nils-herrmann/clean_scirepeval huggingface dataset:
A comprehensive survey on point cloud registration
Venue: ArXiv
Year: 2021

Registration is a transformation estimation problem between two point clouds, which has a unique and critical role in numerous computer vision applications. The developments of optimization based methods and deep learning methods have improved registration robustness and efficiency. Recently, the combinations of optimization based and deep learning methods have further improved performance. However, the connections between optimization based and deep learning methods are still unclear. Moreover, with the recent development of 3D sensors and 3D reconstruction techniques, a new research direction emerges to align cross source point clouds. This survey conducts a comprehensive survey, including both same source and cross source registration methods, and summarize the connections between optimization based and deep learning methods, to provide further research insight. This survey also builds a new benchmark to evaluate the state of the art registration algorithms in solving cross source challenges. Besides, this survey summarizes the benchmark data sets and discusses point cloud registration applications across various domains. Finally, this survey proposes potential research directions in this rapidly growing field.
Sources of high PM2.5 concentrations in Milan, Northern Italy: molecular marker data and CMB modelling.
Venue: The Science of the total environment
Year: 2012

In Milan (MI) the largest city in Northern Italy, the annually average PM2.5 concentration is above 25 mg m( 3) the value that the EU established as a target for 2010, and the upper limit from 2015 onwards (2008/30/CE) Over a three year period (2006 2009) PM concentrations and chemical compositions were measured in an urban site (MI) a rural site (OB) and a remote site (ASC) in Northern Italy. Chemical characterization (EC/OC, inorganic ions, elements, C20 C32 n alkanes, C2 C5 mono and dicarboxylic acids, levoglucosan and PAHs) was carried out on PM2.5 samples from the three sites, and PM10 from MI. Molecular markers were used in Chemical Mass Balance (CMB) modelling to estimate the contributions of primary sources to OC, and then PM mass from each source was reconstructed in MI, OB and ASC for different seasons. Estimates of the traffic (TR) source contribution to PM2.5 mass ranged from 4.1 2.0) mg m( 3) during the summer, to 13.3 6.7) mg m( 3) during the winter in MI. TR was the main primary source for PM2.5 concentrations in MI (17 24% Its contribution was lower at the OB site (7 9% and at the remote ASC site (3 4% TR is a local source, while biomass burning (BB) is a diffuse regional source in Northern Italy: during fall and winter, BB was 25 30% and 27 31% of PM2.5 at MI and OB respectively. Other primary sources accounted for a small amount of the PM2.5, i.e. natural gas combustion (0 1% plant debris (0 4% road dust (RD=0 4% but 15% at ASC during winter and 10% of PM10 at MI during summer) and sea salt (0 1% Secondary inorganic+organic aerosol constituted the major part of the PM2.5 mass during spring and summer (50 65% at the three sites.
Archaeogaming: An Introduction to Archaeology in and of Video Games by Andrew Reinhard (review)
Year: 2019

Page 257 04/06/19 5:25 PM JEMAHS 7.2_06_Book Reviews.indd Page 256 04/06/19 5:25 PM Archaeogaming, by Andrew Reinhard, is an introductory text to a relatively new subfield of archaeology. At first glance, the title of this work immediately brings to mind media studies of archaeology focusing on well worn characters such as Lara Croft from the Tomb Raider series or the various adaptations of Indiana Jones to the gaming universe. While Reinhard does spend some time discussing media representation of archaeology and archaeologists in video games, his project is significantly broader than this, aspiring to outline a variety of perspectives from which archaeological thought can be brought to bear on digital worlds and their impact in "meatspace" (that is, real life) (p. 2) The book is divided into six sections, with four primary chapters as well as the introduction and conclusion. The primary chapters are essentially categorical, with the first three addressing, in order, an archaeology of the video game industry, archaeology in video games, and video games as sites of study in their own right. The fourth chapter, titled "Material Culture of the Immaterial" addresses a mixture of these topics. The final substantive section of the book is an appendix (pp. 203 9) containing the code of ethics for the No Man's Sky Archaeological Survey (NMSAS) discussed in Chapter 3 (pp. 130 48) After opening the introduction with a series of short vignettes from his own life to illustrate a few scenarios where the archaeogaming moniker might apply, Reinhard launches into a discussion of what archaeogaming is and identifies it as being analogous to real world archaeology. Accordingly, archaeogaming addresses five themes (p. 3) though these are more of a starting point than an exhaustive list. The first is rather uncontroversial, being the study of the material culture of gaming. Having gone through roughly five decades of development, digital gaming has generated a substantial material assemblage and has been the driving force behind the development of a variety of social phenomena (see Chapters 1 and 4) Second is the representation of archaeology and museum studies in video games and the handling of topics such as looting, ethics, and racism (Chapter 2, pp. 172 75) Third, and perhaps most interesting (or frustrating, given the seemingly infinite number of debates that could emerge from the topic! is the notion of doing archaeology in video games. There are a variety of issues to discuss here ranging from how to conceive of games as archaeological sites to the question of whether in game cultures are truly cultures in the sense of aggregates of phenomena transmitted through social learning. Whether one agrees with Reinhard or not, the notion of conducting archaeology in video games as discussed in the book provides much to think about. The fourth and fifth themes are more vaguely worded, justifying direct quotation so the reader may try to parse their meaning for themselves:
Reconstruction of Sparse Signals in Impulsive Disturbance Environments
Venue: Circuits Syst. Signal Process.
Year: 2017

