Data for Social Good

This open access book provides practical guidance for non-profits and community sector organisations about how to get started with data analytics projects using their own organisations’ datasets and open public data. The book shares best practices on collaborative social data projects and methodology. For researchers, the work offers a playbook for partnering with community organisations in data projects for public good and gives worked examples of projects of various sizes and complexity

On the relationships between domain-based coupling and code clones: an exploratory study

Knowledge of similar code fragments, also known as code clones, is important to many software maintenance activities including bug fixing, refactoring, impact analysis and program comprehension. While a great deal of research has been conducted for finding techniques and implementing tools to identify code clones, little research has been done to analyze the relationships between code clones and other aspects of software. In this paper, we attempt to uncover the relationships between code clones and coupling among domain-level components. We report on a case study of a large-scale open source enterprise system, where we demonstrate the probability of finding code clones among components with domain-based coupling is more than 90%. While such a probabilistic view does not replace a clone detection tool per se, it certainly has the potential to complement the existing tools by providing the probability of having code clones between software components. For example, it can both reduce the clone search space and provide a flexible and language independent way of focusing only on a specific part of the system. It can also provide a higher level of abstraction to look at the cloning relationships among software components

Data for Social Good

This open access book provides practical guidance for non-profits and community sector organisations about how to get started with data analytics projects using their own organisations’ datasets and open public data. The book shares best practices on collaborative social data projects and methodology. For researchers, the work offers a playbook for partnering with community organisations in data projects for public good and gives worked examples of projects of various sizes and complexity

The Circles of Connections: An evidence-based social visualisation tool to diagnose strengths and weaknesses of your social connections

In modernity, there is a growing obsession with tracking various aspects of an individual’s life, that is the ‘quantified self’. The latest trends in technology have made it much easier to track many elements of life such as heart rate, weight loss, fitness activity, and sleep patterns. The list can be extended by collecting data on others as well (such as a baby or pet), leading to the notion of the ‘quantified other’. This new wave in quantified self/other data has an impact on social and behavioural science research as well, moving the field away from a focus on survey studies towards more complex data-driven approaches. However, feasible ways of measuring the more intangible aspects of life such as connectedness, feelings, and resilience are rarely on offer in the self-quantified market. To address this, in partnership with Red Cross Australia, we have developed a social visualisation tool that helps people to assess their social connections, and understand how these connections contribute to aspects of social capital such as participation, support, feelings of safety and trust. We believe having such a tool to self-quantify an individual’s social connections offers the potential for better public health outcomes. The greater impact can be made at a community level to understand and facilitate social connections of diverse communities and raise awareness about their needs. Enriching such information with other spatial or sociodemographic data can help organisations like the Red Cross for provision of targeted supports particularly around areas of disaster management and engaging marginalised or vulnerable populations, and thus to build more resilient communities

Assigning Creative Commons Licenses to Research Metadata: Issues and Cases

This paper discusses the problem of lack of clear licensing and transparency of usage terms and conditions for research metadata. Making research data connected, discoverable and reusable are the key enablers of the new data revolution in research. We discuss how the lack of transparency hinders discovery of research data and make it disconnected from the publication and other trusted research outcomes. In addition, we discuss the application of Creative Commons licenses for research metadata, and provide some examples of the applicability of this approach to internationally known data infrastructures.Comment: 9 pages. Submitted to the 29th International Conference on Legal Knowledge and Information Systems (JURIX 2016), Nice (France) 14-16 December 201

ExpFinder: An Ensemble Expert Finding Model Integrating NN-gram Vector Space Model and μ\muCO-HITS

Finding an expert plays a crucial role in driving successful collaborations and speeding up high-quality research development and innovations. However, the rapid growth of scientific publications and digital expertise data makes identifying the right experts a challenging problem. Existing approaches for finding experts given a topic can be categorised into information retrieval techniques based on vector space models, document language models, and graph-based models. In this paper, we propose $\textit{ExpFinder}$, a new ensemble model for expert finding, that integrates a novel $N$-gram vector space model, denoted as $n$VSM, and a graph-based model, denoted as \textit{\muCO-HITS}, that is a proposed variation of the CO-HITS algorithm. The key of $n$VSM is to exploit recent inverse document frequency weighting method for $N$-gram words and $\textit{ExpFinder}$ incorporates $n$VSM into \textit{\muCO-HITS} to achieve expert finding. We comprehensively evaluate $\textit{ExpFinder}$ on four different datasets from the academic domains in comparison with six different expert finding models. The evaluation results show that $\textit{ExpFinder}$ is a highly effective model for expert finding, substantially outperforming all the compared models in 19% to 160.2%.Comment: 15 pages, 18 figures, "for source code on Github, see https://github.com/Yongbinkang/ExpFinder", "Submitted to IEEE Transactions on Knowledge and Data Engineering

