This PDF file contains the front matter associated with SPIE Proceedings Volume 13108, including the Title Page, Copyright information, and Conference Committee information.

Digital holographic microscopy (DHM) is a label- free quantitative imaging technique to image and characterize translucent to transparent samples. It uses coherent principles of the light source for interferometric detection of transparent and semi- transparent samples. The coherence property of the laser source leads to speckles which often act as noise. Laser speckle contrast imaging is a non-destructive tool for full field mapping of flow in the field of view. It can be integrated with off-axis DHM for applications in optofluidics. This enables the mapping of flow within a microfluidic channel and quantifying the channel dimensions as well as the particles flowing through the channel.

This manuscript presents a novel method for the transformation of bulk aluminium metal powder into aluminium oxide nanoparticles in a liquid medium using pulsed laser irradiation. The process demonstrates high precision and control over the oxide formation, resulting in the production of nanostructured aluminium oxide particles. The synthesized material exhibits promising properties for applications in clad-modified fiber optic gas sensing due to its enhanced surface area, breakdown in particle size dimension and improved gas adsorption capabilities. The methodology outlined in this study provides a viable pathway for the development of advanced sensing materials with improved performance characteristics.

Laser Induced Breakdown Spectroscopy (LIBS) is an analytical method rooted in Atomic Emission Spectroscopy (AES). LIBS employs a short, intense laser pulse directed onto the sample's surface, generating a micro-plasma. The optical emissions from this laser produced plasma are then analyzed to ascertain both the elemental composition and concentrations of the sample. Qualitative and quantitative analysis using LIBS is tedious with conventional approaches. Over the past decade, LIBS elemental analysis integrating with machine learning algorithms have grown significantly. Among the conventional machine learning algorithms, Deep learning Neural Network (DNN) coupled LIBS is a promising analytical tool developed for the efficient compositional analysis. The simulation of optical emission spectra at laserproduced plasma conditions (T_e = 1 eV, Ne = 10¹⁷ cm^-3) allows obtaining synthetic spectra for training the DNN model for different concentration of elements for a range of plasma electron temperature and density. In this work, we have proposed a computational algorithm for simulating the optical emission spectra of different elements in the periodic table and thereby generating datasets (spectrum) needed for training the deep learning neural network models for elemental analysis. This study suggests that employing DNN-supported LIBS is a promising analytical tool for multi-elemental compositional analysis.

Metal nanostructures can cage the free space electromagnetic energy to subwavelength regime via excitation of surface plasmons on metal dielectric interface. The rich color of the metal nanostructures is attributed to light absorption in the vicinity of their resonant surface plasmon polariton (SPP) frequency. This absorption is diverse owing to multiple resonances in complex metal nanostructures and is sensitive to its shape, size, periodicity, and dielectric environment. By precise tailoring, these plasmon resonances can be tuned over the entire solar spectrum. Indebted to strong electric field confinement, these nanostructures are of utmost importance in fundamental research e.g., in Surface Enhanced Raman Spectroscopy (SERS), Fluorescence Enhancement etc. Expanding its horizons, metal nanostructures attract wide attention in the industrial domain and is used as high-end data storage devices, electrochemical and optical sensors. As light harvesters, they are extensively used in solar cells and photovoltaics. Many theoretical models and simulation studies have been carried out to explore these light matter interactions. Our work focusses on the fabrication of silver and gold gratings via Focused Ion Beam milling and tuning it to plasmon resonance of our interest. The polarization dependent reflectance measurements clearly demonstrate the excitation of surface plasmon propagating modes on the grating. We also modelled a similar structure in COMSOL Multiphysics incorporating important experimental aspects and will illustrate how angle resolved spectroscopic measurements can help us establish its Plasmonic Band Structure and mode number identification.

Globally, thyroid dysfunction, which includes disorders including hyperthyroidism and hypothyroidism, poses a serious health risk. Patients experience pain and annoyance as a result of the invasive procedures that are frequently used in conventional diagnostic approaches. In this context, the employment of non-invasive techniques like diffuse reflectance spectroscopy (DRS) shows significant promise. A wide spectrum of metabolic problems known as thyroid diseases are defined by deviations in thyroid hormone production and function. Regular assessments are necessary for precise diagnosis and ongoing monitoring of thyroid problems. Many existing diagnostic techniques involve invasive procedures that result in patient discomfort. Identifying non-invasive techniques for predicting thyroid-related parameters is a challenging endeavor. The primary objective of this study is to perform an analysis to evaluate the effectiveness of Standard Normal Variate (SNV) and Partial Least Square Regression (PLSR), in non-invasively predicting thyroid parameters using Diffuse Reflectance Spectroscopy. A cohort of 30 participants was recruited from SRMMCHRC (SRM Medical College Hospital and Research Center) with the approval of the Ethical Committee. These participants were instructed to relax and sit comfortably with informed consent while DRS light in the wavelength range of 550-1040nm was passed through their thyroid region non-invasively. The data was later compared with clinically observed blood tests. In terms of fitting the response variable and estimating Performance metrics, the PLSR (Partial Least Square Regression) model demonstrated an RMSE of 0.286 and 0.93 indicating its strong predictive capability for non-invasive assessment of thyroid parameters. In conclusion, the research showcases the potential of using SNV in combination with the PLSR regression model for the non-invasive assessment of thyroid patients.

