Field Hot Spots Research Articles

Biosynthesis Investigations of Terpenoid, Alkaloid, and Flavonoid Antimicrobial Agents Derived from Medicinal Plants.

The overuse of antibiotics in the past decades has led to the emergence of a large number of drug-resistant microorganisms. In recent years, the infection rate caused by multidrug-resistant microorganisms has been increasing, which has become one of the most challenging problems in modern medicine. Plant-derived secondary metabolites and their derivatives have been identified to display significant antimicrobial abilities with good tolerance and less adverse side effects, potentially having different action mechanisms with antibiotics of microbial origin. Thus, these phyto-antimicrobials have a good prospect in the treatment of multidrug-resistant microorganisms. Terpenoids, alkaloids, and flavonoids made up the predominant part of the currently reported phytochemicals with antimicrobial activities. Synthetic biology research around these compounds is one of the hotspot fields in recent years, which not only has illuminated the biosynthesis pathways of these phyto-antimicrobials but has also offered new methods for their production. In this review, we discuss the biosynthesis investigations of terpenoid, alkaloid, and flavonoid antimicrobial agents—using artemisinin and oleanolic acid (terpenoids), berberine and colchicine (alkaloids), and baicalin (flavonoids) as examples—around their antimicrobial action mechanisms, biosynthesis pathway elucidation, key enzyme identification, and heterologous production, in order to provide useful hints for plant-derived antimicrobial agent discovery and development.

Status, trends and enlightenment of global oil and gas development in 2021

By analyzing the distribution of global oil and gas fields and the reasons why some oil and gas fields are not in production, the distribution characteristics of oil and gas remaining recoverable reserves and their year-on-year changes, the distribution characteristics of oil and gas production and their year-on-year changes, and the development potential of oil and gas to be tapped in 2021, this paper sorts out systematically the current status and characteristics of global oil and gas development, summaries the major trends of global oil and gas development, puts forward enlightenment for international oil and gas cooperation. In 2021, oil and gas fields were widely distributed, the number of non-producing oil and gas fields was large; the whole oil and gas remaining recoverable reserves declined slightly, unconventional oil and gas remaining recoverable reserves dropped significantly; the overall oil and gas production continuously increased, the outputs of key resource-host countries kept year-on-year growth; undeveloped oilfields had abundant reserves and great development potential. Combined with global oil and gas geopolitics, oil and gas industry development trends, oil and gas investment intensity, and the tracking and judgment of hotspot fields, the major trends of global oil and gas development in 2021 are summarized. On this basis, the four aspects of enlightenment and suggestions for international oil and gas cooperation and development strategies are put forward: attach great importance to the obligation of marine abandonment to ensure high-quality and long-term benefit development of offshore oil and gas; adhere to the principle of not going to dangerous and chaotic places, strengthen the concentration of oil and gas assets, and establish multi stable supply bases; based on the multi-scenario demand of natural gas, realize the transformation from integrated collaboration to full oil and gas industry chain development; increase the acquisition of high-quality large-scale assets, and pay attention to the continuous optimization of the shareholding ratio of projects at different stages.

Mapping intellectual structures and research hotspots in the application of artificial intelligence in cancer: A bibliometric analysis.

BackgroundArtificial intelligence (AI) is more and more widely used in cancer, which is of great help to doctors in diagnosis and treatment. This study aims to summarize the current research hotspots in the Application of Artificial Intelligence in Cancer (AAIC) and to assess the research trends in AAIC.MethodsScientific publications for AAIC-related research from 1 January 1998 to 1 July 2022 were obtained from the Web of Science database. The metrics analyses using bibliometrics software included publication, keyword, author, journal, institution, and country. In addition, the blustering analysis on the binary matrix was performed on hot keywords.ResultsThe total number of papers in this study is 1592. The last decade of AAIC research has been divided into a slow development phase (2013-2018) and a rapid development phase (2019-2022). An international collaboration centered in the USA is dedicated to the development and application of AAIC. Li J is the most prolific writer in AAIC. Through clustering analysis and high-frequency keyword research, it has been shown that AI plays a significantly important role in the prediction, diagnosis, treatment and prognosis of cancer. Classification, diagnosis, carcinogenesis, risk, and validation are developing topics. Eight hotspot fields of AAIC were also identified.ConclusionAAIC can benefit cancer patients in diagnosing cancer, assessing the effectiveness of treatment, making a decision, predicting prognosis and saving costs. Future AAIC research may be dedicated to optimizing AI calculation tools, improving accuracy, and promoting AI.

