Large Projects Research Articles

The TRAPUM Large Magellanic Cloud pulsar survey with MeerKAT – I. Survey set-up and first seven pulsar discoveries

ABSTRACT The Large Magellanic Cloud (LMC) presents a unique environment for pulsar population studies due to its distinct star formation characteristics and proximity to the Milky Way. As part of the TRAPUM (TRAnsients and PUlsars with MeerKAT) Large Survey Project, we are using the core array of the MeerKAT radio telescope (MeerKAT) to conduct a targeted search of the LMC for radio pulsars at L-band frequencies, 856–1712 MHz. The excellent sensitivity of MeerKAT, coupled with a 2-h integration time, makes the survey 3 times more sensitive than previous LMC radio pulsar surveys. We report the results from the initial four survey pointings which have resulted in the discovery of seven new radio pulsars, increasing the LMC radio pulsar population by 30 per cent. The pulse periods of these new pulsars range from 278 to 1690 ms, and the highest dispersion measure is 254.20 $\mathrm{ pc} \, \mathrm{ cm}^{-3}$. We searched for, but did not find any significant pulsed radio emission in a beam centred on the SN 1987A remnant, establishing an upper limit of 6.3 $\mu \mathrm{ Jy}$ on its minimum flux density at 1400 MHz.

Russian diplomacy and western gas wars against Russia

The article is devoted to the study the use by Western countries, primarily the United States and the EU, of the gas factor for political and economic pressure on Russia in order to squeeze it out of world gas markets, primarily European, and reduce the fl ow of funds from Russian gas exports to the state budget. The article analyzes how, in order to achieve their goals, the United States and a number of members of the European Union manipulate the actions of Qatar, Turkey and the Balkan countries to disrupt the implementation of large gas projects to deliver gas from Russia to Europe through main gas pipelines along the bottom of the Baltic and Black Seas, bypassing Ukrainian transit. Special attention how the West has used and is using Ukraine to displace Russian pipeline gas from European markets. The article also considers how the West has used and is using Ukraine to displace Russian pipeline gas from European markets. Special attention is paid to the role of liquefi ed natural gas (LNG)to increase the supply of Russian gas to the world market, which makes it possible to reduce Russia's dependence on gas exports through pipelines. The issue of prospects for the reorientation of gas exports from the West to the East, primarily to China, is also being considered.

The Impacts on Interorganizational Project Coordination: A Multiple Case Study on Large Railway Projects

Interorganizational transportation projects are increasingly difficult to manage because of a need to coordinate complex interdependencies pertaining to railway organizations with increasing levels of connectedness. In this article, the perceived dynamics of coordination mechanisms in the decision-making processes of interorganizational projects of the Dutch railway system are investigated. The results of this study suggest that the perceived effectiveness of interorganizational decision-making can be positively impacted during the pre-project phase, by emphasizing relational coordination. A reinforcing relationship between trust and mutual understanding among stakeholders by means of relational coordination mechanisms is one explored explanation.

Searching for pulsars, magnetars, and fast radio bursts in the sculptor galaxy using MeerKAT

Abstract The Sculptor Galaxy (NGC 253), located in the Southern Hemisphere, far off the Galactic Plane, has a relatively high star-formation rate of about 7 M⊙ yr−1 and hosts a young and bright stellar population, including several super star clusters and supernova remnants. It is also the first galaxy, apart from the Milky Way Galaxy to be associated with two giant magnetar flares. As such, it is a potential host of pulsars and/or fast radio bursts in the nearby Universe. The instantaneous sensitivity and multibeam sky coverage offered by MeerKAT therefore make it a favourable target. We searched for pulsars, radio-emitting magnetars, and fast radio bursts in NGC 253 as part of the TRAPUM large survey project with MeerKAT. We did not find any pulsars during a four-hour observation, and derive a flux density limit of 4.4 μJy at 1400 MHz, limiting the pseudo-luminosity of the brightest putative pulsar in this galaxy to 54 Jy kpc2. Assuming universality of pulsar populations between galaxies, we estimate that detecting a pulsar as bright as this limit requires NGC 253 to contain a pulsar population of ⪞20 000. We also did not detect any single pulses and our single pulse search flux density limit is 62 mJy at 1284 MHz. Our search is sensitive enough to have detected any fast radio bursts and radio emission similar to the brighter pulses seen from the magnetar SGR J1935+2154 if they had occurred during our observation.

