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This study uses computer-aided design to improve the ecological and environmental sustainability of early-stage landscape designs. Urban expansion on open land and natural habitats has led to a decline in biodiversity and increased climate change impacts, affecting urban inhabitants' quality of life and well-being. While sustainability indicators have been employed to assess the performance of buildings and neighbourhoods, landscape designs' ecological and environmental sustainability has received comparatively less attention, particularly in early-design stages where applying sustainability approaches is impactful.

The authors propose a computation framework for evaluating key landscape sustainability indicators and providing real-time feedback to designers. The method integrates spatial indicators with widely recognized sustainability rating system credits. A specialized tool was developed for measuring biomass optimization, precipitation management and urban heat mitigation, and a proof-of-concept experiment tested the tool's effectiveness on three Mediterranean neighbourhood-level designs.

The results show a clear connection between the applied design strategy to the indicator behaviour. This connection enhances the ability to establish sustainability benchmarks for different types of landscape developments using parametric design.

The study allows non-expert designers to measure and embed landscape sustainability early in the design stages, thus lowering the entry level for incorporating biodiversity enhancement and climate mitigation approaches.

This study expands the parametric vocabulary for measuring landscape sustainability by introducing spatial ecosystem services and architectural sustainability indicators on a unified platform, enabling the integration of critical climate and biodiversity-loss solutions earlier in the development process.

The present study aims to investigate the psychometric properties of the picture story exercise (PSE), a tool for measuring implicit motivations in Iran.

The research method is descriptive correlation and was conducted in two studies. In the first study 24 psychology master’s students were selected by convenience sampling method and tested them to check retest and inter-coder reliability. The second study investigated the correlation between self-reports and the PSE test on a sample of managers. Its statistical population comprised all the managers of a refinery company, 50 people were selected by convenience sampling method. To check the concurrent validity of the PSE test, the participants of the second study, completing the PSE, also completed the needs questionnaire of Steers and Porter (1979).

The findings showed that the PSE test in the Iranian sample had high retest reliability (0.62 on mean) and inter-coder reliability (0.87 on mean), and, following previous research, it does not show a significant relationship with self-reported motives.

PSE can be used in future research as a tool that has demonstrated its reliability and validity in the Iranian sample.

Measurement of implicit motives is a practical factor for predicting people’s behavior, the necessity of using tools that can accurately evaluate implicit motives is strongly felt. Taking into account the fact that so far, in Iranian samples, implicit motivations have not been measured, therefore, the current research is trying to answer this question, whether one of the most important and prominent tools that were made for this purpose and used in various studies can also be used in Iranian samples.

In the past few decades, performance measuring systems have become important managerial tools for healthcare organizations. Healthcare performance metrics are a useful tool in understanding how healthcare organizations achieve their goals while satisfying the needs of their patients and conforming to national and international standards. Various efforts have been made to assess healthcare performance. Most of these measures are focused on a single perspective or developed by a single source to meet management and strategic objectives on time.

We develop a review of the literature to shed light on the measures used to assess performance in the healthcare sector at various points in time, as well as to establish a thorough understanding of healthcare performance measurement.

Developing real-time digital traceability of metrics and an integrative perspective that increases the actionability of information acquired is an attractive potential made possible by the introduction of new technologies and the digitization of data.

We conclude that a proper measurement system should be one to combine patient, physician, non-medical staff and system perspective, which will further facilitate the assessment of healthcare performance and the comparative function.

Three-dimensional (3D) casting means using additive manufacturing (AM) techniques to print the mould for casting the cast tool. The printed mould, however, should be checked for its dimensional accuracy. 3D scanning can be used for the same. The purpose of this study is to combine the different AM techniques for 3D casting with 3D scanning to produce parts with close tolerance for preparing electrical discharge machining (EDM) electrodes.

The four processes, namely, stereolithography, selective laser sintering, fused deposition modelling and vacuum casting, are used to print the casting mould. The mould is designed in two halves, assembled to form a complete mould. The mould is 3D scanned in two stages: before and after using it as a casting mould. The mould's average and maximum dimensional deviations are calculated using 3D-scanned results. The eutectic Sn-Bi alloy is cast in the mould. The surface roughness of the mould and the cast tool are measured.

