610 27 M) and thermostability. Conclusions: The results illustrated that SdPI is a potent and stable serine protease inhibitor. Further mutagenesis and molecular dynamics simulation revealed that SdPI possesses a serine protease inhibitory active site similar to other Kunitztype venom peptides. To our knowledge, SdPI is the first functionally characterized Kunitz-type trypsin inhibitor derive

The ratio of systolic and diastolic pressure is associated with carotid and femoral atherosclerosis

BackgroundAlthough the impact of hypertension on carotid intima-media thickness (IMT) and plaques has been well established, its association with femoral IMT and plaques has not been extensively examined. In addition, the role of the ratio of systolic and diastolic pressure (SDR) in the subclinical atherosclerosis (AS) risk remains unknown. We assessed the relationship between SDR and carotid and femoral AS in a general population.MethodsA total of 7,263 participants aged 35–74 years enrolled from January 2019 to June 2021 in a southeast region of China were included in a cross-sectional study. Systolic and diastolic blood pressure (SBP and DBP) were used to define SDR. Ultrasonography was applied to assess the AS, including thickened IMT (TIMT) and plaque in the carotid and femoral arteries. Logistic regression and restricted cubic spline (RCS) models were the main approaches.ResultsThe prevalence of TIMT, plaque, and AS were 17.3%, 12.4%, and 22.7% in the carotid artery; 15.2%, 10.7%, and 19.5% in the femoral artery; and 23.8%, 17.9% and 30.0% in either the carotid or femoral artery, respectively. Multivariable logistic regression analysis found a significant positive association between high-tertile SDR and the higher risk of overall TIMT (OR = 1.28, 95% CI = 1.10–1.49), plaques (OR = 1.36, 95%CI = 1.16–1.61), or AS (OR = 1.36, 95% CI = 1.17–1.57), especially in the carotid artery. RCS analysis further revealed the observed positive associations were linear. Further analyses showed that as compared to the low-tertile SDR and non-hypertension group, high-tertile SDR was associated with increased risks of overall and carotid TIMT, plaques, or AS in both groups with or without hypertension.ConclusionsSDR is related to a higher risk of subclinical AS, regardless of hypertension or not, suggesting that as a readily obtainable index, SDR can contribute to providing additional predictive value for AS

Anti-HIV-1 Activity of a New Scorpion Venom Peptide Derivative Kn2-7

For over 30 years, HIV/AIDS has wreaked havoc in the world. In the absence of an effective vaccine for HIV, development of new anti-HIV agents is urgently needed. We previously identified the antiviral activities of the scorpion-venom-peptide-derived mucroporin-M1 for three RNA viruses (measles viruses, SARS-CoV, and H5N1). In this investigation, a panel of scorpion venom peptides and their derivatives were designed and chosen for assessment of their anti-HIV activities. A new scorpion venom peptide derivative Kn2-7 was identified as the most potent anti-HIV-1 peptide by screening assays with an EC50 value of 2.76 µg/ml (1.65 µM) and showed low cytotoxicity to host cells with a selective index (SI) of 13.93. Kn2-7 could inhibit all members of a standard reference panel of HIV-1 subtype B pseudotyped virus (PV) with CCR5-tropic and CXCR4-tropic NL4-3 PV strain. Furthermore, it also inhibited a CXCR4-tropic replication-competent strain of HIV-1 subtype B virus. Binding assay of Kn2-7 to HIV-1 PV by Octet Red system suggested the anti-HIV-1 activity was correlated with a direct interaction between Kn2-7 and HIV-1 envelope. These results demonstrated that peptide Kn2-7 could inhibit HIV-1 by direct interaction with viral particle and may become a promising candidate compound for further development of microbicide against HIV-1