Assessing the impact of transformational leadership, organizational climate, and personality on individual innovativeness at work

Innovation is critical for any organization’s success in the twenty first century. Organizations are continuously seeking to create new products and services to differentiate themselves from their completion and to create a competitive advantage in the dynamic global business environment. In order for this to occur, the organization needs to encourage employee creativity. Furthermore, leaders in the organization also need to work with the employees to help guide and support them as they embark on the development of products and services. This study examined this organizational environment by assessing the impact that the organizational climate promotes innovation. It also assessed if transformational leadership where the leader works with the employee to identify changes and create a vision to implement these changes. The study also investigated the effect of employee personality on individual innovativeness at work. The results of the study suggest a positive and significant relationship between organizational climate, transformational leadership, and individual innovativeness at work. Employee openness and extraversion showed a positive and significant relationship also to employee innovativeness while the intuition personality type did not show a positive relationship. The extraversion personality trait also moderated the relationship between organizational climate, transformational leadership, and individual innovativeness at work. The results of the study confirm the role of the organization, leader, and employee in creating and implementing creative products and services in the work place

Physical Activity and Obesity Indicators: National Cross Sectional Study on Lebanese Adults

Association between higher levels of physical activity and lower rates of obesity has been shown. The aim is to assess the relation between the prevalence of physical activity and the Physical Activity Index (PAI) of 300 Lebanese healthy adults, with age, gender, occupation, body mass indices and waist circumferences (WC). The cutoff points of WC for both genders were determined using the values of Body Mass Index (BMI). A cross-sectional study using self-reported valid questionnaire was conducted randomly on 150 men and 150 women, between 18 and 74 years, from Beirut region. Association between variables was performed using chi2, T-Test and ANOVA. Linear regression determined the WC cutoffs based on BMI. 22% of the population was obese with WC mean level of 92.47±14.4cm (87.71±14.4 cm for women and 97.24±12.96 cm for men). The prevalence of physical activity was 34% in overall population (27% in women and 40% in men).There was no significant association between BMI values and PAI (p< 0.085 for men and p< 0.300 for women). However there was an inverse association between WC values and PAI in both genders (p<0.043 in men and p< 0.036 in women). Linear regression showed WC cut-off point in Lebanese women with BMI ≥25 kg/m2 and ≥30 kg/m2 of 86 cm and 100 cm respectively, whereas for men it was 92.12 cm and 105 cm respectively. The prevalence of physical activity in Beirut is low with differences among genders. The highest physical activity index is associated with the decreased values of waist circumference

Application of smart classification techniques to non-destructive testing of composites

Composites manufactured for applications in the automotive industry were non-destructively tested to determine damage using the following techniques: (1) Low frequency tapping. (2) High frequency (C-Scan). (3) Visual imaging. (4) Low and high temperature pulse video thermography. Various levels of impact energy were applied to the following types of composites (I) RIM: Reaction injection moulded. (II) Woven Glass. (III) GMT: Glass mat thermoplastic. Some interesting results were obtained which could be explained through analytical and numerical modelling. These results were analyzed through developments of the following algorithms: (a) A novel approach to damage detection using wavelength variation and sequence grouping software. (b) Correlation of the various NDT techniques through one mathematical equation and software. (c) The introduction of the uniformity factor concept and software to account for variations among samples quality in relation to experimental results. (d) The development of smart classification system together with standard neural network algorithms for prediction and classification. The objectives of this research were all achieved

A priori testing of sparse adaptive polynomial chaos expansions using an ocean general circulation model database

This work explores the implementation of an adaptive strategy to design sparse ensembles of oceanic simulations suitable for constructing polynomial chaos surrogates. We use a recently developed pseudo-spectral algorithm that is based on a direct application of the Smolyak sparse grid formula and that allows the use of arbitrary admissible sparse grids. The adaptive algorithm is tested using an existing simulation database of the oceanic response to Hurricane Ivan in the Gulf of Mexico. The a priori tests demonstrate that sparse and adaptive pseudo-spectral constructions lead to substantial savings over isotropic sparse sampling in the present setting.United States. Office of Naval Research (award N00014-101-0498)United States. Dept. of Energy. Office of Advanced Scientific Computing Research (award numbers DE-SC0007020, DE-SC0008789, and DE-SC0007099)Gulf of Mexico Research Initiative (contract numbers SA1207GOMRI005 (CARTHE) and SA12GOMRI008 (DEEP-C)