The cast tool is selected from the four processes in terms of dimensional accuracy and surface finish. The same is electroplated with copper. The microstructure of the cast tool (low-melting-point alloy) and deposited copper is analysed using a scanning electron microscope. Energy dispersive spectroscopy and X-ray diffraction techniques are used to verify the composition of the cast and coated alloy. The electroplated tool is finally tested on the EDM setup. The material removal rate and tool wear are measured. The performance is compared with a solid copper tool. The free-form customised EDM mould is also prepared, and the profile is cast out. The same is tested on the EDM. Thus, the developed path can be successfully used for rapid tooling applications.

The eutectic composition of Sn-Bi is cast in the 3D-printed mould using different AM techniques combined with 3D scanning quality to check its feasibility as an EDM electrode, which is a novel work and has not been done previously.

The circular economy concept emerged as the resolution to the destructive linear economy practices. Nevertheless, the transition to a circular built environment is hindered due to the ambiguities of the economic value of the concept. Conversely, numerous decision-making tools are applied in the construction industry in assessing economic alternatives, even if there is a gap in utilising these tools in appraising circular economic practices. Hence, this study investigates the potential benefits of applying proven decision-making practices, particularly criteria scoring matrices, in developing circular built environments.

A qualitative approach was followed to achieve the aim of the study. A conceptual design of a criteria scoring matrix was developed with a comprehensive literature survey. Semi-structured interviews of a three-round Delphi expert survey were employed to assess the matrix qualitatively and develop the matrix further. Data were analysed using the content analysis method.

The lack of a value assessment tool in economically assessing the circular economy principles is a key barrier to transcending to a circular built environment. In addressing this issue, this study develops a criteria scoring matrix for circularity value assessment during the design stage of a construction project.

This research contributes to the theory by developing a criteria scoring matrix to measure the economic contribution of circular economy principles. Further, this research contributes to the practice by allowing construction alternatives to be selected, balancing the potential economic return options of a project with the project's contribution to a circular economy.

The concept of developing clothing sizes has taken importance in recent years due to increasing expectations of consumers for branded clothing and its value in terms of fit and durability. The kids’ ready-to-wear brands are expected to pose the least fit issues, thereby covering a wider population of a particular size. This necessitates the standardization of measurements. The lack of standardized approaches has caused fit issues like mismatching of sizes and alterations, in a heterogenous consumer market, like India. The performance of branded apparel depends on the quality of the measurements considered in developing sizes and the approach for standardization. There is a lacuna in the measurements used by the kids’ apparel domestic brands. This study aims to propose an anthropometric approach for deriving quality measurements that can be used effectively in developing kids’ sizes to fit a wider population of kids, thereby reducing the need for alterations.

The measurement data was gathered through the quantitative method. An anthropometric survey was conducted by measuring school kids. A total of 544 kids (girls and boys) of age group 6–8 years were measured to obtain prime anthropometric measurements required for ready-to-wear apparel production. WHO manual and ISO 8559, 1998 meant for anthropometry survey for garment industry was referred for accurate measuring following the landmarks for measuring.

The findings revealed differences in the anthropometric measurements based on gender and age. The anthropometric measurements showed variations within the same body mass index (BMI) range. S, M and L sizes were identified within an age group. The apparel manufacturers and designers need to focus on the discrepancies occurring in the body measurements of an age group to address and control fit issues in kids ready to wear apparel.

The anthropometric approach can be significantly used to control undesired fit and comfort issues in kids’ ready-to-wear apparel.

This study helped to understand the importance of scientific measuring practices to arrive at standardized measurements to develop sizes in ready-to-wear apparel manufacturing.

Based on profound information lacking in compiled information materials, the risks of losing knowledge related to the values of traditional woodworking processes are increasing. The purpose of this article is to collect and structure diverse marking tool data into a comprehensive, understandable and clear design schematic view, which serves as a basis for the accumulation and preservation of diverse marking objects and shows woodworking marking tool relation in the group and subgroup levels.

