catena-Poly[[[(1,10-phenanthroline)copper(I)]-μ-cyanido] ethanol hemisolvate]

In the title coordination polymer, {[Cu(CN)(C12H10N2)]·0.5C2H5OH}n, there are two CuI ions, two 1,10-phenanthroline (phen) ligands and two cyanide ions in the asymmetric unit along with a highly disordered ethanol solvent mol­ecule, which was modelled as being disordered over two sets of sites in a 0.829 (7):0.171 (7) ratio. The orientation/ordering of the C and N atoms of the cyanide ions could not be determined in the present refinement and they were modelled as being statistically disordered. Both copper ions are coordinated by an N,N′-bidentate phen ligand and two cyanide ligands, generating distorted tetra­hedral CuN2 Q 2 (Q = C or N) tetra­hedra. The μ-cyanide ligands link the metal ions, forming a zigzag chain propagating in [001]. The chains are cross-linked by numerous aromatic π–π stacking contacts between adjacent phen rings [minimum centroid–centroid separation = 3.620 (3) Å]

Identification and characterization of single nucleotide polymorphisms in 12 chicken growth-correlated genes by denaturing high performance liquid chromatography

The genes that are part of the somatotropic axis play a crucial role in the regulation of growth and development of chickens. The identification of genetic polymorphisms in these genes will enable the scientist to evaluate the biological relevance of such polymorphisms and to gain a better understanding of quantitative traits like growth. In the present study, 75 pairs of primers were designed and four chicken breeds, significantly differing in growth and reproduction characteristics, were used to identify single nucleotide polymorphisms (SNP) using the denaturing high performance liquid chromatography (DHPLC) technology. A total of 283 SNP were discovered in 31 897 base pairs (bp) from 12 genes of the growth hormone (GH), growth hormone receptor (GHR), ghrelin, growth hormone secretagogue receptor (GHSR), insulin-like growth factor I and II (IGF-I and -II), insulin-like growth factor binding protein 2 (IGFBP-2), insulin, leptin receptor (LEPR), pituitary-specific transcription factor-1 (PIT-1), somatostatin (SS), thyroid-stimulating hormone beta subunit (TSH-β). The observed average distances in bp between the SNP in the 5'UTR, coding regions (non- and synonymous), introns and 3'UTR were 172, 151 (473 and 222), 89 and 141 respectively. Fifteen non-synonymous SNP altered the translated precursors or mature proteins of GH, GHR, ghrelin, IGFBP-2, PIT-1 and SS. Fifteen indels of no less than 2 bps and 2 poly (A) polymorphisms were also observed in 9 genes. Fifty-nine PCR-RFLP markers were found in 11 genes. The SNP discovered in this study provided suitable markers for association studies of candidate genes for growth related traits in chickens

N-Benzyl­pyridin-2-amine

In the title compound, C12H12N2, the dihedral angle between the benzene and pyridine rings is 67.63 (8)°. Mol­ecules are linked into centrosymmetric dimers by a simple inter­molecular N—H⋯N hydrogen bond with graph-set motif R 2 2(8)

NavCoT: Boosting LLM-Based Vision-and-Language Navigation via Learning Disentangled Reasoning

Vision-and-Language Navigation (VLN), as a crucial research problem of Embodied AI, requires an embodied agent to navigate through complex 3D environments following natural language instructions. Recent research has highlighted the promising capacity of large language models (LLMs) in VLN by improving navigational reasoning accuracy and interpretability. However, their predominant use in an offline manner usually suffers from substantial domain gap between the VLN task and the LLM training corpus. This paper introduces a novel strategy called Navigational Chain-of-Thought (NavCoT), where we fulfill parameter-efficient in-domain training to enable self-guided navigational decision, leading to a significant mitigation of the domain gap in a cost-effective manner. Specifically, at each timestep, the LLM is prompted to forecast the navigational chain-of-thought by: 1) acting as a world model to imagine the next observation according to the instruction, 2) selecting the candidate observation that best aligns with the imagination, and 3) determining the action based on the reasoning from the prior steps. Through constructing formalized labels for training, the LLM can learn to generate desired and reasonable chain-of-thought outputs for improving the action decision. Experimental results across various training settings and popular VLN benchmarks (e.g., Room-to-Room (R2R), Room-across-Room (RxR), Room-for-Room (R4R)) show the significant superiority of NavCoT over the direct action prediction variants. Through simple parameter-efficient finetuning, our NavCoT outperforms a recent GPT4-based approach with ~7% relative improvement on the R2R dataset. We believe that NavCoT will help unlock more task-adaptive and scalable LLM-based embodied agents, which are helpful for developing real-world robotics applications. Code is available at https://github.com/expectorlin/NavCoT

