Agglomerate Structure Research Articles

Discovering the common latent structure of commercial districts focusing on the spatial co-occurrence relationship between stores

Store agglomeration in a commercial district is considered to follow synergistic and complementary relationships between stores. The micro-interactions, that is, co-occurrence relationships, between stores are thought to create commercial districts’ universality and characteristics. This study aims to empirically identify latent attributes that can explain the mechanism of store agglomeration from the co-occurrence relationships between stores in commercial districts, and to identify universal characteristics in store agglomeration. We represented store agglomeration as a store co-occurrence network with stores as nodes and co-occurrence relationships between stores as links in 10 major commercial districts in Japan. We estimated latent attributes of stores that generated the store co-occurrence network and empirically clarified the quantitative and qualitative nature of store agglomeration. The co-occurrence networks of stores with estimated latent attributes were compared across those of districts, and the co-occurrence patterns common to latent attributes were clarified. The estimated latent attributes were empirically shown to have more explanatory power for the store agglomeration than the conventional business category classification, suggesting their usefulness as a new classification axis for stores. In addition, by comparing 10 districts, common co-occurrence relationships were extracted, and the universal spatial structure of store agglomeration was empirically clarified.

Effect of adding various supplements on physicochemical properties and starch digestibility of cooked rice

This study investigated the physicochemical modifications of cooked rice caused by adding various supplements (rapeseed oil, dried wasabi powder, and dried chili pepper powder). The physicochemical and digestive properties of treated cooked rice were analyzed using multiple techniques to determine the impact of supplements on the rice quality, including its starch digestibility. All samples with added supplements showed an increase in surface firmness (0.77–0.95 kg·m/s2 (N)) and a decrease in thickness (2.23–2.35 mm) and surface adhesiveness (1.43–7.22 J/m3). Compared to the control group, two absorption peaks at 2856 and 1748 cm−1 and new signals at 1683 and 1435 cm−1 appeared in the Fourier transform infrared (FTIR) spectroscopy. Analysis of FTIR results revealed that the interaction force was mainly through noncovalent interactions. Moreover, adding supplements increased the resistant starch (RS) levels in all samples. Scanning electron microscopy (SEM) suggested that oil-enriched phases, proteins, and polyphenols could cause large agglomeration and loose gel structure. These results suggested the formation of amylose-guest molecule complexes, which may influence starch functionality. Our work could provide insight into the starch–supplement interactions and the key factors affecting starch digestibility.

Magnesium nitrate-tricine nanoparticles: Temperature impact to enhancing third order optical nonlinearity

Nano-hybrid promoted as materials with improved optical properties. The aim of this study was to analyze differences in optical properties at micro-scale. This research focuses on the impact of reaction temperature during the creation of magnesium nitrate-tricine nanoparticles through chemical vapor deposition. The study investigates how temperatures of 200°C and 300°C affect the particle size, crystallinity, and morphology of the nanoparticles. Optimizing these properties is essential for achieving the desired third-order NLO effect. By understanding the influence of temperature on nanoparticle characteristics, researchers can develop more effective NLO materials for future photonic devices. This study explores the chemical and structural differences between MNT 300 and MNT 400 materials using various techniques. Spectroscopic analysis reveals similarities in both materials with a shared peak at 1400 cm−1. However, MNT 400 exhibits additional peaks suggesting the presence of aromatic rings, nitro compounds, or variations in N–H bonds. Both MNT 300 and MNT 400 exhibit micro porous behaviour with a narrow pore size distribution around 14 nm to 15 nm, indicating tightly packed structures. Transmission Electron Microscopy analysis shows a wide particle size range (2 nm to 200 nm) in both materials, suggesting the presence of atomic clusters, individual molecules, and potentially agglomerated structures. FT-Raman spectroscopy reveals higher intensity peaks in MNT 400, which could be due to a higher concentration of specific bonds, a more ordered structure, or enhanced Raman scattering. This suggests greater crystallinity or molecular uniformity in MNT 400 compared to MNT 300.

