Structure Of System Research Articles

Between Tuition Fees and Trainee Allowances: Financing of Schools in the German Health Care System

Schools in the health sector play a significant role in the structure of the German education system. In addition to public schools, there are numerous schools, either substitute or supplementary, in the private sector. Many schools are directly attached to a hospital, in contrast to others operating financially independently having cooperation agreements with corresponding facilities for practical training. This article explains the differences between public, substitute and supplementary schools in the health care sector, with particular emphasis on their financing. It also shows the impact of the integration of a school at a hospital. The information regarding the types of schools was generated through expert interviews and by reviewing current laws. A schematic illustration is intended to promote further understanding of school financing in the health care sector, thus contributing to more transparency. The legal framework conditions for the professions of physiotherapy, occupational therapy and speech therapy are elaborated, as well as basic German Law forming the legal basis for the Hospital Financing Act (KHG). The financing of public schools is regulated by law and is carried by the respective state or municipality. This also applies to public schools in the health care sector. Uniform regulations are also applicable to replacement and supplementary schools falling under the KHG. Trainees receive a salary if their schools cooperate with hospitals with which corresponding funding agreements are in place. However, private schools not affiliated with the KHG training fund must rely on alternative sources of funding, ultimately leading to the necessity to charge tuition fees. Different federal/state-specific regulations contributing to the financing of health care education is often unclear and incomprehensible. Due to current laws, tuition-free education cannot be guaranteed in every federal state or at every school. It remains to be seen if or to what extent changes will take place leading to uniform, transparent and comprehensible financing of the training landscape in the health professions in the German education system.

Nonlinear finite element model updating and fourier neural operator for digital twin of reinforced concrete containment vessel under seismic excitations

A series of unidirectional seismic excitation tests on a 1/20 scaled reinforced concrete containment vessel (RCCV) specimen was conducted using a 6-DOF shake table. This study presents the development of a digital twin to accurately capture the complex behavior of reinforced concrete structures under seismic effects. With the aid of finite element (FE) software Abaqus, the RCCV structure was initially modeled and analyzed to obtain preliminary structural acceleration and displacement results. To enhance the accuracy of these simulations, a nonlinear FE model updating framework was developed by integrating Abaqus software with Python. The model updating of RCCV was conducted subsequently based on the shake table measured data to obtain results with significantly improved accuracy. It is shown that the FE simulations and the nonlinear FE model updating algorithm are highly effective for the high-fidelity simulation of large and complex structures. Furthermore, a Fourier neural operator (FNO) model is used to learn the FE simulation database and predict the FE simulation results. It is observed that FNO has an excellent performance in predicting the structural responses with various material and damping parameters and accomplished speedup over 5000 times compared to the FE simulations. The findings provide a basis for the application of nonlinear model updating algorithms at the structure system level through the high-performance GPU-based parallel computing and underscore that the strategy of FE analysis combined with artificial intelligence (AI) has great potential in the field of digital twins for large and complex structures.

Analysis of landscape vegetation ecology and cellular structure in nature reserves based on an improved analytic hierarchy process

With the increasing severity of global environmental issues, natural reserves have become crucial areas for maintaining biodiversity and protecting natural ecosystems. The ecological status of landscape vegetation and the characteristics of cellular structures within these reserves have become focal points of research. However, traditional evaluation methods have limitations when dealing with the complex ecosystems of natural reserves, making it difficult to assess the relationship comprehensively and accurately between vegetation ecology and cellular structures. Therefore, this paper proposes an analysis of landscape vegetation ecology and cellular structure in natural reserves based on an improved Analytic Hierarchy Process (AHP). By incorporating fuzzy set theory and expert scoring mechanisms, the evaluation process is enhanced in terms of objectivity and precision. An evaluation index system for landscape vegetation ecology and cellular structure in natural reserves is constructed, covering aspects such as vegetation species richness, community structural complexity, and ecological functional stability. This systematic approach reflects the ecological status of vegetation and cellular structure characteristics, providing scientific support for targeted protection and management measures.

