Topically Driven Neural Language Model

Language models are typically applied at the sentence level, without access to the broader document context. We present a neural language model that incorporates document context in the form of a topic model-like architecture, thus providing a succinct representation of the broader document context outside of the current sentence. Experiments over a range of datasets demonstrate that our model outperforms a pure sentence-based model in terms of language model perplexity, and leads to topics that are potentially more coherent than those produced by a standard LDA topic model. Our model also has the ability to generate related sentences for a topic, providing another way to interpret topics.Comment: 11 pages, Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017) (to appear

A Law and Economics Critique of the Law Review System

The law review system prizes placement of articles in highlyranked journals, and the optimum method to ensure the best placement, which many scholars have intuited, is a saturation submission strategy of submitting articles to as many journals as possible. However, there has neither been an explanation as to what incentivizes this submission strategy nor any analysis as to what happens to scholars who cannot afford this strategy. This article uses a law and economics approach to study the incentive structures of the law review system, and identifies two features of the system that encourage saturation submission and punishes the poorly-resourced: (a) journals have no availability to accept all articles of equal quality; and (b) there is an insufficient match between acceptance and journal ranking. It demonstrates that the law review system behaves as a market, and is meritocratic only for those scholars who can afford to practice saturation submission. This article concludes with some thoughts about reforming the system

Patent Nationalism and the Case for a New U.S. Patent Working Requirement

A working requirement is a provision of intellectual property law that uses the threat of punishment to encourage holders to “work” their intellectual property. This Article examines the case for adding a working requirement to U.S. patent law. It explains that, given the current global trends in economic and technological development, a working requirement that increases the exposure of Americans to new technologies through the manufacture of inventions is necessary for the U.S. patent system to fulfill its constitutional purpose, specifically, “[t]o promote the Progress of Science and Useful Arts.” To that end, this Article analyzes elements of working requirements in foreign patent laws to identify specific features that should be incorporated within a new U.S. working requirement. It also addresses how to structure the working requirement to prevent potential abuse and presents a law and economics analysis as to how the requirement can be used to encourage manufacturing in the United States

The effect of typewriting vs. handwriting lecture notes on learning: a systematic review and meta-analysis.

This study is a systematic review and meta-analysis of studies examining the effect of note-taking modality during lecture, that is, taking notes by hand using pen and paper vs. taking notes using a keyboard and computer, on learning among secondary and postsecondary students. I begin with a review of the literature and theoretical introduction to the theories and terms used. From a theoretical standpoint, there are strong reasons to believe that taking notes by hand might offer recall benefits relative to taking notes using a computer and keyboard. At the same time, I point out that one problem, which I term the “fundamental problem of modality research”, is that when researchers randomly assign participants to a note-taking modality they are also, indirectly, assigning them to a note-taking style. Furthermore, most studies do not consider factors such as participant transcription capacity that might serve as theoretically important moderators. I then describe the methods used for the systematic review and meta-analysis. These included a robust literature search, double screening of all potentially eligible studies, and double coding of all eligible studies. The meta-analytic methods involved multilevel applications of standard meta-analytic methods. The systematic review resulted in identification of 33 eligible reports containing 42 independent samples and 88 effect sizes, all evaluating whether there are recall differences — almost always operationalized as scores on a quiz given after exposure to lecture material — between participants taking notes by handwriting vs. typewriting, that is, the modality effect. A statistically significant overall meta-analytic average was found g = +0.144 [0.023, 0.265], p = .021, benefiting handwriters over typewriters. This is a small effect; on average, in the typical study typewriters scored about 50% on the recall quiz. The effect size of g = +0.14 translates into an average percent correct of about 57% in the handwriting group. There is some evidence that providing participants with an opportunity to review their notes might substantially reduce the observed advantage for handwriters

Assessing AI output in legal decision-making with nearest neighbors

Artificial intelligence (“AI”) systems are widely used to assist or automate decision-making. Although there are general metrics for the performance of AI systems, there is, as yet, no well-established gauge to assess the quality of particular AI recommendations or decisions. This presents a serious problem in the emerging use of AI in legal applications because the legal system aims for good performance not only in the aggregate but also in individual cases. This Article presents the concept of using nearest neighbors to assess individual AI output. This nearest neighbor analysis has the benefit of being easy to understand and apply for judges, lawyers, and juries. In addition, it is fundamentally compatible with existing AI methodologies. This Article explains how the concept could be applied for probing AI output in a number of use cases, including civil discovery, risk prediction, and forensic comparison, while also presenting its limitations

Investigation in stability of eight synthetic piperazines in human whole blood under various storage conditions over time

