Exploration of nutritional and bioactive peptide properties in goat meat from various primal cuts during in vitro gastrointestinal digestion and absorption

OBJECTIVE

This research aims to explore the nutritional and bioactive peptide properties of goat meat taken from various primal cuts, including the breast, shoulder, rib, loin, and leg, to produce these bioactive peptides during in vitro gastrointestinal (GI) digestion and absorption.

METHODS

The goat meat from various primal cuts was obtained from Boer goats with an average carcass weight of 30±2 kg. The meat was collected within 3 h after slaughter and was stored at -80°C until analysis. A comprehensive assessment encompassed various aspects, including the chemical composition, cooking properties, in vitro GI digestion, bioactive characteristics, and the bioavailability of the resulting peptides.

RESULTS

The findings indicate that the loin muscles contain the highest protein and essential amino acid composition. When the meats were cooked at 70°C for 30 min, they exhibited distinct protein compositions and quantities in the sodium dodecyl sulfate-polyacrylamide gel electrophoresis profile, suggesting they served as different protein substrates during GI digestion. Subsequent in vitro simulated GI digestion revealed that the cooked shoulder and loin underwent the most significant hydrolysis during the intestinal phase, resulting in the strongest angiotensin-converting enzyme (ACE) and dipeptidyl peptidase-IV (DPP-IV) inhibition. Following in vitro GI peptide absorption using a Caco-2 cell monolayer, the GI peptide derived from the cooked loin demonstrated greater bioavailability and a higher degree of ACE and DPP-IV inhibition than the shoulder peptide.

CONCLUSION

This study highlights the potential of goat meat, particularly cooked loin, as a functional meat source for protein, essential amino acids, and bioactive peptides during GI digestion and absorption. These peptides promise to play a role in preventing and treating metabolic diseases due to their dual inhibitory effects on ACE and DPP-IV.

CRISPR/Cas9 genome editing of CCR5 combined with C46 HIV-1 fusion inhibitor for cellular resistant to R5 and X4 tropic HIV-1

Hematopoietic stem-cell (HSC) transplantation using a donor with a homozygous mutation in the HIV co-receptor CCR5 (CCR5Δ32/Δ32) holds great promise as a cure for HIV-1. Previously, there were three patients that had been reported to be completely cured from HIV infection by this approach. However, finding a naturally suitable Human Leukocyte Antigen (HLA)-matched homozygous CCR5Δ32 donor is very difficult. The prevalence of this allele is only 1% in the Caucasian population. Therefore, additional sources of CCR5Δ32/Δ32 HSCs are required. The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) system is one method to mediate CCR5 knockout in HSCs that has been successfully employed as a gene editing tool in clinical trials. Additional anti-HIV-1 strategies are still required for broad-spectrum inhibition of HIV-1 replication. Here in this study, we combined an additional anti-HIV-1 therapy, which is C46, a cell membrane-anchored HIV-1 fusion inhibitor with the CRISPR/Cas9 mediated knockout CCR5. The combined HIV-1 therapeutic genes were investigated for the potential prevention of both CCR5 (R5)- and CXCR4 (X4)-tropic HIV-1 infections in the MT4CCR5 cell line. The combinatorial CRISPR/Cas9 therapies were superior compared to single method therapy for achieving the HIV-1 cure strategy and shows potential for future applications.

Exploring Deep Learning to Predict Coconut Milk Adulteration Using FT-NIR and Micro-NIR Spectroscopy

Accurately identifying adulterants in agriculture and food products is associated with preventing food safety and commercial fraud activities. However, a rapid, accurate, and robust prediction model for adulteration detection is hard to achieve in practice. Therefore, this study aimed to explore deep-learning algorithms as an approach to accurately identify the level of adulterated coconut milk using two types of NIR spectrophotometer, including benchtop FT-NIR and portable Micro-NIR. Coconut milk adulteration samples came from deliberate adulteration with corn flour and tapioca starch in the 1 to 50% range. A total of four types of deep-learning algorithm architecture that were self-modified to a one-dimensional framework were developed and tested to the NIR dataset, including simple CNN, S-AlexNET, ResNET, and GoogleNET. The results confirmed the feasibility of deep-learning algorithms for predicting the degree of coconut milk adulteration by corn flour and tapioca starch using NIR spectra with reliable performance (R2 of 0.886-0.999, RMSE of 0.370-6.108%, and Bias of -0.176-1.481). Furthermore, the ratio of percent deviation (RPD) of all algorithms with all types of NIR spectrophotometers indicates an excellent capability for quantitative predictions for any application (RPD > 8.1) except for case predicting tapioca starch, using FT-NIR by ResNET (RPD < 3.0). This study demonstrated the feasibility of using deep-learning algorithms and NIR spectral data as a rapid, accurate, robust, and non-destructive way to evaluate coconut milk adulterants. Last but not least, Micro-NIR is more promising than FT-NIR in predicting coconut milk adulteration from solid adulterants, and it is portable for in situ measurements in the future.

