Better Diffusion Models Further Improve Adversarial Training

It has been recognized that the data generated by the denoising diffusion probabilistic model (DDPM) improves adversarial training. After two years of rapid development in diffusion models, a question naturally arises: can better diffusion models further improve adversarial training? This paper gives an affirmative answer by employing the most recent diffusion model which has higher efficiency ($\sim 20$ sampling steps) and image quality (lower FID score) compared with DDPM. Our adversarially trained models achieve state-of-the-art performance on RobustBench using only generated data (no external datasets). Under the $\ell_\infty$-norm threat model with $\epsilon=8/255$, our models achieve $70.69\%$ and $42.67\%$ robust accuracy on CIFAR-10 and CIFAR-100, respectively, i.e. improving upon previous state-of-the-art models by $+4.58\%$ and $+8.03\%$. Under the $\ell_2$-norm threat model with $\epsilon=128/255$, our models achieve $84.86\%$ on CIFAR-10 ($+4.44\%$). These results also beat previous works that use external data. We also provide compelling results on the SVHN and TinyImageNet datasets. Our code is available at https://github.com/wzekai99/DM-Improves-AT.Comment: ICML 202

LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition

Low-rank adaptations (LoRA) are often employed to fine-tune large language models (LLMs) for new tasks. This paper investigates LoRA composability for cross-task generalization and introduces LoraHub, a strategic framework devised for the purposive assembly of LoRA modules trained on diverse given tasks, with the objective of achieving adaptable performance on unseen tasks. With just a few examples from a novel task, LoraHub enables the fluid combination of multiple LoRA modules, eradicating the need for human expertise. Notably, the composition requires neither additional model parameters nor gradients. Our empirical results, derived from the Big-Bench Hard (BBH) benchmark, suggest that LoraHub can effectively mimic the performance of in-context learning in few-shot scenarios, excluding the necessity of in-context examples alongside each inference input. A significant contribution of our research is the fostering of a community for LoRA, where users can share their trained LoRA modules, thereby facilitating their application to new tasks. We anticipate this resource will widen access to and spur advancements in general intelligence as well as LLMs in production. Code will be available at https://github.com/sail-sg/lorahub.Comment: Work in progress. The first three authors contributed equally to this wor

Drill String Mechanics and Extension Capacity of Extended-Reach Well

For the design and construction of the extended-reach well, the ultimate elongation capacity of the extended-reach well was studied. Given the drilling practice of extended-reach well, the extension limit prediction criterion of extended-reach well is established. In this paper, based on the drilling practice of extended-reach well, by the finite element method, the gap element method and the dynamic finite element method of the whole drill string, static analysis model of the extended-reach well and the mechanicsꞌ analysis model of drill string vibration are established. The frictional resistance condition and strength condition of the limit extension of the extended-reach well are solved respectively, and the extended limit prediction criterion of the extended-reach well is established. The software was prepared based on the model and theory, the model and software were validated with the example of drilling, and the average error of the calculated value is 6.94% when compared with the measured values in the field. It can meet the needs of drilling engineering and study of the extension capability of the extended-reach wells

Bag of Tricks for Training Data Extraction from Language Models

With the advance of language models, privacy protection is receiving more attention. Training data extraction is therefore of great importance, as it can serve as a potential tool to assess privacy leakage. However, due to the difficulty of this task, most of the existing methods are proof-of-concept and still not effective enough. In this paper, we investigate and benchmark tricks for improving training data extraction using a publicly available dataset. Because most existing extraction methods use a pipeline of generating-then-ranking, i.e., generating text candidates as potential training data and then ranking them based on specific criteria, our research focuses on the tricks for both text generation (e.g., sampling strategy) and text ranking (e.g., token-level criteria). The experimental results show that several previously overlooked tricks can be crucial to the success of training data extraction. Based on the GPT-Neo 1.3B evaluation results, our proposed tricks outperform the baseline by a large margin in most cases, providing a much stronger baseline for future research. The code is available at https://github.com/weichen-yu/LM-Extraction.Comment: ICML 202

Electrocardiographic and cardiometabolic risk markers of left ventricular diastolic dysfunction in physically active adults: CHIEF heart study