A new method for transformer hot-spot temperature prediction based on dynamic mode decomposition

The Accurate prediction of a hot spot temperature (HST) is critical for ensuring the reliable operation of transformers. The existing HST prediction methods are based on the black-box model. They cannot take into account both the real-time prediction and the acquisition of the winding temperature field, and the prediction results are unexplained. Therefore, a new HST prediction method based on dynamic mode decomposition (DMD) is proposed in this study. First, the electromagnetic-thermal-flow coupling model of a transformer winding temperature field was established for a transient calculation. A simulation snapshot set of the winding temperature field was obtained. DMD and DMD dominant modes selection were then performed on the snapshot set. Finally, the HST and winding temperature field distributions at the subsequent times were predicted by the DMD dominant modes and their revolution laws. By comparing the prediction results of the HST and winding temperature field distribution with the simulation and experimental measurement results, the speed and accuracy of the proposed prediction method were verified. The DMD-based prediction method can predict the HST and winding temperature field distribution in a few seconds and has a clear physical meaning. • Transformer model for analysing electromagnetic-thermal-flow coupling is proposed. • Prediction method based on dynamic mode decomposition is proposed. • Hot-spot temperatures and winding temperature fields of transformers are predicted. • An experimental platform is built to verify the validation of the proposed method.

Numerical investigation of plasmonic bowtie nanorings with embedded nanoantennas for achieving high SEIRA enhancement factors

This paper presents the numerical investigation of several complex plasmonic nanostructures — bowtie nanoring and crossed-bowtie nanoring nanoantennas with embedded bowtie nanoantennas and crossed-bowtie nanoantennas — for surface enhanced infrared absorption (SEIRA) spectroscopy-based substrates. The proposed nanostructures exhibit substantially large SEIRA enhancement factor (∼8.1 × 105) compared to previously reported enhancement factor values for bowtie nanoantennas or nanoring antennas. The plasmonic properties of the proposed nanostructures have been studied by the numerical evaluation of the near-field electromagnetic enhancement at resonant plasmon mode excitation wavelengths in the mid-IR spectral regime. The highest SEIRA enhancement of ∼8.1 × 105 occurs at a wavelength of ∼6800 nm (6.8 μm). A substantial electric field enhancement as large as ∼375, corresponding to SEIRA EF of ∼1.4 × 105 is noted even when the minimum gaps between the plasmonic nanostructures is as large as 10 nm, which can easily be fabricated using the conventional nanolithography techniques. The occurrence of several electric field hotspots due to the presence of plasmonic nanoantennas embedded inside the nanorings was observed, as the electric fields are enhanced in the vicinity of the plasmonic nanostructures being proposed. The multiple electric field hotspots in the proposed nanostructures can lead to larger average electric field enhancement as well as the average SEIRA enhancement for these substrates. Moreover, by embedding plasmonic nanoantenna structures inside the bowtie nanorings and crossed-bowtie nanorings, large spectral tunability of plasmon resonance wavelengths is achieved in the spectral regime from 4 μm to 8 μm. This is done by varying a larger number of spectral parameters that are present in these complex nanostructures. This paper also reports a novel configuration of crossed-bowtie nanoring plasmonic structure exhibiting less polarization dependence of the SEIRA enhancement factor. This structure also exhibits tunability of hotspot positions when the direction of the polarization of the incident light is rotated. The proposed structures in this paper can be fabricated by the state-of-the-art nanofabrication technologies. The proposed structures could find potential applications in chemical and biological sensing and biochemical detection of analyte molecules.

Global trends in research on miRNA-microbiome interaction from 2011 to 2021: A bibliometric analysis.