Optimizing Waste Heat Conversion: Integrating Phase-Change Material Heatsinks and Wind Speed Dynamics to Enhance Flexible Thermoelectric Generator Efficiency

Flexible thermoelectric generators (FTEGs) have garnered significant attention for their potential in harnessing waste heat energy from various sources. To optimize their efficiency, FTEGs require efficient and adaptable heatsinks. In this study, we propose a cost-effective solution by integrating phase-change materials into FTEG heatsinks. We developed and tested three flexible phase-change material thicknesses (4 mm, 7 mm, and 10 mm), focusing on preventing leaks during operation. Additionally, we investigated the impact of wind speed on the output performance of FTEGs with a flexible phase-change material heatsink. The results indicate that the appropriate flexible phase-change material thickness, when integrated with considerations for wind speed, demonstrates remarkable heat-absorbing capabilities at phase-change temperatures. This integration enables substantial temperature differentials across the FTEG modules. Specifically, the FTEG equipped with a 10 mm thick flexible phase-change material heatsink achieved a power density more than four times higher when the wind speed was at 1 m/s compared to no wind speed. This outcome suggests that integrating phase-change material heatsinks with relatively low wind speeds can significantly enhance flexible thermoelectric generator efficiency. Finally, we present a practical application wherein the FTEG, integrated with the flexible phase-change material heatsink, efficiently converts waste heat from a circular hot pipe into electricity, serving as a viable power source for smartphone devices. This work opens exciting possibilities for the future integration of flexible thermoelectric modules with flexible phase-change material heatsinks, offering a promising avenue for converting thermal waste heat into usable electricity.

Insights into Recent Updates on Factors and Technologies That Modulate the Glycemic Index of Rice and Its Products

Rice is a staple food and energy source for half the world's population. Due to its quick digestion and absorption in the gastrointestinal tract, rice is typically regarded as having a high or medium-high glycemic index (GI); however, this can vary depending on the variety, nutrient compositions, processing, and accompanying factors. This report included a table of the glycemic index for rice and rice products in different countries, which could give an overview and fundamental information on the recent GI of different rice varieties. In addition, latest updates about the mechanism effects of rice nutritional profiles and processing techniques on GI were also provided and discussed. The influence of state-of-the-art GI regulation methods was also evaluated. Furthermore, the effectiveness and efficiency of applied technologies were also given. Furthermore, this review offered some aspects about the potential nutraceutical application of rice that food scientists, producers, or consumers might consider. Diverse types of rice are grown under various conditions that could affect the GI of the product. The instinct nutrients in rice could show different effects on the digestion rate of its product. It also revealed that the rice product's digestibility is process-dependent. The postprandial glucose response of the rice products could be changed by modifying processing techniques, which might produce the new less-digestive compound or the inhibition factor in the starch hydrolysis process. Because of the significant importance of rice, this paper also concluded the challenges, as well as some important aspects for future research.

Nano-scale smooth surface of the compact-TiO2 layer via spray pyrolysis for controlling the grain size of the perovskite layer in perovskite solar cells

