Sophrosyne in Aeschylus

This is a study on the semantics of sophrosyne, and the importance of this culturally significant term for the political vocabulary of Aeschylus. The author argues that the core of the semantics of sophrosyne is the status-based behavioral propriety within a hierarchy. By examining all the occurrences of the term’s cognates in the Aeschylean corpus, the author concludes that Aeschylus used sophrosyne as a tool in a pro-democratic rhetoric. Given that the deviance from status-based propriety in Aeschylean tragedy results in socio-political catastrophes, the monarchic societies of Greek myth and Persia are presented as political environments that endanger sophrosyne, whereas democratic processes as its bulwark

Mineralogy of Kentucky Soils

Very few mineralogical data have been published for soils in Kentucky. As an initial attempt to classify mineralogy of the subsoil, a general mineralogy map of the state was constructed based on currently available information (Fig. 1). The map suggests that quartz, mica, and feldspars are the dominant minerals of the sqnd and silt size fractions and that illite, smectite, kaolinite and hydroxyinterlayered vermiculite or smectite dominate the clay size soil fraction. Soils of the Western Coalfields, Eastern Coalfields, and Eastern Pennyrile regions generally contain more quartz in the sand and silt fraction than soils of the Purchase, Western Pennyrile, and Bluegrass regions. The sand and silt fractions of the latter regions, although still dominated by quartz, contain significant amounts of potassium feldspars and mica. The feldspar component is generally more prominent in soils of Western Kentucky, with mica being more prominent in central and eastern parts of the state. Soils with high feldspar or mica content are considered to have adequate water-soluble, exchangeable, and non-exchangeable IC-supplying capacity because of the potassium released from their mineral structure during weathering. However, muscovite-type micas are more resistant to weathering than feldspars, with a rate of IC-release not fast enough to replenish the solution K as it is removed by plants. Furthermore, not all mica-type minerals contain the same amount of Kin their crystal structure (muscovite 11%, glauconite 5%, biotite 8%). Potassium availability to plants in these soils also depends on the rate and duration of ion exchange reactions, the nature of which is affected by soil mineralogical composition, IC-specificity for certain exchange mineral sites and the nature of other ions in solution

Potassium Mineralogy of Kentucky Soils

Feldspars and mica minerals are the two primary natural sources of potassium for most agricultural soils in Kentucky. Potassium feldspars are common mineral constituents of loess deposits in western Kentucky. Mica minerals, although dominant in shales, are also found in variable quantities in siltstone, sandstone and limestone parent materials of soils in the other regions of Kentucky. Because most of the soils in the western Coalfields and western Pennyroyal, and to a lesser extent in eastern Pennyroyal and Bluegrass, are covered by a loess cap of variable thickness, their surface mineralogy has been influenced by the feldspar-rich mineralogy of the loess mantle

Mineralogy and Soil Productivity

The soil that is often called dirt is not as dirty as many people think. If we remove the 5 to 10% of the soil material, composed of organic matter and amorphous Fe, Al and Si hydrous oxides, the remaining 90 to 95% is a mixture of crystalline or subcrystalline minerals. We are able to see and identify with the naked eye, the large crystalline particles of the sand fraction. For the smaller mineral particles of the silt and clay fractions microscopic or other more sensitive methods (x=ray diffraction, thermal) are needed for their identification and quantification. While little attention is often given to these crystalline minerals as to their relation to soil productivity, their different morphological and physicochemical properties play a very important role, in controlling soil behavior. Sometimes the presence of even very small amounts of certain minerals in the soil is more critical than the presence of large amounts of others because of unique characteristics affecting their reactivity. For example. the mineral smectite (montmorillonite) with its high cation exchange capacity, surface area, and shrink-swell potential is a determining factor in ion exchange reactions, sorption processes and mechanical strength of soils. On the other hand quartz, the dominant mineral in many soils. is relatively non-reactive and is largely considered as a dilutant of other more reactive mineral components in soils. Other soil minerals such as mica and kaolinite are intermediate in reactivity between those of smectite and quartz

A New Concept in Treating Wastewaters ... Constructed Wetlands

During the last few years a new technology for treating municipal and industrial waste water has emerged, which also shows some potential for treatment of farm and home wastewaters. This technology involves the construction of artificial wetlands and establishing a dominant vegetation of Typha (cattails), Sphagnum (moss), certain algae, and other plant species which have the potential to beneficially affect small flows of waste water moving through them by biochemical processes. Interest in these systems has steadily increased because of their low cost (1/10 to 1/2 that of conventional treatment), efficiency, and near nonexistent maintenance. These constructed wetland biochemical-treatment systems appear to have such a great potential that over 200 experimental systems have already been established in the Appalachian region for acid mine drainage (AMO) and municipal water treatment. These systems are designed to mimic natural wetland ecosystems and their function in water purification

