Progress report for the National Design Council

12 leaves

Linear programming can help identify practical solutions to improve the nutritional quality of food aid.

OBJECTIVES: To assess the nutritional quality of food aid delivered by food banks in France and to identify practical modifications to improve it. DESIGN: National-level data were collected for all food aid distributed by French food banks in 2004, and its nutrient content per 2000 kcal was estimated and compared with French recommendations for adults. Starting with the actual donation and allowing new foods into the food aid donation, linear programming was used to identify the minimum changes required in the actual donation to achieve the French recommendations. RESULTS: French food-bank-delivered food aid does not achieve the French recommendations for dietary fibre, ascorbic acid, vitamin D, folate, magnesium, docosahexaenoic acid, alpha-linolenic acid and the percentage of energy from saturated fatty acids. Linear programming analysis showed that these recommendations are achievable if more fruits, vegetables, legumes and fish were collected and less cheese, refined cereals and foods rich in fat, sugar and/or salt. In addition, new foods not previously collected are needed, particularly nuts, wholemeal bread and rapeseed oil. These changes increased the total edible weight (42%) and economic value (55%) of the food aid donation, with one-third of its edible weight coming from fruits and vegetables, one-third from staples, one-quarter from dairy products and approximately a tenth from meat/fish/eggs. CONCLUSIONS: Important changes in the types and amounts of food collected will improve the nutritional quality of food-bank-delivered food aid in France. Such changes are recommended to improve the diets of deprived French populations

Deconstructing Inequality: Cumulative Impacts, Environmental Justice, and Interstate Redevelopment

The siting and development of Interstate 81 in Syracuse, New York, similar to highway projects across the nation, lead to the displacement of Black Syracusans and has exposed thousands of remaining residents at heightened environmental harm. As the interstate is slated to be redeveloped due to age and safety issues, national attention has focused on the highway as a potential exemplar for similar projects across the United States. Federal law mandates that environmental impact analysis be conducted, and due to the prevalence of marginalized populations, environmental justice impacts are a critical feature in this assessment. This article evaluates both the redevelopment of the interstate through an assessment of a 10,000+ page draft environmental impact statement, review of relevant policy documents and attendance at public meetings to assess the potential for environmentally sustainability and just outcomes. It concludes that, along with similar redevelopment projects from online due to the nation’s aging infrastructure, environmental analysis and planning must employ restorative justice frameworks to strengthen and heal communities impacted from the legacy of racist urban planning

The effect of brain breaks on student outcomes of school-aged children in k-12 classrooms: a meta-analysis

BACKGROUND: Integrated physical activity in the classroom has been shown to affect K-12 students’ development positively. Students of all abilities benefit from multimodality learning. PURPOSE: This study investigates the relationship between classroom brain breaks and school-aged students\u27 classroom behaviors. METHODS: The Meta-analysis search process consisted of 3 Phases: (1) Screen the titles, (2) Screen the abstracts, and (3) Retrieve the Full Text. Literature searches were conducted in eight electronic academic journal databases: SPORTDiscus, PsycINFO, PsycARTICLES, Cochrane Database, Web of Science/Web of Knowledge, ProQuest, Child Development and Adolescent Studies, and ERIC. Students (N) are enrolled in schools serving students from kindergarten through twelfth grade. RESULTS: The overall effect that brain breaks provided across all outcomes was small (k = 56, g = 0.36, 95% CI = 0.22, 0.50, P \u3c 0.001) with large prediction intervals for each of the category outcomes that suggest a large degree of variability. CONCLUSIONS: Future research should consider the methods used to implement brain breaks by following specified guidelines that produce positive results for the intended outcomes being studied

Utilizing a novel high-resolution malaria dataset for climate-informed predictions with a deep learning transformer model

長崎大学学位論文 [学位記番号]博（医歯薬）甲第1602号 [学位授与年月日]令和6年3月19日(2024-03-19)thesi

The Biblical Basis of William Wilberforce\u27s Fight for the Abolition of Slave Trade in the British Empire as Evidenced from His Writings and Speeches

William Wilberforce was the foremost legislator who singlehandedly worked to rally the British government to abolish slavery in the British empire. He rallied through writings and speeches and this article attempts to find his spiritual conviction in his fight against slavery. Wilberforce was driven by his conviction that stemmed from his belief in the Bible as  the word of God and he frequently justified his stand by the words from the Bible. We can find him using many verses of the Bible to direct his audience to rooting for the legislation to abolish slavery and he ultimately succeeded through his strong faith and utmost perseverance in valuing those who were termed as barbaric and enslaved because they were inferior

Utilizing a novel high-resolution malaria dataset for climate-informed predictions with a deep learning transformer model

