Bringing self assessment home: repository profiling and key lines of enquiry within DRAMBORA

Digital repositories are a manifestation of complex organizational, financial, legal, technological, procedural, and political interrelationships. Accompanying each of these are innate uncertainties, exacerbated by the relative immaturity of understanding prevalent within the digital preservation domain. Recent efforts have sought to identify core characteristics that must be demonstrable by successful digital repositories, expressed in the form of check-list documents, intended to support the processes of repository accreditation and certification. In isolation though, the available guidelines lack practical applicability; confusion over evidential requirements and difficulties associated with the diversity that exists among repositories (in terms of mandate, available resources, supported content and legal context) are particularly problematic. A gap exists between the available criteria and the ways and extent to which conformity can be demonstrated. The Digital Repository Audit Method Based on Risk Assessment (DRAMBORA) is a methodology for undertaking repository self assessment, developed jointly by the Digital Curation Centre (DCC) and DigitalPreservationEurope (DPE). DRAMBORA requires repositories to expose their organization, policies and infrastructures to rigorous scrutiny through a series of highly structured exercises, enabling them to build a comprehensive registry of their most pertinent risks, arranged into a structure that facilitates effective management. It draws on experiences accumulated throughout 18 evaluative pilot assessments undertaken in an internationally diverse selection of repositories, digital libraries and data centres (including institutions and services such as the UK National Digital Archive of Datasets, the National Archives of Scotland, Gallica at the National Library of France and the CERN Document Server). Other organizations, such as the British Library, have been using sections of DRAMBORA within their own risk assessment procedures. Despite the attractive benefits of a bottom up approach, there are implicit challenges posed by neglecting a more objective perspective. Following a sustained period of pilot audits undertaken by DPE, DCC and the DELOS Digital Preservation Cluster aimed at evaluating DRAMBORA, it was stated that had respective project members not been present to facilitate each assessment, and contribute their objective, external perspectives, the results may have been less useful. Consequently, DRAMBORA has developed in a number of ways, to enable knowledge transfer from the responses of comparable repositories, and incorporate more opportunities for structured question sets, or key lines of enquiry, that provoke more comprehensive awareness of the applicability of particular threats and opportunities

Broadening the Scope and Increasing the Usefulness of Learning Analytics: The Case for Assessment Analytics

This paper argues that the role that assessment could play within a learning analytics strategy is both significant and, as yet, underdeveloped and underexplored. It proposes that assessment analytics has the potential to make a valuable contribution to the field of learning and academic analytics by both broadening its scope and increasing its usefulness. In doing so it considers issues of operationalization and then moves on to define what we might understand as assessment analytics

Granular technologies to accelerate decarbonization

Of the 45 energy technologies deemed critical by the International Energy Agency for meeting global climate targets, 38 need to improve substan- tially in cost and performance while accelerating deployment over the next decades.Low-carbon technological solutions vary in scale from solar panels, e-bikes, and smart thermostats to carbon capture and storage, light rail transit, and whole-building retrofits. We make three contributions to long-standing debates on the appropriate scale of technological responses in the energy system. First, we focus on the specific needs of accelerated low-carbon transformation: rapid technology deployment, escaping lock-in, and social legitimacy. Second, we synthesize evidence on energy end-use technologies in homes, transport, and industry, as well as electricity generation and energy supply. Third, we go beyond technical and economic considerations to include innovation, investment, deployment, social, and equity criteria for assessing the relative advantage of alternative technologies as a function of their scale. We suggest numerous potential advantages of more-granular energy technologies for accelerating progress toward climate targets, as well as the conditions on which such progress depends

Effects of Steel and Polypropylene Fiber Addition on Interface Bond Strength between Normal Concrete Substrate andSelf-Compacting Concrete Topping

Based on facts that the composite action in semi-precast and strengthened structural system depends on the bond strength of the interface between concrete faces of different ages, this preliminary research is aimed to investigate effects of mixed polypropylene (PPF) and steel fiber (SF) addition on the hardened properties of Self-Compacting Concrete (SCC) and its bond strength when used as topping layer on normal concrete substrate. Effects of hybrid fiber addition on the hardened properties of SCC were investigated based on the compressive, splitting tensile and flexural strength of concrete specimens which is tested in 28 days of age. In the next step, the tensile and shear strength of the interface were evaluated using indirect splitting tensile and bi-surface shear test method. In this research, fiber addition were prepared using 1 kg/m PPF and various SF addition ranging from 15 kg/m3, 20 kg/m3, 25 kg/m3 and 30 kg/m3. Test results indicate that hybrid fiber addition does not affect the compressive strength significantly but it leads ositive improvement to the splitting tensile and flexural strength of hardened SCC and also improve the bond strength between SCC and normal concrete. Hybrid fiber addition of 1 kg/m3 PPF which is combined with 20 kg/m3 SF can be suggested as optimum composition for Hybrid Fiber Reinforced Self-Compacting Concrete (HyFRSCC) that will be used as topping or overlay material based on its hardened properties and interface strength

Flow cytometric characterization of freshwater crayfish hemocytes for the examination of physiological status in wild and captive animals

