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In recent years, thin-film manufacturing has required highly solution-processable and flexible transparent electrodes. Transparent conductive films with high stability were prepared in this work by embedding silver nanowires (AgNWs) in tin oxide (SnO2)-modified colorless polyimide for double-sided perovskite solar cells and heaters. The composite conductive films exhibit good light transmittance over 80% at 550 nm (T550) conductivity with the lowest sheet resistance of 10.0 Ω sq–1 and a smooth surface with a root-mean-squared roughness of 13.3 nm. The anticipated interaction between AgNWs and CPI mediated by metallic oxide (SnO2) has been achieved through the reduction of hydrophobicity by SnO2 on CPI. With a heat resistance exceeding 200 °C, CPI exhibits enhanced adhesive properties following optimized heat treatment at 210 °C, resulting in the formation of a substantial composite structure. The conductive layer can withstand 10 cycles of peeling experiments without peeling off. Furthermore, the top layer also selects SnO2 to smooth the stacking AgNWs networks. The complete coverage is used to passivate the surface defects of the electrode. Double-sided perovskite solar cells (PSCs) are fabricated based on the composite transparent electrode. The power conversion efficiency for the PSCs of 6.34% is attained close to the ITO side (8.72%). A flexible transparent heater was successfully constructed, which could reach up to 85 °C within a short response time (250 s). [ABSTRACT FROM AUTHOR]

The steam heating pipeline, as a heat energy delivery method, plays an important role in petrochemical, food processing, and other industrial fields. Research on dynamic hydraulic and thermal calculation methods for steam heating pipelines is the basis for the realization of precise control and efficient operation of steam pipe networks, which is also the key to reducing the energy consumption and carbon emissions of urban heating. In this study, the coupled hydraulic–thermal model of a steam pipeline is established considering the steam state parameter changes and condensate generation, the SIMPLE algorithm is used to realize the model solution, and the accuracy of the model is verified by the actual operation data of a steam heat network. The effects of condensate, environmental temperature, and steam pipeline inlet temperature and pressure changes on the hydraulic and thermal characteristics of the steam pipeline are simulated and analyzed. Results indicate that condensate only has a large effect on the steam outlet temperature and has almost no effect on the outlet pressure. As the heat transfer coefficient of the steam pipeline increases, the effect of both condensate and environmental temperature on the steam outlet temperature increases. The effect of the steam inlet pressure on the outlet pressure is instantaneous, but there is a delay in the effect of the inlet temperature on the outlet temperature, and the time required for outlet temperature stabilization increases by about 25 s to 30 s for each additional 400 m of pipeline length. The research can be applied to the control of supply-side steam temperature and pressure parameters in actual steam heating systems. Utilizing the coupled hydraulic–thermal characteristics of the steam pipeline network, tailored parameter control strategies can be devised to enhance the burner's combustion efficiency and minimize fuel consumption, thereby significantly augmenting operational efficiency and fostering sustainable development within the steam heating system. [ABSTRACT FROM AUTHOR]

In the context of China, higher education institutions, including colleges and universities, bear the significant responsibility of cultivating proficient contributors and future representatives aligned with the socialist agenda. This is achieved through the provision of ideological and political theory courses. However, students face challenges in achieving desired educational outcomes in these courses. Therefore, it is necessary to investigate the process of knowledge acquisition in ideological and political theory courses as experienced by students. This study employs a qualitative case study methodology, based on flow theory, conducted in a selected college located in Shijiazhuang, Hebei Province, China. The research aims to gather relevant insights by examining data collected from 15 participants through individual semi-structured interviews. Subsequently, the qualitative data is meticulously analyzed using MAXQDA 2020 software. The findings of this study reveal that the factors influencing college students' perception of ideological and political theory courses encompass both internal factors, such as learning behavior and learning holistic quality, as well as external factors, including teaching behavior and teaching holistic quality. Drawing on the model developed in this study to elucidate the impact on college students' sense of acquisition in ideological and political theory courses, it is posited that flow experience constitutes the core factor influencing college students' sense of acquisition, whereby the intensity of flow experienced by college students in ideological and political courses directly affects the extent of their sense of acquisition. This research expands the scholarly exploration of instructional and pedagogical advancements specific to ideological and political theory courses within Chinese tertiary education institutions. Moreover, understanding the influential factors shaping the knowledge acquisition and comprehension process among college students in these courses has the potential to contribute to innovative educational approaches and strategies. [ABSTRACT FROM AUTHOR]

