The green development of oil and gas resource-based cities is not only a necessary choice to address resource depletion, protect the ecological environment, promote economic transformation, and improve residents' quality of life but also a crucial approach to ensuring long-term, stable, and sustainable urban economic development.This paper constructs an evaluation index system for the green development of oil-and-gas resource-based cities based on the DPSIR model.The system includes five sub-systems: driving forces, pressures, status, impacts, and responses.By utilizing the entropy weight TOPSIS model and obstacle degree model, this study evaluates and analyzes the level of green development as well as obstacle factors in 17 oil-and-gas resource-based prefecture-level cities in China from 2011 to 2021.The findings indicate that: (1) Overall, the green development level of oil and gas resource-based cities is relatively low, with significant regional disparities.(2) Both the driving force system and pressure system generally exhibit a declining trend in terms of green development level, while the state system shows improvement over time; meanwhile, both the influence system and response system demonstrate fluctuations.(3) Major obstacles faced by oil-and-gas resource-based cities include per capita green space availability, accessibility of public transport vehicles per 10k people, coverage area per capita for urban roads, R&D expenditure proportion in GDP, as well as social security subsidies proportion in general public budget expenditure.Based on these evaluation results and analysis outcomes, it is recommended that city governments optimize their policy systems, prioritize training programs for attracting talents specializing in green industries, and enhance efficiency regarding urban green development.

Biomedical patches have extraordinary application value in the field of wound repair. The biosafety and effectiveness can be further improved by exploring their structural design. Herein, we present core-shell microfibers with liquid metal (LM) core and gelatin/methacrylated hyaluronic acid (HAMA) shell fabricated by microfluidic spinning method. Then the obtained core-shell microfibers are 3D-printed into regularly stacked patches. During the printing process, the initial morphological stability is provided by the thermoresponsive gelatin networks, while the irreversible structure is formed following the covalent photocrosslinking network of HAMA. Owing to the core-shell morphology, LM microdroplets are stably encapsulated in the core, to prevent leakage. The large specific surface area of LM microdroplets contributes to robust photothermal antibacterial effect. The core-shell microfiber-based patches have predominated antibacterial effect and can greatly promote wound healing. Thus, it is believed that the proposed patches composed of LM-encapsulated core-shell microfibers will show significant potential in wound treatments.

Incorporating emissions of greenhouse gases other than carbon dioxide into the metrics for agricultural eco-efficiency is critical for addressing climate change, given the significant role of agriculture in global emissions. Existing studies more focus on single carbon emission indicators and overlooks emissions of other significant greenhouse gases in measuring agricultural eco-efficiency, such as methane and nitrous oxide, leading to a potential underestimation of the true ecological impact of agricultural practices. Utilizing a dataset spanning 2000 to 2021 from China, this study for the first time includes methane and nitrous oxide in the assessment of agricultural eco-efficiency with SBM-DEA model, which defines a more standardized and accurate indicator system of agricultural eco-efficiency, and provides a more comprehensive framework for assessing the impact of agriculture on the environment. Furthermore, it rigorously assesses the variations in China’s agricultural eco-efficiency before and after accounting for multiple greenhouse gases. The study found that, first, before and after embedding a wide range of GHGs, China’s agricultural eco-efficiency overalltrends are basically the same, both showing slow growth in fluctuation, but the ecological impacts of non-CO2 emissions are underestimated. Second, the agricultural eco-efficiency among China’s provinces is characterized by “high in the northwest and low in the southeast”, with spatial heterogeneity in the efficiency level. Last, the underestimation level of the balance of production and marketing area is the highest.This study proposes a novel approach by recommending the integration of various greenhouse gas emissions into the evaluation of agricultural eco-efficiency. It explores cooperative strategies for reducing emissions across several metrics. Such an approach offers quantitative insights that inform the development of green agricultural policies tailored to various regions.