Defect Study of MgO-CaO Material Doped with CeO 2

MgO-CaO refractories were prepared using analytical reagent chemicals of Ca(OH)2 and Mg(OH)2 as starting materials and CeO2 as dopant, then sintered at 1650°C for 3 h. The effect of CeO2 powders on the defect of MgO-CaO refractories was investigated. The sample characterizations were analyzed by the techniques of XRD and SEM. According to the results, with the addition of CeO2, the lattice constant of CaO increased, and the bulk density of the samples increased while apparent porosity decreased. The densification of MgO-CaO refractories was promoted obviously. In the sintering process, MgO grains grew faster than CaO, pores at the MgO-CaO grain boundaries decreased while pores in the MgO grains increased gradually, and no pores were observed in the CaO grains. The nature of the CeO2 promoting densification lies in the substitution and solution with CaO. Ce4+ approaches into CaO lattices, which enlarges the vacancy concentration of Ca2+ and accelerates the diffusion of Ca2+

Comprehensive studies of biological characteristics, phytochemical profiling, and antioxidant activities of two local citrus varieties in China

Citrus is widely grown all over the world, and citrus fruits have long been recognized for their nutritional and medical value for human health. However, some local citrus varieties with potentially important value are still elusive. In the current study, we elucidated the biological characteristics, phylogenetic and phytochemical profiling, antioxidants and antioxidant activities of the two local citrus varieties, namely Zangju and Tuju. The physiological and phylogenetic analysis showed that Zangju fruit has the characteristics of wrinkled skin, higher acidity, and phylogenetically closest to sour mandarin Citrus sunki, whereas, Tuju is a kind of red orange with vermilion peel, small fruit and high sugar content, and closely clustered with Citrus erythrosa. The phytochemical analysis showed that many nutrition and antioxidant related differentially accumulated metabolites (DAMs) were detected in the peel and pulp of Zangju and Tuju fruits. Furthermore, it was found that the relative abundance of some key flavonoids and phenolic acids, such as tangeritin, sinensetin, diosmetin, nobiletin, and sinapic acid in the peel and pulp of Zangju and Tuju were higher than that in sour range Daidai and satsuma mandarin. Additionally, Zangju pulp and Tuju peel showed the strongest ferric reducing/antioxidant power (FRAP) activity, whereas, Tuju peel and pulp showed the strongest DPPH and ABTS free radical scavenging activities, respectively. Moreover, both the antioxidant activities of peel and pulp were significantly correlated with the contents of total phenols, total flavonoids or ascorbic acid. These results indicate that the two local citrus varieties have certain nutritional and medicinal value and potential beneficial effects on human health. Our findings will also provide an important theoretical basis for further conservation, development and medicinal utilization of Zangju and Tuju

ADD 2023: the Second Audio Deepfake Detection Challenge

Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the world to build new innovative technologies that can further accelerate and foster research on detecting and analyzing deepfake speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023 focuses on surpassing the constraints of binary real/fake classification, and actually localizing the manipulated intervals in a partially fake speech as well as pinpointing the source responsible for generating any fake audio. Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio game sub-challenge. The ADD 2023 challenge includes three subchallenges: audio fake game (FG), manipulation region location (RL) and deepfake algorithm recognition (AR). This paper describes the datasets, evaluation metrics, and protocols. Some findings are also reported in audio deepfake detection tasks

The SARS-CoV-2 vaccination rate and hesitation in Shanghai older adults with dementia

BackgroundOlder adults, particularly those with dementia, are at the greatest risk for being affected by SARS-CoV-2. Despite the Chinese government’s efforts to encourage older adults to receive SARS-CoV-2 vaccines, the vaccination rate, especially among older adults with dementia, remains low.ObjectiveThis study aimed to examine the willingness and attitudes towards vaccination among guardians of older adults with dementia and to uncover the factors that may have influenced attitudes towards vaccination during the 2022 Omicron Variant of SARS-CoV-2 outbreak in Shanghai, China.MethodsWe conducted a cross-sectional study using self-administered anonymous questionnaires to guardians of dementia patients in three settings: psychogeriatric inpatient wards, long-term care facilities, and home settings from April to May 2022. The primary outcome was participants’ willingness to allow dementia patients to receive SARS-CoV-2 vaccines. Logistic regression analyses were used to identify factors associated with vaccination willingness.ResultsA total of 327 valid questionnaires were collected. The vaccination rate among participants from long-term care facilities (12.9%) was lower than those in the psychiatric ward (19.3%) or community-dwelling settings (27.1%) (p < 0.05). The guardians’ primary concern was that vaccination would aggravate the health conditions of dementia patients [adjusted odds ratio (OR) = 5.11; 95% confidence interval (CI): 1.86–14.05]. Additionally, negative reports about the vaccination [OR = 3.94; 95% CI: 1.68–9.24], and adverse reactions [OR = 2.50; 95% CI: 1.13–5.52] were related to higher odds of vaccine hesitancy.ConclusionOur results showed that low vaccination rates in older adults with dementia were mainly due to their guardians’ concerns about vaccine safety. Our findings first uncovered the actual SARS-CoV-2 vaccination rates among older adults with dementia and may provide potential interventions to reduce unjustified worries towards vaccination