Relative rate techniques were used to estimate k(OH+HFE-7100) ≈ 1.2 × 10 -14 cm 3 molecule -1 s -1 at 295 K leading to an estimate of ≈5 years for the atmospheric lifetime of HFE-7100 (HFE ) hydrofluoroether). Pulse radiolysis transient UV absorption spectroscopy was used to study the ultraviolet absorption spectra and kinetics of C 4 F 9 OCH 2 and C 4 F 9 OCH 2 O 2 radicals at 296 K. At 300 nm σ(C 4 F 9 OCH 2 ) ) (5.80 ( 0.76) × 10 -19 and at 250 nm σ(C 4 F 9 OCH 2 O 2 ) ) (2.24 ( 0.24) × 10 -18 cm 2 molecule -1 . Both UV spectra showed two absorption maxima, one below 230 nm and one at 290 nm. Rate constants for the self-reactions of C 4 F 9 OCH 2 and C 4 F 9 OCH 2 O 2 radicals, the reaction of C 4 F 9 OCH 2 radicals with O 2 , and the reactions of C 4 F 9 -OCH 2 O 2 radicals with NO and NO 2 were (3.5 ( 0.8) × 10 -11 , (1.35 ( 0.17) × 10 -11 (uncorrected for possible secondary chemistry), (2.5 ( 0.5) × 10 -12 , (8.5 ( 2.5) × 10 -12 , and (8.8 ( 1.8) × 10 -12 cm 3 molecule -1 s -1 , respectively. Using a pulse radiolysis method we measured k(F+HFE-7100) ) (1.6 ( 0.6) × 10 -11 cm 3 molecule -1 s -1 . Using a Fourier transform infrared spectroscopic technique rate, constants for the reaction of F and Cl atoms with HFE-7100 and Cl atoms with C 4 F 9 OC(O)H were determined to be (1.3 ( 0.3) × 10 -11 , (9.7 ( 1.4) × 10 -14 , and (1.6 ( 0.7) × 10 -14 cm 3 molecule -1 s -1 , respectively. Finally, it was determined that the sole atmospheric fate of C 4 F 9 OCH 2 O‚ radicals is reaction with O 2 to give C 4 F 9 OC(O)H (perfluorobutyl formate). The results are discussed with respect to the atmospheric chemistry of HFE-7100.
Recent studies suggest that children younger than 8 years old fail to use imagery instructions, resulting in memorial deficits. This inferior recall performance has been ascribed to encoding, storage, and/or retrieval deficiencies. One method recently used to assess the encoding/storage vs. the retrieval effects of imagery instructions on recall is to employ imagery instructions with or without a partial picture during the learning and/or recall phase of the study. The present study employed a 2 (imagery, no-imagery instructions) by 2 (partial picture during story, no par· tial picture during story) by 2 (partial picture during questioning, no partial picture during questioning) factorial design, with first·gradechildren as subjects. Recall of items specified in narrative passages was the dependent variable. Recall of narrative prose for 6-year-old children was consistently facilitated by partial pictures during story presentation. Imagery instructions were ineffective in facilitating recall.Child researchers have become increasingly interested in imagery as it relates to cognitive development. Pressley (1977), for example, suggests that the age span of 5-8 years is the crucial period in the development of imagery in cognitive processes. Piaget and Inhelder (1971) suggest that cognitive stages are highly related to the child's ability to manipulate images.Most of the recent child research has focused on the question of whether young school·age children employ imagery strategies as effectively as older children. Lesgold, Levin, Shirnron, and Guttman (1975) and Rohwer (1973) suggest that a lower probability exists in younger children relative to older children in their use of images. Current developmental research tends to sup· port their position. For example, Shirnron (1975) found that although recall performance of narrative passages was facilitated by imagery instructions presented to fourth·grade children, imagery instructions failed to aid recall memory of fust.graders. Guttman, Levin, and Pressley (1977) were concerned with the possible inter· active effects of imagery and visually presented illustra· tions on the recall of a prose passage. The research paradigm included a control condition in which only the story was read, an imagery instruction condition, a group that was shown a complete picture during the story, and a group that received the story accompanied by partial pictures. These partial pictures contained all the information included in the story except the to·be· remembered item. Thus, the object of interest (e.g., a
Deep learning is becoming increasingly adopted in business and industry due to its ability to transform large quantities of data into high-performing models. These models, however, are generally regarded as black boxes, which, in spite of their performance, could prevent their use. In this context, the field of eXplainable AI attempts to develop techniques that temper the impenetrable nature of the models and promote a level of understanding of their behavior.Here we present our contribution to XAI methods in the form of a framework that we term SpecXAI, which is based on the spectral characterization of the entire network. We show how this framework can be used to not only understand the network but also manipulate it into a linear interpretable symbolic representation.
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