Biochemical parameters of typical chernozem soil under sunflower and vetch+oats in crop rotation with different fertilization

The aim of research was to compare soil biological properties under three fertilization systems in crop rotation.. The objective was to evaluate the impact of organic fertilizers in crop rotation on enzymatic activities representative of some steps of biogeochemical nutrient cycles: C(invertase), N(urease), P(phosphatase), and general microbial activity (basal soil respiration, ammonification capacity, dehydrogenase activity) in comparison to mineral and mixed fertilization. It was shown, the majority of biochemical parameters studied was reduced in soil under mixture vetch+oats followed sunflower in crop rotation, though the tendencies of change were similar. The enzyme activities were expressed per unit of soil organic carbon and it didn’t change the previous conclusion: the urease and phosphatase activities increased, but the invertase activity reduced in soil fertilized by manure in comparison to NPK amendment. Soil basal respiration at field under sunflower was significantly lower (P<0,05) in soil amended by manure in comparison to one fertilized by NPK. Nitrogen mineralization capacity (ammonification) values were highly variable and do not allowed to reveal significant differences among treatments. Soil dehydrogenase activities of soil samples under both studied crops have shown the lower values at mineral fertilization. Our data confirm the assertion that the organic farming has the favorable impact on the chernozem soil biological propertie

Roadside Truck Placard Readers for Advanced Notice and Response at Safety-Critical Facilities: Phase 2

The transport of hazardous and dangerous materials (HAZMAT) through safety-critical facilities poses significant risk to overall system reliability should those assets be incapacitated by the occurrence of a related incident. This problem is particularly acute for facilities in remote locations such as Virginia\u2019s mountain tunnels on Interstate 77 (I-77) due to limitations on alternate routes and the availability and proximity of emergency responders and specialized equipment/supplies. Automated placard reader systems (APRSs) are commercially available camera-based computer vision systems that \u201cread\u201d hazardous material placards on passing trucks from roadside installations. This information, along with other pertinent vehicle identification data may then be forwarded to critical facility operators to inform any preparations or responses that may be required. The Virginia Tech Transportation Institute conducted an initial phase of work to assess the readiness of APRSs for their reliable and effective roadside deployment and to determine how the data from such a system could be used by facility operators to improve safety and mitigate disruption during an event involving HAZMAT. The findings of the first phase of work indicated that available APRS technology was sufficiently advanced to warrant a second phase of work that included field testing and further refinement of the preliminary deployment plan. In Phase I, an APRS from Intelligent Imaging Systems (IIS) was identified for further evaluation. In this (second) phase of work, a mobile APRS system provided by IIS was evaluated under experimental and naturalistic scenarios at the Virginia Smart Roads and at several locations on Virginia public roads. A photographic survey of public HAZMAT placard usage conducted previously was used to inform this testing. Additional naturalistic data were acquired from a permanent APRS installation in Delaware when difficulties with the mobile APRS were encountered. The mobile and permanent APRSs were able to classify HAZMAT placard accurately at rates of 96% and 99%, respectively. The mobile and permanent systems were able to read United States Department of Transportation (USDOT) numbers from the sides of tractors correctly at rates of 46% and 67%, respectively, and tractor license plates correctly at rates of 43% and 39%, respectively. Moderate levels of rain and snow, as observed through roadside cameras and reported at nearby weather stations, had minimal impact on reporting accuracy. Performance of the system at night compared favorably with daytime performance. To address potential false negative concerns, a visual survey of 187 commercial vehicles was conducted that revealed that the APRS was 85% successful at locating and identifying the presence of placards on commercial vehicles passing in the near lane. With respect to implementation, the nature of how the subject APRS data is provided to users is not currently conducive to automated integration with existing or future VDOT tunnel or traffic management systems as data must be read from an online interface and no \u201cpush\u201d options are currently available. Also, providing advance warning of the approach of HAZMAT to tunnel operators on I-77 is not feasible given constraints related to the geographic siting of potential APRS installations and respective traffic characteristics. However, facility operator access to APRS data after an incident has occurred may provide benefits of improved responder and traveler safety as well as faster clearance times