The Answer ALS return of results study: Answering the duty to disclose

Objective: The Return of Answer ALS Results (RoAR) Study was designed to provide a mechanism for participants in Answer ALS, a large, prospectively designed natural history and biorepository study to receive select clinical genetic testing results and study participants’ experience with the results disclosure. Methods: Participants consented to receive results of five ALS genes (C9orf72, SOD1, FUS, TARDP, TBK1) and/or 59 medically actionable genes as designated by the American College of Medical Genetics. Patient-reported genetic testing outcomes were measured via a post-disclosure survey. Results: Of 645 eligible Answer ALS enrollees, 143 (22%) enrolled and completed participation in RoAR. Pathogenic variants were identified in 22/143 (15.4%) participants, including 13/143 (9.0%) in ALS genes and 9/143 (6.3%) in ACMG genes. Participant-reported measures of result utility indicated the research result disclosure was as or more successful than published patient-reported outcomes of result disclosure the clinical setting. Conclusions: This study serves as a model of a “disclosure study” to share results from genomic research with participants who were not initially offered the option to receive results, and our findings can inform the design of future, large scale genomic projects to empower research participants to access their genetic information.

Probabilistic evaluation method for the stability of large underground cavern considering the uncertainty of rock mass mechanical parameters: A case study of Baihetan underground powerhouse project

For deep large underground cavern projects under complex geological conditions, the determination of rock mass mechanical parameters and stability analysis is fraught with a great deal of uncertainty. This paper proposes a set of methods for estimating rock mass mechanical parameters and probabilistic stability assessment suitable for construction characteristics of large underground caverns. On the one hand, according to the Hoek-Brown criterion and Monte Carlo simulation, a dynamic estimation method for rock mass mechanical parameters is proposed by using Rock Mass Rating (RMR), the uniaxial compressive strength (UCS) of intact rock, and the material constant (mb) as input parameters. On the other hand, considering the uncertainty of rock mass mechanical parameters, a probabilistic evaluation method applicable to the unloading response characteristics of rock mass (including displacement and fracturing zones) around the large cavern is put forward, combining the point estimation method and numerical simulation. The proposed methods were applied to an underground powerhouse, with an excavation span of 34 m and height of 88.7 m, at the Baihetan hydropower station in the southwest of China. Based on extensive field investigations and tests, the probability distributions of key rock mass mechanical parameters were obtained. Furthermore, the high sensitivity of input parameters in the H-B criterion for estimating rock mass mechanical parameters were revealed. Through dynamic simulation, the probability distributions of the displacement and fracturing zones in surrounding rock during the layer-by-layer excavation of the cavern were presented. Comprehensive on-site tests showed that the simulated results were in basic agreement with the actual unloading response behavior during the cavern excavation, validating the correctness and applicability of the proposed methods. The study provides a relatively comprehensive approach for estimating rock mass mechanical parameters and stability evaluation in similar underground engineering projects, and also has guiding significance for predicting and preventing engineering rock mass hazards.

