Characteristic Bands Research Articles

Anatomía del pecíolo de 16 especies de Polypodiaceae presentes en México

Background and aims: Several works have shown that the petiole possesses useful anatomical characteristics for differentiating groups. Therefore, we carried out a descriptive and comparative anatomical study of the basal, middle, and apical regions of the petiole of 16 species belonging to 8 genera of Polypodioideae growing in Mexico, to identify anatomical characters that can contribute to their delimitation and identification M&M: Samples were collected from the basal, middle, and apical regions of the petiole and processed according to the paraffin embedding technique to obtain permanent preparations. The generated information was evaluated through a clustering analysis and a principal component analysis. Results: All petioles showed an unistratified epidermis, a cortex differentiated into external and internal, and vascular bundles with Polypodium-type distribution. Differences were registered in the petiole diameter, indument type, circumendodermal band, and number of vascular bundles. Four types of external cortex are recognized and the presence of nectaries in Campyloneurum amphostenon and C. costatum is reported for the first time, as well as the glandular hairs inserted at the base of the scales in Microgramma percussa. Identification keys were elaborated. Conclusions: The anatomical characteristics of the petiole allow us to differentiate taxonomically the genera and most of the species analyzed, the most important traits being the petiole diameter, the characteristics of the circumendodermal band, and the presence of aerophores and/or wings

Mapping irrigation regimes in Chinese paddy lands through multi-source data assimilation

Water-saving irrigation (WI) is a crucial agricultural management with the benefits to save irrigation water, reduce energy consumption, and suppress methane emissions from paddy lands. Classifying WI practices from traditional flooding irrigation (FI) is a key component in detecting the rice irrigation status, which is significant to estimate the total agriculture-associated greenhouse gas emissions. In this study, we developed an automatic method to map irrigation regimes across Chinese paddy lands. First, we used seven variables related with irrigation facility or vegetation cover as proxy to generate representative WI and FI samples. Besides, we composited 123 features of optical bands and synthetic aperture radar from MODIS and Sentinel-1 data. Then, we trained a random forest model for each province with these samples. Finally, we applied the trained model to generate maps of WI/FI practices at 500 m resolution. Comparisons of the resultant maps with census data indicated highly accurate estimations of the WI area at a city- or province-level, with a R2 higher than 0.92. The overall accuracy of the classification was approximately 0.73, as validated through ground truth samples. Additionally, we also conducted a data quality analysis and confirmed the classification results were reliable in main rice production area of China. With the push towards carbon neutrality goals and the increasing demand for clean management practices, we developed and demonstrated an advanced method to produce near real-time maps of irrigation regimes and provide crucial data support for agricultural emissions reduction and irrigation management decisions.

Synthesis of Silver Nanoparticles Using Plant Extracts from Legeneraria Siceraria Fruits and Assessment of their Anti-Bacterial and Anti-Oxidant Activities

Nanotechnology is a key subject of science, engineering, and technology that is experiencing enormous growth in the current century. In this study, fruits of the legeneraria siceraria plant, this is widely used in traditional medicines in Ethiopian rural areas, used as reducing and capping agent for AgNPs synthesis. The legeneraria siceraria fruits -mediated synthesized AgNPs characterized by ultravioletvisible (UV-VIS.) spectrophotometry, Fourier transform-infrared (FT-IR) spectroscopy, X-ray diffractometer (XRD), scanning electron microscopy (SEM), dynamic light scattering (DLS). The optimal synthesization parameters for AgNPs in this study were temperature 60 °C, stirring time 60 minutes, pH 11, and 2 mM silver nitrate concentration. Characteristic and well-defined SPR bands for AgNPs were confirmed at around λmax = 426 nm. Synthesized AgNPs of calculated mean crystallite size were 10.21 nm. Scanning electron microscopy (SEM) revealed the synthesized AgNPs have a spherical structure. The antibacterial activity of AgNPs synthesized using legeneraria siceraria fruits medicinal plants demonstrated that Gram-positive and Gram-negative bacteria inhibited. Additionally, the AgNPs showed minimal toxicity to human cells. AgNPs were useful antioxidants for health preservation against different oxidative stress associated with degenerative diseases. In this work, it acts at scavenging against DPPH.

