Phase Transitions in a Vanthoffite-Type Compound, NaZn(SO): Insights from PXRD and Raman Spectroscopy.

The study of phase transitions in minerals or synthetic compounds analogous to mineral structures is of fundamental interest in different scientific disciplines, with applications ranging from understanding the Earth's geological history to advancing materials science and technology. They provide valuable data and insight into developing new functional materials with desired properties. In this context, we have investigated the structural phase transitions of NaZn(SO), a synthetic compound analogous to the Vanthoffite mineral NaMg(SO), which occurs abundantly in nature as oceanic salt deposits.

The Fock-space landscape of many-body localisation.

This article reviews recent progress in understanding the physics of many-body localisation (MBL) in disordered and interacting quantum many-body systems, from the perspective of ergodicity breaking on the associated Fock space. This approach to MBL is underpinned by mapping the dynamics of the many-body system onto that of a fictitious single particle on the high-dimensional, correlated and disordered Fock-space graph; yet, as we elaborate, the problem is fundamentally different from that of conventional Anderson localisation on high-dimensional or hierarchical graphs. We discuss in detail the nature of eigenstate correlations on the Fock space, both static and dynamic, and in the ergodic and many-body localised phases as well as in the vicinity of the MBL transition.

Assessing the spatial scale of synchrony in forest tree population dynamics.

Populations of forest trees exhibit large temporal fluctuations, but little is known about the synchrony of these fluctuations across space, including their sign, magnitude, causes and characteristic scales. These have important implications for metapopulation persistence and theoretical community ecology. Using data from permanent forest plots spanning local, regional and global spatial scales, we measured spatial synchrony in tree population growth rates over sub-decadal and decadal timescales and explored the relationship of synchrony to geographical distance.

Maximizing Blue Energy via Densely Grafted Soft Layers in Nanopores.

We investigate energy generation from salinity gradients inside a nanopore that is connected to reservoirs at both ends. We consider that the inner wall surfaces are grafted with a densely grafted polyelectrolyte layer (PEL). We developed the PEL grafting density-dependent correlation of dielectric permittivity, molecular diffusivity, and dynamic viscosity in this endeavor.

(Re)packing Equal Disks into Rectangle.

The problem of packing of equal disks (or circles) into a rectangle is a fundamental geometric problem. (By a packing here we mean an arrangement of disks in a rectangle without overlapping.) We consider the following algorithmic generalization of the equal disk packing problem.

Auditory Spatial Perception as a Function of Recreational Noise Exposure in Gen-Z Adults with Normal Hearing.

The study aimed to evaluate auditory spatial perception in individuals with and without recreational noise exposure using Virtual Acoustic Space Identification. A standard group comparison design using purposive sampling was conducted on 60 normal-hearing participants aged 18-30. They were divided into experimental and control groups based on their scores on the recreational hearing habits questionnaire (CHAR).

Vegetation disturbance and regrowth dynamics in shifting cultivation landscapes.

Shifting cultivation, an age-old agricultural practice, is a major factor in forest cover change across Southeast Asia, where repeated cycles of vegetation disturbance and regrowth lead to far-reaching environmental and socio-economic impacts. The present study aims to assess the spatio-temporal patterns of vegetation disturbance and regrowth caused by shifting cultivation in Tripura state of India, over the past three decades, utilizing temporal segmentation of time-series Landsat data. The study analyzed vegetation disturbance and regrowth patterns in a shifting cultivation landscape from 1991 to 2020 using normalized burn ratio trends through LandTrendr, validated by the TimeSync tool.

Urban transformation of lakes and its impacts on a lake series: A case study of the yele mallappa shetty lake series Bengaluru, India.

The interconnected systems of lakes of Bengaluru, India, experience tremendous stress due to unsustainable urbanisation. Traditional lake-centric research approach struggles to capture and address this issue due to the cascaded nature of impacts in interconnected lake systems. Hence, this study assesses the impact of urbanisation on a lake series scale, focusing on the Yele Mallappa Shetty Lake series (YMSLS).

Cavity induced modulation of intramolecular vibrational energy flow pathways.

Recent experiments in polariton chemistry indicate that reaction rates can be significantly enhanced or suppressed inside an optical cavity. One possible explanation for the rate modulation involves the cavity mode altering the intramolecular vibrational energy redistribution (IVR) pathways by coupling to specific molecular vibrations in the vibrational strong coupling (VSC) regime. However, the mechanism for such a cavity-mediated modulation of IVR is yet to be understood.

Ultrasensitive Detection of Blood-Based Alzheimer's Disease Biomarkers: A Comprehensive SERS-Immunoassay Platform Enhanced by Machine Learning.

