Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting impact damage , residual strength and crashworthiness of composite structures

The development of the latest generation of wide-body carbon-fibre composite passenger aircraft has heralded a new era in the utilisation of these materials. The premise of superior specific strength and stiffness, corrosion and fatigue resistance, is tempered by high development costs, slow production rates and lengthy and expensive certification programmes. Substantial effort is currently being directed towards the development of new modelling and simulation tools, at all levels of the development cycle, to mitigate these shortcomings. One of the primary challenges is to reduce the extent of physical testing, in the certification process, by adopting a ‘certification by simulation’ approach. In essence, this aspirational objective requires the ability to reliably predict the evolution and progression of damage in composites. The aerospace industry has been at the forefront of developing advanced composites modelling tools. As the automotive industry transitions towards the increased use of composites in mass-produced vehicles, similar challenges in the modelling of composites will need to be addressed, particularly in the reliable prediction of crashworthiness. While thermoset composites have dominated the aerospace industry, thermoplastics composites are likely to emerge as the preferred solution for meeting the high-volume production demands of passenger road vehicles. This keynote paper outlines recent progress and current challenges in the development of finite-element-based predictive modelling tools for capturing impact damage, residual strength and energy absorption capacity of thermoset and thermoplastic composites for crashworthiness assessments. CITATION: Falzon, B. and Tan, W. , "Predicting Impact Damage, Residual Strength and Crashworthiness of Composite Structures," SAE Int. J. Mater. Manf. 9(3):2016, doi:10.4271/2016-01-0497. 2016-01-0497 Published 04/05/2016 Copyright © 2016 SAE International doi:10.4271/2016-01-0497 saematman.saejournals. org Downloaded from SAE International by Brian Falzon, Tuesday, April 05, 2016
Lack of association of VEGF-A polymorphisms and susceptibility to amyotrophic lateral sclerosis and multiple sclerosis: A systematic review and meta-analysis

Amyotrophic lateral sclerosis (ALS) and multiple sclerosis (MS) are degenerative scleroses with unclear etiology. Vascular endothelial growth factor A ( VEGF-A ) is a growth factor that plays multiple roles in the central nervous system. Previous studies indicated a potential association between polymorphisms in this gene and the susceptibility of ALS and MS; however, the results have been inconclusive. Here, we conducted a systematic review and meta-analysis to elucidate the relationship between polymorphisms in the VEGF-A gene and these degenerative scleroses. We searched for observational studies in PubMed, Web of Science, EMBASE, Virtual Health Library (BVS) and SCOPUS
NBER WORKING PAPER SERIES THE ECONOMIC IMPACT OF NON-COMMUNICABLE DISEASE IN CHINA AND INDIA: ESTIMATES, PROJECTIONS, AND COMPARISONS

