Pest population dynamics are related to a continental overwintering gradient.

Overwintering success is an important determinant of arthropod populations that must be considered as climate change continues to influence the spatiotemporal population dynamics of agricultural pests. Using a long-term monitoring database and biologically relevant overwintering zones, we modeled the annual and seasonal population dynamics of a common pest, Helicoverpa zea (Boddie), based on three overwintering suitability zones throughout North America using four decades of soil temperatures: the southern range (able to persist through winter), transitional zone (uncertain overwintering survivorship), and northern limits (unable to survive winter). Our model indicates H. zea population dynamics are hierarchically structured with continental-level effects that are partitioned into three geographic zones. Seasonal populations were initially detected in the southern range, where they experienced multiple large population peaks. All three zones experienced a final peak between late July (southern range) and mid-August to mid-September (transitional zone and northern limits). The southern range expanded by 3% since 1981 and is projected to increase by twofold by 2099 but the areas of other zones are expected to decrease in the future. These changes suggest larger populations may persist at higher latitudes in the future due to reduced low-temperature lethal events during winter. Because H. zea is a highly migratory pest, predicting when populations accumulate in one region can inform synchronous or lagged population development in other regions. We show the value of combining long-term datasets, remotely sensed data, and laboratory findings to inform forecasting of insect pests.

Lake browning counteracts cyanobacteria responses to nutrients: Evidence from phytoplankton dynamics in large enclosure experiments and comprehensive observational data.

Lakes worldwide are affected by multiple stressors, including climate change. This includes massive loading of both nutrients and humic substances to lakes during extreme weather events, which also may disrupt thermal stratification. Since multi-stressor effects vary widely in space and time, their combined ecological impacts remain difficult to predict. Therefore, we combined two consecutive large enclosure experiments with a comprehensive time-series and a broad-scale field survey to unravel the combined effects of storm-induced lake browning, nutrient enrichment and deep mixing on phytoplankton communities, focusing particularly on potentially toxic cyanobacterial blooms. The experimental results revealed that browning counteracted the stimulating effect of nutrients on phytoplankton and caused a shift from phototrophic cyanobacteria and chlorophytes to mixotrophic cryptophytes. Light limitation by browning was identified as the likely mechanism underlying this response. Deep-mixing increased microcystin concentrations in clear nutrient-enriched enclosures, caused by upwelling of a metalimnetic Planktothrix rubescens population. Monitoring data from a 25-year time-series of a eutrophic lake and from 588 northern European lakes corroborate the experimental results: Browning suppresses cyanobacteria in terms of both biovolume and proportion of the total phytoplankton biovolume. Both the experimental and observational results indicated a lower total phosphorus threshold for cyanobacterial bloom development in clearwater lakes (10-20 µg P L-1 ) than in humic lakes (20-30 µg P L-1 ). This finding provides management guidance for lakes receiving more nutrients and humic substances due to more frequent extreme weather events.

Review on the current long-term, limited lead electroencephalograms.

In the last century, 10-20 lead EEG recordings became the gold standard of surface EEG recordings, and the 10-20 system provided comparability between international studies. With the emergence of advanced EEG sensors, that may be able to record and process signals in much more compact units, this additional sensor technology now opens up opportunities to revisit current ambulatory EEG recording practices and specific patient populations, and even electrodes that are embedded into the head surface. Here, we aim to provide an overview of current limited sensor long-term EEG systems. We performed a literature review using Pubmed as a database and included the relevant articles. The review identified several systems for recording long-term ambulatory EEGs. In general, EEGs recorded with these modalities can be acquired in ambulatory and home settings, achieve good sensitivity with low false detection rates, are used for automatic seizure detection as well as seizure forecasting, and are well tolerated by patients, but each of them has advantages and disadvantages. Subcutaneous, subgaleal, and subscalp electrodes are minimally invasive and provide stable signals that can record ultra--long-term EEG and are in general less noisy than scalp EEG, but they have limited spatial coverage and require anesthesia, a surgical procedure and a trained surgeon to be placed. Behind and in the ear electrodes are discrete, unobtrusive with a good sensitivity mainly for temporal seizures but might miss extratemporal seizures, recordings could be obscured by muscle artifacts and bilateral ictal patterns might be difficult to register. Finally, recording systems using electrodes in a headband can be easily and quickly placed by the patient or caregiver, but have less spatial coverage and are more prone to movement because electrodes are not attached. Overall, limited EEG recording systems offer a promising opportunity to potentially record targeted EEG with focused indications for prolonged periods, but further validation work is needed.