In this study, we obtain the film characteristics like thickness, and roughness of bio and GO PVA films by a couple of locally developed optical techniques, speckle interferometry, and Doppler shifted optical coherence tomography The results were compared with the SEM cross sectional images The extracted thickness range compares favorably with those measured by SEM cross sections.

This paper introduces a novel blood sample analysis method utilizing a bio-photonic sensor based on a dual defect layer photonic crystal within a one-dimensional topological structure. This structure is constructed with alternating silicon dioxide (SiO2) and zinc oxide (ZnO) layers and evaluated with a transfer matrix approach. Integrating defect layers in the photonic crystal structure facilitates the creation of localized resonant modes, enabling the detection of specific components. Analyzing the transmission spectrum with incident light that is enabled by photonic crystals with defect layers can be used in biosensing applications. In this paper, the one-dimensional photonic crystals with dual defect layer structure are explored for the analysis of blood samples. The dual defect layer structure increases the sensor's capability to detect and measure specific biomarkers in terms of sensitivity, selectivity, and detection limits. This innovation holds promise for continuous health monitoring, diagnostics, illness detection, and label-free, real-time blood sample monitoring. The combination of photonic crystal structures and the transfer matrix approach provides an adaptable framework for developing and optimizing biosensors with potential applications in healthcare and beyond.

Diagnostic modalities that determine the extent of damage to peripheral nerve tissues that can happen in the case of burn injuries and skin cancer are significant for optical imaging. Optical coherence tomography (OCT) is a well-established imaging tool for ophthalmology, skin diseases and dental applications. Recently, the polarized optical coherence tomography (PS-OCT) technique has been used for nerve tissue imaging in ophthalmology. This technique involves slow and fast axis, which gives the phase retardation depending upon the birefringence of a the target material and provides information about tissue characteristics and thickness. Skin, dental tissue, and nerve tissue layers also show birefringence characteristics. In the present study, the imaging of the nerve tissues by the PS-OCT technique is proposed and demonstrated. Initially, the birefringence characteristics of a chicken nerve tissue were studied using a polarized light source with a wavelength of 532 nm and measuring the transmission characteristic through a rotating analyzer. The widening of the output intensity peak clearly indicated the birefringent nature of the nerve fiber. The PS-OCT setup was built using a polarizing beam splitter and quarter-wave plates. A superluminescent diode (SLD) with a wavelength of 1300 nm was used to image birefringent and non-birefringent samples along with the nerve tissue by PS-OCT setup. The spectral information of both polarization states confirmed the birefringence characteristics of the nerve tissue. Further studies are planned for nerve tissue imaging in a near-infrared region using a supercontinuum light source with a wavelength of around 1060 nm to increase the penetration depth during measurements.

Phosphates are inorganic complex compositions which finds applications in the field of light emitting devices , charge storage devices etc, due to their high thermal stability, relatively low sintering temperature, strong optical absorption, flexible compositions and less hygroscopic nature[1,2]. Yavapaiite structured SrTi(PO₄)₂ belongs to the double monophosphate family having general formula A^IIB^IV(PO₄)₂ ( A= Cd, Ca and Sr; B= Zr, Sn, Mo and Ti) get extensively studied for their applications in dielectric materials, catalysts and ionic conductors [3,4]. &Bull; Here we select Eu³⁺ as an activator ion to produce orange-red emission owing to its ⁵D₀→ ⁷F_J (0, 1, 2, 3 and 4) transitions. &Bull; Eu³⁺ incorporated red phosphors are widely used in white LED, display devices, forensic applications etc.

Neonatal jaundice is a common medical condition in newborns characterized by the yellowing of the skin and eyes because of increased levels of bilirubin in the blood. This condition is a result of the physiological breakdown of fetal hemoglobin and the immature liver's inability to efficiently process and excrete bilirubin. Although neonatal jaundice often appears benign, it can worsen and cause long-term neurological issues called kernicterus in some babies. Serum bilirubin testing, a traditional diagnostic approach, is often utilized to evaluate neonatal jaundice. This procedure is invasive, time-consuming, and occasionally associated with infections in newborns. On the other hand, Diffuse Reflectance Spectroscopy (DRS) has become an effective, non-invasive method for identifying and quantifying various biological chromophores. The assessment of tissue scattering and absorption characteristics over a wide spectral range, typically from UV to near-infrared, is the basic principle of the DRS approach. By analyzing the diffuse reflectance spectra, it becomes possible to extract valuable information about the concentration and distribution of chromophores in tissues. In this study, we used an optical approach to quantify the concentration of bilirubin in the neonates from the diffuse reflected signal of their skin. In comparison to SBR, it is found that it is viable to estimate the bilirubin concentration with a low margin of error as well as that it requires less time. This early diagnosis and non-invasive method might assist pediatricians in initiating further therapies such as phototherapy and exchange transfusion.

The usefulness of high absorbance in photodetectors, IR Imaging and thermal emitters, motivates us to trap light in the dielectric film The coupling between surface phonon polaritons at the air dielectric interface and surface plasmon polaritons at the metal dielectric interface results the strong confinement of the electric field in the dielectric film.

