Search Results (6,785)

Most fire spread is caused by the absence of suppression means at the beginning of the fire. This results in the missed golden time. There are various factors that cause initial fires, such as electrical outlets, general distribution circuits, and oil–vapor–gas cluster spaces. In most cases, these places are out of reach of human hands or they lose the initial suppression time when a fire occurs, causing the spread of fire. This study implements an intelligent fire suppression device that connects sensor IoT based on microcapsules to secure initial fire suppression and golden time in the event of a fire in blind spots that cannot be seen by humans or at a time when it is difficult to recognize a fire. The microcapsule is a micro-collection unit that collects Novec 1230 gas generated in the semiconductor production process. The microcapsule is molded into a form with a fire suppression function and, when a fire occurs, the molded body explodes and absorbs ambient oxygen to suppress the fire. The complex-sensor IoT executes smoke and heat detection generated when a fire is suppressed within 10 s, which ensures the reliability of the detector by notifying of the fire and detecting the ignition point through communication linkages such as Ieee 485 and WiFi or LoRa. Full article

In recent decades, composite materials have been widely used in several fields. The challenge in recent years has been to find an effective and automatable repair technique for these materials. Low-speed impact tests were carried out on panels made from prepregs in carbon fibre and epoxy resin. An innovative repair technique has been tested by injecting resin into the delamination due to the impact event. After the first impact, some panels were repaired and re-impacted, while others were impacted twice consecutively. The data analysis and damage detection by an ultrasound technique demonstrate that the absorbed energy of the twice-impacted panels is lower than that of the repaired ones, demonstrating a configuration similar to that of the panels impacted only once. The results of this research have demonstrated the effectiveness of the repairs. Full article

Background: Differentiated thyroid carcinoma (DTC), mainly papillary (PTC), at low risk of recurrence is currently managed with active surveillance strategies or less aggressive surgeries. However, total thyroidectomy with ¹³¹I treatment is still performed both if these tumors are diagnosed before or occasionally after surgery. This real-life study aimed to evaluate the rate of biochemical, structural, and functional events in a large series of consecutive DTCs at low risk of recurrence treated by total thyroidectomy, but not with ¹³¹I, in a medium–long-term follow-up. Patients and Methods: We evaluated clinical–pathologic data of 383 consecutive patients (2006–2012) with unifocal DTC [T1a/b(s)] at low risk of recurrence, treated with total thyroidectomy but without lymph node dissection and ¹³¹I treatment after surgery. We evaluated if structural, biochemical, and functional events were detected during the follow-up. Results: Females accounted for 75.7% of our study group, and the median age was 50 years. The median tumor dimension was 0.4 cm (range 0.1–1.2). Most of the patients had a unifocal T1a tumor (98.9%), and 73.6% had a classic variant of PTC. We divided the patients according to the absence (group A—n = 276) or presence (group B—n = 107) of interfering TgAb at first control after surgery. After a median follow-up of 10 years, no structural events were detected. Sixteen out of three hundred and eighty-three (4.2%) patients developed biochemical events: 12/276 (4.3%) in group A and 4/107 (3.7%) in group B. The median time elapsed from surgery to detecting a biochemical event was 14.5 and 77.5 months in groups A and B, respectively. No patients performed additional treatments and were followed up with an active surveillance strategy. Conclusions: This study confirmed that patients with DTC at low risk of recurrence showed an excellent outcome in a medium long-term follow-up since no structural events were diagnosed. Significant variations in Tg/TgAb were detected in a few cases, all managed with an active surveillance strategy without the need for other treatments. Therefore, a relaxed follow-up with neck ultrasound and Tg/TgAb measurement is enough to early identify those very unusual cases of recurrence. Full article

Background/Objectives: Relatively little has been established about the association of rapid ventricular response (RVR) with further recurrence of atrial fibrillation (AF). This study investigated the impact of RVR on the recurrence of AF. Methods: Data were obtained from a multicenter, prospective registry of non-valvular AF patients. RVR was defined as AF with a ventricular rate > 110 bpm. The primary endpoint was the recurrence of AF, defined as the first AF detected on 12-lead electrocardiography during follow-up. Secondary endpoints included manifestation of AF during follow-up and major adverse cardiovascular events (MACEs), a composite of thromboembolic events, major bleeding, myocardial infarction, and death. Results: Among 5533 patients, 493 (8.9%) presented RVR. Patients with RVR were younger, had smaller left atrial diameters, and more frequently had paroxysmal AF. During the mean follow-up duration of 28.6 months, the RVR group exhibited significantly lower recurrence of AF (hazard ratio: 0.58, 95% confidence interval: 0.53–0.65, p < 0.001). There was no significant difference in the occurrence of MACEs between patients with RVR and those without RVR (0.96, 0.70–1.31, p = 0.800). AF with RVR was identified as an independent negative predictor of AF recurrence (0.61, 0.53–0.71, p < 0.001). Conclusions: In patients with AF, those with RVR had a significantly lower recurrence of AF without an increase in MACEs. RVR is a favorable marker that may benefit from early rhythm control. Full article