Enumeration of invertebrate hemocytes is a potentially powerful tool for the determination of physiological effects of extrinsic stressors, such as hypoxia, disease, and toxicant exposure. A detailed flow cytometric method of broad application was developed for the objective characterization and enumeration of the hemocytes of New Zealand freshwater crayfish Paranephrops planifrons for the purpose of physiological health assessment. Hemocyte populations were isolated by flow cytometric sorting based on differential light scatter properties followed by morphological characterization via light microscopy and software image analysis. Cells were identified as hyaline, semigranular, and granular hemocytes based on established invertebrate hemocyte classification. A characteristic decrease in nuclear size, an increase in granularity between the hyaline and granular cells, and the eccentric location of nuclei in granular cells were also observed. The granulocyte subpopulations were observed to possess varying degrees of granularity. The developed methodology was used to perform total and differential hemocyte counts from three lake populations and between wild and captive crayfish specimens. Differences in total and differential hemocyte counts were not observed among the wild populations. However, specimens held in captivity for 14 d exhibited a significant 63% reduction in total hemocyte count, whereas the relative hemocyte proportions remained the same. These results demonstrate the utility of this method for the investigation of subacute stressor effects in selected decapod crustaceans

Autoencoders for strategic decision support

In the majority of executive domains, a notion of normality is involved in most strategic decisions. However, few data-driven tools that support strategic decision-making are available. We introduce and extend the use of autoencoders to provide strategically relevant granular feedback. A first experiment indicates that experts are inconsistent in their decision making, highlighting the need for strategic decision support. Furthermore, using two large industry-provided human resources datasets, the proposed solution is evaluated in terms of ranking accuracy, synergy with human experts, and dimension-level feedback. This three-point scheme is validated using (a) synthetic data, (b) the perspective of data quality, (c) blind expert validation, and (d) transparent expert evaluation. Our study confirms several principal weaknesses of human decision-making and stresses the importance of synergy between a model and humans. Moreover, unsupervised learning and in particular the autoencoder are shown to be valuable tools for strategic decision-making

A heuristic model of bounded route choice in urban areas

There is substantial evidence to indicate that route choice in urban areas is complex cognitive process, conducted under uncertainty and formed on partial perspectives. Yet, conventional route choice models continue make simplistic assumptions around the nature of human cognitive ability, memory and preference. In this paper, a novel framework for route choice in urban areas is introduced, aiming to more accurately reflect the uncertain, bounded nature of route choice decision making. Two main advances are introduced. The first involves the definition of a hierarchical model of space representing the relationship between urban features and human cognition, combining findings from both the extensive previous literature on spatial cognition and a large route choice dataset. The second advance involves the development of heuristic rules for route choice decisions, building upon the hierarchical model of urban space. The heuristics describe the process by which quick, 'good enough' decisions are made when individuals are faced with uncertainty. This element of the model is once more constructed and parameterised according to findings from prior research and the trends identified within a large routing dataset. The paper outlines the implementation of the framework within a real-world context, validating the results against observed behaviours. Conclusions are offered as to the extension and improvement of this approach, outlining its potential as an alternative to other route choice modelling frameworks

Andic soils and catastrophic mudflows in Italy: morphological and hydropedological evidences

In Italy rapid landslides are the most frequently occurring natural disasters and, after earthquakes, cause the highest number of victims. In this contribution we attempt to prove that there exist a tight connection between the presence of a specific soil type, namely andic soils, and the occurrence of the main catastrophic mudflows and debris flows occurred in Italy in the last decades. The study was performed by means of an integrated pedological and hydrological analysis on the detachment crowns of some of the most important catastrophic mudflows and debris flows occurred in Italy in the last decades and involving/evolving surface soils. The results at both regional (Campania) and National (Italy) scale clearly show that despite the large variability of the environmental settings of the studied sites there are indeed some striking homogeneous soil features in the detachment crowns including (i) soil morphology, (ii) andic features ranging from high to moderate, (iii) high water retention throughout a large range of pressure heads. Results seem to reveal clear cause-effect evidences between andic soils and the investigated catastrophic mudflows/debrisflows; this must be related to the unique physical properties of these soils inducing high landslide vulnerability

Effect of Particle Size on Droplet Infiltration into Hydrophobic Porous Media As a Model of Water Repellent Soil

The wettability of soil is of great importance for plants and soil biota, and in determining the risk for preferential flow, surface runoff, flooding,and soil erosion. The molarity of ethanol droplet (MED) test is widely used for quantifying the severity of water repellency in soils that show reduced wettability and is assumed to be independent of soil particle size. The minimum ethanol concentration at which droplet penetration occurs within a short time (≤10 s) provides an estimate of the initial advancing contact angle at which spontaneous wetting is expected. In this study, we test the assumption of particle size independence using a simple model of soil, represented by layers of small (0.2–2 mm) diameter beads that predict the effect of changing bead radius in the top layer on capillary driven imbibition. Experimental results using a three-layer bead system show broad agreement with the model and demonstrate a dependence of the MED test on particle size. The results show that the critical initial advancing contact angle for penetration can be considerably less than 90° and varies with particle size, demonstrating that a key assumption currently used in the MED testing of soil is not necessarily valid

Can banks circumvent minimum capital requirements? The case of mortgage portfolios under Basel II

The recent mortgage crisis has resulted in several bank failures as the number of mortgage defaults increased. The current Basel I capital framework does not require banks to hold sufficient amounts of capital to support their mortgage lending activities. The new Basel II capital rules are intended to correct this problem. However, Basel II models could become too complex and too costly to implement, often resulting in a trade-off between complexity and model accuracy. In addition, the variation of the model, particularly how mortgage portfolios are segmented, could have a significant impact on the default and loss estimated and, thus, could affect the amount of capital that banks are required to hold. This paper finds that the calculated Basel II capital varies considerably across the default prediction model and segmentation schemes, thus providing banks with an incentive to choose an approach that results in the least required capital for them. The authors also find that a more granular segmentation model produces smaller required capital, regardless of the economic environment. In addition, while borrowers' credit risk factors are consistently superior, economic factors have also played a role in mortgage default during the financial crisis.Capital ; Banks and banking ; Basel capital accord