Research on the TNT Equivalence of Aluminized Explosive

AbstractAluminum as an important fuel component has been widely used in the field of arms and ammunition. The Determination of TNT equivalent of aluminized explosive, focused on the experimental study, is still lack of numerical calculation study. It is one of the main factors on safety research, so that effective measures should be taken to determine the TNT equivalence of aluminized explosive. In previous studies, the determination of TNT equivalence of aluminized explosive is mainly based on experimental study. But the affection to its explosive heat due to different ratio of aluminum powder is neglected in experiment researches. Based on the minimum free energy method, this paper programmed composition with Matlab. The equilibrium products of aluminized explosive detonation were calculated. The TNT equivalence of aluminized explosive with different ratio was determined. The results show that for the same mass of aluminized explosive, the higher mass fraction of aluminum powder was, the higher thermal damage to the environment was

Rethinking Learning Rate Tuning in the Era of Large Language Models

Large Language Models (LLMs) represent the recent success of deep learning in achieving remarkable human-like predictive performance. It has become a mainstream strategy to leverage fine-tuning to adapt LLMs for various real-world applications due to the prohibitive expenses associated with LLM training. The learning rate is one of the most important hyperparameters in LLM fine-tuning with direct impacts on both fine-tuning efficiency and fine-tuned LLM quality. Existing learning rate policies are primarily designed for training traditional deep neural networks (DNNs), which may not work well for LLM fine-tuning. We reassess the research challenges and opportunities of learning rate tuning in the coming era of Large Language Models. This paper makes three original contributions. First, we revisit existing learning rate policies to analyze the critical challenges of learning rate tuning in the era of LLMs. Second, we present LRBench++ to benchmark learning rate policies and facilitate learning rate tuning for both traditional DNNs and LLMs. Third, our experimental analysis with LRBench++ demonstrates the key differences between LLM fine-tuning and traditional DNN training and validates our analysis

Protective effect of furofuranone against cerebral ischemic stroke via activation of PI3k/Akt/GSK 3β signaling pathway

Purpose: To study the protective effects of furofuranone on oxygen and glucose-deprived damage to brain microvascular endothelial cells (BMECs) in vitro, and in vivo in cerebral ischemic stroke rat model. Methods: BMECs were isolated from the Sprague Dawley rats and deprived of oxygen and glucose. The effect of 10, 20, 30, 40, 50 and 100 µM furofuranone on the oxygen/glucose-deprived BMECs was studied using Transwell chamber method. A rat cerebral ischemic stroke model was established using middle cerebral arterial occlusion method. Caspase-3 and other proteins, inflammatory cytokines, and other parameters of the brain tissue were evaluated by enzyme-linked assay (ELISA), polymerase chain reaction (PCR) and Western blot as appropriate. Further studies on the brain tissues was carried out by immunochemical analysis and hematoxylin and eosin staining. Results: Furofuranone decreased caspase 3 levels in a dose-based manner in rat BMECs, and significantly reduced the release of lactate dehydrogenase (LDH) in ischemic stroke rat model (p < 0.05). It also led to marked increases in the levels of p PI3k, p Akt and p GSK3β in cerebral ischemic stroke rats. Growth-associated protein-43 (GAP-43) and microtubule-associated protein 2 (MAP-2) levels increased in the cerebral ischemic stroke rat brain tissues, in addition to marked increase in ionized calcium-binding adaptor protein (IBA-1) and glial fibrillary acidic protein (GFAP) (p < 0.05). Furofuranone treatment reduced the population of microtubule-associated protein light chain 3 (MAP1LC3A) and Beclin 1-positive cells, and significantly downregulated L selectin, leptin, monocyte chemotactic protein-1 (MCP-1) and tumor necrosis factor (TNF)-α (p < 0.05). The release of tissue inhibitor of metalloproteinases 1 (TIMP-1) was enhanced in the cerebral ischemic stroke rats by furofuranone treatment. Conclusion: Furofuranone treatment prevents cerebral ischemic stroke-induced damage in rats via phosphorylation of PI3k, Akt and GSK3β proteins, and reduction of inflammatory cytokine levels. Therefore, furofuranone may be useful as chemotherapeutic agent for cerebral ischemic stroke

A Multi-objective Particle Swarm Optimization Algorithm Based on Reverse Learning

In order to solve the contradiction between population diversity and convergence in particle swarm optimization algorithm, in this paper, a particle swarm optimization algorithm with reverse learning is proposed. On this basis, the values of learning factor and constraint factor parameters are modified, and the linear decreasing weight strategy was adopted. By modifying the learning factor and the constraint factor, the algorithm improves the particle optimization ability. It balances the global search and local search of the particle, and the convergence speed is improved by using the inertia weight. When it is detected that the algorithm falls into the local optimal region, the position information of these poor particles is used to guide some particles to reverse learning at a faster flight speed, and the particles are quickly pulled out of the local optimal region. The reverse learning process can not only improve the diversity of particle population, but also ensure the global detection ability of the algorithm. Experimental results show that, compared with the basic MOPSO algorithm, this algorithm has fast convergence speed and high solution accuracy in function optimization