Nagasaki University (長崎大学)博士(医学)Climatic factors influence malaria transmission via the effect on the Anopheles vector and Plasmodium parasite. Modelling and understanding the complex effects that climate has on malaria incidence can enable important early warning capabilities. Deep learning applications across fields are proving valuable, however the field of epidemiological forecasting is still in its infancy with a lack of applied deep learning studies for malaria in southern Africa which leverage quality datasets. Using a novel high resolution malaria incidence dataset containing 23 years of daily data from 1998 to 2021, a statistical model and XGBOOST machine learning model were compared to a deep learning Transformer model by assessing the accuracy of their numerical predictions. A novel loss function, used to account for the variable nature of the data yielded performance around + 20% compared to the standard MSE loss. When numerical predictions were converted to alert thresholds to mimic use in a real-world setting, the Transformer’s performance of 80% according to AUROC was 20–40% higher than the statistical and XGBOOST models and it had the highest overall accuracy of 98%. The Transformer performed consistently with increased accuracy as more climate variables were used, indicating further potential for this prediction framework to predict malaria incidence at a daily level using climate data for southern Africa.長崎大学学位論文 学位記番号:博(医歯薬)甲第1602号 学位授与年月日:令和6年3月19日Author: Micheal T. Pillay, Noboru Minakawa, Yoonhee Kim, Nyakallo Kgalane, Jayanthi V. Ratnam, Swadhin K. Behera, Masahiro Hashizume & Neville SweijdCitation: Scientific Reports, 13, art. no. 23091; 2023Nagasaki University (長崎大学), 博士(医学) (2024-03-19)doctoral thesi

Traditional agroforestry for food security and agrobiodiversity- The Angami Naga nhalie-teizie binary system in Nagaland state of India

Traditional agroforestry practice of Angami Nagas is the integrated system of cultivating multipurpose local tree species with traditional crops varieties. Nhalie (slash and burn) and teizie (home garden) are the two major forms of traditional agroforestry which are the primary sources of food, medicine, firewood, fodder, cultural needs, livelihoods and other utilities of equal importance. The present study, which was conducted from, March 2016 to November 2019, aims to investigate the contribution of traditional agroforestry to food security among the Angami Nagas of Kohima district, Nagaland. Data collection methods included group discussion, semi-structured interview and field observations. Angami agroforestry is the main repository of agrobiodiversity. Agrobiodiversity plays important role in food security of the Angami Nagas. Agrobiodiversity avails of continuous accessibility of diverse foods all the year round. This study documented 32 species under 8 types of crops cultivated in nhalie and 71 species of food plants from teizie (homegarden). Nhalie has the potential to augment coproduction of foods and firewood to meet the increasing needs of food and energy security without negative consequences on environment. Pretty good number of wild edibles and conventional crops growing in home gardens contributes towards supplementing food during off season. Well-designed Angami granary and traditional techniques of preservation help to ensure food security by reducing unwanted post-harvest damages. Angami agroforestry not only enhances food and energy security but also infers as a tool for conservation of agrobiodiversity and sustainable development

Response-based methods to measure road surface irregularity: a state-of-the-art review

"jats:sec" "jats:title"Purpose"/jats:title" "jats:p"With the development of smart technologies, Internet of Things and inexpensive onboard sensors, many response-based methods to evaluate road surface conditions have emerged in the recent decade. Various techniques and systems have been developed to measure road profiles and detect road anomalies for multiple purposes such as expedient maintenance of pavements and adaptive control of vehicle dynamics to improve ride comfort and ride handling. A holistic review of studies into modern response-based techniques for road pavement applications is found to be lacking. Herein, the focus of this article is threefold: to provide an overview of the state-of-the-art response-based methods, to highlight key differences between methods and thereby to propose key focus areas for future research."/jats:p" "/jats:sec" "jats:sec" "jats:title"Methods"/jats:title" "jats:p"Available articles regarding response-based methods to measure road surface condition were collected mainly from “Scopus” database and partially from “Google Scholar”. The search period is limited to the recent 15 years. Among the 130 reviewed documents, 37% are for road profile reconstruction, 39% for pothole detection and the remaining 24% for roughness index estimation."/jats:p" "/jats:sec" "jats:sec" "jats:title"Results"/jats:title" "jats:p"The results show that machine-learning techniques/data-driven methods have been used intensively with promising results but the disadvantages on data dependence have limited its application in some instances as compared to analytical/data processing methods. Recent algorithms to reconstruct/estimate road profiles are based mainly on passive suspension and quarter-vehicle-model, utilise fewer key parameters, being independent on speed variation and less computation for real-time/online applications. On the other hand, algorithms for pothole detection and road roughness index estimation are increasingly focusing on GPS accuracy, data aggregation and crowdsourcing platform for large-scale application. However, a novel and comprehensive system that is comparable to existing International Roughness Index and conventional Pavement Management System is still lacking."/jats:p" "/jats:sec Document type: Articl