Scientific Journal of Technology is a monthly online, international, peer-reviewed journal, dedicated to publish empirical, academic, theoretical and review research articles that contribute to the practice in science, technology, and related topics. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.
Study on Collaborative Optimization of Economic Dispatch for Demand Response of Multi-energy System in Distribution Network
To address the issues of high operating costs in distribution grids and insufficient user willingness to respond to demand when a high proportion of distributed generation is connected, this study establishes a coordinated optimization model for economic dispatch and demand response that takes into account user comfort, with the aim of reducing system costs and enhancing demand-side regulation capabilities. Using a modified 33-node system as the subject, an economic dispatch model was established that includes distributed gas turbines, energy storage, photovoltaic systems, and power purchases from the main grid. The objective is to minimize total operating costs, taking into account power flow, voltage and current, and equipment constraints. The total operating cost in Scenario 2 was 16,053.38 yuan, a 4.05% reduction compared to Scenario 1; grid power purchases decreased by 6.84% (from 12,840.06 kWh to 11,962.04 kWh). Under demand response, the load adjustment rate increased, exhibiting a pattern of rising marginal costs. The ChOA algorithm converged in 13 iterations with a convergence time of 3.45 seconds, outperforming the Particle Swarm Optimization (28 iterations, 7.01 seconds) and Genetic Algorithm (24 iterations, 6.23 seconds), demonstrating stable convergence and strong robustness.
Distribution Network Economic Dispatch; User Psychological Comfort; Demand Response; Multi-energy System.
Copyright (c) 2026 Scientific Journal of Technology https://creativecommons.org/licenses/by-nc/4.0
Study on "Four-Property Relationship" and Effective Thickness Lower Limit of Chang4+5 Reservoir in Zhenbei Area
Zhenbei Area is located on the southwestern margin of the Ordos Basin, north of Zhenyuan County. The Yanchang Formation is a key horizon for oil and gas exploration and development in this region. Although certain exploration achievements have been made in Chang 8, Chang 7 and Chang 3 members of the Yanchang Formation in Zhenbei Area, the Chang4+5 member has multiple oil-producing wells and great exploration potential. Controlled by different sediment sources, the Chang4+5 reservoir in Zhenbei Area is lithologically different from that in adjacent eastern blocks, and can be subdivided into Chang4+5₂ and Chang4+5₁ sub-members vertically. As a typical low-permeability reservoir with complex oil-water distribution, low resistivity and low oil saturation, it is difficult to identify oil and water layers by conventional methods. Based on core data, grain size analysis, physical property parameters, logging and production performance data, this study systematically analyzed the four-property relationship (lithology, physical property, electrical property and oil-bearing property) of the Chang4+5 reservoir in Zhenbei Area, established logging interpretation models, and clarified the lower limits of physical property, oil-bearing property, electrical property and effective thickness. The results show that the Chang4+5 reservoir is dominated by fine sandstone and extra-fine sandstone, with low porosity and extra-low permeability; obvious electrical differences exist between eastern and western parts of the study area; the lower limits of physical property are porosity >9% and permeability >0.1 mD, and the lower limit of effective thickness is 0.4 m. This study provides a reliable basis for reservoir evaluation, fluid identification and reserve calculation of the Chang4+5 reservoir in Zhenbei Area.
Zhenbei Area; Chang4+5 Reservoir; Four-Property Relationship; Effective Thickness Lower Limit; Logging Interpretation.
Seismic Activity Simulation and Detection of Wenchuan Earthquake Sequence
The Coulomb rate state model (CRS) based on rate state-dependent constitutive law simulates the seismic activity of three main earthquakes in Wenchuan earthquake sequence. The results show that the model considering the trigger source of secondary aftershocks is more in line with the observation. We come to the conclusion that the trigger of the main earthquake sequence is generated by the self-excitation of small earthquakes under the stress field dominated by Coulomb stress of the main earthquakes of adjacent faults, which is similar to the point process model of ETAS.
Coulomb Stress Rate State Model (CRS); Main Earthquake Trigger; Secondary Aftershock Trigger.
Research on Improved YOLOv8 Based on EMA and DyHead for Mine Target Detection
As an important part of intelligent mine construction, target detection technology is crucial to ensure mine safety production. However, in practical applications, due to the drastic changes in lighting, severe dust interference, small target size and complex dynamic background in the mine environment, the information obtained by traditional detection algorithms often has large errors, leading to missed detection and false detection. In order to solve this problem, this study proposes a YOLOv8-ED model enhanced by EMA attention mechanism and DyHead dynamic detection head. By embedding EMA attention after the C2f module of the backbone network, the model's ability to extract key features in low-light and high-occlusion scenes is enhanced. The original detection head is replaced with DyHead to realize unified modeling and dynamic feature fusion in three dimensions of scale, space and task. Experiments on the self-built mine violation dataset and PASCAL VOC2012 dataset show that the mAP@0.5 of YOLOv8-ED is improved by 3.2% and 2.0% respectively compared with the original YOLOv8. This research provides an effective technical solution for intelligent mine safety monitoring and has important significance for improving the overall performance of mine detection systems.
Mine Target Detection; YOLOv8; EMA Attention Mechanism; DyHead.
Stress Relaxation and Viscoelastic Creep of Polymer Composites: A Critical Review of Models, Methods, and Mechanisms
This review provides a comprehensive and critical assessment of the literature on stress relaxation and viscoelastic creep in polymer composites, covering constitutive modeling, relaxation-creep interconversion, energy dissipation, time-dependent damage, and temperature effects. Three major constitutive approaches are compared and evaluated: the Prony series, the Standard Linear Solid model with finite loading rate correction, and fractional-order viscoelastic models. For interconversion, the Boltzmann convolution integral, direct SLS prediction formulas, and the engineering J 1/E approximation are critically assessed. A time-dependent damage framework D(t) extended from Weibull fatigue damage is discussed. Key gaps in the literature are identified, and future research directions are proposed.
