One Test to Rule Them All: Retiring the Dual Standard for Fictional Character Copyrightability in the Ninth Circuit

(Excerpt) From Captain Jack Sparrow sailing on the Black Pearl in Pirates of Caribbean to Frodo Baggins trekking through Mordor in Lord of the Rings, well-developed characters are vital to the success of a story. Iconic characters like Captain Jack and Frodo Baggins have each developed a cult following as a result of their interesting storylines and character development. The instant recognition and nostalgia associated with such iconic characters has motivated companies to monetize their likenesses. Whether it is car companies recreating the Batmobile or the recent trend in creating story-based pop-up shops, there is a lot of value in asserting ownership over fictional characters. Since characters, like stories, are products of ideas, they are considered intangible property and are thus governed by intellectual property law, specifically copyright. Given the potential for financial gain, there has been much dispute over the copyrightability of fictional characters. While it is relatively straightforward to assert ownership over a film, television show, or novel under copyright law, it is more difficult to assert ownership over a character. Various circuit courts have taken different approaches to defining the scope of copyright protection for fictional characters. For example, the Ninth and Second Circuits, two of the most influential circuits for copyright law, employ slightly different approaches

A Galois connection between classical and intuitionistic logics. II: Semantics

Three classes of models of QHC, the joint logic of problems and propositions, are constructed, including a class of subset/sheaf-valued models that is related to solutions of some actual problems (such as solutions of algebraic equations) and combines the familiar Leibniz-Euler-Venn semantics of classical logic with a BHK-type semantics of intuitionistic logic. To test the models, we consider a number of principles and rules, which empirically appear to cover all "sufficiently simple" natural conjectures about the behaviour of the operators ! and ?, and include two hypotheses put forward by Hilbert and Kolmogorov, as formalized in the language of QHC. Each of these turns out to be either derivable in QHC or equivalent to one of only 13 principles and 1 rule, of which 10 principles and 1 rule are conservative over classical and intuitionistic logics. The three classes of models together suffice to confirm the independence of these 10 principles and 1 rule, and to determine the full lattice of implications between them, apart from one potential implication.Comment: 35 pages. v4: Section 4.6 "Summary" is added at the end of the paper. v3: Major revision of a half of v2. The results are improved and rewritten in terms of the meta-logic. The other half of v2 (Euclid's Elements as a theory over QHC) is expected to make part III after a revisio

Comparative analysis of diagnostic performance, feasibility and cost of different test-methods for thyroid nodules with indeterminate cytology

Since it is impossible to recognize malignancy at fine needle aspiration (FNA) cytology in indeterminate thyroid nodules, surgery is recommended for all of them. However, cancer rate at final histology is < 30%. Many different test-methods have been proposed to increase diagnostic accuracy in such lesions, including Galectin-3-ICC (GAL-3-ICC), BRAF mutation analysis (BRAF), Gene Expression Classifier (GEC) alone and GEC+BRAF, mutation/fusion (M/F) panel, alone, M/F panel+miRNA GEC, and M/F panel by next generation sequencing (NGS), FDG-PET/CT, MIBI-Scan and TSHR mRNA blood assay. We performed systematic reviews and meta-analyses to compare their features, feasibility, diagnostic performance and cost. GEC, GEC+BRAF, M/F panel+miRNA GEC and M/F panel by NGS were the best in ruling-out malignancy (sensitivity = 90%, 89%, 89% and 90% respectively). BRAF and M/F panel alone and by NGS were the best in ruling-in malignancy (specificity = 100%, 93% and 93%). The M/F by NGS showed the highest accuracy (92%) and BRAF the highest diagnostic odds ratio (DOR) (247). GAL-3-ICC performed well as rule-out (sensitivity = 83%) and rule-in test (specificity = 85%), with good accuracy (84%) and high DOR (27) and is one of the cheapest (113 USD) and easiest one to be performed in different clinical settings. In conclusion, the more accurate molecular-based test-methods are still expensive and restricted to few, highly specialized and centralized laboratories. GAL-3-ICC, although limited by some false negatives, represents the most suitable screening test-method to be applied on a large-scale basis in the diagnostic algorithm of indeterminate thyroid lesions

