Structural Decomposition Research Articles

Provincial marine carbon sink transfer in China: structural drivers and key consumption pathways

The ocean is the largest carbon sink on Earth and an important pathway to China achieving carbon neutrality. From a consumption perspective, studying the capacity of marine carbon sink in each of China’s provinces and its inter-regional transfer is of great significance in harnessing the increase in ocean carbon sink driven by final demand. This article first calculates the production-side carbon sink in coastal provinces. Then, based on the 2007, 2012, 2015, and 2017 Chinese inter-regional input-output tables, each province’s consumption-side marine carbon sink is calculated. The article further examines the influencing factors and key transfer paths for the growth of marine carbon sink through Structural Decomposition Analysis (SDA) and Structural Path Analysis (SPA) methods. The results show that each province’s total consumption-side carbon sink continues to rise, with significant regional disparities, demonstrating a trend of higher carbon sink in coastal provinces than inland provinces. Among the nine coastal provinces, Hainan and Guangdong are in a net input state regarding carbon sink transfer, while the other seven are in a net output state. SDA results indicate that the carbon sink intensity effect and the consumption demand effect are important factors inhibiting and promoting carbon sink growth, respectively, while the influence of the input-output technical effect is weak and variable. SPA analysis reveals that carbon sink outputs are primarily transferred to the food and tobacco sector, the agricultural and forestry products and services sector, and the wood processing and furniture industry. The key transfer paths mostly occur within a province, with a relatively small proportion of interprovincial transfer paths. Based on the research findings, this article suggests steadily increasing the proportion of marine product consumption, actively expanding the value chain of shellfish and seaweed industries, continuously strengthening coordination between land and marine industries, and further promoting the domestic circulation of marine carbon sinks.

Tetracycline degradation in the system of peracetic acid activation by liquid discharge plasma

The oxidative degradation ability of peracetic acid (PAA) for organic pollutants can be enhanced by different activation methods. This study investigated the degradation efficiency and mechanisms of tetracycline (TC) using PAA activated by liquid-phase discharge plasma. An 86.08 % degradation efficiency for TC after 60 min treatment was achieved in the Plasma/PAA system, much higher than that of the sole Plasma (46.64 %) and PAA (15.19 %). Acidic conditions and neutral conditions were more favorable for TC removal than alkaline conditions. Inorganic ions generally inhibited TC degradation, though notably, low concentrations of Cl− and NO3− promoted it. Free radical quenching experiments and electron paramagnetic resonance (EPR) analysis confirmed the crucial roles of OH, RO, and 1O2 in TC degradation. Three-dimensional fluorescence spectroscopy (3DFS) and ultraviolet–visible absorption spectroscopy (UV–VIS) elucidated the TC degradation mechanism, revealing key aspects of antibiotic structural decomposition. Further analysis of the degradation products by liquid chromatography-mass spectrometry (LC-MS) indicated three potential degradation pathways. Biotoxicity evaluations indicated that the synergistic system significantly reduced the biotoxicity of the degradation products. This study demonstrated an efficient method for plasma-activated PAA in degrading persistent pharmaceutical pollutants. It also confirmed the system’s applicability across a broad spectrum of organic pollutants and water bodies, highlighting its potential for a wide range of environmental protection applications.

Patterning strategies in grade 1 students with low and high number sense proficiency

AbstractRepeating patterning proficiency predicts students’ later mathematical proficiency. A comparative multi-case design enabled the present study to compare patterning success and strategy use for repeating patterns of 75 Norwegian 6-year-old grade 1 students. We provided the students with duplicate, extend, transfer, and unit isolation activities in a semi-structured, task-based interview that was video-recorded. The students’ number sense was also measured using a digital assessment. In-depth analysis of 52 students (divided evenly into two groups based on their number sense scores, lowest and highest) was performed. A statistically significant group difference was found for extend activities. Multimodal video analysis of strategies employed revealed that both student groups used recursive and different strategies and only students with high number sense used relational strategies. The students with low number sense used more variants of recursive patterning strategies. Our findings also demonstrated that attention to pattern features may both hinder identification of a pattern’s underlying structure and reflect advanced strategy use rather than not showing pattern awareness. We discuss group differences in terms of decomposition and awareness of mathematical pattern and structure and emphasise the need for scaffolding awareness of mathematical pattern and structure through communication.

