21:I[432972,["/_next/static/chunks/bb923814e1f4d2e9.js","/_next/static/chunks/dd3ee9f5b7716ca6.js","/_next/static/chunks/4204a0ae82542ca8.js","/_next/static/chunks/1270dead247da766.js","/_next/static/chunks/6e1aa89a642f40be.js","/_next/static/chunks/2d7aa753e81324a8.js","/_next/static/chunks/8ffd0b71567920d8.js","/_next/static/chunks/67ea6dfd21f16c5f.js","/_next/static/chunks/24eb4379f68013fd.js","/_next/static/chunks/b8cd775ffdf935bd.js","/_next/static/chunks/983103cd9eb7b428.js","/_next/static/chunks/263f2cdcb9aa2341.js","/_next/static/chunks/294b9525248c8e5f.js"],"default"] 22:T4ad,Quantile, equal interval, and natural breaks methods are widely used data classification methods in geospatial analysis and cartography. However, when applied to data with skewed distributions, they can only reveal the variations of either high frequent values or extremes, which often leads to undesired and biased classification results. To handle this problem, Esri provided a compromise method, named geometric interval classification (GIC). Although GIC performs well for various classification tasks, its mathematics and solution process remain unclear. Moreover, GIC is theoretically only applicable to single-peak (single-modal), one-dimensional data. This paper first mathematically formulates GIC as a general optimization problem subject to equality constraint. We then further adapt such formulated GIC to handle multi-peak and multi-dimensional data. Both thematic data and remote sensing images are used in this study. The comparison with other classification methods demonstrates the advantage of GIC being able to highlight both middle and extreme values. As such, it can be regarded as a general data classification approach for thematic mapping and other geospatial applications.23:T46f,The reverse atom transfer radical polymerization (RATRP) of acrylonitrile (AN) was carried out in N, N-dimethylformamide (DMF) with AIBN as initiator, FeCl₃•6H₂O/triphenylphosphine (PPh₃) and FeCl₃•6H₂O/pentamethyldle-thylenetrlamlne (PMDETA) as catalytic systems, respectively. Effect of reaction time and initiator concentration on polymerization rate, molecular weight and molecular weight distribution were investigated in detail. The Fourier transform infrared spectrometer (FTIR) and ¹H nuclear magnetic resonance spectroscopy (¹HNMR) were employed to analyze the chain end of the PAN. Gel permeation chromatography (GPC) was applied to measure the molecular weight and polydispersity index (PDI) of PAN. The polymerization demonstrated a typical pseudo first-order kinetics characteristics as evidenced by the number-average molecular weights (Mn) increasing linearly with monomer conversion; the Mn decreasing with the increasing of the initiator concentration. Meanwhile, the low PDI value (<1.2) indicated the controllability of polymerization.24:T4b3,Light-management materials play a great significant role in efficient-energy buildings because they reduce indoor energy consumption by adjusting to natural sunlight, enhancing heat insulation, and creating comfortable indoor lighting. Here, we fabricated an ecofriendly and sustainable lignocellulose-based light-management film via a facile homogenization and mechanical hot-pressing method without complicated treatment or toxic reagents. The resulting film exhibited a favorable ultraviolet (UV) blocking performance of 82.25% for UVA, high visible light transmittance, and high haze, with a desirable tensile strength of 197 MPa, which was significantly higher than those of most petroleum-based plastics. Accordingly, the film was further endowed with near-infrared absorption performance by spray-coating with lanthanum hexaboride (LaB₆) nanoparticles─there were almost no adverse effects on its light transmittance or mechanical strength. Meanwhile, the high haze of the film implied that it met the requirement for privacy protection in smart buildings. The MFC/lignin/LaB₆ composite film has potential applications in ener

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1	Engineering	3	3	283
2	Chemical Engineering	2	2	265
3	Chemistry	2	2	265
4	Natural Sciences	1	1	18
5	Data Science	1	1	18

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