The Entity-Deduction Arena: A playground for probing the conversational reasoning and planning capabilities of LLMs

Large language models (LLMs) are effective at answering questions that are clearly asked. However, when faced with ambiguous queries they can act unpredictably and produce incorrect outputs. This underscores the need for the development of intelligent agents capable of asking clarification questions to resolve ambiguities effectively. This capability requires complex understanding, state tracking, reasoning and planning over multiple conversational turns. However, directly measuring this can be challenging. In this paper, we offer a surrogate problem which assesses an LLMs's capability to deduce an entity unknown to itself, but revealed to a judge, by asking the judge a series of queries. This entity-deducing game can serve as an evaluation framework to probe the conversational reasoning and planning capabilities of language models. We systematically evaluate various LLMs and discover significant differences in their performance on this task. We find that strong LLMs like GPT-4 outperform human players by a large margin. We further employ Behavior Cloning (BC) to examine whether a weaker model is capable of imitating a stronger model and generalizing to data or domains, using only the demonstrations from a stronger model. We finally propose to use Reinforcement Learning to enhance reasoning and planning capacity of Vicuna models through episodes of game playing, which lead to significant performance improvement. We hope that this problem offers insights into how autonomous agents could be trained to behave more intelligently in ambiguous circumstances.Comment: 22 page

An Empirical Study and Improvement for Speech Emotion Recognition

Multimodal speech emotion recognition aims to detect speakers' emotions from audio and text. Prior works mainly focus on exploiting advanced networks to model and fuse different modality information to facilitate performance, while neglecting the effect of different fusion strategies on emotion recognition. In this work, we consider a simple yet important problem: how to fuse audio and text modality information is more helpful for this multimodal task. Further, we propose a multimodal emotion recognition model improved by perspective loss. Empirical results show our method obtained new state-of-the-art results on the IEMOCAP dataset. The in-depth analysis explains why the improved model can achieve improvements and outperforms baselines.Comment: Accepted by ICASSP 202

Ferromagnetism in two-dimensional CrTe2epitaxial films down to a few atomic layers

Two-dimensional (2D) van der Waals ferromagnetic materials have attracted intense attention due to their potential impact on both fundamental and applied research studies. Recently, a new 2D ferromagnet CrTe2, prepared by mechanical exfoliation or chemical vapor deposition, has gained interest due to its novel magnetic properties. In this work, high quality CrTe2 epitaxial thin films were prepared on GaAs (111)B substrates using solid source molecular beam epitaxy, with the thickness varying from 35 to 4 monolayers (MLs). The magnetic easy axis of all the films is oriented along the c-axis. A Curie temperature of 205 K is found in the 35 ML CrTe2 film, measured by the temperature-dependent anomalous Hall resistance (RAHE). Importantly, even when the film thickness decreases to 4 MLs, a robust out-of-plane ferromagnetism with a Curie temperature of 191 K has been demonstrated. This finding could pave the way for investigating the fundamental studies in 2D ferromagnetism and has great significance in device applications

Epigenetic regulation during cancer transitions across 11 tumour types

Chromatin accessibility is essential in regulating gene expression and cellular identity, and alterations in accessibility have been implicated in driving cancer initiation, progression and metastasi

Determining the Level of Prefabricated Module Requirements in Offsite Construction

Offsite construction technique presents substantially speedier construction processes whilst lowering construction wastes. The level of prefabricated for offsite construction projects depend largely on the amount of complexity and the level of prefabricated components, which can be classified into two levels such as 2D penalized and 3D volumetric construction. However, there is often no specific method adoptable for determining the level of prefabrication construction. This research aims to determine the level of prefabrication requirement for offsite construction and their significance. An online database collected for offsite construction projects was analysed with decision making models. The results revealed that the building volume, i.e., the building footprint and height were the most influential factors. Furthermore, three other factors related to timber material, low-income target user, and residential function of prefabricated projects were also identified crucial in deciding the prefabrication level. The research concluded with certain guidance recommended for choosing the appropriate prefabrication level for building construction. For example, penalized construction generally had higher level of implementation than volumetric construction in prefabrication

Three-Dimensional Precession Feature Extraction of Ballistic Targets Based on Narrowband Radar Network

