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@inproceedings{bib_Brea_2025, AUTHOR = {Hitesh, Bhole Gaurav and C, Poorvi H and Ramachandran, Madhav Jayachandran and Krishnanunni, Vinod Palakkad and Bhimalapuram, Prabhakar }, TITLE = {Breast Cancer Subtyping with HyperCLSA: A Hypergraph Contrastive Learning Pipeline for Multi-Omics Data Integration}, BOOKTITLE = {Conference on Pattern Recognition and Machine Intelligence}. YEAR = {2025}}

Accurate molecular subtyping of cancer is crucial for advancing personalized medicine. Although multiomics data contain valuable predictive information, effectively integrating them is challenging domics sources, providing a robust framework for molecular characterizations-modal biological interactions. We propose HyperCLSA (Hypergraph Contrastive Learning with Self-Attention), a novel deep learning framework for efficient multi-omics integration in breast cancer subtyping. HyperCLSA combines hypergraph-based sample encoding, supervised contrastive learning for latent space alignment, and multi-head self-attention for adaptive fusion of omics modalities. Evaluated on The Cancer Genome Atlas Breast Cancer dataset (TCGA-BRCA) forPAM50 subtype classification, HyperCLSA achieves a state-of-the-art accuracy of 90.1%, significantly outperforming established baselines. Our results demonstrate HyperCLSA’s effectiveness in extracting complementary information across heterogeneous omics sources, providing a robust framework for molecular characterization of breast cancer.

@inproceedings{bib_The__2024, AUTHOR = {Gureja, Akshit and Hussain, Aftab M. and Viswanadh, Kandala Savitha and Walchatwar, Nagesh Laxman and Agrawal, Rishabh Anup and Sinha, Shiven and Chaudhari, Sachin and Vaidhyanathan, Karthik and Choppella, Venkatesh and Bhimalapuram, Prabhakar and Kandath, Harikumar }, TITLE = {The Engineering End-to-End Remote Labs using IoT-based Retrofitting}, BOOKTITLE = {IEEE Access}. YEAR = {2024}}

Remote labs are a groundbreaking development in the education industry, providing students with access to laboratory education anytime, anywhere. However, most remote labs are costly and difficult to scale, especially in developing countries. With this as a motivation, this paper proposes a new remote labs (RLabs) solution that includes two use case experiments: Vanishing Rod and Focal Length. The hardware experiments are built at a low-cost by retrofitting Internet of Things (IoT) components. They are also made portable by designing miniaturised and modular setups. The software architecture designed as part of the solution seamlessly supports the scalability of the experiments, offering compatibility with a wide range of hardware devices and IoT platforms. Additionally, it can live-stream remote experiments without needing dedicated server space for the stream. The software architecture also includes an automation suite that periodically checks the status of the experiments using computer vision (CV). The software architecture is further assessed for its latency and performance. RLabs is qualitatively evaluated against seven non-functional attributes - affordability, portability, scalability, compatibility, maintainability, usability, and universality. Finally, user feedback was collected from a group of students, and the scores indicate a positive response to the students’ learning and the platform’s usability.

@inproceedings{bib_A_la_2024, AUTHOR = {Zahra, Dr. Andleeb and Sinha, Swarnim and Modak, Alimpan and Siddiqui, Imran and Syed, Azeemuddin and Bhimalapuram, Prabhakar and Sau, Tapan Kumar and Kumar, Pawan and Abbas, Zia }, TITLE = {A label-free sensing of creatinine using radio frequency-driven lab-on-chip (loc) system}, BOOKTITLE = {Engineering Research Express}. YEAR = {2024}}

