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Introduction: Worldwide coastal fish resources face severe threats from fisheries overexploitation. However, the evaluation of abundance trends in most coastal fisheries is constrained by limited data. This study took blackmouth croaker (Atrobucca nibe), a stock depleted by coastal trawl fishery in southwestern Taiwan, as an example to showcase the development of a relative abundance index from data-limited fishery (only landing data were available). Methods: This study employed unique data sourcing from voyage data recorders (VDRs) to estimate fishing effort (in combination with landing data to estimate the catch per unit effort, CPUE) that demonstrated the potential application in global data-limited fisheries and assessed alternative approaches for predictors of fishery-targeting practices to condition effort for producing more accurate metrics of relative abundance. The nominal CPUE was standardized using three statistical models: generalized linear model, generalized additive model (GAM), and vector-autoregressive spatiotemporal models (VASTs) with two treatments of each of the four effects: environmental (sea temperature, salinity, density of mixing layer, seafloor temperature, and chlorophyll), vessel, spatial, and targeting effects. A total of 15 models were designed and compared for these effects, and their explanatory power (EP) was evaluated using cross-validation R2 and other metrics. Results and discussion: Results indicated that the targeting effect exerted the most significant influence on standardization and was suggested to be addressed through the principal component analysis (PCA) approach. Both vessel and spatial effects demonstrated considerable influence, whereas the environmental effect exhibited a limited impact, possibly due to the small fishing area in this study. Regarding models' EP, given the nonlinear nature of the PCA algorithm and environmental data, the study highlighted the superiority of the GAM over linear-based models. However, incorporating nonlinear features in VAST (M15) makes it the most effective model in terms of predictive power in this study. Concerning the stock status, despite variations in relative CPUE trends among major models, a general declining trend since 2015 signals the potential decline of the blackmouth stock and urges fishery managers to consider further design of management measures. [ABSTRACT FROM AUTHOR]

In the face of biodiversity loss worldwide, it is paramount to quantify species' extinction risk to guide conservation efforts. The International Union for the Conservation of Nature (IUCN)'s Red List is considered the global standard for evaluating extinction risks. IUCN criteria also inform national extinction risk assessments. Bayesian models, including the state‐of‐the‐art JARA ('Just Another Red List Assessment') tool, deliver probabilistic statements about species falling into extinction risk categories, thereby enabling characterisation and communication of uncertainty in extinction risk assessments.We coupled the state‐of‐the‐art VAST ('Vector Autoregressive Spatio‐Temporal') modelling tool and JARA, for better informed Red List assessments of marine fishes. In this framework, VAST is fitted to scientific survey catch rate data to provide indices to JARA whose uncertainty is propagated to JARA outcomes suggesting extinction risk categories (under the population reduction criterion). In addition, VAST delivers a valuable habitat assessment to better understand what may be driving extinction risk in the study region. Here, we demonstrate the coupled VAST‐JARA modelling framework by applying it to five contrasting North Sea species, with or without a quantitative stock assessment and with different conservation statuses according to the latest global Red List assessments.The North Sea application coupled with previous assessments and studies suggest that, among the three elasmobranchs, starry ray is in most need of urgent research (and conservation actions where appropriate), followed by spurdog, while lesser‐spotted dogfish is increasing in biomass. Moreover, both the VAST‐JARA modelling framework and previous research indicate that, while European plaice is not of conservation concern, cod has likely met the IUCN criteria for being listed as Endangered recently.Synthesis and applications. The predictions of the VAST‐JARA modelling framework for North Sea species, including JARA output and VAST habitat assessment, constitute valuable supporting information to make interpretations based on Red List guidelines, which will help decision‐makers in their next North Sea Red List assessment. We foresee applications of the modelling framework to assist Red List assessments of numerous marine fishes worldwide. Our modelling framework has many potential advantageous uses, including informing resource management about climate change impacts on species' extinction risks. [ABSTRACT FROM AUTHOR]

