Triazole–Au(I) complex as chemoselective catalyst in promoting propargyl ester rearrangements

Triazole–Au (TA–Au) catalysts were employed in several transformations involving propargyl ester rearrangement. Good chemoselectivity was observed, which allowed the effective activation of the alkyne without affecting the reactivity of the allene ester intermediates. These results led to the investigation of the preparation of allene ester intermediates with TA–Au catalysts under anhydrous conditions. As expected, the desired 3,3-rearrangement products were obtained in excellent yields (generally \u3e90% yields with 1% loading). Besides the typical ester migrating groups, carbonates and carbamates were also found to be suitable for this transformation, which provided a highly efficient, practical method for the preparation of substituted allenes

Terahertz Sources, Detectors, and Transceivers in Silicon Technologies

With active devices lingering on the brink of activity and every passive device and interconnection on chip acting as potential radiator, a paradigm shift from “top-down” to “bottom-up” approach in silicon terahertz (THz) circuit design is clearly evident as we witness orders-of-magnitude improvements of silicon THz circuits in terms of output power, phase noise, and sensitivity since their inception around 2010. That is, the once clear boundary between devices, circuits, and function blocks is getting blurrier as we push the devices toward their limits. And when all else fails to meet the system requirements, which is often the case, a logical step forward is to scale these THz circuits to arrays. This makes a lot of sense in the terahertz region considering the relatively efficient on-chip THz antennas and the reduced size of arrays with half-wavelength pitch. This chapter begins with the derivation of conditions for maximizing power gain of active devices. Discussions of circuit topologies for THz sources, detectors, and transceivers with emphasis on their efficacy and scalability ensue, and this chapter concludes with a brief survey of interface options for channeling THz energy out of the chip

A Multiobjective Computation Offloading Algorithm for Mobile Edge Computing

In mobile edge computing (MEC), smart mobile devices (SMDs) with limited computation resources and battery lifetime can offload their computing-intensive tasks to MEC servers, thus to enhance the computing capability and reduce the energy consumption of SMDs. Nevertheless, offloading tasks to the edge incurs additional transmission time and thus higher execution delay. This paper studies the trade-off between the completion time of applications and the energy consumption of SMDs in MEC networks. The problem is formulated as a multiobjective computation offloading problem (MCOP), where the task precedence, i.e. ordering of tasks in SMD applications, is introduced as a new constraint in the MCOP. An improved multiobjective evolutionary algorithm based on decomposition (MOEA/D) with two performance enhancing schemes is proposed.1) The problem-specific population initialization scheme uses a latency-based execution location initialization method to initialize the execution location (i.e. either local SMD or MEC server) for each task. 2) The dynamic voltage and frequency scaling based energy conservation scheme helps to decrease the energy consumption without increasing the completion time of applications. The simulation results clearly demonstrate that the proposed algorithm outperforms a number of state-of-the-art heuristics and meta-heuristics in terms of the convergence and diversity of the obtained nondominated solutions

Novel insights into circular RNAs in clinical application of carcinomas

Circular RNAs (circRNAs), formed by nonsequential back-splicing of pre-messenger RNA (pre-mRNA) transcripts, have been widely concerned in recent years. With advances in high-throughput RNA sequencing (RNA-seq) technology, previous work has revealed that a large number of circRNAs, which are endogenous, abundant and stable in mammalian cells, may be involved in atherosclerotic vascular disease risk, neurological disorders, prion diseases and carcinomas. Remarkably, interaction between circRNAs and microRNA has already been observed to perform a significant role in a variety of cancers, including gastric cancer and colorectal cancer. Recent work has suggested that circRNAs may play critical roles in the initiation and development of cancers and could become potential new biomarkers for cancers. Herein, we review the current understanding of the roles of circRNAs in cancers and the potential implications of circRNAs in cancer-targeted therapy

Estimation of soil moisture using modified antecedent precipitation index with application in landslide predictions

