1,984 research outputs found
Standards as Barriers Versus Standards as Catalysts: Assessing the Impact of HACCP Implementation on U.S. Seafood Imports
The United States mandated a Hazard Analysis Critical Control Points (HACCP) food safety standard for seafood in 1997. Panel model results for 1990 to 2004 suggest that HACCP introduction had a negative and significant impact on overall imports from the top thirty-three suppliers. While the effect for developed countries was positive, the negative effect for developing countries supports the view of “standards as barriers” versus “standards as catalysts.” A different perspective emerges from individual country-level analysis. Regardless of development status, leading seafood exporters generally experienced a positive HACCP effect, while most other smaller trading partners faced a negative effect
GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos
The interest in video anomaly detection systems that can detect different types of anomalies,
such as violent behaviours in surveillance videos, has gained traction in recent years. The current
approaches employ deep learning to perform anomaly detection in videos, but this approach has
multiple problems. For example, deep learning in general has issues with noise, concept drift,
explainability, and training data volumes. Additionally, anomaly detection in itself is a complex
task and faces challenges such as unknownness, heterogeneity, and class imbalance. Anomaly
detection using deep learning is therefore mainly constrained to generative models such as generative
adversarial networks and autoencoders due to their unsupervised nature; however, even they suffer
from general deep learning issues and are hard to properly train. In this paper, we explore the
capabilities of the Hierarchical Temporal Memory (HTM) algorithm to perform anomaly detection
in videos, as it has favorable properties such as noise tolerance and online learning which combats
concept drift. We introduce a novel version of HTM, named GridHTM, which is a grid-based HTM
architecture specifically for anomaly detection in complex videos such as surveillance footage. We
have tested GridHTM using the VIRAT video surveillance dataset, and the subsequent evaluation
results and online learning capabilities prove the great potential of using our system for real-time
unsupervised anomaly detection in complex videos
Culturally safe speech-language supports for First Nations children: Achieving Sustainable Development Goals 3, 4, 8 and 10
Purpose: Self-determination is foundational to health and well-being for First Nations people. Colonisation has undermined self-determination and widespread effects are observed as disparities in health and well-being. Chronic middle ear disease is more highly prevalent in First Nations children, is associated with delays in speech and language and lower levels of educational readiness. However, there is a paucity of culturally and linguistically sensitive speech-language assessments and habilitation services globally. Focussing on high-income colonial-settler countries (including United States, Canada, Australia and New Zealand), where health disparities are significant, we aim to discuss the importance of and the challenges in providing culturally safe care to First Nations children with communication disabilities. Result: To be effective, both cultural and linguistic diversity and cultural safety must be considered in all aspects of assessment and intervention. Furthermore, speech-language pathologists must be equipped to work with First Nations children with communication disorders. Conclusion: To optimally support First Nations’ children with communication disabilities, services need to be culturally safe, family-centred and strengths-based. This commentary focuses on the United Nations Sustainable Development Goals (SDGs)3, 4, 8 and 10
Impairment of Sexual Life in 3,485 Dermatological Outpatients From a Multicentre Study in 13 European Countries
Skin conditions may have a strong impact on patients' sexual life, and thus influence personal relationships. Sexual issues are difficult to discuss directly in clinical practice, and a mediated instrument may be useful to capture such information. In this study item 9 of the Dermatology Life Quality Index was used to collect information on sexual impact of several skin conditions in 13 European countries. Among 3,485 patients, 23.1% reported sexual problems. The impairment was particularly high in patients with hidradenitis suppurativa, prurigo, blistering disorders, psoriasis, urticaria, eczema, infections of the skin, or pruritus. Sexual impact was strongly associated with depression, anxiety, and suicidal ideation. It was generally more frequent in younger patients and was positively correlated with clinical severity and itch. It is important to address the issue of sexual well-being in the evaluation of patients with skin conditions, since it is often linked to anxiety, depression, and even suicidal ideation.Peer reviewedFinal Published versio
A simplicial gauge theory
We provide an action for gauge theories discretized on simplicial meshes,
inspired by finite element methods. The action is discretely gauge invariant
and we give a proof of consistency. A discrete Noether's theorem that can be
applied to our setting, is also proved.Comment: 24 pages. v2: New version includes a longer introduction and a
discrete Noether's theorem. v3: Section 4 on Noether's theorem has been
expanded with Proposition 8, section 2 has been expanded with a paragraph on
standard LGT. v4: Thorough revision with new introduction and more background
materia
Decisions on statin therapy by patients’ opinions about survival gains: cross sectional survey of general practitioners
HTAD: A Home-Tasks Activities Dataset with Wrist-Accelerometer and Audio Features
In this paper, we present HTAD: A Home Tasks Activities Dataset. The dataset contains wrist-accelerometer and audio data from people performing at-home tasks such as sweeping, brushing teeth, washing hands, or watching TV. These activities represent a subset of activities that are needed to be able to live independently. Being able to detect activities with wearable devices in real-time is important for the realization of assistive technologies with applications in different domains such as elderly care and mental health monitoring. Preliminary results show that using machine learning with the presented dataset leads to promising results, but also there is still improvement potential. By making this dataset public, researchers can test different machine learning algorithms for activity recognition, especially, sensor data fusion methodsacceptedVersio
CELLULAR, A Cell Autophagy Imaging Dataset
Cells in living organisms are dynamic compartments that continuously respond to changes in their environment to maintain physiological homeostasis. While basal autophagy exists in cells to aid in the regular turnover of intracellular material, autophagy is also a critical cellular response to stress, such as nutritional depletion. Conversely, the deregulation of autophagy is linked to several diseases, such as cancer, and hence, autophagy constitutes a potential therapeutic target. Image analysis to follow autophagy in cells, especially on high-content screens, has proven to be a bottleneck. Machine learning (ML) algorithms have recently emerged as crucial in analyzing images to efficiently extract information, thus contributing to a better understanding of the questions at hand. This paper presents CELLULAR, an open dataset consisting of images of cells expressing the autophagy reporter mRFP-EGFP-Atg8a with cell-specific segmentation masks. Each cell is annotated into either basal autophagy, activated autophagy, or unknown. Furthermore, we introduce some preliminary experiments using the dataset that can be used as a baseline for future research
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