Identification and phylogenetic analysis of carbapenemase genes from clinical strains of Klebsiella pneumoniae.

Klebsiella pneumoniae is an encapsulated Gram-negative bacterium that is responsible for numerous infections in healthcare facilities worldwide and is frequently isolated. The World Health Organization has listed K. pneumoniaeas as a critical antibiotic resistant bacterial pathogen for which new antibiotics are urgently needed. This study aimed to use molecular tools to identify and examine antibiotic resistance in clinical strains of K. pneumoniae. A total of 15 unduplicated K. pneumoniae strains isolated from patient samples with multidrug-resistant (MDR) profiles were subjected to polymerase chain reaction (PCR) to amplify the most common carbapenem resistance genes. (GTG)5 PCR and phylogenetic analysis were performed to identify the genetic relationship between the strains. All strains yielded a (GTG)5-PCR profile, and this allowed us to group these strains into 8 groups according to the size and number of characteristic bands. Phylogenetic analysis was done using the free software UPGMA and a single bacterial clone with a correlation coefficient of over 97% was identified. New Delhi metallo-beta-lactamase NDM-like (blaNDM) carbapenem resistance genes were detected in three strains of K. pneumoniae, which represented a resistance rate of 20%. However, carbapenemases type A [Klebsiella pneumoniae carbapenemase (KPC) and imipenem-hydrolysing beta-lactamase (IMI), type D [oxacillinase-48 (OXA-48)], and other metallo-β-lactamase [Verona integron-encoded metallo-beta-lactamase (VIM), and enzyme active on imipenem (IMP)] were not detected. We identified and grouped the blaNDM resistance genes of Klebsiella pneumonia strains.

OPTIMIZATION OF PECTIN EXTRACTION FROM SUGAR BEET PULP USING MICROWAVE TREATMENT

Pectin is a natural heteropolysaccharide contained in plant cell walls and plant waste. In recent years, various alternative methods (enzymatic, microwave, ultrasonic) have been used to increase the yield of pectin, which can increase the efficiency of the process, pectin yield and improve quality. The principal advantages of using microwaves for the extraction of pectin from plant waste materials are the significant reduction in processing time, the higher yield of the natural polymer and the quality maintenance due to the more gentle processing conditions. The purpose of the work is to improve the method of pectin extraction from beet pulp using microwave treatment. Experiments were carried out to establish the optimal conditions of polysaccharide extraction. The pectin extraction was optimized by varying the microwave power, the pH of the medium, the processing time, the type of extracting agent (citric, malic, hydrochloric and acetic acids) and the ratio of beet pulp to extracting agent. A titrimetric method was used to determine the degree of esterification and the uronide component. Results and discussion. Extraction of pectin from sugar beet pulp includes the following main steps: polymer extraction by microwave treatment, pectin purification and drying. Among the studied parameters, the ratio of beet pulp to extracting agent and microwave processing time had a significant effect on the yield and properties of pectin. The highest yield of pectin (5.7%) was achieved at a heating power of 520 W, pH - 2.0, processing time of 30 minutes, using citric acid as the extraction agent and a beet pulp to extraction agent mass ratio of 15:1. IR spectra of the extracted pectin show the presence of characteristic bands typical of the pectin spectrum. Conclusions. Varying the parameters of pectin extraction from sugar beet pulp using microwave treatment allowed to increase the yield of pectin with desired characteristics. The perspective of using ecologically pure organic acids (citric and malic acids) as an extracting agent is shown.

Hyperspectral Prediction Models of Chlorophyll Content in Paulownia Leaves under Drought Stress.

