An investigation of the required skills for the delivery of low and zero carbon buildings within a region

The United Kingdom is committed to a raft of requirements to create a low-carbon economy. Buildings consume approximately 40% of UK energy demand. Any improvement on the energy performance of buildings therefore can significantly contribute to the delivery of a low-carbon economy. The challenge for the construction sector and its clients is how to meet the policy requirements to deliver low and zero carbon (LZC) buildings, which spans broader than the individual building level, to requirements at the local and regional levels, and wider sustainability pressures. Further, the construction sector is reporting skills shortages coupled with the need for ‘new skills’ for the delivery of LZC buildings. The aim of this paper is to identify, and better understand, the skills required by the construction sector and its clients for the delivery of LZC buildings within a region. The theoretical framing for this research is regional innovation system (RIS) using a socio-technical network analysis (STNA) methodology. A case study of a local authority region is presented. Data is drawn from a review of relevant local authority documentation, observations and semi-structured interviews from one (project 1) of five school retrofit projects within the region. The initial findings highlight the complexity surrounding the form and operation of the LZC network for project 1. The skills required by the construction sector and its clients are connected to different actor roles surrounding the delivery of the project. The key actors involved and their required skills are: project management and energy management skills required by local authority; project management skills (in particular project planning), communication and research skills required by school end-users; and a ‘technical skill’ relating to knowledge of a particular energy efficient measure (EEM) and use of equipment to implement the EEM is required by the EEM contractors.

Processing of zero-derived words in English: an fMRI investigation

Derivational morphological processes allow us to create new words (e.g. punish (V) to noun (N) punishment) from base forms. The number of steps from the basic units to derived words often varies (e.g., nationalitydence that complex derivations cause more brain activity than simple ones ( Meinzer, Lahiri, Flaisch, Hannemann, & Eulitz, 2009). However, all studies to date have investigated derivational processes in which morphological complexity is related to a change in surface form. It is therefore unclear whether the effects reported are attributable to underlying morphological complexity or to the processing of multiple surface morphemes. Here we report the first study to investigate morphological processing where derivational steps are not overtly marked (e.g., bridge-N>bridge-V) i.e., zero-derivation ( Aronoff, 1980). We compared the processing of one-step (soakingderivations together with monomorphemic control words (grumble) in an fMRI experiment. Participants were presented with derived forms of words (soaking, bridging) in a lexical decision task. Although the surface derived -ing forms can be contextually participles, gerunds, or even nouns, they are all derived from verbs since the suffix -ing can only be attached to verb roots. Crucially, the verb root is the basic form for the one-step words, whereas for the two-step words the verb root is zero derived from a basic noun. Significantly increased brain activity was observed for complex (one-step and two-step) versus simple (zero-step) forms in regions involved in morphological processing, such as the left inferior frontal gyrus (LIFG). Critically, activation was also more pronounced for two-step compared to one-step forms. Since both types of derived words have the same surface structure, our findings suggest that morphological processing is based on underlying morphological complexity, independent of overt affixation. This study is the first to provide evidence for the processing of zero derivation, and demonstrates that morphological processing cannot be reduced to surface form-based segmentation.

Zero-Dimensional Units of Ligand-Bridged Gallium-Sulfide Supertetrahedra

The synthesis and characterization of the first anions containing two gallium-sulfide supertetrahedra linked via an organic moiety are described.

Zero attracting recursive least squares algorithms

The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity. In order to achieve a closed-form solution, the l1-norm of the parameter vector is approximated by an adaptively weighted l2-norm, in which the weighting factors are set as the inversion of the associated l1-norm of parameter estimates that are readily available in the adaptive learning environment. ZA-RLS-II is computationally more efficient than ZA-RLS-I by exploiting the known results from linear algebra as well as the sparsity of the system. The proposed algorithms are proven to converge, and adaptive sparse channel estimation is used to demonstrate the effectiveness of the proposed approach.