The two faces of power-sharing

Lijphart’s claim that power-sharing spurs democratization in divided societies has strongly influenced ‘institutional engineering’ and is widely accepted among scholars despite the fact that empirical tests of its merits remain rare. This article revisits the democratic effect of power-sharing, arguing that it has two antagonist faces. On the positive side, it provides guarantees of inclusion to political elites, allowing them to commit to democratic rules. On the negative side, it also has an illiberal face, entailing limits on competition and individual rights. In this article, these contrary characteristics are traced back to two institutional types of power-sharing: a more flexible and open, liberal, type and a more rigid, corporate one. Using a novel dataset on power-sharing rules for 138 multi-ethnic countries and the period from 1945 to 2016, their respective democratic merits are tested. Conforming to theoretical expectations, the findings indicate that only liberal forms of power-sharing exhibit strong positive effects on democracy while corporate forms exert mixed or even negative ones. These findings are robust to a series of alternate model specifications and operationalizations as well as to instrumental variable approaches. In conclusion, the article indicates only a partial democratic effect of power-sharing, limited to its liberal subtype.

Knockdown and Knockout of Tissue Factor Pathway Inhibitor in Zebrafish

Tissue Factor Pathway Inhibitor (TFPI) is an anticoagulant that inhibits factor VIIa and Xa in the blood coagulation pathways. TFPI contains three Kunitz domains, K1, K2, and K3. K1 and K2 inhibit factor VIIa and Xa, respectively. However, the regulation of TFPI is poorly studied. Since zebrafish has become an alternate model to discover novel actors in hemostasis, we hypothesized that TFPI regulation could be studied using this model. As a first step, we confirmed the presence of tfpia in zebrafish using RT-PCR. We then performed piggyback knockdowns of tfpia and found increased coagulation activity in tfpia knockdown. We then created a deletion mutation in tfpia locus using CRISPR/Cas9 method. The tfpia homozygous deletion mutants showed increased coagulation activities similar to that found in tfpia knockdown. Taken together, our data suggest that tfpia is a negative regulator for zebrafish coagulation, and silencing it leads to thrombotic phenotype. Also, the zebrafish tfpia knockout model could be used for reversing this thrombotic phenotype to identify antithrombotic novel factors by the genome-wide piggyback knockdown method.

A pessimistic bilevel stochastic problem for elastic shape optimization

We consider pessimistic bilevel stochastic programs in which the follower maximizes over a fixed compact convex set a strictly convex quadratic function, whose Hessian depends on the leader’s decision. This results in a random upper level outcome which is evaluated by a convex risk measure. Under assumptions including real analyticity of the lower-level goal function, we prove the existence of optimal solutions. We discuss an alternate model, where the leader hedges against optimal lower-level solutions, and show that solvability can be guaranteed under weaker conditions in both, a deterministic and a stochastic setting. The approach is applied to a mechanical shape optimization problem in which the leader decides on an optimal material distribution to minimize a tracking-type cost functional, whereas the follower chooses forces from an admissible set to maximize a compliance objective. The material distribution is considered to be stochastically perturbed in the actual construction phase. Computational results illustrate the bilevel optimization concept and demonstrate the interplay of follower and leader in shape design and testing.

Pre-implantation mouse embryo movement under hormonally altered conditions

Precise regulation of embryo movement is crucial to successful implantation, but the role of ovarian hormones in this process is not understood. We ascertain the effects of altered hormonal environment on embryo movement using two delayed implantation models: Natural lactational Diapause (ND), a naturally occurring alternate model of pregnancy, and Artificially induced Diapause (AD), a laboratory version of ND. Our previous work suggests that embryos in a natural pregnancy (NP) first display unidirectional clustered embryo movement, followed by bidirectional scattering and spacing movement. In contrast, in the ND model, embryos are present as clusters near the oviductal-uterine junction for ~24-hours longer than NP, followed by locations consistent with a unidirectional scattering and spacing movement. Intriguingly, the AD model closely resembles embryo location in NP and not ND. Further, unlike the popular paradigm of reduced estrogen (E2) levels in diapause E2 levels are comparable across NP, ND, and AD, while progesterone (P4) levels are reduced in ND and highly increased in AD when compared to NP. Exogenous administration of E2 or P4 modifies the unidirectional clustered embryo movement, while E2 treatment causes a reduction in P4 and affects the bidirectional phase of embryo movement. Taken together, our data suggest embryo movement can be modulated by both P4 and E2. Understanding natural hormonal adaptation in diapause provides an opportunity to determine key players regulating embryo movement and implantation success. This knowledge can be leveraged to understand pregnancy survival and implantation success in hormonally altered conditions in the clinic.

The relation between public assistance and self-employment in census tracts: a long-term perspective

We present evidence on the long-term relationship between the breadth (the proportion of households) and depth (the amount per household) of public assistance and the prevalence of self-employment in US neighbourhoods. The analysis of decennial data of 71,437 census tracts over four decades (1970 to 2000) shows that the poverty ratio lowers self-employment, and that breadth (but not depth) of public assistance mitigates the negative relationship between the poverty ratio and self-employment. The results are robust to alternate model specifications and are informative about the distributional effects of welfare spendings.