Stress Relaxation; Viscoelastic Creep; Constitutive Modeling; Interconversion; Energy Dissipation; Damage Mechanics; Time-Temperature Superposition.
Research on Market Development and Innovation of Third-Party Automotive R&D Institutions
Against the backdrop of rapid iteration in the new energy vehicle industry and continuous upgrading of automakers' R&D systems, third-party automotive R&D institutions, as a vital part of the automotive industry’s R&D chain, play a key role in compensating for automakers’ R&D shortcomings, optimizing the allocation of industrial technical resources, and driving industrial technological iteration. To explore the market-oriented operation and innovative development paths of third-party automotive R&D institutions, this paper relies on cooperation cases with typical domestic automakers, selects traditional automaker AA Motors and new energy vehicle startups BB Motors and CC Motors as research subjects, and reviews the practical experience of market development and project resource management of the institution. By analyzing the evolution of cooperation models, pain points, and demand differences among automakers at different development stages and of different types, it summarizes differentiated market development strategies for third-party R&D institutions targeting mature traditional automakers and emerging automakers, and extracts three core cooperation models: joint vehicle development, specialized technology construction, and government-enterprise-institute tripartite collaboration. Meanwhile, considering the current red ocean competition in the industry, it proposes innovative optimization solutions from four dimensions: business philosophy, team structure, customer classification, and technical system. The research indicates that third-party automotive R&D institutions must abandon the single-minded cost-effectiveness competition mindset, focus on forward-looking technology R&D, process system construction, and differentiated service optimization, and achieve long-term development through tiered customer operation, professional team configuration, and standardized technology accumulation. This study aims to provide practical reference and theoretical guidance for third-party automotive R&D institutions to optimize market layout, enhance industrial competitiveness, and achieve high-quality sustainable development.
Third-Party R&D Institutions; Automotive Engineering; Market Development; Business Innovation; Automaker Cooperation Models.
Coloring Mechanisms and Archaeometric Identification of Ancient Black Pottery: A Cross-Cultural Review
Black pottery is widely attested across Neolithic China and the Classical Mediterranean, yet the physicochemical origins of its black coloration differ substantially between these regions. This review classifies ancient black pottery firing techniques into four categories based on coloring mechanism: (1) reduction firing, where iron oxides are converted to magnetite or wüstite under oxygen-depleted conditions; (2) carbon infiltration, where free carbon from incomplete combustion deposits in the ceramic body; (3) three-stage oxidation–reduction–reoxidation firing, which produces black iron-based glass-ceramic coatings; and (4) burnishing, where directional alignment of platy minerals suppresses diffuse reflection. For each category, we review formation mechanisms, archaeological examples, and diagnostic microstructural features. A hierarchical analytical framework is then presented, ranging from non-destructive screening to micro-area quantitative analysis. Common pitfalls including post-depositional alterations and equifinality in technique attribution are discussed, alongside emerging techniques such as synchrotron micro-X-ray diffraction, X-ray absorption near-edge structure spectroscopy, and micro-computed tomography. Cross-cultural comparison reveals that Chinese and Mediterranean potters developed parallel yet distinct strategies for controlling kiln atmosphere and surface microstructure.
Black Pottery; Firing Technology; Coloring Mechanism; Carbon Infiltration; Reduction Firing; Three-Stage Firing; Burnishing; Archaeometry.
The Impact of Artificial Intelligence on High School Students' Writing Anxiety in Continuation Writing
Artificial intelligence is reshaping English writing instruction, offering new possibilities for alleviating senior high school students’ anxiety in continuation writing tasks. Grounded in control-value and sociocultural theories, this study positions AI as a "cognitive partner." Through in-depth interviews with 12 students, the research reveals that AI mitigates anxiety by enhancing perceived control via three pathways: cognitive load sharing, immediate feedback regulation, and positive emotion activation. However, AI use may also trigger new forms of anxiety, including dependence, evaluation, and value anxiety. Students expect clear rules, personalized support, and autonomy preservation. Accordingly, the study proposes four pedagogical pathways for human-AI collaboration: teacher role transformation, boundary setting, differentiated intervention, and value clarification. It emphasizes that AI is not a substitute for teachers but a cognitive partner, and that the key to alleviating anxiety lies not in the technology itself, but in the mode of human-technology collaboration.
Artificial Intelligence; Continuation Writing; Writing Anxiety; Human-AI Collaboration; Pedagogical Pathways.
Synergistic Mechanism and Progressive Path of BIM Application in Historic Building Restoration: A Case Study of the Zhengyangmen Gate Tower Restoration Project
To address the persistent challenge of “high-value recognition but low adoption intention” of Building Information Modeling (BIM) in the field of historic building restoration, this paper takes the Zhengyangmen Gate Tower restoration project in Beijing as a typical case and adopts a chain-of-evidence analysis method to systematically investigate the application mechanism of BIM in real engineering contexts. The study finds that the Zhengyangmen project has developed a synergistic closed loop of “environmental drivers → organizational innovation → technological empowerment → value recognition”. In this loop, policy support and public attention constitute the external driving forces, while organizational mechanisms and tool innovations form the responsive layer. This effectively mitigates the complexity of modeling non‑standard components, allowing the technical advantages of monitoring and early warning, nesting recording, and concealed craftsmanship preservation to materialize, thereby fostering value recognition among practitioners. Based on this, a three‑stage progressive promotion path of “digital documentation → process integration → lifecycle management” is constructed, and synergistic barrier‑breaking strategies are proposed from the technology, organization, and environment dimensions. This study provides an actionable engineering path for the systematic promotion of BIM technology in historic building restoration and offers practical guidance for the digital preservation of cultural heritage.