An increasing number of research suggests that the microRNA (miRNA)–microbiome interaction plays an essential role in host health and diseases. This bibliometric analysis aimed to identify the status of global scientific output, research hotspots, and frontiers regarding the study of miRNA–microbiome interaction over the past decade. We retrieved miRNA–microbiome-related studies published from 2011 to 2021 from the Web of Science Core Collection database; the R package bibliometrix was used to analyze bibliometric indicators, and VOSviewer was used to visualize the field status, hotspots, and research trends of miRNA–microbiome interplay. In total, 590 articles and reviews were collected. A visual analysis of the results showed that significant increase in the number of publications over time. China produced the most papers, and the United States contributed the highest number of citations. Shanghai Jiaotong University and the University of California Davis were the most active institutions in the field. Most publications were published in the areas of biochemistry and molecular biology. Yu Aiming was the most prolific writer, as indicated by the h-index and m-index, and Liu Shirong was the most commonly co-cited author. A paper published in the International Journal of Molecular Sciences in 2017 had the highest number of citations. The keywords “expression” and “gut microbiota” appeared most frequently, and the top three groups of diseases that appeared among keywords were cancer (colorectal, et al.), inflammatory bowel disease (Crohn’s disease and ulcerative colitis), and neurological disorders (anxiety, Parkinson’s disease, et al.). This bibliometric study revealed that most studies have focused on miRNAs (e.g., miR-21, miR-155, and miR-146a), gut microbes (e.g., Escherichia coli, Bifidobacterium, and Fusobacterium nucleatum), and gut bacteria metabolites (e.g., butyric acid), which have the potential to improve the diagnosis, treatment, and prognosis of diseases. We found that therapeutic strategies targeting the miRNA–microbiome axis focus on miRNA drugs produced in vitro; however, some studies suggest that in vivo fermentation can greatly increase the stability and reduce the degradation of miRNA. Therefore, this method is worthy of further research.

Absorption Improvement of the Anapole Metastructure for Sensing Applications

In this paper, a metastructure absorber based on the non-radiating anapole mode is firstly proposed and theoretically demonstrated. The combination of four split rings leads to a classical resonant anapole behavior upon the normally illuminating of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${y}$ </tex-math></inline-formula> -polarized wave, which is originated from the destructive interference of the toroidal and electric dipoles. The results show that a point electric field hotspot with up to 20 times enhancement is strictly confined at the geometric center of the proposed structure in the near field and the absorption in the far-field reaches 50.18% at 1.25 THz. To further effectively enhance the absorption efficiency, an improved version is further presented by inserting two vertical asymmetric split rings on both sides of the first design, in which the strengthened magnetic dipole moments reconfigure the mode coupling of multipolar excitations and greatly enhance the absorption to 98.51% at 1.2 THz, while the confinement of the electric field amplifies to nearly 200 times. In addition, the sensing performance of this improved design for measuring the relative permittivity of the background surrounding from 1 to 1.5 has also been explored with the sensitivity, maximum FOM, minimum detection limit and minimum resolution of 341 GHz/RIU, 11.37, 0.00438 and 0.02481. Such an implementation of the absorption enhancement mechanism based on anapole mode enriches the theoretical framework and provides a new platform for multipole electrodynamics in the fields of ultra-sensitive sensing, label-free detection, optical switch, optical modulation, and so on.

Physically Evocative Meso-Informed Burn Model: Topology of Evolving Hotspot Fields

Reactive burn models for heterogeneous energetic material initiation must account for chemistry as well as microstructure to predict shock-to-detonation transition. Upon transient (strong) shock loading, the collapse of individual voids leads to ignition of hotspots, which then grow and interact to completely consume the surrounding material. This paper shows that a length scale measuring the perimeter of the evolving burn front in a field of hotspots, in combination with a topological function/form factor for the hotspot field, is a key input to a framework for constructing a meso-informed reaction rate model. The approach suggested in this paper provides a route to constructing reaction rate models with only two quantities of interest, viz., the burn front perimeter and burn front velocity, which are physically evocative of the underlying hotspot physics and can be quantified individually using meso-scale simulations. It overcomes the problem of calibrating many free parameters that appear in phenomenological burn models and therefore suggests a route to developing general frameworks for simulation-derived meso-informed burn models.

Plasmonic Nanostructures for Optically Induced Movement

Optical forces generated at the nanoscale using electric field gradients have proven to be a powerful tool for trapping and moving nano-objects in a variety of application fields ranging from aerospace engineering to biology and medicine. Typically, to achieve this optical effect plasmonic resonant cavities that combine localized surface plasmon resonances and propagative surface plasmon polaritons are used. Indeed, these structures allow to engineer the distribution of the excited field hotspots, so inducing a precise movement of the nanoparticles interacting with the plasmonic field. In this paper, starting from the theoretical analysis of the surface plasmons, the potentialities of plasmonic nanostructures are reviewed, analysing the geometric conformation designed according to the application. The configurations with the most interesting performance, among those mentioned in the literature, are described in detail, examining their main characteristics and limitations. Finally, the future development and prospects of these plasmonic nanostructures are discussed.

Gold@Carbon Nitride Yolk and Core-Shell Nanohybrids.