In Canada, vaccine safety studies are often conducted at the provincial/territorial level where the primary data on vaccination reside. Combining health services data from multiple jurisdictions using a pooled data analytic approach would reduce the amount of time needed to detect vaccine safety signals. To determine the difference in the time it would take to identify safety signals using different proportions of the Canadian population, we conducted power and sample size calculations for a hypothetical self-controlled case series-based surveillance analysis. We used scenarios modeled after the real-world examples of myocarditis and vaccine-induced immune thrombotic thrombocytopenia (VITT) following COVID-19 vaccination as our base cases. Our calculations demonstrated that in the case of a myocarditis-type event, a pooled analysis would reduce the time needed to detect a safety signal by over 60% compared to using Ontario data alone. In the case of a VITT-type event, a pooled analysis could detect a safety signal 49 days sooner than using Ontario data alone, potentially averting as many as 30 events. Our analysis demonstrates that there is substantial value in using pan-Canadian health services data to evaluate the safety of vaccines. Efforts should be made to develop a pan-Canadian vaccine data source to allow for an earlier evaluation of suspected adverse events following immunization. Full article

Soil and water bioengineering (SWBE) measures in fire-prone areas are essential for erosion mitigation, revegetation, as well as protection of settlements against inundations and landslides. This study’s aim was to detect erosive areas at the basin scale for SWBE implementation in pre- and post-fire conditions based on a wildfire event in 2019 in southern Ecuador. The Revised Universal Soil Loss Equation (RUSLE) was used in combination with earth observation data to detect the fire-induced change in erosion behavior by adapting the cover management factor (C-factor). To understand the spatial accuracy of the predicted erosion-prone areas, high-resolution data from an Unmanned Aerial Vehicle (UAV) served for comparison and visual interpretation at the sub-basin level. As a result, the mean erosion at the basin was estimated to be 4.08 t ha⁻¹ yr⁻¹ in pre-fire conditions and 4.06 t ha⁻¹ yr⁻¹ in post-fire conditions. The decrease of 0.44% is due to the high autonomous vegetation recovery capacity of grassland in the first post-fire year. Extreme values increased by a factor of 4 in post-fire conditions, indicating the importance of post-fire erosion measures such as SWBE in vulnerable areas. The correct spatial location of highly erosive areas detected by the RUSLE was successfully verified by the UAV data. This confirms the effectivity of combining the RUSLE with very-high-resolution data in identifying areas of high erosion, suggesting potential scalability to other fire-prone regions. Full article

As both satellite imagery and image-based machine learning methods continue to improve and become more accessible, they are being utilized in an increasing number of sectors and applications. Recent applications using convolutional neural networks (CNNs) and satellite imagery include estimating socioeconomic and development indicators such as poverty, road quality, and conflict. This article builds on existing work leveraging satellite imagery and machine learning for estimation or prediction, to explore the potential to extend these methods temporally. Using Landsat 8 imagery and data from the Armed Conflict Location & Event Data Project (ACLED) we produce subnational predictions of the risk of conflict fatalities in Nigeria during 2015, 2017, and 2019 using distinct models trained on both yearly and six-month windows of data from the preceding year. We find that predictions at conflict sites leveraging imagery from the preceding year for training can predict conflict fatalities in the following year with an area under the receiver operating characteristic curve (AUC) of over 75% on average. While models consistently outperform a baseline comparison, and performance in individual periods can be strong (AUC > 80%), changes based on ground conditions such as the geographic scope of conflict can degrade performance in subsequent periods. In addition, we find that training models using an entire year of data slightly outperform models using only six months of data. Overall, the findings suggest CNN-based methods are moderately effective at detecting features in Landsat satellite imagery associated with the risk of fatalities from conflict events across time periods. Full article