A scalable synergy-first backbone decomposition of higher-order structures in complex systems

In the last decade, there has been an explosion of interest in the field of multivariate information theory and the study of emergent, higher-order interactions. These “synergistic” dependencies reflect information that is in the “whole” but not any of the “parts.” Arguably the most successful framework for exploring synergies is the partial information decomposition (PID). Despite its considerable power, the PID has a number of limitations that restrict its general applicability. Subsequently, other heuristic measures, such as the O-information, have been introduced, although these measures typically only provide a summary statistic of redundancy/synergy dominance, rather than direct insight into the synergy itself. To address this issue, we present an alternative decomposition that is synergy-first, scales much more gracefully than the PID, and has a straightforward interpretation. We define synergy as that information encoded in the joint state of a set of elements that would be lost following the minimally invasive perturbation on any single element. By generalizing this idea to sets of elements, we construct a totally ordered “backbone” of partial synergy atoms that sweeps the system’s scale. This approach applies to the entropy, the Kullback-Leibler divergence, and by extension, to the total correlation and the single-target mutual information (thus recovering a “backbone” PID). Finally, we show that this approach can be used to decompose higher-order interactions beyond information theory by showing how synergistic combinations of edges in a graph support global integration via communicability. We conclude by discussing how this perspective on synergistic structure can deepen our understanding of part-whole relationships in complex systems.

Catalyst‐free pretreatment of raw wheat straw by atmospheric‐pressure pulsed air discharge for enhancement of sugar production

AbstractThis study presents atmospheric‐pressure plasma as a novel catalyst‐free pretreatment method for raw wheat straw (RWS) biomass. The work explores the effects of processing parameters, such as milled particle size, moisture content of RWS, and plasma generations, on pretreatment efficiency. To understand the mechanisms behind the enhanced pretreatment efficiency, various analysis techniques were used to analyze the physical and chemical properties of RWS before and after pretreatment. The analysis reveals that plasma pretreatment significantly damages the surface smoothness of RWS and enhances the decomposition of lignocellulosic structures. These effects are primarily attributed to the reactive species generated by the pulsed discharge, rather than the accompanying UV radiation, acidification, or heating actions during plasma pretreatment.

Molecular dynamics simulations on the anti-memory effect of vinyl lactam-based polymers

Molecular dynamics simulations were carried out to study the microscopic working mechanism of PVCap-co-TBA and PVCap, especially its working mechanism on the memory effect of hydrates. Our simulation results indicate that PVCap-co-TBA could weaken or even eliminate the hydrate memory effect under the higher subcooling conditions compared with PVCap. The hydrogen bonds formed by the double-bond oxygen atoms and nitrogen atoms of the lactam groups in PVCap with water molecules make the hydrate residual structures around PVCap less susceptible to decompose and provide nucleation sites for hydrate reformation at high subcooling conditions. Compared with PVCap, the introduction of strong hydrophobic tertiary butyl functional groups in PVCap-co-TBA accelerates the mass transfer of water and methane molecules, leading to the decomposition of the hydrate residual structures and the aggregation of large nano-bubble, thereby delaying the hydrate re-nucleation even at high subcooling conditions (e.g. 273 K and 30 MPa).

System model of risks and trees of alternative solutions for improving the logistics chain at a manufacturing enterprise

The subject of this article is the decision-making processes for improving the elements of the supply chain of a manufacturing enterprise under conditions of uncertainty and risks. The purpose of the research is to reduce the time and cost of in supply and distribution of products of manufacturing enterprises by considering possible risks through making rational management decisions. The article addresses the following tasks: examination of the characteristics of supply chain elements; investigation of the main problems of supply and distribution management and identification of ways to solve them; development of a systemic model of logistic risks for a manufacturing enterprise; and formation of decision trees for alternative decisions in strategic supply chain management at manufacturing enterprises. The methods applied include a systems approach, structural decomposition methods, a risk-oriented approach. The following results were obtained: features and problems of supply chain elements such as supply, production, storage, and distribution were examined and identified; main supply chain management tasks were investigated and solutions identified; problems in warehouse management were pinpointed; internal and external supply risks were identified; a systemic model of logistic risks for a manufacturing enterprise was formed, which main components are logistic problems, partial risks, their consequences, and possible management decisions to mitigate risks; decision trees were built for problems of raw material supply instability and transportation bottlenecks and delays; an alternative decision diagram was constructed for an illustrative example. Conclusions: To overcome the problem of raw material supply instability, it is recommended to develop diversification of supply sources, stock reservation, and the use of alternative transport routes. Building alternative decision trees in strategic management is an effective tool for making rational decisions by manufacturing enterprises in complex conditions of uncertainty and risks. They help to analyze alternatives and their consequences to choose a path to optimize the supply chain.

