Machine learning assisted hepta band THz metamaterial absorber for biomedical applications.

A hepta-band terahertz metamaterial absorber (MMA) with modified dual T-shaped resonators deposited on polyimide is presented for sensing applications. The proposed polarization sensitive MMA is ultra-thin (0.061 λ) and compact (0.21 λ) at its lowest operational frequency, with multiple absorption peaks at 1.89, 4.15, 5.32, 5.84, 7.04, 8.02, and 8.13 THz. The impedance matching theory and electric field distribution are investigated to understand the physical mechanism of hepta-band absorption. The sensing functionality is evaluated using a surrounding medium with a refractive index between 1 and 1.1, resulting in good Quality factor (Q) value of 117. The proposed sensor has the highest sensitivity of 4.72 THz/RIU for glucose detection. Extreme randomized tree (ERT) model is utilized to predict absorptivities for intermediate frequencies with unit cell dimensions, substrate thickness, angle variation, and refractive index values to reduce simulation time. The effectiveness of the ERT model in predicting absorption values is evaluated using the Adjusted R2 score, which is close to 1.0 for nmin = 2, demonstrating the prediction efficiency in various test cases. The experimental results show that 60% of simulation time and resources can be saved by simulating absorber design using the ERT model. The proposed MMA sensor with an ERT model has potential applications in biomedical fields such as bacterial infections, malaria, and other diseases.

Comparative Evaluation of Serum Tumor Necrosis Factor α in Health and Chronic Periodontitis: A Case-Control Study.

BACKGROUND: Tumor necrosis factor-alpha (TNF-α), a " major inflammatory cytokine," not only plays an important role in periodontal destruction but also is extremely toxic to the host. Till date, there are not many studies comparing the levels of TNF-α in serum and its relationship to periodontal disease. AIM: Our study aimed to compare the serum TNF-α among the two study groups, namely, healthy controls and chronic periodontitis patients and establish a correlation between serum TNF-α and various clinical parameters. Hence, an attempt is made to estimate the level of TNF-α in serum, its relationship to periodontal disease and to explore the possibility of using the level of TNF-α in serum as a biochemical " marker" of periodontal disease. MATERIALS AND METHODS: Forty individuals participated in the study and were grouped into two subgroups. Group A - 20 systemically and periodontally healthy controls. Group B - twenty patients with generalized chronic periodontitis. The serum samples were assayed for TNF-α levels by enzyme-linked immunosorbent assay method. RESULTS: The mean serum TNF-α cytokines for Group B Generalized chronic periodontitis (GCP) was 2.977 ± 1.011, and Group A (healthy) was 0.867 ± 0.865. The range of serum TNF-α was from (0.867 to 2.977). Serum TNF-α cytokines had highly significant correlation with all clinical parameters (plaque index, probing pocket depth, clinical attachment loss, and gingival index) among all study participants (P = 0.001). CONCLUSION: These observations suggest a positive association between periodontal disease and increased levels of TNF-α in serum. It can be concluded that there is a prospect of using the estimation of TNF-α in serum as a "marker" of periodontal disease in future. However, it remains a possibility that the absence or low levels of TNF-α in serum might indicate a stable lesion and elevated levels might indicate an active site but only longitudinal studies taking into account, the disease "activity" and "inactivity" could suggest the possibility of using TNF-α in serum as an "Indicator" of periodontal disease.

Removal and recovery of heavy metals through size enhanced ultrafiltration using chitosan derivatives and optimization with response surface modeling.

N­N­N­triethylammonium chitosan (TEAC) and carboxymethyl chitosan (CMCh), the two water-soluble chitosan derivatives were utilized for the removal and recovery of heavy metals by size enhanced ultrafiltration (SEUF). The strong positive quaternary ammonium [-N+(C2H5)3] cation in TEAC interacts with Cr(VI), which exists as a strong chromate anion thereby enabling the efficient removal of chromate through ultrafiltration. CMCh consists of COOH and NH2 moieties, which facilitate interactions with heavy metals such as Cu(II) and Ni(II). FTIR, SEM, and EDAX were used to characterize the chitosan derivatives before and after the removal of metals. The experiments were designed with the central composite design (CCD) of response surface methodology (RSM). The metal ion removal experiments were conducted as per the statistical design to determine the optimum process conditions; initial pH of the feed solution, polymer to metal loading ratio (P/M), and initial concentration of the feed solution. The optimization study was conducted to maximize the heavy metal rejection and binding capacity of the chitosan derivatives. The analysis of variance (ANOVA) was performed to validate the developed regression models.

Bilayer graphene/HgCdTe based very long infrared photodetector with superior external quantum efficiency, responsivity, and detectivity.

We present a high-performance bilayer graphene (BLG) and mercury cadmium telluride (Hg1-x Cd x=0.1867Te) heterojunction based very long wavelength infrared (VLWIR) conductive photodetector. The unique absorption properties of graphene enable a long carrier lifetime of charge carriers contributing to the carrier-multiplication due to impact ionization and, hence, large photocurrent and high quantum efficiency. The proposed p+-BLG/n-Hg0.8133Cd0.1867Te photodetector is characterized and analyzed in terms of different electrical and optical characteristic parameters using computer simulations. The obtained results are further validated by developing an analytical model based on drift-diffusion, tunneling and Chu's methods. The photodetector has demonstrated a superior performance including improved dark current density (∼1.75 × 10-14 µA cm-2), photocurrent density (∼8.33 µA cm-2), internal quantum efficiency (QEint ∼ 99.49%), external quantum efficiency (QEext ∼ 89%), internal photocurrent responsivity (∼13.26 A W-1), external photocurrent responsivity (∼9.1 A W-1), noise equivalent power (∼8.3 × 10-18 W), total noise current (∼1.06 fA), signal to noise ratio (∼156.18 dB), 3 dB cut-off frequency (∼36.16 GHz), and response time of 9.4 ps at 77 K. Furthermore, the effects of different external biasing, light power intensity, and temperature are evaluated, suggesting a high QEext of 3337.70% with a bias of -0.5 V near room temperature.