A Disclosure-Focused Approach to Compelled Commercial Speech

In 2010, the Food and Drug Administration passed a rule revising compelled disclaimers on tobacco products pursuant to the Family Smoking Prevention and Tobacco Control Act. The rule required that tobacco warnings include something new: all tobacco products now had to bear one of nine graphic images to accompany the text. Tobacco companies filed suit contesting the constitutionality of the rule, arguing that the government violated their right to free commercial speech by compelling disclosure of the graphic content. Yet First Amendment jurisprudence lacks a doctrinally consistent standard for reviewing such compelled disclosures. Courts’ analyses typically depend on whether the regulation compels or restricts speech, how far that regulation extends, and why the government chose to regulate in the first place. This Note seeks to articulate a coherent standard-—a disclosure-focused approach—-for reviewing compelled commercial speech under the First Amendment. Under this disclosure-focused approach, courts would adopt a lenient standard of review for compelled disclosures of factual, uncontroversial information while reserving more exacting scrutiny for restricted speech or compelled ideological disclosures. This approach centers on the structure and content of the regulation rather than the governmental motive. Accordingly, the disclosure-focused approach aligns with the goal of commercial speech protection—-namely, maximizing the information available to consumers

Overhauling Rules of Evidence in Pro Se Courts

State civil courtrooms are packed to the brim with litigants, but not with lawyers. Since the early 1990s, more and more litigants in state courts have appeared without legal counsel. Pro se litigation has grown consistently and enormously over the past few decades. State court dockets are dominated by cases brought by unrepresented litigants, most often in domestic violence, family law, landlord-tenant, and small claims courts. Yet, the American courtroom is not designed for use by those unrepresented litigants—it is designed for use by attorneys. The American civil court is built upon a foundation of dense procedural rules, thick tomes of long-evolved substantive law, and—the focus of this piece—a complex set of evidentiary prohibitions and exceptions. The American civil court is designed for two competing adversaries to face off against one another. It is built on the assumption that both of those adversaries will present the best case they can, employing an accurate understanding of the complex rules and laws that govern the proceedings. Nonlawyer pro se litigants often struggle to adhere to the norms of the adversarial American legal system. As a result, complex legal rules present an access-to-justice barrier to unrepresented litigants unable to comply with them

Reforming Service of Process: An Access-to-Justice Framework

Over the past few decades, the number of pro se litigants in state civil courts has risen exponentially-between 75 percent and 90 percent of litigants in family law cases, landlordtenant disputes, and small claims actions did not have a lawyer in 2015. Procedural rules governing those proceedings, however, often impose requirements that disproportionately burden unrepresented litigants, fail to optimally protect the due process rights of those parties, and thereby deny them access to justice. Rules governing service of process illustrate this problem by requiring litigants to find a third party to hand-deliver court papers to a defendant directly or to a co-resident at the defendant\u27s home. For many low income, pro se litigants, this poses a significant barrier: housing instability, homelessness, and unemployment make it extraordinarily difficult to locate low-income defendants and serve them in the manner prescribed by the rules, a task made even more challenging by the requirement that the plaintiff secure a third party to serve. Until plaintiffs can accomplish service, they are denied access to a hearing on the merits of their claim and defendants are denied notice of the claims brought against them. In short, burdensome service of process rules bar access to justice for both parties. Using those service of process rules as a case study, this article advances an access-to-justice framework through which rulemakers can re-evaluate procedural rules in courts hearing predominately pro se cases and better protect the parties\u27 procedural interests. First, rulemakers must identify the full scope of procedural rights at stake for both parties. Second, rulemakers should view the rules in context, considering how the rules operate in practice, the experiences of each class of litigants involved, and how the rules will affect low-income, unrepresented litigants in particular. Finally, rulemakers should adjust the rules to reflect that context, aiming to optimally protect each procedural interest at stake. Applying this framework to service of process rules in domestic violence cases shows that both parties\u27 rights can be better protected by allowing a new form of service of process: service through electronic media, such as text message, email, and social media messaging. By updating court rules to capture the realities of low-income, pro se litigants, the legal community can increase efficiency and fairness, thereby giving litigants better access to the just resolution of legal disputes

Symbolic analysis of bursting dynamical regimes of Rulkov neural networks

Neurons modeled by the Rulkov map display a variety of dynamic regimes that include tonic spikes and chaotic bursting. Here we study an ensemble of bursting neurons coupled with the Watts-Strogatz small-world topology. We characterize the sequences of bursts using the symbolic method of time-series analysis known as ordinal analysis, which detects nonlinear temporal correlations. We show that the probabilities of the different symbols distinguish different dynamical regimes, which depend on the coupling strength and the network topology. These regimes have different spatio-temporal properties that can be visualized with raster plots