Sparse signals corrupted by impulsive disturbances are considered. The assumption about disturbances is that they degrade the original signal sparsity. No assumption about their statistical behavior or range of values is made. In the first part of the paper, it is assumed that some uncorrupted signal samples exist. A criterion for selection of corrupted signal samples is proposed. It is based on the analysis of the first step of a gradient based iterative algorithm used in the signal reconstruction. An iterative extension of the original criterion is introduced to enhance its selection property. Based on this criterion, the corrupted signal samples are efficiently removed. Then, the compressive sensing theory based reconstruction methods are used for signal recovery, along with an appropriately defined criterion to detect a full recovery event among different realizations. In the second part of the paper, a case when all signal samples are corrupted by an impulsive disturbance is considered as well. Based on the defined criterion, the most heavily corrupted samples are removed. The presented criterion and the reconstruction algorithm are applied on the signal with a Gaussian noise.
Stability of melamine formaldehyde (MF) resin under different pH and ionic strength values
Year: 2020

Melamine and melamine formaldehyde (MF) resin are both commonly used materials in food technology. It is shown in this work that the stability of aqueous solutions of MF resins during storage is strongly influenced by the ionic strength and the pH value of the suspending medium. Aggregation phenomena, polymerization, or disintegration of MF resin particles can take place. The critical aggregation concentration (CAC 1.67 x 10 2 M KNO3) and the rate constant kapp (1.24 x 10 23 ml/s) for the bimolecular process of aggregation are determined. When the electrolyte concentration is very close to the CAC, the aggregation is slow. By increasing the electrolyte concentration the aggregation process is faster. In high values of ionic strength the aggregation happens almost immediately. At low pH values aggregation phenomena and split of the MF in smaller particles can influence the stability of MF resin particles. For this study, field flow fractionation technique was used.  The present work investigates the role of ionic strength and pH on the stability of melamine. It is shown that aggregation phenomena, polymerization, or disintegration of MF resin particles can take place. Both, aggregation phenomena and split of the MF in smaller particles can influence the stability of MF resin particles at low pH values. These results show that dishes and kitchen utensils made of melamine resins could release melamine when used for acidic foods. The results of this work could be of great importance for both consumers and industry, since they concern preservation, construction, manufacturing, and use of common housewares.
Association Rules Enhanced Knowledge Graph Attention Network
Venue: ArXiv
Year: 2020

Most existing knowledge graphs suffer from incompleteness. Embedding knowledge graphs into continuous vector spaces has recently attracted increasing interest in knowledge base completion. However, in most existing embedding methods, only fact triplets are utilized, and logical rules have not been thoroughly studied for the knowledge base completion task. To overcome the problem, we propose an association rules enhanced knowledge graph attention network (AR KGAT) The AR KGAT captures both entity and relation features for high order neighborhoods of any given entity in an end to end manner under the graph attention network framework. The major component of AR KGAT is an encoder of an effective neighborhood aggregator, which addresses the problems by aggregating neighbors with both association rules based and graph based attention weights. Additionally, the proposed model also encapsulates the representations from multi hop neighbors of nodes to refine their embeddings. The decoder enables AR KGAT to be translational between entities and relations while keeping the superior link prediction performance. A logic like inference pattern is utilized as constraints for knowledge graph embedding. Then, the global loss is minimized over both atomic and complex formulas to achieve the embedding task. In this manner, we learn embeddings compatible with triplets and rules, which are certainly more predictive for knowledge acquisition and inference. We conduct extensive experiments on two benchmark datasets: WN18RR and FB15k 237, for two knowledge graph completion tasks: the link prediction and triplet classification to evaluate the proposed AR KGAT model. The results show that the proposed AR KGAT model achieves significant and consistent improvements over state of the art methods.
Multimode Optimization Research on a Multiport Magnetic Planetary Gear Permanent Magnet Machine for Hybrid Electric Vehicles
Venue: IEEE Transactions on Industrial Electronics
Year: 2018