How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs

Most traditional AI safety research has approached AI models as machines and centered on algorithm-focused attacks developed by security experts. As large language models (LLMs) become increasingly common and competent, non-expert users can also impose risks during daily interactions. This paper introduces a new perspective to jailbreak LLMs as human-like communicators, to explore this overlooked intersection between everyday language interaction and AI safety. Specifically, we study how to persuade LLMs to jailbreak them. First, we propose a persuasion taxonomy derived from decades of social science research. Then, we apply the taxonomy to automatically generate interpretable persuasive adversarial prompts (PAP) to jailbreak LLMs. Results show that persuasion significantly increases the jailbreak performance across all risk categories: PAP consistently achieves an attack success rate of over $92\%$ on Llama 2-7b Chat, GPT-3.5, and GPT-4 in $10$ trials, surpassing recent algorithm-focused attacks. On the defense side, we explore various mechanisms against PAP and, found a significant gap in existing defenses, and advocate for more fundamental mitigation for highly interactive LLMsComment: 14 pages of the main text, qualitative examples of jailbreaks may be harmful in natur

Promoting H2O2 production via 2-electron oxygen reduction by coordinating partially oxidized Pd with defect carbon.

Electrochemical synthesis of H2O2 through a selective two-electron (2e-) oxygen reduction reaction (ORR) is an attractive alternative to the industrial anthraquinone oxidation method, as it allows decentralized H2O2 production. Herein, we report that the synergistic interaction between partially oxidized palladium (Pdδ+) and oxygen-functionalized carbon can promote 2e- ORR in acidic electrolytes. An electrocatalyst synthesized by solution deposition of amorphous Pdδ+ clusters (Pd3δ+ and Pd4δ+) onto mildly oxidized carbon nanotubes (Pdδ+-OCNT) shows nearly 100% selectivity toward H2O2 and a positive shift of ORR onset potential by ~320 mV compared with the OCNT substrate. A high mass activity (1.946 A mg-1 at 0.45 V) of Pdδ+-OCNT is achieved. Extended X-ray absorption fine structure characterization and density functional theory calculations suggest that the interaction between Pd clusters and the nearby oxygen-containing functional groups is key for the high selectivity and activity for 2e- ORR

Early malperfusion, ischemia reperfusion injury, and respiratory failure in acute complicated type B aortic dissection after thoracic endovascular repair

BACKGROUND: The aim of this study was to determine the early mortality and major complications of acute complicated type B aortic dissection (ACBD) after thoracic endovascular aortic repair (TEVAR). METHODS: Twenty-six consecutive patients with ACBD who underwent TEVAR were included. Clinical indications before TEVAR and in-hospital mortality and major complications after TEVAR were analyzed and compared with similar reports. RESULTS: TEVAR was technically successful in all cases. In-hospital mortality occurred in four patients (15%), and major complications occurred in an additional four patients (15%). Three of the four (75%) of the deaths were associated with malperfusion and ischemia reperfusion injury (IRI), and 3/4 (75%) of the major complications were caused by respiratory failure (RF). CONCLUSIONS: In-hospital mortality associated strongly with severe end-organ malperfusion and IRI, while major complications associated with RF, during TEVAR. Our results indicate that malperfusion, IRI and respiratory failure during TEVAR should be carefully monitored and aggressively treated

Solution for Point Tracking Task of ICCV 1st Perception Test Challenge 2023

This report proposes an improved method for the Tracking Any Point (TAP) task, which tracks any physical surface through a video. Several existing approaches have explored the TAP by considering the temporal relationships to obtain smooth point motion trajectories, however, they still suffer from the cumulative error caused by temporal prediction. To address this issue, we propose a simple yet effective approach called TAP with confident static points (TAPIR+), which focuses on rectifying the tracking of the static point in the videos shot by a static camera. To clarify, our approach contains two key components: (1) Multi-granularity Camera Motion Detection, which could identify the video sequence by the static camera shot. (2) CMR-based point trajectory prediction with one moving object segmentation approach to isolate the static point from the moving object. Our approach ranked first in the final test with a score of 0.46

Photometric and Spectroscopic Studies of V582 Lyr and V1016 Oph

We present new CCD photometric light curves about two eclipsing binaries of V582 Lyr and V1016 Oph. Our observations were carried out by the SARA 91.4 cm telescope of America in 2016 and the 60 cm telescope of Chile in 2018. V582 Lyr’s spectra type was classified as K5, and its radial velocity was determined using the LAMOST spectral survey. There are absorptions in the observed Hα line and excess emissions in the subtracted Hα line, which show weak chromospheric activity. We obtained the updated ephemeris information for V582 Lr and V1016 Oph, and found that their orbital periods are both decreasing.We concluded that the decreased rate is −0.474 (±0.011)Å~10−7 days yr−1 for V582 Lyr and 3.460 (±0.014)Å~10−7 days yr−1 for V1016 Oph. For V582 Lyr, the period variation was interpreted as a mass transfer from the secondary component to the primary one, and the corresponding rate is dM2/dt=−1.10 (±0.03)Å~10−7 Me yr−1. For V1016 Oph, we explain it by transferring from the primary component to the secondary one, and the corresponding rate is dM1/dt=−2.69 (±0.04)Å~10−7 Me yr−1. The photometric solution of V1016 Oph was obtained by analyzing the CCD photometry with the Wilson–Devinney program. We also obtained the orbital parameters of V1016 Oph by simultaneously analyzing our BVRI light curves and radial-velocity curve from the LAMOST low-resolution spectral survey. Finally, our orbital solution shows that they are contact eclipsing binaries with contact factors of 3.35 (±0.08)% for V582 Lyr and 41.0 (±0.1)% for V1016 Oph