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Cohesion, combat performance and civil-military relations : contextualizing “The Word of Command”
No full textIn 2006, Armed Forces & Society published my article on small unit cohesion, “The Word of Command.” It has been the focus of considerable discussion since that time. This essay describes the origins and the purpose of that 2006 article, as an attempt to contribute to an emergent “practical” paradigm in the study of cohesion. Instead of focusing on interpersonal cohesion, my original article prioritized skill—task cohesion. This commentary argues that although the political implications of small unit cohesion was subordinate in 2006, that initial article—and my wider work on cohesion—speaks directly to a key theme in the journal: civil-military relations
SDG commentary : service ecosystems with the planet - weaving the environmental SDGs with human services
Get PDFPurpose:
Humanity and all life depend on the natural environment of Planet Earth, and that environment is in acute crisis across land, sea and air. One of a set of commentaries on how service can address the UN’s sustainable development goals (SDGs), the authors focus on environmental goals SDG 13 (climate action), SDG 14 (life below water) and SDG 15 (life on land). This paper aims to propose a conceptual framework that incorporates the natural environment into transformative services.
Design/methodology/approach:
The authors trace the evolution of service thinking about the natural environment, from a stewardship perspective of the environment as a set of resources to be managed, through an acknowledgement of nonhuman organisms as actors that can participate in service exchange, towards an emergent concept of ecosystems as integrating human social actors and other biological actors who engage fully in value co-creation.
Findings:
The authors derive a framework integrating human and other life forms as co-creating actors, drawing on shared natural resources to achieve mutualism, where each actor can have a net benefit from the relationship. Future research questions are posited that may help services research address SDGs 13–15.
Originality/value:
The framework integrates ideas from environmental ecosystem literature to inform the nature of ecosystems. By integrating environmental actors and ecological insights into the understanding of service ecosystems, service scholars are well placed to make unique contributions to the global challenge of creating a sustainable future
Polarized Raman spectroscopic study and investigation of phonon modes of Co3(VO4)2 at variable thermodynamic conditions
No full textPolarized Raman spectroscopic investigation on oriented single crystal of orthovanadate Co3(VO4)2 is carried out. We have observed and identified symmetries of 32 out of 36 expected Raman active modes of Co3(VO4)2 in different polarization directions. Evolution of frequencies of observed Raman active modes in Co3(VO4)2 are also investigated under variable thermodynamical conditions. The isothermal high pressure Raman spectroscopic investigation indicates stable orthorhombic (Cmca) structure up to 15.7 GPa consistent with reported literature. The isobaric high temperature Raman spectroscopic investigation up to 823 K is used to estimate the total anharmonicity of all the observed Raman active modes. Evolution of Raman spectra indicates structural stability in the temperature and pressure range investigated. By a combination of high pressure and temperature dependent Raman spectroscopic data, the analysis of anharmonicity of observed Raman modes are calculated. Our measurements indicate dominant contribution of three phonon decay process for almost all the observed Raman active modes in Co3(VO4)2. The anharmonicity information along with symmetry of these observed modes can be used as an input in the analysis of expected spin-phonon anomalies around the magnetic transition in Co3(VO4)2 in future investigations
Structural and practical identifiability analysis in bioengineering : a beginner’s guide
No full textAdvancements in digital technology have brought modelling to the forefront in many disciplines from healthcare to architecture. Mathematical models, often represented using parametrised sets of ordinary differential equations, can be used to characterise different processes. To infer possible estimates for the unknown parameters, these models are usually calibrated using associated experimental data. Structural and practical identifiability analyses are a key component that should be assessed prior to parameter estimation. This is because identifiability analyses can provide insights as to whether or not a parameter can take on single, multiple, or even infinitely or countably many values which will ultimately have an impact on the reliability of the parameter estimates. Also, identifiability analyses can help to determine whether the data collected are sufficient or of good enough quality to truly estimate the parameters or if more data or even reparameterization of the model is necessary to proceed with the parameter estimation process. Thus, such analyses also provide an important role in terms of model design (structural identifiability analysis) and the collection of experimental data (practical identifiability analysis). Despite the popularity of using data to estimate the values of unknown parameters, structural and practical identifiability analyses of these models are often overlooked. Possible reasons for non-consideration of application of such analyses may be lack of awareness, accessibility, and usability issues, especially for more complicated models and methods of analysis. The aim of this study is to introduce and perform both structural and practical identifiability analyses in an accessible and informative manner via application to well established and commonly accepted bioengineering models. This will help to improve awareness of the importance of this stage of the modelling process and provide bioengineering researchers with an understanding of how to utilise the insights gained from such analyses in future model development
Explicit convergence bounds for Metropolis Markov chains : isoperimetry, spectral gaps and profiles
No full textWe derive the first explicit bounds for the spectral gap of a random walk Metropolis algorithm on Rd for any value of the proposal variance, which when scaled appropriately recovers the correct d−1 dependence on dimension for suitably regular invariant distributions. We also obtain explicit bounds on the L2-mixing time for a broad class of models. In obtaining these results, we refine the use of isoperimetric profile inequalities to obtain conductance profile bounds, which also enable the derivation of explicit bounds in a much broader class of models. We also obtain similar results for the preconditioned Crank--Nicolson Markov chain, obtaining dimension-independent bounds under suitable assumption
Superhydrophobic antifrosting 7075 aluminum alloy surface with stable Cassie–Baxter state fabricated through direct laser interference lithography and hydrothermal treatment
