11563 research outputs found
Sort by
Sustainably engineered pollen-derived carbon dots for efficient multi metal-ion sensing
No full textCarbon dots (CDs) derived from biomass have garnered considerable attention as an environmentally friendly alternative for metal ion detection. This study presents a novel approach for synthesizing CDs from natural pollen sources: Hibiscus rosa-sinensis (H-CDs) and Sphagneticola trilobata L. (S-CDs), for heavy metal ion detection. Using a rapid and scalable microwave-assisted method, the structural and optical characteristics of the synthesized CDs were examined using UV–Vis spectroscopy, X-ray diffraction (XRD), and Fourier Transform Infrared (FTIR) spectroscopy. High-Resolution Transmission Electron Microscopy (HRTEM) confirmed the quasi-spherical morphology and crystallinity, revealing an interlayer spacing of 0.32 nm and an average particle size below 15 nm. Fluorescence analysis revealed that S-CDs (quantum yield: 23.6 %) selectively detected Fe2+ and Co2+, while H-CDs (quantum yield: 21.3 %) targeted Fe2+ and Ni2+. The quenching mechanism involved both static and dynamic interactions. The detection limits were 0.22 ppm (Ni2+) and 0.24 ppm (Fe2+) for H-CDs, and 0.34 ppm (Fe2+) and 0.38 ppm (Co2+) for S-CDs. This is the first study on pollen-derived CDs for optical applications, demonstrating their potential as eco-friendly, sustainable and efficient metal ion sensors
An Overview of DC-DC Converter Topologies and Controls in DCM Microgrid
No full textDC Microgrid has a promising future due to its better compatibility with distributed renewable enerdyresources, higher efficiency and higher system reliability. This paper presents a comprehensive literature review of DC-DC Converters topologies used in DC Microgrids. The advantages and limitations of classical and recent converter topologies are discussed. The Hierarchical Control Strategies-Primary and Secondary controls have been reviewed. Primary control relies only on local measurements used for proper load sharing among converters. Secondary control is a coordinated control with some form of communication for additional functionalities. A brief note on protection and the key challenges faced in DC Microgrid operation have also been discussed. This paper gives a brief idea about the recent developments and overall operation of DC Microgrid
Durable Bio-Based Hydrophobic Recrystallized Wax Coatings
No full textBio-waxes derived from natural species are beneficial for preparing non-wetting surfaces. Herein, the wetting properties of recrystallized wax coatings extracted from three naturally occurring superhydrophobic species−, Lotus leaves, Bauhinia leaves, and Periwinkle flowers, are reported as a function of recrystallization time, temperature, pH of water, and impact pressure. Lotus wax coatings showcased nanorods similar to that of Lotus leaves, while Periwinkle and Bauhinia waxes could not replicate micro-/nanofeatures from their respective natural species. Lotus wax coatings exhibited water contact angles (WCAs) of ∼150°, roll-off angles (RAs) of ∼8°, and self-cleaning properties. On the contrary, both Periwinkle and Bauhinia waxes showed WCAs of only ∼110°. Nevertheless, all coatings demonstrated remarkable temporal stability over 180 days, retaining their hydrophobicity. They also exhibit excellent thermal stability up to 100 °C and chemical stability for pH variations from 2.6 to 11.5. Furthermore, they withstand the impact of 3000 water droplets without losing their hydrophobicity. All three wax coatings showed very low moisture absorption coefficients in the order Periwinkle (5.5 × 10-4 wt %/day) -4 wt %/day) -3 wt %/day), making them highly effective for moisture resistant applications such as food packaging, protective wood finishes, etc
Prediction of Lateral Capacity of Flexible Pile Group Subjected to Lateral Load in Sloping Ground for Prescribed Displacement
No full textTo understand the resistance of laterally loaded pile groups in a slope, an experimental 1 g model study and a finite element analysis study were conducted. The parameters varied were soil shear strengths, spacing between the piles, slope angles and various pile positions. The pile group were placed along the slope at a position related to relative stiffness from the crest of the slope. Additionally, finite element analysis was carried where the soil was modelled as a Mohr–Coulomb material, and the pile was represented as a beam element. With an increase in shear strength and spacing, the lateral resistance increases. It decreased with an increase in steepness of the slope and when it was placed away from the crest of the slope, compared to horizontal ground. The bending moment was high for lower consistency and spacing, and it was high for higher slope angles and larger stiffness factors. The depth of the maximum bending moment increased when the pile moved along the slope. From the parametric study conducted, a non-dimensional chart was proposed to estimate the lateral bearing capacity of the pile group along the slope
Dynamics of monitored SSH model in Krylov space: from complexity to quantum Fisher information
No full textIn this paper, we investigate the dynamics of a non-Hermitian SSH model that arises out of the no-click limit of a monitored SSH model in the Krylov space. We find that the saturation timescale of the complexity associated with the spread of the state in the Krylov subspace increases with the measurement rate, and late time behaviour differs across the PT symmetry transition point. Furthermore, extending the notion of this complexity for subsystems in Krylov space, we find that the scaling of its late time value with subsystem size shows a discontinuous jump across the PT transition point, indicating that it can be used as a suitable order parameter for such transition but not for the measurement-induced transition. Finally, we show that the measurement-induced transition can be detected using a generalized measure in the Krylov subspace, which contains information about the correlation landscape, such as Quantum Fisher information, which also possesses some structural similarity with the complexity functional
Speech Enhancement via Maximum Likelihood Modal Beamforming with Complex Gaussian and Laplacian Priors
