Project Model Research Articles

Research on Performance Evaluation of Sponge City PPP Projects in the Yangtze River Delta Region

In order to alleviate urban water ecological problems and promote sustainable urban development, many cities in my country are building sponge cities. At present, the country is vigorously promoting the application of the PPP model for project construction. The national government departments are actively preparing for the construction of sponge cities, promoting the construction of sponge cities in 30 pilot cities across the country, and encouraging sponge city construction projects using the PPP model, attracting a large amount of social capital to participate, and promoting The PPP model has been widely used in sponge city construction projects. This article takes the sponge city PPP project as the research object. In order to scientifically and rationally evaluate the construction performance of the sponge city PPP project, and on the basis of studying and summarizing the characteristics of the sponge city PPP project model and the development status of the performance evaluation system in my country, we conduct an analysis of the content of the performance evaluation. and research; establish and select a performance evaluation index system; conduct a comparative analysis of this model with other commonly used models, and build a PSIR-based PPP project performance evaluation model based on the design flaws of the existing performance evaluation system; and analyze and summarize the data. , clarifying its specific application and impact in practice; finally, a summary and outlook of the entire research are given.

Virtual trial assembly of large steel members with bolted connections based on multiscale point cloud fusion

AbstractVirtual trial assembly (VTA) using 3D laser scanning as the digital carrier can overcome the shortcomings of time‐consuming and costly physical preassembly. However, its application in large steel structures with bolted connections remains limited. First, this study introduces a novel approach for acquiring multiscale point cloud data of large steel members using terrestrial laser scanners (TLSs) and hand‐held scanner (HHS). This approach considers both the global data and the local details of the steel members. Additionally, a precise registration method based on magnetic 3D targets is proposed for multiscale point clouds, which enables the registration accuracy of multisource point clouds to reach submillimeter precision. Subsequently, a novel algorithm for feature point screening is introduced, which utilizes a dichotomous point cloud grid approach to identify and extract a significant quantity of bolt holes effectively. This approach enables fully automated and fast extraction of the point cloud on the cylindrical inner surface of the holes. Finally, the bounding box and Procrustes analysis approach are employed to perform VTA using the point cloud of the cylindrical bolt holes as the assembled features. The accuracy and feasibility of the above method are verified by a down‐scale modeling experiment and project test, which provide technical support for the VTA of large steel truss structures.

Relative and Combined Impacts of Climate and Land Use/Cover Change for the Streamflow Variability in the Baro River Basin (BRB)

The interplay between climate and land use/cover significantly shapes streamflow characteristics within watersheds, with dominance varying based on geography and watershed attributes. This study quantifies the relative and combined impacts of land use/cover change (LULCC) and climate change (CC) on streamflow variability in the Baro River Basin (BRB) using the Soil and Water Assessment Tool Plus (SWAT+). The model was calibrated and validated with observed streamflow data from 1985 to 2014 and projected the future streamflow from 2041 to 2070 under two Shared Socio-Economic Pathway (i.e., SSP2-4.5 and SSP5-8.5) scenarios, based on the ensemble of four Coupled Model Intercomparison Project (CMIP6) models. The LULCC was analyzed through Google Earth Engine (GEE) and predicted for the future using the Land Change Modeler (LCM), revealing reductions in forest and wetlands, and increases in agriculture, grassland, and shrubland. Simulations show that the decrease in streamflow is attributed to LULCC, whereas an increase in flow is attributed to the impact of CC. The combined impact of LULCC and CC results in a net increase in streamflow by 9.6% and 19.9% under SSP2-4.5 and SSP5-8.5 scenarios, respectively, compared to the baseline period. Our findings indicate that climate change outweighs the impact of land use/cover (LULC) in the basin, emphasizing the importance of incorporating comprehensive water resources management and adaptation approaches to address the changing hydrological conditions.

Evaluation of ChatGPT and Gemini large language models for pharmacometrics with NONMEM.

