Raman signatures of inversion symmetry breaking structural transition in quasi-1D compound, (TaSe4)3I.

The breaking of inversion symmetry combined with spin-orbit coupling, can give rise to intrigu- ing quantum phases and collective excitations. Here, we report systematic temperature dependent Raman scattering and theoretical calculations of phonon modes across the inversion symmetry- breaking structural transitions in a quasi-one-dimensional compound (TaSe4)3I. Our investigation revealed the emergence of three additional Raman-active modes in Raman spectra of the low- temperature (LT) non-centrosymmetric (NC) structure of the material.

Incongruent Expectations: A Qualitative Study of the Gendered Experiences of Canadian Young People.

While the early mental health of girls and boys is similar, as children age, girls tend to report worse mental health than boys. Explanations for these gendered disparities remain elusive. This study seeks to understand the social context in which mental health experiences are shaped.

The theory of Barlow packings: Basic properties and cohesive energies from exact lattice summations within the sticky hard-sphere model.

The theory of periodic Barlow multi-lattices (X1X2…XN)∞ with Xi ∈ {A, B, C} and Xi ≠ Xi+1 of stacked two-dimensional hexagonal close-packed layers is presented and used to derive exact lattice sum expressions in terms of fast converging Bessel function expansions for inverse power potentials. We describe in detail the mathematical properties of Barlow sphere packings and demonstrate that only two basic lattice sums are required to describe all periodic packings. For the sticky hard-sphere model with an attractive inverse power law potential, we find a linear correlation between the cohesive energies of different Barlow packings and the face-centered cubic packing fraction.

Mapping rapeseed () aboveground biomass in different periods using optical and phenotypic metrics derived from UAV hyperspectral and RGB imagery.

Aboveground biomass (AGB) is a key indicator of crop nutrition and growth status. Accurately and timely obtaining biomass information is essential for crop yield prediction in precision management systems. Remote sensing methods play a key role in monitoring crop biomass.

New Campylobacter Lineages in New Zealand Freshwater: Pathogenesis and Public Health Implications.

This study investigated the diversity of thermophilic Campylobacter species isolated from three New Zealand freshwater catchments affected by pastoral and urban activities. Utilising matrix-assisted laser desorption ionisation-time of flight and whole genome sequence analysis, the study identified Campylobacter jejuni (n = 46, 46.0%), C.

Multi-regional control of amygdalar dynamics reliably reflects fear memory age.

The basolateral amygdala (BLA) is crucial for the encoding and expression of fear memory, yet it remains unexplored how neural activity in this region is dynamically influenced by distributed circuits across the brain to facilitate expression of fear memory of different ages. Using longitudinal multisite electrophysiological recordings in male mice, we find that the recall of older contextual fear memory is accompanied by weaker, yet more rhythmic, BLA gamma activity which is distally entrained by theta oscillations in both the hippocampal CA1 and the anterior cingulate cortex. Computational modeling with Light Gradient Boosting Machine using extracted oscillatory features from these three regions, as well as with Transformer using raw local field potentials, accurately classified remote from recent memory recall primarily based on BLA gamma and CA1 theta.

Out of (the) bag-encoding categorical predictors impacts out-of-bag samples.

Performance of random forest classification models is often assessed and interpreted using out-of-bag (OOB) samples. Observations which are OOB when a tree is trained may serve as a test set for that tree and predictions from the OOB observations used to calculate OOB error and variable importance measures (VIM). OOB errors are popular because they are fast to compute and, for large samples, are a good estimate of the true prediction error.

Visual Integration of Genome-Wide Association Studies and Differential Expression Results with the Hidecan R Package.

Background/objectives: We present hidecan, an R package for generating visualisations that summarise the results of one or more genome-wide association studies (GWAS) and differential expression analyses, as well as manually curated candidate genes, e.g., extracted from the literature.

Activity patterns in ring networks of quadratic integrate-and-fire neurons with synaptic and gap junction coupling.

We consider a ring network of quadratic integrate-and-fire neurons with nonlocal synaptic and gap junction coupling. The corresponding neural field model supports solutions such as standing and traveling waves, and also lurching waves. We show that many of these solutions satisfy self-consistency equations which can be used to follow them as parameters are varied.

Visible Light-Induced Regioselective to Isomerization of Polarized 1,3-Dienes: Experimental and Theoretical Insights.

The stereocontrol of → isomerization on a (1,3)-diene, instead of a simple alkene, can be more challenging due to the increased number of isomerization possibilities. Herein, we report visible light-mediated regioselective (1,3 → 1,3) isomerization of (1,3)-diene. The reaction conditions are mild and easy to apply and can be applied to a wide range of substances, with an excellent yield and selectivity (90:10).

Quantitative assessment of The Group of Seven's collaboration in sustainable development goals.

Strengthening international collaboration is essential to achieving the United Nations' SDGs. The Group of Seven (G7) is recognized for acting and enhancing cooperation to achieve the SDGs. However, the current understanding of G7's cooperation is rather subjective without quantitative measurements.

Q-RPL: Q-Learning-Based Routing Protocol for Advanced Metering Infrastructure in Smart Grids.

Efficient and reliable data routing is critical in Advanced Metering Infrastructure (AMI) within Smart Grids, dictating the overall network performance and resilience. This paper introduces Q-RPL, a novel Q-learning-based Routing Protocol designed to enhance routing decisions in AMI deployments based on wireless mesh technologies. Q-RPL leverages the principles of Reinforcement Learning (RL) to dynamically select optimal next-hop forwarding candidates, adapting to changing network conditions.

