Deep Learning (DL) has proved to be a promising methodology for classification, recognition, prediction and end-to-end tasks. Recently it has proved its high potential in healthcare applications demostrating to be a succesful approach for physiological signals analysis. Therefore, in this paper we survey the lastest scientific research on deep learning in physiological signal data. The purpose of this paper is to indentify the lastest contributions on this field and overview lastest deep learning approaches.

The High-latitude Ionosphere Dynamics for Research Applications (HIDRA) model is part of the Multiscale Atmosphere-Geospace Environment (MAGE) model under development by the Center for Geospace Storms (CGS) NASA DRIVE Science Center. This study employs HIDRA to simulate upflows of H+, He+, O+, and N+ ions, with a particular focus on the relative N+ concentrations, production and loss mechanisms, and thermal upflow drivers as functions of season, solar activity, and magnetospheric convection. The simulation results demonstrate that N+ densities typically exceed He+ densities, N+ densities are typically ~10% O+ densities, and N+ concentrations at quiet-time are approximately 50-100% of N+ concentrations during storm-time. Furthermore, the N+ and O+ upflow fluxes show similar trends with variations in magnetospheric driving. The inclusion of ion-neutral chemical reactions involving metastable atoms is shown to have significant effects on N+ production rates. With this metastable chemistry included, the simulated ion density profiles compare favorably with satellite measurements from Atmosphere Explorer C (AE-C) and Orbiting Geophysical Observatory 6 (OGO-6).

We examined large-amplitude inertia gravity waves (GWs) over Syowa Station, Antarctica, comparing PANSY radar data and ERA5 reanalysis from October 2015 to September 2016. Focusing on large-amplitude events with a large absolute momentum flux (AMF), hodograph analysis was applied to estimate the wave parameters and found that the percentage of these waves with a downward phase velocity increased with altitude. Vertical wavelengths shortened, intrinsic periods lengthened, and horizontal wavelengths became longer with increasing altitude. Southward propagation of GWs was predominant in the stratosphere. Compared to a previous study, the wave parameters’ altitude variation remained consistent, but horizontal and vertical wavelengths were longer in this study. ERA5 underestimated AMF by about 1/5 between 5 and 12.5 km, with a larger underestimation at higher altitudes. The underestimation was related to the power spectra of horizontal and vertical winds, particularly vertical winds. The greater underestimation in the stratosphere might be due to ERA5’s vertical grid spacing and shorter vertical wavelengths of dominant GWs.

Dong Wanga,b,*, Paul C. Struika, Lei Liangb & Xinyou Yina,*a Centre for Crop Systems Analysis, Department of Plant Sciences, Wageningen University & Research, P.O. Box 430, 6700 AK Wageningen, The Netherlandsb Shanghai Lankuaikei Technology Development Co. Ltd., No. 888 Huanhu West 2nd Road, Pudong New District, Shanghai, China*Corresponding Authors: Dong Wang (dong.wang@wur.nl; dong.wang@lankuaikei.cn ); Xinyou Yin (xinyou.yin@wur.nl)

Dong Wanga,b, Paul C. Struika, Lei Liangb,* & Xinyou Yina,*a Centre for Crop Systems Analysis, Department of Plant Sciences, Wageningen University & Research, P.O. Box 430, 6700 AK Wageningen, The Netherlandsb Shanghai Lankuaikei Technology Development Co. Ltd., No. 888 Huanhu West 2nd Road, Pudong New District, Shanghai, China*Corresponding AuthorsE-mail address: xinyou.yin@wur.nl, lei.liang@lankuaikei.cn

We showcase steps in prototyping and programming TRITON, a system for real-time telemetry in oceans using Internet of Things and LoRa. TRITON encompasses tags and receiver antennas (solar powered and electrically powered gateways).

AbstractAutism spectrum disorder (ASD) is a complex neurodevelopmental disorder that impacts a variety of cognitive and behavioral domains. While a genetic component of ASD has been well-established, none of the numerous syndromic genes identified in humans accounts for more than 1% of the clinical patients. Due to this large number of target genes, numerous mouse models of the disorder have been generated. However, the focus on distinct brain circuits, behavioral phenotypes and diverse experimental approaches has made it difficult to synthesize the overwhelming number of model animal studies into concrete throughlines that connect the data across levels of investigation. Here we chose to focus on one circuit, the hippocampus, and one hypothesis, a shift in excitatory/inhibitory balance, to examine, from the level of the tripartite synapse up to the level of in vivo circuit activity, the key commonalities across disparate models that can illustrate a path towards a better mechanistic understanding of ASD’s impact on hippocampal circuit function.

