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Cyclic loading test for UHPC-filled steel tube composite columns reinforced with steel-FRP composite bars
No full textYesTo enhance the post-earthquake repairability of concrete-filled steel tube (CFST) columns, this study introduces a novel steel-FRP composite bars (SFCBs) reinforcing ultra-high-performance concrete (UHPC)-filled steel tube composite (UHPCFST) column. The seismic performance of these UHPCFST composite columns was investigated through cycle loading tests. The results indicated that replacing normal strength concrete with UHPC and increasing the SFCB reinforcement ratio can significantly enhance the seismic performance of composite columns. An increase in the SFCB’s reinforcement ratio from 3 % to 4 % improves the overall performance by 27.6 %, with a minimal cost increase of only 1.8 %, demonstrating the high cost-effectiveness of SFCB reinforcement. Furthermore, an increased axial load ratio enhances the bearing capacity, initial stiffness, and energy dissipation capacity of the columns. However, excessively high axial loads accelerate stiffness degradation and worsen post-earthquake reparability. Compare to steel bar-reinforced UHPCFST composite column, SFCB-reinforced UHPCFST composite column shows superior performance, exhibiting slower performance degradation and better post-earthquake repairability. Finally, a restoring force model for UHPCFST composite columns was developed based on theoretical modeling and regression analysis, which demonstrates excellent consistency with experimental results
Kainate Receptors Trafficking, Signalling and Functional Roles
No full textNoKainate receptors (KARs) regulate glutamate-mediated ion flow in the brain, influencing neurotransmission and synaptic plasticity. KARs are comprised of primary and secondary subunits, forming tetramers with diverse functions based on their composition. Precise trafficking and localisation, modulated by splicing, post-translational modifications and protein interactions, are crucial for synaptic modulation and plasticity. Dysregulation of KARs is implicated in many neurodevelopmental and neurological disorders such as temporal lobe epilepsy, autism spectrum disorder and major depressive disorder. Understanding the KAR function offers insights into therapeutic interventions for these conditions. This chapter explores KARs role in synaptic balance, neural network integrity and the pathogenesis of neurological disorders, highlighting their potential as therapeutic targets
Optimising 3D point cloud semantic segmentation: ML and manual refinement in the UNESCO Saltaire Village
No full textYesSemantic segmentation of 3D point clouds has been an ongoing challenge in recent years. The present research focuses on refining existing standalone Machine Learning (ML) algorithms to enhance their performance in segmenting mid-19th-century industrial housing architectural components, drawing on the UNESCO World Heritage Site Saltaire Industrial Village. Its architecture is actively influenced by contemporary human activity, introducing complexities into the original fabric and spatial composition.
This research provides methodological insights into optimising segmentation performance through a combination of pragmatically reviewed ML classification techniques and manual refinement strategies. The methodology is based on two classification methods: Standalone ML and Multilayer ML. For the first time, this study provides detailed evidence of the challenges encountered in transitioning from traditional human-led models to HBIM in densely altered heritage environments.
Results evaluate the performance of each method with the final aim of laying the groundwork for a semi-automated AI-backed scan-to-BIM approach for 19th-century architecture, contributing to a deeper understanding of its unique characteristics and supporting a sustainable transition to robust HBIM.Arts and Humanities Research Council: [Grant Numbers AH/V012555X/1 and AH/W009102/1]
Together at work: employee motivation, cognition and commitment for better management decision-making
Get PDFYesPurpose
This study examines the impact of motivational tools on organizational commitment by using the Fuzzy Cognitive Mapping (FCM) method, which is a modeling method for complex decision-making. As a result, this study aims to provide managers with an evidence-based decision-support model for employee retention and enhancing organizational commitment. By revealing the causal relationships between motivational factors that affect organizational commitment and their relative weights of importance, the research analyzes the extent of the direct and indirect impacts created by various motivational tools. Consequently, businesses can strategically direct their resources to create the highest impact, significantly reduce employee turnover rates and achieve long-term workforce stability.
Design/methodology/approach
Using an FCM approach, the study models the causal relationships between motivational factors and organizational commitment. Expert judgments were incorporated to create a hierarchical structure of motivational attributes, which were analyzed through iterative simulations.
Findings
The study shows that “career and promotion opportunities” and “authority and responsibility” play the most significant roles in shaping organizational commitment. These are closely followed by “Income” and “Job Quality,” which are equally important. The findings highlight that employee motivation is a complex and interconnected concept, requiring a well-rounded approach rather than focusing on just one factor to drive improvement.
Practical implications
Businesses should strengthen organizational commitment by creating career paths that clarify progression criteria and timelines, encouraging decision-making authority within employees' areas of expertise, ensuring that roles become more diverse and meaningful through job enrichment programs, and supporting these efforts by offering competitive compensation and benefits packages.