BIM; Historic Building Restoration; Zhengyangmen; Progressive Promotion Path; Organizational Innovation.
A Closed-Loop Alarm Management System for Hazardous Chemical Enterprises Based on Personnel Positioning Data
Personnel positioning platforms are widely used in hazardous chemical enterprises, but location output alone is still not a safety-control process. In many plant deployments, frequent location snapshots sit apart from rule configuration, alarm archives, response traces, and later review. The scheme uses the output of an existing positioning engine to support closed-loop alarm management. The localization algorithm is left unchanged. The main work is to convert location results into normalized events, electronic geofences, reusable alarm strategies, responsibility-delivery ledgers, response logs, and loop indicators that can be audited. The architecture includes the positioning platform, a business-processing layer, and a front-end management interface. The service layer unifies snapshots, binds tags to personnel objects, performs floor-aware geofence judgment, creates alarm events, records delivery and response evidence, and calculates loop processing time. Anonymized operational samples from alarm, delivery, response, and positioning tables are used for limited verification. The checks cover event-chain completeness, timestamp consistency, calculable closure duration, timeout identification, and ledger consistency. The result is a workflow for turning personnel positioning data into traceable safety-management actions in hazardous chemical plant scenarios, while broader efficiency evaluation requires larger sample disclosure.
Personnel Positioning; Electronic Geofencing; Alarm Closed-Loop; Safety Management; Hazardous Chemical Enterprise.
Characteristics, Genetic Mechanisms and Hydrocarbon Accumulation Control of Abnormal High Pressure in the Northwestern Qaidam Basin
Abnormal high-pressure systems are widely developed within the Cenozoic strata of the northwestern Qaidam Basin (NW Qaidam), which is a key geological factor constraining hydrocarbon exploration and drilling safety. This study systematically investigates their distribution characteristics, genetic mechanisms, and controlling effects on hydrocarbon accumulation by comprehensively utilizing a large amount of geological, geophysical, and basin modeling data. The results indicate that the abnormal pressure in the NW Qaidam exhibits a four-segment vertical zonation: low pressure in shallow sections, normal pressure in middle sections, overpressure in mid-deep sections, and strong overpressure in deep sections. The top interface of overpressure lies between 1000 and 2500 m. On a planar scale, the overpressure centers are highly coupled with sedimentary centers. From the Upper Member of the Lower Ganchaigou Formation (E32) to the Upper Youshashan Formation (N22), the overpressure centers migrated eastward along with the sedimentary centers. Analysis of genetic mechanisms reveals that the overpressure in the study area results from the combined effects of undercompaction, tectonic compression, and hydrocarbon generation. The widely developed gypsum-salt rocks played a crucial indirect role in the formation and preservation of the overpressure system by enhancing sealing capacity and promoting organic matter enrichment and hydrocarbon generation. The evolution of abnormal high pressure is highly coupled with hydrocarbon charging episodes. The source-reservoir excess pressure difference (up to 10-20 MPa) provided the key driving force for hydrocarbon migration. The overpressure system itself constitutes an effective seal, forming an "overpressure compartment" together with the gypsum-salt caprocks. This compartment controls hydrocarbon accumulation and distribution, leading to primary high-pressure reservoirs within the compartment and secondary normal-pressure reservoirs outside it. This research deepens the theoretical understanding of overpressure systems in saline lacustrine basins under strong tectonic compression and provides a scientific basis for hydrocarbon exploration and drilling engineering safety in the NW Qaidam.
Northwestern Qaidam Basin; Abnormal High Pressure; Genetic Mechanism; Overpressure Evolution; Hydrocarbon Accumulation.
Research on Security Mechanism and Testing Verification Method of Encryption Chips for Automotive Information Security Components
Against the background of the rapid popularization of intelligent connected vehicles, the in-vehicle electronic and electrical architecture is continuously upgraded to domain control and centralization, putting forward higher requirements for information security in links such as in-vehicle data interaction, vehicle-cloud communication, firmware upgrade, and identity authentication. As the hardware root of trust in the in-vehicle information security system, encryption chips undertake key functions such as key storage, encryption and decryption operations, digital signature, secure boot, and communication authentication, and their security directly determines the entire vehicle network and data security capabilities. Starting from the actual application scenarios of in-vehicle encryption chips, this paper systematically sorts out their hardware security architecture, key management system, cryptographic algorithm implementation, physical anti-attack design, and secure communication mechanism, analyzes the typical risks faced by encryption chips in the current in-vehicle environment such as physical attacks, side-channel attacks, illegal interface access, and key leakage, and constructs a comprehensive testing verification method covering functional testing, cryptographic performance, physical security, interface security, and environmental reliability combined with ISO/SAE 21434, national cryptographic algorithm standards, and automotive-grade security requirements. Verified through bench testing and real-vehicle environment, the testing system proposed in this paper can comprehensively identify the security shortcomings of encryption chips and realize quantitative evaluation of security capabilities, providing a systematic technical reference for the selection, development, evaluation, and engineering implementation of in-vehicle security chips.
Automotive Information Security; Encryption Chip; Security Mechanism; Key Management; Side-Channel Analysis; Testing Verification; Automotive-Grade Security.