OsHV-1 caused detrimental infections in a variety of bivalve species of major importance to aquaculture worldwide. Since 2012, there has been a notable increase in the frequency of mass mortality events of the blood clam associated with OsHV-1 infection. The pathological characteristics, tissue and cellular tropisms of OsHV-1 in A. broughtonii remain unknown. In this study, we sought to investigate the distribution of OsHV-1 in five different organs (mantle, hepatopancreas, gill, foot, and adductor muscle) of A. broughtonii by quantitative PCR, histopathology and in situ hybridization (ISH), to obtain insight into the progression of the viral infection. Our results indicated a continuous increase in viral loads with the progression of OsHV-1 infection, reaching a peak at 48 h or 72 h post-infection according to different tissues. Tissue damage and necrosis, as well as colocalized OsHV-1 ISH signals, were observed primarily in the connective tissues of various organs and gills. Additionally, minor tissue damage accompanied by relatively weak ISH signals was detected in the foot and adductor muscle, which were filled with muscle tissue. The predominant cell types labeled by ISH signals were infiltrated hemocytes, fibroblastic-like cells, and flat cells in the gill filaments. These results collectively illustrated the progressive alterations in pathological confusion and OsHV-1 distribution in A. broughtonii, which represent most of the possible responses of cells and tissues to the virus. Full article

In this study, a spatiotemporal analysis of drought occurrence and trends across Sicily using ERA50-Land continuous gridded data is carried out. We first use the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) to evaluate drought conditions at various time scales from 1950 to 2023. Then, the Modified Mann–Kendall test was employed to detect trends and Sen’s slope estimator was used to quantify their magnitude. An analysis of the historical series confirms that 2002 was the most severe drought year, impacting all time scales from short-term to long-term. The spatial analysis revealed that the western regions of Sicily experienced the highest severity and frequency of drought events. In contrast, the northeastern regions were less severely affected compared with the other parts of the island. The analysis detects significant increasing trends in SPI values in the eastern coastal areas of the island, which are related to a possible historical increase in precipitation. On the other hand, the analysis of the SPEI indicates significant decreasing trends in the western part of the island, which are mainly related to increased evapotranspiration rates. These results are partially consistent with previous analyses of future climate change scenarios, where changes in the SPEI values in the island are projected to be way clearer than changes in SPI values. Full article

There has been a recent increase in the frequency of mass disaster events. Following these events, the rapid location of victims is paramount. Currently, the most reliable search method is scent detection dogs, which use their sense of smell to locate victims accurately and efficiently. Despite their efficacy, they have limited working times, can give false positive responses, and involve high costs. Therefore, alternative methods for detecting volatile compounds are needed, such as using electronic noses (e-noses). An e-nose named the ‘NOS.E’ was developed and has been used successfully to detect VOCs released from human remains in an open-air environment. However, the system’s full capabilities are currently unknown, and therefore, this work aimed to evaluate the NOS.E to determine the efficacy of detection and expected sensor response. This was achieved using analytical standards representative of known human ante-mortem and decomposition VOCs. Standards were air diluted in Tedlar gas sampling bags and sampled using the NOS.E. This study concluded that the e-nose could detect and differentiate a range of VOCs prevalent in ante-mortem and decomposition VOC profiles, with an average LOD of 7.9 ppm, across a range of different chemical classes. The NOS.E was then utilized in a simulated mass disaster scenario using donated human cadavers, where the system showed a significant difference between the known human donor and control samples from day 3 post-mortem. Overall, the NOS.E was advantageous: the system had low detection limits while offering portability, shorter sampling times, and lower costs than dogs and benchtop analytical instruments. Full article

The growing frequency of news arrivals, partly fueled by the proliferation of data sources, has made the assumptions of the classical probability of informed trading (PIN) model outdated. In particular, the model’s assumption of a single type of information event no longer reflects the complexity of modern financial markets, making the accurate detection of information types (layers) crucial for estimating the probability of informed trading. We propose a layer detection algorithm to accurately find the number of distinct information types within a dataset. It identifies the number of information layers by clustering order imbalances and examining their homogeneity using properly constructed confidence intervals for the Skellam distribution. We show that our algorithm manages to find the number of information layers with very high accuracy both when uninformed buyer and seller intensities are equal and when they differ from each other (i.e., between 86% and 95% accuracy rates). We work with more than 500,000 simulations of quarterly datasets with various characteristics and make a large set of robustness checks. Full article

