Letter from Edwin M. Ryland to George Sibley, January 15, 1838

Transcript of Letter from Edwin M. Ryland to George Sibley, January 15, 1838. Ryland says that he has named his son after Sibley; asks the Sibleys to come and visit; discusses the growth of the area around Lexington, Missouri

Demonstration of the test-retest reliability and sensitivity of the Lower Limb Functional Index as a measure of functional recovery post burn injury: A cross-sectional repeated measures study design

Background: Lower limb burns can significantly delay recovery of function. Measuring lower limb functional outcomes is challenging in the unique burn patient population and necessitates the use of reliable and valid tools. The aims of this study were to examine the test-retest reliability, sensitivity, and internal consistency of Sections 1 and 3 of the Lower Limb Functional Index-10 (LLFI-10) questionnaire for measuring functional ability in patients with lower limb burns over time. Methods: Twenty-nine adult patients who had sustained a lower limb burn injury in the previous 12 months completed the test-retest procedure of the study. In addition, the minimal detectable change (MDC) was calculated for Section 1 and 3 of the LLFI-10. Section 1 is focused on the activity limitations experienced by patients with a lower limb disorder whereas Section 3 involves patients indicating their current percentage of pre-injury duties. Results: Section 1 of the LLFI-10 demonstrated excellent test-retest reliability (intra-class correlation coefficient (ICC) 0.98, 95 % CI 0.96–0.99) whilst Section 3 demonstrated high test-retest reliability (ICC 0.88, 95 % CI 0.79–0.94). MDC scores for Sections 1 and 3 were 1.27 points and 30.22 %, respectively. Internal consistency was demonstrated with a significant negative association (rs=−0.83) between Sections 1 and 3 of the LLFI-10 (p\u3c0.001). Conclusions: This study demonstrates that Section 1 and 3 of the LLFI-10 are reliable for measuring functional ability in patients who have sustained lower limb burns in the previous 12 months, and furthermore, Section 1 is sensitive to changes in patient function over time

Platinum(II) phosphonate complexes derived from endo-8-camphanylphosphonic acid

The reactions of cis-[PtCl₂L₂] [L = PPh₃, PMe₂Ph or L₂ = Ph₂P(CH₂)₂PPh₂ (dppe)] with endo-8-camphanylphosphonic acid (CamPO₃H₂) and Ag₂O in refluxing dichloromethane gave platinum(II) phosphonate complexes [Pt(O₃PCam)L₂]. The X-ray crystal structure of [Pt(O₃PCam)(PPh₃)₂]•₂CHCl₃ shows that the bulky camphanyl group, rather than being directed away from the platinum, is instead directed into a pocket formed by the Pt and the two PPh₃ ligands. This allows the O₃P–CH₂ group to have a preferred staggered conformation. The complexes were studied in detail by NMR spectroscopy, which demonstrates non-fluxional behaviour for the sterically bulky PPh₃ and dppe derivatives, which contain inequivalent phosphine ligands in their ³¹P NMR spectra. These findings are backed up by theoretical calculations on the PPh₃ and PPhMe₂ derivatives, which show, respectively, high and low energy barriers to rotation of the camphanyl group in the PPh₃ and PPhMe₂ complexes. The X-ray crystal structure of CamPO₃H₂ is also reported, and consists of hydrogen-bonded hexameric aggregates, which assemble to form a columnar structure containing hydrophilic phosphonic acid channels surrounded by a sheath of bulky, hydrophobic camphanyl groups

Text mixing shapes the anatomy of rank-frequency distributions

Natural languages are full of rules and exceptions. One of the most famous quantitative rules is Zipf\u27s law, which states that the frequency of occurrence of a word is approximately inversely proportional to its rank. Though this law of ranks has been found to hold across disparate texts and forms of data, analyses of increasingly large corpora since the late 1990s have revealed the existence of two scaling regimes. These regimes have thus far been explained by a hypothesis suggesting a separability of languages into core and noncore lexica. Here we present and defend an alternative hypothesis that the two scaling regimes result from the act of aggregating texts. We observe that text mixing leads to an effective decay of word introduction, which we show provides accurate predictions of the location and severity of breaks in scaling. Upon examining large corpora from 10 languages in the Project Gutenberg eBooks collection, we find emphatic empirical support for the universality of our claim

Identifying missing dictionary entries with frequency-conserving context models

In an effort to better understand meaning from natural language texts, we explore methods aimed at organizing lexical objects into contexts. A number of these methods for organization fall into a family defined by word ordering. Unlike demographic or spatial partitions of data, these collocation models are of special importance for their universal applicability. While we are interested here in text and have framed our treatment appropriately, our work is potentially applicable to other areas of research (e.g., speech, genomics, and mobility patterns) where one has ordered categorical data (e.g., sounds, genes, and locations). Our approach focuses on the phrase (whether word or larger) as the primary meaning-bearing lexical unit and object of study. To do so, we employ our previously developed framework for generating word-conserving phrase-frequency data. Upon training our model with the Wiktionary, an extensive, online, collaborative, and open-source dictionary that contains over 100000 phrasal definitions, we develop highly effective filters for the identification of meaningful, missing phrase entries. With our predictions we then engage the editorial community of the Wiktionary and propose short lists of potential missing entries for definition, developing a breakthrough, lexical extraction technique and expanding our knowledge of the defined English lexicon of phrases

Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs

The emergence and global adoption of social media has rendered possible the real-time estimation of population-scale sentiment, an extraordinary capacity which has profound implications for our understanding of human behavior. Given the growing assortment of sentiment-measuring instruments, it is imperative to understand which aspects of sentiment dictionaries contribute to both their classification accuracy and their ability to provide richer understanding of texts. Here, we perform detailed, quantitative tests and qualitative assessments of 6 dictionary-based methods applied to 4 different corpora, and briefly examine a further 20 methods. We show that while inappropriate for sentences, dictionary-based methods are generally robust in their classification accuracy for longer texts. Most importantly they can aid understanding of texts with reliable and meaningful word shift graphs if (1) the dictionary covers a sufficiently large portion of a given text’s lexicon when weighted by word usage frequency; and (2) words are scored on a continuous scale