Study on the Workability and Mechanical Properties of Low-Carbon Fair-Faced Concrete Incorporating Multiple Mineral Admixtures
To achieve coordinated optimization of workability and mechanical performance in fair-faced concrete, an ordinary Portland cement-based binder system incorporating fly ash (FA), ground granulated blast-furnace slag (BFS), metakaolin (MK), and diatomite (DE) was developed to prepare low-carbon fair-faced concrete with multiple mineral admixtures. An L16(44) orthogonal design was employed to systematically investigate the effects of these factors on spread diameter, T500, compressive strength at 3, 7, and 28 days, and splitting tensile strength at the same ages. Range analysis, analysis of variance, interaction analysis, and the entropy weight-TOPSIS method were further used for comprehensive evaluation. The results show that workability is mainly governed by FA and MK: FA improves flowability, whereas MK and DE increase system cohesiveness and impair fresh-state performance. The strength at all ages is dominated by BFS, indicating that slag powder is the key constituent for enhancing the mechanical properties of low-carbon fair-faced concrete. Comprehensive evaluation ranked the 16 mixtures in the order of L7, L8, and L4, with L7 exhibiting the best overall performance. The study demonstrates a clear need to balance workability and strength in systems containing multiple mineral admixtures, and that the synergistic use of moderate FA and relatively high BFS is more conducive to improving the overall performance of low-carbon fair-faced concrete.
Low-carbon Fair-faced Concrete; Mineral Admixtures; Workability; Mechanical Properties; Orthogonal Experiment.
Simulation Study on the Influence of Drag Reducing Agent on Oil Mixing Segment in Product Oil Pipeline Transportation
Drag reducing agents (DRAs) play a vital role in reducing flow resistance, improving transportation efficiency, and saving energy consumption in product oil pipeline transportation. During long-distance transportation, product oil usually operates in a turbulent state, and turbulent fluctuations and energy dissipation inside the fluid are the main causes of pressure drop along the pipeline. As high-molecular polymers, DRAs can interact with turbulent structures, attenuate turbulent fluctuations, and reduce energy loss, thereby achieving drag reduction and throughput enhancement. Meanwhile, DRAs also exert certain effects on fluid viscosity and flow field structure, making the flow regime more stable, which presents favorable engineering application value. In this paper, a numerical model of DRA injection into product oil pipelines is established based on FLUENT software to investigate the flow, mixing, and diffusion processes of DRAs in pipelines. By adjusting parameters such as injection angle, injection pipe diameter, injection flow rate, and injection position, the distribution characteristics of DRAs and their influences on the flow field under different working conditions are compared and analyzed. The results show that a reasonable injection scheme can promote uniform distribution of DRAs in the pipeline and improve the mixing degree with the main flow oil, thus enhancing the drag reduction effect. In summary, focusing on the application of DRAs in product oil pipelines, this paper conducts research from both mechanism analysis and numerical simulation, and analyzes the flow characteristics of DRAs in pipelines and their influence laws on the oil mixing segment. The research results can provide a reference for the optimization of DRA injection modes and the control of product oil batch transportation process, which is of certain engineering significance for improving pipeline operation efficiency and reducing transportation costs.
Product Oil Pipeline; Drag Reducing Agent; CFD Numerical Simulation; Mixing and Diffusion; Batch Transportation; Oil Mixing Segment.
Diffusion Characteristics of Particulate Pollutants Across Street Locations
Street canyons, as a key component of the urban built environment, strongly influence the diffusion and retention of particulate pollutants due to their complex airflow structures. To investigate the diffusion mechanisms of particulate matter released from different locations within street canyons, a two-dimensional idealized canyon model without vegetation was employed. A steady-state flow field was simulated using computational fluid dynamics (CFD), and a Lagrangian particle-tracking approach was applied to analyze particle trajectories and transport behaviors at different spatial positions. Results indicate the formation of a stable primary vortex within the canyon. The central region, characterized by low wind speeds and recirculating streamlines, significantly inhibits particle dispersion, whereas the upper canyon and free-flow regions promote rapid particle removal due to higher wind velocities. Particle release location plays a critical role in diffusion efficiency: particles released near the upper region or close to the free-flow boundary disperse rapidly when their initial momentum aligns with the main flow direction; particles in the vortex core are prone to long-term trapping; and particles near the ground can gradually rise due to boundary layer disturbances but exhibit prolonged residence times. Additionally, the alignment between particle initial velocity and local flow structure significantly affects their ability to escape vortex constraints. These findings highlight the sensitivity of particulate dispersion to spatial location and flow structures within street canyons, providing a theoretical basis for optimizing urban ventilation and pollution control strategies.
Street Canyon; Particle Dispersion; Lagrangian Particle Tracking.
Short-Term Wind Power Forecasting Method Based on Implicit Scenario Discovery and Dynamic Weighted Fusion
Wind power intermittency and uncertainty significantly increase the complexity of power grid dispatch and impose more stringent requirements on the secure and stable operation of power systems. To address this challenge, this paper proposes a scenario-oriented dynamic selection and fusion decision framework based on dynamic quantile thresholds and a performance matrix. First, a forecasting model pool consisting of physical mechanism models, statistical regression models, and individual deep learning models is constructed, and the applicable boundaries of different model categories are clarified. Second, a three-dimensional orthogonal feature space is established, and dynamic quantile thresholds are introduced to enable implicit scenario identification for wind power time series. Finally, a pyramidal evaluation index system is developed, together with a dynamic selection and fusion triggering mechanism. On the basis of the scenario–model performance matrix, the proposed framework adaptively switches between the two modes of single-model locking and multi-model weighted fusion. Experimental results using measured data from a wind farm show that the proposed method effectively mitigates the degradation in forecasting performance of individual models under extreme scenarios, such as ramping events and cut-in/cut-out moments. Consequently, the method significantly improves forecasting accuracy while demonstrating strong scenario adaptability and robustness.
