Radar Chart Research Articles

Diagnosis and location of inter-turn short circuit fault in pumped storage unit

In order to monitor the inter-turn insulation health of the rotor windings of pumped storage unit (PSU) in real time, a fault diagnosis method based on magnetic field detection is proposed in this study. Firstly, the characteristic harmonics of the air-gap flux density (AGFD) corresponding to the different states are obtained by deriving the expressions for the AGFD in the normal and inter-turn short circuit (ITSC) states of the rotor winding. Secondly, the detection principle of Hall sensor and its application are studied, and an intelligent detection theory combining frequency-resolved spectrum (FRS) and radar chart is proposed. Thirdly, constructing a electromagnetic model based on the actual operating PSU size, then the time/frequency characteristics of the Hall induced electromotive force (HIEF) are analysed, from which the intelligent diagnostic spectrums are constructed for fault detection. Finally, the Hall probe detection sensitivity is calibrated to 1 mV/mT. By installing Hall probe on the slot wedge surface of the generator stator, HIEF signals for different ITSC levels are acquired and integrated with pole positioning signals for condition monitoring, which can effectively identify and locate ITSC fault, while the detection sensor has significant advantages in terms of size and installation simplicity.

The Shape of Relations to Come: Multidimensional Analyses of Complex Human Behavior

AbstractScience, understood to be the behavior of scientists, falls within the purview of behavior analysis. All scientists use scientific instruments to study a natural phenomenon, and for the behavior analyst, perhaps no tool is more important than the graph used to show changes in level, trend, and variability, and upon which behavior analysts make data-based decisions. Modern behaviorism as we know it dates back to the development of the cumulative recorder first developed in the 1930s. Though revolutionary to the science of behavior, two-dimensional graphs may be limited in application for analyzing complex human behavior. In the current article, we conceptualize verbal behavior as a multidimensional field of environmental relations, and introduce the use of multi-axial radar charts for its visual and quantitative analysis. From there, we survey the use of radar charts toward advancing a behavior-analytic understanding of human language and cognition. We demonstrate the use of radar charts for calculating simple shape descriptors as a quantitative measure of dynamic interactants, and show how they can be used to measure change over time.

A Graphical method for PQ assessment: EDA tools using traditional indices and Higher-order Statistics

This paper presents a new qualitative method for assessing the power quality (PQ) of electrical systems using both time domain traditional indices and higher-order statistics. The method employs engineering data analysis (EDA) tools to analyse and interpret the PQ data coming from real datasets. Boxplot of each index are considered an essential tool that deserves to be included and studied when an external dataset it is analysed. But this research intends to go a step further, and for this reason a new tool for the spatial visualization of supply quality based on a radar chart is proposed. Each of its vertices constitutes an index, integrating from 3rd to 6 th order statistics with the traditional indicators SNR, SINAD and crest factor. The proposed methodology is applied to the analysis of real available signals and both, boxplot and radarchart, results are compared and commented. Finally, relationships are established between the altered indicators and the type(s) of event found in the signal.

Multi-objective optimization of regional integrated energy system matrix modeling considering exergy analysis and user satisfaction

Integrated energy system achieves the collaborative optimization of different energy forms such as electricity/gas/heat/cold, and it is an important strategic development direction in the international energy field in the future. However, with the development of smart grid technology and the increase of renewable energy penetration, it needs more flexible load to adapt to the changing energy supply–demand relationship. Considering the impact of user-side load fluctuations on the system, this paper establishes a two-tier closed-loop system model formed by users and the market. The upper-layer is based on the user’s perspective. A comprehensive user satisfaction model is established by the radar chart area method and consumer preference theory. The lower-layer is based on the market perspective. It proposes an improved layering matrix Energy Hub model and conducts the regional integrated energy system exergy efficiency evaluation study. Then, taking economy, carbon emission and exergy efficiency as objective functions, a multi-objective optimization model is constructed. Non-dominated Sorting Genetic Algorithms-II is applied to solve the model, and the output parameters is a Pareto front surface. A combination weighting TOPSIS method is used to select a compromise solution of multi-objective optimization from the optimal solution set. Compared with the primary energy utilization efficiency as the objective function, the exergy efficiency reduces the system cost by 8.64%. Finally, the multi-objective optimization solution based on different user satisfaction is obtained. Through the analysis of the examples, compared with the original load, the introduction of the upper-layer user satisfaction model reduces the system cost by 2.8%. The reasonable setting of user satisfaction and load adjustment amount can improve the economy of system, which verifies the effectiveness of the two-tier closed-loop system based on user satisfaction model.

