A Nonlinear Mixed-Effects Model for Multivariate Longitudinal Data with Dropout with Application to HIV Disease Dynamics

The main challenge in biomedical and clinical studies which involve collection of longitudinal data is the premature withdrawal of the subjects from the study resulting in incomplete data. Standard statistical analysis approaches usually give biased estimates of the model parameters if the mechanisms that led to dropout are ignored. In this discussion, we consider nonlinear mixed-effects models for multivariate longitudinal data in the presence of subject dropout. We present techniques for estimation of model parameters. These procedures are applied to estimate the parameters in the HIV dynamic system using routine observational data from an HIV clinic.     

Limits to agricultural growth in the Sistan Closed Inland Delta,Iran

The Sistan Delta in Iran is located at the end of a closed basin with nearly 100% of the supply coming from Afghanistan. This supply is supporting irrigated agriculture in the area and is the source for the lake system around the delta. These Hamoun lakes are ecological very valuable wetlands; a number of them are registered as Ramsar sites. The Iranian government tries to improve the living conditions of the people in the area, among others by providing infrastructure for irrigated agriculture. Further development of the irrigated area will mean less water for the Hamouns with resulting lower average water coverage of the lakes. This will not only endanger the ecosystem that the Hamouns support but also the livelihoods of the people that depend on the goods and services that the lakes provide. This paper describes a study that has been carried out to support decision making on potential development schemes in the delta. The non-availability of data from Afghanistan requires the development of various tools and the use of remote sensing techniques to enable to make estimates for the river flow that Iran can expect from Afghanistan. An IWRM approach has been used for the balancing of interests involved. Some preliminary conclusions are described.     

Productive efficiency of the sandfish <Emphasis Type="Italic">Arctoscopus japonicus</Emphasis> coastal gillnet fishery using stochastic frontier analysis

It is important to estimate the productive efficiencies of industries, especially the fishing industry, in order to determine policies that can improve business conditions. In this study, the productive efficiency of the sandfish coastal gillnet fishery on the east coast of Korea has been estimated using stochastic frontier analysis (SFA). A translog production function wherein the inefficiency was represented by a truncated-normal distribution was established; the output variable was the trip production quantity, the input variables were physical production factors directly related to the fishing activities of vessels, such as tonnage, horsepower, and the number of employed fishers. The average productive efficiency of the sample was 0.59 [0.40–0.79], which implied that productive inefficiency occurs in sandfish coastal gillnet vessels. Moreover, it was verified that there are no differences among the average productive efficiencies of fishing vessels of different tonnages.     

Comparison of larval thermal maxima between <Emphasis Type="Italic">Fundulus heteroclitus</Emphasis> and <Emphasis Type="Italic">F. grandis</Emphasis>

Fundulus heteroclitus and F. grandis are resident salt marsh fishes that overlap in distribution over a narrow range in northeastern Florida. The objective of the present study was to examine whether the limits of the species’ ranges could be explained by differences in thermal tolerance. Two populations of each species were collected and then spawned in the laboratory, and 9-day-old larvae were used for critical thermal maxima trials. Mean LOE temperatures of larvae ranged from 43.04 to 43.65°C and showed little difference between species. Therefore, differences in high temperatures experienced cannot account for the differences of the distributions of the two species. Condition-specific competition may play a greater role in determining the observed range of the two species.     

Fe<Superscript>2+</Superscript> and Mn<Superscript>2+</Superscript>, potential agents to induce suppression of <Emphasis Type="Italic">Fusarium oxysporum</Emphasis> for biological soil disinfestation

Here Fusarium oxysporum was killed in exudates obtained from soil biologically disinfested with ethanol, indicating that physical interaction with soil microorganisms was not essential. Because acetic acid was confirmed to accumulated during the treatment, we evaluated the effect of acetic acid amendment against the pathogen in plastic containers. A drop in the soil redox potential seemed to be correlated with the fungicidal efficacy of acetic acid. Under reductive soil conditions, metal ions such as Mn²⁺ and Fe²⁺ formed, and the pathogen was effectively suppressed in Mn²⁺ and Fe²⁺ solution. Therefore, Fe²⁺ and Mn²⁺ may be the agents that induce suppression of the pathogen during biological soil disinfestation.     