Implicit Scenarios; Power Forecasting; Weighted Fusion; Dynamic Selection.
BALIMONT Bifidobacterial Synbiotic/Postbiotic Composition for Increasing IgA: Clinical Evidence and Translational Interpretation
We evaluated the translational basis of a BALIMONT immune-support composition that combines Bifidobacterium bifidum, Bifidobacterium longum, Lactobacillus rhamnosus, heat-inactivated Lactococcus lactis, prebiotic substrates, and a double-layer encapsulation system. Rather than presenting an unverified trial as completed research, we integrated the formulation's retained technical findings with publicly available randomized controlled trials, pilot studies, and meta-analytic evidence relevant to mucosal IgA, secretory IgA, bifidobacterial enrichment, and immune challenge responses. The retained formulation data support an equal-ratio live-strain design, a 1:1 postbiotic-to-probiotic balance, and an encapsulation strategy intended to improve survival through gastric transit. Public human evidence shows that synbiotic supplementation can raise stool sIgA in healthy adults, that bifidobacterial and lactobacillary interventions can augment salivary secretory IgA or vaccine-response markers, and that heat-treated bifidobacterial preparations can support mucosal immune endpoints in selected populations. At the same time, the literature also shows substantial strain specificity and outcome heterogeneity. Taken together, the available evidence supports the biological plausibility of an IgA-oriented synbiotic/postbiotic strategy, but it does not yet establish the clinical efficacy of this exact composition. We therefore interpret the present formulation as a scientifically coherent candidate for a future registered human trial, supported by a stronger translational rationale than by direct source-verified efficacy data.
IgA; Secretory IgA; Mucosal Immunity; Bifidobacterium; Postbiotic; Synbiotic; Lactobacillus Rhamnosus; Gut Microbiota.
Research on Power Battery Closed-loop Supply Chain Recycling Strategy Considering Service Level
Against the backdrop of the rapid development of the new energy vehicle industry, the recycling of waste power batteries has gradually become a research hotspot. The service level of recycling enterprises and the energy density of power batteries are key factors influencing the recycling efficiency and overall profit of the closed-loop supply chain. Taking the closed-loop supply chain of power batteries as the research subject, this paper considers the energy density of power batteries and the recycling service level, and constructs three game models of closed-loop supply chains where power battery manufacturers, new energy vehicle enterprises, and third-party recycling enterprises are responsible for recycling, respectively. Through a comparative analysis of the optimal decisions among different models, it is found that improving the recycling service level can significantly enhance the overall recovery rate and the total profit of the supply chain. Among the three modes, the recycling mode led by power battery manufacturers exhibits the greatest advantages in both the recovery rate and the total system profit. This study provides a theoretical basis for the selection of recycling modes and the optimization of service decisions in the closed-loop supply chain of new energy power batteries.
Closed-loop Supply Chain; Power Battery; Recycling Service Level; Game Theory; Recycling Mode.
Application of New Energy Technologies in Aero Engines and Gas Turbines
The intensification of global climate change and environmental pollution has made achieving carbon peaking and carbon neutrality a core strategy for global development. With the continuous advancement of new energy technologies, the utilization of clean energy sources such as wind, solar, and hydrogen has brought profound transformations to the traditional energy structure. In this context, the fields of aero engines and gas turbines are also facing both pressure and opportunities for low-carbon transition. This paper analyzes new energy power generation technologies under the “dual carbon” strategy, and, in conjunction with the working principles and development trends of aero engines and gas turbines, explores the application prospects and challenges of these technologies in the aviation and energy sectors. It further proposes a technological integration pathway for low-carbon and high-efficiency power systems. The results indicate that the integration of new energy generation technologies with aero engines and gas turbines provides a feasible technical route for advancing the green energy transition; however, numerous technical challenges remain to be addressed in practical applications.
Dual Carbon Strategy; New Energy; Hydrogen Energy; Aero Engine; Gas Turbine.
The Supporting Role and Challenges of Remote Sensing Technology in Whole-Process Carbon Emission Accounting
Traditional carbon emission accounting has long been constrained by insufficient spatiotemporal resolution, limited coverage, and inadequate dynamic monitoring capabilities. Remote sensing technology, leveraging its inherent advantages of non-contact observation, synchronous wide-area sensing, and multi-scale dynamic tracking, has been deeply integrated into the entire process of carbon emission accounting, emerging as a pivotal force for addressing these challenges. Combined with practical application examples of technologies such as night light remote sensing and LiDAR, it deeply analyzes the core technical challenges in accounting accuracy control, multi-source heterogeneous data fusion, and industry-specific accounting method adaptation. Research has shown that remote sensing technology can construct a 1km-scale high-resolution carbon emission spatial grid. The correlation coefficient between the vegetation net primary productivity inverted by the CASA model and the ground measured values ranges from 0.6–0.9. However, factors including observation environmental interferences, inversion algorithm limitations, and industrial emission heterogeneity render the issue of data uncertainty highly pronounced. This article proposes a targeted technological optimization path to enhance the scientific and accurate accounting of carbon emissions throughout the entire process, and provide practical reference for the implementation of the "dual carbon" strategic goals.