Generating biomass-at-age indices for fisheries stock assessments with acoustic data collected by uncrewed surface vessels (USVs) has been hampered by the need to resolve acoustic backscatter with contemporaneous biological (e.g., age) composition data. To address this limitation, Pacific hake (Merluccius productus; “hake”) acoustic data were gathered from a USV survey (in 2019) and acoustic-trawl survey (ATS; 2019 and eight previous years), and biological data were gathered from fishery-dependent and non-target (i.e., not specifically targeting hake) fishery-independent sources (2019 and eight previous years). To overcome the lack of contemporaneous biological sampling in the USV survey, age class compositions were estimated from a generalized linear mixed spatio-temporal model (STM) fit to the fishery-dependent and non-target fishery-independent data. The validity of the STM age composition estimation procedure was assessed by comparing estimates to age compositions from the ATS in each year. Hake biomass-at-age was estimated from all combinations of acoustics (USV or ATS in 2019, ATS only in other years) and age composition information (STM or ATS in all years). Across the survey area, proportional age class compositions derived from the best STM differed from ATS observations by 0.09 on average in 2019 (median relative error (MRE): 19.45%) and 0.14 across all years (MRE: 79.03%). In data-rich areas (i.e., areas with regular fishery operations), proportional age class compositions from the STM differed from ATS observations by 0.03 on average in 2019 (MRE: 11.46%) and 0.09 across years (MRE: 54.96%). On average, total biomass estimates derived using STM age compositions differed from ATS age composition-based estimates by approximately 7% across the study period (~ 3% in 2019) given the same source of acoustic data. When biomass estimates from different sources of acoustic data (USV or ATS) were compared given the same source of age composition data, differences were nearly ten-fold greater (22% or 27%, depending on if ATS or STM age compositions were used). STMs fit to non-contemporaneous data may provide suitable information for assigning population structure to acoustic backscatter in data-rich areas, but advancements in acoustic data processing (e.g., automated echo classification) may be needed to generate viable USV-based estimates of biomass-at-age.

Connectomics is fundamental in propelling our understanding of the nervous system's organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous systemand developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from four different animals and five datasets, amounting to around 180 h of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of four pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics. [ABSTRACT FROM AUTHOR]

In recent years, zebrafish have become commonly used as a model for studying human traits and disorders. Their small size, high fecundity, and rapid development allow for more high-throughput experiments compared to other vertebrate models. Given that zebrafish share >70% gene homologs with humans and their genomes can be readily edited using highly efficient CRISPR methods, we are now able to rapidly generate mutations impacting practically any gene of interest. Unfortunately, our ability to phenotype mutant larvae has not kept pace. To address this challenge, we have developed a protocol that obtains multiple phenotypic measurements from individual zebrafish larvae in an automated and parallel fashion, including morphological features (i.e., body length, eye area, and head size) and movement/behavior. By assaying wild-type zebrafish in a variety of conditions, we determined optimal parameters that avoid significant developmental defects or physical damage; these include morphological imaging of larvae at two time points [3 days post fertilization (dpf) and 5 dpf] coupled with motion tracking of behavior at 5 dpf. As a proof-of-principle, we tested our approach on two novel CRISPR-generated mutant zebrafish lines carrying predicted null-alleles of syngap1b and slc7a5, orthologs to two human genes implicated in autism-spectrum disorder, intellectual disability, and epilepsy. Using our optimized high-throughput phenotyping protocol, we recapitulated previously published results from mouse and zebrafish models of these candidate genes. In summary, we describe a rapid parallel pipeline to characterize morphological and behavioral features of individual larvae in a robust and consistent fashion, thereby improving our ability to better identify genes important in human traits and disorders.

Attention Deficit-Hyperactivity Disorder (ADHD) was first identified in 1902 by a British pediatrician, Sir George Still, as an abnormal defect in children’s moral control that caused poor control of their behavior despite their average and/or above intellectual capacity. It was not until the late 20th century when the American Psychiatric Association formally recognized ADHD as a mental disorder, whose hallmarks are excessive amounts of inattention, hyperactivity, and impulsivity. Also known as the triad of impairments in ADHD, these symptoms are pervasive, impairing in multiple contexts, and otherwise age-inappropriate. Only recently, Hallowell and Ratey (2021) introduced the concept of Variable Attention Stimulus Trait (VAST) in their book ADHD 2.0 to describe the condition. They argued that VAST/ADHD is unrelated to intelligence and has nothing to do with the deficit of attention. VAST/ADHD describes about how each brain/mind is uniquely wired affecting the way one deals with stimulation and attention. In this paper, the authors have chosen to explore two of the traits on the VAST/ADHD spectrum - (i) attentional control/sustained attention, and (ii) emotional regulation/impulse control - to illustrate the condition of ADHD as a variability of attention rather than a deficit of attention. [ABSTRACT FROM AUTHOR]

