Rapid and low-cost diagnosis of COVID-19 is essential to identify the infected subjects, particularly the asymptomatic cases, primarily to arrest the spread of the disease through local transmission Antibody-based chromatographic serological tests, as an alternative to RT-PCR, offer only limited help due to high false positives We propose to exploit our field-deployable/portable plasmonic fiber-optic absorbance biosensor (P-FAB) platform for one-step, wash-free detection of SARS-CoV-2 virus particles directly in saliva sample with minimal sample pre-processing

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P-FAB: A Fiber-Optic Biosensor Device for Rapid Detection of COVID-19

Many complex systems, ranging from migrating cells to animal groups, exhibit stochastic dynamics described by the underdamped Langevin equation. Inferring such an equation of motion from experimental data can provide profound insight into the physical laws governing the system. Here, we derive a principled framework to infer the dynamics of underdamped stochastic systems from realistic experimental trajectories, sampled at discrete times and subject to measurement errors. This framework yields an operational method, Underdamped Langevin Inference, which performs well on experimental trajectories of single migrating cells and in complex high-dimensional systems, including flocks with Viscek-like alignment interactions. Our method is robust to experimental measurement errors, and includes a self-consistent estimate of the inference error.

Inferring the Dynamics of Underdamped Stochastic Systems

We demonstrate universal computation in an all-fluidic two-phase microfluidic system Nonlinearity is introduced into an otherwise linear, reversible, low-Reynolds number flow via bubble-to-bubble hydrodynamic interactions A bubble traveling in a channel represents a bit, providing us with the capability to simultaneously transport materials and perform logical control operations We demonstrate bubble logic AND/OR/NOT gates, a toggle flip-flop, a ripple counter, timing restoration, a ring oscillator, and an electro-bubble modulator These show the nonlinearity, gain, bistability, synchronization, cascadability, feedback, and programmability required for scalable universal computation With increasing complexity in large-scale microfluidic processors, bubble logic provides an on-chip process control mechanism integrating chemistry and computation

Microfluidic bubble logic

A wide range of geometrical deformations of fiber optic sensors (FOSs) have been explored to improve their performance. In particular, fiber optics bent into a U-shape present various advantages over other approaches and considerably improved performance in terms of sensitivity. The improvement in sensitivity can be understood as a result of the enhanced penetration depth of the evanescent field and higher evanescent power in the cladding or surrounding medium. Consequently, a larger portion of the propagating light experiences changes due to variations in the local refractive index (RI). In view of their significant benefits, U-shaped FOSs deserve a thorough investigation. This review outlines the theoretical model and design considerations along with the fabrication process of U-shaped FOSs. In addition, this paper aims to provide researchers with guidelines on the factors to consider in designing and optimizing U-shaped FOSs.

Theoretical Model and Design Considerations of U-Shaped Fiber Optic Sensors: A Review

A U-shaped double-side polished plastic optical fiber (POF) is demonstrated as a liquid refractive index (RI) sensor. The refractive index of glycerinum solutions is identified by the intensity detection on the bending and evanescent wave loss change. Heat treatment and mechanical polishing are adopted to form the symmetrical side-polished POF probe. The processing parameters are experimentally optimized on the power transmittance. The sensitivity of 1541%/RIU (Refractive Index Unit) can be obtained with a resolution of 5.35 × 10−4 in the scope of 1.33–1.39. The favorable temperature characteristic is proved to offer stable RI sensing from 20 to 50 °C. This simple POF sensor has potentials in low-cost visible light intensity RI detection.

https://www.mdpi.com/1424-8220/20/18/5253/pdf

Refractive Index Sensor Based on Double Side-Polished U-Shaped Plastic Optical Fiber.

We report on the dynamics of collective alignment in groups of the cichlid fish, Etroplus suratensis. Focusing on small-to-intermediate sized groups ($10<N<100$), we demonstrate that schooling (highly polarised and coherent motion) is noise-induced, arising from the intrinsic stochasticity associated with finite numbers of interacting fish. The fewer the fish, the greater the (multiplicative) noise and therefore the likelihood of alignment. Such empirical evidence is rare, and tightly constrains the possible underlying interactions between fish: computer simulations indicate that E. suratensis align with each other one at a time, which is at odds with the canonical mechanism of collective alignment, local direction-averaging. More broadly, our results confirm that, rather than simply obscuring otherwise deterministic dynamics, noise is fundamental to the characterisation of emergent collective behaviours, suggesting a need to re-appraise aspects of both collective motion and behavioural inference.

