6,520 research outputs found
Mitigating Over-smoothing in Transformers via Regularized Nonlocal Functionals
Transformers have achieved remarkable success in a wide range of natural
language processing and computer vision applications. However, the
representation capacity of a deep transformer model is degraded due to the
over-smoothing issue in which the token representations become identical when
the model's depth grows. In this work, we show that self-attention layers in
transformers minimize a functional which promotes smoothness, thereby causing
token uniformity. We then propose a novel regularizer that penalizes the norm
of the difference between the smooth output tokens from self-attention and the
input tokens to preserve the fidelity of the tokens. Minimizing the resulting
regularized energy functional, we derive the Neural Transformer with a
Regularized Nonlocal Functional (NeuTRENO), a novel class of transformer models
that can mitigate the over-smoothing issue. We empirically demonstrate the
advantages of NeuTRENO over the baseline transformers and state-of-the-art
methods in reducing the over-smoothing of token representations on various
practical tasks, including object classification, image segmentation, and
language modeling.Comment: 24 pape
Stability of twin circular tunnels in cohesive-frictional soil using the node-based smoothed finite element method (NS-FEM)
This paper presents an upper bound limit analysis procedure using the node-based smoothed finite element method (NS-FEM) and second order cone programming (SOCP) to evaluate the stability of twin circular tunnels in cohesive-frictional soils subjected to surcharge loading. At first stage, kinematically admissible displacement fields of the tunnel problems are approximated by NS-FEM using triangular elements (NS-FEM-T3). Next, commercial software Mosek is employed to deal with the optimization problems, which are formulated as second order cone. Collapse loads as well as failure mechanisms of plane strain tunnels are obtained directly by solving the optimization problems. For twin circular tunnels, the distance between centers of two parallel tunnels is the major parameter used to determine the stability. In this study, the effects of mechanical soil properties and the ratio of tunnel diameter and the depth to the tunnel stability are investigated. Numerical results are verified with those available to demonstrate the accuracy of the proposed method
The cost effectiveness of brief intervention by primary health care workers to reduce alcohol related disease and injury in Vietnam
A Clinical and Epidemiological Investigation of the First Reported Human Infection With the Zoonotic Parasite Trypanosoma evansi in Southeast Asia
Background. Trypanosoma is a genus of unicellular parasitic flagellate protozoa. Trypanosoma brucei species and Trypanosoma cruzi are the major agents of human trypanosomiasis; other Trypanosoma species can cause human disease, but are rare. In March 2015, a 38-year-old woman presented to a healthcare facility in southern Vietnam with fever, headache, and arthralgia. Microscopic examination of blood revealed infection with Trypanosoma. Methods. Microscopic observation, polymerase chain reaction (PCR) amplification of blood samples, and serological testing were performed to identify the infecting species. The patient's blood was screened for the trypanocidal protein apolipoprotein L1 (APOL1), and a field investigation was performed to identify the zoonotic source. Results. PCR amplification and serological testing identified the infecting species as Trypanosoma evansi. Despite relapsing 6 weeks after completing amphotericin B therapy, the patient made a complete recovery after 5 weeks of suramin. The patient was found to have 2 wild-type APOL1 alleles and a normal serum APOL1 concentration. After responsive animal sampling in the presumed location of exposure, cattle and/or buffalo were determined to be the most likely source of the infection, with 14 of 30 (47%) animal blood samples testing PCR positive for T. evansi. Conclusions. We report the first laboratory-confirmed case of T. evansi in a previously healthy individual without APOL1 deficiency, potentially contracted via a wound while butchering raw beef, and successfully treated with suramin. A linked epidemiological investigation revealed widespread and previously unidentified burden of T. evansi in local cattle, highlighting the need for surveillance of this infection in animals and the possibility of further human cases
Participatory agro-climate information services: A key component in climate resilient agriculture
The brief promotes participatory agro-climate information services as a key component in achieving climate-smart agriculture. The brief emphasizes that actionable agro-climate information starts with—and responds to—gender-based needs of farmers, integrated at all stages of the value chain. Timely forecasts and accurate agroclimate advisories have been proven to provide farmers with production, adaptation, and mitigation benefits
Willingness to Pay for Improving Household Solid Waste Management in Vietnam
Management of solid waste is a major challenge in urban areas of most parts of the world, especially in developing countries. The study aimed to determine and estimate the willingness to pay (WTP) of the selected households for the improvement of solid waste management in Vietnam. The research evaluated WTP of household solid waste in case studies in Bien Hoa and My Tho cities using contingent valuation method (CVM). The data were collected through a closed-ended questionnaire survey and interviews with 200 households. The results showed that the most willingness to pay was equal to 10,000 and 15,000 VND per month. The respondents were willing to pay in Bien Hoa and My Tho with an average of 14,450 VND (0.63 USD) and 13,000 VND (0.56 USD) per month, respectively. Regression model identified influential factors on WTP of households in the two cities of Vietnam. The factors that significantly influence households’ WTP were monthly household income, education of respondents, age, occupation and solid waste volume (p<0.05). The results of this study can be used for the urban planning and implemented the sustainable development process in Bien Hoa and My Tho cities
Public health responses to influenza in care homes: a questionnaire-based study of local Health Protection Units.
BACKGROUND: Influenza virus infection poses a major threat to the elderly people in residential care. We sought to describe the extent to which local public health services in England were positioned to detect and respond effectively to influenza-like illness (ILI) in nursing homes. METHODS: A questionnaire-based survey was conducted in all 34 Health Protection Units (HPUs) regarding the 2004-05 influenza season. RESULTS: Of the 20 responses, half reported 24 outbreaks of ILI in care homes. The mean resident population attack rate was 41% (range 15-79) with 31 deaths. Staff ILI occurred in 23 of 24 outbreaks. Seven of 20 HPUs stated that a local policy for the management of ILI in nursing homes was in place, with only four specifying the use of neuraminidase inhibitors (NI) for treatment of cases and prophylaxis of residents. In the outbreaks reported, NIs were used for treatment and prophylaxis, respectively, in only 46 and 54% of instances. CONCLUSIONS: Given the availability of effective interventions for treatment and prophylaxis, there is potential to prevent substantial morbidity and mortality from influenza in at-risk populations. This study suggests that challenges remain in the effective response to influenza outbreaks in care homes and that there are wide variations in practice at local level
Program Management Integrated with Data and Decision Sciences
Program management (PM) complexity depends on the budget size and program types. In general, the program types can be classified into three categories, namely, defense, commercial, and civilian types. This chapter presents and discusses an approach for integrating the PM discipline areas with emerging data science and decision science1 (DDS) for any program type. Additionally, we describe the key PM areas and present a corresponding generalized model consists of a list of multiple PM discipline areas that can be tailored for any program types. To demonstrate the PM-DDS integration approach, we focus on three key PM areas and corresponding PM discipline areas related to schedule, cost, and risk management. These three discipline areas are analyzed to identify appropriate program elements that can be enhanced using existing DDS technology enablers (TEs). We also propose a flexible PM-DSS integration framework by leveraging existing machine learning operations (MLOps) framework. The proposed integration framework is expected to allow for enhancing the program planning and execution by reducing the program risk using a wide range of DDS TEs, including big data analytics, artificial intelligence, machine learning, deep learning, neural networks, and artificial intelligent
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