From metalinguistic instruction to metalinguistic knowledge, and from metalinguistic knowledge to performance in error correction and oral production tasks

The purpose of this study is to analyse the effect of metalinguistic instruction on students' metalinguistic knowledge on the one hand, and on students' performance in metalinguistic and oral production tasks on the other hand. Two groups of primary school students learning English as a foreign language were chosen. One of them (Rule group) was provided with metalinguistic instruction on English possessive determiners (PDs) for six weeks (N= 21), while the Comparison group (N= 22) did not receive such instruction. These students' progress was analysed through a pre-test/post-test design by means of a written error correction task, a 'free production' oral task, and a metalinguistic judgement task. The results of the statistical analyses indicate that, although the learners in the Rule group were more advanced in their knowledge and use of the English PDs than their peers in the Comparison group, the differences between groups were not statistically significant in all the tests. Additional analyses revealed that there were correlations between students' knowledge and performance in the Rule group, indicating that the learners who made the most gains from pre- to post-test were the ones who had demonstrated a more advanced knowledge of the rule

Reasoning Competence

In the 1970s, various experiments were carried out on\ud ordinary people"s reasoning powers suggesting our natural\ud ability to reason does not match up to the normative\ud standards endorsed in logic and probability theory. The\ud two most famous of these have come to be termed the\ud selection experiment, and the conjunction experiment (or\ud Linda experiment). In the first, Peter Wason asked\ud subjects to test a rule for cards with numbers on one side\ud and letters on the other, such as "If the card has a vowel\ud on one side, it has an odd number on the other" (Wason\ud 1971). Wason"s basic finding was that very few subjects\ud selected the two cards that are necessary to test such a\ud rule, suggesting that they do not understand the logic of\ud conditionals (that they are false just if the antecedent is\ud true and the consequent false). In the second experiment,\ud Kahneman and Tversky told subjects a story about a\ud woman called Linda, and then gave them a list of\ud statements about Linda concerning what kind of occupation\ud she has and/or what she does in her free time, and\ud asked them to rank the statements from most to least\ud likely. Nearly all subjects ranked the statement Linda is a\ud bank teller and active in the feminist movement as more\ud likely than Linda is a bank teller, which contravenes a\ud fundamental theorem of statistics to the effect that the\ud probability of any single event A can never be lower than\ud the probability of both A and some other event B. (Cf.\ud Tversky & Kahneman 1983.

Standardized Testing

When we do standardized assessments um there’s one in particular that we use and when you follow like the standardized protocol you do every test item in order. Um and that’s the way you are expected to do the test protocol that’s the only way it’s standardized assessment but I have never met a therapist in my entire life who goes in that order. There’s def [Inaudible as speaker and collector say something at once.] There’s an unspoken rule between therapists that you do similar test items together. (Okay) So like um some of the test has um kids imitate block designs like building with little blocks. Um and you would never like you would never ask a kid to build a tower and then take the blocks away and then, give them uh beads to string and then take the beads away and then give them the blocks back and back and forth. So like every therapist gives them cause they’re like, the test is set up so it’s developmental. So they should be able to stack two blocks and then they should be able tooo uummm, gosh I don’t know the next item, but, but they don’t go. And then and then five items later then they should be able to stack five blocks. But I’m not gonna give a kid two blocks and be like “Stack it!” [said in tone as if to child]. Um you know I’m gonna give them all the blocks and see how high they can stack. (right) And then I’ll count all the test items they got correct. Um, or then there’s another one where you imitate a train so you put three blocks, down and then one on top. And so when the kid has the blocks I just ask them to do all of the block items. Um and then there’s writing items. So there’s that you know one item is drawing a vertical line and another item is drawing a horizontal line another one is drawing a circle um. And those test items are spread out throughout the assessment but I just give them all the writing together

Cointegration and Asset Allocation: A New Fund Strategy

Many recent papers have documented the existence of periodicities in returns, return volatility, bid-ask spreads and trading volume, in both equity and foreign exchange markets. In this paper, we propose and employ a new test for detecting subtle periodicities in financial markets based on a signal coherence function. The technique is applied to a set of seven half-hourly exchange rate series. Overall, we find the signal coherence to be maximal at the 8 hour and 12 hour frequencies. Retaining only the most coherent frequencies for each series, we implement a trading rule based on these observed periodicities. Our results demonstrate in all cases except one that, in gross terms, the rules are able to generate returns considerably greater than those of a buy-and-hold strategy. We conjecture that this methodology could constitute an important tool for market microstructure researchers, which will enable them to better detect, quantify and rank the various periodic components in financial data.Hedge Fund, Cointegration, Equity, Market Neutral

