19,617 research outputs found
Impurity scattering and Friedel oscillations in mono-layer black phosphorus
We study the effect of impurity scattering effect in black phosphorurene (BP)
in this work. For single impurity, we calculate impurity induced local density
of states (LDOS) in momentum space numerically based on tight-binding
Hamiltonian. In real space, we calculate LDOS and Friedel oscillation
analytically. LDOS shows strong anisotropy in BP. Many impurities in BP are
investigated using -matrix approximation when the density is low. Midgap
states appear in band gap with peaks in DOS. The peaks of midgap states are
dependent on impurity potential. For finite positive potential, the impurity
tends to bind negative charge carriers and vise versa. The infinite impurity
potential problem is related to chiral symmetry in BP
Fiber Based Multiple-Access Optical Frequency Dissemination
We demonstrate a fiber based multiple-access optical frequency dissemination
scheme. Without using any additional laser sources, we reproduce the stable
disseminated frequency at an arbitrary point of fiber link. Relative frequency
stability of 3E10^{-16}/s and 4E10^{-18}/10^4s is obtained. A branching fiber
network for highly-precision synchronization of optical frequency is made
possible by this method and its applications are discussed.Comment: 5 pages, 3 figure
Dual-mode mechanical resonance of individual ZnO nanobelts
Β©2003 American Institute of Physics. The electronic version of this article is the complete one and can be found online at: http://link.aip.org/link/?APPLAB/82/4806/1DOI:10.1063/1.1587878The mechanical resonance of a single ZnO nanobelt, induced by an alternative electric field, was studied by in situ transmission electron microscopy. Due to the rectangular cross section of the nanobelt, two fundamental resonance modes have been observed corresponding to two orthogonal transverse vibration directions, showing the versatile applications of nanobelts as nanocantilevers and nanoresonators. The bending modulus of the ZnO nanobelts was measured to be ~52 GPa and the damping time constant of the resonance in a vacuum of 5Γ10β8 Torr was ~1.2 ms and quality factor Q = 500
Existence problem of proton semi-bubble structure in the state of Si
The fully self-consistent Hartree-Fock (HF) plus random phase approximation
(RPA) based on Skyrme-type interaction is used to study the existence problem
of proton semi-bubble structure in the state of Si. The
experimental excitation energy and the B(E2) strength of the state in
Si can be reproduced quite well. The tensor effect is also studied. It
is shown that the tensor interaction has a notable impact on the excitation
energy of the state and a small effect on the B(E2) value. Besides, its
effect on the density distributions in the ground and state of
Si is negligible. Our present results with T36 and T44 show that the
state of Si is mainly caused by proton transiton from orbit to orbit, and the existence of a proton
semi-bubble structure in this state is very unlikely.Comment: 6 pages, 3 figures, 3 table
Celecoxib inhibits tumor growth and angiogenesis in an orthotopic implantation tumor model of human colon cancer