An automated AI-powered IoT algorithm with data processing and noise elimination for plant monitoring and actuating

This article aims to develop a novel Artificial Intelligence-powered Internet of Things (AI-powered IoT) system that can automatically monitor the conditions of the plant (crop) and apply the necessary action without human interaction. The system can remotely send a report on the plant conditions to the farmers through IoT, enabling them for tracking the healthiness of plants. Chili plant has been selected to test the proposed AI-powered IoT monitoring and actuating system as it is so sensitive to the soil moisture, weather changes and can be attacked by several types of diseases. The structure of the proposed system is passed through five main stages, namely, AI-powered IoT system design, prototype fabrication, signal and image processing, noise elimination and proposed system testing. The prototype for monitoring is equipped with multiple sensors, namely, soil moisture, carbon dioxide (CO2) detector, temperature, and camera sensors, which are utilized to continuously monitor the conditions of the plant. Several signal and image processing operations have been applied on the acquired sensors data to prepare them for further post-processing stage. In the post processing step, a new AI based noise elimination algorithm has been introduced to eliminate the noise in the images and take the right actions which are performed using actuators such as pumps, fans to make the necessary actions. The experimental results show that the prototype is functioning well with the proposed AI-powered IoT algorithm, where the water pump, exhausted fan and pesticide pump are actuated when the sensors detect a low moisture level, high CO2 concentration level, and video processing-based pests’ detection, respectively. The results also show that the algorithm is capable to detect the pests on the leaves with 75% successful rate.

Empirical Evaluation and Simulation of the Impact of Global Navigation Satellite System Solutions on Uncrewed Aircraft System–Structure from Motion for Shoreline Mapping and Charting

Uncrewed aircraft systems (UASs) and structure-from-motion/multi-view stereo (SfM/MVS) photogrammetry are efficient methods for mapping terrain at local geographic scales. Traditionally, indirect georeferencing using ground control points (GCPs) is used to georeference the UAS image locations before further processing in SfM software. However, this is a tedious practice and unsuitable for surveying remote or inaccessible areas. Direct georeferencing is a plausible alternative that requires no GCPs. It relies on global navigation satellite system (GNSS) technology to georeference the UAS image locations. This research combined field experiments and simulation to investigate GNSS-based post-processed kinematic (PPK) as a means to eliminate or reduce reliance on GCPs for shoreline mapping and charting. The study also conducted a brief comparison of real-time network (RTN) and precise point positioning (PPP) performances for the same purpose. Ancillary experiments evaluated the effects of PPK base station distance and GNSS sample rate on the accuracy of derived 3D point clouds and digital elevation models (DEMs). Vertical root mean square errors (RMSEz), scaled to the 95% confidence interval using an assumption of normally-distributed errors, were desired to be within 0.5 m to satisfy National Oceanic and Atmospheric Administration (NOAA) requirements for nautical charting. Simulations used a Monte Carlo approach and empirical tests to examine the influence of GNSS performance on the quality of derived 3D point clouds. RTN and PPK results consistently yielded RMSEz values within 10 cm, thus satisfying NOAA requirements for nautical charting. PPP did not meet the accuracy requirements but showed promising results that prompt further investigation. PPK experiments using higher GNSS sample rates did not always provide the best accuracies. GNSS performance and model accuracies were enhanced when using base stations located within 30 km of the survey site. Results without using GCPs observed a direct relationship between point cloud accuracy and GNSS performance, with R2 values reaching up to 0.97.

Longitudinal change in the adjective intensifier system of Hexagonal French

Abstract Intensifiers are known for their dynamic nature, due in part to the expressive function they serve. However, while the quantitative patterning of English intensifiers has been studied extensively, the intensifier system of French has yet to be well documented. This study therefore examines intensifier use from a variationist sociolinguistic perspective in the ESLO corpus of spoken Hexagonal French. The quantitative distributions of adjective intensifiers are compared across two corpora collected in 1970 and 2010. Results show a significant decrease in intensification rate over time. Analysis of individual intensifiers show some to have decreased in use over time (e.g. très, tellement), others to have increased (e.g. vraiment, tout), and others to appear only in the later sample (e.g. super, hyper). Longitudinal change is also found in the adjectival function (predicative vs. attributive) and collocational width of intensifiers. Relating to social factors, no significant gender difference is found between female and male speakers’ intensification rate over time. Furthermore, très dominates as the preferred intensifier among older generations, while younger speakers favour more varied intensifiers. Analyzing such changes in the use of intensifiers over the past half century contributes to a better understanding of the structure and development of the French intensifier system.