Concentration-dependent effects of lithium on Daphnia magna: Life-history profiles and integrated biomarker response implementation

The growing use of lithium (Li) in industrial and energy applications and increasing demand worldwide has inevitably resulted in its wide dispersal, representing a significant threat to aquatic systems. Unfortunately, as a ubiquitous emerging contaminant, the comprehensive toxicological information regarding Li at multifarious levels is limited. To diminish this gap, this work was focused to explore Li-induced cascading effects on Daphnia magna as a key species in freshwater ecosystems. Specifically, the organisms were chronically exposed to gradient Li concentrations with emphasis on characterizing life-history traits from individual to population scale, primarily as observed by a markedly concentration-dependent decrease along exposure gradients. In parallel, a robust set of biomarkers relating to energy reserves, antioxidant and biotransformation enzymes, cellular damage, ionoregulation and neurotoxicity were assayed for further understanding potential underlying mechanisms. As a result, biomarker alterations were characterized by significant decreases in energy storage and enzymatic profiles of antioxidant and biotransformation systems, not only triggering an imbalance between reactive oxygen species (ROS) generation and elimination under Li exposure, but compromising the fecundity fitness of phenotypical costs. In contrast, malondialdehyde (MDA) levels were remarkably enhanced as a consequence of inefficient antioxidant and biotransformation capacity leading to lipid peroxidation (LPO). Additionally, Li exerted a dose-dependent biphasic effect on the activities of superoxide dismutase (SOD), Na+,K+-ATPase and acetylcholinesterase (AChE) by interfering with inherent balance. In terms of responsive patterns and dose-effect trends, the integrated biomarker response indices (IBRv2) and star plots were consistent with the differences in biomarker profiles, not only presenting comprehensively biological effects in a visualized form, but signaling the importance of progressive induced changes in an integrative way. Overall, these findings highlighted the need for elucidating Li-produced impacts from a comprehensive perspective, providing valuable insights into better understanding the toxicity of Li in relation to aquatic ecosystem functioning and ecological relevance.

Preparation and Performance of Bitumen Modified by Melt-Blown Fabric of Waste Mask Based on Grey Relational and Radar Chart Analysis.

To effectively utilize waste mask materials in road engineering and minimize resource waste, the melt-blown fabric (MBF) of waste masks was utilized to modify the virgin bitumen. The preparation process of MBF-modified bitumen was investigated, and the physical and rheological properties of bitumen were measured. Subsequently, the blending mechanism during preparation and the dispersion morphology of the modifier were explored. Finally, the pavement performance of the mixture was investigated, and a radar chart analysis was performed to quantitatively assess the effects of MBF modification. Results suggested that the recommended preparation process of shear time, shear rate, and shear temperature was 170 °C, 4000 r/min, and 15 min, respectively. MBF enhanced the high-temperature stability of the binder and weakened the temperature susceptibility. The modification was primarily a physical process. No network structure and agglomeration formed in the bitumen after modification. The addition of MBF significantly improved the resistance of the asphalt mixture to a high-temperature deformation and water damage but harmed its low-temperature crack resistance. The comprehensive assessment results of 0% (f1), 1% (f2), 3% (f3), and 5% (f4) MBF to improve the properties of the mixture were in the following order: f3>f4>f2>f1, where the impact of 3% MBF was the most significant, followed by 5% and 1% MBF.