The Relationship Between Three-Dimensional Spatial Structure and CO2 Emission of Urban Agglomerations Based on CNN-RF Modeling: A Case Study in East China

Good urban design helps mitigate carbon dioxide emissions and is important for achieving global low-carbon goals. Previous studies have mostly focused on the two-dimensional level of urban socio-economic activities, urban land use changes, and urban morphology, neglecting the importance of the three-dimensional spatial structure of cities. This study takes 30 cities in East China as an example. By using urban building data and carbon emission datasets, four machine learning algorithms, BP, RF, CNN, and CNN-RF, are established to build a CO2 emission prediction model based on three-dimensional spatial structure, and the main influencing factors are further studied. The results show that the CNN-RF model performed optimally in both the testing and validation phases, with the coefficient of determination (R2), root mean square error (RMSE), and residual prediction deviation (RPD) of 0.85, 0.82; 10.60, 22.32; and 2.53, 1.92, respectively. Meanwhile, in the study unit, S, V, NHB, AN, BCR, SCD, and FAR have a greater impact on CO2 emissions. This indicates a strong correlation between urban three-dimensional spatial structure and carbon emissions. The CNN-RF model can effectively evaluate the relationship between them, providing strategic support for spatial optimization of low-carbon cities.

Can the resource and environmental dilemma due to water-energy-carbon constraints be solved in the process of new urbanization?

The rapid development of basin resource-based cities (BRCs) in developing countries have led to severe resource and environmental problems centered on the “water-energy-carbon” (WEC) nexus. Based on their spatiotemporal evolution, WEC constraints are evaluated via a multidimensional coupling coordination degree (CCD) mode. Resource-environmental efficiency (REE) under these constraints is measured via the superefficiency SBM model. The path of resource and environmental improvement via new urbanization (NU) is discussed based on the spatial econometric model. Water resource consumption in the BRCs decreased by 12.22 %, but energy consumption and carbon emissions increased by 20.1 % and 70.05 %, respectively, and the CCD of the WEC nexus showed a “highly coordinated - seriously imbalanced” change. Therefore, the REE increase of 44.03 % was unsustainable. NU improved REE and reduced water resource consumption but did not reduce energy consumption or carbon emission, and there is significant regional variability. Scientific and technological innovation, economic agglomeration and land structure diversity contributed to the resource-environmental improvement effects of NU, but optimized industrial structures and environmental governance had masking effects. The policy implication is that during NU, efficiency gains must be combined with policies to promote industrial structure optimization and environmental governance and thus achieve sustainable urban development.

How Does the Spatial Structure of Innovation Agglomeration Affect Energy Efficiency? From the Role of Industrial Structure Upgrading

This paper employs the instrumental variable method and the intermediary model to explore the influence of monocentric and polycentric spatial structures of innovation agglomeration on energy efficiency. This paper uses data from 2010 to 2021 in China, and also panel data regression models were used. The findings indicate that the monocentric spatial structure of provincial system innovation agglomeration is primarily concentrated in northeastern and western regions of China, whereas the polycentric spatial structure is mainly distributed in eastern coastal areas. A monocentric spatial structure inhibits the enhancement of energy efficiency, but there is an environmental paradox of excessive resource agglomeration. In contrast, a polycentric spatial structure and its strengthening tendency facilitate the improvement of energy efficiency. A monocentric spatial structure has an inhibitory impact on the improvement of energy efficiency in the three sectors of agriculture, industry, and construction, while a polycentric spatial structure aids it. A monocentric spatial structure further hinders the improvement of energy efficiency by impeding the upgrading of the industrial structure, while the upgrading of the industrial structure driven by the polycentric spatial structure plays a role in enhancing energy efficiency. The policy recommendations of this paper are intended to help coordinate the pace of innovation development between cities, adjust the spatial structure of innovation agglomeration between regions, and promote the upgrading of the comprehensive industrial structure, thereby improving overall energy efficiency.