Patient Safety in Canadian Epilepsy Monitoring Units: A Survey of Current Practices.

BACKGROUND: Guidelines on epilepsy monitoring unit (EMU) standards have been recently published. We aimed to survey Canadian EMUs to describe the landscape of safety practices and compare these to the recommendations from the new guidelines. METHODS: A 34-item survey was created by compiling questions on EMU structure, patient monitoring, equipment, personnel, standardized protocol use, and use of injury prevention tools. The questionnaire was distributed online to 24 Canadian hospital centers performing video-EEG monitoring (VEM) in EMUs. Responses were tabulated and descriptively summarized. RESULTS: In total, 26 EMUs responded (100% response rate), 50% of which were adult EMUs. EMUs were on average active for 23.4 years and had on average 3.6 beds. About 81% of respondents reported having a dedicated area for VEM, and 65% reported having designated EMU beds. Although a video monitoring station was available in 96% of EMUs, only 48% of EMUs provided continuous observation of patients (video and/or physical). A total of 65% of EMUs employed continuous heart monitoring. The technologist-to-patient ratio was 1:1-2 in 52% of EMUs during the day. No technologist supervision was most often reported in the evening and at night. Nurse-to-EMU-patient ratio was mostly 1:1-4 independent of the time of day. Consent forms were required before admission in 27% of EMUs. CONCLUSION: Canadian EMUs performed decently in terms of there being dedicated space for VEM, continuous heart monitoring, and adequate nurse-to-patient ratios. Other practices were quite variable, and adjustments should be made on a case-by-case basis to adhere to the latest guidelines.

Nonlinear trends in abundance and diversity and complex responses to climate change in Arctic arthropods.

Time series data on arthropod populations are critical for understanding the magnitude, direction, and drivers of change. However, most arthropod monitoring programs are short-lived and restricted in taxonomic resolution. Monitoring data from the Arctic are especially underrepresented, yet critical to uncovering and understanding some of the earliest biological responses to rapid environmental change. Clear imprints of climate on the behavior and life history of some Arctic arthropods have been demonstrated, but a synthesis of population-level abundance changes across taxa is lacking. We utilized 24 y of abundance data from Zackenberg in High-Arctic Greenland to assess trends in abundance and diversity and identify potential climatic drivers of abundance changes. Unlike findings from temperate systems, we found a nonlinear pattern, with total arthropod abundance gradually declining during 1996 to 2014, followed by a sharp increase. Family-level diversity showed the opposite pattern, suggesting increasing dominance of a small number of taxa. Total abundance masked more complicated trajectories of family-level abundance, which also frequently varied among habitats. Contrary to expectation in this extreme polar environment, winter and fall conditions and positive density-dependent feedbacks were more common determinants of arthropod dynamics than summer temperature. Together, these data highlight the complexity of characterizing climate change responses even in relatively simple Arctic food webs. Our results underscore the need for data reporting beyond overall trends in biomass or abundance and for including basic research on life history and ecology to achieve a more nuanced understanding of the sensitivity of Arctic and other arthropods to global changes.

A multi-population approach supports common patterns in marine growth and maturation decision in Atlantic salmon (Salmo salar L.) from southern Europe.