A multiple-objective capacity allocation optimisation method for cogeneration integrated energy systems considering life cycle carbon emission

ABSTRACT With the increasing penetration of renewable sources, the cogeneration integrated energy system (CIES) is much more efficient and flexible to achieve various types of energy supply for remote loads. Due to uncertainties in both sources and loads, the CIES should be carefully planned and optimised to keep it working at the suitable operation condition. Therefore, this paper proposes a multi-objective capacity allocation optimisation method for the islanded CIES, which is composed of renewable energy generation unit, electric-thermal conversion unit, electric storage, thermal storage and various loads. Firstly, three optimisation objectives are selected as typical indexes, including economic cost, solar energy utilisation, and life cycle carbon emission. An improved radar chart evaluation (RCE) solution is subsequently utilised for calculating a fitness function and building the multi-objective optimisation model. Besides, several compulsory constraints are supplemented to ensure the overall CIES performance satisfy energy supply requirement. As a mature and widely accepted algorithm, a genetic algorithm is chosen as an example to obtain the optimal capacity allocation scheme. Case study of an islanded CIES is provided on the basis of real data from the remote region of northwestern China, which successfully verifies the effectiveness of the proposed optimal capacity allocation method.

Ergonomic Workspace Design to Reduce the Risk of Musculoskeletal Disorders

Office activities were closely tied to document handling and computer interaction. Based on initial identification with the Nordic Body Map, MSDs (Musculoskeletal Disorders) complaints were identified in the shoulders, wrists, waist, buttocks, and back. This study aimed to offer recommendations for enhancing office workstations to minimize the risk of MSDs. The methods used are ROSA to identify employee work postures, product design to provide proposed work facilities, 5S for document organization, and a Radar Chart for evaluation. Initial identification shows the problems that exist in work facilities, workspace layout, and work environment factors. The initial identification of the workspace with Radar Chart also showed a poor score on 5 aspects of Seiri, Seiton, Seiso, Seiketsu, and Shitsuke with an average of 41.75. The proposed intervention is the improvement of ergonomic tables and chairs, structuring documents by applying 5S aspects, and improving the layout of the workspace. The proposed improvements were then evaluated again using the Office 5S Audit Checklist and Radar Chart so that after the ergonomics intervention, the Radar Chart value became 90.75 (excellent) and the 5S aspects (Seiri, Seiton, Seiso, Seiketsu, and Shitsuke) increased. The results of this improvement can be expected to overcome the risk of MSDS problems in the lower neck, buttocks, back, and waist and the resulting ergonomic, organized, and efficient workstations.

Intervention on Mathematics Self-Efficacy: Solution-Focused Brief Therapy.

Research has demonstrated a strong correlation between mathematics self-efficacy and math performance. Middle school children are increasingly receiving solution-focused brief therapy (SFBT), which is a type of psychotherapy. The study intends to use SFBT intervention to improve mathematics self-efficacy of students and to determine whether SFBT intervention was effective. To examine whether Rasch model can be used to evaluate students' mathematics self-efficacy. This study intends to use Radar chart, Rasch model, Line chart to measure the variations of mathematics self-efficacy of three 8th graders (n=3) during SFBT intervention. Radar chart and Rasch model demonstrated a general increment in the mathematics self-efficacy of two pupils, while another one decreased. Additionally, three students showed a decline in their mathematics self-efficacy on particular mathematical problems using a line chart. Overall, students with varied degrees of self-efficacy in math benefited from SFBT interventions, which partially supports the usefulness of SFBT as a tool for assessing students' mathematics self-efficacy. It supported that Rasch model can reflected the changes in students' mathematics self-efficacy. This study provides guidance for measuring the improvement of students' academic self-efficacy through SFBT intervention using Rasch model.

