Iowa Public Library Statistics, July 1, 2011-June 30, 2012

The 2010-2011 (FY11) edition of Iowa Public Library Statistics includes information on income, expenditures, collections, circulation, and other measures, including staff. Each section is arranged by size code, then alphabetically by city. The totals and percentiles for each size code grouping are given immediately following the alphabetical listings. Totals and medians for all reporting libraries are given at the end of each section. There are 543 libraries included in this publication; 525 submitted a report. The table of size codes (page 5) lists the libraries alphabetically. The following table lists the size code designations, the population range in each size code, the number of libraries reporting in each size code, and the total population of the reporting libraries in each size code. The total population served by the 543 libraries is 2,339,070. Population data is used to determine per capita figures throughout the publication.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Molecular crime and cellular punishment: active detoxification of misfolded and aggregated proteins in the cell by the chaperone and protease networks.

Labile or mutation-sensitised proteins may spontaneously convert into aggregation-prone conformations that may be toxic and infectious. This hazardous behavior, which can be described as a form of "molecular criminality", can be actively counteracted in the cell by a network of molecular chaperone and proteases. Similar to law enforcement agents, molecular chaperones and proteases can specifically identify, apprehend, unfold and thus neutralize "criminal" protein conformers, allowing them to subsequently refold into harmless functional proteins. Irreversibly damaged polypeptides that have lost the ability to natively refold are preferentially degraded by highly controlled ATP-consuming proteases. Damaged proteins that escape proteasomal degradation can also be "incarcerated" into dense amyloids, "evicted" from the cell, or internally "exiled" to the lysosome to be hydrolysed and recycled. Thus, remarkable parallels exist between molecular and human forms of criminality, as well as in the cellular and social responses to various forms of crime. Yet, differences also exist: whereas programmed death is the preferred solution chosen by aged and aggregation-stressed cells, collective suicide is seldom chosen by lawless societies. Significantly, there is no cellular equivalent for the role of familial care and of education in general, which is so crucial to the proper shaping of functional persons in the society. Unlike in the cell, humanism introduces a bias against radical solutions such as capital punishment, favouring crime prevention, reeducation and social reinsertion of criminals.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Effects of maintaining ditch networks on the development of Scots pine stands

Tiivistelmä: Kunnostusojituksen vaikutus rämemänniköiden kehitykseen

Regional deterministic characterization of fracture networks and its application to GIS-based rock fall risk assessment

The study investigates the possibility to incorporate fracture intensity and block geometry as spatially continuous parameters in GIS-based systems. For this purpose, a deterministic method has been implemented to estimate block size (Bloc3D) and joint frequency (COLTOP). In addition to measuring the block size, the Bloc3D Method provides a 3D representation of the shape of individual blocks. These two methods were applied using field measurements (joint set orientation and spacing) performed over a large field area, in the Swiss Alps. This area is characterized by a complex geology, a number of different rock masses and varying degrees of metamorphism. The spatial variability of the parameters was evaluated with regard to lithology and major faults. A model incorporating these measurements and observations into a GIS system to assess the risk associated with rock falls is proposed. The analysis concludes with a discussion on the feasibility of such an application in regularly and irregularly jointed rock masses, with persistent and impersistent discontinuities.

Discharge water quality from old ditch networks in Finnish peatland forests

Tiivistelmä: Vanhoilta metsäojitusalueilta valuvan veden ominaisuudet

Iowa Library Services/State Library Update, June 2014, Vol. 12, no. 2

Quarterly update for Iowa Library Services/State Library patrons.

Generation of biological association networks: A novel strategy to detect new targets in cancer therapy

The aim of this work was to design a novel strategy to detect new targets for anticancer treatments. The rationale was to build Biological Association Networks from differentially expressed genes in drug-resistant cells to identify important nodes within the Networks. These nodes may represent putative targets to attack in cancer therapy, as a way to destabilize the gene network developed by the resistant cells to escape from the drug pressure. As a model we used cells resistant to methotrexate (MTX), an inhibitor of DHFR. Selected node-genes were analyzed at the transcriptional level and from a genotypic point of view. In colon cancer cells, DHFR, the AKR1 family, PKC¿, S100A4, DKK1, and CAV1 were overexpressed while E-cadherin was lost. In breast cancer cells, the UGT1A family was overexpressed, whereas EEF1A1 was overexpressed in pancreatic cells. Interference RNAs directed against these targets sensitized cells towards MTX.

Plastic modifications within inhibitory control networks induced by practicing a stop-signal task: an electrical neuroimaging study.

INTRODUCTION: Inhibitory control refers to our ability to suppress ongoing motor, affective or cognitive processes and mostly depends on a fronto-basal brain network. Inhibitory control deficits participate in the emergence of several prominent psychiatric conditions, including attention deficit/hyperactivity disorder or addiction. The rehabilitation of these pathologies might therefore benefit from training-based behavioral interventions aiming at improving inhibitory control proficiency and normalizing the underlying neurophysiological mechanisms. The development of an efficient inhibitory control training regimen first requires determining the effects of practicing inhibition tasks. METHODS: We addressed this question by contrasting behavioral performance and electrical neuroimaging analyses of event-related potentials (ERPs) recorded from humans at the beginning versus the end of 1 h of practice on a stop-signal task (SST) involving the withholding of responses when a stop signal was presented during a speeded auditory discrimination task. RESULTS: Practicing a short SST improved behavioral performance. Electrophysiologically, ERPs differed topographically at 200 msec post-stimulus onset, indicative of the engagement of distinct brain network with learning. Source estimations localized this effect within the inferior frontal gyrus, the pre-supplementary motor area and the basal ganglia. CONCLUSION: Our collective results indicate that behavioral and brain responses during an inhibitory control task are subject to fast plastic changes and provide evidence that high-order fronto-basal executive networks can be modified by practicing a SST.

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

Report on a special investigation of the Malvern Public Library for the period July 1, 2006 through October 31, 2013

Report on a special investigation of the Malvern Public Library for the period July 1, 2006 through October 31, 2013

A guide to resources for the study of the recent history of the United States in the libraries of the University of Iowa, the State Historical Society of Iowa, and in the Herbert Hoover Presidential Library, 1977

This guide is designed as a finding aid for researchers seeking materials on a particular topic and it indicates the nature and extent of resources for the study of United States history available at the Historical Society of Iowa, the Herbert Hoover Presidential Library and the Iowa University Libraries.

Iowa Library Services FY12 Annual Report, June 2013

Annual report for State Library of Iowa