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The human-AI dyad: Navigating the new frontier of entrepreneurial discourse
No full textThe rapid progression of Artificial Intelligence (AI) is further solidifying the importance of redefining entrepreneurship and reshaping how ventures and innovations are conceived, developed, and managed. This paper investigates how AI is transforming entrepreneurship by reshaping traditional business paradigms and entrepreneurs’ roles. It examines AI's influence on entrepreneurial decision-making, innovation, and identity. Through a comprehensive literature review and thematic analysis of previously published data, the research identifies emergent themes in AI's integration into entrepreneurial discourse. The findings indicate that AI enhances operational efficiency and decision-making but challenges traditional notions of entrepreneurial identity and creativity. Furthermore, entrepreneurs increasingly depend on AI for data-driven insights, strategic foresight, and personalised customer interactions, reshaping business strategies and competitive landscapes. This article emphasises the importance of AI literacy and adaptive strategies for entrepreneurs to leverage the human-AI dyad effectively while maintaining values and ethics. It also highlights the significance of concentrating research efforts on entrepreneurs as they are the very cohort to shape new norms and pioneer new business models and innovations. Future research should explore AI's long-term impacts on entrepreneurial ecosystems, including psychological, ethical, and socio-cultural dimensions, with comparative studies across industries and regions providing further insights
Navigating adaptive futures: Analysing the scope of political possibilities for climate adaptation
No full textThe growing scale and intensity of climate change poses a substantial challenge to the status quo of society and politics. Adapting to the risks associated with extreme weather events and changing climatic conditions will require the re-imagination of many aspects of politics and society. Therefore, climate change can be framed as a problem of imagination; one in which our relationship to the future is central to understanding how possibilities in the present are perceived. This research analyses public submissions made on New Zealand’s first draft National Adaptation Plan to understand how future climate adaptation is framed and imagined by different groups. In analysing submissions we identify and describe four thematic ‘adaptive futures’ that each argue for varied amounts of socio-political change from the status quo: data driven resilience; growth and opportunity; nature-society change; and flaxroots transformation. Underpinning these adaptive futures are emerging advocacy coalitions that seek to shape what is seen as possible, imaginatively, politically and materially. Our analysis also highlights how risks and opportunities are perceived by whom, and insights into attempts to delineate the boundaries of adaptive imagination and political possibility.
Glossary of Māori terms: hapū: kinship group; iwi: extended kinship or tribal group; kaitiakitanga: intergenerational sustainability; kaupapa Māori: Māori approach, a philosophical doctrine, incorporating the knowledge, skills, attitudes and values of Māori society; kawa: protocols; mana: authority, dignity, control, governance & power; mana whenua: territorial rights, power from the land, authority over land or territory, jurisdiction over land or territory; te ao Māori: the Māori worldview; tikanga: correct procedures, lore & practises Definitions sourced from Blackett et al. 2022 & Te Aka Māori Dictionar
The floral interface: A playground for interactions between insect pollinators, microbes, and plants
No full textInsect pollinators acquire microorganisms when they visit flowers for nutrients. The interactions that occur at the floral interface are complex with three participants – pollinators, plants and microorganisms. The majority of the insect pollinator’s microbiome is shaped by their behaviour, diet and environment. At present the bee (Apidae family) microbiome is the best documented and contributes to our understanding of the bi-directional exchange of microbes between pollinators and flowers. The transferred microorganisms may be mutualistic, commensal or pathogenic. We identify a lack of information due to limited studies concerning the diversity of pollinators and a focus on pathogenic microorganisms and their gut microbiome influence on their health. Each candidate, the insect, plant and microbe, makes their own contribution which aids the interaction, but some participants may benefit more than others. The benefits for pollinators include enhanced acquisition of nutritional resources; for microorganisms dispersal and a ‘new’ habitat to colonise and for plants pollination is the outcome. Finally, we explore a novel concept of whether the fruit acts as a potential vector for insect microorganisms to hibernate and extend their lifecycle in the absence of a pollinator host
A holistic marine biosecurity risk framework that is inclusive of social, cultural, economic and ecological values