No full textCapturing speech from a target source in the presence of interfering sources and noise using acoustic beamforming is an important processing tool for machine listening. When the target speaker can be at any location in the 3D space, spherical microphone arrays are desirable due to their ability to steer the beamformer towards any direction without affecting its directivity pattern. In this work, two beamformers based on the maximum likelihood estimation principle are introduced in the spherical harmonics domain. The first beamformer is designed by assuming that the coefficients of the target speech in the time-frequency domain at the beamformer output follow a zero-mean complex Gaussian prior distribution with time-varying variances. As speech coefficients are better modelled using Laplacian distribution, the second beamformer is designed by assuming a Laplacian prior for the target speech coefficients. To aid the capture of the desired speech, a distortionless constraint is also added to the formulation of both beamformers. The iterative update rules for the variances and the weights of both beamformers have been derived. Simulation results show that the proposed beamformers are more effective in target speech enhancement and distant speech recognition applications. � 2023 Elsevier B.V., All rights reserved
TLK1 as a therapeutic target in TMZ resistant glioblastoma using small molecule inhibitor
No full textThe acquired resistance to existing therapies poses a grave concern in achieving successful therapeutic outcomes. Temozolomide (TMZ), a widely used alkylating chemotherapeutic in Glioblastoma therapy, often encounters resistance, necessitating the investigation of the underlying mechanisms of TMZ-acquired resistance. To study TMZ resistance, a cell-based model system was generated by intermittently exposing glioblastoma cells to increasing concentrations and time of TMZ over six months. The survival response of cells at higher concentrations confirmed TMZ-resistant cells, which exhibited a phenotypic shift toward a mesenchymal-like state, with decreased epithelial traits, indicating mesenchymal-epithelial transition (MET). This transition likely facilitates the stabilization and clonal growth of TMZ-resistant cells. Subsequent analysis revealed elevated expression of TLK1, a DNA repair protein, thus reinforcing its potential involvement in mechanisms associated with acquired resistance. To explore the therapeutic aspect of TLK1 inhibition, we utilized an in-house developed TLK1 inhibitor, J54. The inhibition of TLK1 in TMZ-resistant cells enhanced cytotoxicity, indicating TLK1 as a potential target to combat TMZ resistance. Moreover, TLK1 inhibition reduced cell migration and invasion, implying its role in promoting metastasis. In conclusion, our study sheds light on the role of TLK1 in the context of TMZ resistance, highlighting its potential as a valuable target for therapeutic intervention
Strong influence of groundwater pumping on streamflow depletion across North India
No full textThe world’s largest freshwater resource - groundwater is essential for irrigation and food security. However, unsustainable groundwater pumping, exceeding recharge from precipitation, has led to significant groundwater depletion, particularly in intensively irrigated regions like north India, with cascading impacts on streamflow. Groundwater storage losses reduce groundwater discharge to streams, reverse flow directions, or cease discharge entirely, thereby reducing streamflow. Despite its critical implications on water security, ecosystem health, and agricultural sustainability, the relative influence of groundwater pumping and climate variability in driving streamflow variability remains poorly understood. Most previous studies often relied on coarse-resolution models that overlook groundwater-surface water interactions and lateral groundwater flow. To address these limitations, we applied the physically based, integrated land surface-groundwater model ParFlow-CLM at a 5 km resolution from 1970 to 2022 across the Ganga and the Indus basins. This physically based model simulates three-dimensional groundwater flow using the Richards equation and couples it with land surface processes, enabling robust analysis of groundwater-streamflow interactions. We find that streamflow variability in north India is primarily driven by groundwater abstraction for irrigation, modulated by precipitation variability. Excessive pumping has shifted streams from gaining groundwater to losing it, approaching critical environmental flow thresholds. The study underscores that prolonged groundwater pumping has significantly reduced baseflow contributions, which has critical implications for water management in India
Titanium diboride-derived nanosheets enhance the mechanical properties of polyurethane: experiments and simulation
No full textAlB2-type metal diborides have garnered significant attention in recent years owing to their ability to yield quasi-2D nanostructures. Titanium diboride (TiB2), a key member of the metal diboride family, is well known for its extraordinary mechanical properties. However, the candidacy of TiB2-based nanosheets to reinforce a polymer matrix has largely remained unexplored. In this work, we compare three kinds of TiB2 reinforcements - the bulk form, pristine nanosheets, and functionalized nanosheets, with respect to their prospects in the mechanical reinforcement of polyurethane (PU). We find that while all fillers lead to an improvement in the mechanical properties of PU, the composite comprising pristine nanosheets exhibits the most significant enhancement. A 2 wt% loading of pristine nanosheets results in ∼80% increase in the ultimate tensile strength and toughness. Detailed molecular dynamics simulations reveal that the TiB2 nanosheets are not only able to distribute the load effectively, but they also promote isotropic mechanical behaviour, which makes the composite stiff and strong. These insights are supplemented by inferences from the hydrogen bonding index (HBI) and degree of phase separation (DPS). This study exemplifies the rich prospects offered by the metal diboride-derived nanosheets for reinforcing polymer matrices
A note on dimensionality reduction in deep neural networks using empirical interpolation method
No full textEmpirical interpolation method (EIM) is a well-known technique to efficiently approximate parameterized functions from pointwise evaluations. This paper proposes to use EIM algorithm to efficiently reduce the dimension of the training data within supervised machine learning. This is termed as DNN-EIM. Applications in data science (e.g., MNIST) and parameterized (and time-dependent) partial differential equations (PDEs) are considered. The proposed DNNs in case of classification are trained in parallel for each class. This approach is sequential, i.e., new classes can be added without having to retrain the network. In case of PDEs, a DNN is designed corresponding to each EIM point. Again, these networks can be trained in parallel, for each EIM point. In all cases, the parallel networks require fewer than ten times the number of training weights. Significant gains are observed in terms of training times, without sacrificing accuracy