Skip to content IOP Science home Accessibility Help Search Journals Books Publishing Support Login Engineering Research Express Inclusive Publishing Trusted Science, find out more. Purpose-led Publishing, find out more. ACCEPTED MANUSCRIPT A label-free sensing of creatinine using radio frequency-driven lab-on-chip (loc) system Andleeb Zahra1, Swarnim Sinha2, Alimpan Modak3, Imran Siddiqui4, Azeemuddin Syed5, Prabhakar Bhimalapuram6, Tapan K. Sau7, Pawan Kumar8 and Zia Abbas9 Accepted Manuscript online 2 August 2024 • © 2024 IOP Publishing Ltd What is an Accepted Manuscript? DOI 10.1088/2631-8695/ad6ad5 DownloadAccepted Manuscript PDF Download PDF Article metrics 6 Total downloads Submit Submit to this Journal Permissions Get permission to re-use this article Share this article Article and author information Abstract This paper presents a promising avenue of Radio Frequency (RF) biosensors for sensitive and real-time monitoring of creatinine detection. Knowing creatinine levels in the human body is related to its possible association with renal, muscular, and thyroid dysfunction. The detection was performed using an Inter-Digitated Capacitor (IDC) made of copper (Cu) metal over an FR4 substrate. To demonstrate our methodology, we have chosen Phosphate Buffer (PB) as our solvent for making the creatinine solutions of different concentrations. Moreover, Assayed Chemistry Control (ACC), a reference control consisting of human serum-based solutions has been mixed with the different concentrations of creatinine in a ratio of 1:9 to spike the creatinine value in the ACC solution. The sensor has been designed using a High-Frequency Structure Simulator (HFSS) tool with an operating frequency of 2.53 GHz. Then the design is fabricated over the FR4 printed circuit board (PCB) and tested using a Vector Network Analyzer (VNA). However, the sensitive area of the IDC is introduced to grade 4 Whatman filter paper for the Sample Under Test (SUT) handling unit. The main advantage of using Whatman filter paper is that the uniform spreading of liquid reduces experimental error, and less volume is required for testing the sample. The principal idea implemented in the biosensor design is to track the shift in the operating frequency in the presence of different concentrations of creatinine mix in ACC solution with Phosphate Buffer (PB) solution as a reference.

@inproceedings{bib_An_i_2024, AUTHOR = {Agarwal, Samriddhi and Yerragudi, Shameer Basha and D, Naveen and Zahra, Andleeb and Bhimalapuram, Prabhakar and Syed, Azeemuddin and Abbas, Zia }, TITLE = {An inductor-less, cost-effective On-chip CMOS VNA for bio-molecule detection}, BOOKTITLE = {IEEE International Symposium on Circuits and Systems}. YEAR = {2024}}

Biomolecules play indispensable roles in all life processes, including disease development, so their accurate detection is critical to cell investigation, medical diagnosis, and treatment. Radio Frequency (RF) sensing has become a popular testing technique compared to traditional methods for biomolecule analysis, providing results in less time using less volume of samples. It allows rapid, sensitive, real-time measurements and label-free techniques. However, for taking the signals from biomolecules over the RF-based sensors we need to connect them with the Vector Network Analyzer (VNA) which is a bulky and costly device. To develop an RF sensing based a true lab-on-chip (LoC) device, the paper presents a fully integrated low-power less-area on-chip single port CMOS VNA designed in 65nm CMOS technology to detect the bio-molecule The proposed design works in a tunable frequency range of 0.5 GHz to 2.5 GHz, ensuring much higher precision. Using an RLC equivalent of an Interdigitated capacitor (IDC) sensor, a fully integrated architecture for detecting $S_{11}$ of the biomolecules has been introduced. A resistive bridge coupler is used for wideband operation with a directivity of 14.89dB up to 2.5 GHz. Also, a high-linearity LNA (low noise amplifier) is designed with a linearity of -13dB and a gain of 14dB. The LNA has a low NF of 3.21dB. The design occupies an active area of 0.01767mm^2 and consumes power of 41mW from a 1 V supply.

