18 research outputs found
COLD CASE INVESTIGATIONS WITHIN FAIRFAX COUNTY: TURNING THE LIABILITY OF TIME INTO AN ASSET
No department or individual involved in the investigation of homicides is ever going to have a 100% closure rate. Therefore, many departments will be faced with a situation where another homicide happens before they are finished handling the previous one.
How does one manage these open cases; how often are they reviewed; and who is responsible once the assigned detective is either transferred or leaves the unit or department? Someone has to be able to answer questions from the family, media and anyone else who might inquire about the case.
Based on the number of unsolved homicide cases within Fairfax County, the concept of a “Cold Case Squad” was explored. During January 1995, the Fairfax County Police Department implemented a Cold Case Squad consisting of one supervisor, three veteran detectives, two auxiliary police officers and one cadet. The Cold Case detectives inherited approximately 75 unsolved homicides which occurred in Fairfax County, Virginia, from 1964 through December 31, 1994. More than half of the unsolved homicides (42) have occurred in the past nine years.
The hypothesis for this thesis was: The formulation of a Cold Case Squad would measurably reduce the number of unresolved homicides within Fairfax County. The primary evaluation factor for the thesis was the Cold Case Squad’s “close-ability” rate.
The thesis identified and evaluated nine solvability factors utilized by the Cold Case Squad Supervisor. The solvability factors are considered when prioritizing case investigation, assigning personnel to an investigation and suspending investigate efforts. One of the goals for utilizing solvability factors is to develop a clear profile of cases with the most potential for close-ability.
The study population for this thesis is the 42 unsolved homicides which have occurred in Fairfax County, Virginia, between January 1, 1986, and December 31, 1994. Solvability factor work sheets were completed and computated for the study population.
The hypothesis has been proven as there is a measurable reduction in the number of unsolved homicides. From the study population, two cases have been closed by arrest, one case closed by exceptional means and one case is pending approval from the Commonwealth Attorney’s Office to obtain arrest warrants. These four cases represent a 9.5% reduction of unsolved cases within the study population.
A copy of this thesis was given to the Cold Case Squad Supervisor for review and application. It is hoped the research from this thesis will be applied to the Cold Case Squad so it will become more effective and continue to turn the liability of time into an asset
Microalgal photophysiology and macronutrient distribution in summer sea ice in the Amundsen and Ross Seas, Antarctica
<div><p>Our study addresses how environmental variables, such as macronutrients concentrations, snow cover, carbonate chemistry and salinity affect the photophysiology and biomass of Antarctic sea-ice algae. We have measured vertical profiles of inorganic macronutrients (phosphate, nitrite + nitrate and silicic acid) in summer sea ice and photophysiology of ice algal assemblages in the poorly studied Amundsen and Ross Seas sectors of the Southern Ocean. Brine-scaled bacterial abundance, chl <i>a</i> and macronutrient concentrations were often high in the ice and positively correlated with each other. Analysis of photosystem II rapid light curves showed that microalgal cells in samples with high phosphate and nitrite + nitrate concentrations had reduced maximum relative electron transport rate and photosynthetic efficiency. We also observed strong couplings of PSII parameters to snow depth, ice thickness and brine salinity, which highlights a wide range of photoacclimation in Antarctic pack-ice algae. It is likely that the pack ice was in a post-bloom situation during the late sea-ice season, with low photosynthetic efficiency and a high degree of nutrient accumulation occurring in the ice. In order to predict how key biogeochemical processes are affected by future changes in sea ice cover, such as <i>in situ</i> photosynthesis and nutrient cycling, we need to understand how physicochemical properties of sea ice affect the microbial community. Our results support existing hypothesis about sea-ice algal photophysiology, and provide additional observations on high nutrient concentrations in sea ice that could influence the planktonic communities as the ice is retreating.</p></div
Correlation between chl <i>a</i> and inorganic macronutrient concentrations (a–c), and between PSII capacity (rETR<sub>max</sub>) and inorganic macronutrient concentrations (d–f).
<p>The grey areas represent 95% prediction intervals of the fitted lines. All concentrations are scaled to brine volume.</p
Station list, environmental and biological characteristics of the sea ice.
<p>Stations are numbered according to a previous study [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195587#pone.0195587.ref034" target="_blank">34</a>]. Bacterial abundance and chl <i>a</i> concentrations are depth-integrated throughout the sea ice column, and presented in either single or duplicated cores.</p
RDA ordination plot of environmental variables (black solid lines) explaining photophysiological data (grey, dashed lines).
<p>The first two RDA axes were significant (pseudo-F = 13.4, p = 0.001, 1000 permutations in Monte Carlo permutation test) and account for 51.0% of the total variation in the dataset. The environmental variables are inorganic macronutrient concentrations (nitrite + nitrate (NO<sub>2</sub> + NO<sub>3</sub>), phosphate (PO<sub>4</sub>), silicic acid (Si)), brine salinity, dissolved inorganic carbon (DIC), pH, snow depth, sampling depth (ice thickness). Photophysiological data include F<sub>v</sub>/F<sub>m</sub>, rETR<sub>max</sub>, E<sub>k</sub>, α<sub>PSII</sub> (alpha<sub>PSII</sub>) and brine-scaled chl <i>a</i> concentration.</p
Simple linear regressions for the major drivers of PSII activity in Southern Ocean sea ice during summer.
<p>Data illustrate the relationships between sampling depth and F<sub>v</sub>/F<sub>m</sub> (<b>a</b>), and light saturation point (E<sub>k</sub>) and snow depth (<b>b</b>). Maximum rate of electron transport rate (rETR<sub>max</sub>) (<b>c</b>) and non-photochemical quenching (NPQ) (<b>d</b>) are negatively and positively correlated with brine salinity in sea-ice algal communities, respectively. P-values are reported from Pearson’s correlation, and the grey areas represent 95% predictor interval of the fitted line.</p
Sea-ice sampling stations during the Oden Southern Ocean 2010/2011 cruise.
<p>Data of average sea extent from December 2010 was provided by the National Snow and Ice Data Center (<a href="http://nsidc.org/" target="_blank">http://nsidc.org/</a>). Map was created using the Quantarctica 2.14 QGIS-package, developed by the Norwegian Polar Institute (<a href="http://www.quantarctica.org" target="_blank">www.quantarctica.org</a>).</p
Means ± standard deviations of temperature (<i>T</i>), salinity (<i>S</i>), total alkalinity (<i>A</i><sub><i>T</i></sub>), total dissolved inorganic carbon (<i>C</i><sub><i>T</i></sub>), total hydrogen ion scale pH (pH<sub>T</sub>), and CO<sub>2</sub> partial pressure (<i>p</i>CO<sub>2</sub>) during incubations.
<p>Means ± standard deviations of temperature (<i>T</i>), salinity (<i>S</i>), total alkalinity (<i>A</i><sub><i>T</i></sub>), total dissolved inorganic carbon (<i>C</i><sub><i>T</i></sub>), total hydrogen ion scale pH (pH<sub>T</sub>), and CO<sub>2</sub> partial pressure (<i>p</i>CO<sub>2</sub>) during incubations.</p
RNA/DNA ratios (means ± standard deviations) in <i>Calanus glacialis</i> copepodites stage V, A) experiment 1 and B) experiment 2.
<p>RNA/DNA ratios (means ± standard deviations) in <i>Calanus glacialis</i> copepodites stage V, A) experiment 1 and B) experiment 2.</p