Connectomics is fundamental in propelling our understanding of the nervous system's organization, unearthing cells and wiring diagrams reconstructed from volume electron microscopy (EM) datasets. Such reconstructions, on the one hand, have benefited from ever more precise automatic segmentation methods, which leverage sophisticated deep learning architectures and advanced machine learning algorithms. On the other hand, the field of neuroscience at large, and of image processing in particular, has manifested a need for user-friendly and open source tools which enable the community to carry out advanced analyses. In line with this second vein, here we propose mEMbrain, an interactive MATLAB-based software which wraps algorithms and functions that enable labeling and segmentation of electron microscopy datasets in a user-friendly user interface compatible with Linux and Windows. Through its integration as an API to the volume annotation and segmentation tool VAST, mEMbrain encompasses functions for ground truth generation, image preprocessing, training of deep neural networks, and on-the-fly predictions for proofreading and evaluation. The final goals of our tool are to expedite manual labeling efforts and to harness MATLAB users with an array of semi-automatic approaches for instance segmentation. We tested our tool on a variety of datasets that span different species at various scales, regions of the nervous system and developmental stages. To further expedite research in connectomics, we provide an EM resource of ground truth annotation from four different animals and five datasets, amounting to around 180 h of expert annotations, yielding more than 1.2 GB of annotated EM images. In addition, we provide a set of four pre-trained networks for said datasets. All tools are available from https://lichtman.rc.fas.harvard.edu/mEMbrain/. With our software, our hope is to provide a solution for lab-based neural reconstructions which does not require coding by the user, thus paving the way to affordable connectomics.

Aim: There has been a wide interest in the effect of biotic interactions on species' occurrences and abundances at large spatial scales, coupled with a vast development of the statistical methods to study them. Still, evidence for whether the effects of within‐trophic‐level biotic interactions (e.g. competition and heterospecific attraction) are discernible beyond local scales remains inconsistent. Here, we present a novel hypothesis‐testing framework based on joint dynamic species distribution models and functional trait similarity to dissect between environmental filtering and biotic interactions. Location: France and Finland. Taxon: Birds. Methods: We estimated species‐to‐species associations within a trophic level, independent of the main environmental variables (mean temperature and total precipitation) for common species at large spatial scale with joint dynamic species distribution (a multivariate spatiotemporal delta model) models. We created hypotheses based on species' functionality (morphological and/or diet dissimilarity) and habitat preferences about the sign and strength of the pairwise spatiotemporal associations to estimate the extent to which they result from biotic interactions (competition, heterospecific attraction) and/or environmental filtering. Results: Spatiotemporal associations were mostly positive (80%), followed by random (15%), and only 5% were negative. Where detected, negative spatiotemporal associations in different communities were due to a few species. The relationship between spatiotemporal association and functional dissimilarity among species was negative, which fulfils the predictions of both environmental filtering and heterospecific attraction. Main conclusions We showed that processes leading to species aggregation (mixture between environmental filtering and heterospecific attraction) seem to dominate assembly rules, and we did not find evidence for competition. Altogether, our hypothesis‐testing framework based on joint dynamic species distribution models and functional trait similarity is beneficial in ecological interpretation of species‐to‐species associations from data covering several decades and biogeographical regions. [ABSTRACT FROM AUTHOR]

Autophagosomes are crucial components of the cellular recycling machinery that form at endoplasmic reticulum (ER)-associated sites. As the autophagosome membrane is largely devoid of transmembrane proteins, autophagosome biogenesis is thought to be largely regulated by lipid transfer and lipid modifications, as well as membrane-associated proteins. While the membrane origin of autophagosomes and their lipid composition are still incompletely understood, previous studies have found the autophagosome membrane to be enriched in unsaturated fatty acids and have little cholesterol, suggesting that cholesterol removal is an integral step during autophagosome biogenesis. In our study, we demonstrate that short term cholesterol depletion leads to a rapid induction of autophagy and identify the ER-localized cholesterol transport protein GRAMD1C as a negative regulator of starvation-induced macroautophagy/autophagy. Abbreviations: ATG: autophagy related; ccRCC: clear cell renal cell carcinoma; ER: endoplasmic reticulum; GRAM: glucosyltransferases, RAB-like GTPase activators and myotubularins; GRAMD: GRAM domain containing; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MCBD: methyl-cyclodextrin; MTOR: mechanistic target of rapamycin kinase; VASt: VAD1 analog of StAR-related lipid transfer. [ABSTRACT FROM AUTHOR]