Over the past decade, synthetic piperazines have been associated with multiple fatalities and was one of the top 25 identified drugs in 2011. While circumventing legislative controls and preventing the detection in standard drug tests, synthetic piperazine derivatives are encountered in forensic casework as “legal” alternatives to ecstasy (3,4-methylenedioxymethamphetamine). These chemically-produced compounds share very similar pharmacological and psychological effects with ecstasy which in turn has led to their popularity as “party pills”. The long-lasting duration of synthetic piperazines, especially when 1-benzylpiperazine (BZP) is mixed with 1-(3-trifluoromethylphenyl)-piperazine (TFMPP), has also made them desirable to drug users to receive enhanced hallucinogenic effects. Although most methods are optimized to accurately quantify the amount of drugs in biological specimens submitted for forensic toxicology testing, unforeseeable challenges may arise to complicate the analysis such as postmortem redistribution, enzymatic reactions, the presence of bacterial activities, chemical and matrix interferences as well as the lack of reference materials. Thus, the purpose of this research was to investigate the stability of synthetic piperazines in human whole blood under various storage conditions and time ranges. A total of eight synthetic piperazines were assessed on their degrees of degradation using a Shimadzu Ultra-Fast Liquid Chromatography (UFLC) with SCIEX 4000 Q-Trap Electrospray Ionization Tandem Mass Spectrometry in positive ionization mode. These analytes included: 1-benzylpiperazine (BZP), 1-(4-fluorobenzyl)-piperazine (FBZP), 1-(4-methylbenzyl)-piperazine (MBZP), 1-(4-methoxyphenyl)-piperazine (MeOPP), 1-(para-fluorophenyl)-piperazine (pFPP), 1-(3-chlorophenyl)-piperazine (mCPP), 2,3-dichlorophenylpiperazine (DCPP), and 1-(3-trifluoromethylphenyl)-piperazine (TFMPP). Individual unknown samples were prepared by spiking certified reference standards (Cayman Chemical, Ann Arbor, MI, U.S.A.) of each synthetic piperazine into certified drug-free human whole blood (UTAK Laboratories, Inc., Valencia, CA, U.S.A.) independently at 1000 ng/mL. To closely monitor the stability of each compound and potential drug-drug interactions, mixed samples consisted of all eight piperazines were also stored at room temperature (~20°C), 4°C and -20°C for one, three, six, nine and twelve months in dark sealed containers. Solid phase extraction (SPE) was performed to remove unwanted components prior to the injection into the LC system. Drug of Abuse (DAU) mixed-mode copolymeric columns (Clean Screen®, UCT Inc., Levittown, PA, U.S.A.) were utilized with a positive pressure manifold rack followed by evaporating to dryness with low heat at 65°C. All samples were then reconstituted with 250 µL of 50:50 mixture of methanol and 2mM ammonium formate buffer with 0.2% formic acid (Fisher Scientific, Waltham, MA, U.S.A.). Analysis was performed in triplicate using a reversed-phase column (Kinetex® F5, Phenomenex®, Torrance, CA, U.S.A.) with a binary gradient of a 2mM ammonium formate buffer with 0.2% formic acid and methanol with 0.1% formic acid. The total run time was 11.5 minutes including equilibration and the flow rate was 0.4 mL/min. Three internal standards including BZP-d7, mCPP-d8 and TFMPP-d4 (Cerilliant, Round Rock, TX, U.S.A) were used to generate calibration curves that were ranged from 20 ng/mL to 2000 ng/mL. Results revealed that BZP, MBZP and FBZP were more stable than phenyl piperazines over time under all storage conditions, in which MBZP was consistently more stable and still had more than 70% remaining after 12 months. Data showed a smaller degree of degradation when samples were kept frozen or refrigerated; whereas storing at room temperature should be avoided to ensure minimal degradation and detrimental impacts on stability of piperazine compounds. For crime laboratories that are facing backlog situations, case samples with synthetic piperazines should be kept frozen or refrigerated even for time period as short as 30 days or less. However, storing them for too long will clearly affect the quantitation accuracy because phenyl piperazines are more susceptible to degrade completely after six months regardless of storage conditions. Additionally, matrix interference was present due to the outlier of MBZP quantified on Day 270. Drug-drug interaction was also observed in the analyte mixture but the exact stability pattern of phenyl piperazines when mixed together could not be determined from this data set alone due to discrepancies observed on Day 91 and 270. This research project had shown a solid method to examine how quickly or slowly synthetic piperazines degrade in blood at different storage conditions. To further this study, it would be also important to evaluate the number of freeze-thaw cycles on each specimen in order to minimize the effect of non-metabolic degradation

Learning, Teaching, and Turn Taking in the Repeated Assignment Game

History-dependent strategies are often used to support cooperation in repeated game models. Using the indefinitely repeated common-pool resource assignment game and a perfect stranger experimental design, this paper reports novel evidence that players who have successfully used an efficiency-enhancing turn-taking strategy will teach other players in subsequent supergames to adopt this strategy. We find that subjects engage in turn taking frequently in both the Low Conflict and the High Conflict treatments. Prior experience with turn taking significantly increases turn taking in both treatments. Moreover, successful turn taking often involves fast learning, and individuals with turn taking experience are more likely to be teachers than inexperienced individuals. The comparative statics results show that teaching in such an environment also responds to incentives, since teaching is empirically more frequent in the Low Conflict treatment with higher benefits and lower costs.Learning, Teaching, Assignment Game, Laboratory Experiment, Repeated Games, Turn Taking, Common-Pool Resources