13,823 research outputs found

    Mentoring Functions and the Supervisory Relationship within Student Teaching

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    This study investigated the mentoring functions and the supervisory relationships of 20 preservice and cooperating teacher-dyads in student teaching. Utilizing three instruments, Mentoring Functions, Supervisory Relationship Measure (SRM), and Supervisory Relationship Questionnaire (SRQ), the compatibility of their mentoring perceptions, their level of satisfaction within their supervisory relationship, and the possible relatedness between the two were examined. The analyses of the results indicated that the mentoring perceptions of the dyads were highly compatible/congruent, with the highest degree of compatibility in the subscales of Advocacy and Role Modeling. Also, the dyads indicated that Coaching, Role Modeling, and Learning Facilitation were the three most important factors in mentoring. Additionally, it was determined that both groups had high degree of satisfaction in their supervisory relationship, more so for the cooperating teachers than for the preservice teachers. Finally, Mentoring Functions (mentoring perceptions) positively correlated to the SRQ (satisfaction) of the preservice teachers

    Most Complex Non-Returning Regular Languages

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    A regular language LL is non-returning if in the minimal deterministic finite automaton accepting it there are no transitions into the initial state. Eom, Han and Jir\'askov\'a derived upper bounds on the state complexity of boolean operations and Kleene star, and proved that these bounds are tight using two different binary witnesses. They derived upper bounds for concatenation and reversal using three different ternary witnesses. These five witnesses use a total of six different transformations. We show that for each n≥4n\ge 4 there exists a ternary witness of state complexity nn that meets the bound for reversal and that at least three letters are needed to meet this bound. Moreover, the restrictions of this witness to binary alphabets meet the bounds for product, star, and boolean operations. We also derive tight upper bounds on the state complexity of binary operations that take arguments with different alphabets. We prove that the maximal syntactic semigroup of a non-returning language has (n−1)n(n-1)^n elements and requires at least (n2)\binom{n}{2} generators. We find the maximal state complexities of atoms of non-returning languages. Finally, we show that there exists a most complex non-returning language that meets the bounds for all these complexity measures.Comment: 22 pages, 6 figure

    Asynchronous In Situ Processing with Gromacs: Taking Advantage of GPUs

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    International audienceNumerical simulations using supercomputers are producing an ever growing amount of data. Efficient production and analysis of these data are the key to future discoveries. The in situ paradigm is emerging as a promising solution to avoid the I/O bottleneck encountered in the file system for both the simulation and the analytics by treating the data as soon as they are produced in memory. Various strategies and implementations have been proposed in the last years to support in situ treatments with a low impact on the simulation performance. Yet, little efforts have been made when it comes to perform in situ analytics with hybrid simulations supporting accelerators like GPUs. In this article, we propose a study of the in situ strategies with Gromacs, a molecular dynamic simulation code supporting multi-GPUs, as our application target. We specifically focus on the computational resources usage of the machine by the simulation and the in situ analytics. We finally extend the usual in situ placement strategies to the case of in situ analytics running on a GPU and study their impact on both Gromacs performance and the resource usage of the machine. We show in particular that running in situ analytics on the GPU can be a more efficient solution than on the CPU especially when the CPU is the bottleneck of the simulation

    Heat transport study of the spin liquid candidate 1T-TaS2

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    We present the ultra-low-temperature thermal conductivity measurements on single crystals of the prototypical charge-density-wave material 1TT-TaS2_2, which was recently argued to be a candidate for quantum spin liquid. Our experiments show that the residual linear term of thermal conductivity at zero field is essentially zero, within the experimental accuracy. Furthermore, the thermal conductivity is found to be insensitive to the magnetic field up to 9 T. These results clearly demonstrate the absence of itinerant magnetic excitations with fermionic statistics in bulk 1TT-TaS2_2 and, thus, put a strong constraint on the theories of the ground state of this material.Comment: 5 pages, 3 figure

    Study of fungicidal properties of colloidal silver nanoparticles (AgNPs) on trout egg pathogen, Saprolegnia sp.

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    Silver nanoparticles (AgNPs) are known to have bactericidal and fungicidal effects. Since, there is few information available on the interaction of colloidal nanosilver with fish pathogens. Hence, the current study investigated the effects of colloidal AgNPs on the in vitro growth of the fish pathogen Saprolegnia sp.. Before the experiments, various important properties of AgNPs were well-characterized. The antifungal activity of AgNPs was then evaluated by determining the minimum inhibitory concentrations (MICs) using two-fold serial dilutions of colloidal nanosilver in a glucose yeast extract agar at 22ºC. The growth of Saprolegnia sp. on the AgNPs agar treatments was compared to that of nanosilver-free agar as controls. The results showed that AgNPs have an inhibitory effect on the in vitro growth of the tested fungi. The MIC of AgNPs for Saprolegnia sp. was calculated at 1800 mg/L, which is equal to 0.18 percent. It seems that AgNPs could be a proper replacement for teratogenic and toxic agents, such as malachite green. In addition, the indirect use of AgNPs could be a useful method for providing new antifungal activity in aquaculture systems
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