This paper provides estimates of the economic impact of non-communicable diseases (NCDs) in China and India for the period 2012-2030. Our estimates are derived using WHO’s EPIC model of economic growth, which focuses on the negative effects of NCDs on labor supply and capital accumulation. We present results for the five main NCDs (cardiovascular disease, cancer, chronic respiratory disease, diabetes, and mental health). Our undiscounted estimates indicate that the cost of the five main NCDs will total USD 27.8 trillion for China and USD 6.2 trillion for India (in 2010 USD). For both countries, the most costly domains are cardiovascular disease and mental health, followed by respiratory disease. Our analyses also reveal that the costs are much larger in China than in India mainly because of China’s higher income and older population. Rough calculations also indicate that WHO’s Best Buys for addressing the challenge of NCDs are highly cost-beneficial. David E. Bloom Harvard School of Public Health Department of Global Health and Population 665 Huntington Ave. Boston, MA 02115 and NBER dbloom@hsph.harvard.edu Elizabeth T. Cafiero Harvard School of Public Health Department of Global Health and Population 665 Huntington Avenue Building 1, Suite 1202 Boston, MA 02115 ecafiero@hsph.harvard.edu Mark E. McGovern Harvard Center for Population and Development Studies 9 Bow Street Cambridge, Massachusetts 02138 mcgovern@hsph.harvard.edu Klaus Prettner Department of Economics University of Göttingen Room 2.138 Platz der Goettinger Sieben 3 D-37073 Goettingen Germany Klaus.prettner@wiwi.uni-goettingen.de Anderson Stanciole The Bill and Melinda Gates Foundation 500 5th Ave N Seattle, WA 98109 Anderson.Stanciole@gatesfoundation.org Jonathan Weiss London School of Hygiene and Tropical Medicine Keppel Street, London WC1E 7HT United Kingdom and UNICEF Supply Division, Copenhagen, Denmark jonathan.weiss@lshtm.ac. uk Samuel Bakkila Department of Global Health and Population Harvard School of Public Health 665 Huntington Avenue Building I 12th Floor, Suite 1202 Boston, Massachusetts 02115 sbakkila@gmail.com Larry Rosenberg Department of Global Health and Population Harvard School of Public Health 665 Huntington Avenue Building I 12th Floor, Suite 1202 Boston, Massachusetts 02115 larry_rosenberg@harvard.edu
Task‐oriented resource prediction and adjustment algorithm for space‐based information network

The tasks of a space‐based information network are complex and diverse, but the resources of a space‐based environment are minimal. The existing methods are challenging to match task demand to resource supply accurately. Aiming at the problem of accurate prediction from task to resource, we propose a resource prediction adjustment strategy. First, we propose a multidimensional resource prediction algorithm based on improved particle swarm optimization and back propagation (IPSO‐BP) neural network. The improved PSO is used to optimize the weight and threshold of BP neural network to make up for the defects that BP neural network is easy to fall into local minimum and the predicted output value is not unique. Second, to meet the quality of service (QoS) of tasks, we propose a density‐based performance evaluation algorithm (DPEA) to adjust resources. This method uses the idea of local sensitive hash to select the evaluation subset for the configuration task, then dynamically selects the k nearest neighbors of the configuration task, and uses the idea of weighted average to evaluate the QoS performance index of the configuration task. Simulation results show that the proposed resource prediction and adjustment strategy effectively reduces the scheduling time overhead and improves resource utilization.
Advanced Dynamic Weight Bearing as an Observer-independent Measure of Hyperacute Hypersensitivity in Mice

ABSTRACT Background Standard methods assessing pain in rodents are often observer dependent, potentially resulting in biased outcomes. Advanced dynamic weight bearing (ADWB) offers an observer-independent approach that can provide objective, reliable data in preclinical pain research. Aims The aim of this study was to characterize the use of ADWB in assessing murine responses to allyl isothiocyanate (AITC)-induced hyperacute hypersensitivity and identify best practices for use of the device. Methods Male C57BL/6J mice received intraplantar injections of saline or 0.1% AITC solution and were assessed using the ADWB system; simultaneous observer-dependent durations of paw licking and biting were measured. ADWB data were analyzed using the proprietary software from Bioseb and correlated to observer-dependent results, with parameters assessed to optimize data collected. Results ADWB detected pain-directed changes in weight and surface area distribution in AITC-treated mice, with paw weight and surface area placement correlating to paw licking and biting. Optimization of adjustable threshold parameters allowed for reduced coefficients of variability and increased duration of validated data. Conclusions The ADWB assay provides an efficient and unbiased measure of chemical-induced hyperacute hypersensitivity in mice. ADWB detection parameters influence amount of validated data and variability, a consideration for data analysis in future studies.
Constitutive model for plain and fiber‐reinforced lightweight concrete under compression

