Extracting mechanical quality factor and eliminating feedthrough using harmonics of thermal-piezoresistive micromechanical resonators.

Thermal-actuation and piezoresistive-detection effects have been employed to pump the effective quality factor of MEMS resonators, targeting simple self-oscillation and better sensing performance in the air. However, the ratio of the pumped effective quality factor to the inherent mechanical quality factor, crucial for characterizing the amplification, is hard to obtain. The main difficulty stems from hidden Lorentz peaks caused by feedthrough effects and the pump effect once the current is applied.

Multi-angle and full-Stokes polarization multispectral images using quarter-wave plate and tunable filter.

Polarization multispectral imaging has advanced significantly due to its robust information representation capability. Imaging application requires rigorous simulation evaluation and experimental validation using standardized datasets. However, the current full-Stokes polarization multispectral images (FSPMI) dataset, while providing simulation data, is limited by image drift and spectral bands.

Modulate the laser phase to improve the ns-LIBS spectrum signal based on orbital angular momentum.

Aiming to enhance the ns-LIBS signal, in this work, we introduced orbital angular momentum to modulate the laser phase of the Gaussian beam into the vortex beam. Under similar incident laser energy, the vortex beam promoted more uniform ablation and more ablation mass compared to the Gaussian beam, leading to elevated temperature and electron density in the laser-induced plasma. Consequently, the intensity of the ns-LIBS signal was improved.

Full-Stokes polarization laser-induced breakdown spectroscopy detection of infiltrative glioma boundary tissue.

The glioma boundary is difficult to identify during surgery due to the infiltrative characteristics of tumor cells. In order to ensure a full resection rate and increase the postoperative survival of patients, it is often necessary to make an expansion range resection, which may have harmful effects on the quality of the patient's survival. A full-Stokes laser-induced breakdown spectroscopy (FSLIBS) theory with a corresponding system is proposed to combine the elemental composition information and polarization information for glioma boundary detection.

Full-Stokes polarization multispectral images of various stereoscopic objects.

Polarization multispectral imaging (PMI) has been applied widely with the ability of characterizing physicochemical properties of objects. However, traditional PMI relies on scanning each domain, which is time-consuming and occupies vast storage resources. Therefore, it is imperative to develop advanced PMI methods to facilitate real-time and cost-effective applications.

Rapid Test for Adulteration of Fritillaria Thunbergii in Fritillaria Cirrhosa by Laser-Induced Breakdown Spectroscopy.

Fritillaria has a long history in China, and it can be consumed as medicine and food. Owing to the high cost of Fritillaria cirrhosa, traders sometimes mix it with the cheaper Fritillaria thunbergii powder to make profit. Herein, we proposed a laser-induced breakdown spectroscopy (LIBS) technique to test the adulteration present in the sample of Fritillaria cirrhosa powder.

Self-adjusting inverse design method for nanophotonic devices.

Nanophotonic devices, which consist of multiple cell structures of the same size, are easy to manufacture. To avoid the optical proximity effect in the ultraviolet lithography process, the cell structures must be maintained at a distance from one another. In the inverse design process, the distance is maintained by limiting the optimized range of the location.

Polarimetry-inspired feature fusion spectroscopy (PIFFS) for ammonia sensing in water.

The sustainable use of water resources is inseparable from water pollution detection. The sensing of toxic ammonia nitrogen in water currently requires auxiliary reagents, which may cause secondary pollution. Benefiting from the ability of substances to change light characteristics, this work proposes polarimetry-inspired feature fusion spectroscopy (PIFFS) to detect ammonia.

Accurate Identification and Quantification of Chinese Yam Powder Adulteration Using Laser-Induced Breakdown Spectroscopy.

As a popular food, Chinese yam (CY) powder is widely used for healthy and commercial purposes. Detecting adulteration of CY powder has become essential. In this work, chemometric methods combined with laser-induced breakdown spectroscopy (LIBS) were developed for identification and quantification of CY powder adulteration.

In-vitro study on the identification of gastrointestinal stromal tumor tissues using laser-induced breakdown spectroscopy with chemometric methods.

Early-stage detection of tumors helps to improve patient survival rate. In this work, we demonstrate a novel discrimination method to diagnose the gastrointestinal stromal tumor (GIST) and its healthy formalin fixed paraffin embedded (FFPE) tissues by combining chemometric algorithms with laser-induced breakdown spectroscopy (LIBS). Chemometric methods which include partial least square discrimination analysis (PLS-DA), k-nearest neighbor (k-NN) and support vector machine (SVM) were used to build the discrimination models.

Evaluation of human melanoma and normal formalin paraffin-fixed samples using Raman and LIBS fused data.

In this research, we developed a novel method of quantitative analysis to increase the detection potential for screening and classification of skin cancer (melanoma). We fused two distinct optical approaches, an atomic spectroscopic detection technique laser-induced breakdown spectroscopy (LIBS) and a vibrational molecular spectroscopic technique known as Raman spectroscopy. Melanoma is a kind of skin cancer, also known as malignant melanoma, that developed in melanocytes cells, which produced melanin.

