High Potential For Improvement Research Articles

Comparative analysis of three methods for estimating the compositions of construction waste.

Determination of the relative compositions of the mixed construction waste is crucial and an important step to enhance resource management. This information influences the design of construction waste recycling and sorting facilities, and aids in formulating effective management strategies for recycled and sorted waste products. However, different methods for waste sorting and composition recognition possess distinct characteristics and only apply to specific practical scenarios. In this study, three methods are compared: (i) manual sorting as a reference method, (ii) a manual image recognition method using infrared thermal imaging, and (iii) a deep learning-based image recognition method based on the SegFormer semantic segmentation model. The comparison focuses on accuracy, preferences, prerequisites, socio-environmental impacts, costs, and improvement potential. Results show that both manual and deep learning-based image recognition methods yield comparable accuracy to manual sorting for inert waste, with relative errors below 5.2%, but relatively higher recognition errors for non-inert waste. Overall, manual sorting remains the most cost-effective and fastest method, despite its high labor demand, spatial constraints, environmental impacts, and limited improvement potential. In comparison, manual image recognition requires approximately 9.2 times the processing time and 2.3 times the cost of manual sorting, while deep learning-based image recognition incurs about 9.9 times the time and 2.5 times the cost. Nevertheless, both image recognition methods offer potential environmental benefits and long-term efficiency gains.

Optimization signal writing with machine learning assisted control

The high-precision signal writing machine, experiencing a 0.1% failure rate due to discrete fourier transform (DFT) of position error signal (PES) exceeding control limits, can be improved with an appropriate controller gain. This paper combines machine learning (ML) classification and controller optimization to determine the suitable gain for the hard disk drive (HDD) signal writing process. The result from machine classification has a high potential for position error improvement, distinguishing them from those with obvious degradation. The identified machine classes with high potential for signal write quality improvement undergo controller optimization using a genetic algorithm (GA). The objective function considers gain crossover frequency, phase margin, and PES DFT at low frequencies. Experimental results demonstrate that the new controller gain enhances signal write quality of class 0 and class 3 by 14.68% and 17.18%, respectively, leading to a reduced failure rate down to 0.05%.

Genetic Variability, Heritability and Genetic Advance for Yield and Yield Related Traits in Rice (Oryza Sativa L.)

Aims: To evaluate genetic variability, heritability, and genetic advance for key agronomic traits in rice to identify traits with high potential for selection and improvement in breeding programs. Experimental Design: The experiment was conducted in a randomized block design (RBD) with three replications. Place and Duration of Study: Regional Sugarcane and Rice Research Station (RS&RRS), Rudrur, Nizamabad, during the kharif 2022 season. Methodology: Eighteen Advanced Varietal Trial (AVT) entries were evaluated with a spacing of 20 cm × 15 cm. Data were recorded from five randomly selected plants per entry in each replication for agronomic and yield-related traits: days to 50% flowering (DFF), plant height (PH), panicle length, number of panicles per square meter, filled grains per panicle, 1000-grain weight, and grain yield per hectare (GY/ha). Analysis of variance (ANOVA) and genetic parameters, including environmental coefficient of variation (ECV), genotypic and phenotypic coefficients of variation (GCV and PCV), heritability (h²), and genetic advance as a percentage of the mean (GAM), were calculated using Windostat Version 9.1. Results: The ECV was low across all traits, indicating minimal environmental influence. GCV was low for DFF (4.957%) and PH (4.789%) but moderate for filled grains per panicle (15.874%) and 1000-grain weight (16.33%). PCV was slightly higher than GCV for most traits, confirming limited environmental effects. Heritability ranged from medium (37.4% for GY/ha) to very high (99.7% for 1000-grain weight). GAM was high for filled grains per panicle (31.96%) and 1000-grain weight (33.586%), indicating strong potential for genetic improvement. Conclusion: Traits with high heritability and genetic advance, such as filled grains per panicle and 1000-grain weight, are ideal for selection. These findings will aid in enhancing rice breeding programs through targeted genetic improvement.

Strategies and Protocols for Optimized Genome Editing in Potato.

