Interactive computation of radiation view factors

The development of a pair of computer programs to calculate the radiation exchange view factors is described. The surface generation program is based upon current graphics capabilities and includes special provisions which are unique to the radiation problem. The calculational program uses a combination of contour and double area integration to permit consideration of radiation with obstruction surfaces. Examples of the surface generation and the calculation are given

Dynamic Transformations of Genome-wide Epigenetic Marking and Transcriptional Control Establish T Cell Identity

T cell development comprises a stepwise process of commitment from a multipotent precursor. To define molecular mechanisms controlling this progression, we probed five stages spanning the commitment process using RNA-seq and ChIP-seq to track genome-wide shifts in transcription, cohorts of active transcription factor genes, histone modifications at diverse classes of cis-regulatory elements, and binding repertoire of GATA-3 and PU.1, transcription factors with complementary roles in T cell development. The results highlight potential promoter-distal cis-regulatory elements in play and reveal both activation sites and diverse mechanisms of repression that silence genes used in alternative lineages. Histone marking is dynamic and reversible, and though permissive marks anticipate, repressive marks often lag behind changes in transcription. In vivo binding of PU.1 and GATA-3 relative to epigenetic marking reveals distinctive factor-specific rules for recruitment of these crucial transcription factors to different subsets of their potential sites, dependent on dose and developmental context

Infection of the fishes with Ligula intestinalis and Bothriocephalus acheilognathi in Sattarkhan Dam, northwestern Iran

After an extensive fish mortality in Sattarkhan Dam, in East-Azarbaijan province during the year 2002, we collected 160 specimens of the fish Alburnus filippi and 5 specimens of the fish and Alburnoides bipunctatus to examine the cause of mortality. The samples measured biometrically an examined them for internal and external infections. We found that of the 160 specimens of Alburnus filippi, 131 (81.8%) were infected with Ligula intestinalis and 26 (16.25%) specimens were infected with Bothriocephalus acheilognathi. Of 5 specimens of Alburnoides bipunctatus, 4 (80%) were infected with Ligula intestinalis and no Bothriocephalus acheilognathi observed. This is the first report of the Ligula and Bothriocephalus parasites infecting fishes in the Sattarkhan Dam

A Semiparametric Estimation for Regression Functions in the Partially Linear Autoregressive Time Series Model

In this paper, a semiparametric method is proposed for estimating regression function in the partially linear autoregressive time series model . Here, we consider a combination of parametric forms and nonlinear functions, in which the errors are independent. Semiparametric and nonparametric curve estimation provides a useful tool for exploring and understanding the structure of a nonlinear time series data set to make for a more efficient study in the partially linear autoregressive model. The unknown parameters are estimated using the conditional nonlinear least squares method, and the nonparametric adjustment is also estimated by defining and minimizing the local L2 -fitting criterion with respect to the nonparametric adjustment and, with smooth-kernel method , these estimates are corrected. Then, the autoregression function estimators, which can be calculated with the sample and simulation data , are obtained. In this case , some strong and weak consistency and simulated results for the semiparametric estimation in this model are presented . The root mean square error and the average square error criterions are also applied to verify the efficiency of the suggested model

A Semiparametric Estimation for the Nonlinear Vector Autoregressive Time Series Model

In this paper, the nonlinear vector autoregressive model is considered and a semiparametric method is proposed to estimate the nonlinear vector regression function. We use Taylor series expansion up to the second order which has a parametric framework as a representation of the nonlinear vector regression function. After the parameters are estimated through the least squares method, the obtained nonlinear vector regression function is adjusted by a nonparametric diagonal matrix, and the proposed diagonal matrix is also estimated through the nonparametric smooth-kernel approach. Estimating the parameters can yield the desired estimate of the vector regression function based on the data. Under some conditions, the asymptotic consistency properties of the proposed semiparametric method are established. In this case, some simulated results for the semiparametric estimators in a nonlinear vector autoregressive function are presented. Mean Squares Error (MSE) criterion is also applied to verify the accuracy and the efficiency of the suggested model. The results of the study indicate the accuracy of the suggested model. Furthermore, the method is applied for the Retail Trade Survey to provide short-term economic indicators of the retail trade sector. The hypothesis of nonlinearity in the vector autoregression function model is also considered by the use of principal components. We use this test for the Retail Trade Survey (RTS) data which is considered to provide short-term economic indicators of the retail trade sector. Here, we use a nonlinear vector autoregression function model to forecast the sales of fresh, takeaway, supermarket, and café restaurant food in New Zealand during 2000 to 2010 on yearly basis. For our empirical example, the test of nonlinearity clearly indicates our model is nonlinear

Comparative survey on anesthetizing effects of medicinal herbs Valerian officinalis, Melissa officinalis, Papaver somniferum, and Papaver bracteatum on gold fish (Carassius auratus)