This study provides a regional picture of long-term changes in Atlantic salmon growth at the southern edge of their distribution, using a multi-population approach spanning 49 years and five populations. We provide empirical evidence of salmon life history being influenced by a combination of common signals in the marine environment and population-specific signals. We identified an abrupt decline in growth from 1976 and a more recent decline after 2005. As these declines have also been recorded in northern European populations, our study significantly expands a pattern of declining marine growth to include southern European populations, thereby revealing a large-scale synchrony in marine growth patterns for almost five decades. Growth increments during their sea sojourn were characterized by distinct temporal dynamics. At a coarse temporal resolution, growth during the first winter at sea seemed to gradually improve over the study period. However, the analysis of finer seasonal growth patterns revealed ecological bottlenecks of salmon life histories at sea in time and space. Our study reinforces existing evidence of an impact of early marine growth on maturation decision, with small-sized individuals at the end of the first summer at sea being more likely to delay maturation. However, each population was characterized by a specific probabilistic maturation reaction norm, and a local component of growth at sea in which some populations have better growth in some years might further amplify differences in maturation rate. Differences between populations were smaller than those between sexes, suggesting that the sex-specific growth threshold for maturation is a well-conserved evolutionary phenomenon in salmon. Finally, our results illustrate that although most of the gain in length occurs during the first summer at sea, the temporal variability in body length at return is buffered against the decrease in post-smolt growth conditions. The intricate combination of growth over successive seasons, and its interplay with the maturation decision, could be regulating body length by maintaining diversity in early growth trajectories, life histories, and the composition of salmon populations.

The added value of the long-term ecological research network to upscale restoration in Europe.

Achieving global restoration targets poses challenges including the need for long-term research and effective monitoring of success, fostering collaborations across diverse fields and actors, ensuring the availability of suitable reference ecosystems, and securing sustained funding. Yet, these conditions are often lacking, limiting the effectiveness of restoration. We provide an overview of ecological restoration practices in the pan-European region of the Long-term Ecological Research Network (eLTER) and demonstrate the importance of eLTER and its potential contributions to support the implementation of the EU Nature Restoration Law. We developed an online questionnaire to collect information on eLTER restoration experts and restoration projects details including the use of eLTER contributions (e.g. infrastructure, data and knowledge), between November 2021 and March 2022. We identified 62 restoration experts and 42 restoration projects from 18 countries. Our results show that eLTER restoration expertise covers most of the European habitats, diverse degradation states and restoration techniques. Most restoration projects (78%) involved long-term monitoring exceeding the average project lifespan, which has proven necessary to achieve restoration success. No common protocol was used for monitoring and evaluation or cost-benefit estimates, but respondents reported effective projects, mostly financed from national funds, and benefits in five ecosystem services on average covered per project. Key eLTER contributions included providing reference ecosystems, biotic and abiotic background data, and interdisciplinary discussion or stakeholder management. Ecological restoration is time intensive and requires long-term research and monitoring standardization to fully understand the restoration process and to ensure comparability across ecosystems. The eLTER network can help address these challenges providing added-value contributions through its infrastructure, long-term datasets, diversity of expertise and strategies that can help identify best restoration practices and support the EU Nature Restoration Law. Finally, additional and long-term funding from the EU and the private sector is needed to achieve global larger-scale restoration targets.

Improving on mapping long-term surface water with a novel framework based on the Landsat imagery series.

Surface water plays a crucial role in the ecological environment and societal development. Remote sensing detection serves as a significant approach to understand the temporal and spatial change in surface water series (SWS) and to directly construct long-term SWS. Limited by various factors such as cloud, cloud shadow, and problematic satellite sensor monitoring, the existent surface water mapping datasets might be short and incomplete due to losing raw information on certain dates. Improved algorithms are desired to increase the completeness and quality of SWS datasets. The present study proposes an automated framework to detect SWS, based on the Google Earth Engine and Landsat satellite imagery. This framework incorporates implementing a raw image filtering algorithm to increase available images, thereby expanding the completeness. It improves OTSU thresholding by replacing anomaly thresholds with the median value, thus enhancing the accuracy of SWS datasets. Gaps caused by Landsat7 ETM + SLC-off are respired with the random forest algorithm and morphological operations. The results show that this novel framework effectively expands the long-term series of SWS for three surface water bodies with distinct geomorphological patterns. The evaluation of confusion matrices suggests the good performance of extracting surface water, with the overall accuracy ranging from 0.96 to 0.97, and user's accuracy between 0.96 and 0.98, producer's accuracy ranging from 0.83 to 0.89, and Matthews correlation coefficient ranging from 0.87 to 0.9 for several spectral water indices (NDWI, MNDWI, ANNDWI, and AWEI). Compared with the Global Reservoirs Surface Area Dynamics (GRSAD) dataset, our constructed datasets promote greater completeness of SWS datasets by 27.01%-91.89% for the selected water bodies. The proposed framework for detecting SWS shows good potential in enlarging and completing long-term global-scale SWS datasets, capable of supporting assessments of surface-water-related environmental management and disaster prevention.