There are many applications that require compact spectrometers that yield results quickly. For example, farmers need to check the soil quality regularly by monitoring its nutrients (Nitrogen, Phosphorus, and Potassium, etc) . Also, it is necessary to test the quality of products like fruits, vegetables, and meat. Conventional laboratory analysis techniques are tedious and time-consuming. Near-infrared reflectance spectroscopy can analyze solid and powder samples without sample preparation by fingerprint molecular absorption. Diffuse Reflection (DR) contains information about the internal and external characteristics of the sample. Commercial NIR Spectrometers are expensive due to the use of linear array detectors that work in the IR region. The lack of domestic suppliers for such components also increases prices. In this work, we look at designing an inexpensive and compact optical system that can be used for diffuse reflectance near-infrared spectroscopy. The samples will be in powder form, requiring simple preparation, enabling ease of use. A Digital Micromirror Device (DMD) along with a single photodetector will be used in the spectrometer rather than a linear array detector. DMDs consist of an array of micromirrors. With suitable optics, they can be used to divert the diffracted spectrum to a single InGaAs photodiode. The NIR spectrometer design is based on the commercial detector active area with a 2 mm diameter and DMD dimensions of 5 mm in length. We describe how to choose the specifications of the grating and other optics in accordance with the detector's active area and DMD dimensions. The NIR spectrometer was designed to work in the spectral range of 1100 nm to 2400 nm with a spectral resolution of 2 nm.

Choroidal neovascularization (CNV) is a significant complication associated with age-related macular degeneration (AMD), particularly its "wet" or exudative form. In the context of AMD, CNV is the leading cause of severe vision loss and legal blindness. Detecting CNV can prove challenging, particularly in its early stages when symptoms may be subtle, or the abnormal blood vessel growth is minimal. Modern diagnostic tools, such as Optical Coherence Tomography (OCT) and Fluorescein Angiography (FA), have greatly improved our ability to diagnose CNV through comprehensive eye examinations. In this paper, we discuss the classification of normal and CNV affected retina optical coherence tomography (OCT) images, aiming to improve diagnostic reliability and assist medical professionals, working in the field of Ophthalmology. CNV is characterized by the growth of new choroidal vessels into the sub-retinal space through breaks in the Bruch's membrane. Our classification model combines image pre-processing, feature extraction, and image classification techniques. It leverages both traditional machine learning methods like Support Vector Machines (SVM), Random Forest, and AdaBoosting, as well as advanced deep learning architectures like Convolutional Neural Networks (CNN) and the highly regarded VGG16. After an extensive evaluation of model performance, the VGG16-SVM hybrid model emerged as the top performer, achieving an outstanding 99% accuracy rate and an equally impressive 99% precision rate. This result highlights the model's robustness and effectiveness in accurately categorizing images. The superiority of the VGG16-SVM hybrid model can be attributed to VGG16's proficiency in hierarchical feature learning. By combining the strengths of deep learning and traditional machine learning, the model harnesses deep networks' exceptional feature extraction capabilities and the robust classification power of Support Vector Machines (SVM). This synergy results in a more balanced and precise classification performance.

The nucleus plays a crucial role in regulating gene expression, DNA replication, DNA repair, and cell cycle progression. The nuclear envelope is a dynamic structure that separates the nucleus from the cytoplasm and regulates the nuclear import and export of molecules via the nuclear pore complexes. The present study seeks to investigate the kinetics of transport of negatively charged graphene quantum dots and FITC dextran through nuclear membranes and quantify their transport rates and translocation characteristics. Experiments are carried out in permeabilized HeLa cells using time-lapse confocal fluorescence microscopy. Introducing negative charge onto the molecules leads to electrostatic interaction with the nuclear pore complexes, resulting in significant changes in their transport rates. We find that the negatively charged graphene quantum dots and FITC dextran have two distinct nuclear transport rates while neutral FITC dextran shows only a single transport rate. The present study shows that the mechanism of nuclear transport is not only controlled by specific sequences such as nuclear localizing signal but is also affected by the presence of charge on the molecules. We propose a model of electrostatic interaction-based transport between negatively charged cargo and positively charged FG nucleoporins to explain the results. Export studies performed after nucleocytoplasmic import confirms the bidirectionality of transport.

The structural and photoluminescence studies of a series of Sr₂Ca_(1-x)TeO₆:xEu³⁺ phosphors synthesized through solid state reaction method were investigated in this work. The phosphor exhibits needle-like morphology which is advantageous for its use in photovoltaic cells and lighting applications. On exciting Sr₂CaTeO₆: Eu³⁺ phosphors with blue light (λ= 464 nm), the phosphors exhibit bright red emission at 615 nm, which corresponds to the transition of Eu³⁺ in Sr₂CaTeO₆ host, originating from ⁵D₀→⁷F₂ electric dipole transition. The optimum concentration of Eu³⁺ in this host is found to be 0.04 mol and the concentration quenching phenomenon is attributed due to dipole-dipole interaction of neighbouring Eu³⁺ ions. The calculated CIE coordinates of the prepared phosphors are similar to the NTSC red phosphor and commercial red phosphors. These results suggest that the Sr₂CaTeO₆:Eu³⁺ phosphors are potential candidate to incorporate in WLEDs as an excellent red emitting phosphor.

We present a theoretical proposal for an EP sensor utilizing a grating waveguide structure made up of silicon nitride(Si3N4). EPs are singularities where eigenfrequencies as well as eigenvectors coalesce. EP singularities demonstrate extraordinary sensitivity to small perturbations. Unlike conventional systems that respond linearly to perturbations, EP singularities exhibit square root dependence on small perturbations. Employing a finite element method-based numerical simulation using Comsol Multiphysics, we calculate the eigenspectrum of our structure. To confirm the presence of the EP, we examine the intensity profile along the grating, which exhibits a polynomial trend, contrary to the typical exponential behavior expected in lossy media. Moreover, we showcase the practical application of our optimized design by developing an ultrahigh sensitive refractive index sensor, capitalizing on the unique physics associated with EPs.