Evaluation of a Buried Cable Roadside Animal Detection System Standard Title Page -Report on Federally Funded Project 1. Report No.: 2. Government Accession No.: 3. Recipient&apos;s Catalog No.: FHWA/VCTIR 15-R25 4. Title and Subtitle: 5. Report Date: Evaluati

Animal-vehicle collisions (AVC) are a concern for departments of transportation as they translate into hundreds of human fatalities and billions of dollars in property damage each year. A recently published report states that the Virginia Department of Transportation (VDOT) currently spends over 4 million yearly to remove about 55,000 deer carcasses from its roadways. Currently, one of the most effective existing methods to reduce AVCs is the use of animal detection systems, which can detect animals near the roadway and alert approaching drivers accordingly. In order to reduce AVCs in Virginia, VDOT, in collaboration with the Virginia Tech Transportation Institute, proposed the evaluation of an innovative roadside animal detection system in naturalistic and controlled conditions. This type of system offers numerous apparent advantages over aboveground animal detection technologies when environmental interferences, such as precipitation and vegetation, and site-specific characteristics, such as topology, subsidence, and road curvature, are considered. The subject animal detection system (ADS), a 300-m-long buried dual-cable sensor, detects the crossing of large and medium-sized animals and provides data on their location along the length of the cable. The system has a central processor unit for control and communication and generates an invisible electromagnetic detection field around buried cables. When the detection field is perturbed, an alarm is declared and the location of the intrusion is determined. Target animals are detected based on their conductivity, size, and movement, with multiple simultaneous intrusions being detected during a crossing event. The system was installed and tested at a highly suitable site on the Virginia Smart Road where large wild animals, including deer and bear, are often observed in a roadside environment. This report describes the installation of the ADS, data collection and analysis methodology, evaluation of the system's reliability and effectiveness, cost analysis, and implementation prospects. The system used continuous, all-weather and nighttime video surveillance to monitor animal movement and to gauge system detections, and potential non-detections of the ADS. Also, a communication link between the buried ADS and the Virginia Smart Road fiber optic network was established to allow operation and monitoring of the system from a dedicated server in the Virginia Smart Road Control Room. A performance verification of the network communication was successfully conducted through continuous data collection and transfer to a storage unit. Data were collected continuously for a period of 10 months that included winter, and then analyzed to determine overall detection performance of the system. Data analyses indicate that the ADS, if properly installed and calibrated, is capable of detecting animals such as deer and bear, and possibly smaller animals, such as fox and coyotes, with over 95% reliability. The ADS also performed well even when covered by 3 ft of snow. Moreover, the system was tested under various traffic conditions and no vehicle interferences were noted during the same monitoring period. The acquired data can be used to improve highway safety through driver warning systems installed along roadway sections where high wildlife activity has been observed. Additionally, this system may be integrated with the connected vehicle framework to provide advance, in-vehicle warnings to motorists approaching locations where animals have been detected in or near the roadway. DISCLAIMER The project that is the subject of this report was done under contract for the Virginia Department of Transportation, Virginia Center for Transportation Innovation and Research. The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Virginia Department of Transportation, the Commonwealth Transportation Board, or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. Any inclusion of manufacturer names, trade names, or trademarks is for identification purposes only and is not to be considered an endorsement. Each contract report is peer reviewed and accepted for publication by staff of Virginia Center for Transportation Innovation and Research with expertise in related technical areas. Final editing and proofreading of the report are performed by the contractor. Copyright 2015 by the Commonwealth of Virginia. All rights reserved. iii ABSTRACT Animal-vehicle collisions (AVC) are a concern for departments of transportation as they translate into hundreds of human fatalities and billions of dollars in property damage each year. A recently published report states that the Virginia Department of Transportation (VDOT) currently spends over 4 million yearly to remove about 55,000 deer carcasses from its roadways. Currently, one of the most effective existing methods to reduce AVCs is the use of animal detection systems, which can detect animals near the roadway and alert approaching drivers accordingly. In order to reduce AVCs in Virginia, VDOT, in collaboration with the Virginia Tech Transportation Institute, proposed the evaluation of an innovative roadside animal detection system in naturalistic and controlled conditions. This type of system offers numerous apparent advantages over aboveground animal detection technologies when environmental interferences, such as precipitation and vegetation, and site-specific characteristics, such as topology, subsidence, and road curvature, are considered. The subject animal detection system (ADS), a 300-m-long buried dual-cable sensor, detects the crossing of large and medium-sized animals and provides data on their location along the length of the cable. The system has a central processor unit for control and communication and generates an invisible electromagnetic detection field around buried cables. When the detection field is perturbed, an alarm is declared and the location of the intrusion is determined. Target animals are detected based on their conductivity, size, and movement, with multiple simultaneous intrusions being detected during a crossing event. The system was installed and tested at a highly suitable site on the Virginia Smart Road where large wild animals, including deer and bear, are often observed in a roadside environment. This report describes the installation of the ADS, data collection and analysis methodology, evaluation of the system&apos;s reliability and effectiveness, cost analysis, and implementation prospects. The system used continuous, all-weather and nighttime video surveillance to monitor animal movement and to gauge system detections, and potential nondetections of the ADS. Also, a communication link between the buried ADS and the Virginia Smart Road fiber optic network was established to allow operation and monitoring of the system from a dedicated server in the Virginia Smart Road Control Room. A performance verification of the network communication was successfully conducted through continuous data collection and transfer to a storage unit. Data were collected continuously for a period of 10 months that included winter, and then analyzed to determine overall detection performance of the system. Data analyses indicate that the ADS, if properly installed and calibrated, is capable of detecting animals such as deer and bear, and possibly smaller animals, such as fox and coyotes, with over 95% reliability. The ADS also performed well even when covered by 3 ft of snow. Moreover, the system was tested under various traffic conditions and no vehicle interferences were noted during the same monitoring period. The acquired data can be used to improve highway safety through driver warning systems installed along roadway sections where high wildlife activity has been observed. Additionally, this system may be integrated with the connected vehicle framework to provide advance, in-vehicle warnings to motorists approaching locations where animals have been detected in or near the roadway