Nickel bronze is provided with excellent wear and high strength, and it is widely applied to aerospace, electronics, machinery manufacturing, and communications. In this study, Cu-12Sn-2Ni alloy wires were facilitated by cold-drawn without intermediate annealing to a tensile strength of 1.3 GPa and a Vickers hardness of 425 HV. During the drawing process, the grains in Cu-12Sn-2Ni alloy are rapidly refined into nano fibers as a result of the interaction between prevailing plane defects, such as stacking faults and nano twins. Dense deformation twins are generated in the wires due to the alloy's low stacking fault energy of 18 mJ/m2. When the strain reaches 3.22, the stacking fault probability and dislocation density increase to 7.6 % and 1.88 x 1015 m- 2, respectively. Dislocation strengthening and boundary strengthening are calculated to be 468.60 MPa and 781.40 MPa in the wire at the strain of 3.22. The fibrous grain boundaries are derived from a considerable proportion of twining indicating that the strength increment by planar defects such as SFs and twin boundaries occupies the crucial position on the Cu-Sn-Ni alloy. The investigation of the strengthening mechanism of the presented Cu-12Sn-2Ni alloy offers further guidance and understanding for ultra-high strength structural metals.

Daqing City is one of the important resource-based cities in China, a city born and prospered by oil. Resource-based cities are cities formed due to the massive exploitation of natural resources, and their rough economic growth methods have caused damage to both the resources and ecological environment of resource-based cities, which must undergo green transformation and development for the sake of economic development. Exploring the status quo of green development in Daqing can not only strengthen the theoretical and empirical research related to green development, but also provide new ways for the green development of other resource cities. Based on the current research situation in Daqing, this paper constructs a green development index system and evaluates and analyzes the level of green development and the obstacle factors in Daqing in the middle of 2011-2021, by using the entropy weight TOPSIS model and obstacle degree model. The results of the study show that: (1) the comprehensive evaluation index of green development increased from 0.375 in 2011 to 0.566 in 2021, and there is still much room for improvement in the level of green development in Daqing. (2) The economic greenness, internal growth mechanism, and industrial greenness of Daqing have been improved to different degrees, and the environmental greenness has been reduced to some extent. (3) The main obstacle factors restricting the level of green development in Daqing are urbanization rate, urban registered unemployment rate, number of university students per 10,000 people, and per capita general public budget income. Based on the evaluation results and analyses, it is recommended that the government promote green economic development, strengthen environmental and ecological governance, and improve the social security system.

Iron-based magnetic nanoparticles have gained significant attention in biomedicine. However, the magnetic properties of iron-based nanoparticles prepared through coprecipitation methods often do not meet application requirements. This study aims to enhance the performance of iron-based magnetic nanoparticles by synthesizing them via the coprecipitation method and doping them with Mn2+, Zn2+, and Co2+ ions in various ratios. Among these, Zn-doped nanoparticles with a 0.6 ratio (ZION-6) exhibits the highest saturation magnetization intensity of 98 emu/g sample and the highest r2 values of 165.2 mM- 1 & sdot;s- 1, making them an effective T2 MRI contrast agent. Our investigation into the coprecipitation process revealed a formation mechanism for ion-doped magnetic ironbased nanoparticles. This mechanism involves the formation of an intermediate phase, alpha-FeOOH, followed by phase transformation, ion doping, and the aggregation of small particles to yield the final magnetic nanoparticles. This research could pave the way for developing magnetic nanoparticles with improved properties for biomedical applications.

We show that delay-differential equations (DDE) exhibit universal bifurcation scenarios, which are observed in large classes of DDEs with a single delay. Each such universality class has the same sequence of stabilizing or destabilizing Hopf bifurcations. These bifurcation sequences and universality classes can be explicitly described by using the asymptotic continuous spectrum for DDEs with large delays. Here, we mainly study linear DDEs, provide a general transversality result for the delay-induced bifurcations, and consider three most common universality classes. For each of them, we explicitly describe the sequence of stabilizing and destabilizing bifurcations. We also illustrate the implications for a nonlinear Stuart–Landau oscillator with time-delayed feedback.

