Generation of simple extended porous surface expression from results of pore-level conjugate heat transfer in spherical-void-phase porous blocks

Studies of convection in porous media continue to be of scientific interest due to the increasing utility of highly-conductive porous materials in heat exchange applications. Of central interest is the ability to model flow and heat transfer through a porous material with high accuracy in a manner that is computationally inexpensive. To this end, use of thermal-equilibrium (TE) or non-thermal-equilibrium (NTE) volume–averaged techniques are of great interest, but use of such methods requires information that is averaged out to be supplied as model coefficients for simple constitutive models that characterize the physical processes. Such models and coefficients are typically derived from either experiments or calculations of pore-level activity in idealized porous materials. Please download the full abstract below

A lexical database for public textual cyberbullying detection

Public textual cyberbullying has become one of the most prevalent issues associated with online safety of young people, particularly on social networks. To address this issue, we argue that the boundaries of what constitutes public textual cyberbullying needs to be first identified and a corresponding linguistically motivated definition needs to be advanced. Thus, we propose a definition of public textual cyberbullying that contains three necessary and sufficient elements: the personal marker, the dysphemistic element and the cyberbullying link between the previous two elements. Subsequently, we argue that one of the cornerstones in the overall process of mitigating the effects of cyberbullying is the design of a cyberbullying lexical database that specifies what linguistic and cyberbullying specific information is relevant to the detection process. In this vein, we propose a novel cyberbullying lexical database based on the definition of public textual cyberbullying. The overall architecture of our cyberbullying lexical database is determined semantically, and, in order to facilitate cyberbullying detection, the lexical entry encapsulates two new semantic dimensions that are derived from our definition: cyberbullying function and cyberbullying referential domain. In addition, the lexical entry encapsulates other semantic and syntactic information, such as sense and syntactic category, information that, not only aids the process of detection, but also allows us to expand the cyberbullying database using WordNet (Miller, 1993)

Autonomous Planetary Rover Final Project Report

This report documents the 2022-2023 Autonomous Planetary Rover Team’s work. The main focus and goal of our team was to improve the locomotion of the rover through mechanical improvements to the suspension and steering systems. The final expectation for the rover given by our sponsor, Dr. Kevin Nickels, was for the rover to complete an obstacle course where it drives over obstacles the height of the radius of its wheel, traverses uneven terrain, and completes turns with a 12-inch turn radius. The main inspirations for our design of the suspension and steering systems come from previous planetary rovers that have completed missions on Mars and the Moon, specifically Curiosity and Sojourner. We have done substantial research on the mechanics of the rocker-bogie suspension system and have chosen this as our method of robust suspension. We also researched different methods of steering and settled on an independent steering system. In terms of primary subsystems, we have focused on suspension and steering, though we will also discuss design choices related to the chassis material and electronic components. This project has been evolving and changing for multiple iterations—four previous teams have worked on the rover, each team focusing on different aspects of improvement. Our team is focusing on improving the mechanical aspects of the rover while making use of previous teams’ additions to the project, but will not focus on any systems related to the autonomous navigation of the rover. This year, the design problem was to mechanically improve the rover so that it was capable of going around and over obstacles in a simple obstacle course. Requirements of the design also included the Rover’s ability to carry a 100-pound load (to simulate experimental equipment) and to traverse over obstacles as tall as 5.1 inches (the radius of the wheels). These design requirements fed into project-specific requirements from our sponsor, which included having a rocker-bogie suspension system and independent steering. Another requirement was the capability of the rover to pass through a standard door frame in Trinity University’s CSI Building. These requirements reflect constraints of real planetary rover design, and will force us to consider environmental factors on the design. In this document, we will discuss all conducted tests and to what extent these tests showed that our prototype fulfilled each requirement. Though individual design components of the rover proved to be successful, the overall prototype was unable to complete the required obstacle course due to issues with stability. The clearance, dimensions, and obstacle construction requirements were successful based on testing, and are important for the next steps of the rover. Some tests showed partial achievement of requirements, which demonstrate that the rover has been improved this year and is on the right track. The team concludes that the suspension system design is a partial success, as similar to the steering system design, because it functioned as expected though not integrated perfectly. The rover was able to be controlled by a joystick, and was capable of making wide turns - showing success for the desired independent steering design. The rover’s ability to overcome obstacles was also deemed a partial success, as though it could statically handle being on top of an obstacle without tipping excessively, it was difficult for it to dynamically climb the obstacle. The team believes that each subsystem of the rover prototype shows promise, and look forward to seeing future iterations