Background: Limited research exists for use of transcutaneous spinal stimulation (TSS) in pediatric spinal cord injuries (SCI) to improve walking outcomes, especially in children diagnosed with SCI secondary to acute flaccid myelitis (AFM). Objective: This case series demonstrates the feasibility and efficacy of TSS paired with gait training in children diagnosed with AFM. Methods: A total of 4 participants diagnosed with incomplete SCI secondary to AFM completed 22, 2-h therapy sessions over 5–8 weeks. TSS paired with body weight-supported treadmill training (BWSTT) was provided for the first 30 min of each session. Changes in walking function were assessed through the 6 min walk test (6MWT), Timed Up and Go (TUG), 10 m walk test (10MWT), and walking index for spinal cord injury II (WISCI-II). To assess safety and feasibility, pain, adverse events, and participant and therapist exertion were monitored. Results: All participants tolerated the TSS intervention without pain or an adverse response. Changes in the 6MWT exceeded the minimal clinically important difference (MCID) for three participants and WISCI-II exceeding the minimal detectable change (MDC) for two of the participants. Conclusions: These results demonstrate that TSS is a safe and clinically feasible intervention for pediatric patients with AFM and may supplement gait-based interventions to facilitate improvements in walking function. Full article

Ruminant abortion events cause economic losses. Despite the importance of livestock production for food security and the livelihoods of millions of people in the world’s poorest communities, very little is known about the scale, magnitude, or causes of these abortions in Africa and Asia. The aim of this review was to determine the current status of surveillance measures adopted for ruminant abortigenic pathogens in Africa and Asia and to explore feasible surveillance technologies. A systematic literature search was conducted using PRISMA guidelines for studies published between 1 January 1990 and 1 May 2024 that reported epidemiological surveys of abortigenic pathogens Africa and Asia. A meta-analysis was used to estimate the species-specific sero-prevalence of the abortigenic agents and the regions where they were detected. In the systematic literature search, 39 full-text manuscripts were included. The most prevalent abortigenic pathogens with sero-prevalence greater than 10% were BHV-1, Brucella, Chlamydia abortus, Neospora caninum, RVFV, and Waddlia chondrophila in cattle, BVDV in sheep, and RVFV and Toxoplasma gondii in goats in Africa. In Asia, Anaplasma, BHV-1, Bluetongue virus, Brucella, and BVDV were prevalent in cattle, whereas Mycoplasma was important in goats and sheep. Full article

The atmosphere is a complex nonlinear system, with the information of its temperature, water vapor, pressure, and cloud being crucial aspects of remote-sensing data analysis. There exist intricate interactions among these internal components, such as convection, radiation, and humidity exchange. Atmospheric phenomena span multiple spatial and temporal scales, from small-scale thunderstorms to large-scale events like El Niño. The dynamic interactions across different scales, along with external disturbances to the atmospheric system, such as variations in solar radiation and Earth surface conditions, contribute to the chaotic nature of the atmosphere, making long-term predictions challenging. Grasping the intrinsic chaotic dynamics is essential for advancing atmospheric analysis, which holds profound implications for enhancing meteorological forecasts, mitigating disaster risks, and safeguarding ecological systems. To validate the chaotic nature of the atmosphere, this paper reviewed the definitions and main features of chaotic systems, elucidated the method of phase space reconstruction centered on Takens’ theorem, and categorized the qualitative and quantitative methods for determining the chaotic nature of time series data. Among quantitative methods, the Wolf method is used to calculate the Largest Lyapunov Exponents, while the G–P method is used to calculate the correlation dimensions. A new method named Improved Saturated Correlation Dimension method was proposed to address the subjectivity and noise sensitivity inherent in the traditional G–P method. Subsequently, the Largest Lyapunov Exponents and saturated correlation dimensions were utilized to conduct a quantitative analysis of FY-4A and Himawari-8 remote-sensing infrared observation data, and ERA5 reanalysis data. For both short-term remote-sensing data and long-term reanalysis data, the results showed that more than 99.91% of the regional points have corresponding sequences with positive Largest Lyapunov exponents and all the regional points have correlation dimensions that tended to saturate at values greater than 1 with increasing embedding dimensions, thereby proving that the atmospheric system exhibits chaotic properties on both short and long temporal scales, with extreme sensitivity to initial conditions. This conclusion provided a theoretical foundation for the short-term prediction of atmospheric infrared radiation field variables and the detection of weak, time-sensitive signals in complex atmospheric environments. Full article