Mapping the Functional Structure of Urban Agglomerations at the Block Level: A New Spatial Classification That Goes beyond Land Use

Mapping the Functional Structure of Urban Agglomerations at the Block Level: A New Spatial Classification That Goes beyond Land Use

Spatial Evolution and Driving Factors of Ecological Well-Being Performance in the Yellow River Basin

Ecological well-being performance (EWP) is a key indicator of sustainable development and has garnered significant research attention. This study measures the overall and stage-by-stage efficiency of the urban agglomerations in the Yellow River Basin based on the ends–means framework of steady-state economics. This study then delves into the spatiotemporal transfer characteristics of EWP through Moran’s I, and spatial Markov chains. Additionally, this research investigates the factors influencing EWP using a random forest model. The findings indicate a notable enhancement in EWP in the urban agglomerations in the YRB from 2006 to 2021, showing clear spatial agglomeration patterns. The shift in EWP types displays a “path dependence” effect, with distinct evolutionary paths influenced by spatial lag effects. Ecological input emerges as a key internal driver of EWP, while urbanization and technological advancements are highlighted as significant external factors. Industrial agglomeration and industrial structure also contribute to improving EWP. The findings of this study help to clarify the spatial and temporal characteristics of ecological welfare performance and its driving mechanisms in the urban agglomerations of the Yellow River Basin. This is conducive to the achievement of high-quality urban transformation and regional green development, and it provides a reference for the construction of an ecological civilization.

Characterization and source identification of PM2.5 during intense haze episodes in an urban environment of Lahore

In the backdrop of persistent haze occurrences affecting Southeast Asia and Pakistan's environmental landscape, this study delves into an in-depth analysis of atmospheric Particulate Matter (PM2.5) during intense haze episodes prevalent in Lahore throughout October, November, and December 2019. Employing advanced analytical techniques encompassing Scanning Electron Microscopy (SEM) coupled with Energy-Dispersive Spectroscopy (EDX), X-ray Diffraction (XRD), and Raman Spectroscopy (RS), this investigation meticulously scrutinized PM2.5 samples. The findings showcased substantial variability in PM2.5 concentrations, peaking notably in December within the range of 43.2–301 μgm−3, averaging 168 ± 88.3 μgm−3, whereas lower concentrations ranging from 30.9 to 268 μgm−3, with an average of 106 ± 66.1 μgm−3, were observed in October. These concentrations displayed correlations with meteorological parameters, demonstrating a direct association with relative humidity and varying relationships with temperature and wind speed. The maximal PM2.5 concentrations aligned with lower temperatures (19.1 °C), while higher temperatures (26.1 °C) coincided with the lowest concentrations, illustrating distinct relationships with relative humidity percentages and wind speeds. Advanced spectroscopic analyses (RS and XRD) confirmed the presence of various minerals and elements within PM2.5 samples, encompassing calcite, calcium aluminosilicate, hematite, barite, quartz, gypsum, organic carbon, and nineteen elements identified by EDX. Morphological evaluations unveiled diverse particle shapes, from round, pointed, and irregular to rod-like, and agglomerate structures. SEM investigations delineated distinctive groups of anthropogenic and geogenic particles, emphasizing emission sources such as automobile emissions, crop residue burning, biomass burning, construction activities, soil dust, and industrial emissions. This comprehensive study lays the groundwork for source apportionment, vital for understanding consequential impacts on climate, visibility, and human health, fostering future investigations in this domain.

Enhancing flowability of lamivudine through quasi-emulsion solvent-diffusion (QESD) crystallization: A comprehensive study on surfactant impact, particle morphology by QbD concepts and tablet compression challenges