Graphitic carbon nitride (g-C3N4) is a promising conjugated polymer with visible light responsiveness and numerous intriguing characteristics that make it highly beneficial for a myriad of potential applications. A novel design and universal approach for the fabrication of unique plasmonic g-C3N4 nanoscale hybrids, with well-controlled morphology, is presented. A single gold nanoprism is encapsulated within dense or hollow g-C3N4 spheres for the formation of Au@g-C3N4 core-shell and Au@g-C3N4 yolk-shell nanohybrids. Au nanoprisms were chosen duo to the strong (visible range) plasmon resonances and electromagnetic field hotspots formed at their sharp corners. The incorporation of Au nanoprisms into the g-C3N4 nanospheres results in a dramatic ∼threefold rise in the emission of plasmonic g-C3N4 yolk-shell nanohybrids and ∼3.6-fold enhancement of the photocurrent density obtained from the plasmonic g-C3N4 core-shell nanohybrids, when compared with the g-C3N4 hollow nanospheres. Hence, these hybrids can potentially benefit applications in the areas spanning from solar energy harvesting to biomedical imaging and theranostics.

Engineered near- and far-field optical response of dielectric nanostructures using focused cylindrical vector beams

Near- and far-field optical properties of silicon nanostructures under linear polarization (Gaussian beam) and azimuthally or radially focused cylindrical vector beams are investigated by finite-difference time-domain method (FDTD) in Meep open-source software. A python toolkit allowing FDTD simulations in Meep for using those excitation sources is provided. In addition to the preferential excitation of specific electric or magnetic resonance modes as a function of the excitation beam polarization, it is shown in the case of spheroids that shape anisotropy affects the resonance wavelength and the dipole orientation of the magnetic or electric dipole mode. Depending on the spheroid symmetry axis with respect to the electric field orientation, the electric dipole resonance can be split into two peaks, giving quasi-unidirectional scattering, separated by an anapole mode. The optical properties in both far-field (scattering pattern) and near-field (electric and magnetic field hot spots) can be tuned by changing the excitation polarization at a fixed wavelength and selecting properly the spheroid shape and dimensions. These numerical simulations are extended to top-down fabrication-friendly nanostructures such as nanocylinders with circular or elliptic sections.

Mapping nanoscale electric field hotspots of a plasmon–molecule system: A theoretical study

The coherent interaction between localized surface plasmon resonance modes and excitons of a single or a collection of quantum emitters have fueled the development of novel applications in quantum optics and material science. In this work, using first-principles simulations, I analyze the modifications in absorption spectra and electric near-field enhancements in a structure consisting of an aluminum nanotriangle interacting with a varying number of pyridine molecules (placed at the nanotriangle tips) in close proximity. What is more, I find very interesting spatial variation in induced electron density and electric near-field enhancements with a remarkable dependence on the number of interacting pyridine molecules and the direction of light illumination. The obtained results may help to improve our understanding of the light–matter interaction at the sub-nanometer scale. • The coherent interaction between LSPR modes and excitons have fueled the development of novel applications in material science. • We study a nanostructure consisting of an aluminum nanotriangle interacting with a varying number of pyridine molecules. • Our results may help to improve our understanding of the light–matter interaction at the sub-nanometer scale.

Histological Study of Tumour Budding in Colorectal Adenocarcinoma and its Association with Tumor Stage and Nodal Status

Introduction: CRC is commonest human carcinoma and leading causes of cancer-related death worldwide. “Tumor budding” is 4 or more tumor cells in invasive front of colorectal adenocarcinoma glands invading up to adjacent stroma, can act as independent prognostic marker for tumor staging which changes prognosis and further treatment plans&#x0D; Objective: Association of tumor budding with stage of tumour and lymph node status.&#x0D; Methods: This is a retrospective study from Jan 2019 – Jan 2022. H&amp;E sections prepared from resected total/hemi/partial colectomy specimens to assess tumor bud count following International tumour budding consensus conference (ITBCC) 2016 criteria “Tumour budding assessed in 1 hotspot (in a field measuring 0.785 mm2) at the invasive front with average 10 consecutive fields with highest bud count in one field (hotspot) under 200x magnifications (field area=0.785 mm2) using Magnus Decahead microscope. The budding was graded as low (0-4 buds), intermediate (5-9 buds), high (10 or more buds).&#x0D; Results: Analysis done according to ITBCC tumor bud scoring shows increased tumor budding is associated with positive higher tumor grade (p value: 0.026) and stage (p value - 0.024) but not with nodal status (p value: 0.096).&#x0D; Conclusion: Current study shows tumor bud score is associated with positive lymph node status, higher tumor grade and stage. However, the study needs to be validated by a larger sample size and follow up studies.