To assess ChatGPT 4.0 (ChatGPT) and Gemini Ultra 1.0 (Gemini) large language models on NONMEM coding tasks relevant to pharmacometrics and clinical pharmacology. ChatGPT and Gemini were assessed on tasks mimicking real-world applications of NONMEM. The tasks ranged from providing a curriculum for learning NONMEM, an overview of NONMEM code structure to generating code. Prompts in lay language to elicit NONMEM code for a linear pharmacokinetic (PK) model with oral administration and a more complex model with two parallel first-order absorption mechanisms were investigated. Reproducibility and the impact of "temperature" hyperparameter settings were assessed. The code was reviewed by two NONMEM experts. ChatGPT and Gemini provided NONMEM curriculum structures combining foundational knowledge with advanced concepts (e.g., covariate modeling and Bayesian approaches) and practical skills including NONMEM code structure and syntax. ChatGPT provided an informative summary of the NONMEM control stream structure and outlined the key NONMEM Translator (NM-TRAN) records needed. ChatGPT and Gemini were able to generate code blocks for the NONMEM control stream from the lay language prompts for the two coding tasks. The control streams contained focal structural and syntax errors that required revision before they could be executed without errors and warnings. The code output from ChatGPT and Gemini was not reproducible, and varying the temperature hyperparameter did not reduce the errors and omissions substantively. Large language models may be useful in pharmacometrics for efficiently generating an initial coding template for modeling projects. However, the output can contain errors and omissions that require correction.

METHOD OF PROTOTYPING CONTROL UNITS BASED ON THE OPENPLC APPLICATION

The problem of designing control devices based on programmable logic controllers (PLCs) is their high cost and, as a rule, unavailability at the initial design stage. The purpose of the research is to reduce the time and cost of designing the system by creating prototypes of control units with the software implementation of control algorithms in the languages of the MEK 61131-3 standard and the execution of programs in the Arduino board. The research method consists in the decomposition of project models of operating and control automata of the control device and their implementation in the software environment of the OpenPLC application in the form of program organization components (POU) in Ladder Diagram, Function Block Diagram, Sequential Function Chart and Structured Text languages. The result of the study is a method of creating typical POU operating and control automata of the control system, which are executed in the Arduino board. An example of the application of the proposed methodology for the design of a prototype of the facility's temperature control system is given. The developed prototype was tested using a logical PLC and a physical prototype, which confirmed their functional compliance with the original and a reduction in the cost of the equipment by at least an order of magnitude.

Quantify uncertainty in historical simulation and future projection of surface wind speed over global land and ocean

Quantifying uncertainty in simulations of surface wind speed (SWS) has significant implications for its applications. Here, we examine the SWS changes from the 6th coupled model intercomparison project (CMIP6) model outputs, and analyzed the simulation uncertainties in CMIP6 both in the historical period and future projections. The results show that the both trend and interannual variability of SWS are underestimated in the CMIP6. The SWS over most of the Northern Hemisphere will reduce by 4%–6% under the high emission scenario in the last 21st Century, whereas it will increase by 6%–10% over South America and Southeastern Pacific. Over land, the majority of projection uncertainties is dominated by model uncertainty, followed by the internal variability and scenario uncertainty. Over ocean, the simulation uncertainty is greatly influenced by model uncertainty and internal variability, with the scenario uncertainty accounting for around 20% of total simulation uncertainty in the late 21st century.