Effect of Soil Mineral Variability on Soil Use and Management

Soil mineralogical variability arises from two factors. The mineralogical composition of the parent material and the degree to which the original composition has been modified by external soil forming factors and internal soil building processes during the course of weathering. Different stages of soil weathering are represented by different mineralogical compositions and therefore a different combination of physical and chemical properties. Some soil scientists have divided these weathering stages into fresh, juvenile, virile, senile, and lateritic. The ability of soil to provide nutrients to plants reaches a maximum at the beginning of the virile stage and then declines rapidly with further weathering. Most of the soils in Kentucky have passed the middle of the virile stage, and therefore, exhibit a declining availability for plant nutrients. At this stage, plant nutrient deficiencies due to advanced stage of weathering should be offset by the application of commercial fertilizers. However, because soil in each small segment of a weathering stage contains a wide range of mineralogical compositions, a variety of management practices may be required to compensate for this variability

Machine Learning Approaches Identify Genes Containing Spatial Information From Single-Cell Transcriptomics Data.

The development of single-cell sequencing technologies has allowed researchers to gain important new knowledge about the expression profile of genes in thousands of individual cells of a model organism or tissue. A common disadvantage of this technology is the loss of the three-dimensional (3-D) structure of the cells. Consequently, the Dialogue on Reverse Engineering Assessment and Methods (DREAM) organized the Single-Cell Transcriptomics Challenge, in which we participated, with the aim to address the following two problems: (a) to identify the top 60, 40, and 20 genes of the Drosophila melanogaster embryo that contain the most spatial information and (b) to reconstruct the 3-D arrangement of the embryo using information from those genes. We developed two independent techniques, leveraging machine learning models from least absolute shrinkage and selection operator (Lasso) and deep neural networks (NNs), which are applied to high-dimensional single-cell sequencing data in order to accurately identify genes that contain spatial information. Our first technique, Lasso.TopX, utilizes the Lasso and ranking statistics and allows a user to define a specific number of features they are interested in. The NN approach utilizes weak supervision for linear regression to accommodate for uncertain or probabilistic training labels. We show, individually for both techniques, that we are able to identify important, stable, and a user-defined number of genes containing the most spatial information. The results from both techniques achieve high performance when reconstructing spatial information in D. melanogaster and also generalize to zebrafish (Danio rerio). Furthermore, we identified novel D. melanogaster genes that carry important positional information and were not previously suspected. We also show how the indirect use of the full datasets’ information can lead to data leakage and generate bias in overestimating the model’s performance. Lastly, we discuss the applicability of our approaches to other feature selection problems outside the realm of single-cell sequencing and the importance of being able to handle probabilistic training labels. Our source code and detailed documentation are available at https://github.com/TJU-CMC-Org/SingleCell-DREAM/

Metal Speciation and Immobilization Reactions Affecting the True Efficiency of Artificial Wetlands to Treat Acid Mine Drainage

The ability of constructed wetlands to lower total metal concentrations and organically complex metals in acid mine drainage (AMD) was investigated under greenhouse and field conditions. In the greenhouse study, Typha plants grown in six different substrates received simulated acid mine drainage of low metal load for five months. Most effluents, especially those from ground flows, showed significant decreases in acidity and metal concentrations. The pine needle and hay substrates most effectively reduced acidity and total Al levels. Effluents from these substrates contained 80% less total Al than respective influents. Organically complexed Al levels were independent of matrix and varied from 10 to 30% of inflow total Al concentrations. Peat and Sphagnum moss most efficiently reduced Fe concentrations but only 10% of the total Fe was organically complexed. Matrix composition had little or no effect on Mn concentrations. Substrates lowered Cu and Zn levels by 40-90% in most effluents, but pine needle and hay mixtures were the most effective. The metal concentration and acidity of a very high metal load AMD were also reduced substantially during the first six months of treatment with a wetland which was constructed by the U.S. Forest Service in McCreary County, KY and used mushroom compost as a substrate. After 8 months of operation, however, and during periods of high flow rates(\u3e 10 gallons/min) the efficiency of the wetland was drastically reduced, apparently due to reduced residence time, insufficient size and metal overloading. No major differences were observed during high flow rate periods between input-output metal concentration, although input concentrations varied due to dilution effects. The majority of Fe, Mn, and Zn in surface effluents was present in inorganic metal species. Nearly 100% of Cu and about 40% of the Al, however, was organically bound. Substrate solutions extracted by centrifugation showed increased organic/inorganic metal species ratios apparently due to increased residence time. A great portion of the metals retained by the greenhouse and field substrates was in residual forms (oxyhydroxides, sulfides, sulfates, carbonates). The metals Fe, Mn, and Zn showed the highest tendency for residual retention, while Al and especially Cu showed high affinity for organic retention. Exchangeable and sorbed forms were present in very small concentrations and in many cases were almost negligible