Over the last decade, there is upsurge of cervical cancer. Most of the cervical cancer cases (>90%) are the result of infection with high-risk human papillomaviruses (HPV). Two approaches for reducing the mortality rate are, Primary: HPV vaccination Secondary: testing and screening at early stages. There are different non-invasive or minimally invasive fluorescence as well as polarization based optical methods for early-stage screening of cervical cancer. The inherent fluorophores present in tissue imprint their characteristic signatures, reflecting corresponding changes in the average dipolar orientations when the light interacts with the tissue. Through the analysis of the interaction between polarized light and tissue, a comprehensive understanding of the complex structural and biochemical characteristics of the cervix can be obtained. The Fluorescence Mueller matrix (FMM) is ideally suited to extract the anisotropic information of excited and emitted states of fluorophores through the parameters, known as diattenuation and polarizance.

Label-free and non-invasive detection of ultrastructural morphology, classification of different types of spheroids and tissues, interaction of biomaterials with tissues, and osseointegration of living bones with implants at different stages, using nanosensitive optical coherence tomography (nsOCT) technique, are beneficial for the treatment planning in oncology, cardiology, dentistry and surgery, without the need for invasive biopsy procedures, requirement of contrast agents or ionizing radiation. In this work, OCT images were acquired from different ex vivo bovine biological tissues such as bone, muscle, fat, and skin using the SD-OCT system (GAN 611C1, Thorlabs), with a 930 nm superluminescent light emitting diode, with a bandwidth of 102 nm, and an axial resolution of 5.5 μm. Compared to a conventional OCT system which provides up to 1 μm axial resolution with a broadband supercontinuum laser source, nsOCT aids in the enhancement of axial resolution to nanoscale order. The characterization of spatial periods between 291 nm and 342 nm, for the wavelength range of 874 nm to 1027 nm, has been possible for different bovine tissues. A difference in the structural patterns in terms of spatial periods was observed between the hard and soft tissues. A definite nanostructural pattern was observed for hard tissues like the bone and burnt skin, whereas, soft tissues, fat, and muscle had an irregular pattern. This work can be further extended towards automated sub-micron level differentiation of healthy and malignant tissues, and also for bone-tissue engineering applications, using Deep Learning algorithms.

Background: Cervical cancer is a significant threat in low-income countries due to limited access to screening, resulting in delayed diagnoses and increased mortality rates. Multispectral imaging enables early detection of cancer by capturing images at multiple wavelengths to identify subtle alterations in cervical tissue. Objective: This work aims to develop a multispectral transvaginal imaging probe that illuminates the tissue with five different wavelengths of LED source namely, 450nm, 545nm, 575nm, 620nm, and white light for early diagnosis of cervical cancer in a low-resource setting. Methods: The probe consists of five pairs of LEDs and an endoscopy camera (Supereyes). The LEDs of different wavelengths are chosen based on the absorption peak of cancer biomarkers. The LED of 450nm matches the absorption peak of protoporphyrin and LEDs of 545nm and 575nm match the absorption peak of oxygenated hemoglobin and deoxygenated hemoglobin. The constant current supply is ensured by using LM317 in the LED driving circuit. Turning ON and OFF LEDs and the camera is controlled by Arduino and Raspberry Pi modules. The intensity ratio R610/R545 will give the extent of malignancy. Results: Multispectral imaging provides a more comprehensive view of tissues and structures. It is seen that intensity ratio R610/R545 tends to increase in case of malignancy. Conclusion: The visualization of the cervix using GynoSight is non-invasive and can provide real-time feedback to the clinician. It reduces the subjectivity often associated with visual examination.

Micronutrients are very essential substances required in regulating the normal human growth and development. Since the human body cannot produce sufficient micronutrients, these have to be supplied through the diet. Among the various micronutrients, zinc plays a vital role in regulating cell growth, metabolism, immune response and wound healing. Zinc micronutrient deficiency is common in most of the developing countries and majorly affects children resulting in stunted growth, cognitive impairment, chronic infections and illnesses [1]. The conventional diagnostic assay for zinc detection involves sophisticated instruments and laborious sample processing procedures [2]. In this proposed study, a point of care and label free biosensing technique is demonstrated for detection of zinc utilizing Surface enhanced Raman spectroscopy (SERS) through synergistic Raman signal enhancement from graphene gold nanocomposites. In order to enhance the intensity of Raman spectral peaks, graphene gold nanocomposite based SERS substrates are developed by simple drop casting technique. The Raman signal enhancement due to graphene gold nanocomposites is investigated in our earlier studies using COMSOL by the finite element method [3]. Herein, graphene gold nanocomposites are drop casted onto paper substrates and dried at room temperature to fabricate a flexible SERS substrate. Label free detection of zinc is achieved by coating zinc samples of different concentrations onto these substrates and the Raman measurement is carried out to investigate the characteristic Raman peaks of zinc molecules. Due to the vibration of OH-bond and stretching band of Zn-H2O, the characteristic peaks at 251 cm-1 and 328 cm-1 revealed the presence of zinc and the intensity of the peaks was increased by ~8.9-fold by graphene gold nanocomposites in comparison with the bare analyte. The proposed graphene gold nanocomposite could be employed for detection of zinc with the detection limit of 1 nM. Further, the study could be extended and optimized for automated diagnosis by investigating the inherent Raman spectral peaks and explored for real time detection of zinc in blood samples.

