University of New Brunswick

Motivated by theories of music-to-language transfer, we investigated whether and how musicianship benefits phonological and lexical prosodic awareness in first language (L1) Cantonese and second language (L2) English. We assessed 86 Cantonese-English bilingual children on rhythmic sensitivity, pitch sensitivity, non-verbal intelligence, inhibitory control, working memory, Cantonese phonological awareness, Cantonese tone awareness, English phonological awareness, and English stress awareness. Based on their prior music learning experience, we classified the children as musicians and non-musicians. The musicians performed better than the non-musicians on Cantonese phonological awareness, Cantonese tone awareness, and English phonological awareness. Additionally, the musicians had superior pitch sensitivity, non-verbal intelligence, inhibitory control, and working memory than the non-musicians. For Cantonese and English phonological awareness, neither cognitive abilities nor pitch and rhythmic sensitivities turned out to be unique predictors. However, working memory uniquely predicted Cantonese tone awareness, with age, rhythmic sensitivity, and pitch sensitivity controlled. From a theoretical perspective, our findings on Cantonese tone awareness favors the cognitive perspective of music-to-language transfer, in which working memory enhancement could explain the musicians’ superior performance in Cantonese tone awareness. However, our findings on phonological awareness do not favor the cognitive perspective, nor do they favor the perceptual perspective, in which enhanced rhythmic and pitch sensitivities could explain musicians’ advantage.

Tetraene-linked Diketopyrrolopyrrole (DPP)-based CMPs were developed via Knoevenagel condensation of ditopic active hydrogen containing DPP with tritopic aryl aldehydes. The "tetra-ene" π-arrangement in the molecular framework promotes uninterrupted π-delocalization, resulting...

An experimental study by Hyun and Luck suggests that object working memory, but not spatial working memory, is employed during mental rotation. In contrast, correlational research points to the relevance of spatial working memory in mental rotation. Considering these somewhat conflicting results and the fact that a small sample was acquired in the study of Hyun and Luck, a replication of their study was conducted. Additionally, potential sex effects were explored. We collected (usable) data from 213 individuals across two experiments. All participants performed a mental-rotation task alone, a working-memory task alone, and both tasks concurrently. We expected greater rotation-dependent interference between tasks when the working memory task concerned object features (Experiment 1) than when it concerned spatial locations (Experiment 2). In Experiment 1, dual-task interference was observed in working-memory accuracy. In Experiment 2, there were interference effects in both mental rotation accuracy and working-memory accuracy. However, interference did not differ between experiments. Moreover, interference was not rotation dependent in either of the experiments. Thus, we could not replicate the findings of Hyun and Luck. No sex differences were found in exploratory analyses. The general interference effects found in this study may reflect the involvement of visual working memory in the processing and decision-making stages of the mental rotation of letters. This study underscores the need for further research to fully understand the role of visual working memory in mental rotation, especially with more complex stimuli.

Computational Pathology (CPath) is an interdisciplinary science that augments developments of computational approaches to analyze and model medical histopathology images. The main objective for CPath is to develop infrastructure and workflows of digital diagnostics as an assistive CAD system for clinical pathology, facilitating transformational changes in the diagnosis and treatment of cancer that are mainly address by CPath tools. With evergrowing developments in deep learning and computer vision algorithms, and the ease of the data flow from digital pathology, currently CPath is witnessing a paradigm shift. Despite the sheer volume of engineering and scientific works being introduced for cancer image analysis, there is still a considerable gap of adopting and integrating these algorithms in clinical practice. This raises a significant question regarding the direction and trends that are undertaken in CPath. In this article we provide a comprehensive review of more than 800 papers to address the challenges faced in problem design all-the-way to the application and implementation viewpoints. We have catalogued each paper into a model-card by examining the key works and challenges faced to layout the current landscape in CPath. We hope this helps the community to locate relevant works and facilitate understanding of the field’s future directions. In a nutshell, we oversee the CPath developments in cycle of stages which are required to be cohesively linked together to address the challenges associated with such multidisciplinary science. We overview this cycle from different perspectives of data-centric, model-centric, and application-centric problems. We finally sketch remaining challenges and provide directions for future technical developments and clinical integration of CPath. For updated information on this survey review paper and accessing to the original model cards repository, please refer to GitHub. Updated version of this draft can also be found from arXiv.

Two-stage submodular maximization problem under cardinality constraint has been widely studied in machine learning and combinatorial optimization. In this paper, we consider knapsack constraint. In this problem, we give n articles and m categories, and the goal is to select a subset of articles that can maximize the function F(S) . Function F(S) consists of m monotone submodular functions $f_{j}, j=1,2, \ldots, m$ , and each $f_{j}$ measures the similarity of each article in category j . We present a constant-approximation algorithm for this problem.