Identifying the interests of stakeholders in large construction projects: Based on Justification theory of Boltanski and Thévenot

In large construction projects, many stakeholders are involved, often with different interests. They look at the interests through the lenses of their conflicting worldviews, leading to the formation of different worlds that often have tensions among them. For example, to be viable, the projects must find a compromise between competition and collaboration. Hence, success in developing and implementing large construction projects requires analyzing the justifications of the world of stakeholders, identifying conflicts and creating agreements among them. Thus, the main purpose of this paper is to use Boltanski and Thévenot's theory to review the justifications of stakeholders’ various and understand the tensions and compromises in large construction projects. The research approach is exploratory qualitative, realized using a multiple case study. In this process, five cases were selected as five large construction projects from the four countries of Iran, Turkey, India and Ethiopia and were analyzed based on the data extracted from written, visual, and audio sources. The results indicate that while six stakeholder groups are identified in the sources, content analysis and clear evidence reveal that the industry, construction, and market groups dominate in large construction projects. In other words, the stakeholders often justify their benefits and losses through the lens of these three worlds. In addition, the research discusses tensions and possible compromises in large construction projects. The results of this research improve the insight and knowledge of project managers and contribute to the success of large construction projects. However, it faces limitations in terms of methodology and data adequacy.

Replication study: Investigating the effects of maximal anaerobic fatigue on dynamic postural control using the Y-Balance Test

ObjectivesThe aim of this study was to replicate the study titled “Investigating the effects of maximal anaerobic fatigue on dynamic postural control using the Y-Balance Test” by Johnston et al. (2018) as part of a large replication project. This study aimed to determine the effects of maximal anaerobic fatigue on dynamic postural control using the Y-Balance Test, with a specific focus on anterior reach distance. DesignA single session intervention. MethodsForty male and female university students (age: 22 ± 3 years, height: 171.88 ± 8.96 cm, mass: 76.20 ± 14.31 kg) partaking in competitive sport, completed a Y-Balance Test protocol at 20, 10, and 0 min before a modified 60 s Wingate fatiguing protocol. Post-fatigue assessments were completed at 0, 10, and 20 min after the Wingate test. Replication outcomes included significance, direction, and effect size comparison using a z-test. ResultsA one-way repeated measures ANOVA showed a significant effect for maximal anaerobic fatigue on normalised anterior reach direction (F1.82, 69.03 = 7.16, p = 0.002, ηp2 = 0.159; 95 % CI: 0.025, 0.320). Therefore, we replicated the original findings for anterior reach distance in terms of statistical significance (F = 3.818, p = 0.025, ηp2 = 0.376; 95 % CI: 0.00, 0.62). The replication and original effect size estimates for anterior reach direction were compared using a z-test and were deemed compatible (z = 1.65, p = 0.05). ConclusionsOverall, we replicated the original study findings for the effect of maximal anaerobic fatigue on anterior reach distance in a Y-Balance Test.

An architecture for model-based and intelligent automation in DevOps

The increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to apply artificial intelligence (AI) principles and techniques, including Machine Learning (ML), to improve their products. However, there is no holistic approach that can support and enhance the growing challenges of DevOps. In this paper, we propose a software architecture that provides the foundations of a model-based framework for the development of AI-augmented solutions incorporating methods and tools for continuous software and system engineering and validation. The key characteristic of the proposed architecture is that it allows leveraging the advantages of both AI/ML and Model Driven Engineering (MDE) approaches and techniques in a DevOps context. This architecture has been designed, developed and applied in the context of the European large collaborative project named AIDOaRt. In this paper, we also report on the practical evaluation of this architecture. This evaluation is based on a significant set of technical solutions implemented and applied in the context of different real industrial case studies coming from the AIDOaRt project. Moreover, we analyze the collected results and discuss them according to both architectural and technical challenges we intend to tackle with the proposed architecture.

Adjusted TextRank for keyword extraction in petrochemical project correspondence documents

A large petrochemical construction project is typically executed by multiple parties, all bound by contract agreement. During the execution phase, issues and problems may arise because the work details are not clearly specified in the contractual agreement. These issues are formally communicated and documented through written correspondence letters. By identifying important keywords within these formal letters, a comprehensive narrative of the project, including its associated issues, can be identified and analyzed. In this research, we introduce an adjusted TextRank algorithm that integrates external features from the Indonesian FastText language model and term frequency-inverse document frequency (TF-IDF) scores to identify important keywords within a dataset of correspondence letters of petrochemical projects. This enhancement involves refining phrase detection, semantic relationship estimation between words, and part-of-speech (POS) identification for words or phrases. Our results show that the proposed adjustments result in improved evaluation scores compared to the baseline standard TextRank and standard TF-IDF, respectively by 24.1% and 25% in terms of F-1 scores.