In today’s world, pesticides are often used in agriculture to reduce post-harvest losses due to contamination and increase productivity. Long term exposure of these pesticides in food lead to various health issues in humans and animals. An ultrasensitive detection of these pesticides traces in agricultural samples are currently in need. In this work, we have demonstrated a rapid, automated and ultrasensitive detection of organophosphorus pesticide in presence of citrate capped AuNPs, aptamer and cationic polymer Polydiallyldimethylammoniumchloride (PDDA). The instrumentation setup consists of an automatic reagent dispenser and a sample chamber associated with optical devices for absorption measurements. Electrostatic interaction between PDDA and aptamer prevents the aggregation of AuNPs whereas no such inhibition is observed in presence of aptamer specific pesticide, thus changing the colour of the AuNPs from red to blue. The limit of detection and the resolution of the developed equipment is 1pM and 500pM respectively.

The emerging field of Cavity-Optomechanics assisted by uniquely engineered structures named PhoXonic crystals is known for realizing strong microscopic interactions between the quasi-particles of light and sound. The PhoXonic interaction allows the additional control over the optical nonlinearities mediated by the additional mechanical strength. The phenomenon opens up a wide variety of applications where the need is to suppress the nonlinear optical losses as a result of poor mechanical strength, operating with longer infrared wavelengths in particular. In this work, we explore the potential of phoXonic crystals to realize ultra-low loss on-chip sensing platform with a multispectral response at midwave infrared wavelengths.

Despite significant strides in diagnosis and treatment, breast cancer remains a formidable health concern, underscoring the ongoing necessity for research. A study employing the polarized Monte Carlo approach has been conducted to investigate and pinpoint breast cancer. Utilizing the Mueller matrix derived from Monte Carlo simulations offers several advantages for diagnostic purposes, including enhanced contrast and the revelation of obscured details. This investigation focuses specifically on scenarios where malignancy is intertwined with normal breast tissue.In addition to its binary classification distinguishing between normal and abnormal conditions, the study presents an additional benefit: pinpointing the center of malignancy in nine specific spatial positions relative to the point of illumination. This offers a means to locate the tumor, even if it is not precisely within the directly illuminated area. The integration of deep learning techniques into a system enables automation and facilitates real-time diagnosis. This research aims to demonstrate the simultaneous detection of both the presence and location of the tumor through Convolutional Neural Network (CNN) implementation on depolarized index images derived from polarized Monte Carlo simulations. The CNN model achieves a classification accuracy of 96%, highlighting its superior performance.

Turn-on time delay of an incoherently fed back semiconductor diode laser is numerically investigated in this work. We have specifically investigated the turn-on delay after one, five, ten and fifteen round-trips. An external mirror is kept at a distance longer than the coherence length of the laser to provide incoherent optical feedback to the semiconductor diode laser. Lang- Kobayashi rate equations for incoherent optical feedback are used for simulations. Incoherent optical feedback to a diode laser results in four regimes. They are stable (regime I), chaotic (regime II), pulsed (regime III) and the two-state (regime IV) regime. Understanding of the turn-on delay after periodic round-trips will be useful in achieving better laser stability which is crucial for secure optical communication. The turn-on time delay after one and five round-trips is found to show a similar pattern with the effect of incoherent feedback. Whereas, a different but similar pattern of turn-on time delay is observed after ten and fifteen round-trips. In regime IV, the turn-on delay after one and five round-trips is found to be complimentary to the turn-on after ten and fifteen round-trips. Thus, it is found that the turn-on time delay of a diode laser subject to incoherent optical feedback is dependent on the external mirror feedback strength as well as the round-trips.

Cervical cancer ranks as the fourth most prevalent cancer globally, emphasizing the critical need for early detection, which is vital for effective treatment. Traditional diagnostic methods have shown limitations in detecting the progression of the disease. Optical techniques, known for their high sensitivity and specificity, are emerging as reliable tools, especially in cancer-related applications. Among these techniques, fluorescence spectroscopy is one of the highly sensitive approaches for identifying biochemical changes that occur during the advancement of cancer. In our study, fluorescence spectral data was collected from human cervix from a diverse group of individuals using a portable smartphone-based fluorescence spectroscopy device. The spectral signals were processed by initially breaking them down into Fourier Bessel series (FBS) coefficients. Subsequently, the Hessian locally linear embedding (HLLE) based dimensionality reduction method was applied to the FBS coefficients, followed by the implementation of a 1D convolutional neural network classifier. The combination of polarized fluorescence spectra acquired from the device and the proposed classification approach has shown promising results, thus it is proven to be a minimally invasive method with the capability to provide real-time diagnoses for patients

Here in our poster we demonstrate an efficient method of synthesizing MoS₂ nanoflakes using a liquid phase exfoliation technique induced by ultrasonication. The effect of adding the alkali metal [Na+] ions to the process is also shown in detail. The differences between the two samples created with and without the addition of alkali metal ions are clearly visible in the recorded images of the samples using Transmission Electron Microscopy (TEM) technique and in their optical characterization, utilizing the absorption and photoluminescence (PL) spectra of the respective samples. The TEM images chiefly concentrate on the structural differences between the samples, clearly revealing a better yield of the nanoflakes on using the alkali metal ions in the synthesis. The recorded PL spectra of the samples display a very unique property of excitation wavelength dependent fluorescence exhibited by the nanoflakes synthesized in an alkaline environment. This property is in close resemblance to the behaviour of MoS₂ Quantum Dots. So on one hand, the addition of Na+ ions boosts the exfoliation efficiency and on the other hand it improves luminous quality of the sample. Hence the MoS₂ nanoflakes synthesized using this method can be employed in a variety of optoelectronic and light-emitting devices. The excitation dependent fluorescence feature can be employed to create futuristic multicolour display devices, sensors, and lasers.