@inproceedings{bib_The__2023, AUTHOR = {Dutta, Shubhangi and Shrivastava, Manish and Bhimalapuram, Prabhakar }, TITLE = {The WEAVE 2.0 Corpus: Role Labelled Synthetic Chemical Procedures from Patents with Chemical Named Entities}, BOOKTITLE = {Pacific Asia Conference on Language, Information and Computation}. YEAR = {2023}}

Discovering new reaction pathways lies at the heart of drug discovery and chemical experimentation. A huge amount of drug reaction data lies in unannotated patent texts which are not machine readable. Reaction roles play an important role in analysing chemical pathways, and tracing chemicals through them, and while there is a vast body of chemical data available, the unavailability of reaction role annotated data is a blocker to effectively deploy deep learning methods for reaction discovery. This paper introduces a new dataset, WEAVE 2.0, obtained from chemical patents, along with full, manual, annotations of novel chemical reactions with reaction role information. We also provide baseline and state of the art models for chemical entity recognition from our raw dataset. Our dataset and associated models form the foundation of neural understanding of chemical reaction pathways via reaction roles.

@inproceedings{bib_Enha_2023, AUTHOR = {Mazumder, Annesha and Bhimalapuram, Prabhakar and Syed, Azeemuddin and Sau, Tapan Kumar }, TITLE = {Enhancement of Sensitivity of Radio Frequency Based Biomolecule Detection in the Presence of Gold Nanoparticles: A Feasibility Study}, BOOKTITLE = {International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization}. YEAR = {2023}}

In this work, the role of gold nanoparticles in enhancing the sensitivity of Radio Frequency based biomolecule detection is assessed. A facile, efficient and rapid microstrip patch antenna based sensor, resonating at 61.747 GHz is utilized for the analysis. Gold nanoparticles are placed in the vicinity of biomolecules, and the extent of improvement is studied under various conditions. In particular, different morphological variations and arrangements of gold particles are investigated. The results indicate that, in general, the presence of gold nanoparticles contributes towards sensitivity improvement. However, the amount of enhancement strongly depends upon the morphological features and arrangements of gold particles and varies within 5-65% for the scenarios studied in this case.

@inproceedings{bib_Role_2023, AUTHOR = {Mazumder, Annesha and Bhimalapuram, Prabhakar and Syed, Azeemuddin and Sau, Tapan Kumar }, TITLE = {Role of presence of gold nanoparticles onenhancement of RF biosensing sensitivity}, BOOKTITLE = {Engineering Research Express}. YEAR = {2023}}

In this work, we explore the enhancement of sensitivity of sensing of biomolecules using Radio Frequency (RF) based sensing, by utilizing gold particles. In particular, we investigate the impact of various parameters of gold particles such as shape, size and arrangements on enhancing sensitivity. The work uses a Microstrip Patch Antenna designed to resonate at 96.84 GHz. The sensor is facile, rapid and efficient, and uses sample volume of 17.5 nL. The results indicate that the presence of gold particles helps in improving the performance of RF sensors in detecting biomolecules. However, the extent of improvement depends on the properties of gold particles and is in the range of 30-80% for the different cases studied in this work.

@inproceedings{bib_Gene_2023, AUTHOR = {Shasya, Shikhar and Sharma, Shubham and Bhimalapuram, Prabhakar }, TITLE = {Generative schemes for drug design with shape captioning}, BOOKTITLE = {Journal of Chemical Sciences}. YEAR = {2023}}

We present three related schemes to generate novel molecules based on seed molecule; all the methods use as input the voxelized representation of the seed molecule to generate the SMILES representation of the novel molecule. At heart of these methods are two networks (a) a variational autoencoder that uses a Riemannian metric to encode the latent space of (hence named RHVAE) and can use pharmacophoric requirements as additional input for decoder and (b) attentive captioning network (a type of recurring neural network) that can efficiently focus, capture and use the ‘content’ of input to generate the SMILES output of novel molecules. We analyze the performance of the three proposed methods. We demonstrate the generation of meaningful new molecules, by generating shapes through an autoencoder network which can then be passed to our attentive captioning network, while requiring smaller data sets for training and retaining similar performance to existing state-of-art methods. Keywords. De Novo Drug Design; Chemical Modeling; Variational autoencoders, Attentive RNNs, Remannian

@inproceedings{bib_The__2023, AUTHOR = {Widom, B and Bhimalapuram, Prabhakar and Koga, Kenichiro }, TITLE = {The hydrophobic effect}, BOOKTITLE = {Physical Chemistry Chemical Physics}. YEAR = {2023}}