Detecting Discourse-Independent Negated Forms of Public Textual Cyberbullying

[EN] Cyberbullying is a risk associated with the online safety of young people and, in this paper, we address one of its most common implicit forms – negation-based forms. We first describe the role of negation in public textual cyberbullying interaction and identify the cyberbullying constructions that characterise these forms. We then formulate the overall detection mechanism which captures the three necessary and sufficient elements of public textual cyberbullying – the personal marker, the dysphemistic element, and the link between them. Finally, we design rules to detect both overt and covert negation-based forms, and measure their effectiveness using a development dataset, as well as a novel test dataset, across several metrics: accuracy, precision, recall, and the F1-measure. The results indicate that the rules we designed closely resemble the performance of human annotators across all measures.Power, A.; Keane, A.; Nolan, B.; O'neill, B. (2018). Detecting Discourse-Independent Negated Forms of Public Textual Cyberbullying. Journal of Computer-Assisted Linguistic Research. 2(1):1-20. doi:10.4995/jclr.2018.891712021Al-garadi, M.A., Varathan, K.D. and Ravana S.D. 2016. "Cybercrime Detection in Online Communications: The Experimental Case of Cyberbullying Detection in the Twitter Network." Computers in Human Behaviour, 63: 433 - 443. https://doi.org/10.1016/j.chb.2016.05.051Allan, K. and Burridge, K. 2006. Forbidden Words: Taboo and Censoring of Language. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9780511617881Boyd, D. 2007. "Why Youth (Heart) Social Network Sites: The Role of Networked Publics in Teenage Social Life." In MacArthur Foundation Series on Digital Learning, Youth, Identity, and Digital Media, edited by David Buckingham, 1 - 26. Cambridge, MA: MIT Press.Chatzakou, D., Kourtellis, N., Blackburn, J., De Cristofaro, E., Stringhini, G., and Vakali, A. 2017. "Mean Birds: Detecting Aggression and Bullying on Twitter." Cornell University Library: https://arxiv.org/abs/1702.06877.Chen, Y., Zhou, Y., Zhu, S. and Xu, H. 2012. "Detecting Offensive Language in Social Media to Protect Adolescent Online Safety." Paper presented at the ASE/IEEE International Conference on Social Computing, 71 - 80. Washington, DC, September 3-5. https://doi.org/10.1109/SocialCom-PASSAT.2012.55Dadvar, M., Trieschnigg, D., R. Ordelman, R., and de Jong, F. 2013. "Improving cyberbullying detection with user context." Paper presented at the 35th European conference on Advances in Information Retrieval, 693 - 696. Moscow, March 24-27. https://doi.org/10.1007/978-3-642-36973-5_62de Marneffe, M.C., and Manning, C.D. 2008a. "The Stanford typed dependencies representation." Paper presented at the COLING 2008 Workshop on Cross-framework and Cross-domain Parser Evaluation. Manchester, UK August 23 - 23. https://doi.org/10.3115/1608858.1608859de Marneffe, M.C., and Manning, C. 2008b. "Stanford typed dependencies manual." https://nlp.stanford.edu/software/dependencies_manual.pdf.Dinakar, K., Jones, B., Havasi, C., Lieberman, H., and Picard, R. 2012. "Common sense reasoning for detection, prevention, and mitigation of cyberbullying." ACM Transactions on Interactive Intelligent Systems, 2: 18:1-18:30. https://doi.org/10.1145/2362394.2362400Dooley, J.J., Pyzalski, J., and Cross, D. 2009. "Cyberbullying versus face-to-face bullying - A theoretical and conceptual review." Journal of Psychology, 217: 182-188. https://doi.org/10.1027/0044-3409.217.4.182Goncalves, M. 2011. "Text Classification". In Modern Information Retrieval, the concepts and technology behind search, edited by Ricardo Baeza-Yates and Berthier Ribeiro-Neto, 281 - 336. Pearson Education Limited.Grigg, D.W. 2010. "Cyber-Aggression: Definition and Concept of Cyberbullying." Australian Journal of Guidance and Counselling, 12: 143-156. https://doi.org/10.1375/ajgc.20.2.143Hinduja, S., and Patchin, J.W. 2009. Bullying beyond the schoolyard: preventing and responding to cyber-bullying. Thousand Oaks, CA: Corw2017.Horn, L. R. 1989. A Natural History of Negation. Chicago: University of Chicago Press.Hosseinmardi, H., Han, R., Lv, Q., Mishra, S., and Ghasemianlangroodi, A. 2014a. "Towards Understanding Cyberbullying Behavior in a Semi-Anonymous Social Network." Paper presented at the International Conference on Advances in Social Networks Analysis and Mining. Beijing, August 17-20. https://doi.org/10.1109/ASONAM.2014.6921591Hosseinmardi, H., Rafiq, R. I., Li, S., Yang, Z., Han, R., Lv, Q., and Mishra, S. 2014b. "A Comparison of Common Users across Instagram and Ask.fm to Better Understand Cyberbullying." Paper presented at the 7th International Conference on Social Computing and Networking. Sydney, December 3-5.Huang, Q., Singh, V.K., and Atrey, P.K. 2014. "Cyber Bullying Detection using Social and Textual Analysis." Paper presented at the 3rd International Workshop on Socially-Aware Multimedia, 3 - 6. Orlando, Florida, November 7. https://doi.org/10.1145/2661126.2661133InternetSlang. 