Feasibility of implementing an integrated long-term database to advance ecosystem-based management in the Laurentian Great Lakes basin.

The North American Great Lakes have been experiencing dramatic change during the past half-century, highlighting the need for holistic, ecosystem-based approaches to management. To assess interest in ecosystem-based management (EBM), including the value of a comprehensive public database that could serve as a repository for the numerous physical, chemical, and biological monitoring Great Lakes datasets that exist, a two-day workshop was organized, which was attended by 40+ Great Lakes researchers, managers, and stakeholders. While we learned during the workshop that EBM is not an explicit mission of many of the participating research, monitoring, and management agencies, most have been conducting research or monitoring activities that can support EBM. These contributions have ranged from single-resource (-sector) management to considering the ecosystem holistically in a decision-making framework. Workshop participants also identified impediments to implementing EBM, including: 1) high anticipated costs; 2) a lack of EBM success stories to garner agency buy-in; and 3) difficulty in establishing common objectives among groups with different mandates (e.g., water quality vs. fisheries production). We discussed as a group solutions to overcome these impediments, including construction of a comprehensive, research-ready database, a prototype of which was presented at the workshop. We collectively felt that such a database would offer a cost-effective means to support EBM approaches by facilitating research that could help identify useful ecosystem indicators and management targets and allow for management strategy evaluations that account for risk and uncertainty when contemplating future decision-making.

Application of diffusive gradient in thin films probes to monitor trace levels of labile methylmercury in freshwaters.

This study aimed to optimize the methods for sampling and analyzing methylmercury (MeHg) concentrated within diffusive gradients in thin films (DGT) and its application to different water bodies. We explored the elution solution for MeHg, comprised of 1.13 mM thiourea and 0.1M HCl, optimizing its volume to 50 mL. In addition, we found that it is necessary to analyze the entire extraction solution after adjusting its pH, to ensure completion of the ethylation reaction. The DGT samplers were deployed in two distinct aquatic environments (i.e., Okjeong Lake and Nakdong River) for up to 6 weeks, and this study demonstrated to predict the time-weighted average concentration with a diffusion coefficient of 7.65 × 10-6 cm2 s-1 for MeHg in the diffusive gel. To assess the diffusive boundary layer (DBL) effects, the DGT samplers with different agarose diffusive gel thickness were deployed. The mass of MeHg accumulated in the DGT resin at a given time decreased with increasing diffusive gel thickness, because of creating longer diffusion pathways within thicker gels. The labile MeHg concentration estimated by the DGT in Okjeong Lake and Nakdong River are found in the range of 61-111 and 55-105 pg L-1, respectively, which were found to be similar to the grab sampling data. Additionally, this study evaluated depth-dependent MeHg in Okjeong Lake. The vertical profile results showed that the concentration of MeHg at the depth of 2.3 and 15.7 m are about 1.5 and 4.6 times of the DGT installed at 0.3 m of the surface layer, respectively, suggesting potential mercury methylation in deep waters. These findings have practical implications for predicting bioavailability, assessing risks, and formulating strategies for water body management and contamination remediation.