This study explored the quantitative inversion of the chlorophyll content in Paulownia seedling leaves under drought stress and analyzed the factors influencing the chlorophyll content from multiple perspectives to obtain the optimal model. Paulownia seedlings were selected as the experimental materials for the potted water control experiments. Four drought stress treatments were set up to obtain four types of Paulownia seedlings: one pair of top leaves (T1), two pairs of leaves (T2), three pairs of leaves (T3), and four pairs of leaves (T4). In total, 23 spectral transformations were selected, and the following four methods were adopted to construct the prediction model, select the best spectral preprocessing method, and explore the influence of water bands: partial least squares modeling with all spectral bands (all-band partial least squares, AB-PLS), principal component analysis partial least squares (PCA-PLS), correlation analysis partial least squares (CA-PLS), correlation analysis (water band) partial least squares, ([CA(W)-PLS]), and vegetation index modeling. Based on the prediction accuracy and the uniformity of different leaf positions, the optimal model was systematically explored. The results of the analysis of spectral reflectance showed significant differences at different leaf positions. The sensitive bands of chlorophyll were located near 550 nm, whereas the sensitive bands of water were located near 1440 and 1920 nm. The results of the vegetation index models indicate that the multiple-index models outperformed the single-index models. Accuracy decreased as the number of indicators decreased. We found that different model construction methods matched different optimal spectral preprocessing methods. First derivative spectra (R') was the best preprocessing method for the AB-PLS, PCA-PLS, and CA-PLS models, whereas the inverse log spectra (log(1/R)) was the best preprocessing method for the CA(W)-PLS model. Among the 14 indices, the green normalized difference vegetation index (GNDVI) was most correlated with the chlorophyll content sensitivity indices, and the water index (WI) was most correlated with the water sensitive indices. At the same time, the water band affected the cross validation accuracy. When characteristic bands were used for modeling, the cross validation accuracy was significantly increased. In contrast, when vegetation indices were used for modeling, the accuracy of the cross validation increased slightly but its predictive ability was reduced; thus, these changes could be ignored. We found that leaf position also affected the prediction accuracy, with the first pair of top leaves exhibiting the worst predictive ability. This was a bottleneck that limited predictive capability. Finally, we found that the CA(W)-PLS model was optimal. The model was based on 23 spectral transformations, four PLS construction methods, water bands, and different leaf positions to ensure systematicity, stability, and applicability.

Tailored proton conductive membranes of PVdF-co-HFP: Investigating the synergistic effects of ammonium tetrafluoroborate and phosphoric acid dopants on dielectric characteristics

This study investigates the structural, thermal, and dielectric properties of pure PVdF-co-HFP matrix and its composite electrolytes, PVdF-co-HFP/NH4BF4[x], both before and after PA doping, using FTIR, SEM, TGA, and dielectric analyses. FTIR spectra reveal characteristic vibrational bands, confirming the presence of various functional groups and phases. SEM images display a smooth and homogeneous surface morphology for pure PVdF-co-HFP, while the composite electrolytes exhibit irregular dispersion of NH4BF4 salt and rougher surfaces upon PA doping. TGA analysis shows that the onset of thermal degradation occurs at approximately 370 ℃ for pure PVdF-co-HFP, while PA-doped samples demonstrate higher decomposition temperatures, exceeding 400 ℃ due to hydrogen bonding and ionic complex formation. The presence of NH4BF4 and PA doping also affects the crystallinity of the PVdF-co-HFP matrix, notably shifting the transition temperatures of the alpha and beta phases. Ionic conductivity measurements indicate that PA doping significantly enhances conductivity by increasing charge carrier concentration and facilitating ion transport. PA-doped PVdF-co-HFP/NH4BF4[10] showed the highest conductivity reaching 1.68 × 10−3 S.cm−1 at 1 MHz and 400 K. Dielectric studies reveal frequency-dependent behavior, with dielectric constant (ε') and loss (ε") showing distinct trends influenced by salt concentration and PA doping. The dielectric tangent loss (tanδ) of PA-doped PVdF-co-HFP/NH4BF4 composite membranes exhibits frequency and temperature dependence. At higher temperatures, tanδ increases with frequency, showing a resonance peak that shifts towards higher frequencies. The study elucidates the impact of PA doping on the structural, thermal, and electrochemical performance of PVdF-co-HFP/NH4BF4 composites, providing insights for their potential applications in advanced electrolyte systems.

