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Teaching policy capacity: A collaborative and constructivist workshop
No full textThis article presents an approach for teaching policy capacity to civil servants based on a workshop that took place in 2018 under the auspices of the Government of Prince Edward Island’s Policy Capacity Learning Series. It argues that workshops which introduce civil servants to the concept of policy capacity can enhance skills-based training and knowledge of the policy environment. Through a learner-focused, collaborative and constructivist pedagogy, the workshop involved a group activity where civil servants constructed a visual diagram of their policy environment by categorizing actors, skills, resources, institutions and concepts according to a policy capacity framework. This article discusses the workshop’s planning and delivery requirements which can be used, adapted and improved by practitioners in other jurisdictions. It also provides considerations for future training and education in public administration
A review of machine learning techniques in agroclimatic studies
No full textThe interplay of machine learning (ML) and deep learning (DL) within the agroclimatic domain is pivotal for addressing the multifaceted challenges posed by climate change on agriculture. This paper embarks on a systematic review to dissect the current utilization of ML and DL in agricultural research, with a pronounced emphasis on agroclimatic impacts and adaptation strategies. Our investigation reveals a dominant reliance on conventional ML models and uncovers a critical gap in the documentation of methodologies. This constrains the replicability, scalability, and adaptability of these technologies in agroclimatic research. In response to these challenges, we advocate for a strategic pivot toward Automated Machine Learning (AutoML) frameworks. AutoML not only simplifies and standardizes the model development process but also democratizes ML expertise, thereby catalyzing the advancement in agroclimatic research. The incorporation of AutoML stands to significantly enhance research scalability, adaptability, and overall performance, ushering in a new era of innovation in agricultural practices tailored to mitigate and adapt to climate change. This paper underscores the untapped potential of AutoML in revolutionizing agroclimatic research, propelling forward the development of sustainable and efficient agricultural solutions that are responsive to the evolving climate dynamics
Real-time peak flow prediction based on signal matching
No full textReal-time peak flow prediction under heavy precipitation is critically important for flood emergency evacuation planning and management. In the case of emergency evacuation, every second matters as a slightly longer lead time could save more lives and reduce the associated social, economic, and health impacts. Here, we present a model (named SIGMA) based on the principle of signal matching to facilitate real-time peak flow prediction at sub-hourly scales (e.g., minutes to seconds). The SIGMA model divides the target watershed into small zones and the heavy precipitation falling into each zone is collected into a small water tank. As the water tank moves downstream and arrives in the watershed outlet, it will discharge the collected precipitation and generate a small single-pulse streamflow signal. By combining all small signals coming from all zones within the watershed, we will be able to generate a synthesized peak flow signal. The proposed model is applied to simulate the peak flow events observed in a real-world watershed to verify its effectiveness in real-time flood prediction. The results suggest that the presented model can reasonably predict three key aspects of a peak flow event, including the peak flow rate, the arrival time of peak flow, and the duration of the peak flow event. The proposed model is demonstrated to be effective in real-time flood prediction and can be used to support flood emergency evacuation planning and management
Deep reinforcement learning for smart restarts in exploration-only exploitation-only metaheuristic hybrids
No full textMetaheuristic algorithms excel in addressing challenging optimization problems but often face the issue of premature convergence, limiting their potential during extended optimization periods. This research aims to overcome this limitation by integrating Reinforcement Learning to implement intelligent restart mechanisms in metaheuristic processes. The objective is to enhance the algorithms’ ability to explore and exploit the solution space more effectively, thereby improving performance in complex optimization scenarios. The study starts with a review of current metaheuristic algorithms, highlighting the issue
of premature convergence. It then explores Reinforcement Learning principles, particularly their decision-making capabilities, to optimize metaheuristic performance. A novel framework is proposed where Reinforcement Learning agents monitor the optimization process, identify stagnation phases, and initiate intelligent restarts. These restarts are strategically guided by the agents’ learned policies, ensuring diversified search when necessary and focused exploration of promising regions. Experiments on benchmark optimization problems demonstrate that integrating Reinforcement Learning significantly mitigates premature convergence, leading to superior solution quality and robust performance across various domains. This research not only addresses a critical limitation in metaheuristic optimization but also suggests new applications of Reinforcement Learning for enhancing algorithmic efficiency. The