Differentiating Legislative from Nonlegislative Rules: An Empirical and Qualitative Analysis

The elusive distinction between legislative rules and nonlegislative rules has frustrated courts, motivated voluminous scholarly debate, and ushered in a flood of litigation against administrative agencies. In the absence of U.S. Supreme Court guidance on the proper demarcating line, circuit courts have adopted various tests to ascertain a rule’s proper classification. This Note analyzes all 241 cases in which a circuit court has used one or more of the enunciated tests to differentiate legislative from nonlegislative rules. These opinions come from every one of the thirteen circuits and span the period of the early 1950s through 2018. This Note identifies six different tests that courts have employed in this effort and offers a qualitative and empirical analysis of each. The qualitative analysis explains the underlying premise of the tests, articulates their merits and shortcomings, and considers how courts have applied them to particular disputes. The empirical portion of this Note uses regression analysis to ascertain how using or rejecting one or more of the tests affects a court’s determination of whether the rule is legislative or nonlegislative. This Note classifies the different tests into two categories: public-focused tests and agency-focused tests. These two categories are defined by a principle that permeates administrative law jurisprudence: achieving a proper balance between efficient agency rulemaking and maintaining a proper check against unconstrained agency action. These two categories thus defined, this Note proposes a balanced approach that incorporates elements of both categories to identify and refine the proper test