Phyto-oestrogens affect fertilisation and embryo development in vitro in sheep

Phyto-oestrogens such as isoflavones are natural compounds that can profoundly affect reproductive function. In the present study, we tested whether including isoflavone compounds (genistein, biochanin A, formononetin) in the maturation medium would affect the outcomes for ovine oocytes in vitro. Each isoflavone compound was evaluated at five concentrations (0, 2.5, 5, 10, 25µgmL-1) and the entire protocol was repeated four times. Cumulus-oocyte complexes were randomly allocated to the treatments, then fertilised and cultured in vitro. Compared with control (0µgmL-1), the lower concentrations of isoflavone (2.5, 5 and 10µgmL-1) had no detectable effect on the rates of cleavage or embryo development, or on embryo total cell counts (TCC). However, the highest concentration (25µgmL-1) of all three isoflavones exerted a variety of effects (P<0.05): genistein decreased cleavage rate, blastocyst rate and blastocyst efficiency (blastocysts produced per 100 oocytes); biochanin A decreased cleavage rate and blastocyst efficiency; and formononetin decreased blastocyst rate and blastocyst efficiency. Biochanin A (25µgmL-1) reduced embryo TCC specifically at the hatched blastocyst stage (P<0.05). We conclude that the presence of isoflavones at 25µgmL-1 during IVM decreases the cleavage rate and inhibits blastocyst hatching

Acute phase proteins, interleukin 6, and heat shock protein 70 in broiler chickens administered with corticosterone

An experiment was conducted to determine the effect of corticosterone (CORT) administration on serum ovotransferrin (OVT), α1-acid glycoprotein (AGP), ceruloplasmin (CPN), and IL-6 concentrations, and brain heat shock protein (HSP) 70 expression in broiler chickens. From 14 to 20 d of age, equal numbers of birds were subjected to either (i) daily intramuscular injection with CORT in ethanol:saline (1:1, vol/vol) at 6 mg/kg of BW, or (ii) daily intramuscular injection with 0.5 mL ethanol:saline (1:1, vol/vol; control). Blood samples were collected before CORT treatment (14 d old), 3 and 7 d after CORT injections, and 4 d after cessation of CORT administration for determination of serum levels of CORT, OVT, AGP, CPN, and IL-6. Brain samples (whole cerebrum) were collected to measure HSP 70 density. Although CORT administration significantly increased feed intake, weight gain was significantly depressed. Administration of CORT also increased CORT, OVT, CPN, AGP, IL-6, and HSP 70 expression. Four days following cessation of CORT administration, OVT declined to the basal level but not CPN and AGP. In conclusion, an elevation in CORT can induce an acute-phase response and HSP 70 expression. Thus, APP and HSP 70 may be of value as indicators of stress in poultry

Leveraging Artificial Intelligence Technology for Mapping Research to Sustainable Development Goals: A Case Study

The number of publications related to the Sustainable Development Goals (SDGs) continues to grow. These publications cover a diverse spectrum of research, from humanities and social sciences to engineering and health. Given the imperative of funding bodies to monitor outcomes and impacts, linking publications to relevant SDGs is critical but remains time-consuming and difficult given the breadth and complexity of the SDGs. A publication may relate to several goals (interconnection feature of goals), and therefore require multidisciplinary knowledge to tag accurately. Machine learning approaches are promising and have proven particularly valuable for tasks such as manual data labeling and text classification. In this study, we employed over 82,000 publications from an Australian university as a case study. We utilized a similarity measure to map these publications onto Sustainable Development Goals (SDGs). Additionally, we leveraged the OpenAI GPT model to conduct the same task, facilitating a comparative analysis between the two approaches. Experimental results show that about 82.89% of the results obtained by the similarity measure overlap (at least one tag) with the outputs of the GPT model. The adopted model (similarity measure) can complement GPT model for SDG classification. Furthermore, deep learning methods, which include the similarity measure used here, are more accessible and trusted for dealing with sensitive data without the use of commercial AI services or the deployment of expensive computing resources to operate large language models. Our study demonstrates how a crafted combination of the two methods can achieve reliable results for mapping research to the SDGs

Response to dietary supplementation of L-glutamine and L-glutamate in broiler chickens reared at different stocking densities under the hot, humid tropical conditions

A study was conducted to determine whether supplementing AminoGut (a commercial dietary supplement containing a mixture of l-glutamine and l-glutamic acid) to broiler chickens stocked at 2 different densities affected performance, physiological stress responses, foot pad dermatitis incidence, and intestinal morphology and microflora. A randomized design in a factorial arrangement with 4 diets [basal diet, basal diet + 0.5% AminoGut from d 1 to 21, basal diet + 0.5% AminoGut from d 1 to 42, and basal diet + virginiamycin (0.02%) for d 1 to 42] and 2 stocking densities [0.100 m2/bird (23 birds/pen; LD) or 0.067 m2/bird (35 birds/pen; HD)]. Results showed that villi length and crypt depth were not changed by different dietary treatments. However, birds in the HD group had smaller villi (P = 0.03) compared with those of the LD group. Regardless of diet, HD consistently increased the serum concentrations of ceruloplasmin, α-1 acid glycoprotein, ovotransferin, and corticosterone (P = 0.0007), and elevated heterophil to lymphocyte ratio (0.0005). Neither AminoGut supplementation nor stocking density affected cecal microflora counts. In conclusion, under the conditions of this study, dietary supplementation of AminoGut, irrespective of stocking density, had no beneficial effect on growth performance, intestinal morphology, and physiological adaptive responses of broiler chickens raised under hot and humid tropical conditions. However, AminoGut supplementation from d 1 to 42 was beneficial in reducing mortality rate. Also, the increased serum concentrations of a wide range of acute phase proteins together with elevated corticosterone and heterophil to lymphocyte ratio suggested that high stocking density induced an acute phase response either indirectly as a result of increased incidence of inflammatory diseases such as foot pad dermatitis or possibly as a direct physiological response to the stress of high stocking density