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BACKGROUND: Suicide is the leading cause of death among Australians. One commonly cited explanation is the impact of social media, in particular, the ways in which young people use social media to communicate about their own experiences and their exposure to suicide-related content posted by others. Guidelines designed to assist mainstream media to safely report about suicide are widespread. Until recently, no guidelines existed that targeted social media or young people. In response, we developed the #chatsafe guidelines and a supporting social media campaign, which together make up the #chatsafe intervention. The intervention was tested in a pilot study with positive results. However, the study was limited by the lack of a control group. OBJECTIVE: The aim of this study is to assess the impact of the #chatsafe social media intervention on young people's safety and confidence when communicating on the web about suicide. METHODS: The study employs a pragmatic, parallel, superiority randomized controlled design. It will be conducted in accordance with the Consolidated Standards of Reporting Trials statement over 18 months. Participants will be 400 young people aged 16-25 years (200 per arm). Participants will be recruited via social media advertising and assessed at 3 time points: time 1-baseline; time 2-8-week postintervention commencement; and time 3-4-week postintervention. They will be asked to complete a weekly survey to monitor safety and evaluate each piece of social media content. The intervention comprises an 8-week social media campaign including social media posts shared on public Instagram profiles. The intervention group will receive the #chatsafe suicide prevention content and the control group will receive sexual health content. Both groups will receive 24 pieces of content delivered to their mobile phones via text message. The primary outcome is safety when communicating on the web about suicide, as measured via the purpose-designed #chatsafe online s

Classification systems are often deployed in resource-constrained settings where labels must be assigned to inputs on a budget of time, memory, etc. Budgeted, sequential classifiers (BSCs) address these scenarios by processing inputs through a sequence of partial feature acquisition and evaluation steps with early-exit options. This allows for an efficient evaluation of inputs that prevents unneeded feature acquisition. To approximate an intractable combinatorial problem, current approaches to budgeted classification rely on well-behaved loss functions that account for two primary objectives (processing cost and error). These approaches offer improved efficiency over traditional classifiers but are limited by analytic constraints in formulation and do not manage additional performance objectives. Notably, such methods do not explicitly account for an important aspect of real-time detection systems -- the fraction of "accepted" predictions satisfying a confidence criterion imposed by a risk-averse monitor. We propose a problem-specific genetic algorithm to build budgeted, sequential classifiers with confidence-based reject options. Three objectives -- accuracy, processing time/cost, and coverage -- are considered. The algorithm emphasizes Pareto efficiency while accounting for a notion of aggregate performance via a unique scalarization. Experiments show our method can quickly find globally Pareto optimal solutions in very large search spaces and is competitive with existing approaches while offering advantages for selective, budgeted deployment scenarios., Comment: IEEE WCCI 2022. arXiv admin note: substantial text overlap with arXiv:2110.13067

Background: Ensuring young people experience good sexual health is a key public health concern, yet some vulnerable groups of young people remain at higher risk of poor sexual health. These individuals require additional support to achieve good sexual health but the best way to provide this remains needs to be better understood. Methods: We searched for randomised controlled trials of behavioural and psychosocial interventions aimed at promoting sexual health in high-risk young populations. Outcomes of interest were indicators of sexual health (e.g., condom use, attitudes to contraception, knowledge of risk). Participants were under 25 years old and in one of the following high-risk groups: alcohol and other drug use; ethnic minority; homeless; justice-involved; LGBTQI+; mental ill-health; or out-of-home care. Results: Twenty-eight papers from 26 trials met our inclusion criteria, with all but one conducted in North America. Condom use was the most frequently reported outcome measure along with knowledge and attitudes towards sexual health but considerable differences in measures used made comparisons across studies difficult. Change in knowledge and attitudes did not consistently result in long-term change in behaviours. Conclusions: There remains a dearth of research undertaken outside of North America across all high-risk groups of young people. Future interventions should address sexual health more broadly than just the absence of negative biological outcomes, with LGBTQI+, homeless and mental ill-health populations targeted for such work. An international consensus on outcome measures would support the research field going forward, making future meta-analyses possible.