In this research work, experimental investigations of the compressive behavior of plain and fiber‐reinforced lightweight‐aggregate concrete have been carried out (this formed part of a wider study, which also examined tensile and flexural behaviors). Compression mechanical properties were established in the studies and a generic constitutive compressive σ–ε model for both plain and fibrous lightweight concrete was derived and validated against experimental results from the present studies and previous research in the literature involving different types of lightweight aggregates, concrete strengths, and steel fibers. The reliability of predictions of the constitutive model was also checked against existing fibrous concrete models. A fiber‐reinforcing factor was also introduced taking into account the fiber volume fraction, fiber length and diameter, the number of fiber bends, and concrete compressive strength. As such, this was considered a better descriptor of the material than simply using the fiber volume fraction. The lightweight aggregates examined in the experimental study were recycled from fly ash waste and the fibers were hooked‐ended with single, double, and triple bends (corresponding to DRAMIX steel fibers 3D, 4D, and 5D types, respectively). The fibers were added at volume fractions Vf of 1% and 2% and the experimental studies were carried out using standard cube and cylinder uniaxial compression test specimens. It was concluded that the higher the number of bends and fiber content, the more pronounced the enhancement provided by the fibers to the compressive strength and ductility responses. All steel fibers used in the present studies were found to significantly improve the compressive toughness, while only 4D and 5D fibers (i.e., those with double and triple end bends) enhanced the compressive strength by up to 12% and 15%, respectively. It was also found that the elastic properties of plain lightweight concrete remained unaffected by the addition of fibers.
What is in your cookie box? Explaining ingredients of web cookies with knowledge graphs

The General Data Protection Regulation (GDPR) has imposed strict requirements for data sharing, one of which is informed consent. A common way to request consent online is via cookies. However, commonly, users accept online cookies being unaware of the meaning of the given consent and the following implications. Once consent is given, the cookie “disappears”, and one forgets that consent was given in the first place. Retrieving cookies and consent logs becomes challenging, as most information is stored in the specific Internet browser’s logs. To make users aware of the data sharing implied by cookie consent and to support transparency and traceability within systems, we present a knowledge graph (KG) based tool for personalised cookie consent information visualisation. The KG is based on the OntoCookie ontology, which models cookies in a machine-readable format and supports data interpretability across domains. Evaluation results confirm that the users’ comprehension of the data shared through cookies is vague and insufficient. Furthermore, our work has resulted in an increase of 47.5% in the users’ willingness to be cautious when viewing cookie banners before giving consent. These and other evaluation results confirm that our cookie data visualisation approach and tool help to increase users’ awareness of cookies and data sharing.
Matching Attribute Resolution to Scale: The Effects of Filtering on DEM Resolution

Raster datasets are important for spatial analysis and modeling as well as for cartographic display. As raster data becomes more readily available at finer spatial resolutions, generalization is required to meet project needs. The modification of detail in Digital Terrain Models through the generalization process of smoothing using a Gaussian Filter will be examined. While it can be assumed that the smoothing process will simplify the terrain through reduction of attribute complexity, the rate of generalization, variations for rough and smooth terrain, and differences in specific landscape conditions, as well as any intermediate spatial resolutions are unknown after iterative filtering. The theoretical contribution of this thesis is to systematically explore the concept of “implicit” resolution (attribute resolution) change, defined in the thesis as a modification to resolution which is the consequence of data processing or modeling without knowing in advance of the operation what is the precise resolution of the output. Several concerns arise after smoothing regarding data resolution and vertical integration with other datasets. This thesis will compare filtered Digital Elevation Models (DEM) to other National Elevation Datasets and National Hydrography Datasets of various spatial resolutions. A standard deviation and semivariogram analysis will relate the attribute resolution of a filtered DEM to a known spatial resolution, which can then be linked to a target mapping scale. A conflation
Models of the energy landscape for an element of shakti spin ice

Powered by TCPDF (www.tcpdf.org) This material is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the repository collections is not permitted, except that material may be duplicated by you for your research use or educational purposes in electronic or print form. You must obtain permission for any other use. Electronic or print copies may not be offered, whether for sale or otherwise to anyone who is not an authorised user. Arnalds, U. B. ; Liashko, S. Y. ; Bessarab, P. F. ; Uzdin, V. M. ; Jonsson, H.
Unlocking the water potential of agriculture