Modeling spatiotemporal variability of fish stocks is important for interpreting changes in magnitude and distribution over time. Biomass indices for four stocks with differences in life history, spatial extent, proportion of zero observations, biomass trajectory, and stock status were modeled using the Vector Autoregressive Spatio-Temporal (VAST) model. We iteratively tested model settings following a workflow developed to find the best model for each stock in the context of developing an absolute index of abundance from fisheries independent data. The best model was determined based on AIC, RMSE, cross-validation, and several metrics of deviation from design-based estimates if one is available for comparison. Biomass indices from the best VAST model had good agreement with design-based indices in three of the stocks. Improvements in model fit tended to asymptote at around 1000 knots for all stocks. The generalized gamma error distribution with a logit link was the best model for two of the stocks, and the gamma error distribution with Poisson link was the best model for the other two. Occasionally a model was selected with much larger estimated biomass compared to the design-based estimates, and metrics based on comparisons with design-based estimates helped resolve model selection in these instances. Simulation self-tests were performed from the best model and fitted with several estimation models, and the model selection tools comparing fitted models to design-based indices calculated from the simulated data were found to be robust in recovering the specifications of the original model. Additional visualizations for spatial residuals and clustering were used to aid interpretation of model fit and to highlight latent spatial patterns. These metrics may be useful in identifying important covariates. We added a depth covariate to the best model for each stock to demonstrate how future model building might proceed. [ABSTRACT FROM AUTHOR]

The fishing grounds of the Pacific saury began shifting eastward after 2013 and deviated further east in 2019 and 2020. Consequently, the migration pattern from the pre‐fishing distribution to fishing grounds may be changing. This study investigated inter‐annual variations in westward spawning migration parameters using a migration model. Case studies were conducted to estimate optimal values for the initiation date of spawning migration and migration speed during spawning migration. The estimated optimal initiation date of spawning migration from 2003 to 2018 was July 13 to August 8, with an average of July 31. However, in 2019 and 2020, the initiation date of spawning migration was August 22 and September 5, respectively, significantly later than that in 2003–2018 (p <.01). The estimated optimal swimming speed during spawning migration in 2019 and 2020 was not significantly different from that in 2003–2018 (p >.7). These results indicate that delays in the initiation of spawning migration occurred in 2019 and 2020, leading to an eastward shift of fishing grounds. The mean body weight of the age‐1 Pacific saury in the pre‐fishing season had a significant negative correlation (p <.01) with the initiation date of spawning migration. This result suggests that Pacific saury with low body weight continues to feed for growth instead of initiating spawning migration. However, body weight at initiation of spawning migration had a significant decreasing trend (p <.01), indicating that the Pacific saury had to start spawning migration despite low body weight in recent years. [ABSTRACT FROM AUTHOR]

Population sizes of many birds are declining alarmingly and methods for estimating fluctuations in species' abundances at a large spatial scale are needed. The possibility to derive indicators from the tendency of specific species to co‐occur with others has been overlooked. Here, we tested whether the abundance of resident titmice can act as a general ecological indicator of forest bird density in European forests. Titmice species are easily identifiable and have a wide distribution, which makes them potentially useful ecological indicators. Migratory birds often use information on the density of resident birds, such as titmice, as a cue for habitat selection. Thus, the density of residents may potentially affect community dynamics. We examined spatio‐temporal variation in titmouse abundance and total bird abundance, each measured as biomass, by using long‐term citizen science data on breeding forest birds in Finland and France. We analyzed the variation in observed forest bird density (excluding titmice) in relation to titmouse abundance. In Finland, forest bird density linearly increased with titmouse abundance. In France, forest bird density nonlinearly increased with titmouse abundance, the association weakening toward high titmouse abundance. We then analyzed whether the abundance (measured as biomass) of random species sets could predict forest bird density better than titmouse abundance. Random species sets outperformed titmice as an indicator of forest bird density only in 4.4% and 24.2% of the random draws, in Finland and France, respectively. Overall, the results suggest that titmice could act as an indicator of bird density in Northern European forest bird communities, encouraging the use of titmice observations by even less‐experienced observers in citizen science monitoring of general forest bird density. [ABSTRACT FROM AUTHOR]