Insight into the formation mechanism of higher-molecular-weight gases during the spontaneous combustion of coal

Higher-molecular-weight gases (HMWGs), which have not received much attention, also contain invaluable information about the coal spontaneous combustion (CSC) development process. In order to investigate the formation mechanism of HMWG, the emission behaviors of HMWG from coal oxidation and pyrolysis experiments were compared, and FTIR and ESR were used to analyze the microstructural evolution of the coal sample. The results show that the volume fractions of most HMWGs increased regularly with increasing temperature. The contribution of the pyrolysis process to the yield of most hydrocarbon HMWGs was close to 100 %, while it was below 89 % for C4 ∼ C6 n-alkanes and benzene and less than 10 % for acetaldehyde and acetone. The decomposition of active structures could produce free radicals, the concentration of which increases with increasing temperature. The formation mechanism of HMWGs was proposed based on the experimental results: HMWGs came from both the thermal reaction and the coal-oxygen reaction process. The thermal reaction process would release the majority of hydrocarbon HMWGs from room temperature. Some active structures began participating in the coal-oxygen reactions to produce oxygen-containing HMWGs at 90 ℃. After reaching 170 ℃, the coal-oxygen reactions were further intensified to release minority n-alkanes, benzene, and small amounts of C4 olefins.

Исследование неоднородности социально-экономического пространства России на уровне макрорегионов

Introduction. This article examines the problem of differentiation of the economic space of Russia. This problem originates during the collapse of the Soviet Union, when, during the transition from a command economy to a market economy, the state was faced with an uneven distribution of natural, territorial, demographic and other resources across the country's regions. The destruction of industrial, financial and social ties of the regions occurred as a result of the policy pursued by Yeltsin B., who pursued a course of strengthening the sovereignty of the subjects of Russia. In the Decree of the President of the Russian Federation No. 803 dated 06/03/1996 "On the main provisions of regional policy in the Russian Federation", the task was set to smooth out significant imbalances in the socio-economic development of the regions. In this paper, the question is considered: has the task regulated by the decree of the President of the Russian Federation been achieved? The purpose of the work is to assess the differences in the socio-economic development of Russian regions grouped into federal districts.Materials and methods. The information base of this study consists of the works of domestic authors and data from the State Statistics Service (Rosstat). The Thale index, its structural decomposition, and the Atkinson index were used to analyze the socio-economic inequality of the regions.Results. The article provides a structural analysis of the socio-economic development of Russia (at the level of macro-regions) from 2000-2020 using the above indices. The results of the study showed significant intergroup differences in the macro-regions of Russia, as well as increased regional inequality in most of the considered indicators. An analysis of the regions within the federal districts showed that the regions of the Central Federal District differ significantly in terms of socio-economic development. In other federal districts, there is a low level of regional inequalityConclusions. As a result of the study, proposals were developed to reduce the socio-economic differentiation of the regions. The conclusions of this work can be used to improve the state regional policy in the field of balanced development of territories.

Understanding and Mitigating Lattice Collapse Degradation in Layered Oxide Materials for Sodium-Ion Battery Anode.

Na2Ti3O7 has attracted significant attention due to its ecofriendliness and cost-effectiveness for sodium-ion batteries. However, their limited cycling stability hampers their practical applications. Herein, we elucidate a mechanism of structural degradation caused by the heterogeneous phase transition in the Na2Ti3O7 anode using aberration-corrected (scanning) transmission electron microscopy (S)TEM and in situ TEM. It is found that the unevenly distributed phase transition results in the accumulation of strain, which promotes the growth of microcracks and eventually leads to structural decomposition and electrochemical failure. Motivated by this degradation mechanism, nanowires were proposed, and the structural stability is thus improved with the lattice strain effectively released. These findings deepen our understanding of ion transport and degradation mechanisms in intercalated layered electrode materials while emphasizing the significance of the material structure engineered for improving electrode performance.