Examining the electronic, structural, optical, and photovoltaic capabilities of Sr3AsBr3 perovskite under tensile and compressive strains with DFT and SCAPS-1D

A significant amount of interest in the field of solar energy has recently been generated by the remarkable optical, structural, and electronic attributes of inorganic perovskite-based substances. A thorough investigation was conducted on how tensile along with compressive strains influence the electronic and optical properties of halide perovskite Sr3AsBr3, utilizing FP-DFT. The PBE functional is used to determine the direct bandgap of 1.512 eV for unstrained Sr3AsBr3 at the Γ position. The bandgap redshifts (1.216 eV at -4 % strain) under compressive strain and slightly increases (1.728 eV at +4 % strain) under tensile tension, causing the absorption coefficient to blueshift. The optical properties, including the functions of dielectric, electron energy loss function, and absorption coefficient, all indicate a considerable capacity for absorption in the area of the visible spectrum, and the band characteristics of this component agree with these qualities. We used Sr3AsBr3 absorbers and CdS electron transport layers (ETL) with different thicknesses, defect densities, and doping concentrations to study solar power capabilities using the SCAPS-1D simulator. The most effective arrangement (at -4 % strain) had a fill factor (FF) of 86.76 %, a short-circuit current density (JSC) of 37.5593 mAcm−2, an open-circuit voltage (VOC) of 0.8712 V, and a power conversion efficiency (PCE) of 28.39 %. Our findings support additional research into Sr3AsBr3, a promising perovskite for optoelectronic uses.

Design and experimentation of width tapered meandered array structure for low frequency broadband vibration energy harvesting

A novel 6DoF Tapered beam energy harvester, capable of operating across a broad and low frequency range, is proposed in this work. The hybrid structure incorporates regular beam array and zig-zag sections, enhancing deformation and bending. Width tapering with constant thickness optimizes the structural performance and energy harvesting capabilities of the beam. Tapering ensures even strain distribution, reducing the risk of structural failure. The proposed structure demonstrates wide band characteristics at low frequencies, delivering higher power output compared to an array of cantilevers for a given area. FEM analysis is conducted to optimize proof mass, aiming for closely spaced resonance frequencies and high-power output. Experimental validation on a prototype confirms the accuracy of the frequency response predicted by the models. Under harmonic base excitation of 0.4 g, the harvester yields an average DC power of 2497 μW, accounting for signal conditioning losses, within the frequency range of 9–20 Hz. The suggested structure offers excellent design flexibility, allowing adjustment of resonant frequencies by varying the number of beams, the slope and the proof mass of individual beams. The geometry of the proposed structure provides versatility, mechanical resilience, uniform strain distribution make it suitable for developing MEMS energy harvesters.

Pyrazine-Based Aromatic Dyes as Novel Photosensitizers with Improved Conduction Band and Photovoltaic Features: DFT Insights for Efficient Dye-Sensitized Solar Cells

Dye-sensitized solar cells (DSSCs) have garnered significant attention due to their exceptional ability to convert solar energy into electricity at a relatively low cost. Novel organic photosensitizers (FZB1-FZB9) from the pyrazine-based aromatic dye (E)-3-(5-(2,3-bis(40-(diphenylamino)-[1,10-biphenyl]-4-yl)-7 (trifluoromethyl)quinoxalin-5-yl)thiophen-2-yl)-2-cyanoacrylic acid (TPPF) have been quantum chemically modeled for their application in dye-sensitized nanocrystalline TiO2 solar cells (DSSCs). The electrochemical and photovoltaic features of modeled dyes are investigated by performing DFT insights, i.e. FMOs, absorption maxima, DOS, TDM, NBO, exciton and binding energy, radiative lifetime analysis (ꚍ), electron-injection (Δ G inject ) and regeneration analysis ( Δ G dye regen )@TiO2. FMO analysis confirmed the better electron injection as HOMO of designed dyes was found to be more positive than redox potential I/I3 (-4.8 eV), and the LUMO appeared more negative than the conduction band of TiO2 (-4.0 eV). The modeled photosensitizers exhibited red shift λmax from 338-494 nm with a lower energy gap from 5.62 eV in FZB (R) to 5.17 eV in FZB9. Bridging modification reduces the exciton and binding energy for designed dye FZB9 and FZB7 compared to reference FZB. The designed dyes appeared with a lower radiative lifetime of up to 1.32 than the reference dye of 1.63, better light harvesting efficiency (LHE), and the highest NBO charge on bridges of designed photosensitizers for enhanced light emitting efficiency. The investigated dyes exhibited more negative values for electron injection, i.e. −0.003 and the highest values of dye regeneration ( Δ G regedye regen ) up to 11.717, which unveils innovative and effective injection of electrons toward semiconductor TiO2. Among all dyes, FZB8 proved best with the novel bridging modification that enables quick charge transfer as exhibited the lowest gap (5.17 eV), lowest excitation energy, better LHE, highest charge on LUMO and more negative electron injection (Δ G inject ) . The outcomes of this computational study confirmed that this research established a new benchmark for achieving novel and efficient photosensitizers, thus recommending them for future DSSC applications.

