Full Orientability of the Square of a Cycle

Let D be an acyclic orientation of a simple graph G. An arc of D is called dependent if its reversal creates a directed cycle. Let d(D) denote the number of dependent arcs in D. Define m and M to be the minimum and the maximum number of d(D) over all acyclic orientations D of G. We call G fully orientable if G has an acyclic orientation with exactly k dependent arcs for every k satisfying m <= k <= M. In this paper, we prove that the square of a cycle C_n of length n is fully orientable except n=6.Comment: 7 pages, accepted by Ars Combinatoria on May 26, 201

Does Culture Matter to Pro-Social Behavior? Evidence from a Cross-Ethnic Lab Experiment

Recent investigations have uncovered large, consistent deviations from the predictions of Homo economics that individuals are entirely self-regarding. Our study undertook a cross-cultural study of behavior search for the evidences of other-regarding behaviors and its ethnic difference, and accounted for by anatomy of culture. This study recruited 90 subjects of three ethnic groups from market trade-based (ethnic Han), nomadism-based (ethnic Zang) and agriculture-based (ethnic Bouyei) areas in China and conducted public good provision experiment with stranger-treatment design. Under the assumption of self-regarding preferences, the Nash equilibrium is zero contribution by all in public account using backward induction. However, we found contributions did not reduce to zero over all three sessions. Besides, the differences in contributions between ethnicities strongly depended on the degree of ethnic dominance, and Zang harbored the strongest reciprocal preference generally over all group structures. A particular set of measurable factors was identified as proxies for cultural influences on behavioral differences observed in experiments between ethnicities. The results showed all of the cultural factors accounted for the behavioral differences between the ethnic Han and the other two minor ethnicities. However, behavioral difference between minor ethnicities was attributed to group structure only. (1) People may harbor various forms of prosocial emotions in economic affairs, and especially exhibit stronger at the initial phase rather than what canonical model assumes. (2) Behavioral differences between ethnicities are prominent and can be explained by differences in cultural influence

The Application of Driver Models in the Safety Assessment of Autonomous Vehicles: A Survey

Driver models play a vital role in developing and verifying autonomous vehicles (AVs). Previously, they are mainly applied in traffic flow simulation to model realistic driver behavior. With the development of AVs, driver models attract much attention again due to their potential contributions to AV certification. The simulation-based testing method is considered an effective measure to accelerate AV testing due to its safe and efficient characteristics. Nonetheless, realistic driver models are prerequisites for valid simulation results. Additionally, an AV is assumed to be at least as safe as a careful and competent driver. Therefore, driver models are inevitable for AV safety assessment. However, no comparison or discussion of driver models is available regarding their utility to AVs in the last five years despite their necessities in the release of AVs. This motivates us to present a comprehensive survey of driver models in the paper and compare their applicability. Requirements for driver models in terms of their application to AV safety assessment are discussed. A summary of driver models for simulation-based testing and AV certification is provided. Evaluation metrics are defined to compare their strength and weakness. Finally, an architecture for a careful and competent driver model is proposed. Challenges and future work are elaborated. This study gives related researchers especially regulators an overview and helps them to define appropriate driver models for AVs

Cellulose-starch hybrid films plasticized by aqueous ZnCl2 solution

Starch and cellulose are two typical natural polymers from plants that have similar chemical structures. The blending of these two biopolymers for materials development is an interesting topic, although how their molecular interactions could influence the conformation and properties of the resultant materials has not been studied extensively. Herein, the rheological properties of cellulose/starch/ZnCl2 solutions were studied, and the structures and properties of cellulose-starch hybrid films were characterized. The rheological study shows that compared with starch (containing mostly amylose), cellulose contributed more to the solution’s viscosity and has a stronger shear-thinning behavior. A comparison between the experimental and calculated zero-shear-rate viscosities indicates that compact complexes (interfacial interactions) formed between cellulose and starch with ≤50 wt % cellulose content, whereas a loose structure (phase separation) existed with ≥70 wt % cellulose content. For starch-rich hybrid films prepared by compression molding, less than 7 wt % of cellulose was found to improve the mechanical properties despite the reduced crystallinity of the starch; for cellulose-rich hybrid films, a higher content of starch reduced the material properties, although the chemical interactions were not apparently influenced. It is concluded that the mechanical properties of biopolymer films were mainly affected by the structural conformation, as indicated by the rheological results. View Full-Tex