Core-periphery structure of a medicinal botanical system in Uruguay

BackgroundHuman evolution has granted upon an individual’s cognitive mechanisms necessary for remembering experiences, vital for both survival and reproduction. These experiences manifest into cultural traits, influencing human culture, particularly in healthcare and maintenance. Studies regarding medicinal plants and treatments are integral to the study of the medical botanical system. Pharmacopeias highlight the prevalence of specific species widely used, aligning with the “consensus within diversity theory” in evolutionary ethnobiology. Within the framework of this theory, we reflect on the results we’ve achieved in a priority area recognized by UNESCO for its biocultural significance, both locally and regionally.MethodsThis study integrated network analysis and qualitative methods to examine the botanical medical system of “Parque Regional Quebradas del Norte” in Rivera, Uruguay.ResultsStudy results demonstrate a core-periphery structure, with a strongly interconnected core resistant to fragmentation, ensuring structural stability. Additionally, the presence of peripheral nodes throughout the system was identified, enhancing the resilience of the botanical medicinal system against potential disturbances.ConclusionThe core species renowned for their versatility and multiple medicinal uses, treating less severe ailments effectively. Additionally, core plants serve as prototypes for innovations. Their extinction poses a threat to the system’s resilience. Conversely, peripheral plants, though vulnerable, offer possibilities for therapeutic innovations. In the face of environmental change, conservation efforts should prioritize species that are vulnerable to extinction, particularly within the core. Simultaneously, preserving knowledge associated with peripheral plants presents a bicultural conservation strategy, ensuring the botanical system’s robustness among evolving ecological conditions.

High-speed microactuation in a supersonic dual-stream jet flow

Supersonic shear layers experience instabilities that generate significant adverse effects; in complex configurations, these instabilities have global impacts as they foster compounding complications with other independent flow features. We consider the flow near the exit of a dual-stream rectangular nozzle. The supersonic core and sonic bypass streams mix downstream of a splitter plate trailing edge (SPTE) just above an adjacent deck. We perform two-dimensional direct numerical simulations with laminar inflow conditions to parametrically explore the influence of active flow control, considering various actuation angles and locations. The goal is to alleviate the prominent tone associated with vortices shed at the SPTE; these vortices initiate an unsteady shock system that affects the entire flow field through a shock-induced separation and the downstream evolution of plume shear layers. Resolvent analysis is performed on the baseline flow. The identified optimal response guides the placement of steady-blowing actuators. Since the resolvent analysis fundamentally investigates the input–output dynamics of a system, it is also utilized to uncover actuation-induced changes in the forcing–response dynamics. Spectral analysis shows that the baseline flow fluctuating energy is concentrated in the shedding instability. Actuating at optimal angles based on location disperses this energy into various flow features; this affects the shedding itself, and the structure and unsteadiness of the shock system, and thus the response of the deck and nozzle wall boundary layers and the plume. The resolvent analysis indicates, and Navier–Stokes solutions confirm, that favourable control is obtained by either indirectly or directly mitigating the baseline instability.

The Aerodynamic Assessment and Shot Point Position Accuracy of UAV Seismic Source

An unmanned aerial vehicle (UAV) seismic source, suitable for complex terrains due to its eco-friendly, cost-effective, and efficient nature, operates by hovering and releasing impact objects to generate seismic waves. The aerodynamic behavior of these impact objects is vital for shotpoint position accuracy and drag magnitude. Excessive drag will result in the loss of seismic source energy, whereas the deviations of the shotpoint position will disrupt the geometric structure of the observation system, significantly impacting the quality of seismic data acquisition. Through theoretical calculations, the influencing factors of air resistance and cross-wind deflection are analyzed. Air resistance increases with the increase in mass, cross-sectional area, speed, and drag coefficient. Increasing the mass and throwing height can increase the upper limit of the output, but after the air resistance and gravity are balanced, the output kinetic energy of the drone’s seismic source will no longer increase when the throwing height is increased. Using computational fluid dynamics simulations and field tests, this study examines the aerodynamics of four prevalent impact object designs. The results show that shuttle and spherical structures have the least drag during descent and are less influenced by crosswinds, thus being optimal for this application. Field measurement data are also presented for reference.