Fault Diagnosis Method for Vacuum Contactor Based on Time-Frequency Graph Optimization Technique and ShuffleNetV2.

This paper presents a fault diagnosis method for a vacuum contactor using the generalized Stockwell transform (GST) of vibration signals. The objective is to solve the problem of low diagnostic performance efficiency caused by the inadequate feature extraction capability and the redundant pixels in the graph background. The proposed method is based on the time-frequency graph optimization technique and ShuffleNetV2 network. Firstly, vibration signals in different states are collected and converted into GST time-frequency graphs. Secondly, multi-resolution GST time-frequency graphs are generated to cover signal characteristics in all frequency bands by adjusting the GST Gaussian window width factor λ. The OTSU algorithm is then combined to crop the energy concentration area, and the size of these time-frequency graphs is optimized by 68.86%. Finally, considering the advantages of the channel split and channel shuffle methods, the ShuffleNetV2 network is adopted to improve the feature learning ability and identify fault categories. In this paper, the CKJ5-400/1140 vacuum contactor is taken as the test object. The fault recognition accuracy reaches 99.74%, and the single iteration time of model training is reduced by 19.42%.

Two-dimensional tetragonal carbon nitride semiconductors with fascinating electronic/optical properties and low thermal conductivity

Abstract Exploring two-dimensional (2D) tetragonal carbon nitride materials is significant for unlocking new physical properties beyond those offered by traditional hexagonal lattices. In this work, we propose three theoretically stable 2D carbon nitride monolayers with tetragonal lattices, namely T-C3N, P-C3N, and PH-C5N4. Electronic structure calculations indicate that all three monolayers exhibit semiconducting characteristics, with T-C3N showing interesting flat band features. Additionally, these three carbon nitrides exhibit anisotropic and high carrier mobilities and excellent light absorption capabilities in the visible-light and near-infrared regions. Meanwhile, the calculated thermal conductivity (κp) of PH-C5N4 is 63.9 Wm−1K−1 at room temperature, significantly outperforming T-C3N (12.2 Wm−1K−1) and P-C3N (18.9 Wm−1K−1). Phonon scattering rates and Grüneisen parameters confirm the origin for the relatively high κp in PH-C5N4. Our study proposes three tetragonal carbon nitride structures with novel physical properties, which lays a theoretical foundation for the multifunctional applications of 2D carbon nitride materials.

Dynamically tunable highly sensitive sensor based on graphene and black phosphorus composite metamaterial

Focusing on the realization of multiple-detection-point sensors in the mid-infrared band, a dynamically tunable high-sensitive index refraction sensor based on graphene and black phosphorus (BP) composite metamaterial is proposed. By adjusting the height of the grating, the strength of the structural plasmon-induced absorption (PIA) can be enhanced within a certain range. The energy transfer mechanism of the system is analyzed by the coupled mode theory (CMT), the theoretical data of CMT fit well with the FDTD simulation results, which proves that the analysis of the system using the CMT model is correct. The resonant wavelengths of the PIA can be efficiently modulated by changing the Fermi level of graphene and the carrier density of BP. It is worth mentioning that under different environmental refractive indexes, our proposed system has excellent sensing characteristics in the mid-infrared band. The maximum sensitivity and the maximum figure of merit (FOM) are up to 5.174 μm/RIU and 26.449, respectively. This research could play an important role in mid-infrared optical sensors.

