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Uncovering outer-sphere mechanisms governing chemoselectivity in copper-photocatalyzed ATRA reactions of CF<sub>3</sub>SO<sub>2</sub>Cl with alkenes
No full textThis work presents a detailed DFT-based mechanistic investigation of copper-photocatalyzed atom transfer radical addition (ATRA) reactions between CF3SO2Cl and alkenes. Depending on the electronic nature of the alkene substrate, these reactions yield either RCl or RSO2Cl products. The unusual divergence in product selectivity has led to the proposal of multiple mechanistic pathways. In this study, we show that all productive pathways proceed exclusively via outer-sphere single-electron transfer and identify two previously unrecognized mechanisms: an S(vi)/S(iv) redox cycling mechanism responsible for RSO2Cl formation, and a 2c–3e Cl-coordination-induced SET mechanism accounting for RCl formation. These two pathways represent the first models to explicitly demonstrate the bifunctional role of the [SO2Cl]− anion in governing divergent product formation. Additionally, we identify a third, cationic mechanism, in which the carbon-centred radical is oxidized to a carbocation by Cu(ii), competing with the other pathways and likewise leading to RCl. Taken together, these results provide a useful framework for understanding chemoselectivity in this class of photocatalytic transformations and may help guide the design of future ATRA protocols.Peer-reviewe
Impacts of 1.5°C and 2.0°C Global Warming on the Onset, Cessation, and Length of the Rainy Season in Global Land Monsoon Regions
No full textThe onset, cessation, and length of the rainy season are crucial for global water resources, agricultural practices, and food security. However, the response of precipitation seasonality to global warming remains uncertain. In this study, we analyze how global warming levels (GWLs) of 1.5°C and 2°C could affect the timing of rainfall onset (RODs), rainfall cessation (RCDs), and the overall duration of the rainy season (LRS) over global land monsoon (GLM) regions using simulations from CMIP6 under the SSP2-4.5 and SSP5-8.5 scenarios. With high model consensus, our results reveal that RODs are projected to occur later over Southern Africa, North Africa, and South America, but earlier over South Asia and Australia, in a warmer climate. The projected early RODs in Australia are more pronounced at the 2°C GWL under SSP5-8.5. On the other hand, early RCDs are projected over South America and East Asia, while late RCDs are projected over North Africa, with high inter-model agreement. These changes are associated with a future decrease in LRS in most GLM regions. Additionally, we found that continuous warming over 1.5°C will further reduce the length of the rainy season, especially over the South America, North Africa, and Southern Africa monsoon regions. The findings underscore the urgent need to mitigate global warming.We thank the World Climate Research Programme’s Working Group on Coupled Modeling for managing the CMIP initiative, and express our gratitude to the climate modeling groups (as listed in Table S1) for their model outputs. We also appreciate the institution that provided the CPC observational data used in this research. Oluwafemi E. ADEYERI is supported by the Australian Research Council (Grant No. CE230100012).Peer-reviewe
Personality and impulsivity traits associated with problematic online gaming and poker playing
No full textOnline gambling and gaming are associated with Problematic Usage of the Internet (PUI) in subgroups of individuals. This study aimed to assess how different personality dimensions are associated with PUI scores of Massively Multiplayer Online Role Playing Games (MMORPG) players and online poker players, and to characterize common and specific personality traits of both groups in their association with PUI. Participants (N = 1144) were recruited online and assessed with the Internet Addiction Test (IAT), the Big Five Inventory and the Short UPPS-P Impulsive Behavior Scale. Data were analyzed with multiple robust linear regression models. The first model tested the associations between personality and impulsivity traits with IAT scores, while controlling for age, gender, and type of online activity. The second model included interaction terms to assess whether these associations differed between MMORPG and poker players. In model 1, neuroticism, negative urgency, positive urgency and sensation seeking were significantly and positively associated with higher IAT scores after controlling for the other personality traits, age, gender, and type of online activity. Extraversion was negatively associated with IAT scores. In Model 2, no significant difference in how these personality traits relate to IAT scores was observed between the two groups. Results highlight that traits such as neuroticism, negative urgency, positive urgency, and sensation seeking constitute potential risk factors for PUI, while extraversion might constitute a protective factor against PUI. The identified associations could be useful in understanding players’ attitudes and supporting them in gaining insight into their difficulties.Peer-reviewe
Topological analysis of topological insulators and political networks: an interdisciplinary study
No full textTopological data analysis is an emerging powerful data analysis tool inspired by algebraic topology. In this thesis I present my application of topological data analysis to the field of topological insulators and political networks.
