title: Under pressure: The chronic effects of lower-body compression garment use during a 6-week military training course

authors: Edgar, David Thomas

subjects: Science & Technology

abstract: Background: Previous studies have shown that compression garments may aid recovery in acute settings; however, less is known about the long-term use of compression garments (CG) for recovery. This study aimed to assess the influence of wearing CG on changes in physical performance, subjective soreness, and sleep quality over 6 weeks of military training. Methods: Fifty-five officer-trainees aged 24 ± 6 y from the New Zealand Defence Force participated in the current study. Twenty-seven participants wore CG every evening for 4–6 h, and twenty-eight wore standard military attire (CON) over a 6-week period. Subjective questionnaires (soreness and sleep quality) were completed weekly, and 2.4 km run time-trial, maximum press-ups, and curl-ups were tested before and after the 6 weeks of military training. Results: Repeated measures ANOVA indicated no significant group × time interactions for performance measures (p > 0.05). However, there were small effects in favour of CG over CON for improvements in 2.4 km run times (d = −0.24) and press-ups (d = 0.36), respectively. Subjective soreness also resulted in no significant group × time interaction but displayed small to moderate effects for reduced soreness in favour of CG. Conclusions: Though not statistically significant, CG provided small to moderate benefits to muscle-soreness and small benefits to aspects of physical-performance over a 6-week military training regime.

text: Under pressure: The chronic effects of lower-body compression garment use during a 6-week military training course Background: Previous studies have shown that compression garments may aid recovery in acute settings; however, less is known about the long-term use of compression garments (CG) for recovery. This study aimed to assess the influence of wearing CG on changes in physical performance, subjective soreness, and sleep quality over 6 weeks of military training. Methods: Fifty-five officer-trainees aged 24 ± 6 y from the New Zealand Defence Force participated in the current study. Twenty-seven participants wore CG every evening for 4–6 h, and twenty-eight wore standard military attire (CON) over a 6-week period. Subjective questionnaires (soreness and sleep quality) were completed weekly, and 2.4 km run time-trial, maximum press-ups, and curl-ups were tested before and after the 6 weeks of military training. Results: Repeated measures ANOVA indicated no significant group × time interactions for performance measures (p > 0.05). However, there were small effects in favour of CG over CON for improvements in 2.4 km run times (d = −0.24) and press-ups (d = 0.36), respectively. Subjective soreness also resulted in no significant group × time interaction but displayed small to moderate effects for reduced soreness in favour of CG. Conclusions: Though not statistically significant, CG provided small to moderate benefits to muscle-soreness and small benefits to aspects of physical-performance over a 6-week military training regime.

year: 2022

title: The state of well-being - A search for meaning in the New Zealand Regulatory Environment

authors: Wallace, Philippa Jane

abstract: The term "well-being" has gained prominence in national and international policy agendas. A malleable term with positive connotations and wide reach, it has become a standard objective for human advancement. New Zealand makes extensive use of the term in legislation, but well-being is seldom defined. This article explores wellbeing in New Zealand law and policy, with a focus on the Resource Management Act 1991 (RMA) and the Local Government Act 2002 (LGA). "Well-being" is revealed as a contested and context-dependent term at the heart of New Zealand's resource debates. Application tends to the uncritical in terms of definition and theoretical foundation. This may mask important differences between the states, which are not necessarily correlative, and may result in conflation of well-being with development. Although the term "well-being" is used with frequency in legislation, important differences are evident in the subject of wellbeing, the nature and extent of any obligation in respect of well-being, the identity of the obligor and the particularisation of dimensions of well-being. At times these nuances are lost in translation, and whilst acknowledging the benefits of the expansive and adaptive term, recommendations are made regarding its use in environmental law.

text: The state of well-being - A search for meaning in the New Zealand Regulatory Environment The term "well-being" has gained prominence in national and international policy agendas. A malleable term with positive connotations and wide reach, it has become a standard objective for human advancement. New Zealand makes extensive use of the term in legislation, but well-being is seldom defined. This article explores wellbeing in New Zealand law and policy, with a focus on the Resource Management Act 1991 (RMA) and the Local Government Act 2002 (LGA). "Well-being" is revealed as a contested and context-dependent term at the heart of New Zealand's resource debates. Application tends to the uncritical in terms of definition and theoretical foundation. This may mask important differences between the states, which are not necessarily correlative, and may result in conflation of well-being with development. Although the term "well-being" is used with frequency in legislation, important differences are evident in the subject of wellbeing, the nature and extent of any obligation in respect of well-being, the identity of the obligor and the particularisation of dimensions of well-being. At times these nuances are lost in translation, and whilst acknowledging the benefits of the expansive and adaptive term, recommendations are made regarding its use in environmental law.

year: 2019

title: A hybrid architecture for labelling bilingual Māori-English tweets

authors: Trye, David

subjects: borrowing

abstract: Most large-scale language detection tools perform poorly at identifying Māori text. Moreover, rule-based and machine learning-based techniques devised specifically for the Māori-English language pair struggle with interlingual homographs. We develop a hybrid architecture that couples Māori-language orthography with machine learning models in order to annotate mixed Māori-English text. This architecture is used to label a new bilingual Twitter corpus at both the token (word) and tweet (sentence) levels. We use the collected tweets to show that the hybrid approach outperforms existing systems with respect to language detection of interlingual homographs and overall accuracy. We also evaluate its performance on out-of-domain data. Two interactive visualisations are provided for exploring the Twitter corpus and comparing errors across the new and existing techniques. The architecture code and visualisations are available online, and the corpus is available on request.

text: A hybrid architecture for labelling bilingual Māori-English tweets Most large-scale language detection tools perform poorly at identifying Māori text. Moreover, rule-based and machine learning-based techniques devised specifically for the Māori-English language pair struggle with interlingual homographs. We develop a hybrid architecture that couples Māori-language orthography with machine learning models in order to annotate mixed Māori-English text. This architecture is used to label a new bilingual Twitter corpus at both the token (word) and tweet (sentence) levels. We use the collected tweets to show that the hybrid approach outperforms existing systems with respect to language detection of interlingual homographs and overall accuracy. We also evaluate its performance on out-of-domain data. Two interactive visualisations are provided for exploring the Twitter corpus and comparing errors across the new and existing techniques. The architecture code and visualisations are available online, and the corpus is available on request.

year: 2022