The potato family includes a highly diverse cultivar repertoire and has a high potential for nutritional yield improvement and refinement but must in line with other crops be adapted to biotic and abiotic stresses, for example, accelerated by climate change and environmental demands. The combination of pluripotency, high ploidy, and relative ease of protoplast isolation, transformation, and regeneration together with clonal propagation through tubers makes potato highly suitable for precise genetic engineering. Most potato varieties are tetraploid having a very high prevalence of length polymorphisms and small nucleotide polymorphisms between alleles, often complicating CRISPR-Cas editing designs and strategies. CRISPR-Cas editing in potato can be divided into (i) characterization of target area and in silico-aided editing design, (ii) isolation and editing of protoplast cells, and (iii) the subsequent explant regeneration from single protoplast cells. Implementation of efficient CRISPR-Cas editing relies on efficient editing at the protoplast (cell pool) level and on robust high-throughput editing scoring methods at the cell pool and explant level. Gene and chromatin structure are additional features to optionally consider. Strategies and solutions for addressing key steps in genome editing of potato, including light conditions and schemes for reduced exposure to hormones during explant regeneration, which is often linked to somaclonal variation, are highlighted.

Utilizing Deep Learning for Field-Level Information Extraction from German Real Estate Tax Notices

ABSTRACT Document processing and related tasks such as information extraction represent a large portion of business workloads and therefore offer high potential for efficiency improvements and process automation. Although semistructured documents such as invoices and receipts have been extensively studied, tax notices represent a largely unexplored area due to their information richness and layout complexity. This article presents a study investigating the potential of deep learning-based information extraction for German real estate tax notices. We propose a hybrid approach based on the LayoutLM transformer model that uses textual, positional, and visual information as well as a rule-based information extraction. We show how such a system can be developed and integrated into the business workflow of organizations on the example of a German tax consulting firm. We also discuss the implications and key challenges that organizations face when planning to adopt such technologies. Data Availability: Custom data and code are not publicly available. Relevant public source code is cited in the text. JEL Classifications: M15; M40; M41.

Trends of diagnostic adverse events in hospital deaths: longitudinal analyses of four retrospective record review studies.

To investigate longitudinal trends in the incidence, preventability, and causes of DAEs (diagnostic adverse events) between 2008 and 2019 and compare DAEs to other AE (adverse event) types. This study investigated longitudinal trends of DAEs using combined data from four large Dutch AE record review studies. The original four AE studies included 100-150 randomly selected records of deceased patients from around 20 hospitals in each study, resulting in a total of 10,943 patient records. Nurse reviewers indicated cases with potential AEs using a list of triggers. Subsequently, experienced physician reviewers systematically judged the occurrence of AEs, the clinical process in which these AEs occurred, and the preventability and causes. The incidences of DAEs, potentially preventable DAEs and potentially preventable DAE-related deaths initially declined between 2008 and 2012 (2.3 vs. 1.2; OR=0.52, 95 % CI: 0.32 to 0.83), after which they stabilized up to 2019. These trends were largely the same for other AE types, although compared to DAEs, the incidence of other AE types increased between 2016 (DAE: 1.0, other AE types: 8.5) and 2019 (DAE: 0.8, other AE types: 13.0; rate ratio=1.88, 95 % CI: 1.12 to 2.13). Furthermore, DAEs were more preventable (p<0.001) and were associated with more potentially preventable deaths (p=0.016) than other AE types. In addition, DAEs had more and different underlying causes than other AE types (p<0.001). The DAE causes remained stable over time, except for patient-related factors, which increased between 2016 and 2019 (29.5 and 58.6 % respectively, OR=3.40, 95 % CI: 1.20 to 9.66). After initial improvements of DAE incidences in 2012, no further improvement was observed in Dutch hospitals in the last decade. Similar trends were observed for other AEs. The high rate of preventability of DAEs suggest a high potential for improvement, that should be further investigated.

