Executive Order, January 9, 1951

Appointments made on the Staff of the Commander-in-Chief in the Iowa National Guard

Executive Order, June 27, 1952

Governor Beardsley orders and directs the Treasurer of Iowa to accept on behalf of the State of Iowa Federal funds allocated to the State for assistance in alleviating hardship and suffering in the Missouri River and the Mississippi River Flood Disaster Areas.

Executive Order, July 4, 1953

General Fred C. Tandy, the Adjutant General of Iowa, is apointed Major General in the Adjutant General's Corps, State of Iowa

Executive Order, July 15, 1953

Otto Weber is appointed to Colonel on Staff of the Commander-in-Chief

Executive Order No. 1, February 27, 1961

Iowa Liquor Commission is directed to coordinate with the State Car Dispatcher the merger of various IBM equipment.

Executive Order No. 2, February 27, 1961

State Car Dispatcher is directed to coordinate with the Iowa Liquor Commission the merger of various IBM equipment.

Executive Order No. 3, March 1, 1961

Informing several departments that approval for the change in data processing equipment should be approved in writing from the State Comptroller prior to submission to the Executive Council.

Executive Order No. 4, March 30, 1961

Requesting that all Department Heads of all Agencies of the State Government compile an inventory of all property in their deparments or under the control of their department.

Executive Order No. 5, April 11, 1961

Requesting all state departments having state automobiles stationed and operated in the Des Moines area have them inspected at the Des Moines Municipal Car Inspection Station.

Executive Order No. 6, February 21, 1962

Approved appointments of Judges are made.

Executive Order No. 7, April 3, 1962

Creates several Governor's Commissions effective January 12, 1961 until January 11, 1963

Executive Order Number Twenty, December 16, 2009

The people of Iowa expect that their state government will efficiently provide services and will be accountable in the use of taxpayer dollars.

Predictive ability of severe rainfall events over Catalonia for the year 2008

This paper analyses the predictive ability of quantitative precipitation forecasts (QPF) and the so-called "poor-man" rainfall probabilistic forecasts (RPF). With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC) for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain), managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9¿10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF) issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h) MM5 tends to overestimate total precipitation, whereas for short events (¿24 h) the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale. Throughout this study, we have only dealt with (SMC-issued) warning episodes in order to analyse deterministic (MM5 and COSMO-I7) and probabilistic (SMC) rainfall forecasts; therefore we have not taken into account those episodes that might (or might not) have been missed by the official SMC warnings. Therefore, whenever we talk about "misses", it is always in relation to the deterministic LAMs' QPFs.

Brain dynamics underlying training-induced improvement in suppressing inappropriate action.

Inhibitory control, a core component of executive functions, refers to our ability to suppress intended or ongoing cognitive or motor processes. Mostly based on Go/NoGo paradigms, a considerable amount of literature reports that inhibitory control of responses to "NoGo" stimuli is mediated by top-down mechanisms manifesting ∼200 ms after stimulus onset within frontoparietal networks. However, whether inhibitory functions in humans can be trained and the supporting neurophysiological mechanisms remain unresolved. We addressed these issues by contrasting auditory evoked potentials (AEPs) to left-lateralized "Go" and right NoGo stimuli recorded at the beginning versus the end of 30 min of active auditory spatial Go/NoGo training, as well as during passive listening of the same stimuli before versus after the training session, generating two separate 2 × 2 within-subject designs. Training improved Go/NoGo proficiency. Response times to Go stimuli decreased. During active training, AEPs to NoGo, but not Go, stimuli modulated topographically with training 61-104 ms after stimulus onset, indicative of changes in the underlying brain network. Source estimations revealed that this modulation followed from decreased activity within left parietal cortices, which in turn predicted the extent of behavioral improvement. During passive listening, in contrast, effects were limited to topographic modulations of AEPs in response to Go stimuli over the 31-81 ms interval, mediated by decreased right anterior temporoparietal activity. We discuss our results in terms of the development of an automatic and bottom-up form of inhibitory control with training and a differential effect of Go/NoGo training during active executive control versus passive listening conditions.