In the context of topological insulators, I explored the potential of using topological data analysis in classifying topological phases in the extended Su-Schrieffer-Heeger (SSH) models, which are fundamental models describing the physical system in topological insulators. I show, in this study, the success of applying topological data analysis to the complex SSH model and the challenges in extending the method into non-Hermitian SSH models.
The application of topological data analysis to professional networks within Australian Parliament from 1947 to 2019 follows a different trajectory. The career background data is significantly more complex compared to the simulated data used in the study of SSH models. As such, the project is separated into two stages, understanding the professional networks using network theory, and the application of topological data analysis to these networks.
The analysis of these professional networks included summary statistics and random graph simulations of party-specific networks within the Australian Labor Party and Liberal Party. Through this analysis, we discovered an important structure within these association networks, the bouquet structures. I show how these structures can be used as a new centrality measure that opens up research opportunities for qualitative work. I also present ongoing work utilising Approximate Bayesian Computation techniques to detect these bouquet structures.
For the second stage of this project, I propose an alternative centrality measure for the professional networks using topological data analysis. We aim to compare the centrality measures proposed in this project against the career success of relevant Members of Parliament.
I also include a published paper in positron physics where we computed the ground state energy of a quasi-free positron in noble gases. This was completed before a change in supervision
On the global centroid moment tensor achievements and the next generation earthquake catalogs
No full textThe systematic determination of the source characteristics of global earthquakes and other seismic sources in a robust and consistent manner is a paramount task in seismology. The Global Centroid Moment Tensor (GCMT) project (Ekström et al., 2012), employing an elegant inversion approach and thoughtful data selection, has been a standard bearer for such an autonomous earthquake catalog. This, by no means an all-encompassing review, celebrates the long-lasting impact and legacy it has left on the seismological and broader Earth science community, from tectonics and structural geology to geodesy and hazard assessment. We also identify and discuss three areas that, in our view, are subject to potential improvement in the current GCMT practice. These include (i) enhanced quantification of uncertainty in MT solutions, (ii) utilization of 3D Earth models, and (iii) robust development of dynamic models that extend beyond a point source assumption in time and space. Recent developments in various areas of theoretical and observational seismology, such as advances in Bayesian inversion, 3D waveform modeling, and applied machine learning methods, will enable the integration of these needed elements into the next generation of routine earthquake catalogs.Peer-reviewe
The applications of two-dimensional materials in electronics and energy harvesting
No full textWith the rapid development of the Internet of Things (IoT), people's daily lives are increasingly dependent on diverse personal electronic devices. To meet the demands of portability, seamless integration, and comfort in wearable and implantable systems, these devices must be smaller, more efficient, and mechanically flexible. However, conventional materials such as silicon, metals, and oxides face limitations including large size, heavy weight, poor biocompatibility, and limited adaptability to deformation. Traditional batteries also show low compatibility with flexible systems and raise environmental and safety concerns. These drawbacks restrict next-generation portable and wearable devices, driving research into novel materials.
Two-dimensional (2D) materials, such as transition metal dichalcogenides (TMDs) and MXenes, have gained attention due to their unique optical, electrical, and mechanical properties, making them promising for miniaturized and flexible devices. Optical studies of heterostructures composed of monolayer WS2 on MXene quantum dots (QDs) show strong photoluminescence (PL) enhancement at room temperature and rich excitonic dynamics at cryogenic temperatures. These arise from localized plasmonic effects of QDs and the suspended WS2 structure, which enhance many-body interactions and emission efficiency. This demonstrates the potential of 2D materials for high-performance optoelectronic devices.
