Marine Toxins from Harmful Algae and Seafood Safety

The rapid expansion of aquaculture around the world is increasingly being impacted by toxins produced by harmful marine microalgae, which threaten the safety of seafood. In addition, ocean climate change is leading to changing patterns in the distribution of toxic dinoflagellates and diatoms which produce these toxins. New approaches are being developed to monitor for harmful species and the toxins they produce. This Special Issue covers pioneering research on harmful marine microalgae and their toxins, including the identification of species and toxins; the development of new chemical and biological techniques to identify and monitor species and toxins; the uptake of marine biotoxins in seafood and marine ecosystems; and the distribution and abundance of toxins, particularly in relation to climate change

Horses as Sentinels of Emerging Infectious Disease

Horses with illness consistent with Hendra virus (HeV) are routinely sampled and submitted with case descriptions, to government laboratories for timely testing. Extensive investigations for further infectious agents are rare, yet <1% of around 1000 horses test HeV positive annually. Most that test negative feature infectious-like signs such as acute, severe neurological or respiratory illness and pyrexia, yet do not receive causative diagnosis HeV in horses and testing of suspect cases have highlighted challenges/ gaps in significant zoonotic disease investigation. Yet horses investigated for HeV-like disease present unique opportunities for improvements of broad profound biosecurity benefit. Horses are maintained in close association with other animals and humans, monitored thoroughly for disease and susceptible to agents transmitted by insects and wildlife such as bats This research identified significant pathogens among horses with severe HeV-like illness beyond those currently recognised and considered disease significance Fore-front diagnostic approaches integrated with information theoretical, epidemiological and virological analyses. Systematic pathologic-basis-interpretation of disease descriptions sensitively informed likelihood of infectious cause. Three innovative pillars were developed • purpose-built SQL database integrating bio-banked sample ID, sample event, subject and clinical details with parallel test results • explorative multiplex microbead immunoassay serological testing approach screening both IgG and IgM for emerging pathogens • explorative molecular methods targeting novel and emerging infectious agents, including high-throughput pan-PCR, metatranscriptomic sequencing and bioinformatical pipelines Integrated application to suitably bio-banked clinical samples served proof-of-concept for proactive convergence research consideration of emerging infectious agents that could affect One health, livestock, trade and industry security and public healt

Design of Data-Driven Decision Support Systems for Business Process Standardization

Increasingly dynamic environments require organizations to engage in business process standardization (BPS) in response to environmental change. However, BPS depends on numerous contingency factors from different layers of the organization, such as strategy, business models (BMs), business processes (BPs) and application systems that need to be well-understood (“comprehended”) and taken into account by decision-makers for selecting appropriate standard BP designs that fit the organization. Besides, common approaches to BPS are non-data-driven and frequently do not exploit increasingly avail-able data in organizations. Therefore, this thesis addresses the following research ques-tion: “How to design data-driven decision support systems to increase the comprehen-sion of contingency factors on business process standardization?”. Theoretically grounded in organizational contingency theory (OCT), this thesis address-es the research question by conducting three design science research (DSR) projects to design data-driven decision support systems (DSSs) for SAP R/3 and S/4 HANA ERP systems that increase comprehension of BPS contingency factors. The thesis conducts the DSR projects at an industry partner within the context of a BPS and SAP S/4 HANA transformation program at a global manufacturing corporation. DSR project 1 designs a data-driven “Business Model Mining” system that automatical-ly “mines” BMs from data in application systems and represents results in an interactive “Business Model Canvas” (BMC) BI dashboard to comprehend BM-related BPS con-tingency factors. The project derives generic design requirements and a blueprint con-ceptualization for BMM systems and suggests an open, standardized reference data model for BMM. The project implements the software artifact “Business Model Miner” in Microsoft Azure / PowerBI and demonstrates technical feasibility by using data from an educational SAP S/4 HANA system, an open reference dataset, and three real-life SAP R/3 ERP systems. A field evaluation with 21 managers at the industry partner finds differences between tool results and BMCs created by managers and thus the po-tential for a complementary role of BMM tools to enrich the comprehension of BMs. A further controlled laboratory experiment with 142 students finds significant beneficial impacts on subjective and objective comprehension in terms of effectiveness, efficiency, and relative efficiency. Second, DSR project 2 designs a data-driven process mining DSS “KeyPro” to semi-automatically discover and prioritize the set of BPs occurring in an organization from log data to concentrate BPS initiatives on important BPs given limited organizational resources. The project derives objective and quantifiable BP importance metrics from BM and BPM literature and implements KeyPro for SAP R/3 ERP and S/4 HANA sys-tems in Microsoft SQL Server / Azure and interactive PowerBI dashboards. A field evaluation with 52 managers compares BPs detected manually by decision-makers against BPs discovered by KeyPro and reveals significant differences and a complemen-tary role of the artifact to deliver additional insights into the set of BPs in the organiza-tion. Finally, a controlled laboratory experiment with 30 students identifies the dash-boards with the lowest comprehension for further development. Third, OCT requires organizations to select a standard BP design that matches contin-gencies. Thus, DSR project 3 designs a process mining DSS to select a standard BP from a repository of different alternative designs based on the similarity of BPS contin-gency factors between the as-is process and the to-be standard processes. DSR project 3 thus derives four different process model variants for representing BPS contingency factors that vary according to determinant factors of process model comprehension (PMC) identified in PMC literature. A controlled laboratory evaluation with 150 stu-dents identifies significant differences in PMC. Based on laboratory findings, the DSS is implemented in the BPM platform “Apromore” to select standard BP reference mod-els from the SAP Best Practices Explorer for SAP S/4 HANA and applied for the pur-chase-to-pay and order-to-cash process of a manufacturing company