Soil moisture plays a key role in land-atmosphere interaction systems. Although it can be estimated through in situ measurements, satellite remote sensing, and hydrological modelling, using indicators to index soil moisture conditions is another useful way. In this study, one of these indicators, the antecedent precipitation index (API), is explored. Modifications were proposed to the conventional version of API by introducing two parameters to make it more in line with the physical process. First, the recession coefficient is allowed to vary with the change of air temperature, which could take into account the variation of the evapotranspiration process. Second, the API value is restricted by the maximum value of API, accounting for the maximum water holding capacity of the soil. The modified API was then calibrated and validated by comparing with the in situ measured soil moisture. The better correlation between these two datasets demonstrates that the modified API could better indicate soil moisture conditions, compared with the conventional API. The capability of the modified API to index soil moisture conditions was further explored by applying it to landslide predictions in the Emilia-Romagna region, northern Italy. Here, the recent 3-day rainfall vs the antecedent soil wetness thresholds (RS thresholds) were constructed, in which the soil wetness is indexed by the modified API. The validation of RS thresholds was carried out with the use of the contingency matrix and receiver operating characteristic (ROC) curves. By comparing the prediction performance between RS thresholds and rainfall thresholds, it is found that RS threshold could provide better prediction capabilities in terms of higher hit rate and lower false alarm rate. The positive results indicate that the modified API could provide superior performance of indexing soil moisture conditions, demonstrating the effectiveness of the proposed modifications

A Quantum-like Multimodal Network Framework for Modeling Interaction Dynamics in Multiparty Conversational Sentiment Analysis

Sentiment analysis in conversations is an emerging yet challenging artificial intelligence (AI) task. It aims to discover the affective states and emotional changes of speakers involved in a conversation on the basis of their opinions, which are carried by different modalities of information (e.g., a video associated with a transcript). There exists a wealth of intra- and inter-utterance interaction information that affects the emotions of speakers in a complex and dynamic way. How to accurately and comprehensively model complicated interactions is the key problem of the field. To fill this gap, in this paper, we propose a novel and comprehensive framework for multimodal sentiment analysis in conversations, called a quantum-like multimodal network (QMN), which leverages the mathematical formalism of quantum theory (QT) and a long short-term memory (LSTM) network. Specifically, the QMN framework consists of a multimodal decision fusion approach inspired by quantum interference theory to capture the interactions within each utterance (i.e., the correlations between different modalities) and a strong-weak influence model inspired by quantum measurement theory to model the interactions between adjacent utterances (i.e., how one speaker influences another). Extensive experiments are conducted on two widely used conversational sentiment datasets: the MELD and IEMOCAP datasets. The experimental results show that our approach significantly outperforms a wide range of baselines and state-of-the-art models

Cyclodepsipeptide Toxin Promotes the Degradation of Hsp90 Client Proteins through Chaperone-Mediated Autophagy

Promoting the degradation of Hsp90 client proteins by inhibiting Hsp90, an important protein chaperone, has been shown to be a promising new anticancer strategy. In this study, we show that an oxazoline analogue of apratoxin A (oz-apraA), a cyclodepsipeptide isolated from a marine cyanobacterium, promotes the degradation of Hsp90 clients through chaperone-mediated autophagy (CMA). We identify a KFERQ-like motif as a conserved pentapeptide sequence in the kinase domain of epidermal growth factor receptor (EGFR) necessary for recognition as a CMA substrate. Mutation of this motif prevents EGFR degradation by CMA and promotes the degradation of EGFR through the proteasomal pathway in oz-apraA–treated cells. Oz-apraA binds to Hsc70/Hsp70. We propose that apratoxin A inhibits Hsp90 function by stabilizing the interaction of Hsp90 client proteins with Hsc70/Hsp70 and thus prevents their interactions with Hsp90. Our study provides the first examples for the ability of CMA to mediate degradation of membrane receptors and cross talks of CMA and proteasomal degradation mechanisms

Thermal-Resistivity Characteristics of Carbon Fabric Reinforced Cementitious Matrix

The thermal-resistivity effect of the carbon fiber reinforced cement (CFRC) has been successfully applied to monitor the temperature of concrete structures. There are insufficient studies on the thermal-resistivity effect of the carbon fabric reinforced cementitious matrix (CFRCM). In this paper, the resistance change of CFRCM from room temperature to 120℃ and the thermal-resistivity characteristics during repeated heating have been studied. It was showed that during the heating process, with the continuous increasement of the carrier concentration, the specimen exhibited obvious negative temperature coefficient (NTC) effect, and a temperature rise of 10℃ lessened relative resistance change by about 0.4%. However, some carriers stayed in the conduction band after the first cooling. Then, the resistance cannot return to the original value, and the curves of subsequent heating processes had a good repeatability