The mechanism of perovskite film growth is critical for the final morphology and, thus, the performance of the perovskite solar cell. The nano-roughness of compact TiO2 (c-TiO2) fabricated via the spray pyrolysis method had a significant effect on the perovskite grain size and perovskite solar cell performance in this work. While spray pyrolysis is a low-cost and straightforward deposition technique suitable for large-scale application, it is influenced by a number of parameters, including (i) alcoholic solvent precursor, (ii) spray temperature, and (iii) annealing temperature. Among alcoholic solvents, 2-propanol and 1-butanol showed a smooth surface without any large TiO2 particles on the surface compared to EtOH. The lowest roughness of the c-TiO2 layer was obtained at 450 °C with an average perovskite grain size of around 300 nm. Increased annealing temperature has a positive effect on the roughness of TiO2. The highest efficiency of the solar cell was achieved by using 1-butanol as the solvent. The decrease in the nano roughness of c-TiO2 promoted larger perovskite grain sizes via a relative decrease in the nucleation rate. Therefore, controlling the spray pyrolysis technique used to deposit the c-TiO2 layer is a promising route to control the surface nanoroughness of c-TiO2, which results in an increase in the MAPbI3 grain size.

Electrospun silk nanofiber loaded with Ag-doped TiO2 with high-reactive facet as multifunctional air filter

Particulate matter (PM) and volatile organic compounds (VOCs) are air pollution that can cause high risk to public health. To protect individuals from air pollution exposure, fibrous filters have been widely employed. In this work, we develop silk nanofibers, which are loaded with Ag-doped TiO2 nanoparticles with exposed (001) (assigned as Ag-TiO2-silk), via electrospinning method and utilized them as multifunctional air filters that can efficiently reduce PM2.5, organic pollutants and microbials. The results showed that Ag-TiO2-silk with a loading of 1 wt% (1%Ag-TiO2-silk) exhibited the best performance among various different Ag-doped samples, as it performed the best as an air filter, which had the highest PM2.5 removal efficiency of 99.04 ± 1.70% with low pressure drop of 34.3 Pa, and also exhibited the highest photodegradation efficiency of formaldehyde. In addition, the Ag-TiO2-silk demonstrated antibacterial activity. These properties make silk composite nanofibers attractive for multifunctional and environmentally-friendly air filter application.

Alternating current properties of bulk- and nanosheet-graphitic carbon nitride compacts at elevated temperatures

The investigations of temperature-dependent electrical properties in graphitic carbon nitride (g-C3N4) have been largely performed at/below room temperature on devices commonly fabricated by vacuum techniques, leaving the gap to further explore its behaviors at high-temperature. We reported herein the temperature dependence (400 → 35 °C) of alternating current (AC) electrical properties in bulk- and nanosheet-g-C3N4 compacts simply prepared by pelletizing the powder. The bulk sample was synthesized via the direct heating of urea, and the subsequent HNO3-assisted thermal exfoliation yielded the nanosheet counterpart. Their thermal stability was confirmed by variable-temperature X-ray diffraction, demonstrating reversible interlayer expansion/contraction upon heating/cooling with the thermal expansion coefficient of 2.2 × 10-5-3.1 × 10-5 K-1. It is found that bulk- and nanosheet-g-C3N4 were highly insulating (resistivity ρ ∼ 108 Ω cm unchanged with temperature), resembling layered van der Waals materials such as graphite fluoride but unlike electronically insulating oxides. Likewise, the dielectric permittivity ε', loss tangent tan δ, refractive index n, dielectric heating coefficient J, and attenuation coefficient α, were weakly temperature- and frequency-dependent (103-105 Hz). The experimentally determined ε' of bulk-g-C3N4 was reasonably close to the in-plane static dielectric permittivity (8 vs. 5.1) deduced from first-principles calculation, consistent with the anisotropic structure. The nanosheet-g-C3N4 exhibited a higher ε' ∼ 15 while keeping similar tan δ (∼0.09) compared to the bulk counterpart, demonstrating its potential as a highly insulating, stable dielectrics at elevated temperatures.

CVD Synthesis of MoS2 Using a Direct MoO2 Precursor: A Study on the Effects of Growth Temperature on Precursor Diffusion and Morphology Evolutions

In this study, the influence of growth temperature variation on the synthesis of MoS2 using a direct MoO2 precursor was investigated. The research showed that the growth temperature had a strong impact on the resulting morphologies. Below 650 °C, no nucleation or growth of MoS2 occurred. The optimal growth temperature for producing continuous MoS2 films without intermediate-state formation was approximately 760 °C. However, when the growth temperatures exceeded 800 °C, a transition from pure MoS2 to predominantly intermediate states was observed. This was attributed to enhanced diffusion of the precursor at higher temperatures, which reduced the local S:Mo ratio. The diffusion equation was analyzed, showing how the diffusion coefficient, diffusion length, and concentration gradients varied with temperature, consistent with the experimental observations. This study also investigated the impact of increasing the MoO2 precursor amount, resulting in the formation of multilayer MoS2 domains at the outermost growth zones. These findings provide valuable insights into the growth criteria for the effective synthesis of clean and large-area MoS2, thereby facilitating its application in semiconductors and related industries.