The thermodynamics of the hydrophobic effect, as measured primarily through the temperature dependence of solubility, is reviewed, and then a class of models that incorporate the basic mechanism of hydrophobicity is described. These models predict a quantitative relation between the free energy of hydrophobic hydration and the strength of the solvent-mediated attraction between pairs of solute molecules. It is remarked that the free energy of attraction being just of the order of the thermal energy kT may be important for the effective operation of the hydrophobic effect in proteins. Deviations from pairwise additivity of hydrophobic forces are also briefly discussed.

@inproceedings{bib_RF_s_2022, AUTHOR = {Mazumder, Annesha and Sau, Tapan Kumar and Syed, Azeemuddin and Bhimalapuram, Prabhakar }, TITLE = {RF sensor-based tracking of nanoparticle’s morphological and relative arrangement variations}, BOOKTITLE = {Microfluidics and Nanofluidics}. YEAR = {2022}}

This article explores the feasibility of utilizing an interdigitated capacitor (IDC) based RF sensor for studying nanoparticle properties. The parameters include their size, shape, thickness, and relative arrangement in aqueous media. The analysis is carried out using the CAD tool high frequency structure simulator (HFSS). We study the variation in properties of spherical, cubical, disc-shaped, and polyhedral gold nanoparticles. The change in the resonance frequency, resonance amplitude, and − 3 dB bandwidth is analyzed for each case. The findings show that the change in the IDC-based RF sensor’s resonance characteristics can be used to track the variations in morphology and arrangements of gold nanoparticles.

@inproceedings{bib_Mult_2022, AUTHOR = {Mazumder, Annesha and Syed, Azeemuddin and Sau, Tapan Kumar and Bhimalapuram, Prabhakar and BISWAS, ARUNANGSHU }, TITLE = {Multi-parameter RF based Characterization of NanoparticlesandBiomolecules}, BOOKTITLE = {IEEE Conference on Nanotechnology}. YEAR = {2022}}

In this work, we explore the use of Radio frequency (RF) based sensing in uniquely identifying nanoparticles and biosamples by utilizing multi-parameter characterization. Most conventional RF sensors suffer from an inability to perform proper identification due to the dependence of the methodology on a single parameter variation. This paper combats this drawback by proposing a technique that extracts multiple parameters from the frequency response of a narrow band, IDC based RF sensor for performing the analysis. Furthermore, to illustrate the method, the identification is performed for different samples, including Biotin, BSA-conjugated Biotin, Gold Nanorods and Silica-coated Goldnanospheres. The results indicate that multi-parameter characterization yields unique spectral signatures for all samples, and thus identification can efficiently be performed.

@inproceedings{bib_Insu_2022, AUTHOR = {Chaudhary, Yagya and Bhimalapuram, Prabhakar }, TITLE = {Insulin aspart dimer dissociation in water}, BOOKTITLE = {The Journal of Chemical Physics}. YEAR = {2022}}

The insulin hormone is stored in the hexameric form and dissociates to the dimeric form and finally to the active monomeric form. When insulin secretion is impaired, thereby affecting various metabolic processes, as a final response, insulin analogs are subcutaneously injected before meals to facilitate glucose metabolism. Depending on the molecular details, analogs are rapid or slow acting based on the dissociation rate of the dimer to monomer. Insulin aspart is a recombinant human insulin analog, acting faster than regular human insulin. Despite its practical and elementary importance, the process of insulin aspart dimer dissociation is relatively unknown. Here, we combined molecular dynamics simulations and umbrella sampling to characterize the energetic and structural features of dissociation of the insulin aspart dimer. Like previous studies on human insulin (another well studied analog), insulin aspart can also display a wide spectrum of pathways for dimer dissociation from dissociation happening without a major change in the monomer structure to dissociation that is coupled with unfolding of a protein. Additionally, water plays a vital role in the dissociation of the insulin aspart by stabilizing the monomers in the dissociated state. Our study shows the molecular details, such as the variation in the structure and orientation and conformational changes along the minimum energy pathways in the process of dissociation of the insulin aspart dimer.