Diagnostic and prognostic value of serum miR-9-5p and miR-128-3p levels in early-stage acute ischemic stroke

OBJECTIVES: To investigate the clinical utility of serum microRNA levels (miR-9-5p and miR-128-3p) in the diagnosis and prognosis of early-stage acute ischemic stroke (AIS). METHODS: We compared the differences in serum miR-9-5p and miR-128-3p levels between patients with AIS and healthy individuals (controls). The serum levels of miR-9-5p and miR-128-3p were quantified using quantitative real-time PCR, and the association of each miRNA with AIS was determined using receiver operator characteristic curve analysis. The predictive value of these indices in the diagnosis of early-stage AIS was evaluated in conjunction with that of computed tomography findings and neuron-specific enolase levels. The prognosis of patients with AIS was evaluated three months after their discharge from hospital using the modified Rankin scale, which classifies the prognosis as either favorable or poor. Logistic regression analysis was used to analyze the correlation between miR-9-5p and miR-128-3p levels and patient prognosis. RESULTS: The serum levels of miR-9-5p and miR-128-3p were upregulated in patients with AIS relative to those in healthy individuals. A pronounced correlation was identified between serum miR-9-5p and miR-128-3p levels and patient prognosis, with high levels of both miRNAs being associated with poor patient outcomes. CONCLUSION: Assessment of serum miR-9-5p and miR-128-3p levels is important for the early diagnosis and prognosis of AIS

Fault diagnosis method using support vector machine with improved complex system genetic algorithm

The idea of dimensional raising and linearization in support vector machine (SVM) provides a new solution for the diagnosis problem of reciprocating compressor in which the spatial distribution of fault data is complex. The selection of parameters in SVM has significant influence on the diagnosis performance. The excellent global searching ability of genetic algorithm (GA) makes itself suitable to optimize the parameters of SVM. However, GA needs many generations and longer training time which results in the low efficiency of diagnosis. To address this issue, a new fault diagnosis method ICSGA-SVM is proposed in this paper. ICSGA-SVM adopts the improved complex system genetic algorithm (ICSGA) to optimize the parameter in SVM. The complex system genetic algorithm (CSGA) applies the features of self-adaption and self-organization in complex system theory to the redesign of GA. According to the characteristics of the data set in reciprocating compressor, an adaptive mutation operator is created to replace the original mutation operator in CSGA. Besides, the gene floating operator in CSGA is removed in ICSGA to further improve the efficiency of the algorithm on-chip run. The simulation results on the fault data of reciprocating compressor indicate that our algorithm reduce the training time by 20.7 % when increasing diagnosis accuracy compared with the diagnosis method of SVM with GA (GA-SVM)

Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding

Contrastive learning, especially self-supervised contrastive learning (SSCL), has achieved great success in extracting powerful features from unlabeled data. In this work, we contribute to the theoretical understanding of SSCL and uncover its connection to the classic data visualization method, stochastic neighbor embedding (SNE), whose goal is to preserve pairwise distances. From the perspective of preserving neighboring information, SSCL can be viewed as a special case of SNE with the input space pairwise similarities specified by data augmentation. The established correspondence facilitates deeper theoretical understanding of learned features of SSCL, as well as methodological guidelines for practical improvement. Specifically, through the lens of SNE, we provide novel analysis on domain-agnostic augmentations, implicit bias and robustness of learned features. To illustrate the practical advantage, we demonstrate that the modifications from SNE to $t$-SNE can also be adopted in the SSCL setting, achieving significant improvement in both in-distribution and out-of-distribution generalization.Comment: Accepted by ICLR 202