A new derivative of our recently reported nonaromatic fluorenophyrin 5 named fluorenonephyrin 6 was synthesized over a sequence of six steps starting with commercially available fluorene as precursor. Our attempts to direct oxidation of 5 to 6 were not successful. Hence, we synthesized 2,7-bis(phenyl(1H-pyrrol-2-yl)methyl)-9-fluorenone (fluorenone tripyrrane) in five simple steps from fluorene, and condensed it with pentafluorobenzaldehyde under mild acidic conditions in CH 2 Cl 2 followed by oxidation with DDQ and chromatographic purification to afford fluorenonephyrin (9%). 6 was characterized and studied by HR-MS, 1D and 2D NMR spectroscopy, absorption, electrochemical and DFT/TD-DFT techniques. The DFT studies revealed that 6 was more distorted than 5 and that introduction of C=O in the macrocyclic core remarkably distorts the pyrrole rings of the dipyrrin unit from the mean plane of macrocyclic framework. The macrocycle showed a band at around 390 nm and a broad band at around 650 nm. The redox properties indicated that the macrocycle was highly electron-deficient in nature. TD-DFT studies were in accordance with the experimental observations.

A sandpile model is studied in which bonds of the system are inhibited for activity after a certain number of transmission of grains. This condition impels an unstable sand column to distribute grains only to those neighbors that have toppled less than m times. In this non-Abelian model grains effectively move faster than the ordinary diffusion ͑superdiffusion͒. A system size dependent crossover from Abelian sandpile behavior to a new critical behavior is observed for all values of the parameter m. ͓S1063-651X͑97͒51111-1͔ PACS number͑s͒: 05.40.ϩj, 05.70.Jk, 05.70.Ln The concept of self-organized criticality ͑SOC͒ was introduced to describe how a system, starting from an arbitrary initial condition may evolve to a scale free critical state following some specific dynamical rules while under the action of repeated external perturbations ͓1͔. Naturally occurring physical phenomena like sandpiles ͓2͔, forest fires ͓3͔, river networks ͓4͔, earthquakes ͓5͔, etc. are argued as systems showing SOC. To demonstrate the idea of SOC a simple model known as the ''sandpile'' model was introduced in which a stochastically driven cellular automata evolves under a nonlinear, diffusive, self-organizing mechanism leading to a nonequilibrium critical state ͓1͔.At present many different versions of the sandpile model are available. However, precise classification of various models in different universality classes in terms of their critical exponents is not yet fully complete and still attracts much attention ͓6͔. Among the different models most widely studied is the Abelian sandpile model ͑ASM͒ in which many analytical ͓7͔ as well as numerical ͓8͔ results are known. Some efforts have also been given towards the analytical calculation of avalanche size exponents ͓9,10͔. Second, a two-state sandpile model with stochastic evolution rules was also studied ͓11͔ that was initially thought to belong to the same universality class as that of ASM ͓11,12͔ but later claimed to be different ͓13͔.We consider a situation in which an intermediate time scale is associated with every bond of the system. Each bond allows only a certain number of grains to cross from its one end to the other and after that it has a dead time and cannot support any further traffic until a new avalanche starts. This dead time is much greater than the time scale of avalanche propagations but much less than the input rate of grains. We call this model as the ''sandpile model with activity inhibition'' ͑SMAI͒.Similar to different sandpile models we also define our model on a regular lattice with open boundary. Non-negative integer numbers (h i ) assigned at the lattice sites represent the heights of the sand columns. Sand grains are added at randomly chosen sites by increasing the h values by unity: h i →h i ϩ1. The possibility of a sand column becoming unstable arises only when the height h i becomes greater than a threshold value h c . Such a column becomes unstable only if the number n i of nearest-neighbor sites that have toppled less than a preassigned cutoff numb...