Transitioning from microsatellites to SNP-based microhaplotypes in genetic monitoring programmes: Lessons from paired data spanning 20 years.

Many long-term genetic monitoring programmes began before next-generation sequencing became widely available. Older programmes can now transition to new marker systems usually consisting of 1000s of SNP loci, but there are still important questions about comparability, precision, and accuracy of key metrics estimated using SNPs. Ideally, transitioned programmes should capitalize on new information without sacrificing continuity of inference across the time series. We combined existing microsatellite-based genetic monitoring information with SNP-based microhaplotypes obtained from archived samples of Rio Grande silvery minnow (Hybognathus amarus) across a 20-year time series to evaluate point estimates and trajectories of key genetic metrics. Demographic and genetic monitoring bracketed multiple collapses of the wild population and included cases where captive-born repatriates comprised the majority of spawners in the wild. Even with smaller sample sizes, microhaplotypes yielded comparable and in some cases more precise estimates of variance genetic effective population size, multilocus heterozygosity and inbreeding compared to microsatellites because many more microhaplotype loci were available. Microhaplotypes also recorded shifts in allele frequencies associated with population bottlenecks. Trends in microhaplotype-based inbreeding metrics were associated with the fraction of hatchery-reared repatriates to the wild and should be incorporated into future genomic monitoring. Although differences in accuracy and precision of some metrics were observed between marker types, biological inferences and management recommendations were consistent.

Ecosystem resilience to invasion and drought: Insights after 24 years in a rare never-grazed grassland.

Understanding the resilience of ecosystems globally is hampered by the complex and interacting drivers of change characteristic of the Anthropocene. This is true for drylands of the western US, where widespread alteration of disturbance regimes and spread of invasive non-native species occurred with westward expansion during the 1800s, including the introduction of domestic livestock and spread of Bromus tectorum, an invasive non-native annual grass. In addition, this region has experienced a multi-decadal drought not seen for at least 1200 years with potentially large and interacting impacts on native plant communities. Here, we present 24 years of twice-annual plant cover monitoring (1997-2021) from a semiarid grassland never grazed by domestic livestock but subject to a patchy invasion of B. tectorum beginning in ~1994, compare our findings to surveys done in 1967, and examine potential climate drivers of plant community changes. We found a significant warming trend in the study area, with more than 75% of study year temperatures being warmer than average (1966-2021). We observed a native perennial grass community with high resilience to climate forcings with cover values like those in 1967. In invaded patches, B. tectorum cover was greatest in the early years of this study (1997-2001; ~20%-40%) but was subsequently constrained by climate and subtle variation in soils, with limited evidence of long-term impacts to native vegetation, contradicting earlier studies. Our ability to predict year-to-year variation in functional group and species cover with climate metrics varied, with a 12-month integrated index and fall and winter patterns appearing most important. However, declines to near zero live cover in recent years in response to regional drought intensification leave questions regarding the resiliency of intact grasslands to ongoing aridification and whether the vegetation observations reported here may be a leading indicator of impending change in this protected ecosystem.

Perceived seizure risk in epilepsy: Chronic electronic surveys with and without concurrent electroencephalography.

