Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow.

Since 2000, the phenology has advanced in some years and at some locations on the Qinghai-Tibetan Plateau, whereas it has been delayed in others. To understand the variations in spring vegetation growth in response to climate, we conducted both regional and experimental studies on the central Qinghai-Tibetan Plateau. We used the normalized difference vegetation index to identify correlations between climate and phenological greening, and found that greening correlated negatively with winter-spring time precipitation, but not with temperature. We used open top chambers to induce warming in an alpine meadow ecosystem from 2012 to 2014. Our results showed that in the early growing season, plant growth (represented by the net ecosystem CO2 exchange, NEE) was lower in the warmed plots than in the control plots. Late-season plant growth increased with warming relative to that under control conditions. These data suggest that the response of plant growth to warming is complex and non-intuitive in this system. Our results are consistent with the hypothesis that moisture limitation increases in early spring as temperature increases. The effects of moisture limitation on plant growth with increasing temperatures will have important ramifications for grazers in this system

Multi-scale analysis of schizophrenia risk genes, brain structure, and clinical symptoms reveals integrative clues for subtyping schizophrenia patients

Analysis linking directly genomics, neuroimaging phenotypes and clinical measurements is crucial for understanding psychiatric disorders, but remains rare. Here, we describe a multi-scale analysis using genome-wide SNPs, gene-expression, grey matter volume (GMV) and the Positive and Negative Syndrome Scale scores (PANSS) to explore the etiology of schizophrenia. With 72 drug-naive schizophrenic first episode patients (FEPs) and 73 matched heathy controls, we identified 108 genes, from schizophrenia risk genes, that correlated significantly with GMV, which are highly co-expressed in the brain during development. Among these 108 candidates, 19 distinct genes were found associated with 16 brain regions referred to as hot clusters (HCs), primarily in the frontal cortex, sensory-motor regions and temporal and parietal regions. The patients were subtyped into three groups with distinguishable PANSS scores by the GMV of the identified HCs. Furthermore, we found that HCs with common GMV among patient groups are related to genes that mostly mapped to pathways relevant to neural signaling, which are associated with the risk for schizophrenia. Our results provide an integrated view of how genetic variants may affect brain structures that lead to distinct disease phenotypes. The method of multi-scale analysis that was described in this research, may help to advance the understanding of the etiology of schizophrenia

Phase Control on Surface for the Stabilization of High Energy Cathode Materials of Lithium Ion Batteries.

The development of high energy electrode materials for lithium ion batteries is challenged by their inherent instabilities, which become more aggravated as the energy densities continue to climb, accordingly causing increasing concerns on battery safety and reliability. Here, taking the high voltage cathode of LiNi0.5Mn1.5O4 as an example, we demonstrate a protocol to stabilize this cathode through a systematic phase modulating on its particle surface. We are able to transfer the spinel surface into a 30 nm shell composed of two functional phases including a rock-salt one and a layered one. The former is electrochemically inert for surface stabilization while the latter is designated to provide necessary electrochemical activity. The precise synthesis control enables us to tune the ratio of these two phases, and achieve an optimized balance between improved stability against structural degradation without sacrificing its capacity. This study highlights the critical importance of well-tailored surface phase property for the cathode stabilization of high energy lithium ion batteries

Outreach syphilis testing services by different health providers to female sex workers in southern China.

Health providers have played important roles on delivering prevention and care services to control syphilis in China. The current study was aimed to evaluate the performance of different health providers in providing outreach syphilis testing services to female sex workers (FSWs). The current study carried out during April to August 2009 in Liuzhou was aimed to investigate the services delivered by two different types of clinics in China. A total of 1,808 FSWs recruited from sex work venues were included in the study. Prevalence of positive syphilis test (6.4%) among FSWs accessed by the local center for disease control outreach teams (CDC teams) was significantly lower than that (9.3%) among FSWs accessed by the local reproductive health hospital outreach teams (RHH teams). As compared with CDC teams, RHH teams had more FSWs to be successfully referred to the designated STD clinics for further syphilis confirmation and intervention (85.7% vs. 26.7%, P<0.001). These findings indicate that RHH teams may be more efficient than CDC teams to provide outreach-based services to FSWs. Participation of the reproductive health providers or other medical facilities in outreach services to FSWs should be considered in developing intervention programs in China

Letter of Intent: Jinping Neutrino Experiment

Jinping Neutrino Experiment (Jinping) is proposed to significantly improve measurements on solar neutrinos and geoneutrinos in China Jinping Laboratory - a lab with a number of unparalleled features, thickest overburden, lowest reactor neutrino background, etc., which identify it as the world-best low-energy neutrino laboratory. The proposed experiment will have target mass of 4 kilotons of liquid scintillator or water-based liquid scintillator, with a fiducial mass of 2 kilotons for neutrino-electron scattering events and 3 kilotons for inverse-beta interaction events. A number of initial sensitivities studies have been carried out, including on the transition phase for the solar neutrinos oscillation from the vacuum to the matter effect, the discovery of solar neutrinos from the carbon-nitrogen-oxygen (CNO) cycle, the resolution of the high and low metallicity hypotheses, and the unambiguous separation on U and Th cascade decays from the dominant crustal anti-electron neutrinos in China.Comment: Proposal for the Jinping Neutrino Experimen

Exploring the singlet scalar dark matter from direct detections and neutrino signals via its annihilation in the Sun

