Essays on House Allocation Problems

We study discrete resource allocation problems in which agents have unit demand and strict preferences over a set of indivisible objects. Such problems are known as house allocation problems. We define a new property that we call “balancedness." We characterize the top trading cycles from individual endowments by Pareto efficiency, group strategy-proofness, reallocation-proofness and balancedness. When there are at least four agents or just two agents, we characterize the top trading cycles from individual endowments by Pareto efficiency, group strategy-proofness and balancedness. When there are three agents, an allocation rule is Pareto efficient, group strategy-proof and balanced if and only if it is a top trading cycles rule from individual endowments or a trading cycles rule with three brokers. We also study house allocation problems with weak preferences. We show that the serial dictatorship with fixed tie-breaking satisfies weak Pareto efficiency, strategy-proofness, non-bossiness, and consistency. Furthermore, the serial dictatorship with fixed tie-breaking is not Pareto dominated by any Pareto efficient and strategy-proof rule. We also show that the random serial dictatorship with fixed (or random) tiebreaking is equivalent to the top trading cycles from random endowments with fixed (or random) tie-breaking

Study on the dynamic response of subway tunnel by viaduct collapsing vibration and the protective measures of reducing vibration

Collapsing vibration caused by demolition blasting of buildings has large effect on the buildings and underground structures nearby. Combined with the demolition blasting of a viaduct, numerical simulation was carried out to investigate dynamic response of subway tunnel subjected to collapsing impact load. The paper put forward composite protective structures of steel-rubber tires and makes safety checking calculation of the subway tunnel on the basis of composite protective measures by numerical simulation. In order to ensure the safety and stability of subway tunnel in the practical operation of demolition blasting of the viaduct, the composite protection system was further optimized, which may provide a good reference for the related engineering practices

Study on the vibration effect on operation subway induced by blasting of an adjacent cross tunnel and the reducing vibration techniques

The Hongshan road tunnels in Nanjing cross up the metro Line 1 tunnel, the closest distance between Hongshan road tunnels and subway tunnels is only 4.14 m. In order to ensure the safety of the subway structure during the Hongshan road tunnels group excavation blasting, the vibration of the subway tunnel was monitored real time. The monitoring results showed that the main frequency distributions of the radial, tangential and vertical vibration of subway tunnel were significantly different. The main frequency and energy of tunnel vibration is mainly concentrated in the high frequency band. This characteristic is very beneficial for the protection of the subway tunnel and catenary. A series of techniques to reduce the vibration were taken during tunnel excavation blasting, which reduced the impact of the blasting vibration to subway tunnel and catenary, and ensured the operation subway safety. The vibration of subway tunnel can be controlled within a certain safety standard with proposed of reducing vibration techniques. It is shown that real-time monitoring and the comprehensive application of the reducing vibration technique are able to guarantee the security of adjacent cross operation subway, which provides references for similar tunnel projects

Tunable nonlinear optical bistability based on Dirac semimetal in photonic crystal Fabry-Perot cavity

In this paper, we study the nonlinear optical bistability (OB) in a symmetrical multilayer structure. This structure is constructed by embedding a nonlinear three-dimensional Dirac semimetal (3D DSM) into a solution filled one-dimensional photonic crystal Fabry-Perot cavity. OB stems from the third order nonlinear conductivity of 3D DSM and the local field of resonance mode could enhance the nonlinearity and reduce the thresholds of OB. This structure achieves the tunability of OB due to that the transmittance could be modulated by the Fermi energy. OB threshold and threshold width could be remarkably reduced by increasing the Fermi energy. Besides, it is found that the OB curve depends heavily on the angle of incidence of the incoming light, the structural parameters of the Fabry-Perot cavity, and the position of 3D DSM inside the cavity. After parameter optimization, we obtained OB with a threshold of 106 V/m. We believe this simple structure provides a reference idea for realizing low threshold and tunable all optical switching devices. Keywords: Optical bistability, Dirac semimetal, Fabry-Perot cavity

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Differential Expression Profiles of the Transcriptome in Breast Cancer Cell Lines Revealed by Next Generation Sequencing

Background/Aims: As MCF-7 and MDA-MB-231 cells are the typical cell lines of two clinical breast tumour subtypes, the aim of the present study was to elucidate the transcriptome differences between MCF-7 and MDA-MB-231 breast cancer cell lines. Methods: The mRNA, miRNA (MicroRNA) and lncRNA (Long non-coding RNA) expression profiles were examined using NGS (next generation sequencing) instrument Illumina HiSeq-2500. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses were performed to identify the biological functions of differentially expressed coding RNAs. Subsequently, we constructed an mRNA-ncRNA (non-coding RNA) targeting regulatory network. Finally, we performed RT-qPCR (real-time quantitative PCR) to confirm the NGS results. Results: There are sharp distinctions of the coding and non-coding RNA profiles between MCF-7 and MDA-MB-231 cell lines. Among the mRNAs and ncRNAs with the most differential expression, SLPI, SOD2, miR-7, miR-143 and miR-145 were highly expressed in MCF-7 cells, while CD55, KRT17, miR-21, miR-10b, miR-9, NEAT1 and PICSAR were over-expressed in MDA-MB-231 cells. Differentially expressed mRNAs are primarily involved in biological processes of locomotion, biological adhesion, ECM-receptor interaction pathway and focal adhesion. In the targeting regulatory network of differentially expressed RNAs, mRNAs and miRNAs are primarily associated with tumour metastasis, but the functions of lncRNAs remain uncharacterized. Conclusion: These results provide a basis for future studies of breast cancer metastasis and drug resistance