Characterizing rangeland vegetation using Landsat and 1-mm VLSA data in central Wyoming (USA)

As an alternative to ground-cover data collection by conventional and expensive sampling techniques, we compared measurements obtained from very large scale aerial (VLSA) imagery for calibrating moderate resolution Landsat data. Using a grid-based sampling scheme, 162 VLSA images were acquired at 100 m above ground level. The percent vegetation cover in each photo was derived using SamplePoint (a manual inventory method) and VegMeasure (a reflectance based, automated method). Approximately two-thirds of the VLSA images were used for calibrating Landsat data while the remainder was used for validation. Regression models with Landsat bands accounted for 55% of the VegMeasure-based measurements of vegetation, whereas models that included both Landsat bands and elevation data accounted for 67%. The relationship between the Landsat bands and the percent vegetation cover measured by SamplePoint was lower (R ² = 20%), highlighting the differences between the inventory and reflectance based protocols. Results from the model validation indicated that the model’s predictive power was lower when the vegetation cover was either <20% or >55%. Additional work is needed in these ecosystems to improve the calibration techniques for sites with low and high vegetation cover; however, these results demonstrate the VLSA imagery could be used for calibrating Landsat data and deriving rangeland vegetation cover. By adopting such methodologies the US Federal land management agencies can increase the efficiency of the monitoring programs in Wyoming and in other western states of the US. Mention of trade names is for information only and does not imply endorsement by USDA over comparable products or services.     

Quantitative trait loci influencing fruit-related characteristics of tomato grown in high-temperature conditions

The objective of this study was to identify molecular markers linked to fruit-related traits in the tomato subjected to high temperatures. In total, 160 F₂ plants derived from a cross between a heat-tolerant breeding line, CL5915-93D4-1-0-3 (Solanum esculentum), and a heat-sensitive wild accession, L4422 (S. pimpinellifolium), were grown in a greenhouse. Six traits including fruit number, fruit weight, brix, seed number, fruit setting, and flower number were scored. The distributions of fruit number, fruit set, flower number, and seed number were skewed towards heat susceptibility which is known to be characteristic of L4422. Polymorphic bands were generated by PCR-derived methods of RAPD, ISSR and AFLP Polymorphism, the segregation ratio, and distribution over the genome of the above 3 markers were compared. Ten linkage groups, ranging 20.6–151.6 cM in size, were constructed with 62 informative markers spanning a total of 776.3 cM. Fruit-related quantitative trait loci (QTLs) were non-randomly distributed in the tomato genome. For the 6 traits investigated, 21 QTLs were dispersed on linkage groups 2–5. The genetic effects of the various QTLs were differently exhibited, in our study we have respectively found from 10.5% to 30.2% of the variation explained by the QTL for flower number (FRN4) and brix (BX2). Thirteen QTL-mapped markers were unique to 1 trait, and 4 markers were linked to more than 1 trait. Among them, QTLs linked to the I868-470 marker had effects on fruit weight and brix, and a significant positive correlation between these 2 traits was noted (r = 0.35, P < 0.05). Thus, the I868-470 marker may have the potential for simultaneous selection of high fruit weight and brix. These markers also allowed us to align genome linkage maps across distantly related species and to reveal the co-localization between these QTLs and major genes.     

浅析无线路由器信号覆盖范围的拓展

由干无线网络设备的有效信号覆盖范围限制,在实际应用中经常出现无信号或信号不稳定现象,本文根据无线局域网中核心设备无线路由器的特点,总结了信号覆盖范围拓展的常用方法.并重点讨论了采用WDS技术连接多个路由器来拓展信号覆盖范围的方法,并给出了具体的配置步骤.     

Adaptation of regional digital soil mapping for precision agriculture

In the initial phase of a national project to map clay, sand and soil organic matter (SOM) content in arable topsoil in Sweden, a study area in south-west Sweden comprising about 100 000 ha of arable land was assessed. Models were created for texture, SOM and two estimated variables for lime requirement determination (target pH and buffering capacity), using a data mining method (multivariate adaptive regression splines). Two existing reference soil datasets were used: a grid dataset and a dataset created for individual farms. The predictor data were of three types: airborne gamma-ray spectrometry data, digital elevation from airborne laser scanning, and legacy data on Quaternary geology. Validations were designed to suit applicability assessments of prediction maps for precision agriculture. The predictor data proved applicable for regional mapping of topsoil texture at 50 × 50 m² spatial resolution (root mean square error: clay = 6.5 %; sand = 13.2 %). A novel modelling strategy, ‘Farm Interactive’, in which soil analysis data for individual farms were added to the regional data, and given extra weight, improved the map locally. SOM models were less satisfactory. Variable-rate application files for liming created from derived digital soil maps and locally interpolated soil data were compared with ‘ground truth’ maps created by proximal sensors on one test farm. The Farm Interactive methodology generated the best predictions and was deemed suitable for adaptation of regional digital soil maps for precision agricultural purposes.