Artificial zinc finger fusions targeting Sp1-binding sites and the trans-activator-responsive element potently repress transcription and replication of HIV-1.

Tat activates transcription by interacting with Sp1, NF-kappaB, positive transcription elongation factor b, and trans-activator-responsive element (TAR). Tat and Sp1 play major roles in transcription by protein-protein interactions at human immunodeficiency virus, type 1 (HIV-1) long terminal repeat. Sp1 activates transcription by interacting with cyclin T1 in the absence of Tat. To disrupt the transcription activation by Tat and Sp1, we fused Sp1-inhibiting polypeptides, zinc finger polypeptide, and the TAR-binding mutant Tat (TatdMt) together. A designed or natural zinc finger and Tat mutant fusion was used to target the fusion to the key regulatory sites (GC box and TAR) on the long terminal repeat and nascent short transcripts to disrupt the molecular interaction that normally result in robust transcription. The designed zinc finger and TatdMt fusions were targeted to the TAR, and they potently repressed both transcription and replication of HIV-1. The Sp1-inhibiting POZ domain, TatdMt, and zinc fingers are key functional domains important in repression of transcription and replication. The designed artificial zinc fingers were targeted to the high affinity Sp1-binding site, and by being fused with TatdMt and POZ domain, they strongly block both Sp1-cyclin T1-dependent transcription and Tat-dependent transcription, even in the presence of excess expressed Tat.

Urinary Sphincter Based on Electronics and Artificial Muscles

Objectives: The AMS 800 is the current artifi cial urinary sphincter (AUS) forincontinence due to intrinsic sphincter defi ciency. Despite good clinical results,technical failures inherent to the hydraulic mechanism or urethral ischemicinjury contribute to revisions up to 60%. We are developing an electronic AUS,called ARTUS to overcome the rigors of AMS. The objective of this study wasto evaluate the technical effi cacy and tissue tolerance of the ARTUS systemin an animal model.Methods: The ARTUS is composed by three parts: thecontractile unit, a series of rings and an integrated microprocessor. The contractileunit is made of Nitinol fi bers. The rings are placed around the urethrato control the fl ow of urine by squeezing the urethra. They work in a sequentialalternative mode and are controlled by a microprocessor. In the fi rst phase athree-rings device was used while in the second phase a two-rings ARTUS wasused. The device was implanted in 14 sheep divided in two groups of six andeight animals for study purpose. The fi rst group aimed at bladder leak pointpressure (BLPP) measurement and validation of the animal model; the secondgroup aimed at verifying midterm tissue tolerance by explants at twelve weeks.General animal tolerance was also evaluated.Results: The ARTUS systemimplantation was uneventful. When the system was activated, the BLPP wasmeasured at 1.038 ± 0.044 bar (mean ± SD). Urethral tissue analysis did notshow signifi cant morphological changes. No infection and no sign of discomfortwere noted in animals at 12 weeks.Conclusions: The ARTUS proved to beeffective in continence achievement in this study. Histological results supportour idea that a sequential alternative mode can avoid urethral atrophy andischemia. Further technical developments are needed to verify long-termoutcome and permit human use.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

On the Source and Rewriting of 1 Corinthians 2.9 in Christian, Jewish and Islamic Traditions (1 Clem 34.8; GosJud 47.10-13; a ḥadīth qudsī)

The article reopens the file of sources, parallels and rewritings of 1 Cor 2.9, a saying that Paul attributes to some written source, when others sources put it into Jesus' mouth (e.g. GosThom 17). A state of research highlights that the hypothesis of an oral source is generally preferred but an accurate study of 1 Clem 34.8, a parallel too often neglected, supports the presence of a written source that existed before 1 Cor 2.9. GosJud 47.10-13 will help to understand the attribution of the saying to Jesus. The last important part of this article studies its parallel in Islamic traditions, a ḥadīth qudsī.