No full textFrost formation and accumulation can have catastrophic effects on a wide range of industrial activities. Hence, a dual-scale surface with a stable Cassie–Baxter state is developed to mitigate the frosting problem by utilizing direct laser interference lithography assisted with hydrothermal treatment. The high Laplace pressure tolerance under the evaporation stimulus and prolonged Cassie–Baxter state maintenance under the condensation stimulus demonstrate the stable Cassie–Baxter state. The dual-scale surface exhibits a lengthy frost-delaying time of up to 5277 s at −7 °C due to the stable Cassie–Baxter state. The self-removal of frost is achieved by promoting the mobility of frost melts driven by the released interfacial energy. In addition, the dense flocculent frost layer is observed on the single-scale micro surface, whereas the sparse pearl-shaped frost layer with many voids is obtained on the dual-scale surface. This work will aid in understanding the frosting process on various-scale superhydrophobic surfaces and in the design of antifrosting surfaces
Harmonisation of assessments of attention, social, emotional, and behaviour problems using the Child Behavior Checklist and the Strengths and Difficulties Questionnaire
Get PDFObjectives: Retrospective harmonisation of data obtained through different instruments creates measurement error, even if the underlying concepts are assumed the same. We tested a novel method for item‐level data harmonisation of two widely used instruments that measure emotional and behavioural problems: the Child Behavior Checklist (CBCL) and the Strengths and Difficulties Questionnaire (SDQ). Methods: Item content of the CBCL and SDQ was mapped onto four dimensions: emotional problems, peer relationship problems, hyperactivity/inattention and conduct problems. A diverse test sample was drawn from four prospective longitudinal birth cohort studies in Australia and Europe who used one or both instruments. The pooled sample included 5188 data points assessing children and adolescents aged 6–13 years (N = 257–704 participants per cohort). Measurement invariance was assessed using latent variable multi‐group confirmatory factor analysis. Results: Fifteen items from the CBCL and SDQ were mapped onto four dimensions allowing for measurement invariance testing as part of a stepwise process. Partial strict invariance between CBCL and SDQ assessments was established for all four dimensions. Conclusions: The harmonised dimensions of emotional, peer relationship, hyperactivity/inattention and conduct problems are invariant across the CBCL and SDQ suggesting that these dimensions can be reliably compared with limited measurement error
Potential assessment of biomass-based single-stage adsorption systems for refrigeration, cooling, and heat-pumping applications
No full textThis article presents the performance estimation of a single-stage vapor adsorption system employing various carbon-based adsorbents with ethanol refrigerant, coupled with a small-scale biomass-based heating unit for space cooling, refrigeration, and heat-pumping applications. A detailed parametric investigation highlights the effects of operating temperatures, and heat exchanger to adsorbent mass ratio on specific cooling energy (SCE), coefficient of performance (COP), uptake efficiency (ηu), and mass of adsorbent to combustion fuel (mad/mcf) to identify the suitable adsorbent and sorption bed designs for each application. The numerical findings reveal that the flat-finned tube (FFT) adsorber outperforms traditional-finned tube (TFT) and tube & shell-type (T&S) adsorbers, achieving 19% and 30% higher COP, respectively, with biomass carbon-ethanol pair. The H2-treated Maxsorb-III shows the greatest optimal cooling COP (0.73), followed by the biomass-carbon (0.72) for refrigeration and space cooling. For heat pumping applications, biomass carbon-ethanol achieves the highest heat pumping COP (1.84) at a desorption temperature of 90°C, surpassing H2-treated Maxsorb-III. Further, the biomass-derived activated carbon requires the lowest amount of adsorbent per unit mass of combustion fuel in the biomass heating unit. The present thermodynamic analysis is a precursor for optimization of the potential heat-exchanger geometries and operating parameters, with the high-performance carbon adsorbents
Research status of laser surface texturing on tribological and wetting properties of materials : a review
No full textLaser surface texturing (LST) holds great potential in fabricating precise and controllable micro/nanostructures, benefiting from its high processing resolution, flexible processing methods, and capability to handle a wide range of materials. This paper aims to comprehensively review the research status of LST in improving materials’ friction and wetting properties. Firstly, the significance of friction and wetting properties is outlined, followed by an introduction to commonly employed LST, including laser ablation, laser interference, and laser shock processing. Then, much emphasis has been placed on the impact of laser parameters and texture design on material properties. By manipulating laser parameters such as pulse width, pulse power density, and number of pulses, different effects can be generated on the geometric characteristics, pattern types, and distribution forms of surface textures, thereby altering the surface’s microscopic topography, roughness, hardness, and wettability to exhibit different friction and wetting performances. Next, the optimization methods for texture performance are discussed, encompassing the optimization of laser parameters and the texture itself. In particular, the fundamental theories and influencing mechanisms of LST on materials’ friction and wetting performance are elaborated in detail, followed by an overview of research conducted on metals, non-metals, and composite materials. Finally, a summary is provided on the application of LST in improving the friction and wetting performance of materials while pointing out the limitations of existing research and prospects for future research directions
Causal optimal transport of abstractions
No full textCausal abstraction (CA) theory establishes formal criteria for relating multiple structural causal models (SCMs) at different levels of granularity by defining maps between them. These maps have significant relevance for real-world challenges such as synthesizing causal evidence from multiple experimental environments, learning causally consistent representations at different resolutions, and linking interventions across multiple SCMs. In this work, we propose COTA, the first method to learn abstraction maps from observational and interventional data without assuming complete knowledge of the underlying SCMs. In particular, we introduce a multi-marginal Optimal Transport (OT) formulation that enforces do-calculus causal constraints, together with a cost function that relies on interventional information. We extensively evaluate COTA on synthetic and real world problems, and showcase its advantages over non-causal, independent and aggregated OT formulations. Finally, we demonstrate the efficiency of our method as a data augmentation tool by comparing it against prior art of CA learning, which assumes fully specified SCMs, on a real-world downstream task