Early warning systems

Hepatitis C, a particularly dangerous form of viral hepatitis caused by hepatitis C virus (HCV) infection, is a major socio-economic and public health problem. Due to the rapid development of deep learning, it has become a common practice to apply deep learning to the healthcare industry to improve the effectiveness and accuracy of disease identification. In order to improve the effectiveness and accuracy of hepatitis C detection, this study proposes an improved denoising autoencoder (IDAE) and applies it to hepatitis C disease detection...

Heat waves pose a substantial and increasing risk to public health. Heat health early warning systems (HHEWSs) and response plans are increasingly being adopted to alert people to the health risks posed by days of extreme heat and recommend protective behaviors. However, evidence regarding the effectiveness of HHEWSs remains limited. We examined the impact of heat wave naming on heat-related beliefs and behaviors to ascertain the potential effectiveness of heat wave naming as a heat health risk communication and management tool...

Wetlands provide numerous ecosystem services to the environment, such as nutrient removal and storage. The aim of this work is to evaluate the nutrient dynamics in different sectors within wetland systems in the south of the Samborombón Bay (Argentina) based on hydrological and/or anthropogenic variations. For this purpose, the hydrological features of the wetland were defined through the analysis of satellite images, precipitation and tidal data, and field surveys. Three sectors were identified in the wetland: one with tidal influence, another which is dependent on rainfall, and another that receives inputs from rainfall and from a sewage effluent treatment plant...

Determining the proximity of ecosystems to tipping points is a critical yet complex task, heightened by the growing severity of climate change and local anthropogenic stressors on ecosystem integrity. Spatial Early Warning Signals (EWS) have been recognized for their potential in preemptively signaling regime shifts to degraded states, but their performance in natural systems remains uncertain. In this study, we investigated the performance of 'recovery length' - the spatial extent of recovery from a perturbation - and spatial EWS as early warnings of regime shifts in Posidonia oceanica meadows...

INTRODUCTION: Alterations in motor activity are well-established symptoms of bipolar disorder, and time series of motor activity can be considered complex dynamical systems. In such systems, early warning signals (EWS) occur in a critical transition period preceding a sudden shift (tipping point) in the system. EWS are statistical observations occurring due to a system's declining ability to maintain homeostasis when approaching a tipping point. The aim was to identify critical transition periods preceding bipolar mood state changes...

High-temperature affordable flexible polymer-based pressure sensors integrated with repeatable early fire warning service are strongly desired for harsh environmental applications, yet their creation remains challenging. This work proposed an approach for preparing such advanced integrated sensors based on silver nanoparticles and an ammonium polyphosphate (APP)-modified laminar-structured bulk wood sponge (APP/Ag@WS). Such integrated sensors demonstrated excellent fire warning performance, including a short response time (minimum of 0...

This research evaluated the relationship between daily new Coronavirus Disease 2019 (COVID-19) cases and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) concentrations in wastewater, followed by effects of differential SARS-CoV-2 shedding loads across various COVID-19 outbreaks. Linear regression analyses were utilized to examine the lead time of the SARS-CoV-2 signal in wastewater relative to new COVID-19 clinical cases. During the Delta wave, no lead time was evident, highlighting limited predictive capability of wastewater monitoring during this phase...

BACKGROUND: In the UK National Health Service (NHS), the patient's vital signs are monitored and summarised into a National Early Warning Score (NEWS) score. A set of computer-aided risk scoring systems (CARSS) was developed and validated for predicting in-hospital mortality and sepsis in unplanned admission to hospital using NEWS and routine blood tests results. We sought to assess the accuracy of these models to predict the risk of COVID-19 in unplanned admissions during the first phase of the pandemic...

Losses from catastrophic floods are driving intense efforts to increase preparedness and improve response to disastrous flood events by providing early warnings. Yet accurate flood forecasting remains a challenge due to uncertainty in modeling, calibrating, and validating a useful early warning system. This paper presents the Requisitely Simple (ReqSim) flood forecasting system that includes key variables and processes of basin hydrology and atmospheric forcing in a data-driven modeling framework. The simplicity of the modeling structure and data requirements of the system allows for customization and implementation in any medium to large rain-fed river basin globally, provided there are water level or discharge measurements at the forecast locations...

The banking industry necessitates implementing an early warning system to effectively identify the factors that impact bank managers and enable them to make informed decisions, thereby mitigating systemic risk. Identifying factors that influence banks in times of stability and crisis is crucial, as it ultimately contributes to developing an improved early warning system. This study undertakes a comparative analysis of the stability of Indonesian Islamic and conventional banking across distinct economic regimes-crisis and stability...