Mechanism design for public projects via three machine learning based approaches

We study mechanism design for nonexcludable and excludable binary public project problems. Our aim is to maximize the expected number of consumers and the expected agents’ welfare. We first show that for the nonexcludable public project model, there is no need for machine learning based mechanism design. We identify a sufficient condition on the prior distribution for the existing conservative equal costs mechanism to be the optimal strategy-proof and individually rational mechanism. For general distributions, we propose a dynamic program that solves for the optimal mechanism. For the excludable public project model, we identify a similar sufficient condition for the existing serial cost sharing mechanism to be optimal for 2 and 3 agents. We derive a numerical upper bound and use it to show that for several common distributions, the serial cost sharing mechanism is close to optimality. The serial cost sharing mechanism is not optimal in general. We propose three machine learning based approaches for designing better performing mechanisms. We focus on the family of largest unanimous mechanisms, which characterizes all strategy-proof and individually rational mechanisms for the excludable public project model. A largest unanimous mechanism describes an iterative mechanism, which is defined by an exponential number of mechanism parameters. Our first approach describes the largest unanimous mechanism family using a neural network and training is carried out by minimizing a cost function that combines the mechanism design objective and the constraint violation penalty. We interpret the largest unanimous mechanisms as price-oriented rationing-free (PORF) mechanisms, which enables us to move the mechanisms’ iterative decision making off the neural network, to a separate simulation process, therefore avoiding the vanishing gradient problem. We also feed the prior distribution’s analytical form into the cost function to achieve high-quality gradients for efficient training. Our second approach treats the mechanism design task as a Markov Decision Process with an exponential number of states. During the Markov decision process, the non-consumers are gradually removed from the system. We train multiple neural networks, each for a different number of remaining agents, to learn the optimal value function on the states. Training is carried out by supervised learning toward a set of manually prepared base cases and the Bellman equation. Our third approach is based on reinforcement learning for a Partially Observable Markov Decision Process. Each RL episode randomly draws a type profile, which is hidden from the RL agent (mechanism designer). The RL agent only observes which cost share offers have been accepted under the largest unanimous mechanism under discussion. We use a continuous action space reinforcement learning approach to adjust the offer policy (i.e., adjust mechanism parameters). Lastly, our first two approaches use “supervision to manual mechanisms” as a systematic way for network initialization, which is potentially valuable for machine learning based mechanism design in general.

Prototypes as catalysts for cross-disciplinary collaboration: Viewpoints from applied food research and innovation

BackgroundPrototypes play a central role in applied food research and innovation (R&I), serving as the initial representations of new products, process, or project ideas. They function as "boundary objects", facilitating interdisciplinary dialogue, knowledge creation, and cooperation. Despite their significance, challenges arise due to the differing perspectives and creative behaviors of scientists in this field. This commentary addresses the question of how prototypes can foster collaboration across disciplines in applied food R&I. Scope and approachOur study explores the application of prototypes within the disciplines of innovation management, consumer and sensory science, and food science and technology. We provide an overview of the diverse roles of prototypes in the R&I process and elucidate their function of bridging interdisciplinary gaps and facilitating knowledge exchange. Furthermore, we analyze the use of prototypes across those disciplines, emphasizing their role as communication facilitators and mutual learning tools. Key findings and conclusionsWhile prototypes are indispensable in applied food R&I, they are predominantly employed in distinct phases according to the discipline, with a lack of interdisciplinary collaboration. However, we observed that prototypes often serve similar purposes across disciplines. Thus, we propose a wider integration of prototyping into research processes, to facilitate communication, improve mutual learning and knowledge exchange, and make research outputs easily transferable. Experienced facilitators should holistically manage diverse prototypes, fostering an iterative project model that transcends disciplinary boundaries. Our commentary emphasizes the transformative potential of prototypes advocating for their informed usage across disciplines to advance cross-disciplinary collaboration and align research outcomes with societal needs, thus supporting responsible applied food R&I.

Persistent climate model biases in the Atlantic Ocean's freshwater transport

Abstract. The Atlantic Meridional Overturning Circulation (AMOC) is considered to be one of the most dangerous climate tipping elements. The salt–advection feedback plays an important role in AMOC tipping behaviour, and its strength is strongly connected to the freshwater transport carried by the AMOC at 34° S, below indicated by FovS. Available observations have indicated that FovS has a negative sign for the present-day AMOC. However, most climate models of the Coupled Model Intercomparison Project (CMIP, phase 3 and phase 5) have an incorrect FovS sign. Here, we analyse a high-resolution and a low-resolution version of the Community Earth System Model (CESM) to identify the origin of these FovS biases. Both CESM versions are initialised from an observed ocean state, and FovS biases quickly develop under fixed pre-industrial forcing conditions. The most important model bias is a too fresh Atlantic Surface Water, which arises from deficiencies in the surface freshwater flux over the Indian Ocean. The second largest bias is a too saline North Atlantic Deep Water and arises through deficiencies in the freshwater flux over the Atlantic Subpolar Gyre region. Climate change scenarios branched from the pre-industrial simulations have an incorrect FovS upon initialisation. Most CMIP phase 6 models have similar biases to those in the CESM. Due to the biases, the value of FovS is not in agreement with available observations, and the strength of the salt advection feedback is underestimated. Values of FovS are projected to decrease under climate change, and their response is also dependent on the various model biases. To better project future AMOC behaviour, an urgent effort is needed to reduce biases in the atmospheric components of current climate models.