From Hard to Soft Dense Sphere Packings: The Cohesive Energy of Barlow Structures Using Exact Lattice Summations for a General Lennard-Jones Potential.

There are infinitely many distinguishable dense sphere packings in dimension three (Barlow structures) with maximum packing density of ρ = π/√18. While Hales [Hales, T. C.

Population structure and pathogen interaction of Escherichia coli in freshwater: Implications of land-use for water quality and public health in Aotearoa New Zealand.

Freshwater samples (n = 199) were obtained from 41 sites with contrasting land-uses (avian, low impact, dairy, urban, sheep and beef, and mixed sheep, beef and dairy) and the E. coli phylotype of 3980 isolates (20 per water sample enrichment) was determined. Eight phylotypes were identified with B1 (48.

On the higher-order smallest ring-star network of Chialvo neurons under diffusive couplings.

Network dynamical systems with higher-order interactions are a current trending topic, pervasive in many applied fields. However, our focus in this work is neurodynamics. We numerically study the dynamics of the smallest higher-order network of neurons arranged in a ring-star topology.

Artificial intelligence based glaucoma and diabetic retinopathy detection using MATLAB - retrained AlexNet convolutional neural network.

Background: Glaucoma and diabetic retinopathy (DR) are the leading causes of irreversible retinal damage leading to blindness. Early detection of these diseases through regular screening is especially important to prevent progression. Retinal fundus imaging serves as the principal method for diagnosing glaucoma and DR.

Profiling the novel plant-based meat alternative category: Consumer affective and sensory response in the context of perceived similarity to meat.

Plant-based meat alternatives (PBMAs) are increasingly popular and may contribute towards reduction of negative environmental impacts associated with the meat industry. Inferior sensory characteristics of PBMAs, compared to conventional meat products, remain a barrier for uptake of these products. This study aimed to profile a wide range of PBMAs for perceived similarity to meat, consumer liking, emotional response and sensory experience, and to determine consumer drivers of liking for this product category.

Directed conservation of the world's reef sharks and rays.

Many shark populations are in decline around the world, with severe ecological and economic consequences. Fisheries management and marine protected areas (MPAs) have both been heralded as solutions. However, the effectiveness of MPAs alone is questionable, particularly for globally threatened sharks and rays ('elasmobranchs'), with little known about how fisheries management and MPAs interact to conserve these species.

Evaluation of deep oscillation therapy for the treatment of lumbar pain syndrome using motion capture systems: A systematic review.

Low back pain is a painful disorder that prevents normal mobilization, increases muscle tension and whose first-line treatment is usually non-steroidal anti-inflammatory drugs, together with non-invasive manual therapies, such as deep oscillation therapy. This systematic review aims to investigate and examine the scientific evidence of the effectiveness of deep oscillation therapy in reducing pain and clinical symptomatology in patients with low back pain, through the use of motion capture technology. To carry out this systematic review, the guidelines of the PRISMA guide were followed.

Potential rapid intraoperative cancer diagnosis using dynamic full-field optical coherence tomography and deep learning: A prospective cohort study in breast cancer patients.

An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specimen-consuming concerns. Here, we report a near-real-time automated cancer diagnosis workflow for breast cancer that combines dynamic full-field optical coherence tomography (D-FFOCT), a label-free optical imaging method, and deep learning for bedside tumor diagnosis during surgery.

The effect of hair removal and filtering on melanoma detection: a comparative deep learning study with AlexNet CNN.

Melanoma is the most aggressive and prevalent form of skin cancer globally, with a higher incidence in men and individuals with fair skin. Early detection of melanoma is essential for the successful treatment and prevention of metastasis. In this context, deep learning methods, distinguished by their ability to perform automated and detailed analysis, extracting melanoma-specific features, have emerged.

Confinement in fibrous environments positions and orients mitotic spindles.

Accurate positioning of the mitotic spindle within the rounded cell body is critical to physiological maintenance. Adherent mitotic cells encounter confinement from neighboring cells or the extracellular matrix (ECM), which can cause rotation of mitotic spindles and, consequently, titling of the metaphase plate (MP). To understand the positioning and orientation of mitotic spindles under confinement by fibers (ECM-confinement), we use flexible ECM-mimicking nanofibers that allow natural rounding of the cell body while confining it to differing levels.

AlpaPICO: Extraction of PICO frames from clinical trial documents using LLMs.

In recent years, there has been a surge in the publication of clinical trial reports, making it challenging to conduct systematic reviews. Automatically extracting Population, Intervention, Comparator, and Outcome (PICO) from clinical trial studies can alleviate the traditionally time-consuming process of manually scrutinizing systematic reviews. Existing approaches of PICO frame extraction involves supervised approach that relies on the existence of manually annotated data points in the form of BIO label tagging.

Infrared Spectroscopy of Synovial Fluid Shows Accuracy as an Early Biomarker in an Equine Model of Traumatic Osteoarthritis.

Osteoarthritis is a leading cause of lameness and joint disease in horses. A simple, economical, and accurate diagnostic test is required for routine screening for OA. This study aimed to evaluate infrared (IR)-based synovial fluid biomarker profiling to detect early changes associated with a traumatically induced model of equine carpal osteoarthritis (OA).