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Inflation Targeting and Capital Flows: A Tale of Two Cycles in Developing Countries
No full textGlobal factors have traditionally determined capital flows, but domestic policies also matter. Developing countries face the challenge of managing procyclical capital inflows that can destabilize their macroeconomic environment. Inflation targeting can help solve this problem by enhancing the credibility and predictability of monetary policy. In this paper, we explore how inflation targeting affects the cyclical behavior of capital inflows in developing countries. First, we complement the data on international capital flows from the IMF with locational and consolidated banking statistics from the BIS. Second, we address the self-selection associated with inflation targeting by using entropy balancing. We find that inflation targeting reduces the procyclicality of capital inflows in developing countries. Specifically, inflation-targeting countries receive more (less) capital inflows during recessions (booms) than non-targeting countries. Other investment debt from the private sector mainly drives this effect. Our results are robust to various sensitivity checks and alternative specifications and methodologies
Exploring Evidentiary Approaches and Reform Potential in the Allies in Change Program for Abusive Intimate Partners
Get PDFThis thesis examines the Allies in Change batterer intervention program, analyzing its curriculum components, alignment with evidence-based practices, unique features, limitations, and implications for domestic violence intervention. The study employs a qualitative mixed-methods approach, including curriculum textual analysis, word frequency count, a semi-structured interview with Chris Huffine, the curriculum author and program founder, and observation of a forty-hour domestic violence training provided for batterer intervention programs and facilitators.
The research begins by reviewing the literature on domestic violence intervention, highlighting the importance of evidence-based practices, cognitive behavioral techniques, and cultural responsiveness. It then conducts a textual analysis of the Allies in Change curriculum, focusing on key themes such as self-care, core beliefs, emotional regulation, accountability, and peer support. The study reveals the program’s strong alignment with current best practices, including Cognitive Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), and trauma-informed approaches.
Distinctive features of the Allies in Change program include its nuanced approach to support provision, integration of collateral information, emphasis on group maturity and peer support dynamics, required reading material, and dedicated LGBTQ+ group. These elements enhance the program\u27s effectiveness and cultural responsiveness, catering to the diverse needs of participants.
However, limitations such as the absence of culturally specific groups beyond LGBTQ+ groups and the fee-based structure may hinder accessibility for marginalized individuals. Addressing these limitations is essential to improve inclusivity and effectiveness.
Recommendations for future research include longitudinal evaluations of program outcomes and innovative methods to enhance participant engagement and cultural inclusion. Implications for practice, policy, and research underscore the importance of evidence-based approaches, participant empowerment, and cultural responsiveness in domestic violence intervention.
This thesis provides valuable insights into the Allies in Change program, highlighting its strengths, unique features, limitations, and implications for addressing domestic violence. By leveraging evidence-based practices and promoting participant empowerment, interventions like Allies in Change can contribute significantly to preventing and mitigating domestic violence within communities
Burned out by the Binary: How Misgendering of Nonbinary Employees Contributes to Workplace Burnout
Get PDFWe examine nonbinary employees’ experiences with misgendering in work contexts and draw from minority stress theory (Meyer, 2003) to understand the consequences of misgendering. Our findings from 29 semi-structured interviews with nonbinary individuals revealed that although being misgendered is a common and highly stressful experience (distal stressor), the emotional labor associated with anticipating and reacting to misgendering acts as an additional and more proximal stressor. Together, these stressors jointly contribute to all three components of employee burnout (emotional exhaustion, depersonalization, and reduced professional efficacy). We also identified support from coworkers and supervisors (in preventing and addressing misgendering) as important ameliorating factors. As such, our findings provide support for the tenets of minority stress theory and extend this work by focusing specifically on nonbinary employees and on burnout, an important outcome for both employees and organizations. These findings provide a more complete understanding of the lived experiences of nonbinary employees and make unique contributions to the diversity/inclusion, gender studies, queer studies, work/life, and occupational health literatures
Rhizobia-legume Symbiosis mediates direct and indirect interactions between plants, herbivores and their parasitoids