All statistical evidence confirms that agriculture is the key sector for water management, now and in the next decades. Nevertheless, the rural water development sector fails at present to get priority, compared to other competing sectors, in international fora. Strong and new arguments are needed to bring rural water back "on line. " Agriculture policies and investments will need to become more strategic. They will have to unlock the potential of agricultural water management practices to raise productivity, spread equitable access to water, and conserve the natural productivity of water resources base.
La Monnaie dans le circuit ou le voile déchiré

Pour comprendre la monnaie, il faut renoncer au circuit classique pour lui substituer le circuit dynamique. Dans ce circuit, la monnaie est purement endogène car elle trouve sa cause dans l’investissement qui permet aux entreprises d'anticiper les dépenses futures des ménages ou des autres entreprises. Le système bancaire ne contrôle pas la quantité de monnaie. Il peut contrôler le niveau du taux d’intérêt, causant ainsi la déformation spéculative du circuit. Un modèle général de ce circuit explique la formation des profits par la dépense d’investissement.
Point cloud segmentation for an individual tree combining improved point transformer and hierarchical clustering

Abstract. Individual tree segmentation of forestry point cloud data is of great significance to forest management and resource detection, because it can quickly and efficiently extract tree parameters and calculate biomass. Although research on individual tree segmentation of forestry point cloud data has made great progress, there are still many problems. For example, it is difficult to separate two trees when they are close to each other or occluded. In this work, a point cloud segmentation method is proposed to obtain an individual tree from forest plantation datasets, which combines improved point transformer and hierarchical clustering method. First, we use the improved point transformer to remove the ground and non-tree data to obtain pure tree point cloud data. Second, the tree point cloud data are converted to digital surface model and the watershed segmentation algorithm is used for the preliminary segmentation. Subsequently, a merging algorithm is proposed to merge the missing segmented point cloud data at the edge of the point cloud with the successfully segmented point cloud data, according to the nearest point cloud category. However, the results after the merging algorithm still have trees that cannot be segmented. Finally, a hierarchical clustering method is proposed for fine segmentation. For the improved point transformer, we utilized three regions for verification and three regions for testing. The mean intersection over union (MIOU) of the improved point transformer on the test set is 0.976, which is 1.1% higher than that of the original point transformer. For individual tree segmentation, we tested on five regions and obtained a MIOU of 0.742. The results demonstrate that the method proposed in this work can achieve better individual tree segmentation than other methods.
Direct versus indirect measures of mixed emotions in predictive models: a comparison of predictive validity, multicollinearity, and the influence of confounding variables

Mixed emotions have been assessed using both direct measures that utilize self-report questionnaires as well as indirect measures that are computed from scores of positive and negative emotions. This study provides a pre-registered methodological examination on the use of direct and indirect measures of mixed emotions in predictive models. Two samples (N = 749) were collected, and path analyses were performed to compare direct measures and indirect measures in predicting psychological conflict, receptivity, and well-being, controlling for demographics, positive emotions, and negative emotions. We also tested whether trait dialecticism, need for cognition, social desirability, or acquiescence could account for these associations. In both samples, results suggest that indirect measures may be more susceptible to multicollinearity when controlling for positive and negative emotions. Specifically, variance inflation factors (VIF) were consistently higher for indirect measures calculated using the minimum index (MIN; VIFSample-1 = 3.53; VIFSample-2 = 9.46) than direct measures (VIFSample-1 = 2.52; VIFSample-2 = 1.68). Direct measures remained consistently associated with increased conflict and reduced coherence upon controlling for positive and negative emotions, while indirect measures remained consistently associated only with increased conflict. We found little evidence that response biases explained associations between direct measures or indirect measures with each of the outcomes. Specifically, associations between mixed emotions with psychological conflict, receptivity, and well-being largely remained unchanged in models that controlled for trait dialecticism, need for cognition, social desirability, or acquiescence. Implications and recommendations based on our findings are discussed.
The Enhancement of Prospective Teachers’ Competence and Awareness in the Understanding by Design

