Massachusetts Institute of Technology

About: Massachusetts Institute of Technology is a education organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Population & Laser. The organization has 116795 authors who have published 268000 publications receiving 18272025 citations. The organization is also known as: MIT & M.I.T..

Coherency strain and the kinetics of phase separation in LiFePO4 nanoparticles.

Abstract: A theoretical investigation of the effects of elastic coherency strain on the thermodynamics, kinetics, and morphology of intercalation in single LiFePO4 nanoparticles yields new insights into this important battery material. Anisotropic elastic stiffness and misfit strains lead to the unexpected prediction that low-energy phase boundaries occur along {101} planes, while conflicting reports of phase boundary orientations are resolved by a partial loss of coherency in the [001] direction. Elastic relaxation near surfaces leads to the formation of a striped morphology with a characteristic length scale predicted by the model, yielding an estimate of the interfacial energy. The effects of coherency strain on solubility and galvanostatic discharge are studied with a reaction-limited phase-field model that quantitatively captures the influence of misfit strain, particle size, and temperature on solubility seen in experiments. Coherency strain strongly suppresses phase separation during discharge, which enhance...

Traffic grooming in WDM networks

Abstract: The emergence of wavelength-division multiplexing technology has led to a tremendous increase In the available transmission capacity in wide area networks. Consequently, these networks may no longer be limited by the transmission bandwidth, but rather by the processing capability of electronic switches, routers, and multiplexers in the network. This realization has led to a new wave of research aimed at overcoming the electronic bottleneck by providing optical bypass at the WDM layer. Traffic grooming can be used as a bypass mechanism by which low-rate circuits are assigned to wavelengths in order to minimize the amount of electronic multiplexing equipment. This topic has received a significant amount of attention in both the research and commercial arenas. We give an overview of the traffic grooming problem and survey some representative work in this area. While most work has focused on grooming in SONET rings, grooming traffic in general mesh networks is an important emerging problem.

Postnatal Neurogenesis in the Guinea-pig

Abstract: The young of rats and mice are immature at birth. After birth, their brains grow in size and there is also a marked proliferation of cells which become differentiated into neurones with short axons (micro-neurones). The proliferation of similar cells has now been demonstrated in the hippocampus of postnatal guinea-pigs even though these rodents are born with nearly full-size brains.

Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying

Abstract: Cyberbullying (harassment on social networks) is widely recognized as a serious social problem, especially for adolescents. It is as much a threat to the viability of online social networks for youth today as spam once was to email in the early days of the Internet. Current work to tackle this problem has involved social and psychological studies on its prevalence as well as its negative effects on adolescents. While true solutions rest on teaching youth to have healthy personal relationships, few have considered innovative design of social network software as a tool for mitigating this problem. Mitigating cyberbullying involves two key components: robust techniques for effective detection and reflective user interfaces that encourage users to reflect upon their behavior and their choices.Spam filters have been successful by applying statistical approaches like Bayesian networks and hidden Markov models. They can, like Google’s GMail, aggregate human spam judgments because spam is sent nearly identically to many people. Bullying is more personalized, varied, and contextual. In this work, we present an approach for bullying detection based on state-of-the-art natural language processing and a common sense knowledge base, which permits recognition over a broad spectrum of topics in everyday life. We analyze a more narrow range of particular subject matter associated with bullying (e.g. appearance, intelligence, racial and ethnic slurs, social acceptance, and rejection), and construct BullySpace, a common sense knowledge base that encodes particular knowledge about bullying situations. We then perform joint reasoning with common sense knowledge about a wide range of everyday life topics. We analyze messages using our novel AnalogySpace common sense reasoning technique. We also take into account social network analysis and other factors. We evaluate the model on real-world instances that have been reported by users on Formspring, a social networking website that is popular with teenagers.On the intervention side, we explore a set of reflective user-interaction paradigms with the goal of promoting empathy among social network participants. We propose an “air traffic control”-like dashboard, which alerts moderators to large-scale outbreaks that appear to be escalating or spreading and helps them prioritize the current deluge of user complaints. For potential victims, we provide educational material that informs them about how to cope with the situation, and connects them with emotional support from others. A user evaluation shows that in-context, targeted, and dynamic help during cyberbullying situations fosters end-user reflection that promotes better coping strategies.