Order Degree and Centrality Analysis of Advanced Fighter Environmental Control System and Thermal Management System

As fighter aircraft become more advanced, traditional air cycle systems have fallen short of meeting the complex environmental control requirements. Advanced fighters such as the F-22 Raptor have responded to these challenges by adopting integrated thermal management systems. These systems feature complex thermodynamic processes and intricate information transmission pathways among various components, creating a sophisticated network structure. To unravel the complexity of such systems, this paper employs a blend of thermodynamics and information theory. We conduct multi-level analysis using structure entropy method and centrality algorithms to explore the information transmission characteristics within these thermodynamic systems. At the system level, we find that variation in environmental parameters have only a 1% impact on order degree, whereas the influence from the system's own structure is more pronounced. At the component level, within the whole system, the varies components in AFT PAO and fuel loops emerge as critical hubs for information transmission. Among these components, the PAO/Fuel stands out as the most important, with closeness and betweenness centrality exceeding that of all other components by at least 11.5% and 29.1%. This study offers a theoretical foundation for the optimization of thermodynamic system structure and layout, viewed through the lens of information theory.

Inhibition of denitrification and enhancement of microbial interactions in the AGS system by high concentrations of quinoline

Quinoline represents a highly toxic and structurally stable nitrogen-containing heterocyclic compound in coking wastewater, posing a potential threat to human beings and the ecological environment. In this study, we investigated the impact of gradually elevating quinoline concentration on pollutant removal efficiency, sludge characteristics, microbial community and their interactions in the aerobic granular sludge (AGS) system. The results demonstrated that AGS was capable of effectively degrading quinoline, with a final removal rate of 90 mg/L quinoline reaching 98.54 ± 0.28%. Notably, the denitrification process was significantly impeded in the presence of 90 mg/L quinoline, with the Phase D effluent displaying a notably high NO3--N concentration of 37.09 ± 21.81 mg/L, primarily attributed to the reduced abundance of norank_f_A4b bacteria. As the quinoline concentration increased, the sludge particle size diminished from 3.46 to 2.60 mm, while the settling performance deteriorated significantly, escalating from 31.29 ± 1.63 mL/g to 62.32 ± 2.87 mL/g. Meanwhile, the protein (PN) content in EPS gradually increased (from 19.87 ± 0.88 mg/g MLVSS to 51.22 ± 3.21 mg/g MLVSS), while the polysaccharide (PS) content fluctuated. Quinoline profoundly modified microbial community composition and structure, with deterministic processes dominating community assembly. Network analysis indicated intensified and complex microbial interactions at 90 mg/L quinoline, characterized by significantly higher positive correlations. In addition, rare taxa (RT) dominated the network nodes, with 74 of 93 key species belonging to RT, highlighting their pivotal roles in sustaining system functions and strengthening microbial connections. This study provides new insights into the effects of quinoline on microbial community structure and interactions in AGS system.

Research on the design of posture adjustment structure and control system of carrying robot based on the bionic characteristics of pupae structure

Research on the design of posture adjustment structure and control system of carrying robot based on the bionic characteristics of pupae structure

Synergistic solar electricity-water generation through an integration of semitransparent solar cells and multistage interfacial desalination

Energy shortage and freshwater scarcity are critical challenges for the sustainable development of the society. The photovoltaic-thermal (PVT) hybrid system offers a promising strategy by harnessing solar energy for electricity and water cogeneration. However, existing systems suffer from relatively low efficiency due to incomplete solar spectrum utilization. To address this, we propose a novel PVT integrated system that combines semi-transparent solar cells and multistage interfacial stills to maximize solar spectrum utilization, allowing for efficient electricity and freshwater co-production. Experimental results demonstrate a record-high solar-to-vapor efficiency of 210% with a production rate of 3.17 L m-2 h-1 under one-sun, while maintaining an uncompromised electrical efficiency of 19.57%. Furthermore, we employ a verified theoretical framework to provide optimized strategies for concurrent enhancement of electricity-water production, by improving internal heat and mass transfer and effectively reducing the thickness of the interstage air gap. Moreover, we introduce a non-contact model for system structure optimization proposed to match the high transmittance of solar cells. This work realizes full solar spectrum utilization to cogenerate electricity and freshwater, offering optimized strategies from the thermal perspective for future research.