Noise-Induced Schooling of Fish

Geometrically modified fiber optic sensors (FOS), particularly U-bent FOS, have gained significant attention due to their remarkably high refractive index (RI) and evanescent wave absorbance (EWA) sensitivity, as well as their ergonomic design and ease in handling. In this article, we present a theoretical model for the U-bent FOS probes to predict the sensor behavior by numerically simulating the light propagation in an equivalent 2D semi-circular ring using ray tracing approach. In addition to the effects due to the modification of geometry, this article presents a thorough investigation of the influence of the bend-induced material deformation on the nature of light propagation and refractive losses. We introduce “bend ratio” (ratio of bend radius to fiber core radius) to explain the influence of geometry modification and the bend-induced inhomogeneity in RI (BIRI) of the fiber core on RI sensitivity. The bend ratio of bent plastic optical fiber sensors falls under one of the four bending regimes, namely, gentle, geometric, saturation, and plastic, for which the bend ratios are less than ∼35, ∼25, 17, and 7, respectively. The results also show that for bend ratios less than 7, BIRI inhomogeneity is responsible for the high RI sensitivity observed with U-bent probes as opposed to the simple geometric modification. This article also indicates the existence of an optimum bend ratio (for a given value of RI of the surrounding medium) where RI sensitivity is maximum. These findings were validated with previously reported experimental results.

Investigating the Refractive Index Sensitivity of U-Bent Fiber Optic Sensors Using Ray Optics

We report on the dynamics of collective alignment in groups of the cichlid fish Etroplus suratensis. Focusing on small- to intermediate-sized groups (10 ≲ N ≲ 100), we demonstrate that schooling (highly polarized and coherent motion) is noise induced, arising from the intrinsic stochasticity associated with finite numbers of interacting fish. The fewer the fish, the greater the (multiplicative) noise and therefore the greater the likelihood of alignment. Such rare empirical evidence tightly constrains the possible underlying interactions that govern fish alignment, suggesting that E. suratensis either spontaneously change their direction or copy the direction of another fish, without any local averaging (the otherwise canonical mechanism of collective alignment). Our study therefore highlights the importance of stochasticity in behavioural inference. Furthermore, rather than simply obscuring otherwise deterministic dynamics, noise can be fundamental to the characterization of emergent collective behaviours. Groups of fish tend to move in an organized fashion. Here the authors investigate the behaviour of schools of freshwater fish and find that schooling is induced by noise; the smaller the group size, the greater the noise and hence the greater the alignment.

Noise-induced schooling of fish

Geometrically modified fiber optic sensors (FOS), particularly U-bent FOS, have gained significant attention due to their remarkably high refractive index (RI) and evanescent wave absorbance (EWA) sensitivity, as well as their ergonomic design and ease in handling. In this study, we present a theoretical model for the U-bent FOS probes, to predict the sensor behavior by numerically simulating the light propagation in an equivalent 2D semi-circular ring using ray tracing approach. In addition to the effects due to the modification of geometry, this study presents a thorough investigation of the influence of the bend-induced material deformation on the nature of light propagation and refractive losses. We introduce bend ratio (ratio of bend radius to fiber core radius), to explain the influence of geometry modification and the bend-induced inhomogeneity in RI (BIRI) of the fiber core on RI sensitivity. The bend ratio of bent plastic optical fiber sensors falls under one of the four bending regimes namely, gentle, geometric, saturation and plastic, for which the bend ratios are less than 35, 25, 17 and 7 respectively. The results also show that for bend ratios less than 7, BIRI inhomogeneity is responsible for the high RI sensitivity observed with U-bent probes as opposed to the simple geometric modification. This study also indicates the existence of an optimum bend ratio (for a given value of RI of the surrounding medium) where RI sensitivity is maximum. These findings were validated with previously reported experimental results.

Investigating the refractive index sensitivity of U-bent fiber optic sensors using ray optics

We propose a modeling strategy to simulate drop movement in a two-phase flow inside a 2-D diverging–converging microchannel. These are planar channels that allow 2-D movement of drops. The increasing cross-sectional area of the diverging section decelerates the drop, and the decreasing cross-sectional area of the converging section accelerates it. These drops as they slow down approach each other and start to interact hydrodynamically and form 2-D arrangements inside the microchannel. We propose interacting drop-traffic models, that are phenomenological in nature, to characterize the different interactions of a drop with the neighboring drops, continuous phase and the channel walls. By incorporating these models into a multi-agent simulation, that employs Newton’s second law of motion along with the creeping flow approximation, we are able to predict the positions and velocities of all the drops inside the microchannel. The time evolution of the dynamic 2-D patterns formed by the drops inside the microchannel is investigated. We are able to qualitatively understand the features in a microchannel that aid the formation of the 2-D patterns. The simulation strategy helps us to understand the layering phenomena that results in the formation of the 2-D structures near the diverging section and the breaking patterns of drops near the converging section of the microchannel.

M. Danny Raj

Papers

Noise-Induced Schooling of Fish

Investigating the Refractive Index Sensitivity of U-Bent Fiber Optic Sensors Using Ray Optics

Noise-induced schooling of fish

Investigating the refractive index sensitivity of U-bent fiber optic sensors using ray optics

Understanding drop-pattern formation in 2-D microchannels: a multi-agent approach