Subtitle: A word of caution in the use of Impella in patients with cardiogenic shockAuthor: Mohammad Reza Movahed, MD, PhD 1,2,3University of Arizona Tucson1 University of Arizona Phoenix2Correspondent:M Reza Movahed, MD, PhD, FACP, FACC, FSCAI, FCCPClinical Professor of Medicine, University of Arizona, TucsonClinical Professor of Medicine, University of Arizona, Phoenix1501 No Campbell AvenTucson, AZ 85724Tel: 949 400 0091Email: rmova@aol.comConflict of interest: NoneKeywords: Acute coronary syndrome; cardiogenic shock; shock; cardiac assist device; IABP; cardiac support; congestive heart failure; device use; myocardial infarction; ImpellaWith great interest, I read the manuscript entitled “Comparative Effectiveness of Percutaneous Microaxial Left Ventricular Assist Device (MCS)  vs Intra-Aortic Balloon Pump or No Mechanical Circulatory Support in Patients With Cardiogenic Shock” in JAMA Cardiology. (1) They found that the adjusted 30-day mortality risk post-PCI was 41.3% in the IABP cohort which was 11.4% lower than with the use of MCS and was similar to no device et al (difference IABP vs no device 3.1%). Their findings were consistent even though they adjusted for every possible confounding factor.  Despite their very convincing findings, the authors downplay the higher mortality found in the MCS cohort.  They also avoided acceptance that mortality was much lower in the IABP cohort in comparison to MCS and was similar to any device use despite the fact that most patients treated with IABP are much sicker and if IABP had no positive effect on mortality, higher mortality suggesting a positive effect of IABP on mortality in their patients with cardiogenic shock.  We published a preprint paper (2) pending peer review publication by analyzing over 844,020 patients with all types of cardiogenic shocks using the largest available Nationwide Inpatient Sample (NIS) database. 101,870 were treated with IABP and 39,645 with an Impella. Consistent with their results, we found much higher inpatient mortality rates with Impella use despite adjusting for over 47 confounding factors. Regardless of the severity or any underlying condition, Impella increased mortality in patients with acute myocardial infarction-induced cardiogenic shock (AMICS) by approximately 30% whereas IABP reduced mortality by over 30%  regardless of severity or hospital type. The benefit of IABP was also consistent regardless of comorbidities and also was highly significant in comparison to no device in all subgroup cohorts. The currently available literature is also consistent with worse outcomes with the Impella device. Two meta-analyses of Impella trials showed worse outcomes using Impella in patients with AMICS. (3,4) Finally, using the NIS database, patients with AMICS showed significantly higher mortality. (5)  Based on increasing mounting data, Impella use in patients with cardiogenic shock appears to cause harm whereas IABP may be beneficial with no significant harm noted. Therefore, until large randomized trials are conducted, cardiologists should utilize IABP first in cardiogenic shock patients and exert utmost caution in the judiciary use of Impella and utilize it only in selected patients until more safety data are available..

Author: Mohammad Reza Movahed, MD, PhD, FACP, FCCP, FACC, FSCAI1,2,3University of Arizona Tucson1 University of Arizona Phoenix2Correspondent:M Reza Movahed, MD, PhD, FACP, FACC, FSCAI, FCCPClinical Professor of Medicine, University of Arizona, TucsonClinical Professor of Medicine, University of Arizona, Phoenix1501 No Campbell AvenTucson, AZ 85724Tel: 949 400 0091Email: rmova@aol.comConflict of interest: NoneKeywords: Acute coronary syndrome; Wellen EKG; Inverted U waves; anterior myocardial infarction; proximal left anterior ascending artery; acute myocardial infarctionWith great interest, I read the paper about challenges in Electrocardiography entitled “Inverted U Waves—Red Flags in Electrocardiogram” by Shu et al. (1)  Initially, the authors correctly described Wellen’s syndrome (2) that was seen in their patient’s first  EKG consistent with proximal LAD disease. However, they described the second EKG as an Inverted U wave syndrome with reference to Dr. Gerson who described first time this condition. Unfortunately, the authors did not review EKGs that were published under inverted U waves in the literature including original Dr. Gerson’s papers. By reviewing published EKGs under inverted U wave including the referenced Dr. Gerson publication, it can clearly be seen that the so-called inverted U wave is actually a terminally inverted T wave similar to Wellen’s description of Wellen’s EKG as inverted U wave. (3,4) Figures below are showing the original EKG illustration described by Dr. Gerson as inverted U wave syndrome.  The first EKG is from the paper describing an inverted U wave after exercise and the second EKG is from the subsequent paper describing an inverted U wave at rest as a warning sign for proximal LAD lesions:

