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  1. Free, publicly-accessible full text available June 1, 2025
  2. The northwest-trending Altai Mountains of central Asia expose a complex network of thrust and strike-slip faults that are key features accommodating intracontinental crustal shortening related to the Cenozoic India-Asia collision. In this study, we investigated the Quaternary slip history of the Fuyun fault, a right-lateral strike-slip fault bounding the southwestern margin of the Altai Mountains, through geologic mapping, geomorphic surveying, and optically stimulated luminescence (OSL) geochronology. At the Kuoyibagaer site, the Fuyun fault displaces three generations of Pleistocene–Holocene fill-cut river terraces (i.e., T3, T2, and T1) containing landslide and debris-flow deposits. The right-lateral offsets are magnified by erosion of terrace risers, suggesting that river course migration has been faster than slip along the Fuyun fault. The highest Tp2 terrace was abandoned in the middle Pleistocene (150.4 ± 8.1 ka uppermost OSL age) and was displaced 145.5 +45.6/–12.1 m along the Fuyun fault, yielding a slip rate of 1.0 +0.4/–0.1 mm/yr since the middle Pleistocene. The lower Tp1 terrace was abandoned in the late Pleistocene and aggraded by landslides and debris flows in the latest Pleistocene–Holocene (36.7 ± 1.6 ka uppermost OSL age). Tp1 was displaced 67.5 +14.2/–6.1 m along the Fuyun fault, yielding a slip rate of 1.8 +0.5/–0.2 mm/yr since the late Pleistocene. Our preferred minimum slip rate of ~1 mm/yr suggests the Fuyun fault accommodates ~16% of the average geodetic velocity of ~6 mm/yr across the Altai Mountains. Integration of our new Fuyun slip rate with other published fault slip rates accounts for ~4.2 mm/yr of convergence across the Chinese Altai, or ~70% of the geodetic velocity field.

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    Free, publicly-accessible full text available April 25, 2025
  3. Abstract

    Platelets play a pivotal role in hemostasis and wound healing and conditional shape change is an important component of platelet functionality. In normal circumstances, platelets travel through the circulatory system in an inactive rounded state, which enables platelets to easily move to vessel walls for attachment. When an injury occurs, platelets are prompted by molecules, such as thrombin, to shift into a stellate shape and increase exposure of fibrin‐binding receptors. When active, platelets promote hemostasis and clot retraction, which enhances clot stability and promotes healing. However, in conditions where platelets are depleted or hyporeactive, these functions are diminished and lead to inhibited hemostasis and healing. To treat platelet depletion, our group developed platelet‐like particles (PLPs) which consist of highly deformable microgels coupled to fibrin binding motif. However, first generation PLPs do not exhibit wound‐triggered shape change like native platelets. Thus, the objective of these studies was to develop a PLP formulation that changes shape when prompted by thrombin. To create thrombin‐sensitive PLPs (TS‐PLPs), we incorporated a thrombin‐cleavable peptide into the microgel body and then evaluated PLP properties before and after exposure to thrombin including morphology, size, and in vitro clot retraction. Once thrombin‐prompted shape change ability was confirmed, the TS‐PLPs were tested in vivo for hemostatic ability and subsequent wound healing outcomes in a murine liver trauma model. We found that TS‐PLPs exhibit a wound‐triggered shape change, induce significant clot retraction following exposure to thrombin and promote hemostasis and healing in vivo after trauma.

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    Free, publicly-accessible full text available April 1, 2025
  4. Free, publicly-accessible full text available October 20, 2024
  5. Binary neural network (BNN) delivers increased compute intensity and reduces memory/data requirements for computation. Scalable BNN enables inference in a limited time due to different constraints. This paper explores the application of Scalable BNN in oblivious inference, a service provided by a server to mistrusting clients. Using this service, a client can obtain the inference result on his/her data by a trained model held by the server without disclosing the data or learning the model parameters. Two contributions of this paper are: 1) we devise lightweight cryptographic protocols explicitly designed to exploit the unique characteristics of BNNs. 2) we present an advanced dynamic exploration of the runtime-accuracy tradeoff of scalable BNNs in a single-shot training process. While previous works trained multiple BNNs with different computational complexities (which is cumbersome due to the slow convergence of BNNs), we train a single BNN that can perform inference under various computational budgets. Compared to CryptFlow2, the state-of-the-art technique in the oblivious inference of non-binary DNNs, our approach reaches 3 × faster inference while keeping the same accuracy. Compared to XONN, the state-of-the-art technique in the oblivious inference of binary networks, we achieve 2 × to 12 × faster inference while obtaining higher accuracy. 
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  6. This paper proposes AdaTest, a novel adaptive test pattern generation framework for efficient and reliable Hardware Trojan (HT) detection. HT is a backdoor attack that tampers with the design of victim integrated circuits (ICs). AdaTest improves the existing HT detection techniques in terms of scalability and accuracy of detecting smaller Trojans in the presence of noise and variations. To achieve high trigger coverage, AdaTest leverages Reinforcement Learning (RL) to produce a diverse set of test inputs. Particularly, we progressively generate test vectors with high ‘reward’ values in an iterative manner. In each iteration, the test set is evaluated and adaptively expanded as needed. Furthermore, AdaTest integrates adaptive sampling to prioritize test samples that provide more information for HT detection, thus reducing the number of samples while improving the samples’ quality for faster exploration. We develop AdaTest with a Software/Hardware co-design principle and provide an optimized on-chip architecture solution. AdaTest’s architecture minimizes the hardware overhead in two ways: (i) Deploying circuit emulation on programmable hardware to accelerate reward evaluation of the test input; (ii) Pipelining each computation stage in AdaTest by automatically constructing auxiliary circuit for test input generation, reward evaluation, and adaptive sampling. We evaluate AdaTest’s performance on various HT benchmarks and compare it with two prior works that use logic testing for HT detection. Experimental results show that AdaTest engenders up to two orders of test generation speedup and two orders of test set size reduction compared to the prior works while achieving the same level or higher Trojan detection rate. 
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