Blood pressure (BP) is a bio-parameter that can directly indicate hypertension and the health complications following it. Traditional methods of measuring blood pressure involve cuff-based measurements (manual or digital sphygmomanometers), which can only take place when the patient is at rest, and each measurement takes about 2-3minutes. Also, BP cuffs are not one-size-fits-all, making them non-inclusive. Recent advancements resulted in a number of devices for continuous measurement of bio-parameters, such as heart rate (HR), heart rate variability (HRV), respiration rate (RR), BP, etc. In this paper, the design of a continuous monitoring of Blood pressure device is proposed that solely uses photoplethysmogram (PPG) signals. The proposed design uses a support-vector regression model (SVR) model to predict blood pressure with PPG wavelets as input, that enable real-time and computationally efficient prediction of BP. Simulation results show that the proposed model predicts the for systolic BP (SBP) and diastolic BP (DBP) with mean absolute error 5.3 ±3.7 mmHg and 13.4±2.1 mm Hg respectively.

The average intensity equation of the Sine hyperbolic Gaussian vortex beam (ShGvB) in oceanic turbulence is derived using the extended Huygens-Fresnel integral. The vortex beam will unavoidably widen as it moves through the turbulence of the ocean, eventually reaching a beam size that differs from the source plane. The adaptive optics technique can be employed in underwater optical wireless communication to correct wavefront distortions caused by oceanic turbulence. The average intensity, average transmittance, beam spread and BER is quantified with and without adaptive optics. The results show that the ShGvB propagation through underwater turbulence can be improved by incorporating adaptive optics correction with improved BER.

Integrated Optic waveguide-based sensors are promising solutions for various applications, notably in the label-free detection of chemical and biological substances. For optimal sensitivity, the guided mode should interact with biomaterial. In this proposed work, we have considered Hollow-core waveguides and Strip waveguide-based biosensors. Hollow-core waveguides are analyzed as optofluidic devices in which bio-analytes form the core. Guiding light within a hollow-core optofluidic waveguide involves confining it to a region of higher refractive index, enclosed by cladding material of lower refractive index. Strip waveguide - Silicon on Insulator (SOI) has been considered for simulation purposes. Bulk sensing and Surface sensing scheme mechanisms were used to study the variations when bio analyte was encountered with waveguide material. In this article, we have modeled, simulated, and analyzed two types of waveguides viz., Optofluidic channel with biomaterial as core, bulk sensing with biomaterial as clad covering the Silicon strip waveguide, and surface sensing with biomaterial covering the surface of the waveguide. Optofluidic channel with sensitivity in the range of 2.4*10 -2 /RIU to 2.8*10 -2 /RIU; Bulk sensing sensitivity in the range of 2.5*10 -1 /RIU to 3.7*10 -1 /RIU; Surface sensing sensitivity in the range of 1.96*10 -2 /RIU to 2.9*10 -3 /RIU for different biomaterials. We here observed results and limitations for design guidelines. Our findings would assist in choosing an appropriate platform and optimizing sensitivity by the effective refractive index for the given bio applications

Hyperspectral imaging (HSI) systems provide non-destructive and high-resolution analysis in agriculture, healthcare, food safety, and industry-related problems. Despite its numerous advantages, HSI faces challenges due to large data generation, high computational power demands, and complexity in real-time monitoring due to redundancy in acquired data. There is an increasing demand to develop a less complex system for non-destructive analysis for various applications. On the same note, this study presents a potential solution for reducing the redundant information from the acquired data. The idea was investigated on HSI signals obtained from gongura (Hibiscus sabdariffa), amaranthus (Amaranthus viridis), and banana (Musa acuminata) leaves with two hundred four wavelengths and identifying the signature wavelengths to classify leaves. Twenty of the two hundred-four wavelengths were selected as signature wavelengths based on the importance scores obtained from the linear discriminant analysis (LDA). These signature wavelengths lie in the visible range of the electromagnetic spectrum. Afterwards, these twenty wavelengths were employed for further experimentation. The current study utilized extra tree classifiers (ETC), random forest (RF), and LDA classifiers for leaf classification. The ten-fold cross-validation findings indicated that LDA performed well among the other classifiers for full-range and signature twenty wavelengths. The promising results demonstrated the effectiveness of signature twenty wavelengths for the classification of leaves applications. Furthermore, these signature wavelengths also open the door to developing a low-complexity HSI system for future studies. Also, the robustness of the model can then be increased by utilizing large amounts of data.

