AutoML-GPT: Large Language Model for AutoML

With the emerging trend of GPT models, we have established a framework called AutoML-GPT that integrates a comprehensive set of tools and libraries. This framework grants users access to a wide range of data preprocessing techniques, feature engineering methods, and model selection algorithms. Through a conversational interface, users can specify their requirements, constraints, and evaluation metrics. Throughout the process, AutoML-GPT employs advanced techniques for hyperparameter optimization and model selection, ensuring that the resulting model achieves optimal performance. The system effectively manages the complexity of the machine learning pipeline, guiding users towards the best choices without requiring deep domain knowledge. Through our experimental results on diverse datasets, we have demonstrated that AutoML-GPT significantly reduces the time and effort required for machine learning tasks. Its ability to leverage the vast knowledge encoded in large language models enables it to provide valuable insights, identify potential pitfalls, and suggest effective solutions to common challenges faced during model training

Streamlined NTRU Prime on FPGA

We present a novel full hardware implementation of Streamlined NTRU Prime, with two variants: A high-speed, high-area implementation, and a slower, low-area implementation. We introduce several new techniques that improve performance, including a batch inversion for key generation, a high-speed schoolbook polynomial multiplier, an NTT polynomial multiplier combined with a CRT map, a new DSP-free modular reduction method, a high-speed radix sorting module, and new en- and decoders. With the high-speed design, we achieve the to-date fastest speeds for Streamlined NTRU Prime, with speeds of 5007, 10989 and 64026 cycles for encapsulation, decapsulation, and key generation respectively, while running at 285 MHz on a Xilinx Zynq Ultrascale+. The entire design uses 40060 LUT, 26384 flip-flops, 36.5 Bram and 31 DSP

Mechanical-Thermal Noise in Drive-Mode of a Silicon Micro-Gyroscope

A new closed-loop drive scheme which decouples the phase and the gain of the closed-loop driving system was designed in a Silicon Micro-Gyroscope (SMG). We deduce the system model of closed-loop driving and use stochastic averaging to obtain an approximate “slow” system that clarifies the effect of thermal noise. The effects of mechanical-thermal noise on the driving performance of the SMG, including the noise spectral density of the driving amplitude and frequency, are derived. By calculating and comparing the noise amplitude due to thermal noise both in the opened-loop driving and in the closed-loop driving, we find that the closed-loop driving does not reduce the RMS noise amplitude. We observe that the RMS noise frequency can be reduced by increasing the quality factor and the drive amplitude in the closed-loop driving system. The experiment and simulation validate the feasibility of closed-loop driving and confirm the validity of the averaged equation and its stablility criterion. The experiment and simulation results indicate the electrical noise of closed-loop driving circuitry is bigger than the mechanical-thermal noise and as the driving mass decreases, the mechanical-thermal noise may get bigger than the electrical noise of the closed-loop driving circuitry

Automatic Verification of Cryptographic Block Function Implementations with Logical Equivalence Checking

Given a fixed-size block, cryptographic block functions gen- erate outputs by a sequence of bitwise operations. Block functions are widely used in the design of hash functions and stream ciphers. Their correct implementations hence are crucial to computer security. We pro- pose a method that leverages logic equivalence checking to verify assem- bly implementations of cryptographic block functions. Logic equivalence checking is a well-established technique from hardware verification. Using our proposed method, we verify two dozen assembly implementations of ChaCha20, SHA-256, and SHA-3 block functions from OpenSSL and XKCP automatically. We also compare the performance of our technique with the conventional SMT-based technique in experiments

Automatic Certified Verification of Cryptographic Programs with COQCRYPTOLINE

COQCRYPTOLINE is an automatic certified verification tool for cryptographic programs. It is built on OCAML programs extracted from algorithms fully certified in COQ with SS- REFLECT. Similar to other automatic tools, COQCRYPTO- LINE calls external decision procedures during verification. To ensure correctness, all answers from external decision procedures are validated by certified certificate checkers in COQCRYPTOLINE. We evaluate COQCRYPTOLINE on cryp- tographic programs from BITCOIN, BORINGSSL, NSS, and OPENSSL. The first certified verification of the reference implementation for number theoretic transform in the post- quantum key exchange mechanism KYBER is also reported

Vancomycin-Loaded Nanoparticles Enhance Sporicidal and Antibacterial Efficacy for Clostridium difficile Infection

Current antibiotic treatments fail to eliminate the Clostridium difficile (C. difficile) spores and induce dysbiosis and intestinal inflammation via off-target effect, which causes refractory C. difficile infection raise an unmet need for a spore-specific antimicrobial treatment. We developed a sporicidal and antimicrobial vancomycin-loaded spore-targeting iron oxide nanoparticle (van-IONP) that selectively binds to C. difficile spores. Cryo-electron microscopy showed that vancomycin-loaded nanoparticles can target and completely cover spore surfaces. They not only successfully delayed the germination of the spores but also inhibited ∼50% of vegetative cell outgrowth after 48 h of incubation. The van-IONPs also inhibited the interaction of spores with HT-29 intestinal mucosal cells in vitro. In a murine model of C. difficile infection, the van-IONP significantly protected the mice from infected by C. difficile infection, reducing intestinal inflammation, and facilitated superior mucosal viability compared with equal doses of free vancomycin. This dual-function targeted delivery therapy showed advantages over traditional therapeutics in treating C. difficile infection

Verified NTT Multiplications for NISTPQC KEM Lattice Finalists: Kyber, SABER, and NTRU

Postquantum cryptography requires a different set of arithmetic routines from traditional public-key cryptography such as elliptic curves. In particular, in each of the lattice-based NISTPQC Key Establishment finalists, every state-ofthe-art optimized implementation for lattice-based schemes still in the NISTPQC round 3 currently uses a different complex multiplication based on the Number Theoretic Transform. We verify the NTT-based multiplications used in NTRU, Kyber, and SABER for both the AVX2 implementation for Intel CPUs and for the pqm4 implementation for the ARM Cortex M4 using the tool CryptoLine. e extended CryptoLine and as a result are able to verify that in six instances multiplications are correct including range properties. We demonstrate the feasibility for a programmer to verify his or her high-speed assembly code for PQC, as well as to verify someone else’s high-speed PQC software in assembly code, with some cooperation from the programmer

IKKβ Suppression of TSC1 Links Inflammation and Tumor Angiogenesis via the mTOR Pathway

SummaryTNFα has recently emerged as a regulator linking inflammation to cancer pathogenesis, but the detailed cellular and molecular mechanisms underlying this link remain to be elucidated. The tuberous sclerosis 1 (TSC1)/TSC2 tumor suppressor complex serves as a repressor of the mTOR pathway, and disruption of TSC1/TSC2 complex function may contribute to tumorigenesis. Here we show that IKKβ, a major downstream kinase in the TNFα signaling pathway, physically interacts with and phosphorylates TSC1 at Ser487 and Ser511, resulting in suppression of TSC1. The IKKβ-mediated TSC1 suppression activates the mTOR pathway, enhances angiogenesis, and results in tumor development. We further find that expression of activated IKKβ is associated with TSC1 Ser511 phosphorylation and VEGF production in multiple tumor types and correlates with poor clinical outcome of breast cancer patients. Our findings identify a pathway that is critical for inflammation-mediated tumor angiogenesis and may provide a target for clinical intervention in human cancer