Lamivudine (LMD), an enantiomer of 2′-deoxy-3′-thiacytidine, plays a crucial role in combatting HIV-1 and managing hepatitis B virus infections. Despite its effectiveness, challenges arise from its difficult flowability and tendency to agglomerate during storage, necessitating a granulation step before tablet compression, as direct compression has proven ineffective. This study aimed to optimize Lamivudine spherical agglomerates using response surface methodology, delving into the intricate relationship between design factors (concentration of tween, span, and acetone) and experimental outcomes (yield and particle size) through central composite design. Analysis of variance (ANOVA) was employed for optimization, with the Quasi-emulsion solvent-diffusion (QESD) crystallization technique utilized for the checkpoint batch. This technique, involving a single solvent and antisolvent with surfactants, showcased remarkable enhancements in flowability and reduced storage agglomeration. The impact of various surfactants [Hydroxy Propyl Methyl Cellulose (HPMC), polysorbate 80, and sorbitane monooleate] on particle morphology, flowability, and storage agglomeration during crystallization was thoroughly assessed. While achieving direct compression into tablets, the porous structure of LMD agglomerates presented challenges in tablet press production speeds, prompting adjustments such as reducing punch speed or implementing a precompression step. Positive outcomes were realized for disintegration and in vitro drug release in comparison to direct compression and wet granulation methods. In conclusion, the QESD crystallization technique successfully yielded hollow, spherical LMD agglomerates with enhanced properties, representing a significant milestone in pharmaceutical formulation.

Identifying the Hierarchical Structure of Nighttime Economic Agglomerations Based on the Fusion of Multisource Data

Identifying the Hierarchical Structure of Nighttime Economic Agglomerations Based on the Fusion of Multisource Data

Does the clusters of high-speed railway network match the urban agglomerations? A case study in China

High-speed railways play a crucial role in intercity transportation, shaping the spatial interactions within urban agglomerations. However, a mismatch between transportation clusters and the spatial structure of urban agglomerations hampers regional economic integration. To address this issue, this paper proposes a community classification model, employing the Louvain algorithm, to analyze the aggregation of high-speed railway networks (HSRN). It compares central cities in city clusters with HSRN communities in relevant areas, examining the influence of central cities on urban agglomerations. The model is applied to a case study of China's high-speed railway network. The community classifications of HSRN are then compared with planned or future urban agglomerations at the national, provincial, and civic levels. The findings reveal that HSRN in China exhibits distinct clusters that align with the distribution of urban agglomerations. The existing central cities within these agglomerations provide good service levels in the HSRN network. However, HSRN communities within each urban agglomeration are overly scattered and should be integrated to reduce accessibility inequalities. This study offers suggestions for the development planning of HSRN and contributes to the economic integration of urban agglomerations.

Service sector agglomeration and industrial structure optimisation: evidence from China's resource‐based cities

Service sector agglomeration and industrial structure optimisation: evidence from China's resource‐based cities

Research on urban agglomeration spatial network structure in the middle reaches of the Yangtze River based on real-time traffic accessibility scenario analysis

ABSTRACT Investigating the spatial network structure of urban agglomerations based on traffic accessibility has an important practical significance in accelerating the process of regional integration. Taking urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) as the case study, this study aims to examine the characteristics associated with the spatial network structure based on traffic accessibility and its changes under scenarios of different traffic accessibilities by adopting real-time traffic data, modified gravity model, and social network analysis (SNA). The main conclusions are as follows. Wuhan, Changsha, and Nanchang are the central cities in the spatial network; the spatial network structure of UAMRYR is imbalanced and in the agglomeration stage of regional economic development. With the development of traffic accessibility, resources first gather in the individual center cities and then spread to other cities, and the network tends toward equilibrium.

In-depth characterization of particulate matter in a highly polluted urban environment at the foothills of Himalaya-Karakorum Region.

