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Fast-moving thin soft-rigid hybrid robot driven by in-plane dielectric elastomer actuator
Get PDFIn-plane thin dielectric elastomer actuators (DEAs) represent a promising solution for miniaturised soft robots capable of navigating confined spaces. However, most existing in-plane DEAs are either fabricated using off-the-shelf materials or rely on membranes attached to rigid frames, which limit their actuation performance and pose challenges for integration into locomotion-based soft robots. This work introduces a novel in-plane DEA-based thin soft-rigid hybrid robot for fast movement. The innovative design features a multi-layer silicone-based elastomer tensioned by an in-plane elastic PETG frame. A detailed spin coating fabrication method is presented for producing multilayer silicone-based in-plane DEAs. The robot demonstrated effective crawling on flat surfaces and resonance-driven high-speed locomotion at 53 Hz, achieving a peak velocity of approximately 12.3 mm s−1 which is 34.2% of its body length per second and 224% of body thickness per second. This study highlights the potential of DEAs for advancing miniaturised soft robotics, especially in applications that demand lightweight, flexible, and thin profile actuators
Comprehensive Performance Assessment of Conventional and Sequential Predictive Control for Grid-Tied NPC Inverters: A Hardware-in-the-Loop Study
Get PDFModel Predictive Control (MPC) has become very attractive for the efficient control of power converters. This paper compares Classical MPC (C-MPC) and Sequential MPC (S-MPC) for a three-level NPC converter. Although C-MPC is simple to implement, it faces challenges such as switching frequency variations and complex weighting factor tuning. S-MPC addresses these issues by prioritizing control objectives sequentially, eliminating weighting factors, and simplifying controller design. Simulation results show that S-MPC improves the tracking of output currents, reduces harmonic distortion, and enhances the balancing of dc–link voltages under steady-state and transient conditions. These findings establish S-MPC as a robust alternative to C-MPC, improving power quality and system performance in multilevel converter applications
Supporting qualitative practitioner research in child and adolescent mental health
No full textThis editorial piece addresses the relationship between clinical practice and qualitative research in child and adolescent mental health. We outline some guiding assumptions informing the development of a practice orientated research 'lab' which focusses on child and adolescent mental health and child welfare research with ethnographic and psychosocial methodologies. We consider cascading effects of practitioner-initiated research, where skills and ambitions for a 'bottom up' research culture can help professionals embed research-minded practice in services. We also address the role of researcher and methodological reflexivity in research that is close to the social and emotional complexity of practice. We suggest 'labs' for such practice-near research generate opportunities for clinical ideas to be examined more effectively as they are resituated outside of the clinic for the purposes of research; furthermore such research can support critical awareness of the socially and historically contingent quality of methods and practices
Bridging Traditional-Statistics and Machine-Learning Approaches in Psychology: Navigating Small Samples, Measurement Error, Nonindependent Observations, and Missing Data
Get PDFIn recent years, machine learning has propagated into different aspects of psychological research, and supervised machine learning methods have increasingly been used as a tool for predicting human behavior or psychological characteristics when there is a large number of possible predictors. However, researchers often face practical challenges when using machine learning methods on psychological data. In this article, we identify and discuss four key challenges that often arise when applying machine learning to data collected for psychological research. The four challenge areas cover (i) limited sample size, (ii) measurement error, (iii) non-independent data, and (iv) missing data. Such challenges are extensively discussed in the “traditional” statistical literature but are often not explicitly addressed, or at least not to the same extent, in the applied machine learning community. We present how each of these challenges is dealt with first from a traditional statistics perspective and then from a machine learning perspective, and discuss the strengths and weaknesses of these solutions by comparing the approaches. We argue that the boundary between traditional statistics and machine learning is fluid, and emphasize the need for cross-disciplinary collaboration to better tackle these core challenges and improve replicability
Helix-bundle and C-terminal GPCR domains differentially influence GRK-specific functions and β-arrestin-mediated regulation
Get PDFG protein-coupled receptors (GPCRs) orchestrate diverse physiological responses via signaling through G proteins, GPCR kinases (GRKs), and arrestins. While most G protein functions are well-established, the contributions of GRKs and arrestins remain incompletely understood. Here, we investigate the influence of β-arrestin-interacting GPCR domains (helix-bundle/C-terminus) on β-arrestin conformations and functions using refined biosensors and advanced cellular knockout systems. Focusing on prototypical class A (b2AR) and B (V2R) receptors and their chimeras (b2V2/V2b2), we show that most N-domain β-arrestin conformational changes are mediated by receptor C-terminus-interactions, while C-domain conformations respond to the helix-bundle or an individual combination of interaction interfaces. Moreover, we demonstrate that ERK1/2 signaling responses are governed by the GPCR helix-bundle, while β-arrestin co-internalization depends on the receptor C-terminus. However, receptor internalization is controlled via the overall GPCR configuration. Our findings elucidate how individual GPCR domains dictate downstream signaling events, shedding light on the structural basis of receptor-specific signaling