PEASANT AND SCIENTIFIC KNOWLEDGE ON PLANOSOLS AS A SOURCE OF MATERIALS IN THE MAKING OF NON-INDUSTRIAL POTTERY

Ethnopedological studies have mainly focused on agricultural land uses and associated practices. Nevertheless, peasant and indigenous populations use soil and land resources for a number of additional purposes, including pottery. In the present study, we describe and analyze folk knowledge related to the use of soils in non-industrial pottery making by peasant potters, in the municipality of Altinho, Pernambuco State, semiarid region at Brazil. Ethnoscientific techniques were used to record local knowledge, with an emphasis on describing the soil materials recognized by the potters, the properties they used to identify those soil materials, and the criteria employed by them to differentiate and relate such materials. The potters recognized three categories of soil materials: “terra” (earth), “barro” (clay) and, “piçarro” (soft rock). The multi-layered arrangement of these materials within the soil profiles was similar to the arrangement of the soil horizon described by formal pedologists. “Barro vermelho” (red clay) was considered by potters as the principal ceramic resource. The potters followed morphological and utilitarian criteria in distinguishing the different soil materials. Soils from all of these sites were sodium-affected Alfisols and correspond to Typic Albaqualf and Typic Natraqualf in the Soil Taxonomy (Soil Survey Staff, 2010).

Guide Specification for Highway Construction Texturing Concrete Pavement for Reduced Tire/Pavement Noise using Artificial Turf Drag, March 1, 2011

This document provides language that can be used by an Owner-Agency to develop materials and construction specifications with the objective of reducing tire/pavement noise. While the practices described herein are largely prescriptive, they have been demonstrated to increase the likelihood of constructing a durable, quieter concrete surface. Guidance is provided herein for texturing the concrete surface since texture geometry has a paramount effect on tire/pavement noise. Guidance for curing is also provided to improve strength and durability of the surface mortar, and thus to improve texture durability.

Sheep Excreta as Source of Nitrous Oxide in Ryegrass Pasture in Southern Brazil

ABSTRACT Livestock urine and dung are important components of the N cycle in pastures, but little information on its effect on soil nitrous oxide (N2O) emissions is available. We conducted a short-term (39-day) trial to quantify the direct N2O-N emissions from sheep excreta on an experimental area of ryegrass pasture growing on a Typic Paleudult in southern Brazil. Four rates of urine-N (161, 242, 323, and 403 kg ha-1 N) and one of dung-N (13 kg ha-1 N) were applied, as well as a control plot receiving no excreta. The N2O-N emission factor (EF = % of added N released as N2O-N) for urine and dung was calculated, taking into account the N2O fluxes in the field, over a period of 39 days. The EF value of the urine and dung was used to estimate the emissions of N2O-N over a 90-day period of pasture in the winter under two grazing intensities (2.5 or 5.0 times the herbage intake potential of grazing lambs). The soil N2O-N fluxes ranged from 4 to 353 µg m-2h-1. The highest N2O-N fluxes occurred 16 days after application of urine and dung, when the highest soil nitrate content was also recorded and the water-filled pore space exceeded 60 %. The mean EF for urine was 0.25 % of applied N, much higher than that for dung (0.06 %). We found that N2O-N emissions for the 90-day winter pasture period were 0.54 kg ha-1 for low grazing intensity and 0.62 kg ha-1 for moderate grazing intensity. Comparison of the two forms of excreta show that urine was the main contributor to N2O-N emissions (mean of 36 %), whereas dung was responsible for less than 0.1 % of total soil N2O-N emissions.

