Charcoal (Biochar) as soil conditioner to enhance fertilizers and water use efficiency in agriculture in acid tropical soils in the Central Amazon Basin

This article summarize result of many experiments conducted in 15 years of research with biochar in nursery and field experiments in the Central Amazon

Oyster Shoal Survey - Spring 1987

This report summarizes data collected during 1987 in the Virginia portion of the Chesapeake Bay. The report focuses on the spring oyster survey in Virginia

Fluchen kontrastiv : zur sexuellen, krankheitsbasierten, skatologischen und religiösen Fluch- und Schimpfwortprototypik im Niederländischen, Deutschen und Schwedischen

Fluch- und Schimpfwortschätze sind aus kontrastiver Perspektive bisher kaum analysiert worden, sieht man von einer Vielzahl populärwissenschaftlicher Publikationen ab. Wissenschaftliche Publikationen beziehen sich meist auf eine Einzelsprache und greifen bei der Erklärung der Motive oft zu kurz, weil sie gerade benachbarte Kulturen und Sprachen (auch Dialektgebiete) zu wenig im Blick haben (Dundes 1983). Der vorliegende Beitrag leistet eine vergleichende Zusammenstellung der Fluch- und Schimpfwortschätze dreier mehr oder weniger benachbarter Sprachen, des (nördlichen) Niederländischen, des Deutschen und des Schwedischen, also zweier eng verwandter westgermanischer und einer nordgermanischen Sprache

Learning from inout-output mixes in DEA: A proportional measure for slack-based efficient projections.

Learning;

Vehicle-Rear: A New Dataset to Explore Feature Fusion for Vehicle Identification Using Convolutional Neural Networks

This work addresses the problem of vehicle identification through non-overlapping cameras. As our main contribution, we introduce a novel dataset for vehicle identification, called Vehicle-Rear, that contains more than three hours of high-resolution videos, with accurate information about the make, model, color and year of nearly 3,000 vehicles, in addition to the position and identification of their license plates. To explore our dataset we design a two-stream CNN that simultaneously uses two of the most distinctive and persistent features available: the vehicle's appearance and its license plate. This is an attempt to tackle a major problem: false alarms caused by vehicles with similar designs or by very close license plate identifiers. In the first network stream, shape similarities are identified by a Siamese CNN that uses a pair of low-resolution vehicle patches recorded by two different cameras. In the second stream, we use a CNN for OCR to extract textual information, confidence scores, and string similarities from a pair of high-resolution license plate patches. Then, features from both streams are merged by a sequence of fully connected layers for decision. In our experiments, we compared the two-stream network against several well-known CNN architectures using single or multiple vehicle features. The architectures, trained models, and dataset are publicly available at https://github.com/icarofua/vehicle-rear

Grain export agreements - no gains, no losses

Grain trade

Effect of Salmonella choleraesuis infection on immunity to hog cholera

This bulletin is a report on School of Veterinary Medicine Research Project 40, 'Hog Cholera Immunization'--P. [3].Digitized 2007 AES.Includes bibliographical references (page 15)

Vehicle classification in intelligent transport systems: an overview, methods and software perspective

Vehicle Classification (VC) is a key element of Intelligent Transportation Systems (ITS). Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet monitoring, traffic safety, and automated parking are using VC. Basically, in the current VC methods, vehicles are classified locally as a vehicle passes through a monitoring area, by fixed sensors or using a compound method. This paper presents a pervasive study on the state of the art of VC methods. We introduce a detailed VC taxonomy and explore the different kinds of traffic information that can be extracted via each method. Subsequently, traditional and cutting edge VC systems are investigated from different aspects. Specifically, strengths and shortcomings of the existing VC methods are discussed and real-time alternatives like Vehicular Ad-hoc Networks (VANETs) are investigated to convey physical as well as kinematic characteristics of the vehicles. Finally, we review a broad range of soft computing solutions involved in VC in the context of machine learning, neural networks, miscellaneous features, models and other methods

Clean fuels from biomass

The feasibility of converting biomass to portable fuels is studied. Since plants synthesize biomass from H2O and CO2 with the help of solar energy, the conversion methods of pyrolysis, anaerobic fermentation, and hydrogenation are considered. Cost reduction methods and cost effectiveness are emphasized