2017. "Internet Slang - Internet Dictionary." Accessed October 19. http://www.Internetslang.com/.Kavanagh, P. 2014. "Investigation of Cyberbullying Language & Methods." MSc diss., ITB, Ireland.Kontostathis, A., Reynolds, K., Garron, A. and Edwards, L. 2013. Detecting Cyberbullying: Query Terms and Techniques. Paper presented at the 5th Annual ACM Web Science Conference. Paris, May 2-4. https://doi.org/10.1145/2464464.2464499Langos, C. 2012. "Cyberbullying: The Challenge to Define." Cyberpsychology, Behavior, and Social Networks, 15(6): 285-289. https://doi.org/10.1089/cyber.2011.0588Lawler, J. 2005. "Negation and NPIs." http://www.umich.edu/~jlawler/NPIs.pdfLivingstone, S.,Haddon, L., Görzig, A., and Ólafsson, K. 2011. "EU Kids Online: final report 2011." http://eprints.lse.ac.uk/45490/1/EU%20Kids%20Online%20final%20report%202011%28lsero%29.pdf.Livingstone, S., Mascheroni, G., Ólafsson, K., and Haddon, L. with the networks of EU Kids Online and Net Children Go Mobile. 2014. "Children's online risks and opportunities: Comparative findings from EU Kids Online and Net Children Go Mobile". http://eprints.lse.ac.uk/60513/1/__lse.ac.uk_storage_LIBRARY_Secondary_libfile_shared_repository_Content_EU%20Kids%20Online_EU%20Kids%20Online-Children%27s%20online%20risks_2014.pdf.Nahar, V., Li, X. and Pang, C. 2013. "An Effective Approach for Cyberbullying Detection." Communications in Information Science and Management Engineering, 3:238 - 247.Nandhini, B.S., and Sheeba, J.I. 2015. "Online Social Network Bullying Detection Using Intelligence Techniques." Procedia Computer Science, 45: 485 - 492. https://doi.org/10.1016/j.procs.2015.03.085Navarro, G. and Ziviani, N. 2011. "Documents: Languages & Properties". In Modern Information Retrieval, the concepts and technology behind search, edited by Ricardo Baeza-Yates and Berthier Ribeiro-Neto, 203 - 254. Pearson Education Limited.Nitta, T., Masui, F., Ptaszynski, M., Kimura, Y., Rzepka, R., and Araki, K. 2013. "Detecting Cyberbullying Entries on Informal School Websites Based on Category Relevance Maximization." Paper presented at the 6th International Joint Conference on Natural LanguageProcessing. Nagoya, October 14-19.Norvig, P. 2007. "How to Write a Spelling Corrector." Accessed October 19. http://norvig.com/spell-correct.html.Oracle. 2017. Java™ Platform, Standard Edition 9 API Specification. Accessed October 19. https://docs.oracle.com/javase/9/docs/api/index.html?overview-summary.html.Power, A., Keane, A., Nolan, B., and O'Neill, B. 2017. "A Lexical Database for Public Textual Cyberbullying Detection". Special issue of Revista de lenguas para fines específicos, entitled New Insights into Meaning Construction and Knowledge Representation.Ptaszynski, M., Dybala, P., Matsuba, T., Rzepka, R. and Araki, K. 2010. "Machine Learning and Affect Analysis Against Cyber-Bullying." Paper presented at the 36th AISB Annual Convention. March 29- April 1.Ptaszynski, M., Masui, F., Nitta, T., Hatekeyama, S., Kimura, Y., Rzepka, R., and Araki, K. 2016. "Sustainable Cyberbullying Detection with Category-Maximised Relevance of Harmful Phrases and Double-Filtered Automatic Optimisation." International Journal of Child-Computer Interaction, 8: 15 - 30. https://doi.org/10.1016/j.ijcci.2016.07.002Reynolds, K., Kontostathis, A. and Edwards, L. 2011. "Using Machine Learning to Detect Cyberbullying." Paper presented at the 10th International Conference on Machine Learning and Applications Workshops. Hawaii, December 18-21. https://doi.org/10.1109/ICMLA.2011.152Sourander, A., Brunstein-Klomek, A., Ikonen, M., Lindroos, J., Luntamo, T., Koskelainen, M., Ristkari, T., Hans Helenius, H. 2010. "Psychosocial risk factors associated with cyberbullying among adolescents: A population-based study." Arch Gen Psychiatry, 67: 720-728. https://doi.org/10.1001/archgenpsychiatry.2010.79Unicode. 2017. "Emoticons." Accessed October 19. http://www.unicode.org/.Van Hee, C., Lefever, E.,Verhoeven, B.,Mennes, J.,Desmet, B., DePauw, G., Daelemans, W., and Hoste, V. 2015. "Detection and Fine-GrainedClassificationofCyberbullyingEvents." Paper presented at the annual conference on RANLP. Hissar, September 5-11.Witten, I.H., Frank, E., and Hall, M.A. 2011. Data Mining: Practical Machine Learning Tools and Techniques (3rd edition). Elsevier Inc., USA.Yin, D., Xue, Z., Hong, L., Davison, B.D., Kontostathis, A., and Edwards, L. 2009. "Detection of harassment on web 2.0." Paper presented at the 1st conference on CAW. Madrid, April 20-24