Sodium-based sorbents (Na2CO3/gamma-Al2O3) hold significant potential for commercial application in CO2 capture. The key point in optimizing the sorbent is to enhance its reaction activity and adsorption capacity. This study utilized organic acids as modifiers for Na2CO3/gamma-Al2O3 sorbents and examined the performance of the sorbents in CO2 capture before and after modification. The results show that the organic acid modification plays a crucial role in adjusting the surface hydroxyl groups, reducing the grain size of the active component, and optimizing the ratio of high-index crystal surface exposure. The novel sorbent, modified with citric acid monohydrate, exhibited an exceptional reaction performance. It achieved a carbonation conversion rate of 88.9% when modified with citric acid at an equivalent ratio of 2.5, representing a substantial enhancement of 31% from the bare sample. The organic acid modification significantly contributes to optimizing the performance of sodium-based sorbents, thereby advancing their potential for practical CO2 capture applications.

An accurate understanding of the mechanism of the oxygen evolution reaction (OER) is crucial for the design of efficient catalysts and the development of hydrogen energy. Despite significant advancements in microscopic pH detection studies through the use of mainstream strategies, such as scanning electrochemical microscopy (SECM), rotating ring-disc electrode (RRDE), and spectroscopic techniques, selective and sensitive detection of the change of proton (H+) concentration near the vicinity of the electrode during OER with high temporal resolution remains elusive. In this study, we pioneered the creation of an efficient hybrid electrochemiluminescence-based (ECL-based) pH sensor that enables the detection of H+ in the vicinity of the electrodes during OER. A new class of luminophore based on ECL resonance energy transfer (ECL-RET) was theoretically predicted and further synthesized by grafting fluorescent dyes onto carbon nitride nanosheets (CN) through non-covalent interaction. We present that one of the newly synthesized emitters, CN-FITC, is capable of detecting proton with fast response time, where the ECL intensity of CN-FITC is regulated by proton concentration. By coating this emitter onto an electrode positioned near OER catalysts, proton generation near the vicinity of the catalysts could be qualitatively detected, providing details of the reaction mechanism of OER and unveiling the catalyst degrading pathway caused by proton accumulation. Additionally, the average proton generation rate on the catalyst was extracted from the local pH measurement, leading to a quantitative descriptor of the OER reaction rate. Owing to the high designability of the dye, this study opens up a new strategy for the detection of more reaction intermediates.

The interaction between vehicles and asphalt pavements can cause different degrees of damage to the pavement structure. Due to this interaction, deformation of pavement is commonly observed, potentially affecting ride quality and driving safety. Investigating the responses of the vehicle–pavement interaction to different pavement structures is therefore a curial task. To this end, we proposed a vehicle–pavement-coupled dynamic model, based on the accelerated loading test of the Research Institute of Highway MOT Track (RIOHTrack). This model is derived by coupling a heavy-duty truck vibration model and the well-known huge multi-layer rectangular plate model. The heavy-duty truck vibration model which describes a 3D vehicle–pavement dynamics system is constructed according to test conditions. We formulate the coupling based on the variable-order fractional Kelvin foundation and the random dynamic load. In particular, to obtain the random dynamic load, we first analyze the time domain equation of road roughness from the field data set of the RIOHTrack test track and then use the Galerkin method for numerical calculation. Using the proposed model, we simulated 19 types of pavement structures of the RIOHTrack test track, which characterize the primary features of the empirical data set. Furthermore, we discuss the bifurcation consensus of the dynamic response of the front and rear wheels under different loads and analyzes comprehensively the dynamic responses of different pavement structures. The results show that the vehicle–pavement-coupled dynamic response model proposed in this paper has better applicability to simulate deformation for different asphalt pavement structures and better reflects the history-dependent process and memory effect of pavement deformation.