The roots of carbon emission differences between China and USA: A quantitative study based on global value chains

China and the USA, as preeminent contributors to global carbon emissions, demonstrate discernible differentials in both magnitude and trajectories of their respective carbon outputs. This article employed two methods, Structural Decomposition Analysis (SDA) and Quantitative Structural Modeling, to scrutinize the underpinnings of these disparities through the lens of the global value chain. Drawing upon data from the World Input-Output Database (WIOD), our analysis revealed that the compounded influences of output composition, input intensity, input composition and input origin collectively elevated China's aggregate carbon footprint from 2000 to 2014, while the scale effect made China's carbon emissions lower than of the USA. Notably, China's carbon emissions surpassed those of USA, with the gap accentuating over time. The quantitative results of the structural model showed that the difference in carbon emissions between China and USA predominantly stem from disparities in productivity, production technology, factor intensity, factor endowment and direct carbon intensity. Differences in trade costs exhibited some discernible impact, their influence remains relatively marginal, whereas distinctions in consumption behaviors and trade imbalances minimally contribute to the observed differentials. These findings have important policy implications for global carbon reduction efforts and China's trajectory towards a low-carbon economic paradigm.

Trade-induced carbon-economic inequality within China: Measurement, sources, and determinants

Carbon-economic inequality (CEI) occurs due to the unequal exchange between embodied CO2 emissions and value-added in interregional trade. How to reduce CEI has become an urgent task to realize the Sustainable Development Goals. In this study, we quantify the CEI in bilateral and regional trade in China using the embodied CO2 emission and value-added during 2012–2017. Then, we analyze the drivers of CEI changes using the multiplicative structural decomposition analysis. Finally, we measure national CEI using an extended Gini coefficient and further identify the sources of inequality using the Shapley decomposition approach. The results indicate that 1) inequalities in bilateral trade mainly occur between the three north regions (North, Northwest, and Northeast) and eastern coastal regions (Beijing–Tianjin, South coast, and Central coast), and the inequalities generally exhibit worsening trends during 2012–2017. In regional trade, the Northwest suffers the worst and widening inequalities, while the Southwest has obtained an expanded advantage. 2) the decomposition results show that coal efficiency and input structure disparities are the main factors that exacerbate CEI in bilateral trade between the three north and Beijing–Tianjin/South coast regions. Improved input structure is the leader in helping the Southwest reduce CEI in bilateral and regional trade. 3) the overall CEI continues to deteriorate, with the Gini coefficient increasing from 0.260 to 0.305 during 2012–2017, where regional gap and intra-regional inequality, coal-induced CO2 emission, and the electricity production industry are the leading causes. This exacerbated CEI calling for optimizing regional trade patterns and providing holistic solutions for sustainable development.

Tripiperidinium pentaformato copper(II) – A unique homoleptic Cu(II) formate

The synthesis, structure and thermal decomposition behaviour of unique mononuclear, homoleptic [pipH]3[Cu(O2CH)5] (2) (pipH+ = piperidinium) is discussed in which the copper(II) ion is exclusively coordinated by five formate anions forming a distorted square-pyramidal coordination sphere. Thermogravimetric studies confirmed a comparatively low decomposition temperature (Tonset = 107 °C) affording solely elemental Cu. Based on TG-MS experiments a decomposition mechanism is presented.______________________________________________________________________________

Biogenic iron oxide nanoparticles (Fe2O3 NPs) adeptly diminish leaf blight of Rosa chinensis by exhibiting higher expression of RcWRKY29 and increasing antioxidant enzymatic activities