Analysis of Anapole States in Dielectric Spheres and Application to Near-Field Enhancement

Anapole states in isolated, homogeneous, and isotropic dielectric spheres are studied theoretically in accordance with Mie theory, numerically by full-wave electromagnetic simulations and by measurements at microwave and millimeter-wave frequency. Depending on the size and material properties of the dielectric spheres, the practical limitations of detection and possible applications of nonradiating anapole states are investigated. The electromagnetic signature, generated by anapole states of a spherical dielectric scatterer, in terms of finite extinction cross section, is verified by measurements, for both its electric and magnetic versions, in silicon and alumina spheres, respectively. In addition, the existence and the detection of higher order and hybrid anapole states are demonstrated. Finally, an approach to engineer electric field hotspots in a subwavelength-sized gap between two magnetic anapole coupled alumina ceramic spheres is demonstrated.

Simulation research on ONAN transformer winding temperature field based on temperature rise test

Studying the oil-natural-air-natural (ONAN) transformer?s temperature field distribution characteristics and hot spot temperature rise during operation is a key step to evaluate the thermal insulation life of this type of transformer. Firstly, considering the transverse oil passages between the windings and the guiding effect of the oil baffle on the oil flow, this paper takes 35 kV ONAN transformer windings as the research object, which establishes the corresponding electromagnetic-thermal-fluid coupling model and uses the finite element method to calculate the overall distribution of the internal winding temperature field. The calculation results show that when the ONAN transformer reaches thermal equilibrium, the axial temperature distribution of the windings is extremely uneven due to the influence of the transformer oil flow rate, whose difference between both ends is as high as 17.4?. However, the existence of the oil baffle increases the flow velocity of the inter-turn transverse oil passage to 12 times of the original. Affected by this, the oil temperature difference between the two ends of the oil baffle is as high as 2.42?. Secondly, this paper conducted a short-circuit temperature rise test on the test prototype, and selected the different axial heights (18%, 72%, 96%, etc.) of the windings on both sides of the transformer as the characteristic sample points for embedding temperature measurement fiber for real-time temperature monitoring. After comparison, it is found that the simulation calculation is basically consistent with experiment data, and the relative error of the two is less than 3.3%.

High-Quality Optical Hotspots with Topology-Protected Robustness

Optical hotspots underpin a wide variety of photonic devices ranging from sensing, nonlinear generation to photocatalysis, taking advantage of the strong light–matter interaction at the vicinity of photonic nanostructures. While plasmonic nanostructures have been widely used for strongly localized electromagnetic energy on surfaces, they suffer from high loss and consequently a low quality factor. Resonance-based dielectric structures provide an alternative solution with a larger quality factor, but there is a mismatch between the maximum values of the light confinement (quality factor) and the leakage (intensity in the near-field). Here, we propose to apply the concept of topological photonics to the formation of hotspots, producing them in both topological edge states and topological corner states. The topology secures strong light localization at the surface of the nanostructures where the underlying topological invariant shows a jump, generating a field hotspot with simultaneous increment of quality factor and light intensity. Meanwhile, it leverages a good robustness to fabrication imperfection including fluctuation in shape and misalignment. After a systematic investigation and comparison of the robustness between 1D and 2D topological structures, we conclude that the hotspots from 1D topological edge states promise a fertile playground for emerging applications that require both enhanced light intensity and high spectral resolution.

Integrated Molecular Optomechanics with Hybrid Dielectric-Metallic Resonators.

Molecular optomechanics describes surface-enhanced Raman scattering using the formalism of cavity optomechanics as a parametric coupling of the molecule’s vibrational modes to the plasmonic resonance. Most of the predicted applications require intense electric field hotspots but spectrally narrow resonances, out of reach of standard plasmonic resonances. The Fano lineshapes resulting from the hybridization of dielectric–plasmonic resonators with a broad-band plasmon and narrow-band cavity mode allow reaching strong Raman enhancement with high-Q resonances, paving the way for sideband resolved molecular optomechanics. We extend the molecular optomechanics formalism to describe hybrid dielectric–plasmonic resonators with multiple optical resonances and with both free-space and waveguide addressing. We demonstrate how the Raman enhancement depends on the complex response functions of the hybrid system, and we retrieve the expression of Raman enhancement as a product of pump enhancement and the local density of states. The model allows prediction of the Raman emission ratio into different output ports and enables demonstrating a fully integrated high-Q Raman resonator exploiting multiple cavity modes coupled to the same waveguide.

