Ultra accurate collaborative information filtering via directed user similarity

A key challenge of the collaborative filtering (CF) information filtering is how to obtain the reliable and accurate results with the help of peers' recommendation. Since the similarities from small-degree users to large-degree users would be larger than the ones opposite direction, the large-degree users' selections are recommended extensively by the traditional second-order CF algorithms. By considering the users' similarity direction and the second-order correlations to depress the influence of mainstream preferences, we present the directed second-order CF (HDCF) algorithm specifically to address the challenge of accuracy and diversity of the CF algorithm. The numerical results for two benchmark data sets, MovieLens and Netflix, show that the accuracy of the new algorithm outperforms the state-of-the-art CF algorithms. Comparing with the CF algorithm based on random-walks proposed in the Ref.7, the average ranking score could reach 0.0767 and 0.0402, which is enhanced by 27.3\% and 19.1\% for MovieLens and Netflix respectively. In addition, the diversity, precision and recall are also enhanced greatly. Without relying on any context-specific information, tuning the similarity direction of CF algorithms could obtain accurate and diverse recommendations. This work suggests that the user similarity direction is an important factor to improve the personalized recommendation performance.Comment: 6 pages, 4 figure

APPLICATION OF HE’S FREQUENCY FORMULA TO NONLINEAR OSCILLATORS WITH GENERALIZED INITIAL CONDITIONS

This paper focuses on the vibration periodic property of Duffing oscillator with generalized initial conditions. Firstly, the undamped case is solved by Ji-Huan He’s frequency formulation; Secondly, the formulation is extended to the damped case. Numerical verification shows that the frequency formulation is mathematically simple and physically insightful and practically applicable. This paper paves a novel way for engineers to use the formulation to study nonlinear vibration system with ease and reliability

Controlling entanglement sudden death in cavity QED by classical driving fields

We investigate the entanglement dynamics of a quantum system consisting of two-level atoms interacting with vacuum or thermal fields with classical driving fields. We find that the entanglement of the system can be improved by adjusting the classical driving field. The influence of the classical field and the purity of the initial state on the entanglement sudden death is also studied. It is shown that the time of entanglement sudden death can be controlled by the classical driving fields. Particularly, the entanglement sudden death phenomenon will disappear if the classical driving fields are strong enough

Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning

Transfer learning has become a common practice for training deep learning models with limited labeled data in a target domain. On the other hand, deep models are vulnerable to adversarial attacks. Though transfer learning has been widely applied, its effect on model robustness is unclear. To figure out this problem, we conduct extensive empirical evaluations to show that fine-tuning effectively enhances model robustness under white-box FGSM attacks. We also propose a black-box attack method for transfer learning models which attacks the target model with the adversarial examples produced by its source model. To systematically measure the effect of both white-box and black-box attacks, we propose a new metric to evaluate how transferable are the adversarial examples produced by a source model to a target model. Empirical results show that the adversarial examples are more transferable when fine-tuning is used than they are when the two networks are trained independently

经侧裂或颞叶入路高血压基底节血肿手术中水分离技术的应用

目的 探讨水分离技术在高血压基底节区脑出血手术治疗中的应用及体会。方法 回顾性分析2011年1月至2012年12月收治的62例高血压基底节区脑出血,其中43例采用常规手术清除血肿，19例术中应用水分离技术解剖侧裂和清除血肿。对比两组手术时间及术后血肿清除范围。结果 常规方式组手术时间在（3±0.30）h；水分离技术组(2.5±0.30)h。常规组20例血肿完全清除，16例血肿清除大于90%，7例小于90%；水分离技术组17例血肿完全清除，2例血肿清除大于90%(c2=10.40，P＜0.05)。结论 水分离技术是一种安全简便的微创技术，在经侧裂岛叶入路清除血肿中能很好的帮助解剖侧裂,在经颞叶清除血肿时,也能很容易将血肿整块清除,且对周围脑组织损伤小，血肿清除彻底。 Objective:  To investigate the effect of water jet dissection technique in surgical treatment of hypertensive basal ganglion hemorrhage through transsylvian transinsular or transtemporal approach. Methods:  43 patients with hypertensive basal ganglion hemorrhage underwent the resection of hemorrhage through transtemporal approach with regular surgery and 19 patients underwent the resection of hemorrhage through transsylvian transinsular or transtemporal approach with water dissection technique from January 2011 to November 2012. Results:  It was observed that operation time was (3±0.30) hours in regular surgery group and (2.5±0.30) hours in water dissection technology group. The postoperative CT within 24h showed that hematoma was removed totally in 20 cases, over 90% in 16 cases and below 90% in 7 cases in the regular group and hematoma was removed totally in 17 cases and over 90% in 2 cases in the water dissection technique group (c2=10.40, P < 0.05). Conclusion:  The water dissection technique can be simply and safely applied, which is very helpful for opening the sylvian fissure and removing hematoma on hypertensive basal ganglion hemorrhage through transylvian transinsular or transtemporal approach with minimal injury of brain tissue and total removement of hematoma

High molecular weight humic-like substances in carboneous aerosol of Ulaanbaatar city

Total carbon content of the atmospheric suspended particulate matters consisted of as high as 89-93% organic carbon (OC) in Ulaanbaatar aerosol without showing seasonal variation. However, limited aerosol measurements have been conducted on these OC rich aerosols particularly for high molecular weight constituents. In order to address the gap above, abundance of high molecular weight humic-like substances (HULIS) in total suspended particulates (TSP) from Ulaanbaatar atmospheric aerosol were determined for the first time. HULIS molecular structure was characterised for different seasons using carbon content and UV absorbance measurements coupled with solid phase extraction methods. Although, HULIS contributions to water soluble organic fraction of the winter and summer aerosols were similar HULIS carbon concentration was higher in winter samples (9-37 mg·L-1) than in summer (2-6 mg·L-1). Consequently quantity of aromatic moieties and degree of aromaticity varied between seasons

Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing

Large language models (LLMs) have made impressive progress in natural language processing. These models rely on proper human instructions (or prompts) to generate suitable responses. However, the potential of LLMs are not fully harnessed by commonly-used prompting methods: many human-in-the-loop algorithms employ ad-hoc procedures for prompt selection; while auto prompt generation approaches are essentially searching all possible prompts randomly and inefficiently. We propose Evoke, an automatic prompt refinement framework. In Evoke, there are two instances of a same LLM: one as a reviewer (LLM-Reviewer), it scores the current prompt; the other as an author (LLM-Author), it edits the prompt by considering the edit history and the reviewer's feedback. Such an author-reviewer feedback loop ensures that the prompt is refined in each iteration. We further aggregate a data selection approach to Evoke, where only the hard samples are exposed to the LLM. The hard samples are more important because the LLM can develop deeper understanding of the tasks out of them, while the model may already know how to solve the easier cases. Experimental results show that Evoke significantly outperforms existing methods. For instance, in the challenging task of logical fallacy detection, Evoke scores above 80, while all other baseline methods struggle to reach 20