In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth's system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The present work is carried out over an insufficiently studied but polluted urban area of Peshawar, which lies at the foothills of the famous Himalaya and Karakorum area, Northern Pakistan. The particulate matter with an aerodynamic diameter of less than 10µm, i.e., PM10 are collected and analyzed for mineralogical, morphological, and chemical properties. Diverse techniques were used to examine the PM10 samples, for instance, Fourier transform infrared spectroscopy, x-ray diffraction, and scanning electron microscopy along with energy-dispersive x-ray spectroscopy, proton-induced x-ray emission, and an OC/EC carbon analyzer. The 24h average PM10 mass concentration along with standard deviation was investigated to be 586.83 ± 217.70µg/m3, which was around 13 times greater than the permissible limit of the world health organization (45µg/m3) and 4 times the Pakistan national environmental quality standards for ambient PM10 (150µg/m3). Minerals such as crystalline silicate, carbonate, asbestiform minerals, sulfate, and clay minerals were found using FTIR and XRD investigations. Microscopic examination revealed particles of various shapes, including angular, flaky, rod-like, crystalline, irregular, rounded, porous, chain, spherical, and agglomeration structures. This proved that the particles had geogenic, anthropogenic, and biological origins. The average value of organic carbon, elemental carbon, and total carbon is found to be 91.56 ± 43.17, 6.72 ± 1.99, and 102.41 ± 44.90µg/m3, respectively. Water-soluble ions K+ and OC show a substantial association (R = 0.71). Prominent sources identified using Principle component analysis (PCA) are anthropogenic, crustal, industrial, and electronic combustion. This research paper identified the potential sources of PM10, which are vital for preparing an air quality management plan in the urban environment of Peshawar.

Phytosynthesis and characterization of tin-oxide nanoparticles (SnO2-NPs) from Croton macrostachyus leaf extract and its application under visible light photocatalytic activities

Nanotechnology is rapidly becoming more and more important in today's technological world as the need for industry increases with human well-being. In this study, we synthesized SnO2 nanoparticles (NPs) using an environmentally friendly method or green method from Croton macrostachyus leaf extract, leading to the transformation of UV absorbance to visible absorbance by reducing the band gap energy. The products underwent UV, FTIR, XRD, SEM, EDX, XPS, BET, and DLS for characterization. Characterization via UV–Vis spectroscopy confirmed the shift in absorbance towards the visible spectrum, indicating the potential for enhanced photocatalytic activity under visible light irradiation. The energy band gap for as-synthesized nanoparticles was 3.03 eV, 2.71 eV, 2.61 eV, and 2.41 eV for the 1:1, 1:2, 1:3, and 1:4 sample ratios, respectively. The average crystal size of 32.18 nm and very fine flakes with tiny agglomerate structures of nanoparticles was obtained. The photocatalytic activity of the green-synthesized SnO2 nanoparticles was explored under visible light irradiation for the degradation of rhodamine B (RhB) and methylene blue (MB), which were widespread fabric pollutants. It was finally confirmed that the prepared NPs were actively used for photocatalytic degradation. Our results suggest the promising application of these green-synthesized SnO2 NPs as efficient photocatalysts for environmental remediation with low energy consumption compared to other light-driven processes. The radical scavenging experiment proved that hydroxyl radicals (_OH) are the predominant species in the reaction kinetics of both pollutant dyes under visible light degradation.

The Influence of the Spatial Structure of Urban Agglomeration on the Digital Economy and Its Impact Mechanism: Evidence From China

The urban agglomeration (UA), as the carrier of regional economic transformation, is an important impetus for the development of the digital economy (DE) in the future. Based on the perspective of the spatial structure of UA, this paper first attempts to clarify the theoretical aspects of the influence of the spatial structure on DE, its heterogeneous characteristics, and inner impact mechanism, and then empirically test the corresponding hypotheses by utilizing the data on China’s 18 UAs from 2011 to 2019. Our findings are as follows: (1) The monocentric structure has an inverted “U-shaped” impact on DE, namely, first promotion and then inhibition effects. (2) Heterogeneity analysis reveals that the inverted “U-shaped” relationship between the monocentric structure and DE is not observed in UAs lacking megacities and is insignificant during the early and middle development phases of UAs. However, this non-linear relationship becomes significant in UAs with megacities and UAs in mature and later development stages. (3) More deeply, this study uncovers that innovation serves as a mediating factor in the influence of the monocentric structure on DE. This article not only enriches the existing body of research on UAs and DE but also provides valuable theoretical insights for the development of DE within UAs.

