Multiple Solutions for the Asymptotically Linear Kirchhoff Type Equations on R

The multiplicity of positive solutions for Kirchhoff type equations depending on a nonnegative parameter λ on RN is proved by using variational method. We will show that if the nonlinearities are asymptotically linear at infinity and λ>0 is sufficiently small, the Kirchhoff type equations have at least two positive solutions. For the perturbed problem, we give the result of existence of three positive solutions

DYNAMICAL EFFECTS OF SPRINT START ON DIFFERENT STARTING BLOCKS

The purpose of this study was to examine the dynamical variables of sprint start in two different starting blocks setups. The ReacTime Personal Systems was used to record the Reaction Time (RT) and the Power of 20 teenaged sprinters (15 males and 5 females) in the sprint start. In addition, the Newtest Powertimer photocells were used to collect subjects’ 0 to 10 metre (T10) performance after the sprint start. The variables were tested by the repeated measures one-way ANOVA by SPSS 19.0 statistical software at a .05 significant level. The results showed that there were better effects on the short starting block (SB) in power generation performance than the long starting block (LB). The athletes can apply short starting block and make adjustments and modifications based on their training conditions

LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning (Practical Experience Report)

The automation of code review activities, a long-standing pursuit in software engineering, has been primarily addressed by numerous domain-specific pre-trained models. Despite their success, these models frequently demand extensive resources for pre-training from scratch. In contrast, Large Language Models (LLMs) provide an intriguing alternative, given their remarkable capabilities when supplemented with domain-specific knowledge. However, their potential for automating code review tasks remains largely unexplored. In response to this research gap, we present LLaMA-Reviewer, an innovative framework that leverages the capabilities of LLaMA, a popular LLM, in the realm of code review. Mindful of resource constraints, this framework employs parameter-efficient fine-tuning (PEFT) methods, delivering high performance while using less than 1% of trainable parameters. An extensive evaluation of LLaMA-Reviewer is conducted on two diverse, publicly available datasets. Notably, even with the smallest LLaMA base model consisting of 6.7B parameters and a limited number of tuning epochs, LLaMA-Reviewer equals the performance of existing code-review-focused models. The ablation experiments provide insights into the influence of various fine-tuning process components, including input representation, instruction tuning, and different PEFT methods. To foster continuous progress in this field, the code and all PEFT-weight plugins have been made open-source.Comment: Accepted to the 34th IEEE International Symposium on Software Reliability Engineering (ISSRE 2023

17βH-Periplogenin, a cardiac aglycone from the root bark of Periploca sepium Bunge

The title compound {systematic name: 4-[(3S,5S,8R,9S,10R,13R,14S,17S)-3,5,14-trihy­droxy-10,13-dimethyl­hexa­deca­hydro-1H-cyclo­penta­[a]phenanthren-17-yl]furan-2(5H)-one}, C23H34O5, was isolated from the roots of Periploca sepium Bunge, a famous Chinese traditional herbal medicine. The three six-membered rings adopt chair conformations, the cyclo­pentane ring displays an approximate envelope conformation (with the C atom bearing the methyl substituent at the flap) and the five-membered lactone ring adopts an essentially planar [maximum deviation of 0.004 (8) Å] conformation. In the crystal, mol­ecules are linked into helical chains along [010] by O—H⋯O hydrogen bonds and weak C—H⋯O inter­actions. Two intra­molecular O—H⋯O hydrogen bonds are also present

Spectral Collaborative Filtering

Despite the popularity of Collaborative Filtering (CF), CF-based methods are haunted by the \textit{cold-start} problem, which has a significantly negative impact on users' experiences with Recommender Systems (RS). In this paper, to overcome the aforementioned drawback, we first formulate the relationships between users and items as a bipartite graph. Then, we propose a new spectral convolution operation directly performing in the \textit{spectral domain}, where not only the proximity information of a graph but also the connectivity information hidden in the graph are revealed. With the proposed spectral convolution operation, we build a deep recommendation model called Spectral Collaborative Filtering (SpectralCF). Benefiting from the rich information of connectivity existing in the \textit{spectral domain}, SpectralCF is capable of discovering deep connections between users and items and therefore, alleviates the \textit{cold-start} problem for CF. To the best of our knowledge, SpectralCF is the first CF-based method directly learning from the \textit{spectral domains} of user-item bipartite graphs. We apply our method on several standard datasets. It is shown that SpectralCF significantly outperforms state-of-the-art models. Code and data are available at \url{https://github.com/lzheng21/SpectralCF}.Comment: RecSys201

Gap Anisotropy in Iron-Based Superconductors: A Point-Contact Andreev Reflection Study of BaFe2−x_{2-x}Nix_{x}As2_2 Single Crystals

We report a systematic investigation on c-axis point-contact Andreev reflection (PCAR) in BaFe$_{2-x}$Ni$_x$As$_2$ superconducting single crystals from underdoped to overdoped regions (0.075 $\leq x\leq 0.15$). At optimal doping ($x=0.1$) the PCAR spectrum feature the structures of two superconducting gap and electron-boson coupling mode. In the $s\pm$ scenario, quantitative analysis using a generalized Blonder-Tinkham-Klapwijk (BTK) formalism with two gaps: one isotropic and another angle dependent, suggest a nodeless state in strong-coupling limit with gap minima on the Fermi surfaces. Upon crossing above the optimal doping ($x > 0.1$), the PCAR spectrum show an in-gap sharp narrow peak at low bias, in contrast to the case of underdoped samples ($x < 0.1$), signaling the onset of deepened gap minima or nodes in the superconducting gap. This result provides evidence of the modulation of the gap amplitude with doping concentration, consistent with the calculations for the orbital dependent pair interaction mediated by the antiferromagnetic spin fluctuations.Comment: 5 pages, 4 figure