1. IntroductionMany authors (1) using unjustified Medina Coronary bifurcation lesion classification that unfortunately divides true bifurcation lesions into three unnecessary groups: 111, 101, and 011 as opposed to The Movahed classification summarizing true bifurcation lesions into one simple category called B2 lesions.

IntroductionCardiovascular disease (CVD) is the leading cause of death worldwide. The total number of cardiovascular disease cases nearly doubled from 1990 to 2019 from 271 million to 523 million.1 One of the main treatments for hyperlipidemia and CVD is a reduction in low density lipoprotein cholesterol (LDL-C). Multiple drugs are available on the market that reduce LDL-C including statins, proprotein convertase kexin/subtilisin type 9 (PCSK9) inhibitors, and ezetimibe. Statins are the most widely prescribed drug in this class. Moderate statin therapy has been shown to reduce LDL-C levels by 30-45%, while high-intensity statin therapy can provide reductions of over 50%.2However, some patients, such as those with familial hypercholesterolemia (FH), cannot reach target LDL-C goals with statin therapy alone. Both the American Heart Association and the European Atherosclerosis Society recommend ezetimibe and PCSK9 inhibitors as secondary treatments for at-risk patients with insufficient LDL-C reductions.3An alternate approach to cholesterol reduction involves using natural products, which are often less costly than their synthetic counterparts and tend to have fewer side effects. The natural compound berberine (Figure 1) is of particular interest for several reasons. First, it lowers cholesterol via multiple pathways.4–9Furthermore, it attenuates inflammation associated with CVD,10,11 Alzheimer’s disease (AD),12–14 and diabetes15,16 by reducing pro-inflammatory cytokines. It is also effective in treating cancer cells17,18. This suggests that it could improve health outcomes for multiple diseases simultaneously.

The process of writing a research paper can be challenging, especially when it comes to conducting a literature review. However, with the advent of artificial intelligence (AI) tools, researchers can conduct their research more efficiently than ever before. SciSpace is an AI-powered tool developed to help researchers read various papers and identify gaps in the current literature. This paper delves into a detailed study of critical features of SciSpace, its pros and cons, and a review of its features. This paper aims to identify the relevant literature on the topic "Retracted Publications in Health Sciences" using the literature search tool SciSpace.

Climate change is likely to alter the selective pressures that drive shifts in adaptive variation. For species with long life histories and low dispersion capacities, rapid climate change could impede the migration of beneficial alleles and their ability to track changing environments. Disentangling the processes of adaptive genetic variation in tree species has important implications for conservation and forest management. In this study, we used landscape genomic approaches and phenotypic data from range-wide sampling to investigate the adaptive genetic and phenotypic variation of the oak Quercus longinux, which is endemic in Taiwan. Among 2,000 single-nucleotide polymorphisms (SNPs) generated by double-digested restriction-site associated DNA (ddRAD) sequencing from 205 individuals, 35 drought- and freeze-resistance genes exhibited signatures of natural selection driven by various environmental pressures. GradientForest and redundancy analysis showed that these putative adaptive SNPs had elevated associations with climate and soil variations. The proportion of joint effects of demography, geology, and environments was high, indicating covariation of environmental gradients and colonization history. Compared with other populations, Q. longinux var. kuoi, a unique variety limited to southern Taiwan, exhibited substantial phenotypic, ecological, and adaptive divergence. Finally, we used the environmentally associated SNPs to estimate the genetic offset for each individual under different climate change scenarios, which revealed that edge populations in northern and southeastern Taiwan may be threatened by rising temperatures and reallocation of precipitation. Our study shed light on the pattern of environment-driven adaptation and provides prediction for future vulnerability of island oaks in subtropical and tropical regions. Keywordsclimate change, genetic offset, landscape genomics, local adaptation, natural selection, Quercus

A document by Wieland Heim. Click on the document to view its contents.