Rose (Rosa chinensis) is subjected to various biotic and abiotic stresses. In this study, rose leaves with blight symptoms were collected and based on microscopic, morphological, and genetic analyses, the disease-causing pathogen was identified as Aspergillus niger. To our knowledge, this is the first report of leaf blight of R. chinensis in Pakistan. To control this disease, iron oxide nanoparticles (Fe2O3 NPs) were synthesized in the seed extract of Trachyspermum ammi. Suitable formation of synthesized Fe2O3 NPs was tested using reliable techniques. Fourier transformed infrared (FTIR) spectrum of Fe2O3 NPs determined the presence of reducing agent like alcohol, alkyl halide and amine on the surface of NPs. X-Ray diffraction (XRD) analysis depicted crystal-like nature and size (41 nm) of NPs, while scanning electron microscopy (SEM) depicted their spherical shape. Sharp Fe and O peaks were observed by energy dispersive X-ray (EDX) analysis. All concentrations of Fe2O3 NPs (0.25, 0.5, 0.75, 1 and 1.5 mg/ mL) inhibited mycelial growth, in vitro and the greatest inhibition (88.9 %) was observed at 1.0 mg/ mL concentration. SEM micrographs showed severe shrinking and structural decomposition of mycelia at this concentration. In pot experiment, Fe2O3 NPs adeptly controlled blight disease of rose leaves by improving various physiological and biochemical attributes and superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) activities. Findings of Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) showed the higher expression of RcWRKY29 by the application of Fe2O3 NPs, depicting its probable role in plant defense mechanism. These results proved that the application of Fe2O3 NPs can efficiently prevent the spread of blight disease.

Delineating the embodied CO2 emissions in Canada's exports: Routes, drivers, and paths

AbstractThis study combined the World Input–Output Database and Asian Development Bank's Multiregional Input–Output database to investigate Canada's embodied CO2 emissions in exports (EEE) for the period of 2000–2018. We examined the key drivers and paths through structural decomposition analysis and structural path analysis. First, the results showed that embodied emissions in the intermediate exports were the major contributor to Canada's EEE, and emission paths involving more than three countries were on the rise, indicating that the expansion of the global industrial supply chains has complicated the paths of Canada's EEE. Second, the factors such as emission intensity of sectors, export structure, and export scale, had varying influences on Canada's EEE over time. For several sectors, the benefit from reduced emission intensity was largely offset by the additional emissions from the increased export scale. Hence, the design of emission regulations should consider the heterogeneity of industrial sectors in order to mitigate emissions for the diverse industries in Canada. Third, energy and resource industries (e.g., electricity, petroleum, wood, metals, and so on) played an essential role in Canada's exports. A significant amount of embodied emissions was transferred from these sectors to the downstream sectors along the supply chain, indicating that abatement measures should be adopted from the whole life cycle perspective of a product/service through an integrated governance of the supply chain. This article met the requirements for a Gold–Silver JIE data openness badge described at http://jie.click/badges.

Structural Phase Transition and Decomposition of XeF2 under High Pressure and Its Formation of Xe-Xe Covalent Bonds.

Noble gases with inert chemical properties have rich bonding modes under high pressure. Interestingly, Xe and Xe form covalent bonds, originating from the theoretical simulation of the pressure-induced decomposition of XeF2, which has yet to be experimentally confirmed. Moreover, the structural phase transition and metallization of XeF2 under high pressure have always been controversial. Therefore, we conducted extensive experiments using a laser-heated diamond anvil cell technique to investigate the above issues of XeF2. We propose that XeF2 undergoes a structural phase transition and decomposition above 84.1 GPa after laser heating, and the decomposed product Xe2F contains Xe-Xe covalent bonds. Neither the pressure nor temperature alone could bring about these changes in XeF2. With our UV-vis absorption experiment, I4/mmm-XeF2 was metalized at 159 GPa. This work confirms the existence of Xe-Xe covalent bonds and provides insights into the controversy surrounding XeF2, enriching the research on noble gas chemistry under high pressure.