Classifiers are often utilized in time-constrained settings where labels must be assigned to inputs quickly. To address these scenarios, budgeted multi-stage classifiers (MSC) process inputs through a sequence of partial feature acquisition and evaluation steps with early-exit options until a confident prediction can be made. This allows for fast evaluation that can prevent expensive, unnecessary feature acquisition in time-critical instances. However, performance of MSCs is highly sensitive to several design aspects -- making optimization of these systems an important but difficult problem. To approximate an initially intractable combinatorial problem, current approaches to MSC configuration rely on well-behaved surrogate loss functions accounting for two primary objectives (processing cost, error). These approaches have proven useful in many scenarios but are limited by analytic constraints (convexity, smoothness, etc.) and do not manage additional performance objectives. Notably, such methods do not explicitly account for an important aspect of real-time detection systems -- the ratio of "accepted" predictions satisfying some confidence criterion imposed by a risk-averse monitor. This paper proposes a problem-specific genetic algorithm, EMSCO, that incorporates a terminal reject option for indecisive predictions and treats MSC design as an evolutionary optimization problem with distinct objectives (accuracy, cost, coverage). The algorithm's design emphasizes Pareto efficiency while respecting a notion of aggregated performance via a unique scalarization. Experiments are conducted to demonstrate EMSCO's ability to find global optima in a variety of Theta(k^n) solution spaces, and multiple experiments show EMSCO is competitive with alternative budgeted approaches., Comment: Minor revisions and additional comparisons

Dopaminergic signaling within the primary motor cortex (M1) is necessary for successful motor skill learning. Dopaminergic neurons projecting to M1 are located in the ventral tegmental area (VTA, nucleus A10) of the midbrain. It is unknown which behavioral correlates are encoded by these neurons. The objective here is to investigate whether VTA-M1 fibers are collaterals of projections to prefrontal cortex (PFC) or nucleus accumbens (NAc) or if they form a distinct pathway. In rats, multiple-site retrograde fluorescent tracers were injected into M1, PFC and the core region of the NAc and VTA sections investigated for concomitant labeling of different tracers. Dopaminergic neurons projecting to M1, PFC and NAc were found in nucleus A10 and to a lesser degree in the medial nucleus A9. Neurons show high target specificity, minimal collateral branching to other than their target area and hardly cross the midline. Whereas PFC- and NAc-projecting neurons are indistinguishably intermingled within the ventral portion of dopaminergic nuclei in middle and caudal midbrain, M1-projecting neurons are only located within the dorsal part of the rostral midbrain. Within M1, the forelimb representation receives sevenfold more dopaminergic projections than the hindlimb representation. This strong rostro-caudal gradient as well as the topographical preference to dorsal structures suggest that projections to M1 emerged late in the development of the dopaminergic systems in and form a functionally distinct system.

The digitization of this collection was funded by a gift from EBSCO Industries.

The digitization of this collection was funded by a gift from EBSCO Industries.

The digitization of this collection was funded by a gift from EBSCO Industries.

The digitization of this collection was funded by a gift from EBSCO Industries.

© 2020 The Author(s). We present an overview of the main techniques for production and processing of graphene and related materials (GRMs), as well as the key characterization procedures. We adopt a 'hands-on' approach, providing practical details and procedures as derived from literature as well as from the authors' experience, in order to enable the reader to reproduce the results. Section I is devoted to 'bottom up' approaches, whereby individual constituents are pieced together into more complex structures. We consider graphene nanoribbons (GNRs) produced either by solution processing or by on-surface synthesis in ultra high vacuum (UHV), as well carbon nanomembranes (CNM). Production of a variety of GNRs with tailored band gaps and edge shapes is now possible. CNMs can be tuned in terms of porosity, crystallinity and electronic behaviour. Section II covers 'top down' techniques. These rely on breaking down of a layered precursor, in the graphene case usually natural crystals like graphite or artificially synthesized materials, such as highly oriented pyrolythic graphite, monolayers or few layers (FL) flakes. The main focus of this section is on various exfoliation techniques in a liquid media, either intercalation or liquid phase exfoliation (LPE). The choice of precursor, exfoliation method, medium as well as the control of parameters such as time or temperature are crucial. A definite choice of parameters and conditions yields a particular material with specific properties that makes it more suitable for a targeted application. We cover protocols for the graphitic precursors to graphene oxide (GO). This is an important material for a range of applications in biomedicine, energy storage, nanocomposites, etc. Hummers' and modified Hummers' methods are used to make GO that subsequently can be reduced to obtain reduced graphene oxide (RGO) with a variety of strategies. GO flakes are also employed to prepare three-dimensional (3d) low density structures, such as s