Non-Destructive Classification of Organic and Conventional Hens' Eggs Using Near-Infrared Hyperspectral Imaging

Eggs that are produced using organic methods retail at higher prices than those produced using conventional methods, but they cannot be differentiated reliably using visual methods. Eggs can therefore be fraudulently mislabeled in order to increase their wholesale and retail prices. The objective of this research was therefore to test near-infrared hyperspectral imaging (NIR-HSI) to identify whether an egg has been produced using organic or conventional methods. A total of 210 organic and 210 conventional fresh eggs were individually scanned using NIR-HSI to obtain absorbance spectra for discrimination analysis. The physical properties of each egg were also measured non-destructively in order to analyze the performance of discrimination compared with those of the NIR-HSI spectral data. Principal component analysis (PCA) showed variation for PC1 and PC2 of 57% and 23% and 94% and 4% based on physical properties and the spectral data, respectively. The best results of the classification using NIR-HSI spectral data obtained an accuracy of 96.03% and an error rate of 3.97% via partial least squares-discriminant analysis (PLS-DA), indicating the possibility that NIR-HSI could be successfully used to rapidly, reliably, and non-destructively differentiate between eggs that had been produced using organic methods from eggs that had been produced using conventional methods.

A Ratiometric Fluorescence Amplification Using Copper Nanoclusters with o-Phenylenediamine Sensor for Determination of Mercury (II) in Natural Water

A simple and rapid method for determining mercury (II) has been developed using L-cysteine-capped copper nanocluster (CuNCs) with o-phenylenediamine (OPD) as the sensor. The characteristic fluorescence peak of the synthesized CuNCs was observed at 460 nm. The fluorescence properties of CuNCs were strongly influenced by the addition of mercury (II). Upon addition, CuNCs were oxidized to form Cu²⁺. Then, the OPD were rapidly oxidized by Cu²⁺ to form o-phenylenediamine oxide (oxOPD), as evidenced by the strong fluorescence peak at 547 nm, resulting in a decrease in the fluorescence intensity at 460 nm and an increase in the fluorescence intensity at 547 nm. Under optimal conditions, a calibration curve between the fluorescence ratio (I547/I460) and mercury (II) concentration was constructed with a linearity of 0-1000 µg L^-1. The limit of detection (LOD) and limit of quantification (LOQ) were found at 18.0 µg L^-1 and 62.0 µg L^-1, respectively. The recovery percentage was in the range of 96.8-106.4%. The developed method was also compared with the standard ICP-OES method. The results were found to be not significantly different at a 95% confidence level (t_stat = 0.365 < t_crit = 2.262). This demonstrated that the developed method could be applied for detecting mercury (II) in natural water samples.

Comparing Machine Learning and PLSDA Algorithms for Durian Pulp Classification Using Inline NIR Spectra

The aim of this study was to evaluate and compare the performance of multivariate classification algorithms, specifically Partial Least Squares Discriminant Analysis (PLS-DA) and machine learning algorithms, in the classification of Monthong durian pulp based on its dry matter content (DMC) and soluble solid content (SSC), using the inline acquisition of near-infrared (NIR) spectra. A total of 415 durian pulp samples were collected and analyzed. Raw spectra were preprocessed using five different combinations of spectral preprocessing techniques: Moving Average with Standard Normal Variate (MA+SNV), Savitzky-Golay Smoothing with Standard Normal Variate (SG+SNV), Mean Normalization (SG+MN), Baseline Correction (SG+BC), and Multiplicative Scatter Correction (SG+MSC). The results revealed that the SG+SNV preprocessing technique produced the best performance with both the PLS-DA and machine learning algorithms. The optimized wide neural network algorithm of machine learning achieved the highest overall classification accuracy of 85.3%, outperforming the PLS-DA model, with overall classification accuracy of 81.4%. Additionally, evaluation metrics such as recall, precision, specificity, F1-score, AUC ROC, and kappa were calculated and compared between the two models. The findings of this study demonstrate the potential of machine learning algorithms to provide similar or better performance compared to PLS-DA in classifying Monthong durian pulp based on DMC and SSC using NIR spectroscopy, and they can be applied in the quality control and management of durian pulp production and storage.

