Bar-Ilan University

About: Bar-Ilan University is a education organization based out in Ramat Gan, Israel. It is known for research contribution in the topics: Population & Poison control. The organization has 12835 authors who have published 34964 publications receiving 995648 citations. The organization is also known as: Bar Ilan University & BIU.

ROS and redox signalling in the response of plants to abiotic stress

Abstract: The redox state of the chloroplast and mitochondria, the two main powerhouses of photosynthesizing eukaryotes, is maintained by a delicate balance between energy production and consumption, and affected by the need to avoid increased production of reactive oxygen species (ROS). These demands are especially critical during exposure to extreme environmental conditions, such as high light (HL) intensity, heat, drought or a combination of different environmental stresses. Under these conditions, ROS and redox cues, generated in the chloroplast and mitochondria, are essential for maintaining normal energy and metabolic fluxes, optimizing different cell functions, activating acclimation responses through retrograde signalling, and controlling whole-plant systemic signalling pathways. Regulation of the multiple redox and ROS signals in plants requires a high degree of coordination and balance between signalling and metabolic pathways in different cellular compartments. In this review, we provide an update on ROS and redox signalling in the context of abiotic stress responses, while addressing their role in retrograde regulation, systemic acquired acclimation and cellular coordination in plants.

Organizational Learning: From Experience to Knowledge

Abstract: Organizational learning has been an important topic for the journal Organization Science and for the field. We provide a theoretical framework for analyzing organizational learning. According to the framework, organizational experience interacts with the context to create knowledge. The context is conceived as having both a latent component and an active component through which learning occurs. We also discuss current and emerging research themes related to components of our framework. Promising future research directions are identified. We hope that our perspective will stimulate future work on organizational learning and knowledge.

Ageing, fitness and neurocognitive function.

Abstract: In the ageing process, neural areas1,2 and cognitive processes3,4 do not degrade uniformly. Executive control processes and the prefrontal and frontal brain regions that support them show large and disproportionate changes with age. Studies of adult animals indicate that metabolic5 and neurochemical6 functions improve with aerobic fitness. We therefore investigated whether greater aerobic fitness in adults would result in selective improvements in executive control processes, such as planning, scheduling, inhibition and working memory. Over a period of six months, we studied 124 previously sedentary adults, 60 to 75 years old, who were randomly assigned to either aerobic (walking) or anaerobic (stretching and toning) exercise. We found that those who received aerobic training showed substantial improvements in performance on tasks requiring executive control compared with anaerobically trained subjects.

Breakdown of the internet under intentional attack.

Abstract: We study the tolerance of random networks to intentional attack, whereby a fraction $p$ of the most connected sites is removed. We focus on scale-free networks, having connectivity distribution $P(k)\ensuremath{\sim}{k}^{\ensuremath{-}\ensuremath{\alpha}}$, and use percolation theory to study analytically and numerically the critical fraction ${p}_{c}$ needed for the disintegration of the network, as well as the size of the largest connected cluster. We find that even networks with $\ensuremath{\alpha}\ensuremath{\le}3$, known to be resilient to random removal of sites, are sensitive to intentional attack. We also argue that, near criticality, the average distance between sites in the spanning (largest) cluster scales with its mass, $M$, as $\sqrt{M}$, rather than as ${log}_{k}M$, as expected for random networks away from criticality.

Self-similarity of complex networks.

Abstract: Complex networks have been studied extensively owing to their relevance to many real systems such as the world-wide web, the Internet, energy landscapes and biological and social networks. A large number of real networks are referred to as 'scale-free' because they show a power-law distribution of the number of links per node. However, it is widely believed that complex networks are not invariant or self-similar under a length-scale transformation. This conclusion originates from the 'small-world' property of these networks, which implies that the number of nodes increases exponentially with the 'diameter' of the network, rather than the power-law relation expected for a self-similar structure. Here we analyse a variety of real complex networks and find that, on the contrary, they consist of self-repeating patterns on all length scales. This result is achieved by the application of a renormalization procedure that coarse-grains the system into boxes containing nodes within a given 'size'. We identify a power-law relation between the number of boxes needed to cover the network and the size of the box, defining a finite self-similar exponent. These fundamental properties help to explain the scale-free nature of complex networks and suggest a common self-organization dynamics.