Abstract Population sizes of many birds are declining alarmingly and methods for estimating fluctuations in species’ abundances at a large spatial scale are needed. The possibility to derive indicators from the tendency of specific species to co‐occur with others has been overlooked. Here, we tested whether the abundance of resident titmice can act as a general ecological indicator of forest bird density in European forests. Titmice species are easily identifiable and have a wide distribution, which makes them potentially useful ecological indicators. Migratory birds often use information on the density of resident birds, such as titmice, as a cue for habitat selection. Thus, the density of residents may potentially affect community dynamics. We examined spatio‐temporal variation in titmouse abundance and total bird abundance, each measured as biomass, by using long‐term citizen science data on breeding forest birds in Finland and France. We analyzed the variation in observed forest bird density (excluding titmice) in relation to titmouse abundance. In Finland, forest bird density linearly increased with titmouse abundance. In France, forest bird density nonlinearly increased with titmouse abundance, the association weakening toward high titmouse abundance. We then analyzed whether the abundance (measured as biomass) of random species sets could predict forest bird density better than titmouse abundance. Random species sets outperformed titmice as an indicator of forest bird density only in 4.4% and 24.2% of the random draws, in Finland and France, respectively. Overall, the results suggest that titmice could act as an indicator of bird density in Northern European forest bird communities, encouraging the use of titmice observations by even less‐experienced observers in citizen science monitoring of general forest bird density.

Allocating quotas among stakeholders requires an agreed‐upon formula. If the stock unit spans multiple management jurisdictions, the formula may require updated biomass estimates of the stock's spatial distribution with respect to those jurisdictions. Data for calculating stock biomass often come from fishery‐independent surveys. While stratified random sampling is a common design, strata boundaries may not always align with state or national jurisdictions, requiring post hoc stratification and imputation to calculate area‐specific biomass. The vector autoregressive spatiotemporal (VAST) model was explored as a tool for calculating fish biomass within subareas of a defined stock unit for three different stocks jointly managed by the United States and Canada on Georges Bank in the Northwest Atlantic Ocean. VAST estimated proportions of stock biomass in each nation's waters were compared with an existing allocation algorithm that utilises a loess smooth through the average design‐based swept area biomass from three fishery‐independent surveys. The ability of VAST to impute biomass when no tows occur in a subarea of a survey stratum was demonstrated, as well as the relatively smoother biomass trend compared with design‐based estimates, which may be desirable if the intent is to avoid large inter‐annual swings in allocated quota. [ABSTRACT FROM AUTHOR]

We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K's comprehensive coverage of the scientific literature in visualization not only reflects the progress of the field but also enables researchers to study the evolution of the state-of-the-art and to find relevant work based on graphical content. We describe the dataset and our semi-automatic collection process, which couples convolutional neural networks (CNN) with curation. Extracting figures and tables semi-automatically allows us to verify that no images are overlooked or extracted erroneously. To improve quality further, we engaged in a peer-search process for high-quality figures from early IEEE Visualization papers. With the resulting data, we also contribute VISImageNavigator (VIN, visimagenavigator.github.io), a web-based tool that facilitates searching and exploring VIS30K by author names, paper keywords, title and abstract, and years. [ABSTRACT FROM AUTHOR]

This study investigated the need for uniqueness, visual aesthetic sensitivity, and their correlation. To investigate these variables, we asked 71 participants to complete the German adaptation of the Need for Uniqueness scale (NfU-G) and the Visual Aesthetic Sensitivity Test (VAST)—including the VAST-Revised (VAST-R). The NfU-G measures the need to set oneself apart from others, whereas the VAST(-R) tests the ability to identify the objective aesthetic goodness of a figural composition. The findings of this study are significantly compliant with theoretical considerations: the higher a participant scores on the NfU-G scale, the lower the percentage of correctly identified drawings on the VAST(-R), with the VAST being a stronger predictor than the VAST-R. Thus, the results suggest that participants who strive for individuality exhibit lower visual aesthetic sensitivity since they tend to violate norms in order to assert their uniqueness. Limitations regarding this outcome are discussed. [ABSTRACT FROM AUTHOR]