Fractal analysis of microCT images of the oviduct during the estrous cycle

It is well known that the oviduct plays a key role in several events deeply related with reproduction, such as sperm storage and capacitation, gametes interactions, fertilization and early embryo development, among others. To better understand some of the interactions and process occurring withing this organ, the study of its morphological modifications is of primordial importance. To that, we adopted a microtomografy (MicroTC) modelling system and the fractal analysis that allow to explore the 3D oviductal functional anatomy, by using eight swine oviducts at different stages of the estrous cycle. MicroCT datasets were acquired by using the high-resolution 3D-imaging system Skyscan 1172G (Bruker, Kontich – Belgium). CT images were analyzed using plugin on ImageJ software (NIH, Bethesda, MD), a box-counting method was applied to calculate the Fractal dimension of the oviduct. Focusing our attention on the utero-tubal junction (involved in sperm selection) and the isthmo-ampullar junction (the fertilization site). We found that by using PCA analysis it was possible to clearly differentiate the oviduct at different cycle stage on the basis of their values for: Db for grid, lacunarity for grid, R2 for Db, Media Db, lacunarity, σ for D for Db, Max for D, Min for D. Lacunarity, Media and Max for Db have a greater influence on the analysis. The results showed that 2 principal components were associated whit the morphological changes. This information, is obtained by a fast nondestructive method, and could be very useful because this innovative approach enables the achievement a 3D model and suggest that using fractal analysis techniques can aid to better understand the modifications of oviduct anatomy that depends on the neuroendocrine axis. This innovative approach could be a start point to design 3D cell culture systems, that could be applied in human and animal assisted reproductive techniques, improving the IVF outcomes

Greensporone A, a fungal secondary metabolite suppressed constitutively activated AKT via ROS generation and induced apoptosis in leukemic cell lines

Greensporone A is a fungal secondary metabolite that has exhibited potential in vitro for anti-proliferative activity in vitro. We studied the anticancer activity of greensporone A in a panel of leukemic cell lines. Greensporone A-mediated inhibition of proliferation is found to be associated with the induction of apoptotic cell death. Greensporone A treatment of leukemic cells causes inactivation of constitutively activated AKT and its downstream targets, including members GSK3 and FOXO1, and causes downregulation of antiapoptotic genes such as Inhibitor of Apoptosis (IAPs) and Bcl-2. Furthermore, Bax, a proapoptotic member of the Bcl-2 family, was found to be upregulated in leukemic cell lines treated with greensporone A. Interestingly, gene silencing of AKT using AKT specific siRNA suppressed the expression of Bcl-2 with enhanced expression of Bax. Greensporone A-mediated increase in Bax/Bcl-2 ratio causes permeabilization of the mitochondrial membrane leading to the accumulation of cytochrome c in the cytoplasm. Greensporone A-induced cytochrome c accumulation causes the activation of caspase cascade and cleavage of its effector, poly(ADP-ribose) polymerase (PARP), leading to apoptosis. Greensporone A-mediated apoptosis in leukemic cells occurs through the generation of reactive oxygen species (ROS) due to depletion of glutathione (GSH) levels. Finally, greensporone A potentiated the anticancer activity of imatinib in leukemic cells. In summary, our study showed that greensporone A suppressed the growth of leukemic cells via induction of apoptotic cell death. The apoptotic cell death occurs by inhibition of AKT signaling and activation of the intrinsic apoptotic/caspase pathways. These results raise the possibility that greensporone A could be developed as a therapeutic agent for the treatment of leukemia and other hematological malignancies.Qatar University , University of North Carolina, National Palliative Care Research Center, Jordan University of Science and Technolog

SnoRNAs and miRNAs networks underlying COVID-19 disease severity

There is a lack of predictive markers for early and rapid identification of disease progression in COVID-19 patients. Our study aims at identifying microRNAs (miRNAs)/small nucleolar RNAs (snoRNAs) as potential biomarkers of COVID-19 severity. Using differential expression analysis of microarray data (n = 29), we identified hsa-miR-1246, ACA40, hsa-miR-4532, hsa-miR-145-5p, and ACA18 as the top five differentially expressed transcripts in severe versus asymptomatic, and ACA40, hsa-miR-3609, ENSG00000212378 (SNORD78), hsa-miR-1231, hsa-miR-885-3p as the most significant five in severe versus mild cases. Moreover, we found that white blood cell (WBC) count, absolute neutrophil count (ANC), neutrophil (%), lymphocyte (%), red blood cell (RBC) count, hemoglobin, hematocrit, D-Dimer, and albumin are significantly correlated with the identified differentially expressed miRNAs and snoRNAs. We report a unique miRNA and snoRNA profile that is associated with a higher risk of severity in a cohort of SARS-CoV-2 infected patients. Altogether, we present a differential expression analysis of COVID-19-associated microRNA (miRNA)/small nucleolar RNA (snoRNA) signature, highlighting their importance in SARS-CoV-2 infection

Application of smart classification techniques to non-destructive testing of composites

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