Solar energy is the cleanest and most abundant renewable energy source on earth, and has been gaining a lot of attention in recent years. In this work, Solar Sun tracker was setup using Arduino UNO®, and its simulation study was done using MATLAB Simulink®. A solar tracker positions the solar panels perpendicular to the sun and follows the sun's path, ensuring optimal incident sunlight on the panels throughout the day. Proposed single-axis tracking design could enhance the energy generation efficiency by about 35%. Experimental solar tracker system was assembled with Arduino UNO® microcontroller, Servo-motor and Light Dependent Resistor’s (LDR). Based on light intensity readings from LDR’s, Arduino® calculates the sun’s position relative to the panel’s orientation. The servo motor then adjusts the angle of the solar panel to maintain perpendicular orientation with respect to sun. The automated sun tracker system gave constant maximum value of voltage throughout the day. In simulated model, the input data were Sun position and Solar Irradiance, based on which Proportional Integral Derivative (PID) feedback motor controller positioned the solar panel. The sun position data were obtained from the National Solar Radiation Database for the GPS Coordinates. As the global demand for sustainable energy solutions intensifies, the world is moving towards large-scale solar deployment. This study also explores recycling processes for end-of-life solar photovoltaic (PV) system to reclaim valuable metals, reducing environmental impacts of mining, processing and refining new raw-material. Utilizing repurposed waste materials in PV cooling is found to improve panel efficiency by about 12%.

The handheld optical imager utilizes 660 nm and 940 nm dual wavelength LEDs and photodetectors. There are four sources, each followed by three detectors and arranged equidistant from one another. A switching circuit was implemented using a 555 timer in astable mode to facilitate the switching of the LED at the aforementioned wavelengths. To acquire data, the rectangular-shaped scanner was kept on a volunteer's palm and moved towards the tip of the finger. At each position of the imager, red and near-IR radiations were sent through the tissue, and the detectors received backscattered radiation. The current signals obtained from the photodiodes were converted into voltages using a trans-impedance amplifier and read into the computer using NI-DAQ in twelve parallel channels. Using Beer-Lamberts law, the attenuation coefficient was calculated and displayed as images. These images show the difference between bony structures and other tissue in the fingers. The distal and proximal phalangeal joints appear lower in intensity in comparison to the bony structure of the finger. The oxygen saturation map of the scanned area was also obtained. Subjects with arthritic conditions have inflamed joints. The arthritic joints are sensitive to changes in oxygen saturation. Therefore, the imager could distinguish between normal and inflamed joints and be a screening tool for arthritis. The FWHM values are calculated to validate the obtained results.

Photoplethysmography signals are universally accounted for in healthcare units due to their non-invasive nature and effectiveness. They are used to calculate heart rate, heart rate variability, and other parameters. The PPG field is moving from the traditional setup to acquire the data with the help of LED and photodetector to image-based data acquisition with the help of cameras called i-PPG signals. This study aims to compare PPG with i-PPG signals captured using a smartphone's front camera, especially in calculating heart rate and its variability. Five healthy volunteers participated for this purpose. The reference value of the volunteers’ heart rate was obtained using a commercially available standard pulse-oximeter and Omron BP monitor. PPG signals were collected using a red LED with a wavelength of 660nm in the circuit built with the MAX30102 sensor. Finally, i-PPG signals were recorded as the videos of the right index finger were captured for the duration of 2 minutes for the analysis. Data was recorded in a calm and quiet environment otherwise interference will be observed in the signals. Videos were converted into i-PPG signals, and then both signals (i-PPG and PPG) were pre-processed to remove baseline drift. The heart rate series of both signals was obtained by calculating the time interval between adjacent peaks and multiplying its inverse by 60. The heart rate variability series was also calculated by taking the difference between two adjacent beats per minute values in the heart rate series. The heart rate obtained from the sensor circuit built has a positive correlation of 0.98, 0.99 and i-PPG signals have a positive correlation of 0.91 and 0.98 with reference methods on par with the values obtained from the pulse oximeter. It is significant to note that there were fluctuations while obtaining reference heart rate values.

Fluorescence spectrum of pyrene molecule in solution form has been of interest in the research community for more than six decades. Sensitivity of these molecules to solvent polarity makes them active probes for sensing impurities. Pyrene molecules when excited form an excimer complex with another molecule in the ground state, typically by the pi - pi orbital interaction. Fluorescence of these excimers are red shifted and results in structureless broad emission band. Pyrene is well-suited for studies on biophysical phenomena like lateral diffusion, inter or trans-bilayer movement of lipid and lateral organization of membranes. Microcrystals of aromatic compounds, such as perylene, coronene, anthracene and pyrene suspended in aqueous solutions, have been found to exhibit anomalous fluorescence spectra different from those of bulk. Our group has previously reported that the fluorescence spectra of single microcrystals are distinctly different from those of excimer emission but are similar to those of the crystalline thin film. In this work, we have used surfactant assisted self-assembly method to recrystallize nano-micro crystals of pyrene. We have undertaken this study in view of the recent investigation that reports excimer formation in nanocrystals. It has been found that while within the absorption band corresponding to the monomer, the excimer emission is dominant, higher aggregates continue to contribute due to excitation into the absorption tail of the nano-micro crystalline pyrene. By doping the synthesized microcrystals on polymer microcavities, whispering gallery modes (WGMs) were observed. WGMs find potential applications in sensing of several physical quantities like size, refractive index, pressure, temperature.

MoS₂ film shows layer-dependent nonlinear absorption behavior on interaction with ultrafast laser pulses [1]. This makes it a promising materials for use in laser mode-locking. Gold nanoparticles (AuNPs) are known to amplify the near field light owing to the surface plasmon resonances [2]. The change in the nonlinear absorption with the thickness of MoS₂ film has been investigated. Moreover, the nonlinear optical behavior of MoS₂-AuNPs hybrid systemhas also been compared to pristine MoS₂.