Design and performance evaluation of a novel parallel kinematic micromanipulator

The targeted placement of selected carbon nanotubes is associated with low throughput rates. Hence, this paper presents a novel stage design for the fully automatic assembly of carbon nanotube field-effect transistors (CNTFETs) via mechanical dry transfer. It constitutes the core module of an assembly machine for the precise deployment of nanotubes onto a prefabricated wafer. The mechanical dry transfer approach allows high level of carbon nanotube selectivity with the aim of enabling a high-volume fabrication of ultra-clean devices. The previous production rate of such ultra-clean devices is less than one per hour, which offers a high potential for improvement. The stage consists of a parallel kinematic mechanism (PKM) with 3 degrees of freedom (X2Y2C1) carrying two additional stacked axes (Z1C2). The PKM is suspended on a vacuum preloaded aerostatic bearing, voice coil motors (VCM) and flexure hinges. Together with a combination of high precision and resolution touch probe measurement systems close to its tool center point (TCP), high accuracy and low settling time can be achieved. Based on realistic manufacturing tolerances, a sensitivity analysis of the mechanism’s pseudo rigid body model (PRBM) suggests a theoretical closed-loop error below 0.15μm over the entire XY workspace of 20mm×2.8mm. Measurements of positioning motions show that the settling time can be decreased by the compensation of friction resistances inside the internal bearings of the VCMs.

Isentropic and exergy analyses of marine steam turbine segments at several loads

This research presents isentropic and exergy analyses of marine steam turbine segments at three loads. Turbine segment is a part of any cylinder which is placed between the steam entrance to the cylinder and first steam extraction, between steam extractions and finally between last steam extraction and steam exit from the cylinder. Division of each cylinder to the segments allows insight into the various cylinder parts operation and an observation is the cylinder properly balanced. The analyzed marine steam turbine is composed of two cylinders – High Pressure Cylinder (HPC) and Low Pressure Cylinder (LPC), while each cylinder has two segments. The dominant part of real mechanical power produced in HPC is actually produced in the first HPC part (segment 1), while in LPC, the dominant part of real mechanical power is produced in the last LPC part (segment 4). Segments 1 and 3 have the highest improvement potential (inlet segments of both HPC and LPC) due to the highest isentropic losses and exergy destructions. HPC is much better balanced cylinder because along with isentropic, also exergy efficiencies between its segments (segment 1 and segment 2) at all loads differ lower than 7%, while the same cannot be stated for the LPC which exergy efficiencies between segments (segment 3 and segment 4) at all loads differ more than 20%. Very low isentropic and exergy efficiencies of the segment 3, at all observed loads, indicate that this turbine segment is highly problematic and at least some of the turbine stages mounted in this segment have difficulties in operation or potential malfunction. In addition, segment 3 is also the highest influenced by the ambient temperature change in comparison to other segments. The ambient temperature increase from 5 °C up to 45 °C can decrease segment exergy efficiency between 1.31% and 3.17%, if all the segments and all loads of the analyzed marine steam turbine are observed.

Investigating the genetic determination of duration-of-fertility trait in breeding hens

The duration-of-fertility (DF), which was defined as the number of days when breeding hens lay fertile eggs following copulation or artificial insemination (AI), is an important economic trait in chick production when it has strong effects on fertile egg output and production costs. Little is known about the underlying genes and molecular markers related to DF trait to date. Here, we measured the DF of 701 Chinese Jinghong hens and 408 Jingfen hens. The DF showed high individual variability and potential for genetic improvement. Then, 192 Jinghong breeding hens were provided for a genome-wide association study, 27 SNPs respectively located in three genomic linkage regions (GGA1:41Kb; GGA3:39Kb and GGA8:39Kb) were suggested to be significantly associated with DF. Particularly, 6 of these 27 SNPs were further verified to be associated with DF in the 701 Jinghong and 408 Jingfen hens using PCR-RFLP genotyping method. These 27 SNPs were also mapped to 7 genes according to their genomic position. Furtherly, 5 of these 7 genes were tested using qPCR. Results show that the CYP2D6, WBP2NL, ESR1 and TGFBR3 mRNA expression levels of hens with long DF were significantly higher than the hens with short DF (P < 0.05). Overall, findings in our research provide new insight into the genetic basis of duration-of-fertility in breeding hens while providing new clues for further functional validation on the DF-related genetic regulation mechanism and improvement of DF through chicken breeding.

