Understanding the Determinantsof Project Performance: Empirical Evidencesfrom Software Houses of Pakistan

Thisstudy is investigating the effects of project quality, project risk and project governance on project performance. Moreover, this study investigatesthe moderation effect of project leadership on these relationships. Data is collected from 354 respondents of software houses and structural equation modeling (SEM) technique is utilized for data analysis. Results suggest that project quality, project risk and project leadership have positive significant impact on project performance while project governance does not have significant impact on project performance. Significant moderation effect of project leadership on the relationship between project quality and project performance is proved but project leadership has no moderation effect on the relationship between project governance, project risk and project performance. The findings of the study provide significant insights forsoftware houses ofPakistan to formulate strategies in order to develop a governance framework and enhance project performance in IT project management

Nomogram based on computed tomography images and clinical data for distinguishing between primary intestinal lymphoma and Crohn’s disease: a retrospective multicenter study

BackgroundDifferential diagnosis of primary intestinal lymphoma (PIL) and Crohn’s disease (CD) is a challenge in clinical diagnosis.AimsTo investigate the validity of the nomogram based on clinical and computed tomography (CT) features to identify PIL and CD.MethodsThis study retrospectively analyzed laboratory parameters, demographic characteristics, clinical manifestations, and CT imaging features of PIL and CD patients from two centers. Univariate logistic analysis was performed for each variable, and laboratory parameter model, clinical model and imaging features model were developed separately. Finally, a nomogram was established. All models were evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA).ResultsThis study collected data from 121 patients (PIL = 69, CD = 52) from Center 1. Data from 43 patients (PIL = 24, CD = 19) were collected at Center 2 as an external validation cohort to validate the robustness of the model. Three models and a nomogram were developed to distinguish PIL from CD. Most models performed well from the external validation cohort. The nomogram showed the best performance with an AUC of 0.921 (95% CI: 0.838–1.000) and sensitivities, specificities, and accuracies of 0.945, 0.792, and 0.860, respectively.ConclusionA nomogram combining clinical data and imaging features was constructed, which can effectively distinguish PIL from CD

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P \u3c 2.25 × 10−6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P \u3c 1 × 10−3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize

Genome-wide association study uncovers new genetic loci and candidate genes underlying seed chilling-germination in maize

As one of the major crops, maize (Zea mays L.) is mainly distributed in tropical and temperate regions. However, with the changes of the environments, chilling stress has become a significantly abiotic stress affecting seed germination and thus the reproductive and biomass accumulation of maize. Herein, we investigated five seed germination-related phenotypes among 300 inbred lines under low-temperature condition (10 °C). By combining 43,943 single nucleotide polymorphisms (SNPs), a total of 15 significant (P < 2.03 ×  10-6) SNPs were identified to correlate with seed germination under cold stress based on the FarmCPU model in GWAS, among which three loci were repeatedly associated with multiple traits. Ten gene models were closely linked to these three variations, among which Zm00001d010454, Zm00001d010458, Zm00001d010459, and Zm00001d050021 were further verified by candidate gene association study and expression pattern analysis. Importantly, these candidate genes were previously reported to involve plant tolerance to chilling stress and other abiotic stress. Our findings contribute to the understanding of the genetic and molecular mechanisms underlying chilling germination in maize

DEA based production planning considering technology heterogeneity with undesirable outputs

Many researchers have concentrated on production planning issues by using data envelopment analysis (DEA). However, the assumption made by existing approaches that all decision making units (DMUs) are equipped with the same level of production technology is not realistic. Additionally, with the development in the society, environmental factors have come to play important roles in the production process as well. Thus, undesirable outputs should be considered in production planning problems. Therefore, this paper considers the technology heterogeneity factors and undesirable outputs using the data envelopment analysis-based production planning approach. Two examples containing a numerical example that compare with other method and a real sample that concerns the industrial development of 30 provinces in China are used to validate the applicability of our approach

Table_1_Nomogram based on computed tomography images and clinical data for distinguishing between primary intestinal lymphoma and Crohn’s disease: a retrospective multicenter study.DOCX

BackgroundDifferential diagnosis of primary intestinal lymphoma (PIL) and Crohn’s disease (CD) is a challenge in clinical diagnosis.AimsTo investigate the validity of the nomogram based on clinical and computed tomography (CT) features to identify PIL and CD.MethodsThis study retrospectively analyzed laboratory parameters, demographic characteristics, clinical manifestations, and CT imaging features of PIL and CD patients from two centers. Univariate logistic analysis was performed for each variable, and laboratory parameter model, clinical model and imaging features model were developed separately. Finally, a nomogram was established. All models were evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, and decision curve analysis (DCA).ResultsThis study collected data from 121 patients (PIL = 69, CD = 52) from Center 1. Data from 43 patients (PIL = 24, CD = 19) were collected at Center 2 as an external validation cohort to validate the robustness of the model. Three models and a nomogram were developed to distinguish PIL from CD. Most models performed well from the external validation cohort. The nomogram showed the best performance with an AUC of 0.921 (95% CI: 0.838–1.000) and sensitivities, specificities, and accuracies of 0.945, 0.792, and 0.860, respectively.ConclusionA nomogram combining clinical data and imaging features was constructed, which can effectively distinguish PIL from CD.</p

Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Kernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P P Arabidopsis CUC1, CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.This article is published as Liu, Min, Xiaolong Tan, Yan Yang, Peng Liu, Xiaoxiang Zhang, Yinchao Zhang, Lei Wang et al. "Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping." Plant biotechnology journal (2019). doi: 10.1111/pbi.13188.</p