Remote Sensing Technology; Carbon Emission Accounting; Carbon Sources and Sinks; Whole-Process Support; Accounting Accuracy.
Pedestrian Flow Prediction Method Based on LSTM
With the acceleration of urbanization in China, the urban population density has risen sharply, leading to increasingly severe social security and traffic congestion problems. To address these issues, this study proposes a dynamic and accurate regional pedestrian flow prediction model based on the LSTM neural network, which fuses temporal, statistical and semantic features. Meanwhile, the prediction results are applied to assist relevant departments in pedestrian flow management. Experimental results show that the model achieves a mean squared error (MSE) as low as 29.2530 and a mean absolute error (MAE) of 3.5059, outperforming traditional prediction methods significantly. Additionally, the integration of the SmoothL1Loss function and early stopping mechanism has notably improved the robustness of the model. Error analysis indicates that 83.5% of the prediction errors are controlled within ±20 people, which fully meets the requirements of public safety early warning and traffic congestion prediction. This model provides data support for relevant departments to manage urban pedestrian flow efficiently and accurately, effectively helping the government reduce management and control costs and improve the efficiency of emergency response.
Pedestrian Flow; Prediction; LSTM Neural Network; Feature Engineering; Model Optimization; Public Security.
The Influence of Synsedimentary Faults on the Restoration of the Original Basin
The restoration of the original basin is a core geological task for reconstructing the original appearance of sedimentary basins, revealing the evolution laws of basins, and guiding the exploration of oil, gas and other mineral resources. As a tectonic phenomenon that occurs simultaneously with sedimentation during the evolution of sedimentary basins, syn-sedimentary faults directly control the boundary morphology of the basin, the migration of sedimentary centers, the distribution of strata thickness and the paleogeomorphic features. They are key controlling factors that cannot be ignored in the process of original basin restoration. This paper systematically reviews the relevant research results of syn-sedimentary faults and original basin restoration, elaborates on the geological overview of typical regions, summarizes the current research status at home and abroad and the commonly used research methods, and focuses on discussing the classification of syn-sedimentary faults, the methods of paleogeomorphic restoration under the control of syn-sedimentary faults, as well as the specific impacts of syn-sedimentary faults on the boundaries of the original basin, sedimentary filling and tectonic patterns. Finally, it summarizes the existing deficiencies in current research and looks forward to future research directions, providing theoretical references and technical support for subsequent original basin restoration research and mineral resource exploration.
Qikou Depression; The Transition Period of the Fault Depression; Tectonic Evolution; Sedimentary System; Original Appearance.
Clinical and Translational Evidence for BALIMONT, a Lactobacillus acidophilus-Centered Biotic Composition, in Modulating Immune-Inflammatory Responses
Background: Low-grade inflammation, mucosal-barrier disruption, and recurrent gastrointestinal inflammatory symptoms frequently coexist in adults with immune-inflammatory dysregulation. Multi-strain probiotic systems and postbiotic preparations have both shown anti-inflammatory potential in human studies, but formulation-specific evidence remains essential. Objective: We aimed to present a evidence paper for the BALIMONT composition by integrating retained formulation benchmark data with available clinical trials and meta-analyses relevant to its strains, postbiotic strategy, biomarker framework, and symptom targets. Methods: We retained the original composition architecture, comparator logic, core numerical benchmarks, and three source figures from the development dossier. We then searched peer-reviewed public sources up to March 2026 for randomized controlled trials, placebo-controlled trials, pilot studies, and meta-analyses involving Lactobacillus acidophilus, Lactiplantibacillus plantarum, Bifidobacterium longum, probiotics, postbiotics, inflammatory biomarkers, and gastrointestinal symptom outcomes. We prioritized adult human data and outcome measures directly relevant to hs-CRP/CRP, IL-6, TNF-alpha, IL-10, calprotectin, and GI symptom burden. Results: The retained BALIMONT benchmark program showed a stronger comparator-direction signal for inflammatory suppression and barrier support than the live-bacteria-only reference, including a 68.2% reduction in total serum inflammatory factors and a 42.6% increase in colonic tight-junction protein expression in the lead example, versus 32.5% and 18.3%, respectively, in the comparator framework. Across external human evidence, a meta-analysis of 42 randomized trials reported significant reductions in hs-CRP, TNF-alpha, and IL-6 together with higher IL-10 after probiotic supplementation, while a 2023 umbrella meta-analysis also supported reductions in CRP, TNF-alpha, and IL-6. Strain-relevant clinical studies further showed improvements in bloating with Lactobacillus acidophilus NCFM plus Bifidobacterium lactis Bi-07, decreased inflammatory and lipid-related markers with heat-killed Lactiplantibacillus plantarum L-137 in overweight adults, improved IBS-D symptom severity with both live and heat-treated Bifidobacterium longum CECT 7347, and significant reduction in fecal calprotectin with Lactiplantibacillus plantarum HEAL9 in older adults with chronic low-grade inflammation. Conclusions: The currently available human evidence supports the anti-inflammatory plausibility of the BALIMONT design and aligns with its retained benchmark endpoints, particularly for CRP-related inflammation, cytokine modulation, GI symptom improvement, and postbiotic-enabled translational relevance. A prospective registered trial remains necessary for direct confirmation of this exact formulation.
BALIMONT; Lactobacillus Acidophilus; Lactiplantibacillus Plantarum; Bifidobacterium Longum; Postbiotics; Inflammation; hs-CRP; IL-6; TNF-alpha; GI Symptoms.
