Fast and efficient identification is critical for reducing the likelihood of weed establishment and for appropriately managing established weeds. Traditional identification tools require either knowledge of technical morphological terminology or time-consuming image matching by the user. In recent years, deep learning computer vision models have become mature enough to enable automatic identification. The major remaining bottlenecks are the availability of a sufficient number of high-quality, reliably identified training images and the user-friendly, mobile operationalization of the technology. Here, we present the first weed identification and reporting app and website for all of Australia. It includes an image classification model covering more than 400 species of weeds and some Australian native relatives, with a focus on emerging biosecurity threats and spreading weeds that can still be eradicated or contained. It links the user to additional information provided by state and territory governments, flags species that are locally reportable or notifiable, and allows the creation of observation records in a central database. State and local weed officers can create notification profiles to be alerted of relevant weed observations in their area. We discuss the background of the WeedScan project, the approach taken in design and software development, the photo library used for training the WeedScan image classifier, the model itself and its accuracy, and technical challenges and how these were overcome.

Using foresight methods such as scenarios, possible futures can be described and anticipated. Needs and requirements as well as product properties can be derived from that, which is necessary to plan successful products for future customers. Changes that occur in the future development can be identified with monitoring and the expected future can be adjusted. A consistent understanding of the use of monitoring for the product engineering process does not exist and is developed in this paper. Thereby, monitoring is considered in the context of validation and located in iPeM.

Limited analyses based on national samples have assessed whether early attention-deficit/hyperactivity disorder (ADHD) symptoms predict later internalizing and externalizing symptoms in youth and the influence of sex and pubertal timing on subsequent psychiatric symptoms. This study analyzed data (n = 2818) from the Environmental influences on Child Health Outcomes Program national cohort. Analyses used data from early childhood (mean age = 5.3 years) utilizing parent-reported ADHD symptoms to predict rates of internalizing and externalizing symptoms from late childhood/adolescence (mean age = 11.9 years). Within a subsample age at peak height velocity (APHV) acted as a proxy to assess pubertal timing from early childhood (mean age = 5.4 years) to adolescence (mean age = 12.3 years). Early-childhood ADHD symptoms predicted later psychiatric symptoms, including anxiety, depression, aggressive behavior, conduct problems, oppositional defiant disorder, and rule-breaking behavior. Earlier APHV was associated with increased Conduct Disorder symptoms from late childhood to adolescence for females only. A stronger relation between ADHD symptoms and later aggression was observed in females with earlier APHV, whereas this same pattern with aggression, conduct problems and depression was observed in males with later APHV. Clinicians should consider that both young girls and boys with elevated ADHD symptoms, particularly with off-set pubertal timing, may be at risk for later psychiatric symptoms.

The long-standing assumption that aboveground plant litter inputs have a substantial influence on soil organic carbon storage (SOC) and dynamics has been challenged by a new paradigm for SOC formation and persistence. We tested the importance of plant litter chemistry on SOC storage, distribution, composition, and age by comparing two highly contrasting ecosystems: an old-growth coast redwood (Sequoia sempervirens) forest, with highly aromatic litter, and an adjacent coastal prairie, with more easily decomposed litter. We hypothesized that if plant litter chemistry was the primary driver, redwood would store more and older SOC that was less microbially processed than prairie. Total soil carbon stocks to 110 cm depth were higher in prairie (35 kg C m−2) than redwood (28 kg C m−2). Radiocarbon values indicated shorter SOC residence times in redwood than prairie throughout the profile. Higher amounts of pyrogenic carbon and a higher degree of microbial processing of SOC appear to be instrumental for soil carbon storage and persistence in prairie, while differences in fine-root carbon inputs likely contribute to younger SOC in redwood. We conclude that at these sites fire residues, root inputs, and soil properties influence soil carbon dynamics to a greater degree than the properties of aboveground litter.