Theory of transient chimeras in finite Sakaguchi-Kuramoto networks

Chimera states are a phenomenon in which order and disorder can co-exist within a network that is fully homogeneous. Precisely how transient chimeras emerge in finite networks of Kuramoto oscillators with phase-lag remains unclear. Utilizing an operator-based framework to study nonlinear oscillator networks at finite scale, we reveal the spatiotemporal impact of the adjacency matrix eigenvectors on the Sakaguchi-Kuramoto dynamics. We identify a specific condition for the emergence of transient chimeras in these finite networks: the eigenvectors of the network adjacency matrix create a combination of a zero phase-offset mode and low spatial frequency waves traveling in opposite directions. This combination of eigenvectors leads directly to the coherent and incoherent clusters in the chimera. This approach provides two specific analytical predictions: (1) a precise formula predicting the combination of connectivity and phase-lag that creates transient chimeras, (2) a mathematical procedure for rewiring arbitrary networks to produce transient chimeras

Ensemble Concerts: Normal West High School Wind Ensemble and Wind Symphony, April 5, 2023

Center for the Performing ArtsApril 5, 2023Wednesday Evening7:00 p.m

Caged Gammarus fossarum (crustacea) as a robust tool for the characterization of bioavailable contamination levels in continental waters. Toward the determination of threshold values

We investigated the suitability of an active biomonitoring approach, using the ecologically relevant species Gammarus fossarum, to assess trends of bioavailable contamination in continental waters. Gammarids were translocated into cages at 27 sites, in the Rhône-Alpes region (France) during early autumn 2009. Study sites were chosen to represent different physico-chemical characteristics and various anthropic pressures. Biotic factors such as sex, weight and food availability were controlled in order to provide robust and comparable results. After one week of exposure, concentrations of 11 metals/metalloids (Cd, Pb, Hg, Ni, Zn, Cr, Co, Cu, As, Se and Ag) and 38 hydrophobic organic substances including polycyclic aromatic hydrocarbons (PAHs), polychlorobiphenyles (PCBs), pentabromodiphenylethers (PBDEs) and organochlorine pesticides, were measured in gammarids. All metals except Ag, and 33 organic substances among 38 were quantified in G. fossarum, showing that this species is relevant for chemical biomonitoring. The control of biotic factors allowed a robust and direct inter-site comparison of the bioavailable contamination levels. Overall, our results show the interest and robustness of the proposed methodological approach for assessing trends of bioavailable contamination, notably for metals and hydrophobic organic contaminants, in continental waters. Furthermore, we built threshold values of bioavailable contamination in gammarids, above which measured concentrations are expected to reveal a bioavailable contamination at the sampling site. Two ways to define such values were investigated, a statistical approach and a model fit. Threshold values were determined for almost all the substances investigated in this study and similar values were generally derived from the two approaches. Then, levels of contaminants measured in G. fossarum at the 27 study were compared to the threshold values obtained using the model fit. These threshold values could serve as a basis for further implementation of quality grids to rank sites according to the extent of the bioavailable contamination, with regard to the applied methodology

Composed solutions of synchronized patterns in multiplex networks of Kuramoto oscillators

Networks with different levels of interactions, including multilayer and multiplex networks, can display a rich diversity of dynamical behaviors and can be used to model and study a wide range of systems. Despite numerous efforts to investigate these networks, obtaining mathematical descriptions for the dynamics of multilayer and multiplex systems is still an open problem. Here, we combine ideas and concepts from linear algebra and graph theory with nonlinear dynamics to offer a novel approach to study multiplex networks of Kuramoto oscillators. Our approach allows us to study the dynamics of a large, multiplex network by decomposing it into two smaller systems: one representing the connection scheme within layers (intra-layer), and the other representing the connections between layers (inter-layer). Particularly, we use this approach to compose solutions for multiplex networks of Kuramoto oscillators. These solutions are given by a combination of solutions for the smaller systems given by the intra and inter-layer system and, in addition, our approach allows us to study the linear stability of these solutions

Discriminating chaotic and stochastic time series using permutation entropy and artificial neural networks

Extracting relevant properties of empirical signals generated by nonlinear, stochastic, and high-dimensional systems is a challenge of complex systems research. Open questions are how to differentiate chaotic signals from stochastic ones, and how to quantify nonlinear and/or high-order temporal correlations. Here we propose a new technique to reliably address both problems. Our approach follows two steps: first, we train an artificial neural network (ANN) with flicker (colored) noise to predict the value of the parameter, $\alpha$, that determines the strength of the correlation of the noise. To predict $\alpha$ the ANN input features are a set of probabilities that are extracted from the time series by using symbolic ordinal analysis. Then, we input to the trained ANN the probabilities extracted from the time series of interest, and analyze the ANN output. We find that the $\alpha$ value returned by the ANN is informative of the temporal correlations present in the time series. To distinguish between stochastic and chaotic signals, we exploit the fact that the difference between the permutation entropy (PE) of a given time series and the PE of flicker noise with the same $\alpha$ parameter is small when the time series is stochastic, but it is large when the time series is chaotic. We validate our technique by analysing synthetic and empirical time series whose nature is well established. We also demonstrate the robustness of our approach with respect to the length of the time series and to the level of noise. We expect that our algorithm, which is freely available, will be very useful to the community