In recent decades, artificial nerve scaffolds have become a promising substitute for peripheral nerve repair. Considerable efforts have been devoted to improving the therapeutic effectiveness of artificial scaffolds. Among numerous biomaterials for tissue engineering scaffolds fabrication, natural polymers are considered as tremendous candidates because of their excellent biocompatibility, low toxicity, high cell affinity, wide source, and environmental protection. With the development of engineering technology, a variety of natural polymer-derived nerve scaffolds have emerged, which are endowed with biological properties and appropriate physicochemical performances to gradually adapt to the needs of nerve regeneration. Significantly, the intergradation of exogenous biomolecules onto the artificial scaffolds is able to avoid low stability, rapid degradation, and redistribution of direct therapeutic drugs in vivo, thereby enhancing nerve regeneration and functional reconstruction. Here, the development of nerve scaffolds derived from natural polymers, and their applications in continuous administration and peripheral nerve regeneration are comprehensively and carefully reviewed, providing an advanced perspective of the field.

This paper investigates the problem of stabilization and Hopf bifurcation for a fractional order disease spreading model simulated by small-world networks via two types of time delays, that is, the linear and nonlinear time delays. It is worth mentioning that the study of making delay parameter pairs as the bifurcation parameter is unprecedented. Firstly, we build a fractional disease transmission network model based on the Caputo fractional derivative, and fix one type of time delay and use another one as the bifurcation parameter to get criterions of stability and Hopf bifurcation. Then, numerical fitting obtains clear stable region and bifurcation boundary curve, and Hopf bifurcation occurs at the equilibrium when select time delay parameter pairs are in the area through the bifurcation boundary curve. Finally, some numerical examples verify the effectiveness of theories. In addition, simulation examples of regular lattices show that the new model covers the extreme conditions of regula and random networks, and it presents more flexible internal nonlinear interactions than previous models.

•Self-assembled colloidal nanoparticles films are traditionally lack of robust.•A new self-assembly method to construct functional hierarchical superhydrophobic surface.•This method is more operability and can prepare the desired film with structural color on arbitrary intricate surfaces.•The structural color provides a visualized method to monitor the losses.

Tremendous interests have been aroused in exploring efficient and readily-prepared barcode particles, with information coding and specific identification features, for biomedical analytical applications. Here, we propose a novel type of barcode for optical encoding and fluorescence enhancement via depositing quantum dots (QDs) on natural pollens intermediated by a polyelectrolyte layer. The exquisite prickly surface morphology and an intrinsic high surface-to-volume ratio of the pollens resulted in a fluorescence enhancement, due to which a much lower detection limit was reached. Besides, the easily-tunable fluorescence peak and intensity of QDs and the repeatable deposition process allowed for the generation of coding combinations for the simultaneous determination of multiple targets. These features endow the QD-coated pollens extraordinary barcodes for applications in multiplexed bioassays.

In this paper, we consider a unidirectional highway road with one entry/exit uniformly distributed on the road interval. One road side unit (RSU) is located on the position of the entry/exit. We build an analytical model to study the network connectivity problem. In building the analytical model, we take into account several parameters, such as vehicle arrival rate, vehicle moving speed, vehicle communication radius, RSU communication radius, highway road length and the probability of vehicles driving through the entry/exit. The analytical model is verified by using simulation tools.

In the readout circuits of the two-dimensional (2-D) resistive sensor arrays, various auxiliary electrical components were used to reduce their crosstalk errors but resulted in increased circuit complexity. Readout circuits with low-complexity structures were necessary for wearable electronic applications. With only several resistors and a microcontroller, readout circuit based on resistance matrix approach (RMA) achieved low complexity but suffered from small resistance range and large measurement error caused by the output ports’ internal resistances of the microcontroller. For suppressing those negative effects, we firstly proposed an improved resistance matrix approach (IRMA) by additionally sampling the voltages on all driving row electrodes in the RMA. Then the effects of the output ports’ internal resistances and the analog-to-digital converter’s accuracy for the RMA and the IRMA were simulated respectively with NI Multisim 12. Moreover, a prototype readout circuit based on the IRMA was designed and tested in actual experiments. The experimental results demonstrated that the IRMA, though it required more sampling channels and more computations, could be used in those applications needing low complexity, small measurement error and wide resistance range.