2015 개정 및 2022 개정 교육과정에 따른 '즐거운 생활' 교육과정과 교과서의 음악 학습 내용 비교

As the 2022 revised curriculum was implemented, significant changes emerged in the content structure and textbook system of the elementary school integrated curriculum. This study aims to investigate how the "Pleasant Life" curriculum and the music learning content in elementary school textbooks impact music education. To this end, the study first compares the characteristics of the "Joyful Life" curriculum in the 2015 and 2022 revised curriculum. Second, the study analyzes in detail the characteristics of songs and music learning activities included in the integrated textbooks of both periods. Third, it identifies the challenges faced in music education for first and second-grade students within the integrated curriculum system and proposes improvement strategies to address these issues. The findings reveal that while the 2022 revised curriculum emphasizes teacher and student autonomy, it does not adequately support foundational music learning. Specifically, as the difficulty of songs in the textbooks increased and music activities decreased, students lacked sufficient opportunities for meaningful musical experiences. Therefore, to ensure effective music education for lower grades, music instruction should be delivered separately from integrated subjects, with a more systematic and developmentally appropriate approach. Additionally, there is a need to present musical scores in varied formats and include easier songs in textbooks. Improvements should also focus on designing music learning activities that align with the developmental stages of young learners, making musical concepts easier to understand and learn systematically.

Bone infection evolution

The present minireview aims to provide a context for imagination of the timespan for bone infection evolution from the origin of cellular bone tissue to modern orthopedic surgery. From a phylogenetic osteomyelitis-bracketing perspective, and due to the time of osteocyte origin, bacteria might have been able to infect the skeleton for approximately 400 million years. Thereby, bone infections happened simultaneously with central expansions of the immune system and development of terrestrial bone structure. This co-evolution might aid in explaining the many immune evasion strategies seen in the field of bone infections. Bone infection patients with long disease-free periods followed by sudden recurrence and anamnesis of long-term and low-grade infections indicate that bacteria can perform silent parasitism within bone tissue (parasitism; one organism lives on another organism, the host, causing it harm and is structurally adapted to it). The silence seems to be disturbed by immunosuppression and the present minireview shows that a compromised immune system has been associated with bone infection development across all species in the phylogenetic tree. Orthopedic surgery, including arthroplasty and osteosynthesis, favor introduction of bacteria and prosthesis/implant related infections are thus anthropogenic infections (anthropogenic; resulting from the influence of human beings on nature). In that light it is important to remember that the skeleton and immune system have not evolved for millions of years to protect titanium alloys and other metals, commonly used for orthopedic devices from bacterial invasion. Therefore, these relatively new orthopedic infection types must be seen as distinct with unique implant/prosthesis related pathophysiology and immunology.

A two-stage bi-level electricity-carbon coordinated optimization model for China's coal-fired power system considering variable renewable energy bidding

With China's grid-connected large-scale variable renewable energy, coal-fired power system is progressively changing from being the main supplier of electric energy to providing flexibility services. The coal-fired power system must increase operating efficiency during this transition process by considering the technical characteristics of various coal-fired power units. Additionally, the trading strategies of coal-fired power units in the electricity-carbon market are impacted differently depending on the extent of VRE penetration. This paper innovatively considers these two factors and proposes a two-stage bi-level clearing model in electricity-carbon joint market to coordinate the synergistic development of variable renewable energy and coal-fired power. The upper level of the model aims to maximize the total profits of the coal-fired power system and variable renewable energy units, while the lower level of the model minimizes the total purchasing costs. Coal-fired power units and variable renewable energy units compete to sell electric energy, with the latter buying peaking regulation from the former. The research results indicate that the proposed model can significantly reduce 66.79 % carbon emissions, increase 33.96 % non-fossil variable renewable energy integration and optimize the generation structure of coal-fired power system.