The spatial coherence function has proven to be a highly effective tool for light field manipulation. Although there has been considerable research on the spatial statistics of light, further exploration is needed to understand the phase variations within the coherence function. This study employs theoretical analysis and experimental investigations to gain insights into the phase modulations of far-field spatial coherence that are solely due to the modulations of the spatially incoherent source. We could modify the phase of the coherence function at different rates between different pairs of points without changing its magnitude. A square-wave amplitude grating is used and moved parallel to its plane to modulate the source intensity distribution. The proposed scheme is experimentally verified using a common-path Sagnac radial-shearing interferometer. This source-modulated phase shift technique has potential applications in optical interferometry schemes that employ incoherent light.

This study investigates the development of a blood-mimicking fluid for applications in optical imaging and characterization. Intralipid, a scatterer commonly used to mimic biological tissue, is explored for its ability to replicate the optical properties of blood. Diffuse reflectance spectroscopy, a technique measuring reflected light was employed to analyze intralipid solutions at varying concentrations (1% - 10%). Concurrently, Monte Carlo simulations were conducted to model light scattering behavior within the intralipid. The findings suggest that intralipid concentrations can be adjusted to mimic the diffused reflected light signature of either oxygenated or deoxygenated blood at the chosen wavelengths. This signifies the potential of intralipid as a substitute for blood in various optical studies, offering a valuable tool for characterizing biological tissues in spectroscopy and imaging applications.

Cognitive decline impact various aspects of lifestyle including sleep. Though there are many way to enhance cognitive skills, meditation has shown promising impact on neural system. This study uses photic meditation for a brief period over 40 healthy volunteers. They are divided into two groups: a non-photic group practicing traditional meditation and photic group in a specially designed setup. Brain signals are recorded before and after intervention by exercising digit span test, Stroop test and Wisconsin card sorting test. After pre-processing brain signals continuous wavelet transform (CWT) is used to compute energy distribution. The study results indicate that the energy concentrated shortly before the intervention is evenly distributed during the testing period following the intervention. Specifically red and green lights shows a better responses in enhancing the cognitive parameters which is also cross validated using paired t-test and perceived stress scale (PSS) score. Thus the proposed method would help in improving specific cognitive skills.

21st century witnessed tremendous progress in the application of Photonics, one of the prominent being lighting industry. The automotive lighting, among various categories of lighting, received immense growth. The lamps which have once been mere candles or lanterns now comprise of several components strategically packed into various sizes, shapes tailored to add unique aesthetics to the vehicle. The current day lamps are not only complex in the structural aspect but also in the end functionality making (night) driving experience dynamic, smart, and safe. For several years such intelligent systems were mere R\&D, marketing ideas but the recent changes in legal regulations, (including the recent approval for AFS in the US) made ‘AFS’, ‘ADB’, ‘Grill lighting’ etc. conventional on the latest vehicles around the world. These rapid transitions, together with the continuous advancements in electronics sector, manufacturing technologies, and automotive qualified materials make the new generation lighting system designs more challenging, competent. In this article, we attempt to provide an overview of some of the current day challenges the lighting designers are encountered with. We present the challenges associated with the development of ‘Efficient High Power Lighting System’. The state of the art market demands of such systems, some of the key limitations of the current design solutions are outlined in this article.

Ever increasing demand for high-capacity and low-bit-error-rate optical communication networks has become imperative with the pervasive use of data-intensive applications such as social networking, cloud computing, and high-definition digital services. This research paper introduces a novel approach to enhance optical communication performance by a Modified Orthogonal Frequency Division Multiplexing system with Relational Reconfigurable LDPC Decoding. This system integrates Asymmetric Clipped Optical Orthogonal Frequency Division Multiplexing (ACO-OFDM) and DC-biased Optical Orthogonal Frequency Division Multiplexing (DCO-OFDM) with Multi-Layer Modulation (MLM) to fulfil the high channel capacity requirements of next-generation access networks. A key feature of this work is the development of a non-binary Relational Reconfigurable Low-Density Parity Check decoding method to effectively identify and correct errors. The proposed system is rigorously evaluated and compared to existing techniques, demonstrating remarkable improvements in terms of bit error rate (BER), spectral efficiency, and multipath distortion tolerance. The results of this work reveal that the Modified ADCO-OFDM system with Relational Reconfigurable LDPC Decoding presents a promising solution to achieve a low-bit-error-rate, cost-effective optical communication network.

We present design and analysis of an all-optical 2:1 and 4:1 multiplexer. With the ever-growing demand for high-speed data communication, there is a need for an efficient and reliable optical multiplexing technology. Our research aims to revolutionize optical signal processing by leveraging the unique properties of optical micro ring resonator to enhance their multiplexing capabilities. Through detailed simulations and analyses, we showcase the effectiveness and feasibility of the proposed design and highlight the potential for achieving high-speed data transmission in optical networks. Logic gates serve as the fundamental building blocks for creating combinatorial and sequential models. However, existing architectures often require numerous micro-ring resonators for the development of logic gates such as AND, OR, and NOT, which results in significant space consumption. To address this issue, we have designed and simulated a 4:1 optical multiplexer by utilizing a combination of a 2:1 optical multiplexer and reversible micro-ring resonator.