Fragmentation and reorganization of agglomerates in catalyst inks: Understanding the time-scale and temperature-dependent effects on the dispersion process

The time and temperature of the dispersive shear process of catalyst inks have a great influence on the agglomerate structure of the ink and the rheological properties of the ink. In this paper, three different catalyst inks were prepared at 20 °C, 30 °C and 40 °C, and tested using characterization such as rheological techniques, zeta (ξ) potential, and particle size measurements. As the temperature rises, the median particle size inside the ink at the end of shear was 400, 308.05 and 157.3 nm, and the zeta potential was −37, −33 and −25 mV, with a decrease in viscosity and a deterioration in thixotropy. The catalyst layers prepared from inks dispersed at different temperatures had the smallest cracks and the flattest surface at 30 °C, and the largest cracks, the largest contact angle, the roughest surface, and the poorest polarization properties at 40 °C. Through the comprehensive analysis of the experimental data, the fragmentation and reorganization processes of agglomerates during the internal dispersion of catalyst ink were revealed from the perspectives of time scale and temperature variation, respectively. This study provides an experimental basis for a deeper understanding of the dispersion performance of catalyst ink at different temperatures.

Energy-efficient scientific-technological approaches to the processing of plastic waste PET, PE, PP, PS to produce hydrogen-containing gas and titanium carbide powder

The paper considers gaseous products, structure and phase composition of hard products resulting from high-temperature exothermic reactions between Ti–PET–(PE, PP, PS) system components, depending on the content of oxygen-free polymers polyethylene (PE), polypropylene (PP), and polystyrene (PS) in the initial blend. It is found that the addition of PE, PP, PS polymers to the Ti–PET system increases the hydrogen content from 45 to 62 vol% and reduces the carbon monoxide content from 38 to 20 vol% in gaseous products. According to calculations, the adiabatic flame temperature of the synthesized gas in air is very close to that of pure hydrogen. The synthesized gas can therefore be used as ecological fuel for energy sources. On the other hand, oxygen-free polymers presenting in the system provide the formation of substoichiometric carbide TiC0.75. Its hardness is not lower than that of stoichiometric TiC and even exceeds widely used carbides and borides of transition metals. In addition, the agglomerate structure of synthesized TiC0.75 allows to apply it as a promising ecological basis for highly-efficient abrasive pastes, in particular for polishing and finishing fabricated metal products.

How Does the Spatial Structure of Urban Agglomerations Affect the Spatiotemporal Evolution of Population Aging?

China has fully become an aging society, and the scientific response to population aging has become a major task that the country must face in the future. Research on population aging in the Chengdu-Chongqing urban agglomeration (CCUA) can provide a scientific basis for future population management in the CCUA. This paper applies spatial autocorrelation, geodetection, and other methods to analyze the temporal and spatial pattern of population aging and its driving factors in the CCUA from 2000 to 2020, taking districts (counties) as the basic unit and combining them with the spatial structure of the urban agglomeration. The results show that: ① in the time dimension, the population aging in CCUA has gone through the evolution process of “mild–moderate–heavy”; in the spatial dimension, the influence of the urban agglomeration’s development planning axes on the spatial differentiation of the aging population has become more and more prominent. ② The aging level has a strong spatial correlation, and with time, the spatial correlation has changed from weak to strong, and the spatial difference has increased. The dual core city shows a typical spatial pattern of a decreasing aging level in the core area and an increasing aging level in the peripheral area, and the heavily aging area is spreading along the axis. ③ The overall aging speed is high, and the aging speeds of the core cities and node cities are lower than those of other regions. There is a clearer positive correlation between the aging level and the speed of aging, showing the characteristic of “the older the faster”. ④ Endogenous factors such as the aging level and fertility level at the beginning of the period have a significant determining power on the change in the aging level, while exogenous factors such as the in-migration rate and the out-migration rate have a persistent determining power on the urban agglomerations and key areas (core cities, central cities, main axes of development, city belts, and dense urban areas).