Bioactive stem cell-laden 3D nanofibrous scaffolds for tissue engineering

This study presents biomimetic nanoscaffolds composed of electrospun polycaprolactone-collagen (PCL-Coll) nanofibers, loaded with bioactive Arnebia euchroma (AE) extract and stem cells, to develop cell-based tissue engineering constructs. The incorporation of AE extract, known for its antioxidant and anti-inflammatory properties, into the PCL-Coll nanofibers resulted in nanoscaffolds denoted as PCL-Coll/AE0, PCL-Coll/AE5, PCL-Coll/AE10, and PCL-Coll/AE15, corresponding to AE extract concentrations of 0.0, 5.0, 10.0, and 15.0 wt%, respectively. The PCL-Coll/AE nanoscaffolds exhibited high porosity values of 62.81 ± 4.78 %, 59.9 ± 2.10 %, 52.44 ± 2.66 %, and 46.32 ± 1.35 %, respectively, thereby providing an optimal 3D environment for cell attachment and proliferation. Analysis of the AE extract revealed the presence of abundant shikonin, a key bioactive compound, as indicated by its characteristic absorption bands at 490, 520, and 560 nm. FE-SEM data confirmed the homogeneous immobilization of AE compounds within the 3D nanofiber scaffolds, with fibers averaging 316 ± 137 nm in diameter, falling within the range of natural collagen fibers. To evaluate the structural integrity of the fully stem cell-laden scaffolds, we assessed cell growth, cell attachment within the PCL-Coll/AE nanoscaffolds, the cytoprotective effects of AE extract, and the expression levels of stemness-related genes, including Nanog, Rex1, Sox2, Oct4, Klf4, and C-Myc. Real-time PCR assays indicated that key indicators of stemness were upregulated, with average increases from 120 ± 15 % in PCL-Coll/AE0 to 250 ± 30 % in PCL-Coll/AE15 over a two-week period. These upregulations promote cell proliferation and facilitate cell cycle progression. Data indicate that increasing the concentration of bioactive AE extract within the scaffolds enhanced cell adhesion on the scaffold surface and improved cell viability after 7 days of culture, with viability rising from 109 ± 6.15 % in PCL-Coll/AE0 to 145.5 ± 10.11 % in PCL-Coll/AE15. Cytoprotective assays against oxidative stress induced by H₂O₂ revealed relative cell viability for PCL-Coll/AE0, PCL-Coll/AE5, PCL-Coll/AE10, and PCL-Coll/AE15 as 42.78 ± 5.85 %, 49.29 ± 6.79 %, 64.98 ± 3.32 %, and 78.68 ± 3.09 %, respectively. These results correlate with the antioxidant potency of AE extract compounds, particularly shikonin and its derivatives. Therefore, the cell-laden biomimetic PCL-Coll/AE15 scaffolds, which demonstrate sustained stemness features and a continuous local release of bioactive AE compounds, represent a promising candidate for tissue engineering applications.

Spray pyrolysis grown Cu and Ni co-doped ZnO thin films: a study of their structural, optical, wettability, and photocatalytic performance

This study explores the impact of Cu and Ni doping on the structural, wettability, optical, and photocatalytic properties of ZnO thin films. The co-doped thin films, with varying Ni concentrations, were deposited using a spray pyrolysis method onto pre-heated soda lime glass substrates. X-ray diffraction analysis confirmed the hexagonal wurtzite structure with preferred orientation primarily along the (002) plane, while crystallinity decreased with higher Ni concentrations. Scanning electron microscopy reveals a compact, adherent structure in all films, with Ni incorporation altering the surface morphology. Fourier transform infrared spectroscopy identified characteristic absorption bands for metal-oxygen bonds. Optical analysis indicated that all thin films exhibited over 88% average transmittance in the visible region, accompanied by a red shift in the optical bandgap. Photoluminescence spectra exhibited a broad emission band in the visible region, indicating intrinsic and extrinsic defects induced by doping. Co-doping transforms the wettability character of ZnO thin films from hydrophilic to hydrophobic. Finally, the photodegradation efficiency of the thin films against methylene blue under sunlight significantly increases from 72% to 92% with an increase in Ni concentration.