Gelatin/Na2Ti3O7 Nanocomposite Scaffolds: Mechanical Properties and Characterization for Tissue Engineering Applications

Materials and manufacturing technologies are necessary for tissue engineering and developing temporary artificial extracellular matrices. In this study, scaffolds were fabricated from freshly synthesized titanate (Na₂Ti₃O₇) and its precursor titanium dioxide and their properties were investigated. The scaffolds with improved properties were then mixed with gelatin to form a scaffold material using the freeze-drying technique. To determine the optimal composition for the compression test of the nanocomposite scaffold, a mixture design with three factors of gelatin, titanate, and deionized water was used. Then, the scaffold microstructures were examined by scanning electron microscopy (SEM) to determine the porosity of the nanocomposite scaffolds. The scaffolds were fabricated as a nanocomposite and determined their compressive modulus values. The results showed that the porosity of the gelatin/Na₂Ti₃O₇ nanocomposite scaffolds ranged from 67% to 85%. When the mixing ratio was 100:0, the degree of swelling was 22.98%. The highest swelling ratio of 85.43% was obtained when the freeze-drying technique was applied to the mixture of gelatin and Na₂Ti₃O₇ with a mixing ratio of 80:20. The specimens formed (gelatin:titanate = 80:20) exhibited a compressive modulus of 30.57 kPa. The sample with a composition of 15.10% gelatin, 2% Na₂Ti₃O₇, and 82.9% DI water, processed by the mixture design technique, showed the highest yield of 30.57 kPa in the compression test.

Kombucha Beverages Produced from Fruits, Vegetables, and Plants: A Review on Their Pharmacological Activities and Health Benefits

Kombucha is a traditional health beverage produced by fermenting sweetened tea with a symbiotic culture of bacteria and yeasts. Consumption of kombucha beverages has been growing and there is kombucha commercially available worldwide as one of the most famous low-alcohol beverages. Kombucha beverages have been claimed to have beneficial effects on human health because they contain a variety of bioactive compounds that possess various functional properties. At present, several kinds of raw material (e.g., milk, fruit, vegetables, and herbs) have been fermented with kombucha consortium and consumed as kombucha beverages. Although several studies have been written regarding the biological activities of kombucha and raw materials, there is however little information available on the characterization of their components as well as the biological activities of fermented kombucha from many raw material mixtures. Several pharmacological activities were reviewed in the scientific literature, describing their potential implications for human health. In addition, the adverse effects and toxicity of kombucha consumption were also reviewed. In this study, we focused on the main and latest studies of the pharmacological effects of kombucha beverages produced from various kinds of raw materials, including antioxidant, anti-inflammatory, immunomodulatory, antimicrobial, anticancer, antidiabetic, antihypertensive, and antihyperlipidemic effects in in vitro and in vivo studies.

Preparation, biological evaluation and QSAR analysis of urea substituted 2,4-diamino-pyrimidine anti-malarials

The synthesis and evaluation of twenty six new phenylurea substituted 2,4-diamino-pyrimidines against Plasmodium falciparum (Pf) 3D7 are reported. Compounds were prepared to improve both anti-malarial activity and selectivity of the series previously reported by our group. Additional properties have been determined to assess their potential as anti-malarial leads including; HepG2 cytotoxicity, solubility, permeability, and lipophilicity, as well as in vitro stability in human and rat microsomes. We also assess their inhibition profile against a diverse set of 10 human kinases. Molecular docking, cheminformatics and bioinformatics analyses were also undertaken. Compounds 40 demonstrated the best anti-malarial activity at Pf 3D7 (0.09 μM), good selectivity with respect to mammalian cytotoxicity (SI = 54) and low microsomal clearance. Quantitative structure activity relationship (QSAR) analyses point to lipophilicity being a key driver of improved anti-malarial activity. The most active compounds in the series suffered from high lipophilicity, poor aqueous solubility and low permeability. The results provide useful information to guide further chemistry iterations.