In this study, a group of participants found the process of designing backward thinking distressing. Furthermore, the lack of practical strategies in schools and the absence of resources related to planning can lead to inadequacy in teachers' planning skills. This research aimed to enhance prospective teachers' competence and awareness of Understanding by Design. A case study was conducted with the participation of 17 teacher candidates from Kırıkkale University, Faculty of Education in Türkiye. The selection of candidates was voluntary. A 30-hour course on the theory and stages of backward design used in Understanding by Design was implemented from May 16th to 19th, 2022. This qualitative research employed data collection tools such as pre- and post-study open-ended questionnaires and performance tasks assessing lesson designs. The Understanding by Design template lesson plan and thought process were used to teach backward design in planning the training activity. The evaluation revealed that the pre-service teachers effectively utilized critical concepts associated with Understanding by Design, expressing their intention to incorporate understanding-based design into their future lessons and projects. The participants also emphasized the importance of all teachers adopting this instructional approach. Ultimately, the research suggests that the participants' competence and awareness of understanding-based design significantly improved throughout the course.
Greenhouse gases (CH4, CO2 and N2O) emissions from a newly flooded hydroelectric reservoir in subtropical South Asia: case of Nam Theun 2 reservoir, Lao PDR

L'augmentation de l'interet concernant la part des reservoirs hydroelectrique dans l'augmentation de la concentration atmospherique des Gaz a Effet de Serre (GES) a amene a mesurer les emissions nettes d'un reservoir hydroelectrique, Nam Theun 2 (NT2) dans la region subtropicale de la Republique Democratique Populaire du Laos, Asie. Ce travail est la premiere evaluation de l'empreinte carbone des GES (c'est a dire : les emissions apres ennoiement moins les emissions avant ennoiement) en relation avec la creation d'un reservoir hydroelectrique. C'est le resultat d'une etude a grande echelle qui s'est deroulee pendant cinq ans (2008-2012). Nous avons tout d'abord quantifie les sources et les puits majeurs des GES des composants terrestres et aquatiques du paysage avant ennoiement (Mai 2008). Ensuite, a partir d'Avril 2009, cette etude similaire a ete realisee au niveau du reservoir, sa zone de marnage et son aval. C'est en Octobre 2009 que le reservoir hydroelectrique NT2 a, pour la premiere fois, atteint son niveau maximal et c'est huit mois plus tard, en Mars 2010, que les turbines ont fonctionnees pour la premiere fois. En se basant sur un suivi bimensuel et sur cinq missions de terrain couvrant toutes les saisons, les emissions des principaux GES (c'est a dire l'oxyde nitreux (N2O), le methane (CH4) et le dioxyde de carbone (CO2)) ont ete mesurees d'Avril 2009 a Decembre 2011. Les emissions ont ete determinees a la surface du reservoir (flux diffusifs et ebullitifs) ainsi que dans les sols de la zone de marnage, qui peut atteindre 370 km2 pour une surface totale de reservoir de 450 km2.
Investigation of Short-Term Intermittency in Solar Irradiance and Its Impacts on PV Converter Systems

Increased installation of solar photovoltaic (PV) systems has drawn concerns of managing and mitigating the fast and unpredictable variations in solar power generation. This paper presents a detailed analysis of short-term (seconds level, transients) solar intermittency and its implications on solar PV array and DC/DC power converters. The impacts of the short term intermittency to the output power variations have also been studied considering the filtering components of the converter. In addition, the paper addresses the challenges about the identification of the short-term solar intermittency by utilising a moving window method. Furthermore, simulation and data analysis results provide insights of overcoming short-term solar uncertainty for PV system design and technical requirements of suitable power converters.