Monolayer WS2, with a direct bandgap of about 2.0 eV and excellent flexibility, is well-suited for wearable optoelectronic applications such as LEDs. Using a hybrid continuous-pulsed injection scheme, WS2 LEDs achieve over 20-fold enhancement in emission efficiency and a large active area (around 25 micronmeter) at room temperature. Moreover, tuning the applied alternating voltage allows emission wavelength modulation over 40 nm, highlighting the potential of 2D materials in high-performance, wavelength-tunable optoelectronics.
Beyond optoelectronics, MXene-based systems offer great promise in energy harvesting due to their biocompatibility and conductivity. A MXene (Ti3C2Tx) 5G antenna efficiently harvests radio-frequency energy under very low input power, requiring about 16 times lower power density than copper antennas, while maintaining over 99% efficiency under 90 degrees of bending. This flexibility underscores its potential as a wireless, battery-free energy harvester for wearables.
Despite these advantages, MXene antennas face challenges such as relatively high minimum input power and restricted operational ranges. To address this, MXene-based hybrid moisture electric generators (hMEGs) have been developed. hMEGs continuously generate electricity by absorbing ambient moisture, providing a sustainable green power supply. When integrated into textiles via screen printing, planar MXene hMEGs can directly power devices such as hearing aids and Bluetooth-enabled power management systems.
In summary, this thesis explores the unique properties of 2D materials, demonstrating their application in flexible optoelectronic devices and energy harvesters. It proposes two types of 2D materials-based generators as sustainable power sources for wearable systems. These results offer valuable insights and guidance for future integration of 2D materials into wearable technologies, both as functional devices and as power supplies
Twelve Japanese War Criminals and one Who Got Away
No full textIn Twelve Japanese War Criminals and One Who Got Away, Robert Cribb and Sandra Wilson tell the stories of twelve people who were convicted of war crimes in Allied courts in the Asia-Pacific region after the Second World War. Included is the story of one man who escaped prosecution. The crimes were committed in the Philippines, Burma, Thailand, Java, Malaya, Singapore, the Maluku islands, New Guinea, and Japan. The characters examined range from senior figures—General Honma Masaharu, who was convicted for the Bataan “death march,” and Japan’s wartime prime minister Tōjō Hideki—to lower-ranking and lesser-known people: a POW camp commander, a camp doctor, a Korean guard, a nurse charged with assisting in vivisection, a doctor convicted of cannibalism, a pimp, a Taiwanese interpreter, a businessman convicted of assault, an officer convicted of massacre, and another convicted of a single execution. Tsuji Masanobu, the man who escaped, was responsible for at least two massacres. He was eventually elected to parliament, indicating the willingness of some elements in postwar Japanese society to overlook wartime atrocities.