Designing for effective online Teacher Professional Development (oTPD) in building education by supporting beliefs, communities, collaboration, and development

This article reports the initial research findings from a large project on online professional development and upskilling of in-service building teachers’ digital competencies. Based on the results from a preceding literature review and the pilot delivery of the course, three key factors for the design of effective online teacher professional development in building education — beliefs, communities and collaboration, and teaching development — are exemplified and discussed. The article concludes that the pilot was successful in developing the participants’ technical skills and competencies to introduce technology in building education; however, the pilot did not significantly influence the participants’ beliefs nor made them change practice within the duration of the course.

Local social perception of mining in Parauapebas and Canaã dos Carajás in the eastern Amazonia, Brazil

The mineral industry plays a role in structural transformations in southeastern Pará, Eastern Amazonia, where large projects in this sector are located. This study analyzes aspects of the social perception of mining from image and reputation concepts in the Amazonian context. This paper aimed to examine the role of socioeconomic, political, and historical variables on social perception. It focused on four dimensions - economic, environmental, relationship and image, and general dimensions in Parauapebas and Canaã dos Carajás cities. The methodology consisted of the application in April of 2018 of questionnaires in a stratified sample of 960 and 349 randomly selected households in each of those cities, respectively. We employed the PCA/factor analysis method to examine whether a set of variables is relevant to social perception. The study found that the mining industry is a partner – not an intruder – because its beginning coincided with the social and historical formation of the territory. Perceptions of image and reputation were positive. Interviewee education, age, income, Whatsapp and Facebook usage, having a formal job, belonging to a union and a political party, occupation, and time of arrival are the main factors for social perception of mining. Despite their significantly negative opinion concerning mining's environmental impact, most interviewees pointed out that mining is reliable, friendly, transparent, and involved with the municipalities' problems. Our work fills a gap in growing literature that shows the challenges of companies, governments, and civil society in contemplating the dynamic aspects of mining for effective planning aiming at the social sustainability of mining regions.

Adopting automated bug assignment in practice — a longitudinal case study at Ericsson

[Context] The continuous inflow of bug reports is a considerable challenge in large development projects. Inspired by contemporary work on mining software repositories, we designed a prototype bug assignment solution based on machine learning in 2011-2016. The prototype evolved into an internal Ericsson product, TRR, in 2017-2018. TRR’s first bug assignment without human intervention happened in April 2019. [Objective] Our study evaluates the adoption of TRR within its industrial context at Ericsson, i.e., we provide lessons learned related to the productization of a research prototype within a company. Moreover, we investigate 1) how TRR performs in the field, 2) what value TRR provides to Ericsson, and 3) how TRR has influenced the ways of working. [Method] We conduct a preregistered industrial case study combining interviews with TRR stakeholders, minutes from sprint planning meetings, and bug-tracking data. The data analysis includes thematic analysis, descriptive statistics, and Bayesian causal analysis. [Results] TRR is now an incorporated part of the bug assignment process. Considering the abstraction levels of the telecommunications stack, high-level modules are more positive while low-level modules experienced some drawbacks. Most importantly, some bug reports directly reach low-level modules without first having passed through fundamental root-cause analysis steps at higher levels. On average, TRR automatically assigns 30% of the incoming bug reports with an accuracy of 75%. Auto-routed TRs are resolved around 21% faster within Ericsson, and TRR has saved highly seasoned engineers many hours of work. Indirect effects of adopting TRR include process improvements, process awareness, increased communication, and higher job satisfaction. [Conclusions] TRR has saved time at Ericsson, but the adoption of automated bug assignment was more intricate compared to similar endeavors reported from other companies. We primarily attribute the difference to the very large size of the organization and the complex products. Key facilitators in the successful adoption include a gradual introduction, product champions, and careful stakeholder analysis.

