Effect of Tillage and Fertilization on Agronomics and Nutrient Uptake of Sweet Sorghum and Soil Test Extractable P and K after Four Years of a Monocrop Production System

Sweet sorghum [Sorghum bicolor (L.) Moench] (SS) has been grown in the southern United States to produce syrup for many years. There is an interest in SS as a biofuel feedstock due to its high sugar content and high total biomass. Currently, little is known about the nutrient demand for SS or how it responds to tillage and fertilization. The objectives of this study were to: 1) evaluate the effects of tillage and phosphorus (P) and potassium (K) fertilization on SS agronomics, 2) evaluate nitrogen (N), P, and K uptake and nutrient partitioning in SS, 3) determine P and K maintenance fertilization rates for sugar and cellulosic ethanol production, and 4) evaluate the effects of tillage and maintenance fertilization on soil test extractable P and K at three depths after four years of a monocrop system. A split-plot, randomized complete block design with four replications was used to evaluate the effects of two tillage treatments (no-till system (NT) and conventional tillage (CT)) and two fertilization treatments (with “maintenance” (MF) and without “maintenance” (NMF)) on SS production from 2012 to 2015. The MF applied 45 and 67 kg ha-1 of P2O5 and K2O, respectively. The CT decreased days to 50% heading and increased the initial plant population. The NT increased the number of harvestable stalks which were derived from tillers. The MF increased plant height, stalk diameter, total biomass, and stalk biomass. The NT increased the P removal rate in green leaves. The MF application increased K concentration of stalk, green leaves, and the total K removal rate of the whole plant. The MF increased the P removal rate in the stalk. A 75 Mg ha-1 of SS would remove 40 and 145 kg ha-1 of P2O5 and K2O, respectively, when only the stalk is harvested. When the whole plant is removed, approximately 78 and 193 kg ha-1 of P2O5 and K2O would be removed, respectively. The MF application increased soil test exactable P at the 15 to 30 cm soil depth. Soil test extractable K was not affected by tillage and fertilization across the different soil depths

What Causes My Test Alarm? Automatic Cause Analysis for Test Alarms in System and Integration Testing

Driven by new software development processes and testing in clouds, system and integration testing nowadays tends to produce enormous number of alarms. Such test alarms lay an almost unbearable burden on software testing engineers who have to manually analyze the causes of these alarms. The causes are critical because they decide which stakeholders are responsible to fix the bugs detected during the testing. In this paper, we present a novel approach that aims to relieve the burden by automating the procedure. Our approach, called Cause Analysis Model, exploits information retrieval techniques to efficiently infer test alarm causes based on test logs. We have developed a prototype and evaluated our tool on two industrial datasets with more than 14,000 test alarms. Experiments on the two datasets show that our tool achieves an accuracy of 58.3% and 65.8%, respectively, which outperforms the baseline algorithms by up to 13.3%. Our algorithm is also extremely efficient, spending about 0.1s per cause analysis. Due to the attractive experimental results, our industrial partner, a leading information and communication technology company in the world, has deployed the tool and it achieves an average accuracy of 72% after two months of running, nearly three times more accurate than a previous strategy based on regular expressions.Comment: 12 page

LTLf satisfiability checking

We consider here Linear Temporal Logic (LTL) formulas interpreted over \emph{finite} traces. We denote this logic by LTLf. The existing approach for LTLf satisfiability checking is based on a reduction to standard LTL satisfiability checking. We describe here a novel direct approach to LTLf satisfiability checking, where we take advantage of the difference in the semantics between LTL and LTLf. While LTL satisfiability checking requires finding a \emph{fair cycle} in an appropriate transition system, here we need to search only for a finite trace. This enables us to introduce specialized heuristics, where we also exploit recent progress in Boolean SAT solving. We have implemented our approach in a prototype tool and experiments show that our approach outperforms existing approaches

Fast LTL Satisfiability Checking by SAT Solvers

Satisfiability checking for Linear Temporal Logic (LTL) is a fundamental step in checking for possible errors in LTL assertions. Extant LTL satisfiability checkers use a variety of different search procedures. With the sole exception of LTL satisfiability checking based on bounded model checking, which does not provide a complete decision procedure, LTL satisfiability checkers have not taken advantage of the remarkable progress over the past 20 years in Boolean satisfiability solving. In this paper, we propose a new LTL satisfiability-checking framework that is accelerated using a Boolean SAT solver. Our approach is based on the variant of the \emph{obligation-set method}, which we proposed in earlier work. We describe here heuristics that allow the use of a Boolean SAT solver to analyze the obligations for a given LTL formula. The experimental evaluation indicates that the new approach provides a a significant performance advantage

rCOS: A refinement calculus for object systems

This article presents a mathematical characterization of object-oriented concepts by defining an observation-oriented semantics for a relational objectoriented language with a rich variety of features including subtypes, visibility, inheritance, type casting, dynamic binding and polymorphism. The language is expressive enough for the specification of object-oriented designs and programs. We also propose a calculus based on this model to support both structural and behavioral refinement of object-oriented designs. We take the approach of the development of the design calculus based on the standard predicate logic in Hoare and He’s Unifying Theories of Programming (UTP). We also consider object reference in terms of object identity as values and mutually dependent methods