Aim: To examine the effect of celecoxib on tumor growth and angiogenesis in an orthotopic implantation tumor model of colon cancer. Methods: Human colorectal adenocarcinoma HT-29 cells were implanted subcutaneously in nude mice. Four groups of animals received different doses of celecoxib after tumor implantation. After 42 days, all animals were evaluated for changes in body weight, the volume and weight of colorectal tumors, and tumor growth inhibition. The content of prostaglandin E2 (PGE2) in the tumor tissue homogenate was estimated by radioimmunoassay (RIA). Cyclooxygenase-2 (COX-2) and CD34 expression in tumor tissue was assessed by immunohistochemistry, and the microvessel density (MVD) of tumor tissue was determined. Apoptosis of the tumor cells was detected by the terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL). The expression of vascular endothelial growth factor (VEGF) mRNA and matrix metalloproteinase-2 (MMP-2) mRNA extracted from the tumor tissue was analyzed by reverse transcriptase polymerase chain reaction (RT-PCR). Results: There was no statistically significant change in the animalsβ body weight between the treatment groups. However, with increasing doses of celecoxib, the volume and weight of the tumor decreased. The rates of tumor growth inhibition for the L (low), M (medium) and H (high) groups were 25.30%, 38.80%, and 76.92%, respectively, which were significant compared to the C (control) group. There were significant differences in COX-2 expression in the tumor tissue between all groups, except between the L and M groups. Celecoxib exposure also reduced PGE2 levels in the tumor tissue homogenates. The level of PGE2 correlated to the weight of tumor (r = 0.8814, P < 0.05) and to COX-2 expression (r = 0.8249, P < 0.05). Compared to the control group, the tumor cells from celecoxib-treated mice had a significantly higher apoptotic index. Celecoxib also decreased CD34+ expression in tumors from treated mice. There were significant differences in the MVD between all groups except between groups H and M. Celecoxib significantly reduced the expression of VEGF and MMP-2 mRNA in the group H but not in L and M groups. The MVD in tumor tissue was closely related to the PGE2 levels, as well as the expression of VEGF and MMP-2 mRNA (r = 0.9006, r = 0.8573 and r = 0.6427, respectively; P < 0.05). Conclusions: By inhibiting COX-2, PGE2 synthesis, and VEGF and MMP-2 mRNA expression in tumor tissue, celecoxib enhances tumor cell apoptosis, thereby inhibiting the growth and angiogenesis of orthotopically implanted tumors in a mouse model of human colorectal cancer.Π¦Π΅Π»Ρ: ΠΈΠ·ΡΡΠΈΡΡ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠ΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ±Π° Π½Π° ΡΠΎΡΡ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΠΈ Π°Π½Π³ΠΈΠΎΠ³Π΅Π½Π΅Π· Π² ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΎΡΡΠΎΠΏΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΈΠΌΠΏΠ»Π°Π½ΡΠ°ΡΠΈΠΈ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΡΠΎΠ»ΡΡΠΎΠΉ ΠΊΠΈΡΠΊΠΈ
ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ°. ΠΠ΅ΡΠΎΠ΄Ρ: ΠΊΠ»Π΅ΡΠΊΠΈ ΠΊΠΎΠ»ΠΎΡΠ΅ΠΊΡΠ°Π»ΡΠ½ΠΎΠΉ Π°Π΄Π΅Π½ΠΎΠΊΠ°ΡΡΠΈΠ½ΠΎΠΌΡ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ° ΠT-29 ΠΏΠΎΠ΄ΠΊΠΎΠΆΠ½ΠΎ ΠΈΠΌΠΏΠ»Π°Π½ΡΠΈΡΠΎΠ²Π°Π»ΠΈ Π±Π΅ΡΡΠΈΠΌΡΡΠ½ΡΠΌ ΠΌΡΡΠ°ΠΌ.
ΠΠΎΡΠ»Π΅ ΠΈΠΌΠΏΠ»Π°Π½ΡΠ°ΡΠΈΠΈ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΡΠ΅ΡΡΡΠ΅ Π³ΡΡΠΏΠΏΡ ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