Automated construction scheduling using deep reinforcement learning with valid action sampling

The growing demand for buildings and infrastructures requires optimal construction schedules under real-world complexities. This paper presents an automated scheduling optimization method for large construction projects, considering real-world constraints and the need for rescheduling. A Deep Reinforcement Learning (DRL) model with a Valid Action Sampling (VAS) mechanism is proposed to optimize schedules. The method integrates a Graph Convolutional Network (GCN) for feature extraction and includes a reward shaping mechanism to expedite convergence. The proposed method outperforms traditional methods with reduced project duration and runtime in both scheduling and rescheduling cases. This advancement benefits construction managers seeking efficient and flexible project management. The findings inspire future research into broader and more practical construction scheduling solutions utilizing DRL.

Blinded like a state: Water scarcity and the quantification dilemma in Morocco

Over the last two decades, the Moroccan state has had to deal with some deeply uncomfortable knowledge regarding mounting water scarcity. This presents governing actors with a difficult dilemma. On the one hand, this knowledge is politically disturbing as it could undermine prevailing hydro-agricultural policies, which are based on the promise of unlimited irrigation expansion. It could also corrode the dominant social alliance built around these policies. On the other hand, accurately quantifying water resources has long been essential for establishing the technocratic legitimacy of the state.This paper investigates how the state manages uncomfortable numbers that it has either produced or endorsed: an issue rarely addressed by social studies of quantification, but increasingly consequential in the current ecological crisis. Drawing from a literature on the production of ignorance, we highlight contradictory processes of knowledge production and ignorance. We show that Moroccan state hydrologists have dealt with uncomfortable figures by keeping them fragmented in space and time. They have continued to produce innumerable measurements of water scarcity. However, they have done so in an increasingly scattered manner, both spatially and temporally, while studiously avoiding integrating these fragments into updated national estimates.This uneasy compromise between “seeing” and “not seeing” like a State has so far helped reproduce the “modernizing” social alliance forged around large hydraulic projects. However, its durability is doubtful. Our case study thus raises a number of hypotheses about what the ecological crisis could do to state quantification in many places and in the near future.

Governance practices of large construction projects

Governance practices of large construction projects

Measurement-induced phase transition in teleportation and wormholes

We demonstrate that some quantum teleportation protocols exhibit measurement induced phase transitions in Sachdev-Ye-Kitaev model. Namely, Kitaev-Yoshida and Gao-Jafferis-Wall protocols have a phase transition if we apply them at a large projection rate or at a large coupling rate respectively. It is well-known that at small rates they allow teleportation to happen only within a small time-window. We show that at large rates, the system goes into a new steady state, where the teleportation can be performed at any moment. In dual Jackiw-Teitelboim gravity these phase transitions correspond to the formation of an eternal traversable wormhole. In the Kitaev-Yoshida case this novel type of wormhole is supported by continuous projections.

Critical Evaluation of the Contract Selection Process Used in the Construction Industry of Kuwait