OBJECTIVE: Previous studies suggested that patients with epilepsy might be able to forecast their own seizures. This study aimed to assess the relationships between premonitory symptoms, perceived seizure risk, and future and recent self-reported and electroencephalographically (EEG)-confirmed seizures in ambulatory patients with epilepsy in their natural home environments. METHODS: Long-term e-surveys were collected from patients with and without concurrent EEG recordings. Information obtained from the e-surveys included medication adherence, sleep quality, mood, stress, perceived seizure risk, and seizure occurrences preceding the survey. EEG seizures were identified. Univariate and multivariate generalized linear mixed-effect regression models were used to estimate odds ratios (ORs) for the assessment of the relationships. Results were compared with the seizure forecasting classifiers and device forecasting literature using a mathematical formula converting OR to equivalent area under the curve (AUC). RESULTS: Fifty-four subjects returned 10 269 e-survey entries, with four subjects acquiring concurrent EEG recordings. Univariate analysis revealed that increased stress (OR = 2.01, 95% confidence interval [CI] = 1.12-3.61, AUC = .61, p = .02) was associated with increased relative odds of future self-reported seizures. Multivariate analysis showed that previous self-reported seizures (OR = 5.37, 95% CI = 3.53-8.16, AUC = .76, p < .001) were most strongly associated with future self-reported seizures, and high perceived seizure risk (OR = 3.34, 95% CI = 1.87-5.95, AUC = .69, p < .001) remained significant when prior self-reported seizures were added to the model. No correlation with medication adherence was found. No significant association was found between e-survey responses and subsequent EEG seizures. SIGNIFICANCE: Our results suggest that patients may tend to self-forecast seizures that occur in sequential groupings and that low mood and increased stress may be the result of previous seizures rather than independent premonitory symptoms. Patients in the small cohort with concurrent EEG showed no ability to self-predict EEG seizures. The conversion from OR to AUC values facilitates direct comparison of performance between survey and device studies involving survey premonition and forecasting.

Gapless Electrocardiogram-Monitoring in stroke at high risk of atrial fibrillation.

BACKGROUND AND PURPOSE: Previous studies investigating prolonged electrocardiogram (ECG)-monitoring after ischemic stroke had significant gaps between the index event and the beginning of long-term monitoring. Atrial fibrillation (AF) detection might be higher if prolonged cardiac rhythm documentation is performed with a gapless approach without any interruption of monitoring time. METHODS: This investigator-initiated, prospective study included patients with acute ischemic stroke or transient ischemic attack at three study centers. Participants received gapless ECG-monitoring via telemetry during stroke-unit admission until implantation of an insertable cardiac monitor (ICM) within the first days after the index event. Patients acted as their own controls and also received standard 24-72-h Holter ECG. RESULTS: A total of 110 patients were included, of whom 86 (78.2%) had an embolic stroke of unknown source, 14 (12.7%) had small-vessel disease, and 10 (9.1%) had large-artery disease. AF was newly diagnosed in 17 (15.5%) patients via ICM monitoring, compared to one (0.9%) patient via Holter ECG during 6 months of follow-up (p < 0.001). The detection rate of AF within the first 30 days was 10.0%, which accounted for 64% of all new AF diagnoses. The median duration of the detected episodes was 1.7 (interquartile range = 0.2-4.7) h. All patients with new onset AF were treated with oral anticoagulation. CONCLUSIONS: Gapless ECG-monitoring is an effective strategy to significantly increase the detection rate of AF after ischemic stroke. This finding supports the use of long-term ECG-monitoring with a gapless approach without any interruption in monitoring time as the gold standard for clinical practice.

The recalcitrance and potential toxicity of polycyclic aromatic hydrocarbons within crude oil residues in beach sediments at the BIOS site, nearly forty years later.

The Arctic is a unique environment characterized by extreme conditions, including daylight patterns, sea ice cover, and some of the lowest temperatures on Earth. Such characteristics in tandem present challenges when extrapolating information from oil spill research within warmer, more temperate regions. Consequently, oil spill studies must be conducted within the Arctic to yield accurate and reliable results. Sites of the Baffin Island Oil Spill (BIOS) project (Cape Hatt, Baffin Island, Canadian Arctic) were revisited nearly 40 years after the original oil application to provide long-term monitoring data for Arctic oil spill research. Surface and subsurface sediment samples were collected from the intertidal zone of the 1981 nearshore oil spill experiment (Bay 11), from 1980 supratidal control plots (Crude Oil Point) and 1982 supratidal treatment plots (Bay 106). Samples were analyzed for Polycyclic Aromatic Hydrocarbons (PAHs) and alkylated homologues via Gas Chromatography - Mass Spectrometry (GC-MS). Our results suggest that total mean concentrations of all measured PAHs range from 0.049 to 14 mg/kg, whereas total mean concentrations of the 16 US EPA priority PAHs range from 0.02 to 2.1 mg/kg. The relative proportions of individual PAHs were compared between sampling sites and with the original technical mixture. Where available, percent loss of individual PAHs was compared with data from samples collected at the BIOS site, in 2001. All three sites featured samples where concentrations of various priority PAHs exceeded the established Interim Marine Sediment Quality Guidelines. All supratidal samples contained potentially toxic levels of PAHs. Even after nearly four decades of weathering, the recalcitrant crude oil residues remain a potential hazard for the native organisms. Continued monitoring of this unique study site is crucial for establishing a timeline for oil degradation, and to observe a reduction in toxicity over time.