No full textEffectively managing non-indigenous marine species risks demands swift, transparent decisions amid limited data and in an environment where conflicting interest across environmental, economic, social, and cultural realms exists. Conventional risk assessment tools often fail to comprehensively evaluate these risks together, leading to stakeholder dissatisfaction, conflicts and poor biosecurity outcomes. To address this, we present a structured 7-step marine biosecurity risk framework. It systematically assesses incursion's ecological, economic, social and cultural impacts, encourages stakeholder engagement and promotes inclusive decision-making. Steps include defining contexts, setting objectives, estimating consequences, determining management options, evaluating trade-offs, implementing decisions, and communicating risks effectively. A simulation using Sabella spallanzanii illustrates its application. By integrating diverse perspectives and employing audience-centred communication plans, our framework facilitates informed and equitable decisions. It standardises data examination, aiding in addressing ecological, economic, social, and cultural integrity amidst non-indigenous marine species threats
Transcriptional activity of ammonia oxidisers in response to soil temperature, moisture and nitrogen amendment
No full textThe contrasting response of AOA, AOB, and comammox Nitrospira amoA transcript abundance to temperature, moisture, and nitrogen was investigated using soil microcosms. The moisture, temperature, and nitrogen treatments were selected to represent conditions typically found in a New Zealand (NZ) dairy farm. AOB dominated all synthetic urine treated soils. Peak AOB amoA transcript abundance was positively correlated with estimated soil ammonia availability. While AOB gDNA abundance and nitrification rate trends were similar. AOA were strongly influenced by soil temperature. At 20◦C, AOA amoA peak transcript abundance averaged over 1 order of magnitude higher than at 8 ◦C. Within the AOA community a member of the Nitrosocosmicus clade was positively correlated with ammonium and estimated ammonia concentrations. The presence and relative increase of an AOA community member in a high nitrogen environment poses an interesting contrast to current scientific opinion in NZ. Comammox Nitrospira abundance showed no correlation with soil moisture. This suggests that previously found associations are more complex than originally thought. Further research is required to determine the drivers of comammox Nitrospira abundance in a high moisture environment. Overall, these results indicate that AOB are the main drivers of nitrification in New Zealand dairy farm soils
House prices and airport proximity: Are they valued equally?
No full textThis study contributes to understanding the link between the housing market, airport location proximity examining the entirety of the price distribution. The research investigates this association across four key urban areas within New Zealand proximal to an international airport - Auckland, Wellington, Christchurch, and Queenstown. Applying hedonic and Quantile regression, the analysis reveals that proximity to airports on house prices has a heterogeneous pricing effect. The regression analysis exhibits distance to comprise a positive effect within Auckland and Christchurch, whereas in Wellington and Queenstown the pricing effect is negative. The quantile regression findings further revealed differences between lower and higher priced properties value, given distance and proximity to airports within each city region. Auckland exhibits a positive distance decay effect moving from the lowest to the highest quantiles which diminishes and becomes negative illustrating that the highest priced properties consider closer proximity to airports comprise a dis-amenity effect on property value, alternatively, the lowest priced properties perceive adjacency to the airport as a positive amenity. Wellington also displays higher priced housing to exhibit much larger negative effects with proximity to the airport than lower priced housing. The findings show that whilst there is a negative impact for proximity to airport this is more pronounced for higher priced properties relative to lower priced properties. The Christchurch region reveals contrasting findings showing there to be a higher positive pricing effect for higher priced housing which gradually decreases when moving down the quantiles. With respect to Queenstown, the findings show a nominal but positive pricing effect for lower priced housing with a negative effect for the highest priced properties
Stochasticity in chiral symmetry breaking
No full textWe explore stochastic behavior in chemical transformations far from equilibrium in this chapter. We build on the mathematical machinery developed so far to study the role of noise in these transformations. By using a case study of chiral symmetry breaking, we show distinct changes in the system behavior in the presence of noise
Understanding the sensory-instrumental nexus of walnut kernels: A dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Food Innovation
No full textWalnuts (Juglans regia L.) are valued for their nutritional profile, sensory attributes, and economic significance. In New Zealand, smaller walnut growers face challenges in accessing professional sensory evaluation services due to high costs. There is a need for low-cost, easy-to-use sensory methods that can provide meaningful insights into walnut sensory attributes and physicochemical properties, both of which are key drivers of consumer acceptance. Rapid profiling techniques, such as Napping®, offer a practical alternative for characterizing sensory differences efficiently.
This study examines the effectiveness of Napping® as a rapid profiling method for characterizing the sensory profile of nine commercially available walnut brands in New Zealand. The sensory data was integrated with physicochemical analyses of peroxide value (PV), acid value (AV), colour (L, a, b*), moisture content, and texture properties to establish the sensory-instrumental nexus of walnuts.