The paper investigates and assesses the contract selection procedure used in Kuwait’s construction sector. The ideas and insights of engineers involved in significant Kuwaiti construction projects will be extensively considered. In the Kuwaiti building sector, various ways of choosing the contract form will be discussed. In order to gather pertinent data about the country’s primary construction projects, questionnaires will be used. This methodology ensures a first-hand account of the challenges and preferences within the industry. This data will be analyzed to determine the best ways to enhance the current system utilized for Kuwaiti building contracts for the choice of contract forms and payment terms that could benefit from the inclusion of measures to guarantee those types of task delivery systems and payment terms in the country’s future construction projects. This paper explores the typical contract types and payment mechanisms used in Kuwait, drawing on a thorough analysis of current literature, governmental regulations, and business practices. The Standard Forms of Contract, which offer fixed-priced payments, have become the most popular option. However, when used for extensive and technically challenging projects, this contract form’s simplicity presents difficulties. Additionally, the existing system encourages contract awards based on the lowest tender, which raises questions regarding appropriateness and proportionality. The study suggests an arsenal of criteria for improving the deal selection process, with an emphasis on diverse terms of payment inside the task delivery system, in order to allay these worries. It highlights the need for a more comprehensive approach for deal selection that takes project complexity, financial constraints, and long-term project interest into account. The proposed criteria additionally include adaptability to project complexity, ensuring flexibility for challenges in large projects. Financial considerations, aligning with budgetary requirements, are crucial. The emphasis is on long-term project success, and finding a balance between simplicity and adaptability in contracts is key. These comprehensive criteria aim to improve decision-making in selecting standard contract forms for construction projects, addressing challenges in large, technically demanding endeavors in Kuwait. This research contributes to the field by introducing a novel set of criteria for contract selection, tailored to the Kuwaiti construction context. The study’s originality lies in its approach to addressing the challenges posed by current practices and its focus on refining the system for future projects. Additionally, the study employs a rigorous questionnaire survey to extract firsthand insights from industry professionals, ensuring a robust and contextually relevant exploration of the contract selection landscape in Kuwait’s construction sector.

Using Version Control Information to Visualize Developers' Knowledge

It is not always clear in case of a software project who has the right amount of knowledge concerning a certain module or file. Programmers frequently ask questions like "Who knows the most about this code?" or "Who can I ask for help when I work on this module?". In a large, long-term software product, knowledge is distributed in an uneven way among developers. Developer fluctuation during the product lifetime might cause some parts of the code to be known very well by a multitude of developers, while other parts might sink to the "gray zone", where developer competence is dangerously scarce. It is important for the project management to identify such critical points, to avoid the complete loss of competence. Version control repositories contain loads of useful information about the evolution of a software project. This paper presents a developer-centered visualization that is intended to show individual, team-bound and company-bound knowledge of large legacy projects. The competence information is computed from the extracted version control information from Git repositories. The calculated competence value is based on the number of commits per developer and their significance. Aggregated views for teams and companies are available based on various heuristics. The visualization is implemented as a new plugin in CodeCompass, a standalone, open-source code comprehension software. Project managers and individual developers may both profit from the tool, whether it concerns software evolution, human-resource management, architecture, knowledge catch-up, or blame.

Knowledge infrastructure for integrated data management and analysis supporting new approach methods in predictive toxicology and risk assessment

The EU-ToxRisk project (2016–2021) was a large European project working towards shifting toxicological testing away from animal tests, towards a toxicological assessment based on comprehensive mechanistic understanding of cause-consequence relationships of chemical adverse effects. More than 40 partners from scientific institutions, industry and regulators coordinated their work towards this goal in a six-year long programme. The breadth and variety of data and knowledge generated, presented a challenging data management landscape.Here, we describe our approach to data management as developed under EU-ToxRisk. The main building blocks of the data infrastructure are: 1) An easy-to-use, extensible data and metadata format; 2) A flexible system with protocols for data capture and sharing from the entire consortium; 3) A methods database for describing and reviewing data generation and processing protocols; 4) Data archiving using a sustainable resource; 5) Data transformation from the archive to the system that provides granular access; 6) Application Programming Interface (API) for access to individual data points; 7) Data exploration and analysis modules, based on a «web notebook» approach to executable data processing documentation; and 8) Knowledge portal that ties together all of the above and provides a collaboration space for information exchange across the consortium. This knowledge infrastructure is being extended and refined for the support of follow-up projects (RISK-HUNT3R, ASPIS cluster, European Open Science Cloud (2021–2026)).