Scenario simulation and synergistic effect analysis of CO2 and atmospheric pollutant emission reduction in urban transport sector: A case study of Chengdu, China

Realizing coordinated control of CO2 and atmospheric pollutants in comprehensive transportation in large cities is an important way to promote sustainable urban development. Based on the LEAP framework, this study established a transport CO2 and atmospheric pollutant emission analysis model for Chengdu from 2021 to 2040, set up three main scenarios for the study of carbon peaking trend and 12 sub-scenarios for the study of the synergistic effect of various emission reduction measures. In addition, the synergistic effects were analyzed by radar charts, grading charts of synergistic effects and the synergetic equivalence index. The results show that under the Green Scenario (GS) and the Strengthen Green Scenario (SGS), the CO2 emissions from comprehensive transportation in Chengdu will peak at 26.774 × 106 t and 23.507 × 106 t in 2032 and 2029, respectively. The emissions of other atmospheric pollutants show a general downward trend. Under SGS, The measures that play the greatest role in reducing CO2, CO, VOCs, and NOx emissions by 2040 are NEV (New energy conversion of vehicles), Among them, the CO2 emission reduction rate relative to BS scenario is 20.7%. While the measures that play the greatest role in reducing PM and SO2 emissions are IES (Improvement of emission standards) and SRT (Strengthen railway transportation), respectively. Compared with other measures, the synergistic effect of SRT is the most highest. The emission reduction effect of NEV is most significant, with a synergistic effect level above level II. Under the joint regulation of multiple measures by GS and SGS, the synergistic equivalence index based on air quality standards has been effectively controlled, showing a downward trend. Overall, Chengdu faces challenges due to a large number of motor vehicles and air passenger throughput. Therefore, vigorously developing hydrogen vehicles and electric vehicles, strengthening railway construction in Chengdu, transferring the pressure of civil aviation and road transportation to railway, can make significant contributions to the pollution reduction and carbon reduction of Chengdu's transportation sector.

HEI Analysis of NHANES Dietary Data: Exploring the Diet Quality of Americans with R Package heiscore

Connections between subpar dietary choices and negative health consequences are well established in the field of nutritional epidemiology. Consequently, in the United States, there is a standard practice of conducting regular surveys to evaluate dietary habits. One notable example is the National Health and Nutrition Examination Survey (NHANES) conducted every two years by the Center for Disease Control (CDC). Several scoring methods have been developed to assess the quality of diet in the overall population as well as different pertinent subgroups using dietary recall data collected in these surveys. The Healthy Eating Index (HEI) is one such metric, developed based on recommendations from the United States Department of Health and Human Services (HHS) and Department of Agriculture (USDA) and widely used by nutritionists. Presently, there is a scarcity of user-friendly statistical software tools implementing the scoring of these standard scoring metrics. Herein, we develop an R package heiscore to address this need. Our carefully designed package, with its many user-friendly features, increases the accessibility of the HEI scoring using three different methods outlined by the National Cancer Institute (NCI). Additionally, we provide functions to visualize multidimensional diet quality data via various graphing techniques, including bar charts and radar charts. Its utility is illustrated with many examples, including comparisons between different demographic groups.

Customized and Optimized Treatment of Extended-Spectrum-Beta-Lactamase Bacteria for Individual Patients

This paper discusses the optimization of customized intravenous-drip therapy regimens for individual patients infected with antibiotic-resistant bacteria, namely Extended-Spectrum-Beta-Lactamase (ESBL) bacteria. By utilizing Ordinary Differential Equations (ODE) to model the system’s dynamics, evaluated the efficiencies of the four most typical types of pulse functions, namely Dirac delta, sine, trapezoid, and normal distribution functions, as well as the time required for each treatment to suppress the pathogen population. The results revealed that a trapezoid pulse function for intravenous delivery of antibiotics is most favorable. Subsequently, infection severity was randomized by altering the bacterial and Beta-Lactamase population. The efficiency of each randomized regimen was evaluated using a predetermined score matrix that assessed the dosing length, dosing interval, maximum rate of antibiotic infusion, net consumption of antibiotics, and the total number of required treatments. Radar charts and box plot models were employed to present the findings. It was discovered that for more severely infected patients with a higher initial population and growth rate, it is important to decrease the time interval between subsequent doses and increase the time of maximum infusion rate. Conversely, for mild infections, the time interval between doses should be increased, and the time of maximum infusion rate should be decreased. It should be noted that maximizing the infusion rate does not enhance treatment efficiency. Furthermore, in comparison to the initial infected bacteria population size, the growth rate, and Bla production rate play more important roles in impacting treatment efficacy.