Clinical Evaluation of an NVTIA 5-HTP-L-Theanine-GABA Sleep Rhythm Support System
Background: Sleep-support formulations are often marketed as simple ingredient stacks, yet clinically relevant performance depends on whether precursor support, relaxation support, sleep-maintenance support, and gastrointestinal tolerability are coordinated within a practical oral dose window. Methods: We evaluated the NVTIA ternary system by combining its ratio-defined formulation disclosure and patent-reported preclinical benchmarks with published human clinical evidence on 5-hydroxytryptophan (5-HTP), L-theanine, and gamma-aminobutyric acid (GABA). We retained the original preclinical data structure and figures, then matched those results against randomized or controlled human studies of the three principal ingredients. We also mapped a realistic sleep-medicine validation setting to the Sleep laboratory of the Department of Pulmonology at University Hospital Zurich. Results: In the source preclinical dataset, the balanced Example V and the higher-GABA Example VI outperformed blank control, 5-HTP alone, and an L-theanine-plus-GABA binary comparator on sleep-onset rate, sleep latency, and total sleep duration. Published human trials showed that 5-HTP 100 mg/day for 12 weeks improved selected sleep-quality components in older adults, particularly among poor sleepers; GABA 300 mg/day for 4 weeks reduced sleep latency and improved sleep efficacy in patients with insomnia symptoms; and L-theanine improved Pittsburgh Sleep Quality Index components, light sleep, and objective sleep efficiency across controlled trials. Conclusions: We interpret the NVTIA system as a clinically credible formulation-engineering platform in which 5-HTP primarily supports sleep initiation, L-theanine supports relaxation and sleep quality, and GABA strengthens sleep-maintenance depth. Current human evidence strongly supports the component logic of the ternary architecture, while direct randomized validation of the exact fixed-ratio formulation remains the next necessary step.
5-HTP; L-theanine; GABA; Sleep Rhythm; Sleep Quality; Insomnia; Randomized Trial; Formulation Engineering; NVTIA.
Synthetic ammonia is widely used in the production processes of industrial nitric acid, ammonium salts, fertilizers, etc., playing an indirect role in promoting the development of the national economy. At the same time, as one of the basic raw materials for industrial construction and chemical development, the demand for ammonia in various related industries has also increased by tons. However, as an important participant in industrial development and the national economy, traditional synthetic ammonia often has huge energy consumption and low profitability. Therefore, research and development of synthetic ammonia catalysts have continuously emerged. This article elaborates on the research and development of synthetic ammonia catalysts, combining the latest content on the research and development of synthetic ammonia, looks forward to the trends in synthetic ammonia research and development, and provides a certain summary, in order to have a comprehensive understanding of the development and operation methods of synthetic ammonia catalysts.
A System Dynamics Approach to Optimizing Pension Insurance Pooling Governance: A Four-Dimensional Collaborative Path for Yingkou City
Based on the author’s doctoral dissertation, this paper examines how system dynamics can be used to optimize regional pooling governance in China’s pension insurance system under unified provincial pooling rules. Using Yingkou City in Liaoning Province as the focal case and drawing on comparative evidence from the province’s 13 prefecture-level cities during 2015-2024, the paper integrates three layers of evidence: efficiency decomposition, influencing-factor identification, and dynamic pathway simulation. The preceding dissertation results show that Yingkou’s main efficiency bottleneck lies in pure technical efficiency (PTE) rather than scale efficiency (SE): the mean PTE is 0.60, clearly lower than the mean SE of 0.89, and during the 2020 shock year PTE declined to 0.54 while SE remained relatively stable at 0.88. This structure indicates that fragmented procedures, inconsistent information standards, weak interdepartmental coordination, and incomplete closed-loop supervision are more important obstacles than simple scale shortage. On this basis, a system dynamics framework is constructed with stock variables such as cumulative fund balance, insured population, benefit recipients, and governance-capacity stock; flow variables such as contribution revenue, fiscal subsidies, benefit expenditure, and risk handling; and four policy dimensions of policy adaptation, resource integration, technological empowerment, and regulatory assurance. The analysis shows that isolated digitalization is insufficient for sustained governance improvement. More stable gains require coordinated reform that first clarifies rules and closes high-frequency processes, then improves resource coordination and data connectivity, and finally embeds risk control and performance constraints into routine operations. The paper therefore proposes a phased optimization path for Yingkou that centers on benefit-eligibility certification, automatic cross-department verification, process reengineering, and continuous monitoring of process-performance indicators. The study contributes a practical city-level pathway for pension insurance governance and extends the dynamic-balance view of efficiency from measurement to simulation-based policy design.
Pension Insurance; System Dynamics; Regional Pooling Efficiency; Yingkou City; Digital Governance; Four-Dimensional Collaborative Mechanism.
Innovation and Application of Cooperative Management Mechanism of Progress and Cost of Oil and Gas Exploration and Development Projects
Aiming at the inefficiency caused by the separation of schedule and cost control in oil and gas exploration and development projects, a dynamic collaborative management mechanism based on digital twinning and deep reinforcement learning (DRL) is constructed in this study. Through system dynamics modeling, it reveals the dynamic influence of key coupling variables such as geological risk index and engineering complexity on schedule and cost, and puts forward a management framework of "three-layer linkage and dynamic closed loop": using the digital twin platform integrated with Internet of Things and BIM to realize real-time correction of geological risks; The deep Q network (DQN) is used to solve the multi-objective optimal scheduling strategy. Establish a closed-loop process of "early warning-negotiation-adjustment-learning" to improve the management synergy coefficient. Taking Block Y of X Oilfield as an example, after implementation, the project duration was shortened by 2.4 months, the cost overrun rate was reduced by 20.9%, and the inter-departmental decision-making period was shortened to 1.5 days, which verified the remarkable effect of this mechanism in unconventional oil and gas field projects and provided a reusable technical path for project collaborative management under complex geological conditions.