Single-arm diagnostic electrocardiography with printed graphene on wearable textiles.

Stimulated by the COVID-19 outbreak, the global healthcare industry better acknowledges the necessity of innovating novel methods for remote healthcare monitoring and treating patients outside clinics. Here we report the development of two different types of graphene textile electrodes differentiated by the employed fabrication techniques (i.e., dip-coating and spray printing) and successful demonstration of ergonomic and truly wearable, single-arm diagnostic electrocardiography (SADE) using only 3 electrodes positioned on only 1 arm. The performance of the printed graphene e-textile wearable systems were benchmarked against the "gold standard" silver/silver chloride (Ag/AgCl) "wet" electrodes; achieving excellent correlation up to ∼ 96% and ∼ 98% in ECG recordings (15 s duration) acquired with graphene textiles fabricated by dip-coating and spray printing techniques, respectively. In addition, we successfully implemented automatic detection of heartrate of 8 volunteers (mean value: 74.4 bpm) during 5 min of static and dynamic daily activities and benchmarked their recordings with a standard fingertip photoplethysmography (PPG) device. Heart rate variability (HRV) was calculated, and the root means successive square difference (rMMSD) metric was 30 ms during 5 min of recording. Other cardiac parameters such as R-R interval, QRS complex duration, S-T segment duration, and T-wave duration were also detected and compared to typical chest ECG values.

Biocompatible and Long-Term Monitoring Strategies of Wearable, Ingestible and Implantable Biosensors: Reform the Next Generation Healthcare.

Sensors enable the detection of physiological indicators and pathological markers to assist in the diagnosis, treatment, and long-term monitoring of diseases, in addition to playing an essential role in the observation and evaluation of physiological activities. The development of modern medical activities cannot be separated from the precise detection, reliable acquisition, and intelligent analysis of human body information. Therefore, sensors have become the core of new-generation health technologies along with the Internet of Things (IoTs) and artificial intelligence (AI). Previous research on the sensing of human information has conferred many superior properties on sensors, of which biocompatibility is one of the most important. Recently, biocompatible biosensors have developed rapidly to provide the possibility for the long-term and in-situ monitoring of physiological information. In this review, we summarize the ideal features and engineering realization strategies of three different types of biocompatible biosensors, including wearable, ingestible, and implantable sensors from the level of sensor designing and application. Additionally, the detection targets of the biosensors are further divided into vital life parameters (e.g., body temperature, heart rate, blood pressure, and respiratory rate), biochemical indicators, as well as physical and physiological parameters based on the clinical needs. In this review, starting from the emerging concept of next-generation diagnostics and healthcare technologies, we discuss how biocompatible sensors revolutionize the state-of-art healthcare system unprecedentedly, as well as the challenges and opportunities faced in the future development of biocompatible health sensors.

A Review of Approaches for Mitigating Effects from Variable Operational Environments on Piezoelectric Transducers for Long-Term Structural Health Monitoring.

