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Variations in critical success factors of PPP-procured construction projects over lifecycle phases
Get PDFWe explore the variations in importance of critical success factors (CSFs) over project lifecycle stages of construction public–private partnership (PPP) projects. A two-staged study is employed involving a literature search and identification of factors supplemented with a two-staged Delphi exercise. Our findings point to the existence of 24 CSFs with varying levels of importance over the project lifecycle. Three CSF appeared important in three of the four phases. Most CSFs appeared important in two of the four phases while six CSFs appeared in only one phase. Findings suggest project stakeholders emphasized specific endogenous CSFs as being more important during the initial phases of the project. However, these CSFs then gave way to the prominence of more exogenous CSFs emphasizing change and transformation as the project moved towards the ‘Execution’ and ‘Benefits realization’ phases. Theoretical and practical implications of the findings are discussed
How do we speak about algorithms and algorithmic media futures? Using vignettes and scenarios in a citizen council on data-driven media personalisation
Get PDF‘New’ media and algorithmic rules underlying many emerging technologies present particular challenges in fieldwork, because the opacity of their design, and, sometimes, their real or perceived status as ‘not quite here yet’ – makes speaking about these challenging in the field. In this article, we use insights from a three-stage citizens council investigating citizens’ views on developments in data-driven media personalisation to reflect on the potentials of using future-orientated vignettes and scenarios in data collection on user experiences, expectations and the ethics of algorithms. We present the possibilities and potentials of using vignettes as part of a data collection approach in user-centric algorithm studies which invites users’ contextual experiences of algorithms but also enables more normative reflections on what good looks like in contemporary datafied societies
The effect of external magnetic field on electro-thermal-flow distribution and field synergy characteristics of long arc
No full textLong arcs (LAs) feature high power (QArc) but low energy efficiency (η), making its optimization crucial for electric arc furnace. As a magnetohydrodynamic fluid, LA is influenced by external magnetic field (EMF). This study develops a coupled electro-thermal-fluid model to investigate LA behaviors under EMF. The effects of magnetic induction intensity (B₀), electrode current (I), and arc length (L) on energy transport and field synergy are analyzed. Results show that EMF induces a helical Lorentz force, forming a vortex ring near the cathode that reduces heat loss. This effect boosts QArc and enhances heat transfer to anode. Under 12.5kA and 200 mm, the average synergy angle (β) along the axis drops by 10.2° when 0.010 T. The η first increases then decreases with B₀ grows, peaking at 28.0 % for 0.005 T. Increasing I or L can raise QArc but reduce η due to increased convective losses. The QArc_Max (3.9 MW) occurs at 15kA, 250 mm, 0.010 T and the η_Max (34.0 %) is at 10kA, 150 mm, 0.005 T. Correlations between working conditions and anode current-heat flux are established with deviations within ±10 %. This study confirms EMF as an effective tool for LA regulation and suggests that promoting “ordered heat transfer” is key to improving both QArc and η
Individual responses: transparency is welcome, but inference needs replication and modelling
No full textUncovering the Limitations of Query Performance Prediction: Failures, Insights, and Implications for Selective Query Processing
No full textQuery Performance Prediction (QPP) estimates the effectiveness of retrieval systems for a given query, offering valuable insights for search effectiveness and query processing. Despite extensive research, QPPs face critical challenges in generalizing across diverse retrieval paradigms and collections. This paper provides a comprehensive evaluation of state-of-the-art QPPs, including NQC, WIG, LETOR-based features, and newly explored dense-based predictors MQPPF and BERT-QPP. Using diverse sparse (BM25, DFree without and with query expansion) and hybrid or dense (SPLADE, ColBERT, and TCT-ColBERT) rankers and diverse test collections: TREC Robust, GOV2, WT10G, and MS-MARCO, we investigate the relationships between predicted and actual performance, with a focus on generalization and robustness. The results show significant variability in the accuracy of predictors, largely influenced by the collections used, followed by the type of rankers. Some sparse predictors perform somehow adequately on specific collections, such as TREC Robust and GOV2, but fail to generalise to other collections like WT10G and MS-MARCO. While certain predictors demonstrate promise in specific scenarios, their overall limitations constrain their utility for applications. We highlight that QPP-driven selective query processing offers only marginal gains, emphasizing the need for improved predictors that generalize across collections, align with dense retrieval architectures, and are useful for downstream applications. We will publicly release our data and code following acceptance