@inproceedings{bib_Mult_2021, AUTHOR = {Mazumder, Annesha and Syed, Azeemuddin and Bhimalapuram, Prabhakar and Sau, Tapan Kumar }, TITLE = {Multi-parameter based Characterization of Biosamples using a Broadband Microstrip Patch based RF Sensor}, BOOKTITLE = {IEEE International Conference on Nano/Molecular Medicine and Engineering}. YEAR = {2021}}

In this study, we characterize biosamples using a microstrip patch based Radio Frequency (RF) sensor by integrating both resonant and non-resonant parameters. In particular, the resonance frequency, the resonance amplitude, −10 dB bandwidth, range of operation, and return loss at center frequency were employed to perform the analysis. The idea was to utilize multiple parameters to build a comprehensive understanding of different bio-samples. In order to demonstrate the working of the methodology, two sets of analytes were studied-(i) aqueous solutions of biomolecules and (ii) body fluids. For both sets of analytes, the method demonstrated significant efficiency in performing qualitative characterization.

@inproceedings{bib_Sepa_2021, AUTHOR = {Bhimalapuram, Prabhakar and Khare, Navya }, TITLE = {Separating classification and regression for faster exploration of phase space in (biomolecular) simulations}, BOOKTITLE = {Physical Chemistry Physical Biology}. YEAR = {2021}}

We present our work in using enhanced sampling method of metadynamics in combination with machine learning techniques to speed-up the exploration of all relevantphase space of biomolecular systems that keeps the two related tasks separate: (a) collective variable should cluster configurations into correct states, that is, classify states accurately and (b) collective variable should improve the local sampling in the ‘current free energy basin’, that is, shape the collective variable in line with the data collected (regression). We demonstrate the method on the alanine tetrapeptide system in explicit solvent. We use Elliptic Envelope (EE) classifier to identify outliers from a particular class, and each class will use a different fully-connected autoencoder (ANC) whose bottleneck layer (latent variable) will be used as collective variable in Well-Tempred Metadynamics simulation to generate more data. Comparison against benchmark indicate that the proposed scheme can traverse all relevant phase space

@inproceedings{bib_Stud_2021, AUTHOR = {PUNJANI, KASHISH and Bhimalapuram, Prabhakar }, TITLE = {Study of shape changes during nanoparticle growth using Kinetic Monte Carlo simulation: a case study on gold nanoparticles}, BOOKTITLE = {Journal of Chemical Sciences}. YEAR = {2021}}

In this paper, we develop a Kinetic Monte Carlo (KMC) based model to simulate the atomistic growth behavior of metallic nanoparticle in the solution of its ions and understand the growth pattern. KMC is used as it can model the growth of nanoparticle to the timescale comparable with that actual experiments. Energy minimas where metal atom can adsorb or surface diffuse have been found using Shrake–Rupley algorithm and conjugate gradient energy minimization algorithm. The rate of adsorption, desorption, and surface diffusion was artificially accelerated, and decelerated to observe different shapes. We demonstrate the model by a case study on growth of gold nanoparticles and find that shapes like the truncated octahedron, cuboctahedron, truncated cube, cube, rhombic dodecahedron, and sphere are seen to form by the model during the growth of NP. This KMC model provides a simplistic understanding of the mechanism and progression of shapes that may be seen during the growth of nanoparticle; these in turn may provide clues to synthesize NP of specific shapes.

@inproceedings{bib_Role_2020, AUTHOR = {Mazumder, Annesha and Syed, Azeemuddin and Sau, Tapan Kumar and Bhimalapuram, Prabhakar }, TITLE = {Role of Shape of Gold Nanoparticles in Sensing Biomolecules using Radio-Frequency based Sensors}, BOOKTITLE = {Sensors}. YEAR = {2020}}

In this paper, the role of the shape of gold nanoparticles in improving the efficiency of sensing of biomolecules using Radio Frequency (RF) has been studied. The analysis has been performed with the help of an Interdigitated Capacitor (IDC) based structure using the CAD tool, High Frequency Structure Simulator (HFSS). The frequency response and E-Field distribution of various shapes of gold nanoparticles have been analysed. The results indicate that the detection efficiency of RF sensing of biomolecules improves significantly in the presence of gold nanoparticles. The shape, as well as the position of biomolecules around the gold nanoparticles, affects the efficiency of detection. These results open up new avenues for developing highly efficient nanoparticle-Radiofrequency-based sensors.