Flow sensing exhibits significant potential for monitoring, controlling, and optimizing processes in industries, resource management, and environmental protection. However, achieving wireless real-time and omnidirectional sensing of gas/liquid flow on a simple, self-contained device without external power support has remained a formidable challenge. In this study, a compact-sized, fully self-powered wireless sensing flowmeter (CSWF) is introduced with a small size diameter of down to less than 50 mm, which can transmit real-time and omnidirectional wireless signals, as driven by a rotating triboelectric nanogenerator (R-TENG)...

BACKGROUND: Malaria remains one the leading communicable causes of death. Approximately half of the world's population is considered at risk of infection, predominantly in African and South Asian countries. Although malaria is preventable, heterogeneity in sociodemographic and environmental risk factors over time and across diverse geographical and climatological regions make outbreak prediction challenging. Data-driven approaches accounting for spatiotemporal variability could offer potential for location-specific early warning tools for malaria...

War and peace, spanning history, deeply affect society, economy, and individuals. Grasping their dynamics is vital to lessen harm and foster global peace. Yet, quantifying them remains hard. Our goal is to create a simple qualitative model using landscape and flux theory, exploring war and peace mechanisms. In this symmetric network, they appear as separate attraction basins, dynamically shifting. Analyzing landscape shape gives insights into global stability. Near critical points, indicators like cross correlations, autocorrelation times, and flickering frequency surge, as warnings...

The global incidence of infectious diseases has increased in recent years, posing a significant threat to human health. Hospitals typically serve as frontline institutions for detecting infectious diseases. However, accurately identifying warning signals of infectious diseases in a timely manner, especially emerging infectious diseases, can be challenging. Consequently, there is a pressing need to integrate treatment and disease prevention data to conduct comprehensive analyses aimed at preventing and controlling infectious diseases within hospitals...

BACKGROUND:  Nurses are at the frontline of detecting patient deterioration. We developed Communicating Narrative Concerns Entered by Registered Nurses (CONCERN), an early warning system for clinical deterioration that generates a risk prediction score utilizing nursing data. CONCERN was implemented as a randomized clinical trial at two health systems in the Northeastern United States. Following the implementation of CONCERN, our team sought to develop the CONCERN Implementation Toolkit to enable other hospital systems to adopt CONCERN...

UNLABELLED: This study adds to knowledge by specifically focusing on the dam spillage-induced floods within a fast-urbanising city with weak law enforcement in a developing country. Employing a sequential mixed-method approach, we first selected and analysed data from 120 respondents through a survey and complemented it with key informants residing in the communities affected by flooding. The findings revealed that dramatic ramifications of dam spillage-induced floods disrupt the livelihoods of many individuals in the form of disruption to income-generating activities and substantial property loss...

In order to reduce the damage to people's health from diseases that attack the respiratory system such as COVID-19, asthma, and pneumonia, it is desired that patients' breathing can be monitored and alerted in real-time. The emergence of wearable health detection sensing devices has provided a relatively good response to this problem. However, there are still problems such as complex structure and poor performance. This paper introduces a laser-induced graphene (LIG) device that is attached to PDMS. The LIG is produced by laser irradiation of Nomex and subsequently transferred and attached to the PDMS...

Despite providing important ecosystem services, termites are also serious pests of wooden structures. Termites are highly adaptive organisms that cause concern as an invasive species. Predictions of the future spread of their distribution range due to factors such as climate change, urban growth, and global trade present new challenges to our capacity to protect our wood and wood-based materials and structures effectively. Reticulitermes grassei Clément, 1978 (Blattodea: Rhinotermitidae) is a subterranean termite native to the Iberian Peninsula and France, whose global distribution has widened over recent years...

BACKGROUND: Cholelithiasis is one of the most common disorders of hepatobiliary system. Gut bacteria may be involved in the process of gallstone formation and are therefore considered as potential targets for cholelithiasis prediction. OBJECTIVE: To reveal the correlation between cholelithiasis and gut bacteria. METHODS: Stool samples were collected from 100 cholelithiasis and 250 healthy individuals from Huzhou Central Hospital; The 16S rRNA of gut bacteria in the stool samples was sequenced using the third-generation Pacbio sequencing platform; Mothur v...

This study aims to investigate the predictability of surrogate safety measures (SSMs) for real-time crash risk prediction. We conducted a year-long drone video collection on a busy freeway in Nanjing, China, and collected 20 rear-end crashes. The predictability of SSMs was defined as the probability of crash occurrence when using SSMs as precursors to crashes. Ridge regression models were established to explore contributing factors to the predictability of SSMs. Four commonly used SSMs were tested in this study...