Evaluation Method of Teaching Quality of Foreign Language Teachers in Colleges and Universities Based on Decision Tree Algorithm

Abstract Teaching evaluation is an important part of the teaching process in colleges and universities and plays a very important role in the development of higher education and the improvement of education quality. Applying a decision tree algorithm to teaching evaluation can uncover the hidden intrinsic connection between teacher information and course quality evaluation results. This study combines the radar graph with the decision tree C4.5 algorithm to construct a foreign language teaching quality evaluation model, which explores the correlation between teacher information and radar graph attributes on teaching quality evaluation grades on the one hand and evaluates the predictive effect of the model on the other hand. The data mined by the radar chart-C4.5 evaluation model show that if the center of gravity of the radar chart is in the first quadrant, then the evaluation grade passes and has the highest support, which is 53.33%. If the radargram area is large, then the evaluation grade good has the highest confidence level of 77.27%. The evaluation result of the model is that the number of error samples of the prediction grade and the expert evaluation grade are 3 excellent, 5 good, 1 average, 4 qualified, and 1 poor, which proves that the performance of the radar map-C4.5 evaluation model is better.

Entropy-Based Thunderstorm Imaging System With Real-Time Prediction and Early Warning

A combination of the sample entropy and the artificial intelligence (AI) would hopefully bring progress to the smart thunderstorm detection. In this paper, we establish an entropy-based thunderstorm point charge imaging system with the data clustering, wherein data are ultra-reliable and have low-latency three-dimensional atmospheric electric field (3DAEF) values. In particular, a high resolution 3DAEF sensor with the single-axis rotary vane is developed to measure the time sequence signal of the 3DAEF. The signal is first denoised, and then decomposed into multiple groups of branch data with the same number of samples. In order to break through the limitations of existing clustering rules, we propose a 3DAEF signal reconstruction method based on entropy intervals. By reconstructing the branch data, multiple time-scale data are formed. Finally, the curve fitting of the data is performed to realize the imaging after clustering the data. Experimental results suggest that the imaging error after the clustering is reduced by about 2.33%. Comparisons with radar charts show that the proposed system can effectively image the point charge moving paths.

Research on the Teaching Reform of Art and Design Courses in Colleges and Universities Driven by Artificial Intelligence

Abstract This paper focuses on analyzing the critical technologies of artificial intelligence technology in the creation and display of art and design teaching in colleges and universities, respectively, using image processing technology, image geometric transformation, and image special effects processing to realize the basic image design of art design, and using head-eye synergistic eye-movement multi-channel interaction and gesture interaction to form an immersive interactive art and design display device. Combined with the radar chart of the acceptance of AI technology in the course teaching, the influencing factors of the three dimensions of cognition, interest and Practice are explored. The OBE concept is introduced to propose a teaching reform program for art and design courses under AI technology. Practical application of the teaching program can improve students’ visual literacy in art and design, and its numerical difference is 0.3254 at the most. Thus, the teaching reform program of art and design courses in colleges and universities based on the OBE concept proposed in this paper is feasible to a certain extent.

Facilitating the learning and adaptation process of regional initiatives that transform towards health and wellbeing systems.