Salamander loss alters montane stream ecosystem functioning and structure through top‐down effects

AbstractAmphibians are among the most endangered taxa worldwide, but little is known about how their disappearance can alter the functioning and structure of freshwater ecosystems, where they live as larval stages. This is particularly true for urodeles, which often are key predators in these ecosystems. The fire salamander (Salamandra salamandra) is a common predator in European fresh waters, but the species is declining due to habitat loss and the infection by fungal pathogens. We studied the consequences of fire salamander loss from three montane streams, by comparing two key ecosystem processes (periphyton accrual and leaf litter decomposition) and the structure of three communities (periphytic algae, aquatic hyphomycetes and invertebrates) using stream enclosures with and without salamander larvae. Salamander loss did not cause changes in invertebrate abundance or community structure, except for one stream where abundance increased in the absence of salamander larvae. However, salamander loss led to lower periphyton accrual, changes in algal community structure and slower leaf litter decomposition, with no associated changes in fungal communities or microbial decomposition. The changes observed may have been caused by release of salamander predatory pressure on invertebrates, which could have promoted their grazing on periphyton, in contrast to their preference for leaf shredding in the presence of salamander. Our study demonstrates an important role of salamander larvae in montane streams through top‐down control of lower trophic levels and thus in regulating key stream ecosystem processes. Our results highlight the need for improving protection measures for amphibians to prevent these alterations on ecosystem structure and function.

CAN EXCHANGE RATE CONTROL IN TURKEY HELP THE CENTRAL BANK EVALUATIONS WITHIN THE FRAMEWORK OF THE TAYLOR RULE

This paper tests the validity of the Augmented Taylor rule in the Turkish economy for the period between February 2011 and February 2024 with the structural vector autoregression model. It is found that the central bank did not use the policy rate against deviations from inflation in the relevant period. On the other hand, the policy rate moves within expectations against deviations in the output gap and the real exchange rate. According to the structural impulse-response functions, the output gap and the inflation gap respond positively to a one-unit shock to the policy rate, while the real exchange rate reacts negatively. According to the results of structural variance decomposition, the most influential variable on changes in the policy rate is the real exchange rate deficit. In conclusion, the policy rate in the Turkish economy takes into account the output gap and the real exchange rate gap. However, it ignores the inflation gap.

How to achieve differentiated urban mitigation? Evidence from the spatial differences in aggregate embodied carbon intensity

A better understanding of the spatial differences in aggregate carbon intensity (ACI) among cities is useful in achieving differentiated urban mitigation. In this study, we investigated the aggregate embodied carbon intensities and spatial differences in the four municipalities in China during 2007–2017 using an input-output (I–O) model at both the aggregate and final demand category levels. The results indicated that the spatial differences were distinct and gradually increased at both levels. In addition, a spatial structural decomposition analysis was utilized to examine the main factors that contributed to these differences. The energy intensity effect was confirmed as the dominant factor, while the structural effects played an increasingly significant role, particularly the Leontief production structure effect. Finally, policy implications associated with the differentiated CO2 peaking paths were proposed.

SLIVER: Unveiling large scale gene regulatory networks of single-cell transcriptomic data through causal structure learning and modules aggregation

Prevalent Gene Regulatory Network (GRN) construction methods rely on generalized correlation analysis. However, in biological systems, regulation is essentially a causal relationship that cannot be adequately captured solely through correlation. Therefore, it is more reasonable to infer GRNs from a causal perspective. Existing causal discovery algorithms typically rely on Directed Acyclic Graphs (DAGs) to model causal relationships, but it often requires traversing the entire network, which result in computational demands skyrocketing as the number of nodes grows and make causal discovery algorithms only suitable for small networks with one or two hundred nodes or fewer. In this study, we propose the SLIVER (cauSaL dIscovery Via dimEnsionality Reduction) algorithm which integrates causal structural equation model and graph decomposition. SLIVER introduces a set of factor nodes, serving as abstractions of different functional modules to integrate the regulatory relationships between genes based on their respective functions or pathways, thus reducing the GRN to the product of two low-dimensional matrices. Subsequently, we employ the structural causal model (SCM) to learn the GRN within the gene node space, enforce the DAG constraint in the low-dimensional space, and guide each factor to aggregate various functions through cosine similarity. We evaluate the performance of the SLIVER algorithm on 12 real single cell transcriptomic datasets, and demonstrate it outperforms other 12 widely used methods both in GRN inference performance and computational resource usage. The analysis of the gene information integrated by factor nodes also demonstrate the biological explanation of factor nodes in GRNs. We apply it to scRNA-seq of Type 2 diabetes mellitus to capture the transcriptional regulatory structural changes of β cells under high insulin demand.