Targeting multiple genes containing long mononucleotide A-T repeats in lung cancer stem cells

BACKGROUND

Intratumour heterogeneous gene expression among cancer and cancer stem cells (CSCs) can cause failure of current targeted therapies because each drug aims to target the function of a single gene. Long mononucleotide A-T repeats are cis-regulatory transcriptional elements that control many genes, increasing the expression of numerous genes in various cancers, including lung cancer. Therefore, targeting A-T repeats may dysregulate many genes driving cancer development. Here, we tested a peptide nucleic acid (PNA) oligo containing a long A-repeat sequence [A(15)] to disrupt the transcriptional control of the A-T repeat in lung cancer and CSCs.

METHODS

First, we separated CSCs from parental lung cancer cell lines. Then, we evaluated the role of A-T repeat gene regulation by counting the number of repeats in differentially regulated genes between CSCs and the parental cells of the CSCs. After testing the dosage and effect of PNA-A15 on normal and cancer cell toxicity and CSC phenotypes, we analysed genome-wide expression to identify dysregulated genes in CSCs.

RESULTS

The number of A-T repeats in genes differentially regulated between CSCs and parental cells differed. PNA-A15 was toxic to lung cancer cells and CSCs but not to noncancer cells. Finally, PNA-A15 dysregulated a number of genes in lung CSCs.

CONCLUSION

PNA-A15 is a promising novel targeted therapy agent that targets the transcriptional control activity of multiple genes in lung CSCs.

Multi-Parameter Vital Sign Telemedicine System Using Web Socket for COVID-19 Pandemics

Telemedicine has become an increasingly important part of the modern healthcare infrastructure, especially in the present situation with the COVID-19 pandemics. Many cloud platforms have been used intensively for Telemedicine. The most popular ones include PubNub, Amazon Web Service, Google Cloud Platform and Microsoft Azure. One of the crucial challenges of telemedicine is the real-time application monitoring for the vital sign. The commercial platform is, by far, not suitable for real-time applications. The alternative is to design a web-based application exploiting Web Socket. This research paper concerns the real-time six-parameter vital-sign monitoring using a web-based application. The six vital-sign parameters are electrocardiogram, temperature, plethysmogram, percent saturation oxygen, blood pressure and heart rate. The six vital-sign parameters were encoded in a web server site and sent to a client site upon logging on. The encoded parameters were then decoded into six vital sign signals. Our proposed multi-parameter vital-sign telemedicine system using Web Socket has successfully remotely monitored the six-parameter vital signs on 4G mobile network with a latency of less than 5 milliseconds.

Synthesis, microstructure, multifunctional properties of mayenite Ca12Al14O33 (C12A7) cement and graphene oxide (GO) composites

The Pristine Mayenite Ca12Al14O33 (C12A7) Cement was simply synthesized by using solid-state reaction. The C12A7 and Graphene Oxide (GO) composites (C12A7_GO-x) with various contents of the GO suspension loading (x = 0 wt%, 1 wt%, 2 wt%, 3 wt%, and 4 wt%) were directly prepared by mixing the C12A7 and GO. X-ray diffraction results of pristine C12A7 and all C12A7_GO composites indicated a pure phase corresponding to the standard of C12A7 cement. Raman spectroscopy confirmed the existence of GO in all C12A7_GO samples. Scanning Electron Microscopy (SEM) showed the micrometer grain sizes and the occurrence of grain boundary interfaces for GO incorporation in all C12A7_GO samples. UV-Vis spectroscopy revealed the absorption value of all C12A7_GO samples and red shift near longer wavelengths when increasing the GO concentrations. The dielectric constant of C12A7_GO composites can be explained by the high density of free electron charges for the interfacial polarization on the GO surface. The maximum specific capacitance of C12A7_GO-4 electrode of 21.514 at a current density of 0.2 A g-1 can be attributed to the increase in the electrochemically active surface area for the formation of the electrical double layer capacitors behavior and the effects of high surface area GO connections. Also, the mechanical properties exhibited an increase in Vickers indenter hardness (HV) values with increasing GO contents. The highest HV value was 117.8 HV/2 kg at the C12A7_GO-4 sample. These results showed that the composite materials of the pristine C12A7 cement with GO were highly efficient. All in all, the GO material contained a high potential for enhancing low-cost cement materials in multifunctional properties such as optical, dielectric, electrochemical, and mechanical properties.