Swept-frequency UHF radiometer for deep probes of earth - A concept

Radiometer, developed for use on moon or planets, could be used to - determine layering and structure as deep as 100 feet below earth surface, determine physical properties of subsurface by variation of dielectric constants, identify types of materials including ore bodies and oil, and locate subsurface deposits of moisture

Leveraging Bias in Forensic Science

Dr. Simon Cole calls for a more hierarchical organization of forensic science in his challenging Article, Acculturating Forensic Science: What is ‘Scientific Culture’, and How can Forensic Science Adopt it? Koppl thinks Dr. Cole is right to say that there are different roles in forensic science, but somewhat mistaken in his call for hierarchy

Limited enforcement and efficient interbank arrangements

Banks have historically provided mutual insurance against asset risk, where the insurance arrangement itself was characterized by limited enforcement. This paper shows that a non-trivial interaction between asset and liquidity risk plays a crucial role in shaping optimal banking arrangements in the presence of limited enforcement. We find that liquidity shocks are essential for the provision of insurance against asset shocks, as they mitigate interbank enforcement problems. These enforcement problems generate endogenous aggregate uncertainty as investment allocations depend upon the joint distribution of shocks. Paradoxically, a negative correlation between liquidity and asset shocks ameliorates enforcement limitations and facilitates interbank cooperation.Risk ; Liquidity (Economics)

Using Procedural Justice to Understand, Explain, and Prevent Decision-Making Errors in Forensic Sciences

It has been estimated that in the United States there are 20,000 false felony convictions a year due to deficiencies in the forensic science and criminal justice systems (Koppl, 2010c). As many of these errors can be attributed to flaws in the processes by which forensic science decisions are made, the principles of procedural justice are a useful lens for analyzing these processes and recommending improved practices. In this secondary analysis of current research, decision-making processes in forensic sciences are analyzed using Leventhal’s six criteria for establishing procedural justice. Specifically, we assesses the current state of forensic science, explain how some industry practices may be prone to error and bias, and provide practical suggestions for improving industry practices to better adhere to the principles of procedural justice. In addition, the implications of this analysis for practitioners outside of forensic sciences are discussed

Fast and Simple Compact Hashing via Bucketing

Compact hash tables store a set S of n key-value pairs, where the keys are from the universe U = {0, ..., u - 1}, and the values are v-bit integers, in close to B(u, n) + nv bits of space, where B(u, n) = log2 ((u)(n)) is the information-theoretic lower bound for representing the set of keys in S, and support operations insert, delete and lookup on S. Compact hash tables have received significant attention in recent years, and approaches dating back to Cleary [IEEE T. Comput, 1984], as well as more recent ones have been implemented and used in a number of applications. However, the wins on space usage of these approaches are outweighed by their slowness relative to conventional hash tables. In this paper, we demonstrate that compact hash tables based upon a simple idea of bucketing practically outperform existing compact hash table implementations in terms of memory usage and construction time, and existing fast hash table implementations in terms of memory usage (and sometimes also in terms of construction time), while having competitive query times. A related notion is that of a compact hash ID map, which stores a set (S) over cap of n keys from U, and implicitly associates each key in (S) over cap with a unique value (its ID), chosen by the data structure itself, which is an integer of magnitude O(n), and supports inserts and lookups on S, while using space close to B(u, n) bits. One of our approaches is suitable for use as a compact hash ID map.Peer reviewe

The Law and Big Data

In this Article we critically examine the use of Big Data in the legal system. Big Data is driving a trend towards behavioral optimization and personalized law, in which legal decisions and rules are optimized for best outcomes and where law is tailored to individual consumers based on analysis of past data. Big Data, however, has serious limitations and dangers when applied in the legal context. Advocates of Big Data make theoretically problematic assumptions about the objectivity of data and scientific observation. Law is always theory-laden. Although Big Data strives to be objective, law and data have multiple possible meanings and uses and thus require theory and interpretation in order to be applied. Further, the meanings and uses of law and data are indefinite and continually evolving in ways that cannot be captured or predicted by Big Data. Due to these limitations, the use of Big Data will likely generate unintended consequences in the legal system. Large-scale use of Big Data will create distortions that adversely influence legal decision-making, causing irrational herding behaviors in the law. The centralized nature of the collection and application of Big Data also poses serious threats to legal evolution and democratic accountability. Furthermore, its focus on behavioral optimization necessarily restricts and even eliminates the local variation and heterogeneity that makes the legal system adaptive. In all, though Big Data has legitimate uses, this Article cautions against using Big Data to replace independent legal judgmen

The Law and Big Data

In this Article we critically examine the use of Big Data in the legal system. Big Data is driving a trend towards behavioral optimization and personalized law, in which legal decisions and rules are optimized for best outcomes and where law is tailored to individual consumers based on analysis of past data. Big Data, however, has serious limitations and dangers when applied in the legal context. Advocates of Big Data make theoretically problematic assumptions about the objectivity of data and scientific observation. Law is always theory-laden. Although Big Data strives to be objective, law and data have multiple possible meanings and uses and thus require theory and interpretation in order to be applied. Further, the meanings and uses of law and data are indefinite and continually evolving in ways that cannot be captured or predicted by Big Data. Due to these limitations, the use of Big Data will likely generate unintended consequences in the legal system. Large-scale use of Big Data will create distortions that adversely influence legal decision-making, causing irrational herding behaviors in the law. The centralized nature of the collection and application of Big Data also poses serious threats to legal evolution and democratic accountability. Furthermore, its focus on behavioral optimization necessarily restricts and even eliminates the local variation and heterogeneity that makes the legal system adaptive. In all, though Big Data has legitimate uses, this Article cautions against using Big Data to replace independent legal judgmen