Introduction: Health-systems in western countries are under pressure due to increasing costs, changing health care demands, and a growing shortage of staff. Therefore, regional initiatives are searching for ways to integrate and reorganize services across domains. This is a complex process and requires an incremental approach based on reflection and adaptation. However, regional initiatives are still searching how to construct these processes. This study aimed to gain more understanding of how the reflection and adaptation process in regional initiatives could be facilitated.
 Methods and analysis: This study included an action research within a Dutch regional initiative, including the program managers, involved municipalities, province, health care insurer and the public health services. The partners reflected on transformation themes, identified in previous evaluation studies, by scoring them in questionnaires and discussing them in interviews. Finally, two reflection meetings were facilitated with representation of all partners, respectively on management and board level. The program manager was interviewed about the experiences with this action research. Notes of this interview and observations of the reflection sessions were analyzed inductively. To broaden the experiences within this one initiative, the experiences with the reflection process were reflected upon in semi-structured interviews with program managers from other regional initiatives (n = 11). The semi-structured interviews were coded and clustered inductively.
 Results: Based on the scoring in questionnaires and interviews a radar chart was shown in the reflection meetings. This highlighted that especially two themes (accountability and citizen participation) would need adaptation. Partners especially recognized the problems regarding accountability and agreed that further elaboration was needed. One of the aims of the reflection process was to create a collective feeling of ownership. Results show that external facilitation of the reflection process, which was objective and knowledge-based, helped to enhance the collective conversation. Reflecting with the program managers of the other initiatives learned that not all initiatives invested in a regional reflection and adaptation process. Lack of this investment was related to partners not prioritizing this process. Some program managers expected the knowledge-based reflection to be helpful in creating a common ground among the partners. The use of scoring, like in the questionnaires, or having actionable options after scoring the themes was expected to be helpful to be able to act upon the reflection.
 Lessons learned and next steps: This study described the experiences with facilitating reflection and adaptation processes of regional initiatives. It showed that knowledge-based reflection by an external facilitator was valued to enhance the collective conversation and common ground about transformation. Further research is needed to learn how this common ground could eventually result in adaptation of the initiatives and thus aid their transformation. This research identified the importance of creating a collective process amongst partners for learning and adaptation, though found that not all initiatives invested in this process due to other priorities. More awareness among partners of the initiatives is needed about the importance of this process for transformation and their role in this collective process.
 

Dual characterization method of temperature uniformity and fluctuation for refrigerator: Experiment, methodology, and improvement

Temperature uniformity and temperature fluctuation are two important parameters of refrigerator and have significant effects on fresh-keeping and cold-storage technology. The influencing factors of temperature distribution attract more attention in refrigerator factory. However, the definitions of temperature uniformity and temperature fluctuation are still ambiguous, and present characterization methods cannot accurately describe the temperature field of refrigerator. This paper proposed a novel dual characterization method to reveal the temperature uniformity and fluctuation (TUF) and presented a new arrangement strategy of temperature measuring elements in refrigerator. Results show the proposed method can simultaneously and visibly characterize the TUF behavior. The slope and area of curves in temperature radar chart reveal the TUF distribution clearly. The first layer of refrigerator shows a greater temperature fluctuation, especially when the compressor is working. Refrigerators with different volume have different TUF phenomena. Adding a cold storage module on the top of refrigerator can notably improve TUF feature and make the internal temperature closer to target temperature. The mechanism of TUF change was discussed from heat transfer and cascaded energy utilization. The proposed dual characterization method can reveal temperature distribution with space and time simultaneously and help improve the temperature field of cold-heat preservation to save energy.

Greenness, whiteness, and blueness assessment with spider chart solvents evaluation of HPTLC-densitometric method for quantifying a triple combination anti-Helicobacter pylori therapy