In recent years, zebrafish have become commonly used as a model for studying human traits and disorders. Their small size, high fecundity, and rapid development allow for more high-throughput experiments compared to other vertebrate models. Given that zebrafish share >70% gene homologs with humans and their genomes can be readily edited using highly efficient CRISPR methods, we are now able to rapidly generate mutations impacting practically any gene of interest. Unfortunately, our ability to phenotype mutant larvae has not kept pace. To address this challenge, we have developed a protocol that obtains multiple phenotypic measurements from individual zebrafish larvae in an automated and parallel fashion, including morphological features (i.e., body length, eye area, and head size) and movement/behavior. By assaying wild-type zebrafish in a variety of conditions, we determined optimal parameters that avoid significant developmental defects or physical damage; these include morphological imaging of larvae at two time points [3 days post fertilization (dpf) and 5 dpf] coupled with motion tracking of behavior at 5 dpf. As a proof-of-principle, we tested our approach on two novel CRISPR-generated mutant zebrafish lines carrying predicted null-alleles of syngap1b and slc7a5, orthologs to two human genes implicated in autism-spectrum disorder, intellectual disability, and epilepsy. Using our optimized high-throughput phenotyping protocol, we recapitulated previously published results from mouse and zebrafish models of these candidate genes. In summary, we describe a rapid parallel pipeline to characterize morphological and behavioral features of individual larvae in a robust and consistent fashion, thereby improving our ability to better identify genes important in human traits and disorders.

The northern Bering Sea is transitioning from an Arctic to subarctic fish community as climate warms. Scientists and managers aim to understand how these changing conditions are influencing fish biomass and spatial distribution in this region, as both are used to inform stock assessments and fisheries management advice. Here, we use a spatio‐temporal model for walleye pollock (Gadus chalcogrammus) to provide two inputs to its stock assessment model: (a) an alternative model‐based biomass index and (b) alternative model‐based age compositions. Both inputs were derived from multiple fishery‐independent data that span different regions of space and time. We developed an assessment model that utilizes both the standard and model‐based inputs from multiple surveys despite inconsistencies in spatial and temporal coverage, and we found that using these data provide an improved spatial and temporal scope of total pollock biomass. Age composition information indicated that pollock density is increasing and moving farther north, particularly for older pollock. We found that including an index of cold pool extent could be used to extrapolate pollock densities in the northern Bering Sea in unsampled years. Stock assessment parameter estimates were similar for standard and model‐based input. This study demonstrates that spatio‐temporal model‐based estimates of a biomass index and age composition can facilitate rapid changes in stock assessment structure in response to climate‐driven shifts in spatial distribution. We conclude that assimilating data from regions neighboring standard survey areas, such as the Chukchi Sea and western Bering Sea, would improve understanding and management efforts as fish distributions change under a warming climate. [ABSTRACT FROM AUTHOR]

Multispecies models are widely used to evaluate management trade‐offs arising from species interactions. However, identifying climate impacts and sensitive habitats requires integrating spatial heterogeneity and environmental impacts into multispecies models at fine spatial scales. We therefore develop a spatio‐temporal model of intermediate complexity for ecosystem assessments (a "MICE‐in‐space"), which is fitted to survey sampling data and time series of fishing mortality using maximum‐likelihood techniques. The model is implemented in the VAST R package, and it can be configured to range from purely descriptive to including ratio‐dependent interactions among species. We demonstrate this model using data for four groundfishes in the Gulf of Alaska using data from 1982 to 2015. Model selection for this case‐study shows that models with species interactions are parsimonious, although a model specifying separate density dependence without interactions also has substantial support. The AIC‐selected model estimates a significant, negative impact of Alaska pollock (Gadus chalcogrammus, Gadidae) on productivity of other species and suggests that recent fishing mortality for Pacific cod (G. microcephalus, Gadidae) is above the biological reference point (BRP) resulting in 40% of unfished biomass; other models show similar trends but different scales due to different BRP estimates. A simulation experiment shows that fitting a model with fewer species at a coarse spatial resolution degrades estimation performance, but that interactions and biological reference points can still be estimated accurately. We conclude that MICE‐in‐space models can simultaneously estimate fishing impacts, species trade‐offs, biological reference points and habitat quality. They are therefore suitable to forecast short‐term climate impacts, optimize survey designs and designate protected habitats. [ABSTRACT FROM AUTHOR]