We explore the singlet scalar dark matter (DM) from direct detections and high energy neutrino signals generated by the solar DM annihilation. Two singlet scalar DM models are discussed, one is the real singlet scalar DM model as the simple extension of the standard model (SSDM-SM) with a discrete Z_2 symmetry, and another is the complex singlet scalar DM model as the simple extension of the left-right symmetric two Higgs bidoublet model (SSDM-2HBDM) with $P$ and CP symmetries. To derive the Sun capture rate, we consider the uncertainties in the hadronic matrix elements and calculate the spin-independent DM-nucleon elastic scattering cross section. We find that the predicted neutrino induced upgoing muon fluxes in the region 3.7 GeV < m_D < 4.2 GeV slightly exceed the Super-Kamiokande limit in the SSDM-SM. However, this exceeded region can be excluded by the current DM direct detection experiments. For the SSDM-2HBDM, one may adjust the Yukawa couplings to avoid the direct detection limits and enhance the predicted muon fluxes. For the allowed parameter space of the SSDM-SM and SSDM-2HBDM, the produced muon fluxes in the Super-Kamiokande and muon event rates in the IceCube are less than the experiment upper bound and atmosphere background, respectively.Comment: 21 pages, 5 figures, 1 table. Accepted for publication in Nuclear Physics

I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBench

Do large language models (LLMs) exhibit any forms of awareness similar to humans? In this paper, we introduce AwareBench, a benchmark designed to evaluate awareness in LLMs. Drawing from theories in psychology and philosophy, we define awareness in LLMs as the ability to understand themselves as AI models and to exhibit social intelligence. Subsequently, we categorize awareness in LLMs into five dimensions, including capability, mission, emotion, culture, and perspective. Based on this taxonomy, we create a dataset called AwareEval, which contains binary, multiple-choice, and open-ended questions to assess LLMs' understandings of specific awareness dimensions. Our experiments, conducted on 13 LLMs, reveal that the majority of them struggle to fully recognize their capabilities and missions while demonstrating decent social intelligence. We conclude by connecting awareness of LLMs with AI alignment and safety, emphasizing its significance to the trustworthy and ethical development of LLMs. Our dataset and code are available at https://github.com/HowieHwong/Awareness-in-LLM

Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding

Decoding visual stimuli from brain recordings aims to deepen our understanding of the human visual system and build a solid foundation for bridging human and computer vision through the Brain-Computer Interface. However, reconstructing high-quality images with correct semantics from brain recordings is a challenging problem due to the complex underlying representations of brain signals and the scarcity of data annotations. In this work, we present MinD-Vis: Sparse Masked Brain Modeling with Double-Conditioned Latent Diffusion Model for Human Vision Decoding. Firstly, we learn an effective self-supervised representation of fMRI data using mask modeling in a large latent space inspired by the sparse coding of information in the primary visual cortex. Then by augmenting a latent diffusion model with double-conditioning, we show that MinD-Vis can reconstruct highly plausible images with semantically matching details from brain recordings using very few paired annotations. We benchmarked our model qualitatively and quantitatively; the experimental results indicate that our method outperformed state-of-the-art in both semantic mapping (100-way semantic classification) and generation quality (FID) by 66% and 41% respectively. An exhaustive ablation study was also conducted to analyze our framework.Comment: 8 pages, 9 figures, 2 tables, accepted by CVPR2023, see https://mind-vis.github.io/ for more informatio

Long-term antagonistic effect of increased precipitation and nitrogen addition on soil respiration in a semiarid steppe

Changes in water and nitrogen (N) availability due to climate change and atmospheric N deposition could have significant effects on soil respiration, a major pathway of carbon (C) loss from terrestrial ecosystems. A manipulative experiment simulating increased precipitation and atmospheric N deposition has been conducted for 9 years (2005–2013) in a semiarid grassland in Mongolian Plateau, China. Increased precipitation and N addition interactively affect soil respiration through the 9 years. The interactions demonstrated that N addition weakened the precipitation-induced stimulation of soil respiration, whereas increased precipitation exacerbated the negative impacts of N addition. The main effects of increased precipitation and N addition treatment on soil respiration were 15.8% stimulated and 14.2% suppressed, respectively. Moreover, a declining pattern and 2-year oscillation were observed for soil respiration response to N addition under increased precipitation. The dependence of soil respiration upon gross primary productivity and soil moisture, but not soil temperature, suggests that resources C substrate supply and water availability are more important than temperature in regulating interannual variations of soil C release in semiarid grassland ecosystems. The findings indicate that atmospheric N deposition may have the potential to mitigate soil C loss induced by increased precipitation, and highlight that long-term and multi-factor global change studies are critical for predicting the general patterns of terrestrial C cycling in response to global change in the future

N-(4-Bromo­phen­yl)-2-[(1-cyclo­hexyl­meth­yl-1H-1,2,4-triazol-3-yl)sulfanyl]­acetamide

The title compound, C17H21BrN4OS, was synthesized as a potential reverse transcriptase (RT) inhibitor of the human immunodeficiency virus type 1 (HIV-1). In the molecule, there is an N—H⋯S hydrogen bond making a five-membered ring. In the crystal, mol­ecules are connected into centrosymmetric dimers via pairs of N—H⋯N and weak C—H⋯N hydrogen bonds. The crystal structure also features C—H⋯O inter­actions