Extending the service life of ageing infrastructure, transportation structures, and processing and manufacturing plants in an era of limited resources has spurred extensive research and development in structural health monitoring systems and their integration. Even though piezoelectric transducers are not the only sensor technology for SHM, they are widely used for data acquisition from, e.g., wave-based or vibrational non-destructive test methods such as ultrasonic guided waves, acoustic emission, electromechanical impedance, vibration monitoring or modal analysis, but also provide electric power via local energy harvesting for equipment operation. Operational environments include mechanical loads, e.g., stress induced deformations and vibrations, but also stochastic events, such as impact of foreign objects, temperature and humidity changes (e.g., daily and seasonal or process-dependent), and electromagnetic interference. All operator actions, correct or erroneous, as well as unintentional interference by unauthorized people, vandalism, or even cyber-attacks, may affect the performance of the transducers. In nuclear power plants, as well as in aerospace, structures and health monitoring systems are exposed to high-energy electromagnetic or particle radiation or (micro-)meteorite impact. Even if environmental effects are not detrimental for the transducers, they may induce large amounts of non-relevant signals, i.e., coming from sources not related to changes in structural integrity. Selected issues discussed comprise the durability of piezoelectric transducers, and of their coupling and mounting, but also detection and elimination of non-relevant signals and signal de-noising. For long-term service, developing concepts for maintenance and repair, or designing robust or redundant SHM systems, are of importance for the reliable long-term operation of transducers for structural health monitoring.

Comparative Analysis of Power Consumption between MQTT and HTTP Protocols in an IoT Platform Designed and Implemented for Remote Real-Time Monitoring of Long-Term Cold Chain Transport Operations.

IoT platforms for the transportation industry are portable with limited battery life and need real-time and long-term monitoring operations. Since MQTT and HTTP are widely used as the main communication protocols in the IoT, it is imperative to analyze their power consumption to provide quantitative results that help maximize battery life in IoT transportation systems. Although is well known that MQTT consumes less power than HTTP, a comparative analysis of their power consumption with long-time tests and different conditions has not yet been conducted. In this sense, a design and validation of an electronic cost-efficient platform system for remote real-time monitoring is proposed using a NodeMCU module, in which experimentation is carried out for HTTP and MQTT with different QoS levels to make a comparison and demonstrate the differences in power consumption. Furthermore, we characterize the behavior of the batteries in the systems and compare the theoretical analysis with real long-time test results. The experimentation using the MQTT protocol with QoS 0 and 1 was successful, resulting in power savings of 6.03% and 8.33%, respectively, compared with HTTP, demonstrating many more hours in the duration of the batteries, which could be very useful in technological solutions for the transport industry.

Multiple drivers of large-scale lichen decline in boreal forest canopies.

Thin, hair-like lichens (Alectoria, Bryoria, Usnea) form conspicuous epiphyte communities across the boreal biome. These poikilohydric organisms provide important ecosystem functions and are useful indicators of global change. We analyse how environmental drivers influence changes in occurrence and length of these lichens on Norway spruce (Picea abies) over 10 years in managed forests in Sweden using data from >6000 trees. Alectoria and Usnea showed strong declines in southern-central regions, whereas Bryoria declined in northern regions. Overall, relative loss rates across the country ranged from 1.7% per year in Alectoria to 0.5% in Bryoria. These losses contrasted with increased length of Bryoria and Usnea in some regions. Occurrence trajectories (extinction, colonization, presence, absence) on remeasured trees correlated best with temperature, rain, nitrogen deposition, and stand age in multinomial logistic regression models. Our analysis strongly suggests that industrial forestry, in combination with nitrogen, is the main driver of lichen declines. Logging of forests with long continuity of tree cover, short rotation cycles, substrate limitation and low light in dense forests are harmful for lichens. Nitrogen deposition has decreased but is apparently still sufficiently high to prevent recovery. Warming correlated with occurrence trajectories of Alectoria and Bryoria, likely by altering hydration regimes and increasing respiration during autumn/winter. The large-scale lichen decline on an important host has cascading effects on biodiversity and function of boreal forest canopies. Forest management must apply a broad spectrum of methods, including uneven-aged continuous cover forestry and retention of large patches, to secure the ecosystem functions of these important canopy components under future climates. Our findings highlight interactions among drivers of lichen decline (forestry, nitrogen, climate), functional traits (dispersal, lichen colour, sensitivity to nitrogen, water storage), and population processes (extinction/colonization).