Building Resilience through Culturally Grounded Practices in Clinical Psychology and Higher Education

There is no “one size fits all” approach when it comes to the process of healing, particularly for individuals who are continuously affected by the many barriers and impacts of systemic oppres- sion. This reality demands the sustained development of a praxis rooted in trauma-informed and culturally grounded care so that we may better serve our most-impacted communities (such as Black, Indigenous and People of Color [BIPOC], disability, queer, and survivor communities). As practitioners in the fields of Clinical Psychology and Higher Education, we engage in cross-disciplinary analysis so that we may amplify and share our tools for collective healing. We highlight the importance of sup- porting client and student development through multisystemic and resilience-oriented frameworks. Specifically, we discuss the implications of the Minority Stress Model (Meyer, 2003) and Bronfenbrenner’s Ecological Systems Theory (1979) in serving our communities more effectively to enhance positive clinical and academic outcomes

Hybrid Profiling in Information Retrieval

Abstract-One of the main challenges in search engine quality of service is how to satisfy the needs and the interests of individual users. This raises the fundamental issue of how to identify and select the information that is relevant to a specific user. This concern over generic provision and the lack of search precision have provided the impetus for the research into Web Search personalisation. In this paper a hybrid user profiling system is proposed -a combination of explicit and implicit user profiles for improving the web search effectiveness in terms of precision and recall. The proposed system is content-based and implements the Vector Space Model. Experimental results, supported by significance tests, indicate that the system offers better precision and recall in comparison to traditional search engines

Conduits of Intratumor Heterogeneity: Centrosome Amplification, Centrosome Clustering and Mitotic Frequency

Tumor initiation and progression is dependent on the acquisition and accumulation of multiple driver mutations that acti­vate and fuel oncogenic pathways and deactivate tumor suppressor networks. This complex continuum of non-stochastic genetic changes in accompaniment with error-prone mitoses largely explains why tumors are a mosaic of different cells. Contrary to the long-held notion that tumors are dominated by genetically-identical cells, tumors often contain many different subsets of cells that are remarkably diverse and distinct. The extent of this intratumor heterogeneity has bewildered cancer biologists’ and clinicians alike, as this partly illuminates why most cancer treatments fail. Unsurprisingly, there is no “wonder” drug yet available which can target all the different sub-populations including rare clones, and conquer the war on cancer. Breast tumors harbor ginormous extent of intratumoral heterogeneity, both within primary and metastatic lesions. This revelation essentially calls into question mega clinical endeavors such as the Human Genome Project that have sequenced a single biopsy from a large tumor mass thus precluding realization of the fact that a single tumor mass comprises of cells that present a variety of flavors in genotypic compositions. It is also becoming recognized that intratumor clonal heterogeneity underlies therapeutic resistance. Thus to comprehend the clinical behavior and therapeutic management of tumors, it is imperative to recognize and understand how intratumor heterogeneity arises. To this end, my research proposes to study two main features/cellular traits of tumors that can be quantitatively evaluated as “surrogates” to represent tumor heterogeneity at various stages of the disease: (a) centrosome amplification and clustering, and (b) mitotic frequency. This study aims at interrogating how a collaborative interplay of these “vehicles” support the tumor’s evolutionary agenda, and how we can glean prognostic and predictive information from an accurate determination of these cellular traits

Bridging the Safe Drinking Water Gap for California’s Rural Poor

Spurred by decades of inaction and continued exposure to unsafe drinking water, community leaders from California’s disadvantaged communities (DACs) advocated for the creation of a human right to water under state law. Shortly thereafter, the California Legislature put forward a bond to finance much needed water infrastructure improvements and drought relief interventions across the state. Voters approved the $7.45 billion bond, which reserved millions of dollars of funding for DACs with persistent water quality problems. In setting aside those funds, the Legislature acknowledged that decades of disinvestment in rural, disadvantaged communities had created severe water contamination, limited water access, and degraded water infrastructure. The bond’s initiating legislation tacitly recognized that taxing DAC residents was futile; those residents had the fewest resources available to address the disinvestment that compounded their water inequality

Framework for Simulation of Coupled Systems by Aggregation

Complex systems can be described by coupling several standalone ODE problems that communicate with input and output signals. The need for simulating such systems has increased in recent years. A major issue when simulating coupled ODE systems has been to communicate coupling relations properly throughout integration and how to handle discontinuities. In this paper a concept that aggregates several ODEs into a single problem is presented. For each right-hand-side function evaluation the aggregated problem communicates coupling relations ensuring that all inputs and outputs in the system are uptodate. Experiments are conducted on systems containing algebraic loops, discontinuities and non-linear couplings; the results suggest potential for the concept

Transnational Corporate Regulation through Sustainability Reporting: A Case Study of the Canadian Extractive Sector

Despite the benefits transnational corporations (TNCs) offer, they remain largely unregulated entities, enabling environmental, social, and human rights violations to be overlooked. Canadian extractive sector TNCs operating internationally are frequently cited as major perpetrators of such violations. Literature on new governance and self-regulation as well as global corporate social responsibility (CSR) increasingly offers disclosure and reporting as a solution for TNC regulation. This study examines disclosure in international CSR frameworks, and the reflexive law and new governance theories explaining the role of such disclosure and reporting. Mirroring international CSR initiatives, Canadian jurisdictions are increasingly recommending disclosure for its extractive sector TNCs, including through its securities laws. Securities law provides a promising foundation for sustainability reporting because of its existing disclosure framework and its ability to compel disclosure. This potential of Canadian securities law also provides a basis for comparison with the Global Reporting Initiative, the leading sustainability reporting standard

Hedge Fund Performance with the Treynor-Black Model

This paper seeks to analyze the information ratio differences between long/short hedge funds over the past two decades using the Treynor-Black model. The Treynor-Black model is a method to derive an optimal portfolio allocation across safe and risky assets, based off of expected alphas of active investments and the unsystematic volatility that can be attributed to each given security. We first developed and implemented a model to forecast information ratios on a database of long/short hedge funds. With the predicted information ratios, we calculated out-of-sample allocation weights from a Treynor-Black active portfolio model. These weights were then tested in a long/short format against a Naive model that invests equally in all hedge funds. By subtracting the Naive weights from the Treynor-Black weight recommendations, we were able to test the efficacy of the Treynor-Black model under performance-neutral circumstances. We found that the Treynor-Black model outperforms in a market that is trending upwards, such as 2017. In a market with a correction, as seen in December 2018, the Treynor-Black model performs in-line with the Naive, generating minimum excess return but taking on no additional risk. Following a market correction into another upwards market (seen in 2019), the Treynor-Black model is not nearly as effective. Due to the importance of the previous year\u27s information ratio, the recommended allocations expected a continuation of market risk and overcorrected. We conclude that information ratio predictions combined with the Treynor-Black model can help generate alpha in a bull market, while taking on average downside risk in a turbulent market, instead of undue downside exposure as seen in some funds