Micro-motion is a crucial feature used in ballistic target recognition. To address the problem that single-view observations cannot extract true micro-motion parameters, we propose a novel algorithm based on the narrowband radar network to extract three-dimensional precession features. First, we construct a precession model of the cone-shaped target, and as a precondition, we consider the invisible problem of scattering centers. We then analyze in detail the micro-Doppler modulation trait caused by the precession. Then, we match each scattering center in different perspectives based on the ratio of the top scattering center’s micro-Doppler frequency modulation coefficient and extract the 3D coning vector of the target by establishing associated multi-aspect equation systems. In addition, we estimate feature parameters by utilizing the correlation of the micro-Doppler frequency modulation coefficient of the three scattering centers combined with the frequency compensation method. We then calculate the coordinates of the conical point in each moment and reconstruct the 3D spatial portion. Finally, we provide simulation results to validate the proposed algorithm

Wet spinning of PVA composite fibers with a large fraction of multi-walled carbon nanotubes

PVA composites fibers with a large fraction of multi-walled carbon nanotubes modified by both covalent and non-covalent functionalization were produced by a wet-spinning process. Model XQ-1 tensile tester, thermogravimetric analysis, scanning electron microscopy, differential scanning calorimetry, and wide-angle X-ray diffraction were used to characterize the properties of PVA/MWNT composite fibers. The TGA results suggested that MWNTs content in composite fibers were ranged from 5.3 wt% to 27.6 wt%. The mechanical properties of PVA/MWNT composite fibers were obviously superior to pure PVA fiber. The Young׳s modulus of composite fibers enhanced with increasing the content of MWNTs, and it rised gradually from 6.7 GPa for the pure PVA fiber to 12.8 GPa for the composite fibers with 27.6 wt% MWNTs. Meanwhile, the tensile strength increased gradually from 0.39 GPa for the pure PVA fiber to 0.74 GPa for the composite fibers with 14.4 wt% MWNTs. Nevertheless, the tensile strength of the composite fibers decreased as the MWNTs content up to 27.6 wt%. SEM results indicated that the MWNTs homogeneously dispersed in the composite fibers, however some agglomerates also existed when the content of MWNTs reached 27.6 wt%. DSC results proved strong interfacial interaction between MWNTs and PVA chain, which benefited composite fibers in the efficient stress-transfer. WXAD characterization showed that the orientation of PVA molecules declined from 94.1% to 90.9% with the increasing of MWNTs content. The good dispersibility of MWNTs throughout PVA matrix and efficient stress-transfer between MWNTs and PVA matrix may contributed to significant enhancement in the mechanical properties

Transcriptome sequencing of Salvia miltiorrhiza after infection by its endophytic fungi and identification of genes related to tanshinone biosynthesis

Context: Salvia miltiorrhiza Bunge (Labiatae) is a traditional Chinese herb. Endophytic fungi, which are biotic elicitors, can induce accumulation of secondary metabolites in their host plants. Objective: To analyze the interaction mechanism between S. miltiorrhiza and endophytic fungi. Materials and methods: Endophytic fungi U104 producing tanshinone IIA were isolated from the healthy disease-free tissue of root of S. miltiorrhiza by conventional methods. The endophytic fungus U104 of S. miltiorrhiza was co-cultured with the sterile seedlings of S. miltiorrhiza for 20 d (temp:day/night = 26 °C/18 °C, photoperiod:12/12 h, illuminance:2000 Lx). Transcriptome sequencing of S. miltiorrhiza seedlings after 20 d of co-cultivation was performed using the Illumina platform. Results: A total of 3713 differentially expressed genes (DEGs) were obtained. These different expression genes, such as STPII, LTP2, MYB transcription factors, CNGC, CDPK, Rboh, CaM, MAP2K1/MEK1, WRKY33, SGT1/SGT and Hsp90/htpG, showed that host S. miltiorrhiza had biological defence response in the initial stage of interaction. Under the induction of endophytic fungi, 14 key enzyme genes were up-regulated in the tanshinone biosynthesis pathway: DXS, DXS2, DXR, HMGR3, AACT, MK, PMK, GGPPS2, GPPS, KSL, IDI, IPII, FDPS and CPS. Discussion and conclusions: A total of 14 key genes were obtained from the tanshinone component synthesis and metabolic pathways, providing a reasonable explanation for the accumulation of tanshinone components, an accumulation induced by endophytic fungi, in the host plants. The large amounts of data generated in this study provide a strong and powerful platform for future functional and molecular studies of interactions between host plants and their endophytic fungi