Application of Knowledge Sharing at UPT Puskesmas Desa Medan Krio

Objective: This review aims to find a relationship between the increasing number of monkeypox cases, especially in LGBT community, based on the literature study approach and case reports. One of the non-medicamentous ways is to reduce travelling abroad, especially in countries with many monkeypox cases. Preventing direct contact, such as abstaining from sex and using condoms, is also a way to reduce the morbidity of monkeypox infection, especially in LGBT community. The treatment has not proven effective, and the available vaccines, especially in Indonesia, are still limited. Only a few cases in Indonesia have been reported. Method: This research is based on a literature study approach and case reports with article sources obtained from Eurosurveillance and Elsevier. It restricts articles using the keywords "cases that occurred in patients in the LGBT / MSM community" to get relevant data following the current monkeypox outbreak conditions. Result: The appearance of the monkeypox virus in 2022 in 58 countries and Indonesia is no exception, which confirmed 1 case in patients post travelling abroad. The current monkeypox infection is still present, with symptoms that vary from person to person and are typically characterized by reddish rashes. Still, it is primarily confined to the genital, perigenital, and perianal areas. It manifests at various stages of development, in addition to transmission from animals caused by hunting activities or in LGBT ( Lesbian, Gay, Bisexual, and Transgender) communities that have unprotected sex and can be infected through semen and saliva. Conclusion: Monkeypox cases that occur globally in 2022 need further research to reduce and prevent, especially in the LGBT community and those at risk of infection, pregnant women and babies, as well as medical personnel in close contact with patients. One of the non-medical procedures is reducing travel abroad, especially in countries with many cases of monkeypox, and reducing direct contact with sufferers, such as abstinence from sex and using condoms in the LGBT community, is also one way to reduce the morbidity of monkeypox infection. The treatment has not been proven effective, and the existing vaccines, especially in Indonesia, are still limited. Only a few cases in Indonesia have been reported

Differentiable VQ-VAE's for Robust White Matter Streamline Encodings

Given the complex geometry of white matter streamlines, Autoencoders have been proposed as a dimension-reduction tool to simplify the analysis streamlines in a low-dimensional latent spaces. However, despite these recent successes, the majority of encoder architectures only perform dimension reduction on single streamlines as opposed to a full bundle of streamlines. This is a severe limitation of the encoder architecture that completely disregards the global geometric structure of streamlines at the expense of individual fibers. Moreover, the latent space may not be well structured which leads to doubt into their interpretability. In this paper we propose a novel Differentiable Vector Quantized Variational Autoencoder, which are engineered to ingest entire bundles of streamlines as single data-point and provides reliable trustworthy encodings that can then be later used to analyze streamlines in the latent space. Comparisons with several state of the art Autoencoders demonstrate superior performance in both encoding and synthesis.Comment: 5 pages, 4 figures, 1 tabl

RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking

In various natural language processing tasks, passage retrieval and passage re-ranking are two key procedures in finding and ranking relevant information. Since both the two procedures contribute to the final performance, it is important to jointly optimize them in order to achieve mutual improvement. In this paper, we propose a novel joint training approach for dense passage retrieval and passage re-ranking. A major contribution is that we introduce the dynamic listwise distillation, where we design a unified listwise training approach for both the retriever and the re-ranker. During the dynamic distillation, the retriever and the re-ranker can be adaptively improved according to each other's relevance information. We also propose a hybrid data augmentation strategy to construct diverse training instances for listwise training approach. Extensive experiments show the effectiveness of our approach on both MSMARCO and Natural Questions datasets. Our code is available at https://github.com/PaddlePaddle/RocketQA.Comment: EMNLP 202

ChatGPT and Simple Linguistic Inferences: Blind Spots and Blinds

This paper sheds light on the limitations of ChatGPT's understanding capabilities, focusing on simple inference tasks that are typically easy for humans but appear to be challenging for the model. Specifically, we target (i) grammatically-specified entailments, (ii) premises with evidential adverbs of uncertainty, and (iii) monotonicity entailments. We present expert-designed evaluation sets for these inference types and conduct experiments in a zero-shot setup. Our results show that the model struggles with these types of inferences, exhibiting moderate to low accuracy. Moreover, while ChatGPT demonstrates knowledge of the underlying linguistic concepts when prompted directly, it often fails to incorporate this knowledge to make correct inferences. Even more strikingly, further experiments show that embedding the premise under presupposition triggers or non-factive verbs causes the model to predict entailment more frequently {regardless} of the correct semantic label. Overall these results suggest that, despite GPT's celebrated language understanding capacity, ChatGPT has blindspots with respect to certain types of entailment, and that certain entailment-cancelling features act as ``blinds'' overshadowing the semantics of the embedded premise. Our analyses emphasize the need for further research into the linguistic comprehension and reasoning capabilities of LLMs, in order to improve their reliability, and establish their trustworthiness for real-world applications