@inproceedings{bib_Stud_2020, AUTHOR = {Mazumder, Annesha and Syed, Azeemuddin and Sau, Tapan Kumar and Bhimalapuram, Prabhakar }, TITLE = {Study of Gold Particles in HFSS with Varying Physical Parameters and Arrangements}, BOOKTITLE = {2020 IEEE 15th International Conference on Nano/Micro Engineered and Molecular System}. YEAR = {2020}}

Radio Frequency (RF) based sensors have shown great potential for the qualitative and quantitative analysis of different chemical and biological entities. In this work, the feasibility of performing RF based sensing by using gold particles has been explored with the help of the computational tool, HFSS (High Frequency Structure Simulator). The analysis is performed for an Interdigitated Capacitor based sensor. Various physical parameters of cylindrical gold particles such as radius and thickness have been varied, and the electrical parameters of the sensor systems have been studied. In particular, the reflection coefficients have been determined for various cases. In addition to the physical parameters, different configurations of the gold particles such as their linear and non-linear arrangements have been analyzed. The analyses offer promising results for the development of efficient sensing platforms.

@inproceedings{bib_Mach_2020, AUTHOR = {PATTNAIK, PUNYASLOK and Raghunathan, Shampa and TEJA, K TARUN and Bhimalapuram, Prabhakar and V, Jawahar C and U, Deva Priyakumar }, TITLE = {Machine Learning for Accurate Force Calculations in Molecular Dynamics Simulations}, BOOKTITLE = {Journal of Physical Chemistry A}. YEAR = {2020}}

The computationally expensive nature of ab initio molecular dynamics simulations severely limits its ability to simulate large system sizes and long time scales, both of which are necessary to imitate experimental conditions. In this work, we explore an approach to make use of the data obtained using the quantum mechanical density functional theory (DFT) on small systems and use deep learning to subsequently simulate large systems by taking liquid argon as a test case. A suitable vector representation was chosen to represent the surrounding environment of each Ar atom, and a -NetFF machine learning model where, the neural network was trained to predict the di↵erence in resultant forces obtained by DFT and classical force fields was introduced. Molecular dynamics simulations were then performed using forces from the neural network for various system sizes and time scales depending on the properties we calculated. A comparison of properties obtained from the classical force field and the neural network model was presented alongside available experimental data to validate the proposed method.

@inproceedings{bib_Dete_2018, AUTHOR = {Mazumder, Annesha and BISWAS, ARUNANGSHU and Sau, Tapan Kumar and Syed, Azeemuddin and Bhimalapuram, Prabhakar }, TITLE = {Determination of Critical Micelle Concentration of Surfactant Using RF Sensing}, BOOKTITLE = {Sensors}. YEAR = {2018}}

This paper utilizes RF Sensing to develop a facile methodology for the determination of Critical Micelle Concentration (CMC) of surfactants. The study is undertaken with the help of an Interdigitated Capacitor based RF Sensor. Due to change in permittivity, the sensor yields distinct resonant frequencies when introduced to solutions of varying concentration of Sodium Dodecyl Sulphate as the electrolyte. As the surfactant approaches micellization, the resonant frequency shift drastically alters, and this sudden transition is used to determine the value of CMC. The proposed technique estimates the CMC of SDS to be 6.5 x10 -3 M The introduced method is effective and less cumbersome as compared to traditional techniques.