The book examines the backgrounds and careers of each character and explains how they came to commit the acts for which they were convicted. It also considers their subsequent careers, if they survived (several were executed for their crimes). Based on years of meticulous research, the book brings to life the texture of individual action and experience in the tumultuous years of conflict and occupation during the Pacific War. The authors recognize Japanese cruelty but also suggest that most of the convicted war criminals were not inherently evil. Some were out of their depth or were forced into circumstances where they made bad decisions; some obeyed illegal orders or were caught in impossible situations in a war that Japan fought with insufficient resources. Ironically, the one who got away was probably the worst of them all.Peer-reviewe
Random effects misspecification and its consequences for prediction in generalized linear mixed models
No full textWhen fitting generalized linear mixed models, choosing the random effects distribution is an important decision. As random effects are unobserved, misspecification of their distribution is a real possibility. Thus, the consequences of random effects misspecification for point prediction and prediction inference of random effects in generalized linear mixed models need to be investigated. A combination of theory, simulation, and a real application is used to explore the effect of using the common normality assumption for the random effects distribution when the correct specification is a mixture of normal distributions, focusing on the impacts on point prediction, mean squared prediction errors, and prediction intervals. Results show that the level of shrinkage for the predicted random effects can differ greatly under the two random effect distributions, and so is susceptible to misspecification. Also, the unconditional mean squared prediction errors for the random effects are almost always larger under the misspecified normal random effects distribution, while results for the mean squared prediction errors conditional on the random effects are more complicated but remain generally larger under the misspecified distribution (especially when the true random effect is close to the mean of one of the component distributions in the true mixture distribution). Results for prediction intervals indicate that the overall coverage probability is, in contrast, not greatly impacted by misspecification. It is concluded that misspecifying the random effects distribution can affect prediction of random effects, and greater caution is recommended when adopting the normality assumption in generalized linear mixed models.This work was supported by the Australian Research Council under Grants DP230101908 and DP240100143. Thank you to Nickson Xu Ning for useful discussions.Peer-reviewe
Synergies and Trade-offs in Urban Green Infrastructure
No full textUrban Green Infrastructure (UGI) is increasingly integrated into urban planning to tackle climate change, biodiversity loss, and public health challenges. Its multifunctionality and ability to deliver multiple Ecosystem Services (ESs) make UGI a "win-win" nature-based solution. Yet, focusing only on benefits risks overlooking Ecosystem Disservices (EDs) and the trade-offs from competing goals. This thesis advances a multidimensional, causally informed understanding of how synergies and trade-offs in UGI are conceptualised in research and practice. It addresses four questions: how these synergies and trade-offs are conceptualised; how they are represented and assessed in studies; how plant functional traits influence them; and what synergies and trade-offs exist between UGI policy objectives and stakeholder perceptions in Canberra, Australia.
A tripartite analytical framework is developed to explain synergies and trade-offs as outcomes shaped by three interconnected dimensions: biophysical processes, sociocultural values, and policy priorities. Moving beyond simple correlations between ESs and EDs, the framework serves as a diagnostic tool to identify causal mechanisms and context-specific dynamics.
A mixed-methods design operationalises and tests the framework. First, a systematic review of 96 global studies shows a dominant focus on biophysical outcomes and a reliance on statistical bundling of ESs and EDs, offering limited explanatory power. It highlights the potential of functional trait analysis as an underused method to identify ecological drivers of ESs and EDs and improve causal inferences.
Building on this, the first case study uses functional trait analysis to examine synergies and trade-offs in microclimatic benefits, Urban Heat Island (UHI) mitigation and thermal stress reduction, provided by four morphologically distinct urban tree species in Canberra. Results show trait-service relationships are highly context-dependent. Factors such as solar irradiance, seasonality, and surface material affect cooling benefits. Traits like crown density consistently deliver synergistic benefits, while others create trade-offs under varying solar conditions. These findings demonstrate the diagnostic value of trait analysis but caution against universal trait prescriptions, calling for locally adapted planning.
The second case study explores sociocultural and policy dimensions through thematic analysis of legislation, policy documents, and stakeholder submissions to a Canberra urban forest inquiry. While legislation is cohesive, policies and stakeholder views diverge. Policies emphasise city-wide canopy expansion for biodiversity and UHI mitigation, whereas stakeholders highlight concerns such as property damage and personal safety. These differences reveal potential mismatches and trade-offs between policy goals and community expectations, and even among policymakers themselves. The study underscores the need for proactive, inclusive engagement to achieve socially sustainable UGI outcomes.
Overall, the research confirms that synergies and trade-offs are shaped not only by ecological factors but also by sociocultural values and policy priorities. The tripartite framework offers both theoretical and practical advances for diagnosing and navigating complexity in UGI planning. It contributes to global debates by promoting an integrative, reflexive approach to planning UGI that is ecologically effective, socially inclusive, and institutionally viable