SUB-6 5G NETWORKS: DESIGN OF BUTTON MUSHROOM MIMO ANTENNA AND IT’S INVESTIGATION

The unlicensed National Information Infrastructure radio band (n77, n78, and n46) is taken into consideration for this research work's "Multiple-input-multiple-output (MIMO)" antenna with dual band features. Gradually, the form design of simple single-patch MIMO antennas gives way to four-element MIMO antennas. Four microstrip antennas are integrated using button-like circular caps on the main patches. Reduced ground is also used in the construction of many band characteristics. Excellent isolation can be achieved by using Rectangular Metallic Strip (RMS). The suggested MIMO antenna has the advantage of covering two significant frequency bands. At 3.07 GHz and 6.31 GHz, the antenna system resonates with a total bandwidth of 2.43 GHz. The antenna design uses a FR4 substrate measuring 35 mm by 49 mm by 1.6 mm in thickness. For simulation purposes, Teflon and a specially made SMA connector with a perfect electrical conductor (PEC) are used to enhance impedance matching. An 8.2 mm feed line with an inset feed is also utilized. Research and investigation are conducted on radiation properties, including mean effective gain, envelope correction coefficient, reflection coefficient, and more. Both the reflection and isolation coefficients have values of less than -10 dB, with the former being less than -15 dB. It is a 16.30 dB increase overall. 5G applications will greatly benefit from having this smaller, four-element MIMO antenna.

SUB-6 5G NETWORKS: DESIGN OF BUTTON MUSHROOM MIMO ANTENNA AND IT’S INVESTIGATION

The unlicensed National Information Infrastructure radio band (n77, n78, and n46) is taken into consideration for this research work's "Multiple-input-multiple-output (MIMO)" antenna with dual band features. Gradually, the form design of simple single-patch MIMO antennas gives way to four-element MIMO antennas. Four microstrip antennas are integrated using button-like circular caps on the main patches. Reduced ground is also used in the construction of many band characteristics. Excellent isolation can be achieved by using Rectangular Metallic Strip (RMS). The suggested MIMO antenna has the advantage of covering two significant frequency bands. At 3.07 GHz and 6.31 GHz, the antenna system resonates with a total bandwidth of 2.43 GHz. The antenna design uses a FR4 substrate measuring 35 mm by 49 mm by 1.6 mm in thickness. For simulation purposes, Teflon and a specially made SMA connector with a perfect electrical conductor (PEC) are used to enhance impedance matching. An 8.2 mm feed line with an inset feed is also utilized. Research and investigation are conducted on radiation properties, including mean effective gain, envelope correction coefficient, reflection coefficient, and more. Both the reflection and isolation coefficients have values of less than -10 dB, with the former being less than -15 dB. It is a 16.30 dB increase overall. 5G applications will greatly benefit from having this smaller, four-element MIMO antenna.

Sentinel-2 Multispectral Satellite Remote Sensing Retrieval of Soil Cu Content Changes at Different pH Levels