Systematic Review of Forensic Mental Health Patients on Conditional Discharge: Part One – Quantitative Findings, Methodology, Limitations and Future Research
Get PDFThis paper describes the quantitative findings of a systematic literature review of research on patients on conditional discharge from forensic mental health services in England and Wales (part one of two). Conditional discharge is a frequently used discharge option which allows forensic patients to receive care within the community, while subject to certain restrictions. In total, 23 quantitative and five mixed-methods studies were included. A synthesis of the quantitative findings identified factors associated with recall and recidivism, as well as positive outcomes for patients. Patients on conditional discharge showed lower violence and recidivism rates compared to those on absolute discharge. We develop hypothesized causal links between predictors and patient outcomes using a novel method of directed acyclic graphs (DAGs). The methods of this review, implications of findings, and directions for further research are discussed
Efficiency of isoflurane capture from anaesthetised veterinary patients: a single-centre study of a volatile capture device
No full textMedical healthcare has been forward in acknowledging its greenhouse gas emissions, which contribute to the existential risk from climate change.1,2 There is similar concern in veterinary healthcare.3,4 An estimated 21% of the carbon emissions for a canine orthopaedic procedure result from volatile anaesthetics.5 Volatile capture devices (VCDs) are of increasing interest to mitigate veterinary fluorinated gas releases.6 In vivo medical studies have reported capture efficiencies of 25–51%.6,7 Here we describe a prospective study in anaesthetised animals, measuring capture efficiency and estimating the carbon savings from using a VCD
Experimental investigation on shear strengthening of RC beams using advanced fibre-reinforced cementitious composites
Get PDFThe increasing demand for durable marine and coastal structures has motivated research into advanced shear strengthening methods that offer both mechanical efficiency and optimized material usage. This research presents an experimental evaluation of three shear retrofitting strategies for reinforced concrete beams: High-Tensile-Strength Strain-Hardening Cementitious Composites (HTS-SHCC), Ultra-High-Performance Concrete (UHPC), and a hybrid UHPC system reinforced with Ultra-High-Tensile-Strength Steel (UHTSS) textiles. Seven reinforced concrete (RC) beams, including one control specimen, were subjected to three-point bending tests to examine the effects of key strengthening variables, including UHTSS textile density (1.57 and 3.14 cords/cm), cementitious composites (HTS-SHCC and UHPC), and jacketing thickness (10 mm and 20 mm). Results demonstrate that all strengthening systems significantly improved shear capacity by 53.2%-83.2%, with the hybrid system combining high-density UHTSS achieving the highest increase. While HTS-SHCC specimens exhibited greater shear strength than their UHPC counterparts, the latter demonstrated superior pseudo-ductile behaviour through progressive crack dispersion. All strengthened beams failed in shear detachment, though the hybrid system experienced larger-scale concrete cover peeling due to stress redistribution induced by UHTSS textiles. The findings underscore the potential of advanced cementitious composites and hybrid solutions to balance strength, ductility, and retrofit practicality in shear-critical RC structures
Development of low-cost Ti alloys with a balanced strength and ductility with generation of ultra-fine microstructures
Get PDFThis study aims to understand the interplay between strength and ductility in metastable β-Ti alloys based on eutectoid and neutral elements. A low-cost ternary Ti-7Cr-4Sn alloy was prepared by furnace cooling from the single β region at the end of the primary processing. Although isothermal ω, a nano-precipitation generally considered to embrittle the material, is present in the obtained ultra-fine microstructure, the material still exhibits a balanced strength and ductility, with a yield stress of 1067 MPa and elongation of about 10 %. The obtained tensile properties surpass traditional primary processed Ti-6Al-4V, and are comparable to a range of expensive commercial high-strength aerospace Ti alloys. Multiple microstructural features, including grain boundary α (αGB), short rod shape primary α (αP), isothermal ω (ωiso) and ω assisted secondary α (αs) are characterised within the room temperature microstructure. Microstructural analysis reveals that strong Cr segregation in the β phase and slight partitioning of Sn between the α and β phase strengthens the β phase while also preserving ductility in the alloy. This results in a microstructure dominated by the ductile α phase and sub-micron α grain boundaries. This study also discusses the evolution of these microstructural features during different stages of cooling from β matrix, substantiating a promising alloy design strategy for affordable high-performance new Ti alloys
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