Multiobjective Transmission Network Planning considering the Uncertainty and Correlation of Wind Power

In order to consider the uncertainty and correlation of wind power in multiobjective transmission network expansion planning (TNEP), this paper presents an extended point-estimation method to calculate the probabilistic power flow, based on which the correlative power outputs of wind farm are sampled and the uncertain multiobjective transmission network planning model is transformed into a solvable deterministic model. A modified epsilon multiobjective evolutionary algorithm is used to solve the above model and a well-distributed Pareto front is achieved, and then the final planning scheme can be obtained from the set of nondominated solutions by a fuzzy satisfied method. The proposed method only needs the first four statistical moments and correlation coefficients of the output power of wind farms as input information; the modeling of wind power is more precise by considering the correlation between wind farms, and it can be easily combined with the multiobjective transmission network planning model. Besides, as the self-adaptive probabilities of crossover and mutation are adopted, the global search capabilities of the proposed algorithm can be significantly improved while the probability of being stuck in the local optimum is effectively reduced. The accuracy and efficiency of the proposed method are validated by IEEE 24 as well as a real system

Layer-wise Representation Fusion for Compositional Generalization

Despite successes across a broad range of applications, sequence-to-sequence models' construct of solutions are argued to be less compositional than human-like generalization. There is mounting evidence that one of the reasons hindering compositional generalization is representations of the encoder and decoder uppermost layer are entangled. In other words, the syntactic and semantic representations of sequences are twisted inappropriately. However, most previous studies mainly concentrate on enhancing token-level semantic information to alleviate the representations entanglement problem, rather than composing and using the syntactic and semantic representations of sequences appropriately as humans do. In addition, we explain why the entanglement problem exists from the perspective of recent studies about training deeper Transformer, mainly owing to the ``shallow'' residual connections and its simple, one-step operations, which fails to fuse previous layers' information effectively. Starting from this finding and inspired by humans' strategies, we propose \textsc{FuSion} (\textbf{Fu}sing \textbf{S}yntactic and Semant\textbf{i}c Representati\textbf{on}s), an extension to sequence-to-sequence models to learn to fuse previous layers' information back into the encoding and decoding process appropriately through introducing a \emph{fuse-attention module} at each encoder and decoder layer. \textsc{FuSion} achieves competitive and even \textbf{state-of-the-art} results on two realistic benchmarks, which empirically demonstrates the effectiveness of our proposal.Comment: work in progress. arXiv admin note: substantial text overlap with arXiv:2305.1216

Towards on-chip spectroscopy based on a single microresonator

Frequency comb generation in the mid-infrared (mid-IR)region is attractive recently. Here, we propose the Ge-on-Si microresonator for power-efficient frequency comb generation in the mid-IR. An octave-spanning comb can be obtained with power reduced to 190 mW. The robustness of the frequency comb generation with localized spectral loss is also analyzed. Based on the analysis, we propose a novel architecture of on-chip spectroscopy systems in the mid-IR

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Mechanisms of ginseng in pancreatic cancer metastasis: A network pharmacology analysis

It has been shown that ginsenosides can inhibit proliferation, migration, and invasion of pancreatic cancer (PC) cells, and promote apoptosis of PC cells. However, the potential mechanisms of ginseng in treating PC metastasis (PCM) have not been fully elucidated. In this study, we employed an integrated bioinformatics approach of network pharmacology analysis. By selecting common targets of diseases and drugs, a drug-component-target-disease network was constructed to analyze the biological functions and signaling pathways involved in the targets. A total of 6 PC samples were includedd, which were divided into primary PC group (PANC-1, n=3) and metastatic PC group. A total of 9263 differentially expressed genes (DEGs) and 14 PC target genes were identified. According to the network pharmacology analysis, we found that ginsenoside Rg3 was associated with the treatment of PCM and identified 6 potential targets. Among them, CD44, EGFR, KRAS, and PRNP were the main DEGs related to the treatment of PC by ginsenoside Rg3. These genes were mainly enriched in the Proteoglycans in Cancer pathway, and KRAS, EGFR, and CD44 were upregulated in the pathway, which may be affected by the ginsenoside Rg3. This provides a new direction for further research on the mechanisms of ginseng in PCM

Antecedents and consequences of the introduction of flexible benefit plans in China

The present study had two aims. The first was to explore the extent of flexible benefit plans (flex plans) within China and to make predictions about future trends. The second aim was to examine the relationships between the use of flex plans and two measures of labour market performance: the ability to attract essential employees and the level of labour turnover. The results from a survey of 324 firms in China reflecting a response rate of 32.4% showed that although there are presently a limited number of firms that adopt flex plans, the number is likely to increase in the next few years. Second, the probability of the adoption of flex plans was not found to vary with the mode of ownership and firm location. Third, flex plans were found to be adopted by firms for several practical reasons including their perceived role in cost containment, improved recruitment and retention, enhancement of job satisfaction and labour productivity. The take-up of such plans, however, was found to be inhibited by perceived administrative burdens and costs, and the limited number of staff qualified in benefit provision. Finally, the adoption of flex plans was significantly related to labour turnover and improved recruitment capacity

Integrated Photonics For Infrared Spectroscopic Sensing

Infrared (IR) spectroscopy is widely recognized as a gold standard technique for chemical analysis. Traditional IR spectroscopy relies on fragile bench-Top instruments located in dedicated laboratory settings, and is thus not suitable for emerging field-deployed applications such as in-line industrial process control, environmental monitoring, and point-ofcare diagnosis. Recent strides in photonic integration technologies provide a promising route towards enabling miniaturized, rugged platforms for IR spectroscopic analysis. Chalcogenide glasses, the amorphous compounds containing S, Se or Te, have stand out as a promising material for infrared photonic integration given their broadband infrared transparency and compatibility with silicon photonic integration. In this paper, we discuss our recent work exploring integrated chalcogenide glass based photonic devices for IR spectroscopic chemical analysis, including on-chip cavityenhanced chemical sensing and monolithic integration of mid-IR waveguides with photodetectors