The Library\u27s Bassin Collection

In May 1973, York College President Milton G. Bassin donated 495 volumes to the York College Library, most of which were written in either Hebrew or Yiddish, with some also in Aramaic. The books belonged to his father, Max Bassin (who was sometimes referred to as Morris, Moses, or Moshe), who was a noted anthologist of Yiddish poetry

In search of hair damage using metabolomics?

YesHair fibres are extraordinary materials, not least because they are exquisitely formed by each of the 5 million or so hair follicles on our bodies and have functions that cross from physiology to psychology, but also because they have well known resistance to degradation as seen in hair surviving from archaeological and historical samples [1]. Hair fibres on the head grow at around 1cm each month, together totalling approximately 12km of growth per person per year. Each fibre is incredibly strong for its small diameter; with one fibre typically holding 100g and together a well-formed ponytail [allegedly] has the collective strength to support the weight of a small elephant! Hair – and from here I mean scalp hair – is under constant scrutiny by each of us; whether it be style, split ends, the first few grey hairs or the collection of hairs in the shower that should be firmly attached - leading to the fear that is hair loss

Pass plays and right-handed gloves: revising American sporting terms in OED3

The start of the online publication of OED3 almost exactly coincided with the establishment of an OED editorial office in America, so that editorial work on North American terms could be handled by native speakers. Much of this work was of an expected sort: drafting new words that derived from, say, rap music; pointing out differing American nuances in existing entries; or revising usage notes or metalanguage for terms not used, or used quite differently, in one variety of English.However, it soon became clear that there were additional and unexpected subtleties. The defining language of the OED is British English, and all definitions must be understandable to speakers of any regional variety. However, many words depend on a background cultural knowledge that cannot easily be expressed in a dictionary definition, at least not without rendering the definition almost absurdly overspecific to speakers already familiar with this knowledge.In this paper I will look specifically at sporting terms, which provide an excellent subject for such concerns. The definitions of many baseball and American football terms in OED2 were not strong, though in many cases it turned out that this was not due to erroneous treatment on the part of the original editors, but because the concepts involved were so foreign to British speakers that there was no straightforward way to explain them. Conversely, when the North American office began to draft entries for American sporting terms, the definitions were often sent back with comments indicating that an apparently unavoidable term in the definition was completely impenetrable to British speakers. I will show various examples from the OED's revision process, explaining the complications they raised, how we dealt with them, and how such examples illustrate the broader kind of issues that the OED regularly deals with during the revision process.</p

Modifying RL Policies with Imagined Actions: How Predictable Policies Can Enable Users to Perform Novel Tasks

It is crucial that users are empowered to use the functionalities of a robot to creatively solve problems on the fly. A user who has access to a Reinforcement Learning (RL) based robot may want to use the robot's autonomy and their knowledge of its behavior to complete new tasks. One way is for the user to take control of some of the robot's action space through teleoperation while the RL policy simultaneously controls the rest. However, an out-of-the-box RL policy may not readily facilitate this. For example, a user's control may bring the robot into a failure state from the policy's perspective, causing it to act in a way the user is not familiar with, hindering the success of the user's desired task. In this work, we formalize this problem and present Imaginary Out-of-Distribution Actions, IODA, an initial algorithm for addressing that problem and empowering user's to leverage their expectation of a robot's behavior to accomplish new tasks