Exergo-economic approach for comprehensive evaluation of the performance of industrial-scale milk and coffee beverage process lines

This study aimed to perform comprehensive analyses of the performance of the industrial-scale production of three different beverages (whole milk, black coffee, and milk coffee) in carton aseptic and glass bottle packaging process lines from raw material to the secondary packed final product by using innovative exergo-economic approach to promote a detailed data for a sustainable, performance-efficient production and economy in beverage industry. System performance efficiencies (energy and exergy) for the whole of production lines and individual processing steps were determined, and the exergo-economic performance of the industrial productions of three different beverages was compared. The maximum overall exergy efficiencies for glass bottle and carton aseptic packaging lines were as 52.57 % and 55.90 %, respectively, in whole milk production whereas the minimum overall exergy efficiencies were for these lines were 47.39 % and 48.67 %, respectively, for milk coffee production. For whole milk, the process steps having the minimum exergy efficiency were the filling step in carton aseptic (23.14 %±1.25) and the seperation step (26.90 %±1.09) in glass bottle packaging lines. For black coffee and milk coffee productions, the process step with the highest improvement potential was the homogenization/deaeration step for both carton aseptic and glass bottle packaging lines. The highest exergy destruction costs were obtained for the milk coffee; 72.52±0.03$/MJ for carton aseptic package and 63.82±1.85$/MJ for glass bottle. The most cost-efficient process was determined to be the black coffee in the carton aseptic packaging line due to the minimum product cost rate (89.71±2.39 $/MJ). It is thought that this study contributes valuable information on the approach of the comparing the performance of different production lines using exergo-economic evaluation.

The Logistics of Volkswagen Development Center Applies Operations Research to Optimize Transshipments

Volkswagen Technical Development (TE) is responsible for all prototype development and prototype production for the Volkswagen brand and has its own logistics department (TE-Logistics). In the logistics of prototype parts in the automotive industry, new versions of prototype parts (henceforth referred to as updating parts) are repeatedly assembled in finished prototype vehicles. These updating parts are stored in warehouses and provided to an assembly site to ensure a timely assembly of the associated prototype vehicles. As the internal warehouse on the company site is not large enough for the high variety of parts, an additional external warehouse in the logistics network is needed. However, since prototype parts are unique, the allocation of the parts in suitable warehouses is particularly important. Currently, the various warehouses and the short-term demands repeatedly lead to reactive transshipments between the warehouses. To this end, we developed an approach for proactive transshipments based on a machine learning forecast and a mixed-integer linear programming model for planning proactive transshipments of parts between the warehouses to minimize transport costs. The model is based on a probability estimation of future demands to anticipate the expected optimal warehouse. After the model had revealed high improvement potential through a case study with real-world data in terms of costs and availability time compared to the current reactive process, we derived decision rules and developed a rule-based heuristic algorithm that leads to the optimal solution for the industrial use case. We implemented the heuristic with a spreadsheet-based decision support system (DSS) for daily transshipment planning. After successful test implementation, TE-Logistics estimated the annual cost savings for transport to be approximately 10%.

On the Secondary Flow System of an Aggressive Inter Compressor Duct

Abstract In contrast to the highly optimized rotating components, the inter compressor duct (ICD) is offering a high potential for further improvements. Due to a more aggressive design, the length of the whole engine can be reduced. Shorter and thus lighter engines are leading to further fuel savings for the next engine generation. The design of current ICDs is very conservative because of high uncertainties in design space. An extensive test campaign on two highly aggressive ICDs has been conducted at an annular cascade at German Aerospace Center (DLR) Cologne to explore these limitations. The test section consists of low-pressure compressor (LPC)-OGVs, struts, and high-pressure compressor (HPC)-inlet guide vanes (IGVs). To simulate the influence of the last rotor of the LPC and to vary the incidence of the OGV, a moveable swirler is placed in front of the OGV. This simplification results in differences compared to a real rotor outlet flow. Due to geometric constraints, the ability to move the swirler can only be achieved by adding partial gaps in the rear part of the swirler at hub and shroud. These gaps have a huge impact on the secondary flow structure of the swirler outflow and therefore on the inflow of the ICD. In this article, the secondary flow system of an aggressive ICD is analyzed in detail by the means of experimentally validated computational fluid dynamics (CFD) simulations. Special attention is given to the influence of the nonrotating swirler on the secondary flow system. Furthermore, a recommendation for future experimental setups with respect to the described effects is concluded.