The massive amount of vehicle plate data generated by intelligent transportation systems is widely used in the field of urban transportation information system construction and has a high scientific research and application value. The adoption of big data platforms to properly preserve, process, and exploit these valuable data resources has become a hot research area in recent years. To address the problems of implementing complex multi-conditional comprehensive query functions and flexible data applications in the key–value database storage environment of a big data platform, this paper proposes a data access model based on the jump hash consistency algorithm. Algorithms such as data slice storage and multi-threaded sliding window parallel reading are used to realize evenly distributed storage and fast reading of massive time-series data on clustered data nodes. A comparative analysis of data distribution uniformity and retrieval efficiency shows that the model can effectively avoid generating the cluster hotspot problem, support comprehensive analysis queries with various complex conditions, and maintain high query efficiency by precisely positioning the data storage range and utilizing parallel scan reading. [ABSTRACT FROM AUTHOR]

When listening to connected speech, the human brain can extract multiple levels of linguistic units, such as syllables, words, and sentences. It has been hypothesized that the time scale of cortical activity encoding each linguistic unit is commensurate with the time scale of that linguistic unit in speech. Evidence for the hypothesis originally comes from studies using the frequency-tagging paradigm that presents each linguistic unit at a constant rate, and more recently extends to studies on natural speech. For natural speech, it is sometimes assumed that neural encoding of different levels of linguistic units is captured by the neural response tracking speech envelope in different frequency bands (e.g., around 1 Hz for phrases, around 2 Hz for words, and around 4 Hz for syllables). Here, we analyze the coherence between speech envelope and idealized responses, each of which tracks a single level of linguistic unit. Four units, that is, phones, syllables, words, and sentences, are separately considered. We show that the idealized phone-, syllable-, and word-tracking responses all correlate with the speech envelope both around 3–6 Hz and below ∼1 Hz. Further analyses reveal that the 1-Hz correlation mainly originates from the pauses in connected speech. The results here suggest that a simple frequency-domain decomposition of envelope-tracking activity cannot separate the neural responses to different linguistic units in natural speech. [ABSTRACT FROM AUTHOR]

Tracer technologies based on naturally occurring substances or intentionally introduced compounds have a broad spectrum of applications in hydrogeological research and subsurface resource management. DNA (deoxyribonucleic acid)-based tracers, with unlimited unique variations and exceptional specificity, could potentially map the complex intricacies of subsurface flow networks in greater detail than traditional tracer methods. Here, we review recent advances in DNA-based tracer research involving modern culture-independent (i.e., molecular) measurement techniques for subsurface/flowpath characterization purposes. The two broad categories of DNA-based tracers, i.e., synthetic and naturally occurring, are further classified into four specific types: "naked DNA", "encapsulated DNA", "barcoding microbial communities", and "indicator microbial communities". We summarize and compare the basic methodological workflows for each type of DNA-based tracer and provide an overview of research developments in the past two decades, covering both laboratory/field-scale experiments and data interpretation methods. Finally, we highlight remaining questions and challenges for each type of DNA-based tracer in terms of practicality. Future research directions are also identified, including the application of emerging DNA tracer methods to a wider range of geological formations. Fundamental characteristics of these novel tracers need to be better understood, and their applicability under a broader range of engineering scenarios requires further validation. [ABSTRACT FROM AUTHOR]

Insufficient understanding of the microbial communities and associated microbial processes in geological reservoirs hinders the utilization of this rich data source for improved resource management. In this study, along with four interwell tracer tests at a 1478-m deep fractured crystalline-rock aquifer, we analyzed the microbial communities in the injected and produced water by high-throughput sequencing. The microbial community similarities across boreholes during an interwell flow scenario frequently encountered in reservoir development was explored. Despite the significant tracer recoveries (~30%) in all tracer tests and the cumulatively >100,000 L of exogenous water (carrying exogenous microbes) injected into the 10-m-scale reservoir, the overall structure of produced-fluid microbiome did not increasingly resemble that of the injectate. However, producers with better connectivity with the injector (based on tracer test results) did have more amplicon sequence variants (ASVs) that overlapped with those in the injectate. We identified possible drivers behind our observations and verified the practicality of repeated microbial sampling in the context of reservoir characterization and long-term monitoring. We highlight that injector-producer microbial profiling could provide insights on the relative connectivities across different producers with a given injector, and that the associated logistical needs may be comparable or even less than that of classic tracer tests. [ABSTRACT FROM AUTHOR]