Nanomedicine, with its advantages of rapid diagnosis, high sensitivity and high accuracy, has aroused extensive interest of researchers, as the cornerstone of nanomedicine, nanomaterials achieve extra attention and rapid development. Among nanomaterials, quantum dots stand out due to their long fluorescence lifetime and excellent antiphotobleaching performance. At present, quantum dots have been applied to the diagnosis and treatment of diseases and various strategies have been presented to fabricate quantum dots. Microfluidic is one promising strategy since microfluidic device can provide an effective platform for the diagnosis of trace disease markers. In this paper, research progress in the microfluidic synthesis of quantum dots and quantum dot-based nanomedical application is discussed. The classification of quantum dots is firstly introduced, and the researches on quantum dots synthesis based on microfluidic is then mainly described, including the sort, design, preparation of microfluidic synthesis device and its application in synthesis. Nanomedical applications of the quantum dots is especially described and emphasized. The prospects for future development of quantum dots from microfluidic for nanomedical application are finally presented. This article is categorized under: Diagnostic Tools > in vitro Nanoparticle-Based Sensing.

Barcodes have been widely used in biomolecular multiplexed screening and diagnosis, but higher throughput is still a challenge. In this work, we developed a kind of molybdenum disulfide (MoS2) encapsulated photonic crystal (PhC) barcodes as a fluorescence biosensor with binary optical encoding strategy for different microRNA (miRNA) detection. Through the introduction of MoS2 nanosheets, PhC barcode and quantum dot (QD) decorated molecular beacons (MBs) were closely combined by covalent bond. The presence of the corresponding target miRNA could open the hairpin structure and recover the fluorescence of the QDs which quenched by MoS2 layer. Using these characteristics, as well as the expanded coding capability of QDs and PhC barcodes, the composite biosensor could realize qualitative and quantitative detection of different tumor markers. These features make the MoS2-encapsulated PhC barcodes (MPCBs) with binary optical encoding strategy ideal for actual screening of tumor samples.

This paper studies the network connectivity problem in a vehicular network and focuses on the two-way connectivity of vehicles moving on a one-way highway road with one entry and exit. The entry and exit separates the road into two segments, where vehicle arrivals follow a Poisson process. At the entry and exit, a vehicle may enter or exit from the road, or drive through the entry and exit. A connectivity analytical model is derived for analyzing the connectivity probability of vehicles moving on the road. The analytical model takes into account several parameters that may affect the connectivity probability, including a vehicle's arrival rate and moving speed as well as the probability that a vehicle drives through the entry and exit. Moreover, it considers two entry and exit scenarios: one with no roadside unit (RSU) deployed, and the other with one RSU deployed. The analytical model is justified through simulation results and the impacts of different parameters on the connectivity probability are investigated based on the derived analytical model.

In this study we used the metafrontier function to analyze carbon dioxide emissions in relation to environmental production technology in China. We, comprehensively, estimated and decomposed total factor carbon productivity in 36 sectors of Chinese industry in the years between 2003 and 2015. Moreover, industry differences and dynamic evolution of total factor carbon productivity were analyzed in order to reveal sources of growth in total factor carbon productivity. The industrial sectors were classified into four groups according to the dual criteria of carbon emissions and technology. The results are as follows: (1) From 2003 to 2015, the total factor carbon productivity of industry in China increased by 5.93%. During 2004 and 2009, extensive expansion of heavy industry caused decline in total factor carbon productivity. After 2010, the transformation of economic development patterns and the substantial increase in green investment have led to a rapid increase in total factor carbon productivity in China. (2) The difference in total factor carbon productivity among sectors is significant. Low-carbon and high-technology industry is the technology leader. (3) Decomposition analysis reveals that technology innovation gradually plays a dominant role in total factor carbon productivity growth of China's industry. Technical efficiency of the high-carbon industries makes the total factor carbon productivity increase. The gap between the low-tech industry and the high-carbon industry with the metafrontier technology continues to expand.