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This paper describes a series of twelve 9,10-dimethoxyanthracene derivatives functionalized with a range of electronically diverse ethynyl substituents at the 2 and 6 positions, aimed at tuning their optoelectronic properties and reactivity with singlet oxygen (1O2). Optical spectroscopy, cyclic voltammetry, and density functional theory calculations reveal that the ethynyl groups decrease the HOMO-LUMO gaps of these acenes. Notably, bis(dimethylanilineethynyl) substituents increase the wavelength of absorbance onset by over 60 nm compared to 9,10-dimethoxyanthracene (DMA). Furthermore, all twelve molecules react with 1O2 through cycloaddition at the 9 and 10 positions to form endoperoxides. Although the presence of ethynyl groups decreases the reaction rates, they are at least 40% of the rate observed for DMA. Finally, these endoperoxides cleave to form quinones when exposed to protic acid. This behavior, combined with red-shifting of absorbance spectra, emphasizes their potential in photocleavable materials. 

Current families of reversible photochemical reactions present challenges for light‐controlled polymers of either photostationary states, which are common in photoinduced cycloaddition/cycloreversion reactions, or exclusively intramolecular bond changes, which characterize most photochromic units. In response to these challenges, here the concept of “proximal photocleavage” is presented, which combines photochemical crosslinking with a photocleavable linker, enabling a one‐time bond formation/cleavage sequence. Proximal photocleavage methacrylate monomers comprising, in series along the pendant of the methacrylate, a coumarin unit for crosslinking and either a phenacyl or ortho‐nitrobenzyl photocleavable group for decrosslinking are reported. The photophysical properties of these monomers and their statistical copolymers with methyl methacrylate are described, and wavelength selective crosslinking and de‐crosslinking of thin polymer films are demonstrated. 

The electronic effects of different (hetero)aryl groups in di(arylethynyl)tetracenes substantially impact their optoelectronic properties and reactivity with singlet oxygen. 

Dialog history enhances downstream classification performance in both speech and text based dialog systems. However, there still exists a gap in dialog history integration in a fully end-to-end (E2E) spoken dialog system (SDS) versus a textual dia- log system. Text-based dialog systems use large language models (LLMs) to encode long-range dependencies by attending to the entire conversation as a contiguous token sequence. This is not possible in an E2E SDS, as speech sequences can be intractably long. We propose a convolution subsampling approach to make the speech sequence of a conversation tractable and use a conformer to attend to the speech-based conversation in a fine-grained manner. This model is further enhanced via a conversation-level knowledge transfer from a LLM using a token-level alignment strategy. Finetuning the E2E model pretrained this way gives significant gains, of up to 8%, over strong non-contextual baselines in the E2E dialog act classification task on two datasets. 

RNN Tranducer (RNN-T) technology is very popular for building deployable models for end-to-end (E2E) automatic speech recognition (ASR) and spoken language understanding (SLU). Since these are E2E models operating on speech directly, there remains a potential to improve their performance using purely text based models like BERT, which have strong language understanding capabilities. In this paper, we propose a new training criteria for RNN-T based E2E ASR and SLU to transfer BERT’s knowledge into these systems. In the first stage of our proposed mechanism, we improve ASR performance by using a fine-grained, tokenwise knowledge transfer from BERT. In the second stage, we fine-tune the ASR model for SLU such that the above knowledge is explicitly utilized by the RNN-T model for improved performance. Our techniques improve ASR performance on the Switchboard and CallHome test sets of the NIST Hub5 2000 evaluation and on the recently released SLURP dataset on which we achieve a new state-of-the-art performance. For SLU, we show significant improvements on the SLURP slot filling task, outperforming HuBERT-base and reaching a performance close to HuBERTlarge. Compared to large transformer based speech models like HuBERT, our model is significantly more compact and uses only 300 hours of speech pretraining data. 

We present Calyx, a new intermediate language (IL) for compiling high-level programs into hardware designs. Calyx combines a hardware-like structural language with a software-like control flow representation with loops and conditionals. This split representation enables a new class of hardware-focused optimizations that require both structural and control flow information which are crucial for high-level programming models for hardware design. The Calyx compiler lowers control flow constructs using finite-state machines and generates synthesizable hardware descriptions. We have implemented Calyx in an optimizing compiler that translates high-level programs to hardware. We demonstrate Calyx using two DSL-to-RTL compilers, a systolic array generator and one for a recent imperative accelerator language, and compare them to equivalent designs generated using high-level synthesis (HLS). The systolic arrays are 4.6× faster and 1.11× larger on average than HLS implementations, and the HLS-like imperative language compiler is within a few factors of a highly optimized commercial HLS toolchain. We also describe three optimizations implemented in the Calyx compiler. 

The spectroscopic, electronic, and geometrical properties of acenes have enabled their broad applicability in organic optoelectronics. Beyond these physical characteristics of acenes, acenes also offer characteristic and predictable reaction chemistry, especially their behavior as dienes in cycloaddition reactions. Although these cycloaddition reactions, especially those with singlet oxygen ( 1 O 2 ) as the dienophile, are detrimental for organic electronics, this reactivity has led to several different applications such as sensing of 1 O 2 , the release of cytotoxic reactive oxygen species (ROS), and stimuli-responsive materials for drug delivery. The rational design of acenes in these chemically-responsive applications beyond organic optoelectronics requires an understanding of how chemical structure influences both the physical properties, such as quantum yield of emission, as well as the reactivity of acenes and their cycloadducts. Therefore, the objective of this review is to summarize how cycloaddition reactions of acenes have expanded their applications in different areas of materials chemistry, and in doing so inspire and inform the rational design of acene-based materials with applications beyond organic electronics.