Pseudorandom sequence generation using binary cellular automata

Tezin basılısı İstanbul Şehir Üniversitesi Kütüphanesi'ndedir.Random numbers are an integral part of many applications from computer simulations, gaming, security protocols to the practices of applied mathematics and physics. As randomness plays more critical roles, cheap and fast generation methods are becoming a point of interest for both scientific and technological use. Cellular Automata (CA) is a class of functions which attracts attention mostly due to the potential it holds in modeling complex phenomena in nature along with its discreteness and simplicity. Several studies are available in the literature expressing its potentiality for generating randomness and presenting its advantages over commonly used random number generators. Most of the researches in the CA field focus on one-dimensional 3-input CA rules. In this study, we perform an exhaustive search over the set of 5-input CA to find out the rules with high randomness quality. As the measure of quality, the outcomes of NIST Statistical Test Suite are used. Since the set of 5-input CA rules is very large (including more than 4.2 billions of rules), they are eliminated by discarding poor-quality rules before testing. In the literature, generally entropy is used as the elimination criterion, but we preferred mutual information. The main motive behind that choice is to find out a metric for elimination which is directly computed on the truth table of the CA rule instead of the generated sequence. As the test results collected on 3- and 4-input CA indicate, all rules with very good statistical performance have zero mutual information. By exploiting this observation, we limit the set to be tested to the rules with zero mutual information. The reasons and consequences of this choice are discussed. In total, more than 248 millions of rules are tested. Among them, 120 rules show out- standing performance with all attempted neighborhood schemes. Along with these tests, one of them is subjected to a more detailed testing and test results are included. Keywords: Cellular Automata, Pseudorandom Number Generators, Randomness TestsContents Declaration of Authorship ii Abstract iii Öz iv Acknowledgments v List of Figures ix List of Tables x 1 Introduction 1 2 Random Number Sequences 4 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Theoretical Approaches to Randomness . . . . . . . . . . . . . . . . . . . 5 2.2.1 Information Theory . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.2.2 Complexity Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2.3 Computability Theory . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3 Random Number Generator Classification . . . . . . . . . . . . . . . . . . 7 2.3.1 Physical TRNGs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3.2 Non-Physical TRNGs . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3.3 Pseudorandom Number Generators . . . . . . . . . . . . . . . . . . 10 2.3.3.1 Generic Design of Pseudorandom Number Generators . . 10 2.3.3.2 Cryptographically Secure Pseudorandom Number Gener- ators . . . . . . . . . . . . . .11 2.3.4 Hybrid Random Number Generators . . . . . . . . . . . . . . . . . 13 2.4 A Comparison between True and Pseudo RNGs . . . . . . . . . . . . . . . 14 2.5 General Requirements on Random Number Sequences . . . . . . . . . . . 14 2.6 Evaluation Criteria of PRNGs . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.7 Statistical Test Suites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.8 NIST Test Suite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.8.1 Hypothetical Testing . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.8.2 Tests in NIST Test Suite . . . . . . . . . . . . . . . . . . . . . . . . 20 2.8.2.1 Frequency Test . . . . . . . . . . . . . . . . . . . . . . . . 20 2.8.2.2 Block Frequency Test . . . . . . . . . . . . . . . . . . . . 20 2.8.2.3 Runs Test . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.8.2.4 Longest Run of Ones in a Block . . . . . . . . . . . . . . 21 2.8.2.5 Binary Matrix Rank Test . . . . . . . . . . . . . . . . . . 21 2.8.2.6 Spectral Test . . . . . . . . . . . . . . . . . . . . . . . . . 22 2.8.2.7 Non-overlapping Template Matching Test . . . . . . . . . 22 2.8.2.8 Overlapping Template Matching Test . . . . . . . . . . . 22 2.8.2.9 Universal Statistical Test . . . . . . . . . . . . . . . . . . 23 2.8.2.10 Linear Complexity Test . . . . . . . . . . . . . . . . . . . 23 2.8.2.11 Serial Test . . . . . . . . . . . . . . . . . . . . . . . . . . 24 2.8.2.12 Approximate Entropy Test . . . . . . . . . . . . . . . . . 24 2.8.2.13 Cumulative Sums Test . . . . . . . . . . . . . . . . . . . . 24 2.8.2.14 Random Excursions Test . . . . . . . . . . . . . . . . . . 24 2.8.2.15 Random Excursions Variant Test . . . . . . . . . . . . . . 25 3 Cellular Automata 26 3.1 History of Cellular Automata . . . . . . . . . . . . . . . . . . . . . . . .26 3.1.1 von Neumann’s Work . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.1.2 Conway’s Life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.1.3 Wolfram’s Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.2 Cellular Automata and the Definitive Parameters . . . . . . . . . . . . . . 31 3.2.1 Lattice Geometry . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.2.2 Cell Content . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.3 Guiding Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.4 Neighborhood Scheme . . . . . . . . . . . . . . . . . . . . . . . . . 36 3.3 A Formal Definition of Cellular Automata . . . . . . . . . . . . . . . . . . 37 3.4 Elementary Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.5 Rule Families . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 3.6 Producing Randomness via Cellular Automata . . . . . . . . . . . . . . . 42 3.6.1 CA-Based PRNGs . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 3.6.2 Balancedness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.6.3 Mutual Information . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.6.4 Entropy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4 Test Results 47 4.1 Output of a Statistical Test . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.2 Testing Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 4.3 Interpretation of the Test Results . . . . . . . . . . . . . . . . . . . . . . . 49 4.3.1 Rate of success over all trials . . . . . . . . . . . . . . . . . . . . . 49 4.3.2 Distribution of P-values . . . . . . . . . . . . . . . . . . . . . . . . 50 4.4 Testing over a big space of functions . . . . . . . . . . . . . . . . . . . . . 50 4.5 Our Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.6 Results and Observations . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4.6.1 Change in State Width . . . . . . . . . . . . . . . . . . . . . . . . 53 4.6.2 Change in Neighborhood Scheme . . . . . . . . . . . . . . . . . . . 53 4.6.3 Entropy vs. Statistical Quality . . . . . . . . . . . . . . . . . . . . 58 4.6.4 Mutual Information vs. Statistical Quality . . . . . . . . . . . . . . 60 4.6.5 Entropy vs. Mutual Information . . . . . . . . . . . . . . . . . . . 62 4.6.6 Overall Test Results of 4- and 5-input CA . . . . . . . . . . . . . . 6 4.7 The simplest rule: 1435932310 . . . . . . . . . . . . . . . . . . . . . . . . . 68 5 Conclusion 74 A Test Results for Rule 30 and Rule 45 77 B 120 Rules with their Shortest Boolean Formulae 80 Bibliograph