Tackling environmental, economic, and practical issues necessitate analytical methods aligned with green and white chemistry principles. This study quantified a challenging combination of three anti-Helicobacter pylori drugs: omeprazole (OMZ), tinidazole (TNZ), and clarithromycin (CLR) using a novel high-performance thin-layer chromatographic approach. The eco-friendly mobile phase comprised a mixture of ethyl acetate and ethanol (6.5:3.5, v/v), with densitometric detection at 290 nm, yielding compact spots for OMZ (Rf 0.27), TNZ (Rf 0.63), and CLR (Rf 0.73). The method demonstrated excellent linearity (r2 > 0.999) over ranges of 0.5–20, 1–50, and 1–25 μg spot−1 for OMZ, TNZ, and CLR, respectively. Method validation showed good precision (<2 %), accuracy (101.94, 100.65, 101.06 %), and the limit of detections (0.161, 0.269, and 0.283 μg spot-1), for OMZ, TNZ, and CLR, respectively. To ensure sustainability, hazardous solvents were replaced with greener alternatives selected using the Green Solvents Selecting Tool and assessed via greenness index spider charts. The greenness evaluation of the developed method achieved a greener National Environmental Method Index (NEMI), and Complementary Green Analytical Procedure Index (ComplexGAPI) quadrants with higher Analytical Greenness Metric (AGREE) (0.81) and lower carbon footprint (0.037) revealing the method's favorable environmental profile. We further applied the concepts of 'blueness' and 'whiteness' assessment using the recently introduced Blue Applicability Grade Index (BAGI) and Red-Green-Blue 12 (RGB 12) algorithms. The high BAGI score (90) indicated excellent applicability, while the RGB12 score (88.9) confirmed cost-effectiveness and sustainability. This novel HPTLC approach offers a rapid, green-and-white alternative to conventional techniques for pharmaceutical analysis.

How to Use Costs in Value-Based Healthcare: Learning from Real-life Examples

BackgroundHealthcare organizations measure costs for business operations but do not routinely incorporate costs in decision-making on the value of care.AimProvide guidance on how to use costs in value-based healthcare (VBHC) delivery at different levels of the healthcare system.Setting and ParticipantsIntegrated practice units (IPUs) for diabetes mellitus (DM) and for acute myocardial infarction (AMI) at the Leiden University Medical Center and a collaboration of seven breast cancer IPUs of the Santeon group, all in the Netherlands.Program Description and EvaluationVBHC aims to optimize care delivery to the patient by understanding how costs relate to outcomes. At the level of shared decision-making between patient and clinician, yearly check-up consultations for DM type I were analyzed for patient-relevant costs. In benchmarking among providers, quantities of cost drivers for breast cancer care were assessed in scorecards. In continuous learning, cost-effectiveness analysis was compared with radar chart analysis to assess the value of telemonitoring in outpatient follow-up.DiscussionCosts vary among providers in healthcare, but also between provider and patient. The joint analysis of outcomes and costs using appropriate methods helps identify and optimize the aspects of care that drive desired outcomes and value.

Extent of integration of nutrition assessment counselling and support interventions in the health system and respective drivers: A case of Tororo district, Uganda.

Uganda embraced Nutrition Assessment Counselling and Support (NACS) since 2009 as a health system strengthening approach to improve health and nutrition outcomes. However, scant evidence exists on NACS integration and drivers. This study therefore assessed the extent of NACS integration in the health system and identified key drivers and barriers. A mixed method design was employed. In a facilitated panel discussions at each of the 17 health facilities, 4-5 health staff participated, responding to a semi-structured questionnaire. Integration was assessed on a 5-point scoring scale of 1 for not done nor integrated, 2-4 for partial and 5 for fully integration. Data was captured, analysed in microsoft excel and presented using as bar and spider charts. Integration drivers were identified deductively from key informant and in-depth interviews using Atlas.ti 9 and thematic analysis. The NACS integration across the health facility level was partial at a score of 2.9 indicating a weak integration into the health system. Integration across the health system building blocks was partial at; service delivery (3.8), health work force (3.7), health information (3.3), community support system (3.0), governance and leadership (3.0) signifying that NACS activities are provided by Ministry of Health but sub-optimal due to weak capacities. Health financing (2.2) and Health supplies (1.5) were the least integrated due to partner dependence. Under service delivery, deworming (5) was fully integrated and provided by Ministry of Health. The key drivers for integration were; good leadership, financing, competent staff, quality improvement approaches, nutrition talks, community dialogues, nutrition logistics and supplies. The NACS integration in the health system was generally low and lacked adequate support. Governance, financing and community follow-up under service delivery require more government investment for enhanced integration.