@inproceedings{bib_Desi_2017, AUTHOR = {MURLIDHAR, PORWAL PRATIK and Syed, Azeemuddin and Bhimalapuram, Prabhakar and Sau, Tapan Kumar }, TITLE = {Design of fractal geometry based RF sensor for detection of complex permittivity of unknown sample}, BOOKTITLE = {IEEE Asia Pacific Microwave Conference}. YEAR = {2017}}

In this paper, RF resonant sensor is designed for measurement of complex permittivity of unknown sample. It takes advantage of peano curve fractal geometry (i.e. higher capacitance in minimum area). It operates in the ISM (industrial, scientific and medical) frequency band of 4-5 GHz. An empirical model of sensor is developed for the accurate calculation of complex permittivity of an unknown sample in terms of shifts in the resonant frequencies and reflection coefficients (S11) under loaded condition. Due to homogeneous E-field at fractal capacitor, placement position of sample will not affect the sensitivity. Significant frequency shifts as high as 60 M Hz, 80 M Hz, 116 M Hz and 134 M Hz are observed for relative permittivity of 5.4, 6.5, 8.9 and 10.6 respectively.

@inproceedings{bib_Desi_2017, AUTHOR = {MURLIDHAR, PORWAL PRATIK and Syed, Azeemuddin and Bhimalapuram, Prabhakar and Sau, Tapan Kumar }, TITLE = {Design of RF sensor for simultaneous detection of complex permeability and permittivity of unknown sample}, BOOKTITLE = {Progress in Electromagnetics Research C}. YEAR = {2017}}

DESIGN OF RF SENSOR FOR SIMULTANEOUS DETECTION OF COMPLEX PERMEABILITY AND PERMITTIVITY OF UNKNOWN SAMPLE

@inproceedings{bib_Dete_2017, AUTHOR = {MURLIDHAR, PORWAL PRATIK and Syed, Azeemuddin and Bhimalapuram, Prabhakar and Sau, Tapan Kumar }, TITLE = {Detection of ferritin concentration from blood sample using RF spiral inductor based cavity}, BOOKTITLE = {IEEE Asia Pacific Microwave Conference}. YEAR = {2017}}

In this paper, a novel microwave planar resonant sensor (using two spiral inductors) is designed and developed for detection of ferritin from the blood sample using non destructive technique. Due to concentration change of ferritin in blood, shift in resonant frequency arise. The frequency range of 15 GHz-16 GHz is used as it is effective for label-free analysis of ferritin. The sensor is designed using the full wave electromagnetic solver, HFSS 13.0, and an empirical model is developed for the accurate calculation of ferritin concentration in terms of shifts in the resonant frequency. Due to homogeneous H-field in spacing between two inductors, placement position of ferritin will not affect the sensitivity. Significant frequency shifts as high as 105 MHz, 192 MHz, 310 MHz and 655 MHz are observed for concentrations as low as 20 ng/ml, 50 ng/ml, 100 ng/ml and 320 ng/ml of ferritin respectively. Simulation results suggest …

@inproceedings{bib_Dete_2016, AUTHOR = {MURLIDHAR, PORWAL PRATIK and Syed, Azeemuddin and Bhimalapuram, Prabhakar and Sau, Tapan Kumar }, TITLE = {Detection of biotin-streptavidin interaction using RF interdigitated capacitive cavity}, BOOKTITLE = {IEEE MTT-S International Microwave and RF Conference}. YEAR = {2016}}

In this paper, biotin streptavidin interaction has been sensed at microwave frequencies with the help of designed sensor. It takes advantage of two pole filter topology where interdigitated capacitor (IDC) is used as a coupling zone between resonators for higher sensitivity. Due to permittivity change of biotin streptavidin combination, shift in resonant frequency arise whereas due to conductivity, magnitude of reflection coefficient changes. The frequency range of 10 GHz - 25 GHz (γ-dispersion region) is used as it is effective for label free analysis of biotin streptavidin. Due to homogeneous E-field between the fingers of IDC, placement position of biotin-streptavidin will not affect the sensitivity. Significant frequency shifts as high as 19 MHz, 45 MHz and 70 MHz are observed for concentrations as low as 10 ng/ml, 20 ng/ml and 30 ng/ml of biotin-streptavidin respectively. Simulation results suggest that proposed biosensor …