findings underscore the potential of intelligent restart mechanisms to transform optimization, enabling more effective and adaptive metaheuristic solutions
Anomalous hydroboration at a four-coordinate Ni(II) diphenylvinylphosphine complex: Geometric impacts on solution equilibria
No full textFor coordination compounds, reliable control of metal geometry and spin state is of great interest, permitting control of reactivity and selectivity. As tuneable outputs, these observables are adjusted through thoughtful choice of ligand. This report examines a family of monophosphine-ligated nickel(II) dihalide compounds containing secondary coordination sphere borane groups. Interestingly, anomalous hydroboration of trans-[NiII(X)2(PPh2Vin)2] (Vin = vinyl) was witnessed upon treatment with HBCy2 (Cy = cyclohexyl), resulting in halide-directed Markovnikov hydroboration; these branched products were observed to be diamagnetic in solution. This outcome is in contrast with the linear ligand variants, which were prepared independently and show solution paramagnetism. Together, this report details an unusual hydroboration outcome and how this anomalous reactivity gives way to unique solution behavior of the resulting nickel(II) products simply by virtue of linear or branched secondary coordination sphere incorporation
The mediating role of reflective functioning and general psychopathology in the relationship between childhood conduct disorder and adult aggression among offenders
No full textBackground
The nature of the pathway from conduct disorder (CD) in adolescence to antisocial behavior in adulthood has been debated and the role of certain mediators remains unclear. One perspective is that CD forms part of a general psychopathology dimension, playing a central role in the developmental trajectory. Impairment in reflective functioning (RF), i.e., the capacity to understand one's own and others' mental states, may relate to CD, psychopathology, and aggression. Here, we characterized the structure of psychopathology in adult male-offenders and its role, along with RF, in mediating the relationship between CD in their adolescence and current aggression.
Methods
A secondary analysis of pre-treatment data from 313 probation-supervised offenders was conducted, and measures of CD symptoms, general and specific psychopathology factors, RF, and aggression were evaluated through clinical interviews and questionnaires.
Results
Confirmatory factor analyses indicated that a bifactor model best fitted the sample's psychopathology structure, including a general psychopathology factor (p factor) and five specific factors: internalizing, disinhibition, detachment, antagonism, and psychoticism. The structure of RF was fitted to the data using a one-factor model. According to our mediation model, CD significantly predicted the p factor, which was positively linked to RF impairments, resulting in increased aggression.
Conclusions
These findings highlight the critical role of a transdiagnostic approach provided by RF and general psychopathology in explaining the link between CD and aggression. Furthermore, they underscore the potential utility of treatments focusing on RF, such as mentalization-based treatment, in mitigating aggression in offenders with diverse psychopathologies
Fisheries management in a changing climate: insights from the Prince Edward Island lobster fishery
No full textThe one hundred-and-fifty-year-old lobster fishery of the Northwest Atlantic is a management success story, boasting increases in abundance and value since the 1980s. However, there are signs that these trends are changing, and this may be related to climate change. This study attempts to illustrate the
adaptive capacity of Prince Edward Island (Canada) lobster fishers through the lens of social capital in the context of climate change and 'islandness'. With data gathered through semi-structured interviews, personal observation and grey and scholarly literature, features of social capital and how it is mobilised are compared and contrasted between two groups of Island fishers with different fishing customs. One group operates with ‘territorial use rights in fisheries’ (TURFs); the other does not. The data suggests that TURFs may have less adaptive capacity in response to some climate impacts on lobster. It also indicates that micro level features of social capital, such as attitudes and practices of collective action, may have less influence on the adaptive capacity of Island fishers than macro level features, which include formal relationships, structures, and participation in the policy process. Lasty, this study and numerous others indicate that continued effort to improve the working relationships of scientists, regulators, processors and fishers is key to strengthening the adaptive capacity of the fishery, as is smaller-scale research and planning
Young people on social media in a globalized world: Self-optimization in highly competitive and achievement-oriented forms of life
