Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning

Recent advancements have significantly augmented the reasoning capabilities of Large Language Models (LLMs) through various methodologies, especially chain-of-thought (CoT) reasoning. However, previous methods fail to address reasoning errors in intermediate steps, leading to accumulative errors. In this paper, we propose Deductive Beam Search (DBS), which seamlessly integrates CoT and deductive reasoning with step-wise beam search for LLMs. Our approach deploys a verifier, verifying the deducibility of a reasoning step and its premises, thus alleviating the error accumulation. Furthermore, we introduce a scalable and labor-free data construction method to amplify our model's verification capabilities. Extensive experiments demonstrate that our approach significantly enhances the base performance of LLMs of various scales (7B, 13B, 70B, and ChatGPT) across 8 reasoning datasets from 3 diverse reasoning genres, including arithmetic, commonsense, and symbolic. Moreover, our analysis proves DBS's capability of detecting diverse and subtle reasoning errors and robustness on different model scales

Volatiles from cotton aphid (Aphis gossypii) infested plants attract the natural enemy Hippodamia variegata

The Aphis gossypii is a major threat of cotton worldwide due to its short life cycle and rapid reproduction. Chemical control is the primary method used to manage the cotton aphid, which has significant environmental impacts. Therefore, prioritizing eco-friendly alternatives is essential for managing the cotton aphid. The ladybird, Hippodamia variegata, is a predominant predator of the cotton aphid. Its performance in cotton plantation is directly linked to chemical communication, where volatile compounds emitted from aphid-infested plants play important roles in successful predation. Here, we comprehensively studied the chemical interaction between the pest, natural enemy and host plants by analyzing the volatile profiles of aphid-infested cotton plants using gas chromatography-mass spectrometry (GC-MS). We then utilized the identified volatile compounds in electrophysiological recording (EAG) and behavioral assays. Through behavioral tests, we initially demonstrated the clear preference of both larvae and adults of H. variegata for aphid-infested plants. Subsequently, 13 compounds, namely α-pinene, cis-3-hexenyl acetate, 4-ethyl-1-octyn-3-ol, β-ocimene, dodecane, E-β-farnesene, decanal, methyl salicylate, β-caryophyllene, α-humulene, farnesol, DMNT, and TMTT were identified from aphid-infested plants. All these compounds were electrophysiologically active and induced detectable EAG responses in larvae and adults. Y-tube olfactometer assays indicated that, with few exceptions for larvae, all identified chemicals were attractive to H. variegata, particularly at the highest tested concentration (100 mg/ml). The outcomes of this study establish a practical foundation for developing attractants for H. variegata and open avenues for potential advancements in aphid management strategies by understanding the details of chemical communication at a tritrophic level

Study on Chinese Speech Intelligibility Under Different Low-Frequency Characteristics of Reverberation Time Using a Hybrid Method

Reverberation time (RT) is an important indicator of room acoustics, however, most studies focus on the mid-high frequency RT, and less on the low-frequency RT. In this paper, a hybrid approach based on geometric and wave methods was proposed to build a more accurate and wide frequency-band room acoustic impulse response. This hybrid method utilized the finite-difference time-domain (FDTD) method modeling at low frequencies and the Odeon simulation at mid-high frequencies, which was investigated in a university classroom. The influence of the low-frequency RT on speech intelligibility was explored. For the low-frequency part, different impedance boundary conditions were employed and the effectiveness of the hybrid method has also been verified. From the results of objective acoustical parameters and subjective listening experiments, the smaller the low-frequency RT was, the higher the Chinese speech intelligibility score was. The syllables, consonants, vowels, and the syllable order also had significant effects on the intelligibility score

The complete mitochondrial genome of an economic sea anemone (Paracondylactis sinensis) in the East China Sea

Paracondylactis sinensis Carlgren, 1934 (Actiniidae, Actiniaria) is an edible sea anemone in China. Their wild population has intensively decreased in recent years due to overharvesting. In this study, the complete mitochondrial genome of this economic species collected in the coast of Zhejiang, China is sequenced and obtained using high throughput methods. The total length of this circular molecule is 20,786 bp. Thirteen protein coding genes, two ribosomal RNA genes, two transfer RNA (tRNATrp, tRNAMet) genes and a putative ORF are annotated in it. Phylogenetic analysis based on the amino acids of mitochondrial genomes indicates that this species belongs to the family of Actiniidae. This result is consistent with the previous work that identified the edible sea anemone as Paracondylactis sinensis although it has always been recognized as Calliactis sinensis (of family Hormathiidae) in most Chinese reports. Overall, the mitochondrial genome produced in this study assists in clarifying the phylogenetic status of this sea anemone and provides a molecular foundation for future protection and breeding work