In this paper, by incorporating the new concept of the noncontact magnetic planetary gear into a permanent magnet brushless machine, a new multiport magnetic planetary gear permanent magnet machine is proposed. To achieve flexible combination and split of the power and torque among different electrical or mechanical ports in the machine, a multiobjective optimization design method considering multioperational modes is proposed and investigated. To obtain high optimization design efficiency, the whole optimization is divided into three steps based on various driving modes. In each step, the multobjective genetic algorithm, response surface method, and direct screening method are utilized, respectively. Moreover, the basic no load characteristics and torque performances of the proposed machine are also studied. Finally, a prototype machine based on the optimized structure dimensions is manufactured and tested. Both the theoretical and experimental analysis verifies the effectiveness of the investigated machine and the proposed method.
Climate Change and Sustainability of Agriculture A Review
Year: 2016

Climate is one of the most important input factors for agricultural productivity all over the world. Global warming because of anthropogenic green house effect has resulted in changing climatic patterns and increased intensity of extreme weather events over different regions of earth, which have adverse effect on agricultural productivity along with far reaching socio economic impacts. Rapid emission and accumulation ofgreen house gases in the atmosphere has exposed us to the potential threat of global warming. As the climatic patterns all over the earth are controlled by the average temperatures, thus variations in the climatic patterns are observed because of increase in temperature. These variations can cause disasters including droughts and floods in different parts of the earth. All these factors have a direct effect on agriculture and pose a severe threat to crop productivity and food security especially in the tropical and sub tropical areas. Several research studies indicate that Increase in the concentration of CO2 upto about 600 ppm can counterbalance the adverse effect of rise in temperature by 1deg C, but further increase in temperature will have negative impact on crop productivity. Improved understanding of the influence of climate on agricultural production is needed to cope with the expected changes in temperature and precipitation and to maintain agricultural sustainability and food security. Suitable mitigation/adaptation strategies need to be identified and adopted to meet the challenges posed by climate change on agricultural productivity.
Training strategies for a lower limb rehabilitation robot based on impedance control
Venue: 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Year: 2012

This paper proposes three training strategies based on impedance control, including passive training, damping active training and spring active training, for a 3 DOF lower limb rehabilitation robot designed for patients with paraplegia or hemiplegia. Controllers with similar structure are developed for these training strategies, consisting of dual closed loops, the outer impedance control loop and the inner position/velocity control loop, known as position based impedance control method. Simulation results verify that position based impedance control approach is feasible to accomplish the training strategies.
Parenting Style as Correlates of Adolescents' Academic Achievement Motivation of Bate Secondary School, Haramaya, Ethiopia
Venue: International Journal of Education and Literacy Studies
Year: 2019

This study aimed at examining the relationship of adolescents' academic achievement motivation and parenting styles. Data were collected from randomly selected 192 adolescent students (93 males and 99 females) through standardized scales of achievement motivation self report inventory and parenting style scale. The data analysis has been done through both descriptive and inferential statistical methods. To this end, finding revealed that authoritarian parenting style is the most commonly practiced parenting style in the families of respondents among other three parenting styles (authoritative, indulgent and neglectful) There is a statistically significant relationship between authoritative parenting style and students' academic achievement motivation. Significant relationship between authoritarian parenting style and students' academic achievement motivation has also been reported. There is strong and negative relationship between neglectful parenting style and students' academic achievement motivation. That it means, neglectful parenting negatively affects students' academic motivation. As expected, significant relationship between indulgent parenting style and students' academic motivation was not reported. In the end, some points were forwarded to suggest ways of properly addressing the gaps noted in this research.
Syddansk Universitet A Proposal for a Study on Treatment Selection and Lifestyle Recommendations in Chronic Inflammatory Diseases
Year: 2017

Chronic inflammatory diseases (CIDs) including Crohn's disease and ulcerative colitis (inflammatory bowel diseases, IBD) rheumatoid arthritis, psoriasis, psoriatic arthritis, spondyloarthritides, hidradenitis suppurativa, and immune mediated uveitis, are treated with biologics targeting the pro inflammatory molecule tumour necrosis factor a (TNF) (i.e. TNF inhibitors) Approximately one third of the patients do not respond to the treatment. Genetics and lifestyle may affect the treatment results. The aims of this multidisciplinary collaboration are to identify (1) molecular signatures of prognostic value to help tailor treatment decisions to an individual likely to initiate TNF inhibitor therapy, followed by (2) lifestyle factors that support achievement of optimised treatment outcome. This report describes the establishment of a cohort that aims to obtain this information. Clinical data including lifestyle and treatment response and biological specimens (blood, faeces, urine, and, in IBD patients, intestinal biopsies) are sampled prior to and while on TNF inhibitor therapy. Both hypothesis driven and data driven analyses will be performed according to pre specified protocols including pathway analyses resulting from candidate gene expression analyses and global approaches (e.g. metabolomics, metagenomics, proteomics) The final purpose is to improve the lives of patients suffering from CIDs, by providing tools facilitating treatment selection and dietary recommendations likely to improve the clinical outcome.
Single shot temporal profile measurement of a soft X ray laser pulse
Year: 2018