Soil salinity affects major viticultural areas worldwide with chloride ions being the primary source of salt toxicity in grapevines (Vitis vinifera). This toxicity impacts vine health and reduces fruit yield and quality. Current breeding efforts to improve grapevine salinity tolerance are limited by the low throughput of available phenotyping methods, which are time‐consuming, labor‐intensive, and destructive. This study demonstrated that hyperspectral proximal sensing can be utilized as a high‐throughput, nondestructive screening technique to identify salinity‐tolerant grapevine germplasm. The predictive abilities of two different hyperspectral devices, which varied in price, resolution, and sensitivity, were compared across 23 Vitis accessions spanning eight species. Prediction models were built using hyperspectral reflectance and leaf chloride content measured with a lab chloridometer. Three distinct approaches were studied: (1) analyzing the correlation between individual wavelengths and chloride content; (2) employing machine learning models, including partial least square regression (PLSR), random forest, and support vector machine, utilizing all wavelengths; and (3) classification‐based prediction using partial least square discriminant analysis (PLSDA). Multiple regions in the spectrum, including 613–660 nm, 689–696 nm, and 1357–1358 nm, showed a medium correlation (0.30–0.50) with chloride content in the leaves. PLSR was the most effective machine learning approach, demonstrating moderate predictive capability for chloride content (maximum R² = 0.67), though performance varied between the two devices tested. With PLSDA, predictions increased considerably, up to an accuracy of 0.97, depending on the instrument used and the spectral data transformation. Overall, the more expensive and sensitive device with a wider spectral range outperformed the more affordable, shorter range device. However, when the prediction model was based on classes (chloride excluders vs. non‐excluders) rather than chloride content, the differences in prediction abilities were minimal, with both instruments performing very well. This is promising for identifying breeding materials with chloride exclusion capabilities at low cost and high throughput.

Arctic ecotones contain dynamic freshwater ecosystems where aquatic biota vary across these transitions and as such can be especially susceptible to environmental change. Here, we examine the palaeoecology of two ponds in the ecotonal Hudson Bay Lowlands, subarctic Canada, to understand how aquatic biota have responded in an increasingly climate‐stressed Anthropocene, and to better anticipate future changes. Using a multi‐proxy palaeolimnological approach, we reconstruct past environmental conditions through the examination of subfossil chironomids (Diptera: Chironomidae) and compare these records to organic carbon and nitrogen elemental and isotope composition, and previously published cellulose‐inferred lake water oxygen isotope records. Despite their close proximity, we found different chironomid assemblages in each pond that reflected differences in hydrological trajectories since 1940; an isolated pond exposed to evaporative stress showed an increasingly littoral chironomid assemblage, while a nearby basin that began receiving waters from a channel fen lost semi‐terrestrial taxa associated with flooded grassy margins that became more permanently submerged. Even though large catchment‐mediated changes resulted in a shift in some chironomids of both ponds, chironomid‐based palaeo‐temperature reconstructions demonstrated similar warming trends. Shifts in the ecology of subarctic lakes and ponds are expected to increase as the effects of climate change become more severe.

The hazards of dust are receiving increasing attention with the application of bamboo industrialization. This study focuses on the morphological characteristics and formation mechanisms of milling dust from raw bamboo, dried bamboo, and thermally modified bamboo treated at varying temperatures. The particle size distribution, area-equivalent diameter, minimum Feret diameter, aspect ratio, roundness, and convexity were investigated. A new method combining sieving and image scanning analysis was applied to identify the size and morphology of the dust. The study has found that thermal modification significantly affects particle size and distribution, impacting dust convexity and surface characteristics. Particle size has a greater impact on dust morphology compared to heat treatment temperature. Thermal treatment is shown to degrade hemicellulose, reducing bamboo’s transverse mechanical properties and thereby altering the generated dust. The three-step cutting process is established, including bamboo milling deformation and dust formation by finite element simulation. This study offers a reference for optimizing dust removal ports and enabling real-time adjustments to dust removal system power based on dust morphology.

Plain Language Summary The Amapari Marker Band (AMB) at Gale crater forms a distinct, dark‐toned, resistant horizon identified from orbit within rock layers of the Mg‐sulfate‐bearing, central mound. Curiosity recently investigated the AMB and found a lower rippled layer, consistent with a shallow lake, contrasting with windblown sediment deposition above and below it. Analysis of the AMB by the Alpha Particle X‐ray spectrometer also revealed a marked change in the chemistry of the rocks, with the highest in situ FeO and Zn abundances measured on Mars, elevated MnO, and a composition consistent with input of different sediment compared to underlying rocks. The change in bulk chemistry persists into the overlying rocks indicating that the AMB marks a significant event in the evolution of Gale crater, and possibly beyond. The AMB may record deposition of basaltic volcanic ash into a lake; the high metal concentrations resulting from gas reactions within an ash cloud. Alternatively, the high metals may be the result of water/sediment interactions: either in the lake, and/or after deposition and possibly after becoming a solid rock. Ongoing and future work will aim to further constrain processes responsible for deposition of the AMB, the high metal concentrations and its regional and global implications.