Reconstruction of an execution architecture view by identifying mapping rules for connectors

An execution architecture view plays a crucial role in depicting the structure of a software system at runtime and analyzing its execution aspects, such as concurrency and performance. However, such execution views are frequently missing in real-world practices. Therefore, researchers have endeavored to reconstruct execution architecture views from software systems. However, existing approaches either require domain experts’ knowledge or are applicable only to systems with particular architecture styles. In this paper, we propose a systematic approach to reconstructing an execution architecture view, without prior knowledge of the components and connectors in the target system. With the proposed approach, by defining a candidate set of execution view connectors and mapping rules from source code to execution view connectors, developers can reconstruct an execution view. To evaluate the proposed approach, we applied it to three real-world software systems. Our evaluation results show that the proposed approach reconstructs an execution architecture with a higher than 86 % F1-score and less than 13.9 person-hours.

Determinants of successful transition from adolescent to adult HIV treatment in Zambia: a facility-level based comparative study

Background: Successful transition from adolescent to adult care has not been extensively evaluated, in Zambia. The study aimed to assess the relationship between facility-based socio-demographic traits and successful transition to adult HIV care, in Zambia. Methods: A retrospective descriptive cross-sectional analysis of 7275 patient files from 718 PEPFAR sponsored facilities. Data was extracted from the National Electronic Health Record (EHR) system and imported into STATA SE v-16 for analysis. Descriptive statistics were calculated on socio-demographic features and facility-level performance. Logistic regression was used to analyse the association between level of facility and successful transition to adult care, comparing third level facilities to lower-level facilities. Chi-square was employed to evaluate the association between socio-demographic traits and effective transition outcomes at a significance level of 0.05. Results: 43.2% had successfully transitioned to adult care. Health posts performed the best, with 57.3% of patients successfully transitioning to adult care. The study found that health post type, private ownership, rural location, and province were significant factors in successful transition. Adolescents in lower-level facilities had a 59.9% success rate compared to those in third-level facilities. Conclusions: The study stresses the importance of health system structure and posits that successful transition depends on many factors, not simply adolescent traits.

Stochastic Decision-Making Optimization Model for Large Electricity Self-Producers Using Natural Gas in Industrial Processes: An Approach Considering a Regret Cost Function

In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is of fundamental importance. This paper presents a decision-making structure for large consumers with flexibility to manage electricity or natural gas consumption to satisfy the demands of industrial processes. The proposed modelling energy system structure relates monthly medium and hourly short-term decisions to which these agents are subjected, represented by two connected optimization models. In the medium term, the decision occurs under uncertain conditions of energy and natural gas market prices, as well as hydropower generation (self-production). The monthly decision is represented by a risk-constrained optimization model. In the short term, hourly optimization considers the operational flexibility of energy and/or natural gas consumption, subject to the strategy defined in the medium term and mathematically connected by a regret cost function. The model application of a real case of a Brazilian aluminum producer indicates a measured energy cost reduction of USD 3.98 millions over a six-month analysis period.

Engineered self-assembled protein nanosheets for in situ biosynthesis of peptide anchored protein-semiconductor hybrids for efficient hydrogen production

Catalytic hydrogen production using solar energy is of great significance in addressing the global energy crisis. Herein, an efficient artificial photocatalytic hydrogen production system based on hierarchical protein self-assembly is designed and developed by in situ biosynthesis of peptide-anchored protein-semiconductor hybrids. The self-grown protein-CdS quantum dot hybrids stabilize and array orderly by the predesigned bioengineered proteins assembled into monolayer nanosheets, perfectly mimicking both the structure and function of the natural photosynthetic system. By mild deposition of Pt nanoparticles, the photocatalytic hydrogen production performance of the system is further enhanced to 69100 μmolh−1 (Cd2+) g −1, 80 times the catalytic activity of free CdS. Remarkably, the protein 2D network effectively enhances the water solubility, dispersibility, and solution stability of the inorganic catalytic centers, affording efficient photocatalytic hydrogen evolution. The system maintains 91.2 % catalytic efficiency after 30 days. Furthermore, its hydrogen production rate can be artificially regulated between 69100 and 52100 μmolh−1 (per g Cd2+) by the assembly-disassembly process of the protein templates. Thus, our work showcases the importance of the protein template and its assembly in maintaining the structural stability and high catalytic performance of the photocatalytic system and provides promising ideas for the simulation of natural photosynthetic systems.