ΠΏΠΎΠ»ΡΡΠ°Π»ΠΈ ΡΠ°Π·Π½ΡΠ΅ Π΄ΠΎΠ·Ρ ΡΠ΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ±Π°. Π§Π΅ΡΠ΅Π· 42 Π΄Π½Ρ ΠΈΠ·ΡΡΠ°Π»ΠΈ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ
Π²Π΅ΡΠ° ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
, ΠΎΠ±ΡΠ΅ΠΌ ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ, ΡΡΡΠ΅ΠΊΡ ΠΈΠ½Π³ΠΈΠ±ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΠΎΡΡΠ° ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ. Π‘ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠ°Π΄ΠΈΠΎΠΈΠΌΠΌΡΠ½Π½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΠΈΠ·Π° (RIA) Π² Π³ΠΎΠΌΠΎ- RIA) Π² Π³ΠΎΠΌΠΎ ) Π² Π³ΠΎΠΌΠΎΠ³Π΅Π½Π°ΡΠ΅
ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»ΠΈ ΡΠΎΠ΄Π΅ΡΠΆΠ°Π½ΠΈΠ΅ ΠΏΡΠΎΡΡΠΎΠ³Π»Π°Π½Π΄ΠΈΠ½Π° E2
(PGE2
). Π ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ ΠΈΠΌΠΌΡΠ½ΠΎΠ³ΠΈΡΡΠΎΡ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ
Π²ΡΡΠ²Π»ΡΠ»ΠΈ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΡ ΡΠΈΠΊΠ»ΠΎΠΎΠΊΡΠΈΠ³Π΅Π½Π°Π·Ρ-2 (COX-2) ΠΈ CD34 ΠΈ ΠΎΡΠ΅Π½ΠΈΠ²Π°Π»ΠΈ ΠΏΠ»ΠΎΡΠ½ΠΎΡΡΡ ΠΌΠΈΠΊΡΠΎΡΠΎΡΡΠ΄ΠΎΠ² (MVD). ΠΠΏΠΎΠΏΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠ΅
ΠΊΠ»Π΅ΡΠΊΠΈ Π²ΡΡΠ²Π»ΡΠ»ΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ TUNEL. ΠΠΊΡΠΏΡΠ΅ΡΡΠΈΡ ΠΌΠ ΠΠ ΡΠ°ΠΊΡΠΎΡΠ° ΡΠΎΡΡΠ° ΡΠ½Π΄ΠΎΡΠ΅Π»ΠΈΡ ΡΠΎΡΡΠ΄ΠΎΠ² (VEGF) ΠΈ ΠΌΠ΅ΡΠ°Π»Π»ΠΎΠΏΡΠΎΡΠ΅ΠΈΠ½Π°Π·Ρ-2
(MMP-2) Π² ΠΎΠΏΡΡ
ΠΎΠ»ΡΡ
ΠΏΡΠΎΠ°Π½Π°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ ΠΎΠ±ΡΠ°ΡΠ½ΠΎΠΉ ΡΡΠ°Π½ΡΠΊΡΠΈΠΏΡΠ°Π·Π½ΠΎΠΉ ΡΠ΅Π°ΠΊΡΠΈΠΈ (RT-PCR). Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ: ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ
Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΡΡ
ΡΠ°Π·Π»ΠΈΡΠΈΠΉ Π² Π²Π΅ΡΠ΅ ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
ΠΌΠ΅ΠΆΠ΄Ρ ΡΠ°Π·Π½ΡΠΌΠΈ Π³ΡΡΠΏΠΏΠ°ΠΌΠΈ ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΎ Π½Π΅ Π±ΡΠ»ΠΎ. ΠΡΠΎ ΠΆΠ΅ Π²ΡΠ΅ΠΌΡ, Ρ ΡΠ²Π΅Π»ΠΈΡΠ΅Π½ΠΈΠ΅ΠΌ
Π΄ΠΎΠ·Ρ ΡΠ΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ±Π° ΠΎΠ±ΡΠ΅ΠΌ ΠΈ Π²Π΅Ρ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΡΠΌΠ΅Π½ΡΡΠ°Π»ΡΡ. ΠΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΊΠΎΠ½ΡΡΠΎΠ»ΡΠ½ΠΎΠΉ Π³ΡΡΠΏΠΏΠΎΠΉ (C), ΡΠΎΡΡ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ
Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΠΎ ΠΈΠ½Π³ΠΈΠ±ΠΈΡΠΎΠ²Π°Π»ΡΡ Π² L (Π½ΠΈΠ·ΠΊΠ°Ρ Π΄ΠΎΠ·Π°), M (ΡΡΠ΅Π΄Π½ΡΡ Π΄ΠΎΠ·Π°) ΠΈ H (Π²ΡΡΠΎΠΊΠ°Ρ Π΄ΠΎΠ·Π°) Π³ΡΡΠΏΠΏΠ°Ρ
ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
Π½Π° 25,30%, 38,80% ΠΈ
76,92% ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ. ΠΡΠ»ΠΈ ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½Ρ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ ΠΎΡΠ»ΠΈΡΠΈΡ Π² ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ COX-2 Π² ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΡΠΊΠ°Π½ΡΡ
ΠΌΠ΅ΠΆΠ΄Ρ Π²ΡΠ΅ΠΌΠΈ
Π³ΡΡΠΏΠΏΠ°ΠΌΠΈ ΠΆΠΈΠ²ΠΎΡΠ½ΡΡ
, ΠΊΡΠΎΠΌΠ΅ Π³ΡΡΠΏΠΏ L ΠΈ M. ΠΡΠ»ΠΎ ΠΏΠΎΠΊΠ°Π·Π°Π½ΠΎ ΡΠ΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ±-Π·Π°Π²ΠΈΡΠΈΠΌΠΎΠ΅ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΠ΅ ΡΡΠΎΠ²Π½Ρ PGE2
Π² Π³ΠΎΠΌΠΎΠ³Π΅Π½Π°ΡΠ°Ρ
ΠΎΠΏΡΡ
ΠΎΠ»Π΅ΠΉ. Π£ΡΠΎΠ²Π΅Π½Ρ PGE2
ΠΊΠΎΡΡΠ΅Π»ΠΈΡΠΎΠ²Π°Π» Ρ Π²Π΅ΡΠΎΠΌ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ (r = 0,8814, P < 0,05) ΠΈ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠ΅ΠΉ COX-2 (r = 0,8249, P < 0,05).
ΠΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ ΠΊΠΎΠ½ΡΡΠΎΠ»ΡΠ½ΠΎΠΉ Π³ΡΡΠΏΠΏΠΎΠΉ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΠ΅ ΠΊΠ»Π΅ΡΠΊΠΈ ΠΌΡΡΠ΅ΠΉ, ΠΏΠΎΠ»ΡΡΠ°Π²ΡΠΈΡ
ΡΠ΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ±, ΠΈΠΌΠ΅Π»ΠΈ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎ Π±ΠΎΠ»Π΅Π΅ Π²ΡΡΠΎΠΊΠΈΠΉ
Π°ΠΏΠΎΠΏΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΈΠ½Π΄Π΅ΠΊΡ. Π¦Π΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ± ΡΠ°ΠΊΠΆΠ΅ ΡΠ½ΠΈΠΆΠ°Π» ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΡ CD34+ Π½Π° ΠΏΠΎΠ²Π΅ΡΡ
Π½ΠΎΡΡΠΈ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΎΠΊ. ΠΡΠ»ΠΈ ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½Ρ
ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈ Π΄ΠΎΡΡΠΎΠ²Π΅ΡΠ½ΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡ Π² MVD ΠΌΠ΅ΠΆΠ΄Ρ Π²ΡΠ΅ΠΌΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½Π½ΡΠΌΠΈ Π³ΡΡΠΏΠΏΠ°ΠΌΠΈ, ΠΊΡΠΎΠΌΠ΅ H ΠΈ M. Π¦Π΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ± ΡΠΏΠΎΡΠΎΠ±ΡΡΠ²ΠΎΠ²Π°Π»
ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΡ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ ΠΌΠ ΠΠ VEGF ΠΈ MMP-2 Π² Π³ΡΡΠΏΠΏΠ΅ Π, Π½ΠΎ Π½Π΅ Π² Π³ΡΡΠΏΠΏΠ°Ρ
L ΠΈ M. MVD Π² ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ ΠΊΠΎΡΠ΅Π»Π»ΠΈΡΠΎΠ²Π°Π» Ρ
ΡΡΠΎΠ²Π½Π΅ΠΌ PGE2
, Π° ΡΠ°ΠΊΠΆΠ΅ Ρ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠ΅ΠΉ ΠΌΠ ΠΠ VEGF ΠΈ MMP-2 (r = 0,9006, r = 0,8573 ΠΈ r = 0,6427 ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ; P < 0,05).
ΠΡΠ²ΠΎΠ΄Ρ: ΡΠ΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ± ΡΠΏΠΎΡΠΎΠ±ΡΡΠ²ΡΠ΅Ρ Π°ΠΏΠΎΠΏΡΠΎΠ·Ρ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΎΠΊ, ΠΈΠ½Π³ΠΈΠ±ΠΈΡΡΠ΅Ρ ΡΠΎΡΡ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ ΠΈ Π°Π½Π³ΠΈΠΎΠ³Π΅Π½Π΅Π· ΠΏΡΠΈ ΠΎΡΡΠΎΡΠΎΠΏΠΈΡΠ΅ΡΠΊΠΎΠΉ
ΠΈΠΌΠΏΠ»Π°Π½ΡΠ°ΡΠΈΠΈ ΠΌΡΡΠ°ΠΌ ΠΊΠΎΠ»ΠΎΡΠ΅ΠΊΡΠ°Π»ΡΠ½ΠΎΠΉ Π°Π΄Π΅Π½ΠΎΠΊΠ°ΡΡΠΈΠ½ΠΎΠΌΡ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠ°. Π’Π°ΠΊΠΎΠΉ ΡΡΡΠ΅ΠΊΡ ΡΠ΅Π»Π΅ΠΊΠΎΠΊΡΠΈΠ±Π° ΡΠ²ΡΠ·Π°Π½ Ρ ΡΠ³Π½Π΅ΡΠ΅Π½ΠΈΠ΅ΠΌ ΡΠΈΠ½ΡΠ΅Π·Π°
COX-2, PGE2 ΠΈ ΡΠΊΡΠΏΡΠ΅ΡΡΠΈΠΈ ΠΌΠ ΠΠ VEGF ΠΈ MMP-2 Π² ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ
Characterization of the mesostructural organization of cement particles in fresh cement paste
Comparative study on the mesostructures of fresh cement paste (FCP) in different dispersion mediums was carried out aiming at characterizing the structural organization of cement particles in FCP at a mesoscopic scale and establishing the correlation of mesostructure with rheological properties. For the first time, Morphologi G3 was adopted to in-situ characterize the mesostructure of FCP. Several dispersion mediums including air, deionized water, ethanol and an aqueous solution of ethanol were chosen to study the dispersion of cement particles in the selected mediums. Superplasticizers, as dispersing aids for cement particles, were added to change the dispersion of cement particles. Results show that Morphologi G3 with the high sensitivity and the high resolution is a powerful tool for in-situ characterization of the mesostructure of FCP by providing high-quality images associated with structural parameters. The structural parameters including particle size, circularity and fractal dimension of particle spatial distribution (Dpd) allow to quantitatively characterize the organization of cement particles in FCP at a mesoscopic scale, through which the relationship between the mesostructure and the rheological behavior of FCP was established. Higher fluidity signifies larger Dpd and circularity but a lower mean particle size. Moreover, the mean particle size and Dpd are more sensitive to indicate the fluidity change
Air pollution forecasts: An overview
Β© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies
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