A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects

Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and industry. However, TKGs often suffer from incompleteness for three main reasons: the continuous emergence of new knowledge, the weakness of the algorithm for extracting structured information from unstructured data, and the lack of information in the source dataset. Thus, the task of Temporal Knowledge Graph Completion (TKGC) has attracted increasing attention, aiming to predict missing items based on the available information. In this paper, we provide a comprehensive review of TKGC methods and their details. Specifically, this paper mainly consists of three components, namely, 1)Background, which covers the preliminaries of TKGC methods, loss functions required for training, as well as the dataset and evaluation protocol; 2)Interpolation, that estimates and predicts the missing elements or set of elements through the relevant available information. It further categorizes related TKGC methods based on how to process temporal information; 3)Extrapolation, which typically focuses on continuous TKGs and predicts future events, and then classifies all extrapolation methods based on the algorithms they utilize. We further pinpoint the challenges and discuss future research directions of TKGC

Poor-prognosis disclosure preference in cancer patient-caregiver dyads and its association with their quality of life and perceived stress: a cross-sectional survey in mainland China

Background This study attempted to examine the discordance between family caregivers and cancer patients in their poor-prognosis disclosure preferences in mainland China and then ascertained the associations between quality of life (QoL), perceived stress, and poor-prognosis disclosure preferences. Methods Six hundred fifty-one pairs of inpatients and their matched caregivers (participation rate = 92.2%) were recruited in this cross-sectional survey. A set of paired self-administered questionnaires were completed independently by patient–caregiver dyads. Results Fewer family caregivers than cancer patients felt that poor prognosis should be disclosed to patients (61.2% vs. 90.0%, p < 0.001). Patients' positive poor-prognosis disclosure preference was associated with patients' better QoL (p < 0.05) and caregivers' reduced perceived stress levels (p = 0.013). However, caregivers' poor-prognosis disclosure preference correlated only with their own physical state (p = 0.028). Moreover, the caregivers who concurred with patients in positive poor-prognosis disclosure preference were more likely to experience a better QoL (p < 0.05) and lower perceived stress levels (p = 0.048) in the III–IV stage subgroup. Conclusions There was a significant discrepancy in poor-prognosis disclosure preference between cancer patients and caregivers in China. The caregivers' preference of concealing poor prognosis from patients was not related to cancer patients' QoL or perceived stress. In addition, caregivers had better QoL and lower stress levels when they held the same positive poor-prognosis disclosure preference as the patients

Sequence determinants of improved CRISPR sgRNA design

The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation (CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies

Sequence determinants of improved CRISPR sgRNA design

The CRISPR/Cas9 system has revolutionized mammalian somatic cell genetics. Genome-wide functional screens using CRISPR/Cas9-mediated knockout or dCas9 fusion-mediated inhibition/activation (CRISPRi/a) are powerful techniques for discovering phenotype-associated gene function. We systematically assessed the DNA sequence features that contribute to single guide RNA (sgRNA) efficiency in CRISPR-based screens. Leveraging the information from multiple designs, we derived a new sequence model for predicting sgRNA efficiency in CRISPR/Cas9 knockout experiments. Our model confirmed known features and suggested new features including a preference for cytosine at the cleavage site. The model was experimentally validated for sgRNA-mediated mutation rate and protein knockout efficiency. Tested on independent data sets, the model achieved significant results in both positive and negative selection conditions and outperformed existing models. We also found that the sequence preference for CRISPRi/a is substantially different from that for CRISPR/Cas9 knockout and propose a new model for predicting sgRNA efficiency in CRISPRi/a experiments. These results facilitate the genome-wide design of improved sgRNA for both knockout and CRISPRi/a studies

Nanoscale heat transfer - from computation to experiment

Heat transfer can differ distinctly at the nanoscale from that at the macroscale. Recent advancement in computational and 5 experimental techniques has enabled a large number of interesting observations and understanding of heat transfer processes at the nanoscale. In this review, we will first discuss recent advances in computational and experimental methods used in nanoscale thermal transport studies, followed by reviews of novel thermal transport phenomena at the nanoscale observed in both computational and experimental studies, and discussion on current understanding of these novel 10 phenomena. Our perspectives on challenges and opportunities on computational and experimental methods are also presented.University of Notre Dame (Startup fund)United States. Dept. of Energy. Office of Basic Energy Sciences (Solid-State Solar-Thermal Energy Conversion Center

Pavement Properties and Predictive Durability Analysis of Asphalt Mixtures

The actual lifetimes of many highways are lower than that expected based on the initial pavement design, which brings increasingly prohibitive costs of pavement maintenance and repair. Although many works have been done, the real service lifetimes are still disappointing, and the researchers are also trying their best to increase the projects&rsquo; life span. In this study, to comprehensively predict the durability and lifetime of newly designed asphalt mixture structures, an asphalt pavement project consisting of three hot mix asphalt (HMA) mixtures were evaluated. The mixtures were constructed in the pavement project of the Weiwu expressway in Gansu Province. Pavement properties of the asphalt mixtures, rutting and temperature fatigue factors of the dynamic modulus are discussed. The fatigue resistance is supposed to improve on increasing the vehicles&rsquo; speed below the freezing point, which may be more suitable for applications in expressways. Meanwhile, the lifetime is measured according to the number of fatigue axle loads calculated, which were corrected between the specimens in the lab and the field core samples. Durability analysis prediction can be obtained based on the fatigue lifetime predictive model accordingly, which can provide more information about the fatigue lifetime and the rehabilitation planning of existing pavements in the future accordingly