In recent years, the Internet of Things has developed rapidly in people's lives. This brand-new technology is flooding people's lives and widely used in many fields, such as medical field, science and technology field, and industry and agriculture field. As a modern technology, the Internet of Things has many characteristics of low power consumption and multifunction, and it also has the characteristics of data-aware computing. This is the characteristic of this new product. In people's daily life, the Internet of Things is also closely related to people's daily life. In the tourism industry, the Internet of Things can make the best use of everything and give full play to its various advantages as much as possible. The Internet of Things can perceive cross-modal tourism routes. So here, this paper summarizes various algorithms recommended by the Internet of Things for this tourist route and works out the experimental data methods of these algorithms for cross-modal tourism route recommendation. The proposed algorithm is verified by data simulation, compared with related algorithms. We analyze and summarize the simulation results. At present, there is no comparative analysis of the performance of ant colony algorithm, genetic algorithm, and its optimization algorithm in tourism route recommendation. On the basis of crawling the tourism data in the Internet, this paper applies ant colony algorithm, genetic algorithm, max–min optimization ant colony algorithm, and hybrid ant colony algorithm based on greedy solution to tourism route recommendation and evaluates and compares the algorithms from three aspects: average evaluation score, optimal evaluation score, and algorithm time. Experimental results show that the max–min optimization ant colony algorithm and the hybrid ant colony algorithm based on greedy solution can be effectively applied to automated tourist route recommendation. [ABSTRACT FROM AUTHOR]

Artificial tracer testing is an effective technique to identify fluid flow pathways and characterize subsurface hydrological properties. Synthetic DNA tracers, available in virtually unlimited number of unique variations, enable multiwell tracer testing and have the potential to improve the characterization of groundwater flowpaths enormously. This study investigated the effect of DNA length (i.e., number of base pairs) and adsorption on DNA tracer transport via well‐controlled laboratory experiments. Nine unique synthetic double‐stranded DNA tracers were designed with varying lengths (90–200 base pairs) and flowed with reference solute tracers (bromide and lithium) through columns packed with glass beads or Ottawa sand. The peak arrivals of DNA tracers were earlier than bromide in the glass‐bead column test, yet significantly retarded in the sand column test. In a given porous medium, DNA length did not have noticeable effects on peak arrival or tracer dispersion. However, DNA tracer recovery increased with increasing DNA length in the glass‐bead column test but decreased with increasing DNA length in the sand column test, likely resulting from the corresponding trends in partition coefficients as revealed by tracer transport modeling. Such reversed trends in different porous media likely resulted from the different likelihoods for longer DNA to have multisegment attachment during transport. Our findings suggest that both DNA length and the surface properties of the porous medium have notable effects on DNA tracer transport and hence need to be considered carefully in future tracer test designs in terms of site selection, DNA sequence design and data interpretation. Key Points: Compared with bromide, DNA tracers had faster breakthrough times in a glass‐bead column but delayed breakthrough in a silica sand columnThe adsorption partition coefficient increased in proportion to DNA length in the sand column but decreased in the glass‐bead columnDNA tracers with the same length but distinct sequences had the same transport characteristics in a given porous medium [ABSTRACT FROM AUTHOR]

Nano- and microparticles are expected to have several functionalities, and the ability to control size and shape is an advantage of using nano-/microparticles. This study investigated a possibility that the sizes of nano-/microparticle can be used to extract new information on structures in a fractured medium. Flow experiments were conducted to observe the particle transport in a micromodel on which a single fracture and rock matrix (grain and pore space) was fabricated on a silicon wafer. Water and nano-/microparticles were injected into the micromodel, and the droplets were collected at the outlet. Tunable Resistive Pulse Sensing (TRPS) was used to measure the frequency distributions of particle diameters from each droplet at each time. The result shows that the larger particles were observed only at early time, while the smaller particles were detected at early time and also at late time. This indicates that the larger particles flow in a fracture quickly, while smaller particles migrate through both fracture and matrix over a wider range of time. Particles with different sizes transport through fractured media differently depending on the fracture structures. The tracer response of nano- and microparticles may be useful to evaluate the fracture structures and the flow properties for different flow pathways. [ABSTRACT FROM AUTHOR]