Genetic diversity, heritability, and estimated breeding values for growth of domesticated Asian seabass Latescalcarifer from Thailand

To establish a new breeding program, genetic diversity of five domesticated populations and two commercial stocks of Asian seabass (Lates calcarifer) were examined. Moderate levels of genetic diversity based on microsatellite polymorphism were found. The number of alleles per locus (NA) was 3.429–11.571. Observed (Ho) and expected (He) heterozygosities were 0.416–0.772 and 0.423–0.805. FST and genetic heterogeneity analysis revealed significant genetic differences of most pairwise comparisons (P < 0.001). Genetic distance between populations was 0.000–0.703. Phylogenetic analysis divided examined populations to two genetic stocks; A: DOF-Chachoengsao 2, DOF-Songkhla, and DOF-Trang and B: Commercial Farm 1 (Phuket) and Commercial Farm 2 (Chachengsao), DOF-Chachoengsao 1 and DOF-Krabi. The base population (G0, 51 families) was established from crosses between these founder populations. Heritability and estimated breeding values (EBVs) for growth in G0 families were evaluated at 519 day post hatch (dph, mean body weight = 616.64 ± 266.80 g, N = 1655). The heritability (h2) for growth of L. calcarifer in this study was 0.386 ± 0.020. The additive genetic coefficient of variation was 28% indicating high potential of genetic improvement for growth in this population. The distribution of EBVs showed high variation both between and within families. Fish exhibiting high EBVs (SATREPS-DOF-G0-hEBVs) clustered with a phylogenetic clade A while the SATREPS-DOF-G0-lEBVs group was phylogenetically allocated to clade B. Genetic selection with +1SD criteria is expected to achieve genetic gain of 28.5% per generation. The information on genetic diversity and EBVs estimates allows efficient implementation of our ongoing breeding program of L. calcarifer.

Implementatie van de Infectierisicoscan in een ziekenhuisnetwerk door het Hospital Outbreak Support Team

Implementation of the Infection Risk Scan in a hospital network by the Hospital Outbreak Support Team The Infection Risk Scan (IRIS) assesses the quality of infection prevention and control (IPC) and antimicrobial stewardship (AMS) in a hospital ward by the standardized measurement of a broad range of quality indicators. IRIS was implemented in the geriatric wards of the 4 hospitals of the Plexus healthcare network ‘Oost-Vlaams-Brabant’ (Belgium). The goal was to compare the IPC and AMS policies of the hospitals in order to define common improvement strategies within the Hospital Outbreak Support Team (HOST), a federal project concerning IPC and AMS. In the first part of IRIS, the risk profile of the patient population is determined by a point prevalence measurement of 4 variables. In the second part, the improvement plot is created based on the measurement of 7 quality indicators. Improvement actions can be deduced from quality indicators with higher improvement potentials. The risk profiles of the 4 hospitals were highly comparable and the improvement plots showed an intermediate to high improvement potential for the use of AMT and hand hygiene compliance. There were important differences in the appropriate use of transurethral and intravascular catheters, with 2 hospitals having a low and 2 hospitals having a high improvement potential. IRIS was a useful tool in the early phase of the HOST project to benchmark the IPC and AMT policies between the Plexus hospitals and to decide what future projects could be collaborated on. As a result of IRIS, it was decided to define common care bundles for the prevention of catheter-associated urinary tract and blood stream infections and to determine hospital-specific actions with regard to the optimisation of AMS.