Structural, spectral, electric-field-induced second harmonic, and theoretical study of Ni(II), Cu(II), Zn(II) ancd VO(II) complexes with [N2O2]unsymmetrical Schiff Bases of S-Methylisothiosemicarbazide Derivatives

New unsymmetrical [N2O2] tetradentate Schiff base complexes of Ni(II), Cu(II), Zn(II), and VO(II) were synthesized by template condensation of the tetradentate precursor 1-phenylbutane-1,3-dione mono-S-methylisothiosemicarbazone with o-hydroxybenzaldehyde or its 5-phenylazo derivative. They were characterized by elemental analysis, IR, UV-vis, electron spin resonance, and NMR spectroscopy, mass spectrometry, and magnetic measurements. The crystal structures of five of them have been determined by X-ray diffraction using, in some cases, synchrotron radiation. These compounds are characterized by a large thermal stability; their decomposition temperatures range from 240 up to 310\ub0C. Complexes with the phenylazo substituent were found to possess a large second-order nonlinear optical (NLO) response, as determined both by measurements of solution-phase direct current electricfield-induced second harmonic generation and by theoretical time-dependent density functional theory (TDDFT) calculations. The molecular hyperpolarizability was found to decrease in the order Zn(II) > Cu(II) > Ni(II) ~ VO(II). The active role of the metal in determining the NLO properties of the complexes was shown through an analysis of their UV-vis spectra, which revealed the presence of metal-to-ligand (in closed-shell complexes) and ligandto- metal (in open-shell complexes) charge-transfer bands together with intra-ligand charge-transfer transitions. Assignment of the bands was based on the analysis of the TDDFT computed spectra