Urgent treatment for neoplasm consists of (1) cautious use of intravenous diuretics and (2) mediastinal irradiation, starting within 24 hours, with a treatment plan designed to give a high daily dose of radiation but a short total course of therapy to rapidly shrink the local tumor. Intensive radiation therapy combined with chemotherapy will palliate the process in up to 90% of patients. In patients with a subacute presentation, radiation therapy alone usually suffices. Chemotherapy is added if lymphoma or small-cell carcinoma is diagnosed

Because rbspy is a sampling profiler (not a tracing profiler), it actually can't tell you how times a function was called -- it just reports "hey, I observed your program 100,000 times, and 98,000 of those times it was in the calculate_thing function". ruby-prof is a tracing profiler for Ruby, which can tell you exactly how many times each function was called at the cost of being higher overhead.

All seem focused on rendering the 404 page manually. However, I wanted to make rescue_from work. My solution is the catch-all route and raising the exception manually.

Enterprise Knowledge Graphs are the next stage in theevolution of knowledge management systems.

Knowledge Graph Embedding: A Survey of Approaches and Applications

Knowledge graph (KG) embedding is to embed components of a KG including entities and relations into continuous vector spaces, so as to simplify the manipulation while preserving the inherent structure of the KG. It can benefit a variety of downstream tasks such as KG completion and relation extraction, and hence has quickly gained massive attention. In this article, we provide a systematic review of existing techniques, including not only the state-of-the-arts but also those with latest trends. Particularly, we make the review based on the type of information used in the embedding task. Techniques that conduct embedding using only facts observed in the KG are first introduced. We describe the overall framework, specific model design, typical training procedures, as well as pros and cons of such techniques. After that, we discuss techniques that further incorporate additional information besides facts. We focus specifically on the use of entity types, relation paths, textual descriptions, and logical rules. Finally, we briefly introduce how KG embedding can be applied to and benefit a wide variety of downstream tasks such as KG completion, relation extraction, question answering, and so forth.

But it is kind of verbose, and it’s also a lot slower, so I can understand why the model test might be preferred.

Those frameworks are used in a similar fashion, but conceptually use quite different approaches (Vue is a more traditional one, a library, and Svelte is a "dissapearing framework").

Depending on your needs, you can use the Simple Approach: Wrapping MDC Web Vanilla Components, or the Advanced Approach: Using Foundations and Adapters.

that a better and cleaner approach would be to use computed properties and a validation library that is decoupled for the UI (like hapi/joi).

Svelte chooses a reverse approach.

In contrast, React apps shun templates and require the developer to create their DOM in Javascript, typically aided with JSX.

While Webpack is focused on using CommonJS as its primary module system and converting everything to that, Rollup decided to take the opposite approach — focusing on ES Modules instead.

The neats: logic and symbolic reasoning[edit source] Logic was introduced into AI research as early as 1958, by John McCarthy in his Advice Taker proposal.[100] In 1963, J. Alan Robinson had discovered a simple method to implement deduction on computers, the resolution and unification algorithm. However, straightforward implementations, like those attempted by McCarthy and his students in the late 1960s, were especially intractable: the programs required astronomical numbers of steps to prove simple theorems.[101] A more fruitful approach to logic was developed in the 1970s by Robert Kowalski at the University of Edinburgh, and soon this led to the collaboration with French researchers Alain Colmerauer and Philippe Roussel who created the successful logic programming language Prolog.[102] Prolog uses a subset of logic (Horn clauses, closely related to "rules" and "production rules") that permit tractable computation. Rules would continue to be influential, providing a foundation for Edward Feigenbaum's expert systems and the continuing work by Allen Newell and Herbert A. Simon that would lead to Soar and their unified theories of cognition.[103] Critics of the logical approach noted, as Dreyfus had, that human beings rarely used logic when they solved problems. Experiments by psychologists like Peter Wason, Eleanor Rosch, Amos Tversky, Daniel Kahneman and others provided proof.[104] McCarthy responded that what people do is irrelevant. He argued that what is really needed are machines that can solve problems—not machines that think as people do.[105] The scruffies: frames and scripts[edit source] Among the critics of McCarthy's approach were his colleagues across the country at MIT. Marvin Minsky, Seymour Papert and Roger Schank were trying to solve problems like "story understanding" and "object recognition" that required a machine to think like a person. In order to use ordinary concepts like "chair" or "restaurant" they had to make all the same illogical assumptions that people normally made. Unfortunately, imprecise concepts like these are hard to represent in logic. Gerald Sussman observed that "using precise language to describe essentially imprecise concepts doesn't make them any more precise."[106] Schank described their "anti-logic" approaches as "scruffy", as opposed to the "neat" paradigms used by McCarthy, Kowalski, Feigenbaum, Newell and Simon.[107] In 1975, in a seminal paper, Minsky noted that many of his fellow "scruffy" researchers were using the same kind of tool: a framework that captures all our common sense assumptions about something. For example, if we use the concept of a bird, there is a constellation of facts that immediately come to mind: we might assume that it flies, eats worms and so on. We know these facts are not always true and that deductions using these facts will not be "logical", but these structured sets of assumptions are part of the context of everything we say and think. He called these structures "frames". Schank used a version of frames he called "scripts" to successfully answer questions about short stories in English.[108] Many years later object-oriented programming would adopt the essential idea of "inheritance" from AI research on frames.

Her words reveal the conflict between allegiance to hercultural background and her adopted culture.

Trying new approaches is a strategy in which some womenbegan to understand and interact within their worlds insomewhat different ways, taking advantage of new optionsthat became apparent.

Teaching More by Grading Less (or Differently)

Hispanic culture