BRACHIARIA IN SELENIUM-CONTAMINATED SOIL UNDER SULPHUR SOURCE APPLICATIONS

ABSTRACT High contents of plant-available selenium in the soil in the form of selenate, resulting from natural or anthropogenic action, jeopardizes agricultural areas and requires research for solutions to establish or re-establish agricultural or livestock operation, avoiding the risk of poisoning of plants, animals and humans. The purpose was to evaluate sulfur sources in the form of sulfate, e.g., ammonium sulfate, calcium sulfate, ferric sulfate, in the remediation of tropical soils anthropogenically contaminated with Se under the tropical forage grass Brachiaria brizantha (Hochst. ex A. Rich.) Stapf cv. Marandu. More clayey soils are less able to supply plants with Se, which influences the effects of S sources, but it was found that high soil Se concentrations negatively affected forage biomass production, regardless of the soil. Of the tested S sources, the highly soluble ammonium sulfate and ferric sulfate reduced plant Se uptake and raised the available sulfur content in the soil.

Solvent vapours in incubators: a source of exposure among neonates?

Hygiene practices in neonatal units require the use of disinfecting solutions containing ethanol or isopropanol. Newly disinfected hands or soaked swabs introduced inside the incubators may emit vapours leading to alcohol exposures to the neonates. Alcohol emissions from hands and other occasional sources (e.g. soaked disinfecting swabs) lead to measurable levels of vapours inside incubators. Average isopropanol and ethanol concentrations ranging from 33.1 to 171.4 mg/m(3) (13.8 to 71.4 ppm) and from 23.5 to more than 146 mg/m3 (9.8 to > 6 ppm) respectively were measured inside occupied incubators (n = 11, measurement time about 230 min) in a neonatal unit of the Centre Hospitalier Universitaire Vaudois in Lausanne during regular activity. Exposure concentrations in a wide range of possible situations were then investigated by modeling using the one-box dispersion model. Theoretical modeling suggested typical isopropanol peaks and average concentrations ranging between 10(2) and 10(3) mg/m(3) (4.10(1) to 4.10(2)ppm), and 10(1) to 10(2) mg/m(3) (4 to 4.10(1) ppm), respectively. Based on our results we suggest several preventive measures to reduce the neonates' exposures to solvent vapours.

Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

GIS - Based Decision and Outreach Tools for Aggregate Source Management, September 2008

This research project combined various datasets, existing and created for this project, into an Interactive Mapping Service (IMS) for use by Iowa DOT personnel, county planning and zoning departments and the public in order to make more informed decisions regarding aggregate sources and future access to them. Iowa DOT Technical Advisory Committee meetings were held, along with public forum presentations, in order to understand better the social, ecological and economic limitations to extracting aggregate. The information needed by potential users was conveyed and integrated into a single informational source, the Aggregate Planning IMS.

Analysis of an iterative deconvolution approach for estimating the source wavelet during waveform inversion of crosshole ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole georadar data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a time-domain waveform inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little-to-no trade-off between the wavelet estimation and the tomographic imaging procedures.

Artificial muscle: the human chimera is the future.

Severe heart failure and cerebral stroke are broadly associated with the impairment of muscular function that conventional treatments struggle to restore. New technologies enable the construction of "smart" materials that could be of great help in treating diseases where the main problem is muscle weakness. These materials "behave" similarly to biological systems, because the material directly converts energy, for example electrical energy into movement. The extension and contraction occur silently like in natural muscles. The real challenge is to transfer this amazing technology into devices that restore or replace the mechanical function of failing muscle. Cardiac assist devices based on artificial muscle technology could envelope a weak heart and temporarily improve its systolic function, or, if placed on top of the atrium, restore the atrial kick in chronic atrial fibrillation. Artificial sphincters could be used to treat urinary incontinence after prostatectomy or faecal incontinence associated with stomas. Artificial muscles can restore the ability of patients with facial paralysis due to stroke or nerve injury to blink. Smart materials could be used to construct an artificial oesophagus including peristaltic movement and lower oesophageal sphincter function to replace the diseased oesophagus thereby avoiding the need for laparotomy to mobilise stomach or intestine. In conclusion, in the near future, smart devices will integrate with the human body to fill functional gaps due to organ failure, and so create a human chimera.