With the advancement of modernization, commoditization and grassroots governance have become important terms. Community governance not only promotes modern democracy but plays a key role in improving community governance capabilities and modernizing the governance system, which is receiving much attention. Despite the expanding number of articles on community governance, few evaluations investigate its evolution, tactics, and future goals. As a result, the particular goal of this study is to provide the findings of a thematic analysis of community governance research. Investigating the skills and procedures needed for practice-based community government. Data for this study were gathered through a thematic assessment of 66 papers published between 2018 and 2023. The pattern required by the researchers was provided by the ATLS.ti23 code used to record the review outcomes. This study proposes six central themes: 1) rural advancement, 2) community (social) capital, 3) public health and order governance, 4) governance technology, 5) sustainable development, and 6) governance model. The research results show that the research trend of community governance should focus on rural advancement, taking rural community governance as the starting point, the dilemma and adjustment of the governance model, community public health and order governance, and digital governance. It will yield new insights into new community governance standards and research trends.

Remote sensing technologies have revolutionized forestry analysis by providing valuable information about forest ecosystems on a large scale. This review article explores the latest advancements in remote sensing tools that leverage optical, thermal, RADAR, and LiDAR data, along with state-of-the-art methods of data processing and analysis. We investigate how these tools, combined with artificial intelligence (AI) techniques and cloud-computing facilities, enhance the analytical outreach and offer new insights in the fields of remote sensing and forestry disciplines. The article aims to provide a comprehensive overview of these advancements, discuss their potential applications, and highlight the challenges and future directions. Through this examination, we demonstrate the immense potential of integrating remote sensing and AI to revolutionize forest management and conservation practices.

This paper presents the state of displacement of a multilayered composite laminate subjected to transverse static load with varying balance, symmetric and anti-symmetric angle-ply and cross-ply staking sequences. Higher-order shear deformation theory (HSDT) is considered in the finite element formulation of nine-noded isoparametric element with seven degrees of freedom at each node. The finite element formulation is transformed into computer codes. A convergence study is carried out first to obtain the optimal mesh size for minimizing the computational time. The maximum deflection at the center of plate for both fixed and simply supported edges is verified with reported literature and a good conformity is found. An attempt has been made to observe the minimum value of maximum deflection in the laminate for attaining the maximum strength of laminate with a suitable combination of stacking sequences with a constant volume of material.

We report on the measurement of the response of Rhodamine 6G (R6G) dye to enhanced local surface plasmon resonance (LSPR) using a plasmonic-active nanostructured thin gold film (PANTF) sensor. This sensor features an active area of approximately ≈ 2.5 × 10¹³ nm² and is immobilized with gold nanourchins (GNU) on a thin gold film substrate (TGFS). The hexane-functionalized TGFS was immobilized with a 90 nm diameter GNU via the strong sulfhydryl group (SH) thiol bond and excited by a 637 nm Raman probe. To collect both Raman and SERS spectra, 10 μL of R6G was used at concentrations of 1 μM (6 × 10¹² molecules) and 10 mM (600 × 10¹⁴ molecules), respectively. FT-NIR showed a higher reflectivity of PANTF than TGFS. SERS was performed three times at three different laser powers for TGFS and PANTF with R6G. Two PANTF substrates were prepared at different GNU incubation times of 10 and 60 min for the purpose of comparison. The code for processing the data was written in Python. The data was filtered using the filtfilt filter from scipy.signals, and baseline corrected using the Improved Asymmetric Least Squares (ISALS) function from the pybaselines.Whittaker library. The results were then normalized using the minmax_scale function from sklearn.preprocessing. Atomic force microscopy (AFM) was used to capture the topography of the substrates. Signals exhibited a stochastic fluctuation in intensity and shape. An average corresponding enhancement factor (EF) of 0.3 × 10⁵ and 0.14 × 10⁵ was determinedforPANTFincubated at 10 and 60 min, respectively.

Among carbon nanoparticles, fullerene has been observed as a unique zero-dimensional hollow molecule. Fullerene has a high surface area and exceptional structural and physical features (optical, electronic, heat, mechanical, and others). Advancements in fullerene have been observed in the form of nanocomposites. Application of fullerene nanocomposites has been found in the membrane sector. This cutting-edge review article basically describes the potential of fullerene nanocomposite membranes for water remediation. Adding fullerene nanoparticles has been found to amend the microstructure and physical features of the nanocomposite membranes in addition to membrane porosity, selectivity, permeation, water flux, desalination, and other significant properties for water remediation. Variations in the designs of fullerene nanocomposites have resulted in greater separations between salts, desired metals, toxic metal ions, microorganisms, etc. Future investigations on ground-breaking fullerene-based membrane materials may overcome several design and performance challenges for advanced applications.