Short title: Respiratory Maneuvers during Invasive Cardiac ProceduresMehrbod Vakhshoori MD1, Mohammad Reza Movahed MD, PhD 1,2University of Arizona Sarver Heart Center, Tucson, Arizona1University of Arizona, College of Medicine, Phoenix, Arizona2

Dry bean (Phaseolus vulgaris L.) is the third largest pulse crop grown in Canada. Due to climate change and extreme weather, dry bean varieties are subjected to abiotic and biotic stresses, which affect yield stability and seed quality. Development of resilient cultivars is the most effective strategy to ensure productivity and environmental sustainability of dry bean crop. In this project, key phenotypic traits will be extracted for genetic improvement and development of elite cultivars with early maturity and high yield. Traditional phenotyping approaches are rigorous, time-consuming, and subject to human errors. Unmanned aerial vehicle (UAV)-based high-throughput phenotyping (HTP) has been changing the way of doing large-scale phenotyping in plant breeding. The use of aerial imaging systems offers a potential solution to provide an intensive tool for complex traits assessment to evaluate a large number of dry bean genotypes. By this, HTP technique will be optimized to improve selection efficiency of agronomic, physiological and disease resistance traits. In this study, two dry bean field trials, Advanced Yield Trial (AYT) consisting of F7 generation [yellow bean (5 entries), Pinto bean (20 entries)], and Performance Yield Trial (PeYT) of F8-F10 generation (49 entries) were grown in a randomized-block design at the Fairfield Research Farm at AAFC Lethbridge, AB. Both field trials were imaged at the specific developmental stages (vegetative, flowering, maturity) using UAV mounted RGB and multispectral sensors. The acquired imagery have been processed to accurately overlay images from different dates (time-series data comparison). We analyzed three-time point RGB and multispectral images to identify valuable traits such as canopy height, crop lodging, physiological maturity and accumulation of crop biomass over time. With the preliminary results, we found the utilization of UAV-based HTP has significant advantage in non-destructive measurements of canopy-level functional traits. Assessment of these traits at same climatic region can be used to identify crop characteristics that are important for screening of high-quality dry bean experimental lines and cultivars in field conditions. In the long term, it will provide a consistent and reliable information system to rapidly screen thousands of breeding populations individually that need to be genotyped for morphological and physiological functional traits.

A document by David Ortega-Paredes. Click on the document to view its contents.

Mars hosts the largest volcano in our solar system, Mons Olympus. Up until now, flexural isostasy has commonly been used to understand the relationship between observed topography, crustal structure, and gravity. NASA’s InSight mission has brought new information about the Martian lithosphere, which warrants a re-analysis of the support of the large volcanic complex. After conducting spectral analysis on the topographic and gravity results from the flexural models, the gravitational signal of Martian topography with thin shell compensation fits well with the observed free-air anomaly for degrees, n≥2. The Martian lithosphere can be modelled by a thin shell model using the following parameters: crustal thickness of 60 ±10 km, crustal density of 3050 ±50 kg/m3, mantle density of 3550 ±100 kg/m3, and the best-fit elastic thickness (Te) is found to be 80 ±5 km. The remaining short scale gravity residuals give insight in Martian crustal density distributions. There appear to be buried mass anomalies in the subsurface of the northern polar plains, suggesting an older history of the northern hemisphere of Mars. A mismatch between modeled and observed gravity field for the long-wavelengths (between n=2-6 degrees) exists. The location of the residual anomaly correlates with the Tharsis Rise. which suggests active large-scale dynamic support of the volcanic region. A substantial negative mass anomaly in the mantle underneath the Tharsis Region can explain the gravity residual. Could mantle convection is still be active in Mars, explaining the relatively young geologic surface volcanism on Mars.

Islanding detection is becoming a vital aspect of the power system as the penetration of distributed generators in the utility power system continues to grow. If the distribution generation (DG) capacity matches the connected feeder load the islanding detection takes longer due to the minimal power imbalance between the DG and the utilities prior to islanding event. This research work proposes a slip and acceleration angle-based islanding detection algorithm using phasor measurement unit (PMU) voltage angle data. Specifically, this research utilizes the grid and DG bus voltage angles in the form of their slip and acceleration angle parameters. This research work presents the performance results of the proposed islanding detection algorithm for the under frequency, over frequency, and match frequency islanding conditions. The proposed algorithm is developed using IEEE 30 bus system and validate with the actual Utility Kerteh system (located in Terengganu, Malaysia) based on simulated PMU voltage angle data for 8 different island and non-island cases. Notably, the proposed algorithm shows that it can detect all islanding conditions of the Utility Kerteh system at 20ms, which means it requires only one cycle duration after island incepts in the network.