Barriers to BIM for facilities management adoption in Nigeria: a multivariate analysis
Get PDFPurposeBuilding information modelling (BIM) has been established in the literature as a successful platform that creates an intelligent virtual model for processing data from conceptual design through construction to operational stage of a facility. However, its adoption for facilities management (FM) provision in Nigeria has been slow due to inherent barriers. The aim of this paper is to (1) assess and categorise using factor analysis BIM for FM barriers and (2) model the barriers using stakeholders' personal/professional attributes.Design/methodology/approachAnchored on quantitative research design, 205 copies of structured questionnaire were distributed to key stakeholders and facilities managers in Nigeria's three strategic cities while 135 valid responses were received giving a response rate of 65.8%. Data collected were analysed using descriptive statistics while multiple regression analysis was used to model the barriers. Kruskal Wallis test was used to test the only hypothesis postulated for the study.FindingsThe study established lack of awareness of BIM for FM, poor supporting infrastructure for Internet services, and lack of education and training as the top three rated barriers militating against adoption of BIM for FM in Nigeria while corruption, widespread mistakes and errors and cultural issues were established as the three least rated barriers. Besides, findings also established eight underlying factors that explained 23 barrier factors used for the study which were subsequently used to develop eight regression models. In effect, gender, professional affiliation, organisation, experience, education, expertise, BIM for FM project type, and location were found to statistically predict the 8 extracted factors driving perceived barriers of BIM for FM adoption in Nigeria.Practical implicationsThe study has provided a framework of barrier factors to help stakeholders identify specific barriers for which appropriate measures can be taken to ameliorate consequences of the perceived barriers. Meanwhile, an improved and rejuvenated advocacy on inherent benefits of BIM for facilities management by frontline stakeholders could potentially steer up interests and increased participation of stakeholders on BIM for FM.Originality/valueThe unique study developed the first ever regression model that links BIM for FM barriers to professional attributes of facilities management stakeholders in Nigeria
A Dual-Polarized and Broadband Multiple-Antenna System for 5G Cellular Communications
Get PDFThis study presents a new multiple-input multiple-output (MIMO) antenna array system designed for sub-6 GHz fifth generation (5G) cellular applications. The design features eight compact trapezoid slot elements with L-shaped CPW (Coplanar Waveguide) feedlines, providing broad bandwidth and radiation/polarization diversity. The antenna elements are compact in size and function within the frequency spectrum spanning from 3.2 to 6 GHz. They have been strategically positioned at the peripheral corners of the smartphone mainboard, resulting in a compact overall footprint of 75 mm × 150 mm FR4. Within this design framework, there are four pairs of antennas, each aligned to offer both horizontal and vertical polarization options. In addition, despite the absence of decoupling structures, the adjacent elements in the array exhibit high isolation. The array demonstrates a good bandwidth of 2800 MHz, essential for 5G applications requiring high data rates and reliable connectivity, high radiation efficiency, and dual-polarized/full-coverage radiation. Furthermore, it achieves low ECC (Envelope Correlation Coefficient) and TARC (Total Active Reflection Coefficient) values, measuring better than 0.005 and −20 dB, respectively. With its compact and planar configuration, quite broad bandwidth, acceptable SAR (Specific Absorption Rate) and excellent radiation characteristics, this suggested MIMO antenna array design shows good promise for integration into 5G hand-portable devices. Furthermore, a compact phased-array millimeter-wave (mmWave) antenna with broad bandwidth is introduced as a proof of concept for higher frequency antenna integration. This design underscores the potential to support future 5G and 6G applications, enabling advanced connectivity in smartphones