AimThis study was aimed to investigate the association of cardiometabolic and ECG markers with left ventricular diastolic dysfunction (LVDD) in physically active Asian young adults, which has not been clarified in prior studies.Methods and resultsA total of 2,019 men aged 18–43 years were included from the military in Taiwan. All the subjects underwent anthropometric, hemodynamic, and blood metabolic marker measurements. Physical fitness was investigated by time for a 3,000-m run. LVDD was defined by presence of either one of the three echocardiographic criteria: (1) mitral inflow E/A ratio < 0.8 with a peak E velocity of > 50 cm/s, (2) tissue Doppler lateral mitral annulus e′ <10 cm/s, and (3) E/e′ ratio > 14. Multiple logistic regressions with adjustments for age, physical fitness, and pulse rate were conducted to determine the association of cardiometabolic and ECG markers with LVDD. The prevalence of LVDD was estimated to be 4.16% (N = 84). Of the cardiometabolic markers, central obesity, defined as waist circumference ≥ 90 cm, was the only independent marker of LVDD [odds ratio (OR) and 95% confidence interval: 2.97 (1.63–5.41)]. There were no association for hypertension, prediabetes, and dyslipidemia. Of the ECG markers, left atrial enlargement and incomplete right bundle branch block/intraventricular conduction delay were the independent ECG markers of LVDD [OR: 2.98 (1.28–6.94) and 1.94 (1.09–3.47), respectively]. There was borderline association for Cornell-based left ventricular hypertrophy and inferior T wave inversion [OR: 1.94 (0.97–3.63) and 2.44 (0.98–6.08), respectively].ConclusionIn the physically active Asian young male adults, central obesity and some ECG markers for left heart abnormalities were useful to identify LVDD

Tetra­aqua­bis(2-oxo-1,2-dihydro­quinoline-4-carboxyl­ato-κO 4)nickel(II)

In the title compound, [Ni(C10H6NO3)2(H2O)4], the central NiII atom is located on an inversion center and coordinated in a slightly distorted octa­hedral geometry by two O atoms from two 2-oxo-1,2-dihydro­quinoline-4-carboxyl­ate ligands and four water mol­ecules, all of which act as monodentate ligands. The crystal structure features an extensive network of inter­molecular hydrogen-bonding inter­actions (O—H⋯O and N—H⋯O) and offset face-to-face π–π stacking inter­actions [centroid–centroid distances = 3.525 (3) and 3.281 (5) Å]

Co-existence of multiple distinct lineages in Vibrio parahaemolyticus serotype O4:K12

Vibrio parahaemolyticus is an important cause of foodborne gastroenteritis globally. Thermostable direct haemolysin (TDH) and the TDH-related haemolysin are the two key virulence factors in V. parahaemolyticus. Vibrio pathogenicity islands harbour the genes encoding these two haemolysins. The serotyping of V. parahaemolyticus is based on the combination of O and K antigens. Frequent recombination has been observed in V. parahaemolyticus , including in the genomic regions encoding the O and K antigens. V. parahaemolyticus serotype O4:K12 has caused gastroenteritis outbreaks in the USA and Spain. Recently, outbreaks caused by this serotype of V. parahaemolyticus have been reported in China. However, the relationships among this serotype of V. parahaemolyticus strains isolated in different regions have not been addressed. Here, we investigated the genome variation of the V. parahaemolyticus serotype O4:K12 using the whole-genome sequences of 29 isolates. We determined five distinct lineages in this strain collection. We observed frequent recombination among different lineages. In contrast, little recombination was observed within each individual lineage. We showed that the lineage of this serotype of V. parahaemolyticus isolated in America was different from those isolated in Asia and identified genes that exclusively existed in the strains isolated in America. Pan-genome analysis showed that strain-specific and cluster-specific genes were mostly located in the genomic islands. Pan-genome analysis also showed that the vast majority of the accessory genes in the O4:K12 serotype of V. parahaemolyticus were acquired from within the genus Vibrio . Hence, we have shown that multiple distinct lineages exist in V. parahaemolyticus serotype O4:K12 and have provided more evidence about the gene segregation found in V. parahaemolyticus isolated in different continents

The immediate effect of backward walking on external knee adduction moment in healthy individuals

Backward walking (BW) has been recommended as a rehabilitation intervention to prevent, manage, or improve diseases. However, previous studies showed that BW significantly increased the first vertical ground reaction force (GRF) during gait, which might lead to higher loading at the knee. Published reports have not examined the effects of BW on medial compartment knee loading. The objective of this study was to investigate the effects of BW on external knee adduction moment (EKAM). Twenty-seven healthy adults participated in the present study. A sixteen-camera three-dimensional VICON gait analysis system, with two force platforms, was used to collect the EKAM, KAAI, and other biomechanical data during BW and forward walking (FW). The first () and second () EKAM peaks and KAAI () were significantly decreased during BW when compared with FW. The BW significantly decreased the lever arm length at the first EKAM peak () when compared with FW. In conclusion, BW was found to be a useful strategy for reducing the medial compartment knee loading even though the first peak ground reaction force was significantly increased