Humans operating in extreme environments often conduct their operations at the edges of the limits of human performance. Sometimes, they are required to push these limits to previously unattained levels. As a result, their margins for error in execution are much smaller than that found in the general public. These same small margins for error that impact execution may also impact risk, safety, health, and even survival. Thus, humans operating in extreme environments have a need for greater refinement in their preparation, training, fitness, and medical care. Precision medicine (PM) is uniquely suited to address the needs of those engaged in these extreme operations because of its depth of molecular analysis, derived precision countermeasures, and ability to match each individual (and his or her specific molecular phenotype) with any given operating context (environment). Herein, we present an overview of a systems approach to PM in extreme environments, which affords clinicians one method to contextualize the inputs, processes, and outputs that can form the basis of a formal practice. For the sake of brevity, this overview is focused on molecular dynamics, while providing only a brief introduction to the also important physiologic and behavioral phenotypes in PM. Moreover, rather than a full review, it highlights important concepts, while using only selected citations to illustrate those concepts. It further explores, by demonstration, the basic principles of using functionally characterized molecular networks to guide the practical application of PM in extreme environments. At its core, PM in extreme environments is about attention to incremental gains and losses in molecular network efficiency that can scale to produce notable changes in health and performance. The aim of this overview is to provide a conceptual overview of one approach to PM in extreme environments, coupled with a selected suite of practical considerations for molecular profiling and countermeasures.

Although associations among borderline personality disorder (BPD), social rejection, and frontal EEG alpha asymmetry scores (FAA, a neural correlate of emotion regulation and approach-withdrawal motivations) have been explored in different studies, relatively little work has examined these relations during adolescence in the same study. We examined whether FAA moderated the relation between BPD features and rejection sensitivity following a validated social exclusion paradigm, Cyberball. A mixed, clinical-community sample of 64 adolescents (females = 62.5%; Mage = 14.45 years; SD = 1.6; range = 11-17 years) completed psychodiagnostic interviews and a self-report measure of BPD (Time 1). Approximately two weeks later (Time 2), participants completed a resting EEG recording followed by Cyberball. FAA moderated the relation between BPD features and overall feelings of rejection following Cyberball: individuals with greater relative left FAA had the highest and lowest feelings of social rejection depending on whether they had high and low BPD feature scores, respectively. Results remained after controlling for age, sex, gender, depression, and BPD diagnosis. These results suggest that FAA may moderate the relation between BPD features and social rejection, and that left frontal brain activity at rest may be differentially associated with those feelings in BPD. Findings are discussed in terms of the link between left frontal brain activity in the regulation and dysregulation of social approach behaviors, characteristic of BPD.

It is well known that John Stuart Mill (JSM) repeatedly acknowledges Harriet Taylor Mill's (HTM) substantial contribution to On Liberty. After her death, however, he decides to publish the book under his name only. Are we justified in continuing this practice, initiated by JSM, of refusing unequivocal co-authorship status to HTM? Drawing on stylometric analyses, we make a preliminary case that JSM did not write On Liberty all by himself and that HTM had a hand in formulating it. Drawing on plausible standards for authorship ascription, we further point out that authorship status requires, in addition to a substantial contribution, the approval by all contributors. We discuss potential reasons to assume that HTM did not approve the published version of On Liberty and would have objected to including her name on the title page.

Worldwide, cardiovascular disease (CVD) is the number 1 cause of mortality and is associated with insulin resistance (IR). Emerging biomarkers such as FGF21 and adiponectin are associated with cardiometabolic risk. Low carbohydrate, high fat (LCHF) diets have been reported to reduce cardiometabolic risk markers; however, few studies have compared a LCHF diet vs. a high carbohydrate (HC), lower fat diet under ad libitum conditions on adiponectin and FGF21. The purpose of this study was to investigate the effects of an ad libitum LCHF vs. HC diet on IR, FGF21 and adiponectin in 16 healthy adults. Ethical approval: Liverpool John Moores University Research Ethics Committee (16/ELS/029); registered with ClinicalTrials.gov (Ref. NCT03257085). Participants were randomly assigned to a HC diet (n = 8, the UK Eatwell guidelines; ≥ 50% of energy from carbohydrates) or a LCHF diet (n = 8, consume < 50 g/day of carbohydrates). All provided plasma samples at 0, 4 and 8 weeks. FGF21 (R&D Systems) was analysed via ELISA and adiponectin, insulin and glucose were analysed via immunoassay technology (Randox Evidence Investigator™ Metabolic Syndrome Arrays I & II). Mann Whitney, Friedmans, Wilcoxon tests and 2×3 ANOVA (IBM SPSS 25®) were undertaken to investigate significant differences between and within groups. The homeostatic model assessment (HOMA) was used to calculate IR. FGF21 significantly (P = 0.04) decreased (Mdn, IQR:148.16, 78.51–282.02 to 99.4, 39.87–132.29 pg/ml) after 4 weeks and significantly (P = 0.02) increased (Mdn, IQR:167.38, 80.82–232.89 pg/ml) by 8 weeks vs. baseline with LCHF. No significant differences (P > 0.05) were observed between groups. Adiponectin was significantly (P = 0.03) different at week 4 only between groups. Adiponectin increased after 4 weeks (Mdn, IQR:13.44, 9.12–25.47 to 16.64, 11.96–21.51 ng/ml) but was only significantly (P = 0.03) different by 8 weeks vs. baseline in the HC group (Mdn, IQR:16, 10.8–27.43 ng/ml). Adiponectin remained unchanged (P = 0.96) in the LCHF group. HOMA significantly decreased with both diets after 8 weeks only (mean ± SD, LCHF: 2.9 ± 1.3 to 1.8 ± 0.8, HC: 2.5 ± 0.6 to 1.9 ± 0.6, P = 0.008) but was not significantly (P = 0.60) different between groups. These preliminary data reveal that while both diets improved insulin sensitivity, they may do so by different mechanisms. Future studies are warranted to investigate further, how a LCHF vs. HC diet affects FGF21 and adiponectin, and the subsequent regulation of IR. Furthermore, studies that extend these findings by determining the impact of LCHF vs. HC on peripheral metabolism to determine potential nutrition-mediated mechanisms of metabolic adaptation are warranted.

