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Tourism
No full textTourism represents a substantial commercial activity in the polar regions and has rapidly grown and diversified over the last half-century, especially in the Antarctic, where tourism represents the only commercial activity utilising the continent itself. Tourism in the Arctic occurs on a greater scale and often entails interactions with local communities, adding a range of socio-economic effects to the suite of impacts of polar tourism, which shape the discourse around the role of tourism and its governance. The majority of polar tourism is ship based, with concentrations of tourism in the Antarctic Peninsula and in Alaska, as well as in Svalbar
Financial inclusion, poverty, and income inequality
Get PDFFinancial inclusion has emerged as a critical tool for promoting economic development, particularly in developing countries. By providing access to affordable financial services, financial inclusion fosters economic participation, reduces poverty, and reduces income inequality. In Ghana, where poverty and income inequality remain persistent, understanding the developmental role of financial inclusion is crucial. This study examines the impact of financial inclusion on poverty alleviation and income inequality in Ghana from 1980 to 2021. A key contribution of this study is the construction of a comprehensive financial inclusion index that integrates both banking and insurance data. This dual-component index captures the broader scope of financial inclusion compared to traditional metrics that often focus solely on banking. The results reveal that financial inclusion indirectly enhances human development by improving education, health, and income equality, even though it does not directly reduce household poverty. Additionally, GDP per capita, ICT literacy, and remittances significantly influence human development outcomes, while inefficient government spending and rural population growth constrain progress. The positive interaction between financial inclusion and GNI per capita underscores the importance of economic growth in amplifying inclusion’s developmental benefits. Strengthening Ghana’s financial system, particularly in rural areas, can further advance poverty reduction and inclusive growth
Differential equations - Theory, modeling, data assimilation and algorithms
Get PDFRooted in years of interdisciplinary research and collaboration, the chapters in this book highlight the central role of differential equations in describing how systems evolve across science and engineering while emphasizing the modern need to connect theory with data and computation. It bridges rigorous mathematical foundations with the practical challenges of modeling and inference, demonstrating how data assimilation refines models using observations and how advanced numerical algorithms enable the study of complex systems beyond analytical reach. By addressing the interplay between models, data, and computation, the book equips advanced students, researchers, and practitioners with the understanding and tools needed to apply differential equations meaningfully in contemporary scientific inquiry
Measuring the performance of the built environment: An investigation of evaluation methods
Get PDFAs landscape architecture shifts toward evidence-based practices, the Landscape Architecture Foundation (LAF)’s Case Study Investigation (CSI) initiative has been instrumental in driving the growth of Landscape Performance Evaluation (LPE) and enhancing disciplinary rigour. This paper reflects on our CSI case study, evaluating Te Whāriki, a master-planned residential landscape in New Zealand. We adopt a methodological reflexivity approach, critically examining the challenges faced and insights gained during the evaluation, providing a comprehensive reflection on the current practical challenges and potential future research directions in the field of LPE. This research reflects upon the methodological reliability of LPE approaches, challenging stereotypes surrounding “measured” and “estimated” methods. Our study emphasises the importance of improving input data quality, explores the trade-off between accuracy and cost, and introduces the concept of a universal currency for landscape benefits. By offering our reflections, this paper aims to stimulate further conversations and catalyse ongoing iterations in the evaluation framework and methodological exploration within this evolving field
Report and recommendation of the review panel: Severe Weather Emergency Recovery (Hawke's Bay Flood Protection Works) Amendment Order 2025
No full textAs required under section 16 of the Severe Weather Emergency Recovery Legislation Act 2023, this is the Review Panel’s report on this draft Order, including its recommendations and brief comments
Expanding the social dimensions of conservation translocations
Get PDFHuman or ‘social’ dimensions are increasingly prominent in the conservation translocation literature yet in practice they tend to be infrequently or narrowly applied. To assist biophysical scientists and practitioners to act upon social dimensions, we distinguish four ways of thinking about the social dynamics of translocations: identified stakeholders, processes of decision-making, visions of nature, and values in science. We use three case studies to show how working through these four social dimensions together can help to illuminate the multiple meanings and effects of translocations. We discuss how biophysical scientists and practitioners can take responsibility for each social dimension and thus make better choices for people and nature