The Irish migration legal framework (MLF) attracts economic migrants to fuel the national economy in the era of globalization, especially for balancing the rapidly ageing population pyramid. The approach closely aligns with the key prisms of domestic politics, institutionalism, and neoliberalism, which focuses on increasing the number of work permit holders rather than operationalizing their employment, social and gender needs to be met through concrete legal measures, so that they could enter the country and engage in employment without experiencing exploitation. The paper underlines the interplay between relevant legislation, government officials, employers, and migrants (work permit holders) that determine the ‘employer-sensitive’ or ‘gender-sensitive’ approach of the Irish MLF. The selected clauses empower government officials and employers to interpret them through their lenses, utilize migrant human resources as per their preferences, and convince them to accept conditional employment. The purpose is to reap the maximum benefits of their presence and encourage them towards ‘return-migration’ or ‘further-emigration’, once their services are no longer required. We draw inferences based on multiple data sources, e.g., visa applicant data from the Department of Justice (DoJ), in-depth interviews with migration experts and migrants (work permit holders), and relevant legislation.

1. IntroductionMost of the identified enzymes are proteins that are commonly introduced as catalysts of chemical reactions in biological environments (i.e., biocatalysts). The key feature of these biocatalysts is their high catalytic efficiency and substrate specificity which make them suitable for playing a specific role in biochemistry. Among different types of enzymes, peroxidase enzymes, especially horseradish peroxidase (HRP), are attractive enzymes from both industrial and clinical points of view. In the real world, the practical application of peroxidase enzyme in industrial reactions as the biocatalyst is an interesting field. Up to now, several researches on these enzymes have been carried out to provide useful information about the enzyme structure, and its functional groups, reaction pathways, and active sites [1-15]. Regarding the peroxidase enzymes, the enzyme-specific substrate is hydrogen peroxide (HP) while their function is catalyzing the oxidation of a hydrogen-donating substrate (for example, benzidine). More precisely, hydrogen peroxide is the initiator of the peroxidase-mediated reactions [16]. Oxidation of a wide range of organic compounds (substrates) including aromatic amines, phenols, and their mixtures can be initiated in the presence of hydrogen peroxide or other hydroperoxides and HRP as enzymes. Many chromogenic substrates have been defined as secondary substrates of horseradish peroxidase due to its low selectivity to electron-donating compounds. These chromogenic substrates are called chromogenic electron donors because these compounds show a distinct color change when oxidized by hydrogen peroxide in the presence of the peroxidase enzyme. It is noteworthy that peroxidase and other natural enzymes show some of the following serious disadvantages including: (1) They are sensitive to environmental changes such as pH and temperature changes and are easily denatured. (2) They are digested by protease enzymes. (3) Their preparation and purification are complicated and expensive [16-20]. Fixing these disadvantages is possible through the development of some stable artificial enzymes with high catalytic ability. In this regard, nanotechnology has opened the doors for the development of new enzyme-mimetic materials [21]. In fact, the fast development of nanoscience and material chemistry has increased interest in researching new and innovative synthesis methods to produce new nanomaterials with unique high biocompatibility [22], unique optical properties [23-25], and catalytic activity [26, 27]. In 2007, it was explored that Fe3O4 magnetic nanoparticles (NPs) exhibited significant peroxidase-like activity [28]. This research opened the door for a new branch of nanochemistry called “nanozyme chemistry”. Nanozyme chemistry is -consists of design, synthesis, modification, biochemical characterization, structural characterization, and application of nanoscale artificial enzymes as well as evaluation of the mechanism of nanozyme-based systems [3-21]. Among different areas of nanozyme chemistry, the main researches of nanozyme chemistry are regarding sensing and detection aims, for instance, during the last years, a wide variety of nanozyme-based colorimetric sensors have been developed for the detection and quantification of a variety of analytes for instance, tryptophan [29], glutathione (GSH) [30], dopamine [31], tetracycline [32], metal cations [33], glucose [34], H2O2 [35], explosives [36], and cysteine [37] as well as after first report of COVID-19 in 2019 [38, 39], the nanozyme-based sensing methods for COVID-19 detection were also reported [40]. Although the nanozyme field is focused on sensing and detection, recently, Mu et al. utilized heme-based nanozymes as redox materials for Li-O2batteries [41]. This investigation can open a new door in nanozyme chemistry regarding nanozyme application in the energy storage field. In this study, MnO2 nanoparticles with enzyme-like properties were synthesized and then their Li-electroactivity was evaluated. The as-prepared materials showed high Li-electroactivity which makes these nanozymes for applying as cathode materials for Li-ion batteries.