Exploring Variability, Character Association and Path Analysis in Chickpea (Cicer arietinum L.) Accessions in the Northwestern Region of India

Assessing genetic variability makes it easier to identify stronger genotypes, allowing to produce high-yielding crops that are climatically resilient and promote efficient crop improvement. The present study aimed to assesses the genetic variability, association study &amp; path analysis of 51 chickpea [Cicer arietinum (L.)] genotypes on 12 characteristics. The experiment utilized Randomized complete block design with three replications conducted in Phagwara, Punjab. The ANOVA recorded significant variance at the 1% level for all traits, indicating considerable variability amongst germplasm. SY expressed comparatively high Genotypic coefficient of variance and heritability with other traits, indicating that it is the most heritable trait and has the highest potential for improvement through selective breeding. Positive correlation with SY was revealed by PH, NPB, NSB, NPP, NFP, TW, BY, HI. Path analysis revealed that NFP had highest positive effect on SY followed by NUFP, HI, BY, NSB, TW, DFF &amp; DM suggesting selection from any of these traits would be beneficial. When selecting traits to improve yield in chickpea through breeding, it is essential to focus on specific characteristics that directly contribute to higher production. This research will help understand yield-influencing factors for resilient chickpea varieties in Punjab environmental conditions.

Design of a Solar Dish Receiver and Life Cycle Assessment of a Hot Water System

The energy sector is the main source of greenhouse gases, so it has the highest potential for improvement. The improvements can be achieved by generating energy from renewable sources. It is necessary to combine production from renewable sources with storage systems. Thermal energy storage using concentrated solar power systems is a promising technology for dispatchable renewable energy that can guarantee a stable energy supply even in remote areas without contributing to greenhouse gas emissions during operation. However, it must be emphasised that greenhouse gases and other impacts can occur during the production process of concentrating solar system components. This paper analyses the receiver design to produce thermal energy for the existing CSP dish plant at the Energy Center of the Politecnico di Torino. The plant is designed to produce electrical energy in the spring and summer periods. In addition to this energy production, the CSP can be adopted to produce thermal energy, through hot water, during the less favourable periods of the year in terms of global solar radiation. The surface heat flux is calculated in the first part of the analysis to obtain the maximum internal temperature in the receiver, which is 873.7 °C. This value is a constraint for the choice of material for the solar receiver. A life cycle assessment is performed to compare the emissions generated during the production of the main components of the CSP system with the emissions generated by the methane-fuelled water heater to produce the same amount of thermal energy. It can be concluded that the production of the main components of the CSP system results in lower greenhouse gas emissions than the operational phase of a conventional system. Given the assumptions made, the utilization of methane leads to the emission of approximately 12,240 kg of CO2, whereas the production of the CSP system results in emissions totalling 5332.8 kg of CO2 equivalent

Evaluation of genetic parameters of growth traits in G2 selected generation of Penaeus monodon

Fifteen whole sib families of the second-generation Penaeus monodon were constructed using artificial mating design in 2020. After labeling the families with fluorescent markers, the growth traits and genetic parameters were evaluated in a cement pond for 56 days. The results showed that the coefficient of variation of growth traits was 11.52-47.53%, indicating a high genetic variation. The heritability range of growth traits of the G2 population of P. monodon was 0.25±0.03-0.41±0.13, which belonged to medium and high heritability, and the statistical test results were significant (P&lt;0.01). The heritability of body length and body weight were 0.38±0.11 and 0.41±0.13, respectively. The evaluation results of genetic correlation among growth traits were highly positive, and the statistical test results were significant (P&lt;0.01). The genetic correlation between body weight and body length was the highest (0.99), and the genetic correlation between the width of the first carapace and the height of the first abdominal segment was the lowest (0.71). The phenotypic correlation between body weight and body length was the highest (0.93), and the lowest was head breastplate width and first abdominal segment height (0.53). These results showed that the G2 generation population of P. monodon has high genetic improvement potential, and the combination of family selection and individual selection achieved better genetic gain. The growth traits were highly positively correlated. Body length and body weight could be selected as the key traits for fast growth line selection, while the other growth traits could be indirectly selected through positive genetic correlation.