With the widely use of cloud computing in enterprise information systems, service governance becomes critical for an enterprise to adapt to a changing business environment. In order to provide a dynamic strategy for continuous service governance, in this paper a comprehensive service analysis solution is proposed to address both design time and run-time requirements for cloud applications. First, a process-centric Semantic Scene Model is composed to combines static business requirements with dynamic execution information. Then service analysis is conducted referring both to the business process mining results from event logs and the Semantic Scene Model given by business model designers. Service governance strategies are generated from the service analysis results and are performed to qualitatively classify the Quality of Service (QoS) of the services. Finally the approach is verified with a transportation logistics service application in a cloud platform. The result shows that our method can get continuous service governance through combining business processes with run-time service analysis. [ABSTRACT FROM AUTHOR]

The effect of initial culture pH and inducer concentration on xanthine oxidase (XOD) fermentation in shake flasks was first carried out. The results showed that the optimum initial culture pH and inducer concentration were 8.6 and 3.6 g/l, respectively. Batch fermentation of XOD by Arthrobacter M3 in a 7.5-l fermentor was then tested under various pH conditions ranging from 7.6 to 8.6. Based on the analysis of the obtained kinetic parameters, a pH-shift strategy in batch fermentation was implemented to enhance the XOD fermentation. In this strategy, the initial culture pH was set at 8.6 without control and was maintained at 7.6 after the biomass reached 2.0 g/l DCW. XOD production ( P) and final average yield coefficient for production on biomass (FAY) in this strategy reached 7,415.3 U/l and 1,229.7 U/g, respectively, which were significantly higher than the results from the other four protocols. In pH-shift batch fermentation, the Luedeking-Piret equation for product accumulation and the Luedeking-Piret-like equation for substrate consumption fit well with the experimental values. The correlation coefficients ( R) of these two fitting curves were 0.977 and 0.992, respectively. [ABSTRACT FROM AUTHOR]

The mechanism of thermal inactivation about xanthine oxidase (XOD) from Arthrobacter M3 was investigated. Results of reducing SDS-PAGE indicated that the inactivation of XOD was not related to the peptide degradation. Meanwhile, fluorimetry and circular dichroism spectroscopy suggested that XOD inactivation might be associated with the exposure of hydrophobic residues to surface and partial loss of secondary structure. Specific formation of soluble aggregates of XOD was detected by size exclusion chromatography. In addition, the thermal-dynamic analysis showed that the inactivation kinetics of XOD followed the first-order model. Therefore, trehalose (cosolute) and betaine (osmolyte) were accordingly employed to attenuate the inactivation of this enzyme. The results associated with these two reagents further confirmed that the loss of XOD activity was mainly due to the exposure of hydrophobic residues and formation of aggregation. Owing to the added trehalose and betaine, half-life could be significantly increased, and the inactivation rate constant ( k) was detected as decreased. [ABSTRACT FROM AUTHOR]

Affinity protocols for the purification of urinary trypsin inhibitor (UTI) were developed. To imitate the substrate/inhibitor-binding domain (S1 domain) of trypsin and chymotrypsin, the key amino acid residues were composed to sorbents. The sorbents were then subjected to adsorption analysis with UTI. The purification process consisted of one step of affinity chromatography and another step of ultrafiltration. The purified enzyme was subjected to SDS-PAGE, trypsin inhibitor activity and peptide map fingerprinting analysis. As calculated, the theoretical maximum adsorption ( Qmax) of two affinity sorbents entitled as S-D-G and S-S-G were 31.7 and 30.1 mg/g, respectively; the desorption constants Kd of the two sorbents were 8.9 and 18.6 μg/mL, respectively. After the separation of UTI with S-D-G and S-S-G, reducing SDS-PAGE analysis revealed that the protein was a single polypeptide with the mass of ∼66 kDa, and the purified proteins were ∼95 and 97% pure, respectively; the band on gel was further confirmed with peptide map fingerprinting analysis. Protein and bioactivity recoveries were 1.3 and 75.9% with S-D-G, 1.0 and 70.2% with S-S-G, respectively. [ABSTRACT FROM AUTHOR]

Methacrylic acid and ethylene glycol dimethacrylate were respectively used as functional monomer and cross-linker to synthesize molecularly imprinted polymers (MIPs), for adsorption of glutathione (GSH), named GSH-MIPs. Evaluation of various polymers by static experiment indicated the optimum ratio of template to functional monomer was 1:4; the optimal concentration and pH of loading buffer were 5.00-6.50 mmol L and 5.0, respectively. By Scatchard analysis, the GSH binding site was found in GSH-MIPs, with K and Q of 1.96 mmol L and 47.19 μmol g, respectively. The method validated the extraction of GSH from yeast cells samples with the enrichment rate of 76%. [ABSTRACT FROM AUTHOR]