Accurate and early disease detection is crucial for improving patient care, but traditional diagnostic methods often fail to identify diseases in their early stages, leading to delayed treatment outcomes. Early diagnosis using blood derivatives as a source for biomarkers is particularly important for managing Alzheimer's disease (AD). This study introduces a novel approach for the precise and ultrasensitive detection of multiple core AD biomarkers (Aβ, Aβ, p-tau, and t-tau) using surface-enhanced Raman spectroscopy (SERS) combined with machine-learning algorithms.

Mark3D - A semi-automated open-source toolbox for 3D head- surface reconstruction and electrode position registration using a smartphone camera video.

Source localization in EEG necessitates co-registering the EEG sensor locations with the subject's MRI, where EEG sensor locations are typically captured using electromagnetic tracking or 3D scanning of the subject's head with EEG cap, using commercially available 3D scanners. Both methods have drawbacks, where, electromagnetic tracking is slow and immobile, while 3D scanners are expensive. Photogrammetry offers a cost-effective alternative but requires multiple photos to sample the head, with good spatial sampling to adequately reconstruct the head surface.

Mapping of drought-induced changes in tissue characteristics across the leaf profile of Populus balsamifera.

Leaf architecture impacts gas diffusion, biochemical processes, and photosynthesis. For balsam poplar, a widespread North American species, the influence of water availability on leaf anatomy and subsequent photosynthetic performance remains unknown. To address this shortcoming, we characterized the anatomical changes across the leaf profile in three-dimensional space for saplings subjected to soil drying and rewatering using X-ray microcomputed tomography.

CO variability over a tropical coastal station in India: Synergy of observation and model.

Carbon dioxide (CO), being the prime greenhouse gas, has largest contribution in radiative forcing and global warming due to increased anthropogenic emissions leading to regional and global climate change. We performed CO measurements using a continuous monitoring instrument at a tropical coastal station at the southern tip of India (Thumba; 8.54° N, 76.

An improved framework for mapping and assessment of dynamics in cropping pattern and crop calendar from NDVI time series across a heterogeneous agro-climatic region.

The absence of spatial and temporal cropping information in semi-arid regions poses a significant challenge in assessing the dynamics of agricultural systems at river basin scales. Satellite remote sensing provides qualitative and quantitative information to derive vegetation dynamics over extensive areas of inherent complexities due to limitations in the availability of field data and the diverse nature of agricultural cropping practices. Utilizing phenological information derived from MODIS Normalized Difference Vegetation Index (NDVI) time series data from 2003-2004 to 2021-2022, this study derives major crop types, and cropping calendar (sowing, maturity, and harvest dates) for each season and year at 250-m resolution.

Evaluating tree-ring proxies for representing the ecosystem productivity in India.

Terrestrial ecosystems are one of the major sinks of atmospheric CO and play a key role in climate change mitigation. Forest ecosystems offset nearly 25% of the global annual CO emissions, and a large part of this is stored in the aboveground woody biomass. Several studies have focused on understanding the carbon sequestration processes in forest ecosystems and their response to climate change using the eddy covariance (EC) technique and remotely sensed vegetation indices.

Cation effects and charge inversion contribute to the electrostatic stabilisation of protein bioconjugates in neat ionic liquids.

Dispersing and stabilising proteins in ionic liquids (ILs) provides significant opportunities for green solvent-based biocatalysis, especially in industrial processes at elevated temperatures. While unmodified proteins undergo denaturation, their polymer-conjugated counterparts have been stabilised in neat ILs. However, the nature of interactions and the generality of protein-bioconjugate stabilisation in neat ILs require further understanding.

Rationalised experiment design for parameter estimation with sensitivity clustering.

Quantitative experiments are essential for investigating, uncovering, and confirming our understanding of complex systems, necessitating the use of effective and robust experimental designs. Despite generally outperforming other approaches, the broader adoption of model-based design of experiments (MBDoE) has been hindered by oversimplified assumptions and computational overhead. To address this, we present PARameter SEnsitivity Clustering (PARSEC), an MBDoE framework that identifies informative measurable combinations through parameter sensitivity (PS) clustering.

Predictive Framework for Flow Reversals and Excursions in Turbulence.

We present a dynamical framework for intermittent reversals and excursions (R&Es) of large-scale circulations in turbulence. We show that R&Es can occur when turbulent trajectories in phase space shadow invariant manifolds of certain unstable periodic orbits (UPOs). Consequently, substantial flow reorganization and extreme fluctuations in flow metrics observed during R&Es can be reconstructed by splicing the unstable manifolds of such dynamically relevant UPOs.

Machine Learnable Language for the Chemical Space of Nanopores Enables Structure-Property Relationships in Nanoporous 2D Materials.

The synthesis of nanoporous two-dimensional (2D) materials has revolutionized fields such as membrane separations, DNA sequencing, and osmotic power harvesting. Nanopores in 2D materials significantly modulate their optoelectronic, magnetic, and barrier properties. However, the large number of possible nanopore isomers makes their study onerous, while the lack of machine-learnable representations stymies progress toward structure-property relationships.