Background: Peripheral intravenous catheter (PIVC) sales per year exceed that of the number of people in the United States (US), 350 million. With only 37 million US hospital patient admissions per year, these data indicate an average usage of 10 PIVCs per patient admission, suggesting a very high failure, very low success rate, and excess cost associated with PIVC insertions. Patients often complain of multiple catheter insertion attempts, and published data reveal up to 53% of PIVCs fail before therapy ends. Methods: Hartford Hospital (Hartford, CT) conducted a prospective comparator single-center clinical superiority design study to determine the impact of bundled practices including device insertions using vascular access specialty team (VAST) intravenous trained nurses versus current practice. The study used a 5 step multimodal best practice intervention strategy designated as the PIV5Rights Bundle with an aim to determine if the intervention outcomes and dwell time improved over current PIVC practices. The study group applied a Lean health care standard work process with a Six Sigma design, define, measure, analyze, improve, control approach that included VAST PIVC dwell time, complications, and economic impact compared with current state general nursing practice. Results: Outcomes of the PIV5Rights Bundle in Group 2 (experimental) using a trained vascular access nursing team for insertion and management achieved a statistically significant result of 89% of catheters achieving end of therapy with a cost saving per bed of $3376 ($1405 versus $4781) per year as compared to standard practice (Group 1; control). Results of Group 1 reflected PIVC dwell time to end of treatment in only 15% of catheters. Prestudy catheter consumption analysis was 4.4 catheters per patient hospital admissions, reflecting waste within labor and supply costs for PIVC insertion and usage. Peripheral intravenous catheter retrospective audits for current practice demonstrated more than 50% catheters failed within the first 24 hours. This application of Lean methodology by Hartford Hospital with infusion therapy resulted in a projected $2.9 million annual savings of $3376 per bed per year for house-wide application. Conclusions: Implementation of the PIV5Rights™ Bundle with a dedicated VAST proved to be a successful model, both from a patient and financial perspective. The journey to nursing excellence included identification of core measures and best practice evidence for PIVC placements as a procedure that affects nearly every patient entering a hospital. By centralizing ownership of vascular access with the team for insertion, management, and securement, the PIV Five Rights is the right approach to achieve the right results in transformation of hospital infusion therapy practices. Bundled approaches have often been used for central catheter infection reduction. This is the first study the authors have identified focusing on 1 PIVC per patient visit as a result of an evidencebased bundle and VAST. [ABSTRACT FROM AUTHOR]

Highlights • Stock, ecosystem, habitat, and climate assessments use different methods and vocabulary. • Population density across space, time, and species is a "common currency". • I provide guidance for 15 major decisions when using Vector Autoregressive Spatio-Temporal (VAST) models. • Three case-studies illustrate decisions in different assessment types. • Economic and survey-optimization assessments are important future research. Abstract Fisheries scientists provide stock, ecosystem, habitat, and climate assessments to support interdisplinary fisheries management in the US and worldwide. These assessment activities have evolved different models, using different review standards, and are communicated using different vocabulary. Recent research shows that spatio-temporal models can estimate population density for multiple locations, times, and species, and that this is a "common currency" for addressing core goals in stock, ecosystem, habitat, and climate assessments. I therefore review the history and "design principles" for one spatio-temporal modelling package, the Vector Autoregressive Spatio-Temporal (VAST) package. I then provide guidance on fifteen major decisions that must be made by users of VAST, including: whether to use a univariate or multivariate model; when to include spatial and/or spatio-temporal variation; how many factors to use within a multivariate model; whether to include density or catchability covariates; and when to include a temporal correlation on model components. I finally demonstrate these decisions using three case studies. The first develops indices of abundance, distribution shift, and range expansion for arrowtooth flounder (Atheresthes stomias) in the Eastern Bering Sea, showing the range expansion for this species. The second involves "species ordination" of eight groundfishes in the Gulf of Alaska bottom trawl survey, which highlights the different spatial distribution of flathead sole (Hippoglossoides elassodon) relative to sablefish (Anoplopoma fimbria) and dover sole (Microstomus pacificus). The third involves a short-term forecast of the proportion of coastwide abundance for five groundfishes within three spatial strata in the US West Coast groundfish bottom trawl survey, and predicts large interannual variability (and high uncertainty) in the distribution of lingcod (Ophiodon elongatus). I conclude by recommending further research exploring the benefits and limitations of a "common currency" approach to stock, ecosystem, habitat, and climate assessments, and discuss extending this approach to optimal survey design and economic assessments. [ABSTRACT FROM AUTHOR]

Myelinating oligodendrocytes are essential for central nervous system (CNS) formation and function. Their disruption is implicated in numerous neurodevelopmental, neuropsychiatric and neurodegenerative disorders. However, recent studies have indicated that oligodendrocytes may be tractable for treatment of disease. In recent years, zebrafish have become well established for the study of myelinating oligodendrocyte biology and drug discovery in vivo. Here, by automating the delivery of zebrafish larvae to a spinning disk confocal microscope, we were able to automate high-resolution imaging of myelinating oligodendrocytes in vivo. From there, we developed an image analysis pipeline that facilitated a screen of compounds with epigenetic and post-translational targets for their effects on regulating myelinating oligodendrocyte number. This screen identified novel compounds that strongly promote myelinating oligodendrocyte formation in vivo. Our imaging platform and analysis pipeline is flexible and can be employed for high-resolution imaging-based screens of broad interest using zebrafish.

