Information Filtering on Coupled Social Networks

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm based on the coupled social networks, which considers the effects of both social influence and personalized preference. Experimental results on two real datasets, \emph{Epinions} and \emph{Friendfeed}, show that hybrid pattern can not only provide more accurate recommendations, but also can enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding structure and function of coupled social networks

Regulation of Calcium-Permeable TRPV2 Channel by Insulin in Pancreatic β-Cells

OBJECTIVE—Calcium-permeable cation channel TRPV2 is expressed in pancreatic β-cells. We investigated regulation and function of TRPV2 in β-cells

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan

Unconventional Low-Cost Fabrication and Patterning Techniques for Point of Care Diagnostics

The potential of rapid, quantitative, and sensitive diagnosis has led to many innovative ‘lab on chip’ technologies for point of care diagnostic applications. Because these chips must be designed within strict cost constraints to be widely deployable, recent research in this area has produced extremely novel non-conventional micro- and nano-fabrication innovations. These advances can be leveraged for other biological assays as well, including for custom assay development and academic prototyping. The technologies reviewed here leverage extremely low-cost substrates and easily adoptable ways to pattern both structural and biological materials at high resolution in unprecedented ways. These new approaches offer the promise of more rapid prototyping with less investment in capital equipment as well as greater flexibility in design. Though still in their infancy, these technologies hold potential to improve upon the resolution, sensitivity, flexibility, and cost-savings over more traditional approaches