Supplementation of New Zealand hemp seed protein improves arterial health in adults with increased cardiovascular risk
No full textThe consumption of hemp derived protein has shown potential to improve cardiovascular disease risk factors(1) For example, Samsamikor et al.(2) showed the efficacy of hemp seed protein in ameliorating high blood pressure in adults with hypertension. However, the effects of hemp seed protein consumption on arterial stiffening have not to our knowledge been investigated in humans. The present study aimed to investigate the effects of New Zealand hemp seed protein on blood pressure and measures of arterial stiffening in adults with one or more risk factor(s) for cardiovascular disease. A randomised control trial was conducted with 33 participants for 16 weeks in which the experimental group consumed 28g of hemp seed protein extract for 5 out of every 7 days while 15 participants acted as a control group instructed to keep their regular daily diet over the experimental period. Blood pressure and arterial stiffening were measured at weeks 1, 8 and 16 using a SphygmoCor Excel device. A linear mixed model was used to analyse the repeated measures for affect differences between weeks, featuring Welches T-Test for uneven variance and an ANOVA test for p-values of the fixed effects. The model included a covariate analysis of the baseline measurement and used Tukey post hoc analysis for pairwise comparisons within and between the experimental and control groups. Results showed that compared to the control group, the experimental group decreased central systolic blood pressure by 6.2 ± 2.2 mmHg (mean ± SE, 95% CI [-1.9, -10.6], p = <0.05), mean arterial pressure by 6.2 ± 2.0 mmHg (95% CI [-2.2, -10.3], p = <0.05) ), augmentation index at 75 bpm by 9 ± 1.8 mmHg (95% CI [-5.4,-12.6], p = <0.05) augmented pressure by 7.3 ± 1.5 mmHg (95% CI [-4.3,-7.3], p = <0.05), and reflection magnitude by 8.3 ± 1.7% (95% CI [-4.9,-11.7], p = <0.05). However, no significant changes were observed in brachial blood pressures. These results suggest that hemp seed protein improves central arterial health in at risk adults after 16 weeks of supplementation. It is hypothesised that reduction in arterial stiffness measurements might be attributed to the ability of hemp seed protein to attenuate endothelial dysfunction through increased nitric oxide production(3)
Climate policy uncertainty and stock markets: Evidence from the United States : A thesis submitted in partial fulfilment of the requirements for the Degree of Doctor of Philosophy at Lincoln University
Get PDFClimate change is playing an increasingly pivotal role in financial markets, posing systemic risks to the financial sector. Concurrently, uncertainty surrounding climate policy presents significant challenges and has attracted growing academic attention. However, the existing literature has yet to comprehensively examine the relationships between climate policy uncertainty in the United States (U.S.) and its impact on financial markets.
This study aims to bridge this research gap by systematically investigating the intricate relationships between the climate policy uncertainty and stock markets in the U.S. It identifies the best-fit copulas to represent the dependence structures between the climate policy uncertainty and stock markets and determines the most reliable machine learning model for forecasting U.S. stock markets based on climate policy uncertainty.
To achieve this, the study uses the U.S. Climate Policy Uncertainty Index developed by Gavriilidis (2021), alongside U.S. stock market data covering major stock indexes and key industrial sectors, including transportation, mining, insurance, energy, waste and disposal services, and health care. The study uses Dynamic Conditional Correlation – Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH) and copula models to investigate conditional correlations and dependence structures between climate policy uncertainty and stock markets, respectively. Various machine learning models are assessed to evaluate the predictive power of climate policy uncertainty in forecasting stock markets.
The DCC-GARCH model findings highlight potential portfolio diversification opportunities in the transportation and insurance sectors because no information transmission is detected between these sectors and climate policy uncertainty using both symmetric and asymmetric models. Empirical results from dependence structure analysis suggest that U.S. stock markets are likely to rise alongside increases in climate policy uncertainty, because the Joe and Gumbel copulas are identified as the best-fit copulas for all examined pairs. Predictability analysis identifies Particle Swarm Optimization with eXtreme Gradient Boosting (PSO-XGBoost) as the most robust machine learning model for predicting U.S. stock markets based on climate policy uncertainty. The study also reveals that climate policy uncertainty exhibits the highest predictive power for the waste and disposal services sector and the lowest predictive power for the mining sector.