In recent years, the increase of data availability through citizen science campaigns has raised questions on the quality of this data. Species distribution models can be severely impacted by non-random spatial distributions of records. Multiple methods exist to correct for spatial bias and most of them imply that the sampling is uneven in space and determined by the observers’ choices of where to search for observations. One common correction method is to include a covariate in the model as a proxy for sampling bias and correcting for this bias by setting this covariate equal to a common value upon prediction. However, this approach implies that each observer behaves in the same manner, which in practice may not be the case. Here, we differentiate two common observer behaviours: exploring and following. Under this paradigm, explorers seek to observe species in new places far away from other observations and away from common routes of transit. By contrast, followers search near already observed species locations and remain closer to common routes of transit. In this paper, we investiage whether the current approaches to correcting for observer bias hold under varying observer behaviours, or whether a data-driven approach based on modelled observer behaviour may lead to better predictions. To do so, we developed a new software platform, obsimulator, to simulate patterns of points driven by observer behaviour. We established two correction methods based on a bias incorporation approach using k-nearest neighbours and density calculation. Broadly, we found that the method of including a bias covariate and setting it to a common value for prediction yields the best results. We also found that the knn-based correction outperformed the density-based correction. Additionally, we provide guidance for setting model parameters based on the ratio of explorers versus followers in the observers’ cohort.

This study is a systematic literature review aimed to identify the key variables on children’s Emotional Intelligence (EI). To the end, a meta-analysis is conducted, and the results are as follows: First, the variables were moderately correlated with EI, suggesting children’s developing EI is influenced by the variables. Second, parental mental comments and school readiness had the largest effects on the EI of children. This suggests parental emotional expression plays an important role in children’s development of EI as well as the importance of EI in terms of successful initial social adaptation. On the other hand, teachers’ self-efficacy had the largest effects on the EI of children which emphasizes the crucial role educational environments play in the development of children’s EI. The results of this study imply the need for multifaceted interpretations of children’s EI and emphasizes the importance of parents and teachers in the environments to develop children’s EI.

Long-term data are crucial for understanding ecological responses to climate and land use change; they are also vital evidence for informing management. As a migratory fish, Atlantic salmon are sentinels of both global and local environmental change. This paper reviews the main insights from six decades of research in an upland Scottish stream (Girnock Burn) inhabited by a spring Atlantic salmon population dominated by multi-sea-winter fish. Research began in the 1960s providing a census of returning adults, juvenile emigrants and in-stream production of Atlantic salmon. Early research pioneered new monitoring techniques providing new insights into salmon ecology and population dynamics. These studies underlined the need for interdisciplinary approaches for understanding salmon interactions with physical, chemical and biological components of in-stream habitats at different life-stages. This highlighted variations in catchment-scale hydroclimate, hydrology, geomorphology and hydrochemistry as essential to understanding freshwater habitats in the wider landscape context. Evolution of research has resulted in a remarkable catalogue of novel findings underlining the value of long-term data that increases with time as modelling tools advance to leverage more insights from “big data”. Data are available on fish numbers, sizes and ages across multiple life stages, extending over many decades and covering a wide range of stock levels. Combined with an unusually detailed characterisation of the environment, these data have enabled a unique process-based understanding of the controls and bottlenecks on salmon population dynamics across the entire lifecycle and the consequences of declining marine survival and ova deposition. Such powerful datasets, methodological enhancements and the resulting process understanding have informed and supported the development of fish population assessment tools which have been applied to aid management of threatened salmon stocks at large-catchment, regional and national scales. Many pioneering monitoring and modelling approaches developed have been applied internationally. This history shows the importance of integrating curiosity-driven science with monitoring for informing policy development and assessing efficacy of management options. It also demonstrates the need of continue to resource long-term sites which act as a focus for inter-disciplinary research and innovation, and where the overall value of the research greatly exceeds the costs of individual component parts.