Confirmatory Factor Analysis of the Athlete Sleep Behavior Questionnaire

Context: Sleep has long been understood as an essential component for overall well-being, significantly impacting physical health, cognitive functioning, mental health, and quality of life. Currently, the Athlete Sleep Behavior Questionnaire (ASBQ) is the only known instrument designed to measure sleep behaviors in the athletic population. However, the psychometric properties of the scale in a collegiate student-athlete and dance population have not been established. Objective: To assess model fit of the ASBQ using a sample of collegiate student-athletes and competitive dancers. Design: Observational study. Setting: Twelve colleges and universities. Patients or Other Participants: Student-athletes and dancers competing at the collegiate level. Main Outcome Measure(s): A confirmatory factor analysis (CFA) was conducted to assess the factor structure of the ASBQ. Principal component analysis (PCA) extraction and covariance modeling analyses were performed to identify an alternate model. Multi-group invariance testing was performed on the alternate model to identify if group differences existed between sex, athletic activity, injury status, and division of competition. Results: The CFA on the ASBQ indicated the model did not meet recommended model fit indices. An alternate three-factor, nine-item model with improved fit was identified; however, the scale structure was not consistently supported during multi-group invariance testing procedures. Conclusions: The original three factor, 18-item ASBQ was not supported for use with collegiate athletes in our study. The alternate ASBQ was substantially improved; however, more research should be completed to ensure the nine-item instrument accurately captures all dimensions of sleep behavior relevant for collegiate athletes.

BEEM-Static: Accurate inference of ecological interactions from cross-sectional microbiome data

The structure and function of diverse microbial communities is underpinned by ecological interactions that remain uncharacterized. With rapid adoption of next-generation sequencing for studying microbiomes, data-driven inference of microbial interactions based on abundance correlations is widely used, but with the drawback that ecological interpretations may not be possible. Leveraging cross-sectional microbiome datasets for unravelling ecological structure in a scalable manner thus remains an open problem. We present an expectation-maximization algorithm (BEEM-Static) that can be applied to cross-sectional datasets to infer interaction networks based on an ecological model (generalized Lotka-Volterra). The method exhibits robustness to violations in model assumptions by using statistical filters to identify and remove corresponding samples. Benchmarking against 10 state-of-the-art correlation based methods showed that BEEM-Static can infer presence and directionality of ecological interactions even with relative abundance data (AUC-ROC>0.85), a task that other methods struggle with (AUC-ROC<0.63). In addition, BEEM-Static can tolerate a high fraction of samples (up to 40%) being not at steady state or coming from an alternate model. Applying BEEM-Static to a large public dataset of human gut microbiomes (n = 4,617) identified multiple stable equilibria that better reflect ecological enterotypes with distinct carrying capacities and interactions for key species. Conclusion BEEM-Static provides new opportunities for mining ecologically interpretable interactions and systems insights from the growing corpus of microbiome data.

A Multi-omic Huntington’s Disease Transgenic Sheep-Model Database for Investigating Disease Pathogenesis

Background: The pathological mechanism of cellular dysfunction and death in Huntington’s disease (HD) is not well defined. Our transgenic HD sheep model (OVT73) was generated to investigate these mechanisms and for therapeutic testing. One particular cohort of animals has undergone focused investigation resulting in a large interrelated multi-omic dataset, with statistically significant changes observed comparing OVT73 and control ‘omic’ profiles and reported in literature. Objective: Here we make this dataset publicly available for the advancement of HD pathogenic mechanism discovery. Methods: To enable investigation in a user-friendly format, we integrated seven multi-omic datasets from a cohort of 5-year-old OVT73 (n = 6) and control (n = 6) sheep into a single database utilising the programming language R. It includes high-throughput transcriptomic, metabolomic and proteomic data from blood, brain, and other tissues. Results: We present the ‘multi-omic’ HD sheep database as a queriable web-based platform that can be used by the wider HD research community (https://hdsheep.cer.auckland.ac.nz/). The database is supported with a suite of simple automated statistical analysis functions for rapid exploratory analyses. We present examples of its use that validates the integrity relative to results previously reported. The data may also be downloaded for user determined analysis. Conclusion: We propose the use of this online database as a hypothesis generator and method to confirm/refute findings made from patient samples and alternate model systems, to expand our understanding of HD pathogenesis. Importantly, additional tissue samples are available for further investigation of this cohort.

AN OBSERVATIONAL STUDY ON THE CONSTRUCTION AND FUNCTIONS OF A WATER CLOCK

This study examines the workings of a water clock and attempts to formulate alternatives while retaining the basic principles of Torricellis law. There is thorough discussion on the history of water clocks, their different types and the apparatus required to model the functioning prototype. This is followed by a detailed explanation of the procedure undertaken for the construction of the alternate model. In the interpretation and results section, readings and observations measured through 18 different experiments are tabulated through charts and graphs, leading up to a summarized discussion in the conclusion.