A case of Klinefelter syndrome with hypersexual desire

Klinefelter syndrome (KS) is a chromosomal disorder affecting males, with the typical karyotype of 47, XXY due to a supernumerary X chromosome, which causes progressive testicular failure resulting in androgen deficiency and infertility. Despite it being the most common sex chromosomal disorder, its diagnosis is easily missed. In addition to its classical clinical features of tall stature, gynaecomastia, small testes, and symptoms and signs of hypogonadism including infertility, KS is also often associated with neurocognitive, behavioural and psychiatric disorders. We present a 44-year-old man with KS who, despite having erectile dysfunction, paradoxically had increased libido. He used sildenafil to overcome his erectile dysfunction. Hypersexuality was manifested by very frequent masturbation, multiple sexual partners most of whom were casual, and a sexual offence conviction at the age of 17 years. Discussion focuses on the frequent failure of clinicians to diagnose KS, the neurocognitive, behavioural and psychiatric aspects of KS, this unusual presentation of hypersexuality in a man with KS, and the challenges of medical management of hypogonadism in a man with a history of a sexual offence

Emergency Department Operations in Top-Performing Safety-Net Hospitals

This report profiles five safety-net hospitals—Boston Medical Center, Denver Health, Memorial Regional Hospital, Memorial Hospital West, and Virginia Commonwealth University Health System—that made improvements to curb emergency department (ED) crowding, reduce long waits, and lower the number of hours spent on ambulance diversion. Hospitals used a combination of interventions, including: reconfiguring the ED to maximize efficiency; devising a pre-diversion system to alert staff of ED crowding; installing an electronic tracking system; designating staff members to be responsible for tracking patients; and developing meaningful performance metrics. To be successful, such interventions need to take place within a broader improvement strategy that entails: recognition that ED crowding is a hospital-wide issue; leadership provided by the CEO and other senior staff; vigilance in pursuing change, reviewing outcomes, and working to improve; transparency; and a commitment to quality for safety-net populations