A structured approach for enhancing clinical risk monitoring and workflow digitalization in healthcare

A multitude of studies have highlighted alarming data on healthcare adverse events and medical errors in many countries, including Italy. Many of these errors appear to be the result of non-compliance with good practices and organizational operating procedures, specified in ministerial directives and international standards. This paper describes the efforts of an Italian research project to propose a structured approach to healthcare process management, emphasizing clinical risk management. Using the Business Process Model and Standard Notation (BPMN), the project models clinical processes and integrates them into the clinical information system to identify process deficiencies, highlight compliance vulnerabilities, monitoring and managing clinical risks. The workflows’ digitalization, enabled the definition and calculation of several Key Performance Indicators (KPIs) for a long-term evaluation of the success of the modeled processes. In the experimental phase, the project allowed to identify areas significantly affected by operational deviations, enabling targeted actions to safeguard patient health and generate economic savings due to the reduction of legal actions against medical workers’ errors. The effects of an overall improvement on quality of care can be appreciated not only by patients but also by medical and administrative staff of the clinics.

European identity's effect on immigration attitudes: Testing the predictions of the common Ingroup identity model versus ingroup projection model

AbstractA superordinate identity unites different subgroups into an overarching, common one. But does superordinate identification then improve or worsen attitudes towards the former outgroup? The common ingroup identity model (CIIM) asserts that recategorization ameliorates outgroup bias by reducing perceptions of intergroup threat. It predicts that superordinate identification will improve intergroup relations by promoting tolerance and acceptance of diversity. In contrast, the ingroup project model (IPM) asserts that identifying superordinately will actually exacerbate outgroup bias because ingroup members naturally project their own characteristics onto the superordinate category and will more strongly dislike the former outgroup for not fitting the “correct” superordinate prototype. Existing evidence—largely drawn from psychology lab experiments, not real‐world situations—suggests both models can be correct insofar as ingroup projection only occurs under certain conditions. In that case, which model is correct for European identity? Results from original survey data collected in three European countries (Germany, Poland, and the United Kingdom) show that increased identification with Europe is almost always associated with more favorable attitudes towards outgroup immigrants, even among those most likely to engage in ingroup projection. Future research should continue to investigate when and why this inclusivity does—and does not—hold.

Students' Perspectives on Innovation of Mathematics Learning Online Course on Their Ability to Develop Innovative Textbooks

The responsibility for developing professional and high-quality teacher candidates lies with the Education Institution for Educational Personnel (LPTK). However, achieving this goal is certainly challenging to achieve during this pandemic. This research explores student perspectives on the effectiveness of lectures in developing the ability to create innovative textbooks. The research employed quantitative descriptive methods and involved students from the mathematics education study program Universitas Negeri Semarang who were enrolled in the Innovation of Mathematics Learning course. The data were collected through questionnaires and analyzed using descriptive statistics. The results of the study indicate that preparing learning resources in modules is crucial during lectures. Additionally, activities such as synchronous lecture activities, use of Learning Management System (LMS), resources like videos, discussions with colleagues, virtual face-to-face, discussions using WhatsApp Group, presentation of each assignment, group assignments, and projects should be prepared during lectures. These results highlight the necessity of implementing a team-based project model to develop students’ abilities in developing innovative textbooks.
 Keywords: innovative textbooks, mathematics learning online course, students’ perspectives.

Development of climate informed management scenarios for fisheries in the eastern Bering Sea

Abstract In recognition of the impact of climate change on marine ecosystems worldwide, integrated research teams have coupled climate change projections with social-ecological models to inform management and evaluate adaptation strategies for the fishing industry and fishing communities. A key step in this process is the selection of scenarios that enable improved adaptation strategies and decision-making through engagements with constituents with diverse interests in the future use of marine resources. This paper presents an approach to selecting and refining climate-informed social-ecological scenarios for groundfish and crab fisheries in the eastern Bering Sea. The approach involved: (a) initial model development to provide worked examples; (b) engagement with stakeholders to seek input on climate-related concerns, priorities, and adaptation options; and (c) establishment of pathways for uptake of climate-informed decision support information into existing management systems. This approach narrowed the range of candidate scenarios, identified pressing climate concerns of constituents, and clarified timelines for scheduling modeling projects to address these concerns. Separating evaluation of management strategies (research modeling) from proposed changes to Fishery Management Plans preserved opportunities for public debate of proposed changes through a well-established regulatory review process. Collectively, these outcomes help to advance the development of a regionally relevant climate-ready harvest policy.