Originality/value
This research is adopted to elucidate the dynamics of motivation and organizational commitment by employing FCM method to elucidate the dynamics of motivation and organizational commitment. In contrast to classical motivation theories, FCM has enabled the empirical modeling of the bidirectional, dynamic, and complex interactions between motivational factors, revealing that job security–traditionally considered a “hygiene factor”–plays a systemic role in amplifying other factors. The resulting causal map provides managers with a concrete, visual, and evidence-based decision support system for prioritizing resource allocation and intervention strategies
Guest Editorial: An analysis of the two-way relationships between management practices and firm innovation
No full textNoThe purpose of this special issue is to provide insights into the application of the concept of innovation as a driver of productivity which is widely discussed in the literature (Dani et al., 2022; Novillo-Villegas et al., 2022; Wei et al., 2025). However, due to the absence of high-quality data, the role of management practices has remained empirically unexplored for a long time such as the practices used in operations, monitoring procedures targets, and incentives (Patyal & Koilakuntla, 2017; Bloom et al., 2012; Ahire & Dreyfus, 2000). In addition to innovation, an analysis of firm-level productivity should consider the quality of the firm's management practices (BartzZuccala et al., 2018). Although they are not identical, there is a correlation between the two; every company uses management practices, but not every company innovates (Lööf & Heshmati, 2002; Younas, 2025)
AI-Enhanced Pilot-Assisted Angle-of-Arrival Estimation for Wearable Devices in Rician Fading Channels: A Low-SNR Focused Method
Get PDFYesAccurate angle-of-arrival (AoA) estimation is critical for precise localisation in wearable devices, particularly in challenging wireless environments such as Rician fading with low signal-to-noise ratios (SNRs). This paper proposes a pilot-assisted AoA estimation technique that integrates pseudo-random permutations and Walsh sequences within an OFDM-based transmission framework. The method preserves phase coherence and enhances spatial resolution by optimising pilot allocation and leveraging advanced signal processing. Comprehensive MATLAB simulations show high robustness: At −38dB (per-subcarrier, per-snapshot SNR), the ≈1.5∘ RMS is achieved by aggregating across L snapshots and multiple subcarriers (see Table 12 for K-factor scenarios), with sub-degree accuracy at moderate-to-high SNRs. Furthermore, a lightweight, one-dimensional (1D) convolutional neural network (CNN) reduces residual carrier-frequency offsets by over 30%, highlighting a promising synergy between classical signal processing and data-driven learning. Comparative analysis against state-of-the-art techniques and a discussion of computational complexity are provided, underscoring the suitability of the proposed method for next-generation wearable and IoT direction-finding applications.This work was supported in part by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/X039366/1;
and in part by the HORIZON-MSCA-RISE, a Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) Initiative titled ‘‘FractuRe Orthopaedic Rehabilitation: Ubiquitous eHealth Solution (Robust),’’ under Project 101086492
Managing Insurgency: Counterinsurgency and Order Negotiation in Northeast India
No full textNoDrawing on award-winning research, Managing Insurgency argues that counterinsurgency campaigns do not simply restore or impose order, but set in motion multi-layered processes of order negotiation which preserve, modify or destabilise the formal and informal rules governing social and political relationships within armed conflict. It breaks new ground in the recent ‘order turn’ in the study of civil wars by developing an original typology of ‘order negotiation’ processes in counterinsurgency (COIN) operations, reintroducing the somewhat neglected role of the state in this emerging field. Showing how counterinsurgents engage in multi-layered processes of Order Preservation, Order Modification and Order Destabilisation along three axes of Internal State, State-Insurgent and State-Societal ordering, the typology opens up the black box of state COIN strategy while generating a novel framework for mapping ordering processes in intra-state conflict. It illustrates these processes by drawing on original fieldwork from the Assam and Naga insurgencies - two understudied conflicts from Northeast India - generating distinctive insights into the workings of counterinsurgency command structures, the careful management and probing of the ‘rules’ of local order and the exploitation of intra-rebel cleavages. These myriad, criss-crossing processes of negotiation have – not necessarily by strategic design – managed the insurgencies into decades of long-term, but imperfect, uneven and uncertain – forms of decline. The deeply complex and political picture of counterinsurgency that the book presents forces a rethinking of conventional assumptions across the Indian and wider COIN literatures. Its conceptual reimagining of civil war processes offers a new lens to map the array of actors that can shape order in conflict settings and locate the state’s interactions within them
Advances in computational modeling and simulation of wet granulation processes
No full textNoGranulation is an essential procedure in various industries, particularly in the pharmaceutical sector, as it is needed for producing solid forms of drugs. The complex interaction of process factors, equipment design, and material qualities has led to an increasing use of computer modeling and simulation tools to understand, improve, and control granulation operations. This literature study offers a comprehensive examination of the latest improvements in modeling approaches employed for simulating different types of wet granulators. The work highlights significant advancements in the application of the discrete element method (DEM) for gaining insights into particle-level interactions, mixing, and granule formation. The book examines the incorporation of DEM and the population balance model in the simulation of wet granulation. Furthermore, the work investigates the integration of DEM with computational fluid dynamics and experimental characterization techniques to develop multiscale models that accurately depict the interplay between fluid dynamics and particle behavior in granulation processes
Understanding the Anomaly: geophysical survey on the arena of the Roman amphitheatre of Porolissum
No full textYesRoman amphitheatre in Romania surveyed with Earth Resistance and GPR, Arena’s infrastructure and later constructions were recorded at different depths