Aim: Lean methods are widely used in engineering for improving processes. These methods have also been begun to be used in the service sector. Value and waste are the most common parameters in the lean methodology. In this study, we focused on waste in laboratory with spaghetti diagrams to improve our processes before drawing the process flow map in order to create more ergonomic laboratory. Methods: This process improvement study was practiced between February and September in Izmir Aliaga State Hospital. We used kaizen chart, timer and brainstorming for Microsoft office in measurements. 13 main processes were measured and redesigned. 37 steps were investigated and discussed. This procedure was repeated three times. We compared the first and last results. Results: Our total walks were 283 meters at the beginning of the study. After the improvement this figures decreased to165 meters. We observed totally 41.5% saving in processes. Conclusion: These findings suggested that using principles of lean methodologies in hospital laboratory are useful tools to improve process. The spaghetti diagram seems to be the basic tool for beginning to draw the process map and become more ergonomic for the laboratory environment. [ABSTRACT FROM AUTHOR]

'Vast' is a word often applied to environmental terrain that is perceived to have large spatial extent. This judgment is made even at viewing distances where traditional metric depth cues are not useful. This paper explores the perceptual basis of vast experience, including reliability and visual precursors. Experiment 1 demonstrated strong agreement in ratings of the spatial extent of two-dimensional (2D) scene images by participants in two countries under very different viewing conditions. Image categories labeled 'vast' often exemplified scene attributes of ruggedness and openness (Oliva & Torralba, 2001). Experiment 2 quantitatively assessed whether these properties predict vastness. High vastness ratings were associated with highly open, or moderately open but rugged, scenes. Experiment 3 provided evidence, consistent with theory, that metric distance perception does not directly mediate the observed vastness ratings. The question remains as to how people perceive vast space when information about environmental scale is unavailable from metric depth cues or associated scene properties. We consider possible answers, including contribution from strong cues to relative depth. [ABSTRACT FROM AUTHOR]

Phase noise spectrum distributions of signal generators for next-generation VSAT satellite system based on DVB-RCS2 were analyzed in this paper. The forward link of VSAT system utilizes the APSK higher-order modulation methods based on the DVB-S2 ACM, the modulation methods of the return link utilizes the higher-order PSK and QAM based on the DVB-RCS2. In digital satellite system using the higher-order modulation techniques, the phase noise have an effect on transmission performance, the transmission performance is dominantly degraded by the phase noise of signal generators in the transmission system. The phase noise spectrum distribution of signal generators are analyzed by considering the ACM conditions that adopts the modulation techniques and data rates due to satellite transmission environment. The proper phase noise spectrum distribution for next-generation VSAT system based on DVB-RCS2 are proposed from the analyzed phase noise spectrum characteristics. [ABSTRACT FROM AUTHOR]

Background Several regulators of programmed cell death (PCD) in plants encode proteins with putative lipid-binding domains. Among them, VAD1 is a regulator of PCD propagation harboring a GRAM putative lipid-binding domain. However the function of VAD1 at the subcellular level is unknown and the domain architecture of VAD1 has not been analyzed in details. Results We analyzed sequence conservation across the plant kingdom in the VAD1 protein and identified an uncharacterized VASt (VAD1 Analog of StART) domain. Using profile hidden Markov models (profile HMMs) and phylogenetic analysis we found that this domain is conserved among eukaryotes and generally associates with various lipid-binding domains. Proteins containing both a GRAM and a VASt domain include notably the yeast Ysp2 cell death regulator and numerous uncharacterized proteins. Using structure-based phylogeny, we found that the VASt domain is structurally related to Bet v1-like domains. Conclusion We identified a novel protein domain ubiquitous in Eukaryotic genomes and belonging to the Bet v1-like superfamily. Our findings open perspectives for the functional analysis of VASt-containing proteins and the characterization of novel mechanisms regulating PCD. [ABSTRACT FROM AUTHOR]