Contextual and Structural Factors, Project Modelling and Sustainability of Entrepreneurial Development Projects: A Conceptual Framework

Projects emanate from ideas to solve an underlying need. Ideally, a project aims to solve a problem among beneficiaries. Notwithstanding the imperative role of entrepreneurship in socioeconomic prosperity, sustainability of development projects focusing on the empowerment of entrepreneurs is gaining attention on the wheels of research. Of interest are entrepreneurial development projects that fail to attain the desired impacts despite huge capital investments. Ineffective decision-making associated with unrealistic expectations often implicates sustainable delivery of outcomes. Hoverers, foundations for sustainable delivery of entrepreneurship development projects are elusively theorized. Lack of theoretical consent and standardized practice of modelling project intervention relative to attaining sustainable deliverables deprives us of essential knowledge for decision-making. Failure to align project implementation models to the prevailing reality of entrepreneurship is believed to contribute to this dismal. Against the background, this paper presents a theoretical and conceptual framework for the interaction between contextual and structural factors, project modelling and sustainability of entrepreneurial development project interventions. 21 peer-reviewed articles were selected through screening. Meta-analysis was used to review the converging and diverging issues while identifying and synthesizing research gaps that connect with the research problem identified. While project modelling was found to be critical in achieving sustainable impacts, the findings were based on linear perspectives and ignored the prevailing structural and contextual dynamics. Hence, the proposition that structural and contextual factors mediate and moderate the sustainability of entrepreneurial development projects, respectively.

Повышение эффективности внедрения ТИМ на различных этапах жизненного цикла ОКС

The article analyzes the existing experience in introducing information modeling technology for a capital construction project at various stages of the life cycle. It is noted that the use of technology is considered at individual stages of the capital construction project life cycle , but there is no mechanism for transition from one information model to another. It was revealed that the rules for maintaining as-built documentation, reflecting not only the actual execution of design and working documentation decisions, but also the actual state of the building structure or its individual elements, are regulated, and the existing approach assumes that the operation of the building will be based on working documentation with changes made to reflect the current state object, i.e. on the basis of as-built documentation.
 The feasibility of information model developing with a different set of detail and attribute coating, corresponding to various types of documentation: design, working and executive, is substantiated.
 A universal roadmap for the information modeling technologies implementation in a design company has been developed, a proposed structure for storing information models of a construction project has been given, and further steps have been proposed for the implementation of information modeling technologies at subsequent stages of the life cycle of a capital construction project to increase the efficiency of its application.

Tools From The "Hat" of an Operational Manager, with an Applied: Case Study

Introduction to Operations Management is an essential starting point for understanding the complexity and importance of effectively managing resources and processes within contemporary organizations. According to Jay Heizer and Barry Render in their seminal work Principles of Operations Management, operations management is defined as the process of designing, managing, and improving processes and systems that create and deliver goods and services. It is a vital component of organizational strategy, having a direct impact on a company's competitiveness and market success. Through operational management, organizations can optimize the use of resources, improve efficiency and provide added value to their customers. We briefly present quantitative forecasting methods, go into detail in a case study with a causal (associative) forecast, then approach the linear regression calculation model. Also, we will estimate pancake sales using the Brown model of exponential leveling, the working tool being QM for Windows. We close the paper by punctually addressing methods of stock optimization by carrying out the case study with the method of uniform price reduction. Finally, we will schematically point out an investment project model for a pancake business.

Textile Trade of India with RCEP Members: A General Equilibrium Assessment

The study quantified Indian textile trade with selected Regional Comprehensive Economic Partnership (RCEP) countries, including Australia, China, Japan, Malaysia, South Korea, and Vietnam, based on their proportional share of the Indian textile trade to analyze the impact of RCEP on the Indian textile trade. The primary objective was to investigate the impact of a 10 per cent reduction in existing Indian tariffs with selected RCEP nations through Global Trade Analysis Project (GTAP) modelling. The study demonstrated that if India reduced tariffs on textile imports, it would allow a flood of imports from other competitive countries. As per the results, India will only achieve prosperity when selected RCEP nations reduce or eliminate their tariffs. The decision to withdraw from RCEP seems reasonable regarding its textile exports from India.

