Model: OpenAlex/bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract
Author: OpenAlex
Pipeline: text-classification
Library: transformers
Tags: transformers, tf, safetensors, bert, text-classification, base_model:google-bert/bert-base-multilingual-cased, base_model:finetune:google-bert/bert-base-multilingual-cased, license:apache-2.0, endpoints_compatible, deploy:azure, region:us
Base models (finetune): id: google-bert/bert-base-multilingual-cased
Card metadata: license: apache-2.0
base_model: bert-base-multilingual-cased
model-index: name: bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract
pipeline_tag: text-classification
widget: <TITLE> From Louvain to Leiden: guaranteeing well-connected communities
<ABSTRACT> Community detection is often used to understand the structure of large and complex networks. One of the most popular algorithms for uncovering community structure is the so-called Louvain algorithm. We show that this algorithm has a major defect that largely went unnoticed until now: the Louvain algorithm may yield arbitrarily badly connected communities. In the worst case, communities may even be disconnected, especially when running the algorithm iteratively. In our experimental analysis, we observe that up to 25% of the communities are badly connected and up to 16% are disconnected. To address this problem, we introduce the Leiden algorithm. We prove that the Leiden algorithm yields communities that are guaranteed to be connected. In addition, we prove that, when the Leiden algorithm is applied iteratively, it converges to a partition in which all subsets of all communities are locally optimally assigned. Furthermore, by relying on a fast local move approach, the Leiden algorithm runs faster than the Louvain algorithm. We demonstrate the performance of the Leiden algorithm for several benchmark and real-world networks. We find that the Leiden algorithm is faster than the Louvain algorithm and uncovers better partitions, in addition to providing explicit guarantees., <TITLE> Cleavage of Structural Proteins during the Assembly of the Head of Bacteriophage T4, <TITLE> NONE
<ABSTRACT> Surface wave (SW) over-the-horizon (OTH) radars are not only widely used for ocean remote sensing, but they can also be exploited in integrated maritime surveillance systems. This paper represents the first part of the description of the statistical and spectral analysis performed on sea backscattered signals recorded by the oceanographic WEllen RAdar (WERA) system. Data were collected on May 13th 2008 in the Bay of Brest, France. The data statistical analysis, after beamforming, shows that for near range cells the signal amplitude fits well the Rayleigh distribution, while for far cells the data show a more pronounced heavy-tailed behavior. The causes can be traced in man-made (i.e. radio communications) and/or natural (i.e. reflections of the transmitted signal through the ionosphere layers, meteor trails) interferences.
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Created: 2024-01-06 12:31:28