We report an original method allowing to recover the temporal profile of any kind of soft X ray laser pulse in single shot operation. We irradiated a soft X ray multilayer mirror with an intense infrared femtosecond laser pulse in a traveling wave geometry and took advantage of the sudden reflectivity drop of the mirror to reconstruct the temporal profile of the soft X ray pulse. We inferred a pulse shape with a duration of a few ps in good agreement with numerical calculations and experimental work.
Health and nutrition related claims of non alcoholic beverage labels in supermarkets: their compliance with Sri Lanka Food Labelling and Advertising Regulations
Year: 2020

The main legislation governing food labelling in Sri Lanka is the Food Act which is implemented by health authorities. Food labels provide information to help consumers make healthier and safe food choices.  To assess the compliance of health and nutrition claims of labels of non alcoholic beverages with food labelling regulation  A descriptive cross sectional study was carried out in all 18 supermarkets in the Kandy Municipal Council Area. Non alcoholic beverages were assessed. A judgmentally validated pre tested checklist containing provisions of the labelling regulation was used as the study instrument. Data collection was done by four trained data collectors.  Of the 214 beverages assessed, 5.1% (n=11) did not have the common name in two languages. Claims or pictures to the effect that the beverage is recommended by medical practitioners or a professional association was present in 8.1% (n=19) Of the 56 milk products and health drinks, 8.9% (n=5) made claims that dietary fats benefit heart patients. Claim of food being an aid for slimming or weight reduction was found in 14% (n=9) of the 64 milk products, health drinks and green tea surveyed. Of the 36 beverages which made special claims, 30 (83% did not have declarations that the natural food items also have the same characteristic.  Labels of considerable proportions of beverages contravene the provisions of the food labelling regulation, indicating the importance of proper implementation of the regulation.
Self Determination Theory: Basic Psychological Needs in Motivation, Development, and Wellness
Year: 2017

I.  An Introduction and Overview II. Philosophical and Historical Considerations 2.  Historical Perspectives on Development and Integration in Living Entities 3. Human Autonomy: Philosophical Perspectives and the Phenomenology of Self 4.  Varied Concepts and a Preliminary Description of Self Determination Theory's Approach 5. A Brief History of Intrinsic Motivation III. The Six Mini Theories of Self Determination Theory 6. Cognitive  Theory, Part I: The Effects of Rewards, Feedback, and Other External Events on Intrinsic Motivation 7. Cognitive  Theory, Part II: Interpersonal and Intrapersonal Processes Affecting Intrinsic Motivation 8. Organismic Integration Theory: Internalization and the Differentiation of Extrinsic Motivation 9. Causality  Individual Differences in, and Priming of, Motivational Orientations 10. Basic Psychological Needs Theory: Satisfaction and Frustration of Autonomy, Competence, and Relatedness in Relation to Psychological Wellness and Illness 11. Goal Contents Theory: Aspirations, Life Goals, and Their Varied Consequences 12.  The Self in Close Relationships IV. Motivation and Human Development in Families, Schools, and Societies 13. Parenting and the Facilitation of Autonomy and Well Being in Development 14. Schools as Contexts for Learning and Social Development 15. Identity Development, Self Esteem, and Authenticity 16. Development, Psychological Needs, and Psychopathology V. The Application and Practice of Self Determination Theory in Multiple Domains 17.  Supporting Maintained Health Behavior Change 19. Sport, Physical Activity, and Physical Education 20. Motivation and Need Satisfaction in Video Games and Virtual Environments 21.  Promoting Wellness and Productivity VI. Basic Psychological Needs in Pervasive Social Contexts 22. Pervasive Social Influences, Part I: Cultural Contexts 23. Pervasive Social Influences, Part II: Economic and Political Systems 24. On Basic Needs and Human Natures: Altruism, Aggression, and the Bright and Dark Sides of Human Motivation A Very Brief Epilogue References Author Index Subject Index
End to End Non Autoregressive Neural Machine Translation with Connectionist Temporal Classification
Venue: EMNLP
Year: 2018

Autoregressive decoding is the only part of sequence to sequence models that prevents them from massive parallelization at inference time. Non autoregressive models enable the decoder to generate all output symbols independently in parallel. We present a novel non autoregressive architecture based on connectionist temporal classification and evaluate it on the task of neural machine translation. Unlike other non autoregressive methods which operate in several steps, our model can be trained end to end. We conduct experiments on the WMT English Romanian and English German datasets. Our models achieve a significant speedup over the autoregressive models, keeping the translation quality comparable to other non autoregressive models.