Anesthetic drugs are widely used aquaculture farms and can create consumption problems for humans, so there is a great need to safer drugs. With regard to long record of herbal drugs consumption in Iran and their benefits, we survey the possibility of using Valerian officinalis, Melissa officinalis, Papaver somniferum, and P. bracteatum as fish anesthetic. We provided, processed, and made consistent extractions of V. officinalis (2, 3 4g/lit), M. officinalis (5, 10, 15g/lit), P. somniferum (0.85, 1.6, 3.2g/lit) and P. bracteatum (0.3, 0.6, 0.9g/lit). We selected 60 goldfish Carassius auratus in the weight range of 7.41 plus or minus 0/2g, and the length range of 8.4 plus or minus 0/11cm and kept them in laboratory conditions under the same oxygen and temperature. The fish were divided into four groups each containing 15 fish and further into three subgroups of five fish each. During the experiments, two herbs P. somniferum and P. bracteaturn were eliminated from statistical analysis because of biased results

Comparison of different nitrogen compounds in three different environments of the Gwatar shrimp farms complex in the Gwatar Gulf region (Baluchestan-Iran)

This study aimed to investigate the quality of effluent water of a large shrimp farming complex in Chabahar region in Sistan and Baluchestan province (Iran). Fifteen sampling stations were designated in three distinct areas of these farms; i.e. the water supply canal, the drainage canal and the receiving area of the farm effluents in Gwatar Gulf. Water samples were taken from June to December 2004 for measurement and monitoring of nitrate, nitrite and ammonia compounds. The results revealed that the shrimp farms effluents have a profound effect on the water quality and aquatic environment of the drainage canal and the Gwatar Gulf. The average concentration of nitrate, nitrite and ammonia remained considerably higher in the drainage canal and Gwatar Gulf compared to the supply canal throughout the study. The amount of these compounds increased considerably in the drainage canal during the final stages of culture period and in Gwatar Gulf at post monsoon. The results of one way analysis of variance (at P<0.01 level) showed that all physical and chemical factors except water temperature were significantly different between stations. Considering that more than 25% of the shrimp farms of this complex were active during this study the measured values of nitrate, nitrite and ammonia compounds in the effluents were at the optimum range recommended for the shrimp farms

Structure and stability of molecular crystals with many body dispersion inclusive density functional tight binding

Accurate prediction of structure and stability of molecular crystals is crucial in materials science and requires reliable modeling of long-range dispersion interactions. Semi-empirical electronic structure methods are computationally more efficient than their ab initio counterparts, allowing structure sampling with significant speedups. Here, we combine the Tkatchenko-Scheffler van-der-Waals method (TS) and the many body dispersion method (MBD) with third-order density functional tight-binding (DFTB3) via a charge population-based method. We find an overall good performance for the X23 benchmark database of molecular crystals, despite an underestimation of crystal volume that can be traced to the DFTB parametrization. We achieve accurate lattice energy predictions with DFT+MBD energetics on top of vdW-inclusive DFTB3 structures, resulting in a speedup of up to 3000 times compared to a full DFT treatment. This suggests that vdW-inclusive DFTB3 can serve as a viable structural prescreening tool in crystal structure prediction

Quality of life, Work ability and other important indicators of women's occupational health

Objectives: Work ability may be considered as an important aspect of well-being and health status. One of the most important factors in association with work ability is health-related quality of life (HRQoL). The aim of this study has been to determine the association between work ability, individual characteristics and HRQoL of female workers. Material and Methods: The design of this study has been cross-sectional. The work ability index (WAI) and Short-Form General Health Survey (SF-12) questionnaires were used to collect data. Three hundred and twenty female workers were selected from food supplier factories in Karaj. One-way analysis of variance, Pearson's correlation analysis, independent sample t-test and multiple linear regression methods were used to analyze data. Results: Mean (M) and standard deviation (SD) of the WAI stood at 35.02 and 5.57, respectively. The categories of the WAI for women being as follows: 8.8 poor, 62 moderate, 25.4 good and 3.7 excellent. Mean±SD for the physical component summary (PCS) and mental component summary (MCS) of quality of life was 58.84±11.12 and 57.45±9.94, respectively. There was a positive significant association between the PCS and MCS with the WAI (p = 0.0001). Workers with higher education had a better work ability (p = 0.002) and shift-work workers had a worse work ability (p = 0.03). Conclusions: Work ability of majority of women was moderate. Considering mean age of studied women (27.6 years old), this work ability is not satisfactory. Physical and mental components of the HRQoL were the important factors associated with work ability

BoXHED2.0: Scalable boosting of dynamic survival analysis

Modern applications of survival analysis increasingly involve time-dependent covariates. In healthcare settings, such covariates provide dynamic patient histories that can be used to assess health risks in realtime by tracking the hazard function. Hazard learning is thus particularly useful in healthcare analytics, and the open-source package BoXHED 1.0 provides the first implementation of a gradient boosted hazard estimator that is fully nonparametric. This paper introduces BoXHED 2.0, a quantum leap over BoXHED 1.0 in several ways. Crucially, BoXHED 2.0 can deal with survival data that goes far beyond right-censoring and it also supports recurring events. To our knowledge, this is the only nonparametric machine learning implementation that is able to do so. Another major improvement is that BoXHED 2.0 is orders of magnitude more scalable, due in part to a novel data preprocessing step that sidesteps the need for explicit quadrature when dealing with time-dependent covariates. BoXHED 2.0 supports the use of GPUs and multicore CPUs, and is available from GitHub: www.github.com/BoXHED.Comment: 12 page