Results show that Napping® is an efficient and applicable method for walnut kernel products, effectively differentiating sensory attributes associated with overall liking and consumer clustering. High liking scores were associated with fresh, nutty, creamy, and sweet attributes, while low liking scores were linked to astringent, rancid, sheen, and bitter characteristics. Consumer clustering was influenced by age, with preference patterns varying across different demographic groups. Instrumental analysis revealed that higher fat (>66%) and protein (≥15.3g/100g) content, moderate moisture levels (3.1-3.4%), lighter colour (L ≥ 41, b ≥ 7.5), and softer textures (hardness ≥ 7000g; chewiness ≥ 150g; gumminess ≥ 350g) were associated with higher liking scores. Walnuts with elevated PV (>14 meq O₂/kg fat), AV (>2.85 meq O₂/kg fat), carbohydrate content (>13.5g/100g) and firmer textures exhibited lower consumer acceptance. PLS-R modelling confirmed statistically significant associations between sensory attributes and physicochemical properties. These relationships confirm the presence of a sensory-instrumental nexus in walnut kernels where physicochemical properties help explain consumer sensory perception. These insights offer a cost-effective sensory evaluation approach, supporting small walnut growers in optimizing quality and targeting consumer preferences, with applications in post-harvest handling and marketing
Transcriptomic analysis of skin tissue reveals molecular mechanisms of thermal adaptation in cold-exposed lambs
No full textCold stress impacts lamb mortality, welfare, and productivity. Wool and skin insulate lambs, but the mechanisms underlying their response to colder environments remain unclear. Shorn lambs (n = 20) of similar age (8 months), of the Hulunbuir (n = 10; average 34.5 ± 0.70 kg) and Hu (n = 10; average 34.9 ± 0.79 kg) breeds, were raised at the Ecological and Agricultural Experimental Station, Gaolan, Gansu Province, People’s Republic of China (36°13″ N, 103°47″ E), at an altitude of 1780 m above sea level. These lambs were divided into four equal groups: Hulunbuir at −20 °C (HB−20), Hulunbuir at 15 °C (HB+15), Hu at −20 °C (HU−20), and Hu at 15 °C (HU+15). The groups were maintained at these temperatures in temperature-controlled facilities for 38 days. Skin tissues were analyzed with transcriptome sequencing, and selected wool and physiological traits were assessed. The HB−20 lambs had greater wool length growth (1.8 ± 0.13 vs. 1.0 ± 0.46 cm, p 2, p = 0.041), rectal temperature (38.1 ± 0.10 vs. 38.8 ± 0.04 °C, p < 0.001), and respiratory rate (15.5 ± 1.08 vs. 24.0 ± 1.89 breaths/min, p = 0.004), compared to the HB+15 lambs. Similar differences in these traits were observed with the Hu lambs at the two temperatures. Transcriptome analyses revealed the activation of pathways related to immune and endocrine systems, signal transduction, and development and regeneration, irrespective of breed at −20 °C. The TNF signaling pathway and osteoclast differentiation may play roles in cold adaptation, as they are associated with differentially expressed genes (DEGs) identified in the Hulunbuir lambs, as well as shared DEGs between both breeds. This study revealed physiological and molecular differences in lambs exposed to lower temperatures and suggests potential targets for improving cold tolerance, welfare, and productivity
Predicting forest fire refugia using machine learning: The role of topography and microclimatic variables
No full textForest fire refugia are areas within fire-prone landscapes that remain fire-free or experience lower fire frequency and severity. These refugia are crucial for biodiversity, supporting species, maintaining mature vegetation, and aiding post-fire recovery. They enhance forest resilience by preserving genetic diversity and facilitating regeneration.Understanding how topography influences fire behaviour is key to identifying and conserving refugia, informing forest management to protect them from logging and disturbances. Machine learning models using wind patterns and altitude can effectively predict refugia in localized areas, aiding conservation efforts and promoting ecosystem resilience in fire-prone regions. Forest fire refugia can be accurately predicted using aspect, surface wind direction and speed (derived from computational fluid dynamics), topographic roughness, and temperature in machine learning algorithms (Random Forest, XGBoost; 2 ensembles models) and K-Nearest Neighbour (all run with and without ADASYN over-sampling). Six iterations were run per algorithm to assess the impact of leaving variables out.Among these variables, aspect is the most influential across both feature importance (Random Forest) and feature gain (XGBoost), as it aligns fire refugia with the leeward slopes of prevailing fire winds. Surface wind speed and direction, and global irradiation are also key predictors, with significant drops in model accuracy when these features are excluded. Temperature and topographic roughness show context-dependent importance. Temperature was significant in XGBoost but diminished after ADASYN oversampling, while topographic roughness increased in importance when elevation was excluded. Elevation did not significantly enhance model performance, and its exclusion had minimal impact on predictive accuracy. Ensemble models consistently produced the most accurate results, although accuracy metrics across all experiments where high and averaged 0.96 (±0.2), indicating robust predictive performance. These findings highlight the importance of topographic and micro climatic variables in fire refugia prediction, with machine learning providing reliable forecasting frameworks