Mid-Cretaceous Wake seamounts in NW Pacific originate from secondary mantle plumes with Arago hotspot composition

The geochemistry of oceanic intraplate (primarily oceanic island and seamount) lavas can provide essential information on the composition and evolution of their mantle source and geodynamics. Due to very limited rock sampling of the many mid-Cretaceous Wake seamounts in NW Pacific, the mantle source lithology and petrogenesis of their lavas, and the geodynamic mechanism responsible for generating the lavas have not been fully delineated. In order to help resolve these issues, here we present whole-rock major-trace element and Sr-Nd-Pb-Hf isotopic data for twenty-one lava samples collected from Lamont, Dacheng, Xufu, Penglai, Niulang, Zhinyu, and Zhanlu seamounts in the Southern Wake seamount trail (WST). These lava samples are silica-undersaturated alkali basalt and basanites/nephelinite. They have high CaO, FeOT and TiO2 contents and CaO/Al2O3 ratios, consistent with their derivation from partial melting of a carbonated peridotite or reaction between carbonated MORB-eclogite-derived silicate melts and fertile peridotite. High Zr/Hf and negative Zr-Hf-Ti anomalies in the most mafic lavas further suggest a contribution from carbonated components in their mantle source. These lavas show FOZO (focal zone)-HIMU (high μ = 238U/204Pb)-like Sr-Nd-Pb-Hf isotopic compositions (e.g., (206Pb/204Pb)i = 19.36–20.72), falling within the Arago (also known as “Young Rurutu” or “Atiu”) hotspot field. Combined with the sparse previous age and geochemical data, we propose that WST lavas were most likely derived from partial melting of secondary plume clusters emanating from the top of Arago mantle plume trapped at the mantle transition zone. Alternatively, WST lavas could have come from a number of secondary plumelets emanating from the top of the Pacific Large Low Shear Velocity Province (LLSVP). The simultaneously upwelling secondary plumes or plumelets generated chronologically overlapping, compositionally similar and closely-spaced Wake seamounts atop the moving Pacific plate.

Influence through mixing: hotspots as benchmarks for basic black-hole behaviour

Effective theories are being developed for fields outside black holes, often with an unusual open-system feel due to the influence of large number of degrees of freedom that lie out of reach beyond the horizon. What is often difficult when interpreting such theories is the absence of comparisons to simpler systems that share these features. We propose here such a simple model, involving a single external scalar field that mixes in a limited region of space with a ‘hotspot’ containing a large number of hot internal degrees of freedom. Since the model is at heart gaussian it can be solved explicitly, and we do so for the mode functions and correlation functions for the external field once the hotspot fields are traced out. We compare with calculations that work perturbatively in the mixing parameter, and by doing so can precisely identify its domain of validity. We also show how renormalization-group EFT methods can allow some perturbative contributions to be resummed beyond leading order, verifying the result using the exact expression.

Research on the evolution and driving forces of the manufacturing industry during the "13th five-year plan" period in Jiangsu province of China based on natural language processing.

The development of China's manufacturing industry has received global attention. However, research on the distribution pattern, changes, and driving forces of the manufacturing industry has been limited by the accessibility of data. This study proposes a method for classifying based on natural language processing. A case study was conducted employing this method, hotspot detection and driving force analysis, wherein the driving forces industrial development during the "13th Five-Year plan" period in Jiangsu province were determined. The main conclusions of the empirical case study are as follows. 1) Through the acquisition of Amap's point-of-interest (POI, a special point location that commonly used in modern automotive navigation systems.) data, an industry type classification algorithm based on the natural language processing of POI names is proposed, with Jiangsu Province serving as an example. The empirical test shows that the accuracy was 95%, and the kappa coefficient was 0.872. 2) The seven types of manufacturing industries including the pulp and paper (PP) industry, metallurgical chemical (MC) industry, pharmaceutical manufacturing (PM) industry, machinery and electronics (ME) industry, wood furniture (WF) industry, textile clothing (TC) industry, and agricultural and food product processing (AF) industry are drawn through a 1 km× 1km projection grid. The evolution map of the spatial pattern and the density field hotspots are also drawn. 3) After analyzing the driving forces of the changes in the number of manufacturing industries mentioned above, we found that manufacturing base, distance from town, population, GDP per capita, distance from the railway station were the significant driving factors of changes in the manufacturing industries mentioned above. The results of this research can help guide the development of manufacturing industries, maximize the advantages of regional factors and conditions, and provide insight into how the spatial layout of the manufacturing industry could be optimized.