Compact Dual-band Wearable Antenna for Millimeter-wave Applications: Designed for Medical and IoT Device Integration
Get PDFThis paper introduces a compact dual-band wearable antenna designed for mmWave applications. The antenna is fabricated on a Rogers 3003 semi-flexible substrate with dimensions of 15 × 15 × 1.52 mm 3 and features a circular radiating patch with a full ground plane. Initially designed to resonate at 28 GHz, the antenna incorporates a square split-ring resonator in the ground plane to achieve an additional resonance at 38 GHz. To improve bandwidth and gain, a round necktie configuration is applied by adding two diagonal rectangular patches to the periphery of the radiating patch. The measured impedance bandwidths are 21.4% at 28 GHz and 23.7% at 38 GHz. The antenna achieves gains of 5.91 dBi and 4.57 dBi, with efficiencies of 90% and 78% at the respective operating bands. Simulated SAR values are 0.57 W/kg and 0.31 W/kg for 1 g and 10 g of human tissue at 28 GHz, and 0.18 W/kg and 0.16 W/kg at 38 GHz. These SAR values comply with FCC and ICNIRP safety standards. Additionally, bending tests illustrate that the antenna's performance was stable under deformation. As a result, the proposed antenna is ideal for fast connectivity 5G and biomedical applications since it efficiently spans fundamental mmWave frequency ranges
Application of in vitro pulmonary models for hazard screening of silica particles
Get PDFThere is an increasing need for new approach methodologies (NAMs) for safety assessment of nanomaterials (NMs) in order to keep pace with innovation. In vitro assays are useful tools during pre-market hazard screening approaches of NMs to prioritize safe(r) candidate NMs and reduce the amount of regulatory testing required. For pre-regulatory hazard screening applications, it is crucial that in vitro assays have the capacity to distinguish between NMs based on their hazard potency and have the ability to provide accurate hazard rankings. In this paper, four types of silica particles (crystalline, pyrogenic, colloidal, and silane functionalized colloidal) were subjected to twenty-four in vitro assays to obtain hazard rankings using dose–response modelling. The assays were chosen for their relevance in the mechanism of action towards pulmonary inflammation upon inhalation of silica particles. The hazard rankings of silica particles were affected by cell type (alveolar or bronchial epithelial cells, macrophages), read-out method (cell viability, release of pro-inflammatory mediators, reactive oxygen species), and exposure method (submerged, air–liquid interface), complicating the assessment of the actual human hazard. Of particular note was an often muted in vitro response to the crystalline silica used in this study (DQ12), when in vivo data ranked this material as high hazard, due to the chronic and persistent in vivo inflammatory response to crystalline silica, highlighting an important functional discord between these models. However, the potency ranking of the silica particles to induce secretion of the pro-inflammatory mediator IL-1β by THP-1 cells differentiated to M0 macrophages as well as red blood cell haemolysis corresponded more closely to the hazard ranking based on data from rat inhalation studies. These assays should be further explored as indicators for human hazard potential of silica particles and other particles following a similar mechanism of action
Examining the Role of Artificial Intelligence, Financial Innovation, and Green Energy Transition in Enhancing Environmental Quality
Get PDFThe growth of emerging economies has led to heightened environmental challenges, underscoring the importance of implementing sustainable technologies and clean energy transitions to alleviate the ecological consequences. Hence, this study explores the roles of Artificial Intelligence (AI), Financial Innovation (FI), and Green Energy Transition (GET) in improving environmental quality in emerging economies. The results are robust using advanced econometric techniques that account for cross-sectional dependence, heterogeneity, unit roots, and cointegration. We test short- and long-run relationships using the cross-sectional augmented autoregressive distributed lag (CS-ARDL) model and validate the results using feasible generalized least squares (FGLS) estimators. The findings indicated the roles of AI (−0.029), FI (−0.071), and GET (−0.144) in decreasing the ecological footprint and enhancing environmental quality. However, economic growth (0.337) contributes to an increased ecological footprint. These findings highlight that sustainable technologies, FIs, and clean energy transitions are necessary to address environmental issues and sustainable economic growth. These findings provide policymakers with valuable insights into the sustainable development of emerging economies
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