The study’s findings provide critical insights into the complex relationships between U.S. climate policy uncertainty and stock markets, offering valuable implications for portfolio managers, policymakers and investors
The effects of drop jump training with different hypoxic levels on the 6-s maximal cycling power test
No full textStrength training applied with hypoxia can offer potential advantages, especially for anaerobic efforts. However, there is uncertainty in the literature about whether high hypoxia may have harmful effects or low hypoxia may be ineffective. This study aimed to examine the impact of 8-week drop jump (DJ) training applied at different normobaric hypoxia levels on maximal anaerobic effort and to reveal the differences between low and high hypoxic training results. Nineteen team-sports athletes performed 8 weeks of DJ training under low normobaric hypoxic (Low-H, n=8), normobaric normoxic (NN, n=6), or high normobaric hypoxic (High-H, n=5) conditions (corresponding to SpO2 of 90%, 97-100%, and 80%, respectively), two times per week. We used a hypoxicator, which has a biofeedback control system that can be set to supply these breathing conditions. Training sessions started with a 10-minute warm-up, and participants were exposed to breathing conditions during the warm-up in addition to DJ exercises. We started with 1x6 DJs in the first week and finished with 2x8 in the 8th week. A Wattbike 6-second max effort anaerobic power test was conducted on a cycle ergometer pre- and post-training. Before testing, participants performed a 5-minute warm-up at a light intensity. The warm-up included two acceleration phases lasting 3 seconds, which started after 90 and 180 seconds. After the warm-up, participants performed maximal cycling in a seated position for 6 seconds. Peak power, average power, and cadence were recorded. Two sprints were completed, and the best one was used for the analysis. This study was granted by TUBITAK (The Scientific and Technological Research Council of Turkey) (No: 1059B191900892). While pre-test peak power was found to be 989.7±158.0 W for the NN group, 1090.4±189.7 W for the High-H group, and 1026.6±267.9 W for the Low-H group, posttest peak power was found to be 947.0±113.0 W for the NN group, 1156.4±225.4 W for the High-H group, and 1065.8±245.0 W for the Low-H group. As a result of mixed-design repeated measures ANOVA, we found no significant difference between pre- and post-tests and any training groups for the variables of the anaerobic power test (p>0.05). It can be concluded that DJ training applied with either low or high hypoxia did not enhance the 6-second anaerobic power test results more than that with normoxi
Effects of calcium propionate seed treatments and foliar sprays of potatoes
No full textPotatoes provide a significant economical value to the New Zealand economy, contributing over $1 billion per year. Candidatus Liberibacter solanacearum (CLso) which causes zebra chip disease and is vectored by tomato potato psyllid (Bactericera cockerelli) (TPP) causes several million dollars of damage to the potato industry. Calcium propionate (Ca prop) is used as a food additive to inhibit micro-organisms. In this series of trials, we investigated its use to prevent infection by CLso. Preliminary investigations in pots using ‘Moonlight’ seed potatoes showed no infection in potato plants, which received a single foliar treatment of 0.25, 0.5, 0.75 or 1% Ca prop or a 2% Ca prop soil drench were not infected. Only untreated tubers were infected with CaLSo after exposure to CLSo-infected TPP for 3 weeks. A second trial focussed on soil drench treatments with concentrations of 0.25, 0.5, 0.75, 1.0, and 2.0%. All soil drench treatments showed a 50 to 100% reduction in CLso infection compared to the control. A third trial using ‘Russet Burbank’ seed tubers treated with of 1% foliar treatment, 5% seed treatment in which tubers were dipped into Ca prop and a third treatment of the foliar and seed treatment combined did not show significant differences. More trials are needed to determine if success is related to potato variety, changes in cell wall strength, or psyllid feeding preferences