An Empirical Evaluation of a New Heuristic Method for Identifying Safety Improvement Sites on Rural Highways: An Oregon Case Study

Road safety is considered one of the fundamental factors for sustainable mobility, which requires establishing effective highway safety management programs and processes. Identifying safety improvement sites (network screening) is a critical step in the state roadway safety programs. The overall effectiveness of these programs largely relies on the robustness of the network screening method in identifying sites with high potential for safety improvements. This study investigates the network screening performance of a new proposed methodology that employs heuristic scoring schemes to account for roadway and roadside characteristics, crash history, and traffic exposure. The new method, originally proposed for use on rural low-volume roads, is simplistic in that it does not require exact and detailed information on traffic and geometric characteristics and can still be applied in the absence of crash data. The performance evaluation is conducted using a sample of 1495 miles of rural two-lane highway segments in Oregon. The effectiveness of the proposed method is assessed using observed crash history and compared to the well-established Empirical Bayes method as a reference. The effect of traffic level on the performance of the proposed method was evaluated using separate analyses for lower and higher traffic volume segments. The study findings indicate that the effectiveness of the proposed method in identifying sites with potential safety improvements is overall high and slightly exceeded that of the more sophisticated and data-intensive Empirical Bayes method. When data were stratified by traffic volume, the proposed method was found to be more effective for lower volume roads; however, the Empirical Bayes method outperformed the proposed method for higher volume roads.

Towards improving agility in public administration

In times of crises, such as the refugee crisis or the corona pandemic, the workload in public administrations increases because of the demands of citizens or short-term legal changes. In addition, there is an increasing need for digitalization or to be able to react flexibly to changes. Agile process models and agile practices are appropriate to overcome these challenges. The objective of this paper is to investigate how public administrations can measure their degree of agility to identify potential for improving it. The authors conducted a descriptive single-case study which included multiple units of analysis in a public administration in Germany. The case study was supported by their questionnaire for measuring the degree of agility. One outcome of this study is a conceptual framework that can be used to drive agile transformation in public administrations by continuously measuring agility. Therefore, a questionnaire for measuring agility at team level in public administrations has been developed. The application of the questionnaire in three teams provide insights into dysfunctionality in the interdisciplinary teams as well as optimization potential in terms of affinity to change. The adoption of agility in public administration is a challenge, given that resistance to change is still prevalent. A transformational change is a constant journey, and therefore, the measurement of progress plays an important role in the continuous improvement of an organization. The applied approach delivers high potential for improvement in terms of agility and provides interesting insights for both practitioners and academics.

Investigating shared decision-making during the use of a digital health tool for physical activity planning in cardiac rehabilitation.

Shared decision making (SDM) between healthcare professionals and persons with CVD can have a positive impact on motivation, adherence, or sustainability regarding long-term goals and integration of cardiovascular disease (CVD) rehabilitation in the everyday lives of persons with CVD. SDM can foster the transition between regular heart-healthy activity at rehabilitation facilities and more independent activity at home, but it is often challenging to implement SDM given limited time and resources, e.g., in the daily practice of rehabilitation. Digital tools can help but must be appropriately tailored for situated use and user needs. We aimed to (1) describe in how far SDM is manifested in the situated context when using a digital tool developed by our group, and, based on that, (2) reflect on how digital health tools can be designed to facilitate and improve the SDM process. In the context of a field study, we investigated how SDM is already naturally applied and manifested when using a digital tool for joint physical activity planning in cardiac rehabilitation in clinical practice. In a two-week qualitative study, we collected data on expectations, experiences and interactions during the use of a digital health tool by seven persons with CVD and five healthcare professionals. Data was collected by means of observations, interviews, questionnaires and a self-reported diary, and analysed with a particular focus on episodes related to SDM. We found that SDM was manifested in the situated context to limited extent. For example, we identified high improvement potential for more structured goal-setting and more explicit consideration of preferences and routines. Based on mapping our findings to temporal phases where SDM can be adopted, we highlight implications for design to further support SDM in clinical practice. We consider this as "SDM supportive design in digital health apps," suggesting for example step-by-step guidance to be used during the actual consultation. This study contributes to further understanding and integration of SDM in digital health tools with a focus on rehabilitation, to empower and support both persons with CVD and healthcare professionals.