Engineering and built environment project conference 2016: book of abstracts - Toowoomba, Australia, 19-23 September 2016

Book of Abstracts of the USQ Engineering and Built Environment Conference 2016, held Toowoomba, Australia, 19-23 September 2016. These proceedings include extended abstracts of the verbal presentations that are delivered at the project conference. The work reported at the conference is the research undertaken by students in meeting the requirements of courses ENG4111/ENG4112 Research Project for undergraduate or ENG8411/ENG8412 Research Project and Dissertation for postgraduate students

Factors affecting social media use by entrepreneurs and the impact of this use on the opportunity recognition process

Social media is believed to play an essential role in supporting entrepreneurial business and opportunity recognition. However, little is known about the factors that drive social media use and how social media capabilities impact entrepreneurial opportunity recognition. In exploring the role of social media to understand the potential role of social media use on entrepreneurial opportunity recognition, the study was based on the Technological-Organization-Environmental (TOE) and the Opportunity Recognition Frameworks. A mixedmethod study was conducted with data collected from a developed economy (Australia) and a developing country (Nigeria). An initial research model was developed based on the extant review of literature on social media use and entrepreneur opportunity recognition. Firstly, qualitative data were collected via interviews with 14 entrepreneurs, which identified eight factors under four broad categories (technology, environment, individual and social media platform factors) that influence entrepreneur social media use. Also, five social media capabilities were identified (networking, searching, observing, experimenting, and social media data analytics) to drive entrepreneurial opportunity recognition. Comparing the qualitative data with themes developed from published literature, the initial research model was revised. In the second stage, a survey of 568 entrepreneurs was used to validate the model and its associated relationships. The analysis suggests that four general factors influence social media use; platform perception, absorptive capacity, platform abuse and external pressure. In addition, the use of social media was found to influence opportunity recognition through four of the five identified capabilities: searching, observing, experimenting, and data analytics. However, the findings indicate differences on how social media capability drives opportunity recognition amongst entrepreneur in Australia and Nigeria, which can be explained based on their individualist and collectivist culture respectively. Interestingly, the multi-group analysis revealed that the influence of social media capabilities on opportunity recognition might vary depending on the entrepreneur&#039;s gender and the age of their business. The theoretical contribution and practical implications of the findings to social media companies, entrepreneurs, and policymakers were discussed. The study limitation includes being a cross sectional study, focusing on small businesses and evaluating two countries