Acceleration of inverse design process on adaptive mesh.

In inverse design, the design and background areas can be represented by different spatial resolutions; thus, adaptive meshes are more efficient than structured meshes. In this study, a second-order interpolation scheme is introduced to realize an inverse design process on an adaptive mesh. Experiment results show that the proposed scheme yields a 1.

Predictive data clustering of laser-induced breakdown spectroscopy for brain tumor analysis.

Limited by the lack of training spectral data in different kinds of tissues, the diagnostic accuracy of laser-induced breakdown spectroscopy (LIBS) is hard to reach the desired level with normal supervised learning identification methods. In this paper, we proposed to apply the predictive data clustering methods with supervised learning methods together to identify tissue information accurately. The meanshift clustering method is introduced to compare with three other clustering methods which have been used in LIBS field.

Primary study of identification of parathyroid gland based on laser-induced breakdown spectroscopy.

The identification and preservation of parathyroid glands (PGs) is a major issue in thyroidectomy. The PG is particularly difficult to distinguish from the surrounding tissues. Accidental damage or removal of the PG may result in temporary or permanent postoperative hypoparathyroidism and hypocalcemia.

Pathological identification of brain tumors based on the characteristics of molecular fragments generated by laser ablation combined with a spiking neural network.

Quick and accurate diagnosis helps shorten intraoperative waiting time and make a correct plan for the brain tumor resection. The common cryostat section method costs more than 10 minutes and the diagnostic accuracy depends on the sliced and frozen process and the experience of the pathologist. We propose the use of molecular fragment spectra (MFS) in laser-induced breakdown spectroscopy (LIBS) to identify different brain tumors.

Discrimination of hazardous bacteria with combination laser-induced breakdown spectroscopy and statistical methods.

Real-time biohazard detectors must be developed to facilitate the rapid implementation of appropriate protective measures against foodborne pathogens. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for the real-time detection of hazardous bacteria (HB) in the field. However, distinguishing among various HBs that exhibit similar C, N, O, H, or trace metal atomic emissions complicates HB detection by LIBS.

DESIGN AND DEVELOPMENT OF HUMAN COMPUTER INTERFACE USING ELECTROOCULOGRAM WITH DEEP LEARNING.

Today's life assistive devices were playing significant role in our life to communicate with others. In that modality Human Computer Interface (HCI) based Electrooculogram (EOG) playing vital part. By using this method we can able to overcome the conventional methods in terms of performance and accuracy.

Comparison of Performance of Equations for Estimated Glomerular Filtration Rate in Chinese Patients with Biopsy-Proven Diabetic Nephropathy.

Background: The performance of various equations for estimated glomerular filtration rate (eGFR) in patients with diabetes remains controversial. We aimed to evaluate the performance of equations for eGFR in Chinese patients with diabetic nephropathy (DN).

Methods: This is a retrospective study included in 308 patients with type 2 diabetes and biopsy-proven DN who were followed up at least one year.

Identification and classification of explosives using semi-supervised learning and laser-induced breakdown spectroscopy.

Public places are often under threat from explosion events, which pose health and safety risks to the public. Therefore, the detection of explosive materials has become an important concern in the fields of antiterrorism and security. Laser-induced breakdown spectroscopy (LIBS) has been demonstrated to be useful in identifying explosives but has limitations.

Importance evaluation of spectral lines in Laser-induced breakdown spectroscopy for classification of pathogenic bacteria.

The correct classification of pathogenic bacteria is significant for clinical diagnosis and treatment. Compared with the use of whole spectral data, using feature lines as the inputs of the classification model can improve the correct classification rate (CCR) and reduce the analyzing time. In order to select feature lines, we need to investigate the contribution to the CCR of each spectral line.

Gene Variants and Diabetic Kidney Disease in MODY.

Background And Objectives: Despite advances in identifying genetic factors of diabetic kidney disease (DKD), much of the heritability remains unexplained. Nine maturity-onset diabetes in young (MODY) probands with kidney biopsy-proven DKD were selected and included in this study. The probands had more severe DKD compared with their parents with MODY, with overt proteinuria or rapid progression to ESKD.

Thyroid hormones and diabetic nephropathy: An essential relationship to recognize.

Aims: Although abnormal thyroid hormone metabolism is common in patients with type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN), the relationship between thyroid hormones and DN is unclear and has been ignored during clinical practice. This study aimed to investigate the relationship between thyroid hormones and clinicopathologic changes in biopsy-proven DN patients.

Methods: Clinical and pathological data for 146 biopsy-proven DN patients were collected.

Diabetic retinopathy may predict the renal outcomes of patients with diabetic nephropathy.

Background: The patients with Type 2 diabetes mellitus (T2DM) and diabetic retinopathy (DR) are prone to develop diabetic nephropathy (DN). In this study, we aimed to clarify the relationship between DR and the progression of DN in patients with T2DM.

Methods: In the cross-section study, 250 patients with T2DM and biopsy-proven DN were divided into two groups: 130 in the DN without DR group (DN group) and 120 in the DN + DR group.