Exploration and Development of Oil and Gas Fields; Cost Collaborative Management; Digital Twins; Deep Reinforcement Learning.
Study on Thermal History Simulation Method of Sedimentary Basin
The study of thermal history of sedimentary basins is an important part of basin dynamics and hydrocarbon accumulation analysis, which is of great significance for revealing the maturation and evolution of source rocks, hydrocarbon generation and expulsion processes and hydrocarbon accumulation rules. In this paper, two basic methods of basin thermal history restoration are systematically sorted out: tectonic thermal evolution method and paleotemperature scale method. The tectonic thermal evolution method is based on the dynamic model of the lithosphere scale. By simulating the tectonic subsidence and thermal effects of different types of basins such as extension, foreland, craton and strike-slip pull-apart, the basin heat flow history is obtained by forward modeling. The paleo-thermometer method uses the paleo-geothermal information recorded by the paleo-thermometer such as vitrinite reflectance, asphalt reflectance, fission track and (U-Th)/He in the sedimentary strata of the basin to invert the thermal history of the basin. The combination of the two methods can give full play to the advantages of forward modeling and inversion, and make up for the shortcomings of a single method. In addition, this paper also discusses the temperature application range of different paleotemperature scales, the progress of dynamic models and their application examples in the analysis of oil and gas basins. The research shows that the tectonic thermal evolution method is suitable for revealing the origin of the basin and the evolution process of the lithosphere, while the paleo-thermometer method, especially the low-temperature thermochronology method, can accurately describe the thermal history path of the basin. The combined use of the two methods is the development trend of the current basin thermal history research.
Sedimentary Basin; Thermal History Simulation; Structural Thermal Evolution Method.
Mechanism of Differential Natural Gas Enrichment on the Northern and Southern Sides of the Lingshui Sag, Qiongdongnan Basin
The natural gas enrichment in the Lingshui Sag of the Qiongdongnan Basin exhibits a prominent spatial pattern characterized as "superior in the south and inferior in the north, dry in the south and mixed in the north." This paper systematically compares the hydrocarbon accumulation conditions on the northern and southern sides to elucidate the mechanisms driving this differential enrichment. Research indicates that the coal-measure source rocks of the Yacheng Formation on the southern side possess tremendous hydrocarbon generation potential. Furthermore, the deep-water gravity flow channel sandstone reservoirs of the Huangliu Formation are large in scale and feature excellent physical properties. Coupled with the development of a highly efficient three-dimensional vertical transport system composed of mud diapirs and associated faults, the southern side possesses a superior foundation for hydrocarbon accumulation. In contrast, the northern side is constrained by multiple unfavorable factors, including low organic matter abundance in source rocks, thin and poor-quality submarine fan reservoirs, weak fault transport connectivity, and a high susceptibility to dispersion, which ultimately limits the scale of natural gas accumulation. The spatial configuration differences in various geological factors—namely generation, storage, and transportation—directly determine the accumulation efficiency and scale of natural gas in this region.
Qiongdongnan Basin; Lingshui Sag; Differential Enrichment.
Core-Shell Nanolipid Co-Delivery of Ergothioneine, Curcumin, and Piperine: Integrating Formulation Performance with Human Clinical Evidence for Anti-Inflammatory and Healthy-Aging Applications
Background: Ergothioneine, curcumin, and piperine are mechanistically complementary but translationally limited by divergent physicochemical behavior, uneven release kinetics, and bioavailability constraints. We therefore reconstructed a core-shell hierarchical nanolipid system and integrated its formulation performance with available human clinical evidence relevant to the three-active strategy. Methods: We extracted formulation architecture, encapsulation, release, and stability data from the source patent dossier. We then performed a targeted evidence synthesis of published human interventional studies indexed in PubMed and related registry records available through 28 March 2026, focusing on ergothioneine and/or curcumin-piperine trials that reported efficacy or safety outcomes relevant to inflammation, redox biology, tissue integrity, cognition, skin physiology, or functional status. Results: The nanolipid embodiments maintained nanoscale particle size (28.4-47.5 nm in leading embodiments), low PDI (0.087-0.112), strong negative zeta potential (-38.7 to -41.2 mV), and high encapsulation efficiencies for all three actives (>91% in the principal embodiments). The leading embodiment also showed synchronized 24-hour release (~74-78% for all three actives) and strong 12-month activity retention (>93% for all three actives), outperforming multiple comparators. Our evidence synthesis identified published human data showing that ergothioneine improved skin hydration and facial condition markers in healthy women and improved learning-related performance with a favorable safety profile in older adults with mild cognitive impairment. Published curcumin-piperine trials demonstrated improvements in oxidative stress, inflammatory markers, glycemic or hepatic indices, and selected functional outcomes across metabolic syndrome, type 2 diabetes, hemodialysis, inflammatory bowel disease, CABG recovery, and sepsis, while one phase III rheumatoid arthritis maintenance trial was neutral for flare-free survival. Conclusions: We interpret the formulation dataset and human evidence base together as a coherent translational signal: the spatially partitioned nanolipid carrier addresses major formulation liabilities, while the published clinical literature supports biological plausibility for anti-inflammatory and healthy-aging applications. A direct randomized trial of the exact triad carrier remains the key next step.
Ergothioneine; Curcumin; Piperine; Nanolipid Carrier; Core-shell Delivery; Oxidative Stress; Inflammation; Healthy Aging; Translational Evidence.