KLZ: A Prototype X Protocol Compression System

One of the most commonly used graphics protocol is the X Protocol, enabling programs to display graphics images. When running the X Protocol over the network, a lot of structured data (messages with fields) need to be transmitted. Delays can be detected by human users when connected through a low-bandwidth network. The solution is to compress the X protocol. XRemote, a network version of the X Protocol, uses Dictionary-based compression. In XRemote, strings are recorded in the dictionary. When a string repeats, its index in the dictionary is transmitted. Higher Bandwidth X (HBX) uses statistical modeling techniques instead. A context model, which depends on the nature of the field in a particular type of message and the frequencies of the values of the field, is associated with each field. XRemote is much faster than HBX, but HBX achieves better compression than XRemote. The KLZ system is developed to take advantage of our knowledge about the fields in the XMotionNotify packet (what X sends when the mouse moves) and fast Dictionary (LZW) compression. In essence, KLZ reorders and rewrites fields in the XMotionNotify packet so that the fields will be more easily compressed by the fast LZ coder. My experiments show that KLZ compresses this packet nearly as well as HBX, and 5 times better than pure LZ. KLZ is slightly faster than pure LZ, and and 10 times faster than HBX. Since many modems already implement LZ compression, KLZ could also be used to reorder data before passing them to the modem with LZ compression for transmission. This reordering would lead to vastly improved compression almost for free

Dynamical clustering of counterions on flexible polyelectrolytes

Molecular dynamics simulations are used to study the local dynamics of counterion-charged polymer association at charge densities above and below the counterion condensation threshold. Surprisingly, the counterions form weakly-interacting clusters which exhibit short range orientational order, and which decay slowly due to migration of ions across the diffuse double layer. The cluster dynamics are insensitive to an applied electric field, and qualitatively agree with the available experimental data. The results are consistent with predictions of the classical theory only over much longer time scales

A theory-informed emotion regulation variability index:Bray-Curtis dissimilarity

Emotion regulation (ER) variability refers to how individuals vary their use of ER strategies across time. It helps individuals to meet contextual needs, underscoring its importance in well-being. The theoretical foundation of ER variability recognizes two constituent processes: strategy switching (e.g., moving from distraction to social sharing) and endorsement change (e.g., decreasing the intensity of both distraction and social sharing). ER variability is commonly operationalized as the standard deviation (SD) between strategies per observation (between-strategy SD) or within a strategy across time (within-strategy SD). In this paper, we show that these SD-based approaches cannot sufficiently capture strategy switching and endorsement change, leading to ER variability indices with poor validity. We propose Bray-Curtis dissimilarity, a measure used in ecology to quantify biodiversity variability, as a theory-informed ER variability index. First, we demonstrate how Bray-Curtis dissimilarity is more sensitive than SD-based approaches in detecting ER variability through two simulation studies. Second, assuming that higher ER variability is adaptive in daily life, we test the relation between ER variability and negative affect (NA) in three experience sampling method (ESM) datasets (total N = [70, 95, 200], number of moment-level observations = [5040, 6329, 14098]) At both the moment-level and person-level, higher Bray-Curtis dissimilarity predicted lower NA more consistently than SD-based indices. We conclude that Bray-Curtis dissimilarity may better capture moment-level within-person ER variability and could have implications for studying variability in other multivariate dynamic processes. The paper is accompanied by an R tutorial and practical recommendations for using Bray-Curtis dissimilarity with ESM data

Rule-based Cross-matching of Very Large Catalogs

The NASA Extragalactic Database (NED) has deployed a new rule-based cross-matching algorithm called Match Expert (MatchEx), capable of cross-matching very large catalogs (VLCs) with >10 million objects. MatchEx goes beyond traditional position-based cross-matching algorithms by using other available data together with expert logic to determine which candidate match is the best. Furthermore, the local background density of sources is used to determine and minimize the false-positive match rate and to estimate match completeness. The logical outcome and statistical probability of each match decision is stored in the database and may be used to tune the algorithm and adjust match parameter thresholds. For our first production run, we cross-matched the GALEX All Sky Survey Catalog (GASC), containing nearly 40 million NUV-detected sources, against a directory of 180 million objects in NED. Candidate matches were identified for each GASC source within a 7''.5 radius. These candidates were filtered on position-based matching probability and on other criteria including object type and object name. We estimate a match completeness of 97.6% and a match accuracy of 99.75%. Over the next year, we will be cross-matching over 2 billion catalog sources to NED, including the Spitzer Source List, the 2MASS point-source catalog, AllWISE, and SDSS DR 10. We expect to add new capabilities to filter candidate matches based on photometry, redshifts, and refined object classifications. We will also extend MatchEx to handle more heterogenous datasets federated from smaller catalogs through NED's literature pipeline

Effectiveness of Traditional Chinese Medicine in Primary Care

Includes bibliographical references