No full textResearch investigating young people’s social media use has been criticized for its limited theoretical foundations and scope. This paper elaborates young people’s social media activity from a socio-ecological evolutionary perspective (SEE), where young people’s online exchanges cannot be divorced from the highly competitive and achievement-oriented modern market cultures in which they live. In highly competitive and achievement-oriented forms of life, young people’s social media environments are often constituted as dynamic and evolving extrinsically oriented ecological niches that afford for status and identity enhancement while also affording for peer approval, belongingness, and self-worth nested within, and subordinate to, these higher-order affordances. The extrinsic value organization of social media platforms that serve young people’s status and identity-enhancement are embodied by a community of mutually interdependent criteria that are evolutionary-based, developmentally salient, and market-driven: physical attractiveness, high (educational and extracurricular) achievements, and material success. Young people’s online signaling of these interdependent extrinsic criteria affords for status-allocation and self-enhancement, where each criteria becomes an arena for social competition and identity formation, enabling young people to build personal and optimal models of social success congruent with their own interests and abilities. Young people’s status and identity enhancing signaling of these extrinsic criteria is moving toward increasingly idealized or perfect embodiments, informed by accelerating, short-term positive feedback processes that benefit from the technological affordances and densely rewarding peer environments instantiated on social media
iPSC ‐derived microglia carrying the TREM2 R47H /+ mutation are proinflammatory and promote synapse loss
No full textGenetic findings have highlighted key roles for microglia in the pathology of neurodegenerative conditions such as Alzheimer's disease (AD). A number of mutations in the microglial protein triggering receptor expressed on myeloid cells 2 (TREM2) have been associated with increased risk for developing AD, most notably the R47H/+ substitution. We employed gene editing and stem cell models to gain insight into the effects of the TREM2 R47H/+ mutation on human-induced pluripotent stem cell-derived microglia. We found transcriptional changes affecting numerous cellular processes, with R47H/+ cells exhibiting a proinflammatory gene expression signature. TREM2 R47H/+ also caused impairments in microglial movement and the uptake of multiple substrates, as well as rendering microglia hyperresponsive to inflammatory stimuli. We developed an in vitro laser-induced injury model in neuron–microglia cocultures, finding an impaired injury response by TREM2 R47H/+ microglia. Furthermore, mouse brains transplanted with TREM2 R47H/+ microglia exhibited reduced synaptic density, with upregulation of multiple complement cascade components in TREM2 R47H/+ microglia suggesting inappropriate synaptic pruning as one potential mechanism. These findings identify a number of potentially detrimental effects of the TREM2 R47H/+ mutation on microglial gene expression and function likely to underlie its association with AD.The Robert A. and Renee E. Belfer Family FoundationJPB FoundationCure Alzheimer's FundHuman Frontier Science Progra
Keratinocytes drive the epithelial hyperplasia key to sea lice resistance in coho salmon
No full textBackground: Salmonid species have followed markedly divergent evolutionary trajectories in their interactions with sea lice. While sea lice parasitism poses significant economic, environmental, and animal welfare challenges for Atlantic salmon (Salmo salar ) aquaculture, coho salmon (Oncorhynchus kisutch ) exhibit near-complete resistance to sea lice, achieved through a potent epithelial hyperplasia response leading to rapid louse detachment. The molecular mechanisms underlying these divergent responses to sea lice are unknown. Results: We characterized the cellular and molecular responses of Atlantic salmon and coho salmon to sea lice using single-nuclei RNA sequencing. Juvenile fish were exposed to copepodid sea lice (Lepeophtheirus salmonis ), and lice-attached pelvic fin and skin samples were collected 12 h, 24 h, 36 h, 48 h, and 60 h after exposure, along with control samples. Comparative analysis of control and treatment samples revealed an immune and wound-healing response that was common to both species, but attenuated in Atlantic salmon, potentially reflecting greater sea louse immunomodulation. Our results revealed unique but complementary roles of three layers of keratinocytes in the epithelial hyperplasia response leading to rapid sea lice rejection in coho salmon. Our results suggest that basal keratinocytes direct the expansion and mobility of intermediate and, especially, superficial keratinocytes, which eventually encapsulate the parasite. Conclusions: Our results highlight the key role of keratinocytes in coho salmon’s sea lice resistance and the diverged biological response of the two salmonid host species when interacting with this parasite. This study has identified key pathways and candidate genes that could be manipulated using various biotechnological solutions to improve Atlantic salmon sea lice resistance