Apolipoproteins (apo) regulate lipoprotein characteristics and lipid metabolism. ApoC-III is a regulator of triglyceride-rich lipoprotein (TRL) metabolism and apolipoproteins are important biomarkers for cardiovascular disease (CVD) risk prediction. A low carbohydrate high fat (LCHF) diet improves cardiometabolic risk, especially via reduction of TRL. However, few studies have compared a LCHF vs. a high carbohydrate (HC), lower fat diet under ad libitum conditions on apoC-III levels. The objectives of this investigation were to measure the effect of a LCHF vs. a HC diet on apoC-III, apoA1, apoB and apoB/apoA1 in 16 healthy Caucasian adults aged 19–64. Ethical approval: Liverpool John Moores University Research Ethics Committee (16/ELS/029); registered with ClinicalTrials.gov (Ref. NCT03257085). Participants randomly assigned to a HC diet (UK Eatwell guidelines; ≥ 50% of energy from carbohydrates) (n = 8), or a LCHF diet (consume < 50 g/day of carbohydrates) (n = 8) provided plasma samples at 0, 4 and 8 weeks. ApoA1 and apoB were analysed by an automated chemistry analyser (Daytona, Randox Laboratories Ltd, UK). ApoC-III was analysed via ELISA (Thermo Fisher Ltd, USA). Factorial 2×3 ANOVA and ANCOVA (IBM SPSS 25®) were undertaken to investigate significant differences and to control for variables influenced by baseline measures and visceral adipose tissue (VAT). Results show 0, 4, and 8 weeks respectively: ApoC-III (LCHF: 19.12 ± 9.14, 16.05 ± 7.95, 15.11 ± 3.17 mg/dl; HC: 22.13 ± 8.38, 28.22 ± 13.85, 22.22 ± 7.7 mg/dl) showed no significant (P = 0.319) change. No significant (P = 0.23) change was also observed in ApoB (LCHF: 107.25 ± 20.35, 111.38 ± 24.81, 111.43 ± 19.93 mg/dl; HC: 94.38 ± 20.79, 105.00 ± 20.13, 99.00 ± 29.09 mg/dl). Similarly apoA1 (LCHF: 158.71 ± 14.27, 166.50 ± 23.09, 173.00 ± 29.42 mg/dl; HC: 164.71 ± 30.25, 172.50 ± 29.44, 174.00 ± 32.83 mg/dl) showed no significant change (P = 0.76). This resulted in a relatively unchanged apoB/A1 throughout the study in both diets (P = 0.30). No significant (P > 0.05) differences were found after 4 weeks or between groups also. ANCOVA revealed a trend (P = 0.06) in apoC-III for a difference between groups (LCHF: Δ-6.6 mg/dl vs. HC: Δ1.2 mg/dl) after 8 weeks but no significant (P > 0.05) changes in other apolipoproteins were detected. These preliminary data reveal that a LCHF diet does not improve the apolipoprotein profile; however, when accounting for other metabolic risk factors (i.e. VAT) there was a trend towards lowering apoC-III levels (P = 0.06). Modulation of apoC-III may lead to improved lipid metabolism, but higher-powered studies are warranted before any improvement on CVD risk can be inferred.