Biological invasions significantly impact native ecosystems, altering ecological processes and community behaviors through predation and competition. The introduction of non-native species can lead to either coexistence or extinction within local habitats. Our research develops a lizard population model that integrates aspects of competition, intraguild predation, and the dispersal behavior of intraguild prey. We analyze the model to determine the existence and stability of various ecological equilibria, uncovering the potential for bistability under certain conditions. By employing the dispersal rate as a bifurcation parameter, we reveal complex bifurcation dynamics associated with the positive equilibrium. Additionally, we conduct a two-parameter bifurcation analysis to investigate the combined impact of dispersal and intraguild predation on ecological structures. Our findings indicate that intraguild predation not only influences the movement patterns of brown anoles but also plays a crucial role in sustaining the coexistence of different lizard species in diverse habitats.

Water use efficiency (WUE) quantifies the amount of water expended per unit of dry leaf matter accumulated, reflecting the trade-offs between water consumption and carbon uptake. It is also a critical parameter for understanding plant responses to environmental changes. This study introduced an innovative set of WUE-related parameters, including maximum water use efficiency (WUEmax) and associated coefficients of water potential, loss, strategic usage, and total usage (WPC, WLC, WSC, and WTC, respectively) in providing a comprehensive evaluation of water use strategies in 48 common tropical plant species during the natural light fluctuations. These parameters exhibited significant differences among plant types, with sun-adapted and shade-tolerant plants (both C3) showing mean of WUEmax values of 3.81 ± 0.63 and 5.42 ± 1.61 μmol mmol−1, respectively, whereas C4 plants demonstrated a greater WUEmax of 7.04 ± 1.77 μmol mmol−1. Compared to C3 plants, particularly shade-tolerant types, C4 plants exhibited significantly higher WPC and WTC (p < 0.05). Furthermore, shade-tolerant plants displayed lower WLC and higher WSC than sun-adapted plants, suggestive of their specialized adaptations to variations in light intensity. The sensitivity of stomatal and mesophyll conductance (i.e., gs and gm) to incident light (Iinc) and/or intercellular CO2 concentration (Ci) helped clarify the source of variation in WUE-related parameters. In sun-adapted plants, gs was sensitive to changes in both Iinc and Ci. In terms of gm, shade-tolerant plants exhibited the lowest overall sensitivity to Iinc. Increasing atmospheric CO2 concentrations from 400 to 450 ppm caused WUE-related parameters to vary, with this response differing among plant types. These insights emphasize the significance of plant adaptation strategies in tropical rainforest ecosystems.

Government of New Brunswick implemented One-at-a-Time (OAAT) therapy, a single-session approach to care, within Addiction and Mental Health (A&MH) services. We conducted interviews to understand determinants of implementation from program champions. Champions of the OAAT therapy implementation (N = 19; Child/Youth n = 8, Adult n = 11) working within A&MH services and school districts were recruited through the provincial implementation team. Transcripts were synthesized using thematic analysis. Determinants were organized as facilitators and barriers in accordance with the Consolidated Framework for Implementation Research (CFIR). Thematic analysis resulted in 18 themes and 5 recommendations. Facilitators within the inner setting included: (1) need for change and perceived benefits of OAAT therapy; (2) compatibility of OAAT therapy with previous practice and service processes; and (3) support received from champions and colleagues. Insufficient resources (e.g., staff and physical infrastructure), and a culture that favored long-term therapy were barriers. Navigating age of consent, and implementation around COVID-19 were barriers within the outer setting. Facilitators within the implementation process domain included: (1) interconnected teams across sites, regions and the province; (2) collaborative implementation planning; (3) flexibility to tailor implementation at sites; and (4) mentorship provided by champions. Insufficient standardization of the implementation and limited representation among affected parties (e.g., community partners) were barriers within the implementation process. This study elucidated determinants that influenced implementation of a new service delivery within an Eastern Canadian provincial health care system. Findings can serve as a heuristic for organizations looking to enact similar implementation initiatives.

Integrating climate change into strategic forest management is crucial for predicting forest dynamics and maintaining resource availability. However, there is no scientific consensus on how to integrate their climate-sensitive outputs into strategic forest planning. In this study, we propose a novel approach to incorporate climate change into a strategic forest planning model, Woodstock, using a parsimonious set of climate-sensitive stand yield tables and transition rules derived from the PICUS stand simulation model, calibrated for the Acadian forest region. Climate-sensitive yield tables were generated for the baseline and two climate forcing scenarios to dynamically capture climate effects on forest growth and composition. Initial forest conditions were grouped into four age classes for each stand type, with future conditions determined by three transition periods. Simulations predict a significant shift toward warm-adapted species, with red maple, white pine, and yellow birch becoming dominant, while cold-adapted species like balsam fir and spruce decline by 2120. Under high climate forcing, the merchantable wood volume is projected to decrease by 50%, indicating potential shortages and economic risks. The incorporation of climate change uncertainty into strategic forest planning is essential to reduce the risk of overutilization of forest resources. This research offers a novel and straightforward approach to integrating climate change into forest planning models.