With the development of multispectral imaging technology, retrieving soil heavy metal content using multispectral remote sensing images has become possible. However, factors such as soil pH and spectral resolution affect the accuracy of model inversion, leading to low precision. In this study, 242 soil samples were collected from a typical area of the Pearl River Delta, and the Cu content in the soil was detected in the laboratory. Simultaneously, Sentinel-2 remote sensing image data were collected, and two-dimensional and three-dimensional spectral indices were established. Constructing independent decision trees based on pH values, using the Successive Projections Algorithm (SPA) combined with the Boruta algorithm to select the characteristic bands for soil Cu content, and this was combined with Optuna automatic hyperparameter optimization for ensemble learning models to establish a model for estimating Cu content in soil. The research results indicated that in the SPA combined with the Boruta feature selection algorithm, the characteristic spectral indices were mainly concentrated in the spectral transformation forms of TBI2 and TBI4. Full-sample modeling lacked predictive ability, but after classifying the samples based on soil pH value, the R2 of the RF and XGBoost models constructed with the samples with pH values between 5.85 and 7.75 was 0.54 and 0.76, respectively, with corresponding RMSE values of 22.48 and 16.12 and RPD values of 1.51 and 2.11. This study shows that the inversion of soil Cu content under different pH conditions exhibits significant differences, and determining the optimal pH range can effectively improve inversion accuracy. This research provides a reference for further achieving the efficient and accurate remote sensing of heavy metal pollution in agricultural soil.

A method for the quantitative analysis of Lycium barbarum polysaccharides (LBPs) using Fourier-transform infrared spectroscopy (FTIR): From theoretical computation to experimental application

Lycium barbarum polysaccharides (LBPs) is one of the most important active substances in Lycium barbarum (LB). It is a challenge to quantitatively determine the content due to their complex structures and lack of suitable reference standard in practice. In this study, a quantitative analysis method of LBPs in LB was established based on Fourier-transform infrared spectroscopy (FTIR). The stretching vibration of CO on the pyranose ring of saccharide at 921 cm−1 was selected as the characteristic absorption band by theoretical calculation, which can’t be impacted by the preparation methods and interfered by the component monosaccharides. The molecular weight CRM of dextran (Mw 63.3 kDa) served as the reference standard. The introducing internal standard (KSCN) can obtain a good precision (RSD = 1.10 %) and effectively compensate for the analysis errors caused by the environment, quality loss and uneven distribution during the tablet pressing processes. The methodological verification suggested that the method had good accuracy according to the recovery rate (96.61 %–105.45 %) and the blank recovery (92.39 %–99.37 %), respectively. The LOD and LOQ of CRMD were 0.10 mg and 0.32 mg, respectively. The polysaccharide content of LB from 24 different regions (0.50–2.54 %) and 10 batches of LB extracts (7.09–10.56 %) determined by the developed method less than the ones using phenol–sulfuric acid assay (1.95 %–4.83 % for LB and 9.83–15.53 % for extracts, respectively). The established method based on FTIR could be served as a supplement to phenol–sulfuric acid assay and a rapid quantitative assay for polysaccharides products. In additional, this study provided a new idea for the quantitative analysis of plant polysaccharides.

Feature Selection and Spectral Indices for Identifying Maize Stress Types

This study aims to identify different types of stress on maize leaves using feature selection and spectral index methods. Spectral data were collected from leaves under heavy metal, water, fertilizer stress, as well as under normal healthy conditions. Preprocessing steps such as continuum removal (CR), standard normal variable (SNV) transformation, multiple scattering correction (MSC), detrend correction (DT), and first-order derivative (FOD) were applied to the raw spectra. Various feature selection methods including ReliefF, chi-square test, recursive feature elimination (FRE), mutual information (MI), random forest (RF), and gradient boosting tree (GBT) were employed to determine the importance scores of different spectral bands, thus identifying sensitive spectral features capable of distinguishing various stress types. Spectral indices for stress type differentiation were constructed using label correlation method. Classification models were built using support vector machine (SVM), K-nearest neighbors (KNN), Gaussian naive Bayes (GNB), extreme gradient boosting (XGBoost), RF, and adaptive boosting (AdaBoost) algorithms. Results indicate that the characteristic spectral bands for differentiating stress types are primarily distributed around the red edge (near 700–800 nm) and water absorption valley (near 1900 nm). Spectral indices constructed using combinations of spectral bands around the near-infrared plateau absorption valley (near 1185 nm) and water absorption valley (near 1460 nm) effectively differentiate maize stress types. Among the modeling classification algorithms, RF and AdaBoost algorithms exhibited optimal performance, demonstrating high classification accuracy on both training and validation sets. These findings hold promise for providing new technical support for maize stress monitoring and diagnosis in agricultural production.