@inproceedings{bib_Impl_2014, AUTHOR = {DHANOA, GAGANDEEP SINGH and SHUKLA, MANISH KUMAR and Bhimalapuram, Prabhakar and Kothapalli, Kishore }, TITLE = {Implementation of Kirchhoff-Helmholtz transform on GPU for use in digital in-line holographic microscopy}, BOOKTITLE = {ACM India Computing Conference}. YEAR = {2014}}

GPUs with their massive Single Instruction Multiple Data (SIMD) capability have become attractive for scientific computation. The Kirchhoff-Helmholtz Transform (KHT) is a two dimensional integral commonly used in numerical reconstruction of the object from its experimentally measured diffraction pattern (called hologram). We explore the evaluation of KHT using GPU at various levels of optimisation. These optimisations are of two types:(a) algorithmic: exploiting the symmetries inherent in KHT, and (b) programmatic: optimizations that are specific to the GPU architecture like the lookup tables, scheduling of read/writes. From the numerical experiments, we report the speedup for each level of optimisation.

@inproceedings{bib_Mode_2010, AUTHOR = {Li, Ying and Bhimalapuram, Prabhakar and Dinne, Aaron R }, TITLE = {Model for how retrograde actin flow regulates adhesion traction stresses}, BOOKTITLE = {Journal of Physics: Condensed Matter}. YEAR = {2010}}

Cells from animals adhere to and exert mechanical forces on their surroundings. Cells must control these forces for many biological processes, and dysfunction can lead to pathologies. How the actions of molecules within a cell are coordinated to regulate the adhesive interaction with the extracellular matrix remains poorly understood. It has been observed that cytoplasmic proteins that link integrin cell-surface receptors with the actin cytoskeleton flow with varying rates from the leading edge toward the center of a cell. Here, we explore theoretically how measurable subcellular traction stresses depend on the local speed of retrograde actin flow. In the model, forces result from the stretching of molecular complexes in response to the drag from the flow; because these complexes break with extension-dependent kinetics, the flow results in a decrease in their number when sufficiently large. Competition between these

@inproceedings{bib_Mech_2010, AUTHOR = {Stewman, Shannon F and Jones-Rhoades, Matthew and Bhimalapuram, Prabhakar and Tchernookov, Martin and Preuss, Daphne and Dinner, Aaron R }, TITLE = {Mechanistic insights from a quantitative analysis of pollen tube guidance}, BOOKTITLE = {BMC plant biology}. YEAR = {2010}}

Background Plant biologists have long speculated about the mechanisms that guide pollen tubes to ovules. Although there is now evidence that ovules emit a diffusible attractant, little is known about how this attractant mediates interactions between the pollen tube and the ovules. Results We employ a semi-in vitro assay, in which ovules dissected from Arabidopsis thaliana are arranged around a cut style on artificial medium, to elucidate how ovules release the attractant and how pollen tubes respond to it. Analysis of microscopy images of the semi-in vitro system shows that pollen tubes are more attracted to ovules that are incubated on the medium for longer times before pollen tubes emerge from the cut style. The responses of tubes are consistent with their sensing a gradient of an attractant at 100-150 μm, farther than previously reported. Our …

@inproceedings{bib_How__2008, AUTHOR = {Li, Ying and Zhao, ong and Bhimalapuram, Prabhakar and Dinner, Aaron R. }, TITLE = {How the nature of an observation affects single-trajectory entropies}, BOOKTITLE = {The Journal of Chemical Physics}. YEAR = {2008}}

Projection of a Markov process with constant rates of transition to a small number of observable aggregated states can result in complex kinetics with memory. Here, we define the entropy production along a single sequence of aggregated states and show that it obeys detailed and integral fluctuation theorems. More importantly, we prove that projection shifts the distribution of entropy production over the ensemble of paths for a nonequilibrium process toward one characteristic of a system at equilibrium. This statement represents an analog of the second law of thermodynamics for path-dependent entropies and thus a new form of constraint of irreversible systems. Numeric examples are presented to illustrate these ideas.