A method for marking tools structuring and analysis are described, including breaking down a set of objects into groups of marking objects, and assigning one or more attributes to the parcelled objects by arranging them into hierarchic levels. Research is based on marking tools used by carpenters, joiners and woodcarvers mainly in the Baltic region.

Collected data, object analyses and comparison within-group and subgroup levels are based on written and visual sources, museum and museum funds visits, and participation in the local craftsmen events. The created structure is expandable in group and subgroup levels. The most comprehensive way for object structuring is chosen as a base to reveal a diversity of the objects.

Structure schemes of woodworking marking tools are important in scientific, educative and cultural levels based on their wide range and use. Aggregated information of the woodworking tools serves as a base for existing tool studies and improvement, new tool and wood product creation as well as complements the structure of the upcoming woodworking hand tool database and book.

This paper undertakes an extensive and systematic review of the literature on earnings management (EM) over the past three decades (1992–2022). Furthermore, the study identifies emerging research themes and proposes future avenues for further investigation in the realm of EM.

For this study, a comprehensive collection of 2,775 articles on EM published between 1992 and 2022 was extracted from the Scopus database. The author employed various tools, including Microsoft Excel, R studio, Gephi and visualization of similarities viewer, to conduct bibliometric, content, thematic and cluster analyses. Additionally, the study examined the literature across three distinct periods: prior to the enactment of the Sarbanes-Oxley Act (1992–2001), subsequent to the implementation of the Sarbanes-Oxley Act (2002–2012), and after the adoption of International Financial Reporting Standards (2013–2022) to draw more inferences and insights on EM research.

The study identifies three major themes, namely the operationalization of EM constructs, the trade-off between EM tools (accrual EM, real EM and classification shifting) and the role of corporate governance in mitigating EM in emerging markets. Existing literature in these areas presents mixed and inconclusive findings, suggesting the need for further theoretical development. Further, the study findings observe a shift in research focus over time: initially, understanding manipulation techniques, then evaluating regulatory measures, and more recently, investigating the impact of global accounting standards. Several emerging research themes (technology advancements, cross-cultural and cross-national studies, sustainability, behavioral aspects and non-financial indicators of EM) have been identified. This study subsequent analysis reveals an evolving EM landscape, with researchers from disciplines like data science, computer science and engineering applying their analytical expertise to detect EM anomalies. Furthermore, this study offers significant insights into sophisticated EM techniques such as neural networks, machine learning techniques and hidden Markov models, among others, as well as relevant theories including dynamic capabilities theory, learning curve theory, psychological contract theory and normative institutional theory. These techniques and theories demonstrate the need for further advancement in the field of EM. Lastly, the findings shed light on prominent EM journals, authors and countries.

This study conducts quantitative bibliometric and thematic analyses of the existing literature on EM while identifying areas that require further development to advance EM research.

The aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.

This study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.

Cutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.

This submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.

This study aims to fully assess the readiness for Lean Six Sigma (LSS) and Quality Performance Improvement (QPI) in an Italian Public Healthcare ecosystem.

Drawing from previously established survey development and adaptation protocols, a replication study was carried out; Lean, Six Sigma and QPI were extracted and validated through confirmatory factor analysis in an Italian Public Healthcare setting, with a sample of health professionals from the Campania region.

This study reports the adaptation of an existing scale for measuring LSS and QPI in an Italian public healthcare organisation. This analysis extracts six conceptual domains and constitutes an original adaptation of an existing scale to assess the readiness to adopt Lean, Six Sigma and Quality Performance in Italian Public Health Organizations. The constructs show strong levels of internal consistency, as demonstrated by each item factor loading and each subscale reliability.

Managers, policymakers and academics can employ the proposed tool to assess the public healthcare ecosystem’s capability to implement LSS initiatives and strategies to improve quality performance.

This is one of the first studies to assess cross-regional organisational readiness for LSS and QPI in an Italian Public Healthcare environment at this scope and level.