Activities Based on Sustainable Education to Foster Students’ English Language Speaking Skills

A quantity- qualitative research was developed at San Daniel Comboni School in the province of Esmeraldas in 2023, with the main aim of the investigating on some activities based on sustainable education to foster students’ English language speaking skills. The methos used were the documentary and explanatory study based on the socio-pedagogical project model with a quantitative approach, also it was used the Inductive – Deductive Metho, Analysis and Synthesis and Statistical one. The technique applied was the survey and the instrument was a questionnaire, and a sample of 46 students in the sixth year of Basic Education and 6 teachers of the mentioned school. The results obtained determined that in the classroom teachers are interested in applying tools focused on sustainable education so that students can strengthen the oral expression of the English language. Therefore, it is concluded that some activities based on sustainable education to foster students’ English language speaking skills in the sixth year of Basic Education students at the San Daniel Comboni School, located in Esmeraldas, in the period 2023. This fact is due to the fact that, through the use of teaching strategies, techniques and teaching resources, it is possible to encourage students to communicate in a natural and simple way in English, and being aware of what is happening around them.

Applying Lean Principles to Eliminate Project Waste, Maximize Value, Cut Superfluous Steps, Reduce Rework and Focus on Customer Centricity

With increasingly complex demands, dynamic environments, and rapid technology changes defining business landscapes, project management methodologies are prime for disruption. Traditional project models – characterized by rigid, sequential stage-gates and siloed functional groups – struggle with wastefulness, reactive mindsets, and misalignment to customer purpose. As such, practitioners are turning to lean philosophies pioneered in manufacturing but applicable across sectors. This paper examines deploying lean principles to project environments to eliminate activities that do not directly add customer value (waste), amplify learning, decide slowly but deliver quickly, empower teams, and continuously improve. Core facets of lean covered include Value Stream Mapping to visualize workflow and identify waste; Kanban systems to limit work-in-progress, facilitate pull-based work authorization, and surface bottlenecks; Root Cause Analysis to get to the heart of problems; 5S activities for well-organized, mistake-proof workstations; and Kaizen events for rapid iterations. As illustrated through integrated case studies, these tools and mindsets facilitate lean’s primary aim within projects – determining what matters for the end-customer and optimizing all activities to directly serve this purpose. Tactics covered include defining value from the beneficiary standpoint early on, focusing on enhancing workflow from end-to-end rather than functional silos, and instilling learning and improvement mechanisms at all levels – from C-suite leadership to ground floor production. The paper closes by delineating a gradual implementation methodology – factoring in change management challenges – as well as outlining skills development required for staff to transition toward cross-functional, accountable, lean-oriented teams. While specifics vary across industries and project types, overarching insights suggest the principles represent the future of project delivery – cutting waste-related costs by upwards of 30%, accelerating timelines by over a third, minimizing scrap/rework to near-zero levels, and serving customer goals substantially better. For leaders to position projects and organizations for increasing marketplace complexity, leanness is pivotal.

Celebrating and Leveraging Classroom Geographic and Cultural Diversity to Enhance Student Learning

In the fall of 2022, we offered a pedagogically redesigned sociotechnical environmental engineering elective for junior and senior undergraduates that applied place-based and culturally sustaining pedagogies. The course featured a project designed to facilitate the celebration and leveraging of classroom geographic and cultural diversity to enhance student learning about water sustainability. We analyzed the students’ written project reflections using an inductive thematic analysis to explore whether and how the project and pedagogical model augmented student learning. The primary themes that emerged included: (1) deepened knowledge of home and culture; (2) global conceptualizations; (3) re-evaluation of perceptions and beliefs (in terms of water sustainability and personal relationships with water); and (4) future-facing viewpoints. We consider each of these ‘enhancements’ to the student learning because they extend beyond the course objectives and explore the sociotechnical aspect of engineering. The purpose of this paper is to share the course and project model, our findings from its implementation, and suggestions on how this pedagogical framework could be adapted and scaled to expand the learning of a range of topics at different learner levels.