Get PDFMicroorganisms associated with plant roots significantly impact the quality and quantity of plant defences. However, the bottom-up effects of soil microbes on the aboveground multitrophic interactions remain largely under studied. To address this gap, we investigated the chemically- mediated effects of nitrogen-fixing rhizobia on legume-herbivore-parasitoid multitrophic interactions. To address this, we initially examined the cascading effects of the rhizobia bean association on herbivore caterpillars, their parasitoids, and subsequently investigated how rhizobia influence on plant volatiles and extrafloral nectar. Our goal was to understand how these plant- mediated effects can affect parasitoids. Lima bean plants (Phaseoulus lunatus) inoculated with rhizobia exhibited better growth, and the number of root nodules positively correlated with defensive cyanogenic compounds. Despite increase of these chemical defences, Spodoptera latifascia caterpillars preferred to feed and grew faster on rhizobia-inoculated plants. Moreover, the emission of plant volatiles after leaf damage showed distinct patterns between inoculation treatments, with inoculated plants producing more sesquiterpenes and benzyl nitrile than non- inoculated plants. Despite these differences, Euplectrus platyhypenae parasitoid wasps were similarly attracted to rhizobia- or no rhizobia-treated plants. Yet, the oviposition and offspring development of E. platyhypenae was better on caterpillars fed with rhizobia-inoculated plants. We additionally show that rhizobia-inoculated common bean plants (Phaseolus vulgaris) produced more extrafloral nectar, with higher hydrocarbon concentration, than non-inoculated plants. Consequently, parasitoids performed better when fed with extrafloral nectar from rhizobia- inoculated plants. While the overall effects of bean-rhizobia symbiosis on caterpillars were positive, rhizobia also indirectly benefited parasitoids through the caterpillar host, and directly through the improved production of high quality extrafloral nectar. This study underscores the importance of exploring diverse facets and chemical mechanisms that influence the dynamics between herbivores and predators. This knowledge is crucial for gaining a comprehensive understanding of the ecological implications of rhizobia symbiosis on these interactions
Self-optimizing Feature Generation via Categorical Hashing Representation and Hierarchical Reinforcement Crossing
Get PDFFeature generation aims to generate new and meaningful features to create a discriminative representation space. A generated feature is meaningful when the generated feature is from a feature pair with inherent feature interaction. In the real world, experienced data scientists can identify potentially useful feature-feature interactions, and generate meaningful dimensions from an exponentially large search space in an optimal crossing form over an optimal generation path. But, machines have limited human-like abilities. We generalize such learning tasks as self-optimizing feature generation. Self-optimizing feature generation imposes several under-addressed challenges on existing systems: meaningful, robust, and efficient generation. To tackle these challenges, we propose a principled and generic representation-crossing framework to solve self-optimizing feature generation. To achieve hashing representation, we propose a three-step approach: feature discretization, feature hashing, and descriptive summarization. To achieve reinforcement crossing, we develop a hierarchical reinforcement feature crossing approach. We present extensive experimental results to demonstrate the effectiveness and efficiency of the proposed method. The code is available at https://github.com/yingwangyang/HRC_feature_cross.git
A Framework for Protecting and Promoting Employee Mental Health through Supervisor Supportive Behaviors
Get PDFThe attention to workplace mental health is timely given extreme levels of burnout, anxiety, depression and trauma experienced by workers due to serious extraorganizational stressors – the COVID-19 pandemic, threats to climate change, and extreme social and political unrest. Workplace-based risk factors, such as high stress and low support, are contributing factors to poor mental health and suicidality (Choi, 2018; Milner et al., 2013, 2018), just as low levels of social connectedness and belonging are established risk factors for poor mental health (Joiner et al., 2009), suggesting that social support at work (e.g., from supervisors) may be a key approach to protecting and promoting employee mental health. Social connections provide numerous benefits for health outcomes and are as, or more, important to mortality as other well-known health behaviors such as smoking and alcohol consumption (Holt-Lundstad et al., 2015), and can serve as a resource or buffer against the deleterious effects of stress or strain on psychological health (Cohen & Wills, 1985). This manuscript provides an evidence-based framework for understanding how supervisor supportive behaviors can serve to protect employees against psychosocial workplace risk factors and promote social connection and belongingness protective factors related to employee mental health. We identify six theoretically-based Mental Health Supportive Supervisor Behaviors (MHSSB; i.e., emotional support, practical support, role modeling, reducing stigma, warning sign recognition, warning sign response) that can be enacted and used by supervisors and managers to protect and promote the mental health of employees. A brief overview of mental health, mental disorders, and workplace mental health is provided. This is followed by the theoretical grounding and introduction of MHSSB. Suggestions for future research and practice follow, all with the focus of developing a better understanding of the role of supervisors in protecting and promoting employee mental health in the workplace
Gestural Temporality in Sciarrino’s Recitativo
Get PDFSciarrino’s writings describe a compositional philosophy that prizes multidimensionality and spatiotemporal discontinuity (1998, 2004). Yet his simultaneous allegiance to teleology, holism, and fractal hierarchies reveals an underlying unifying organicism with which these qualities may initially seem to conflict. I take Sciarrino’s 1999 piano concerto Recitativo oscuro as a case study for examining the composer’s gestural organicism and its various contradictions and double meanings. First, close analysis of the opening piano solo demonstrates how seemingly contradictory aesthetic priorities—organic unity and temporal multiplicity—co-exist within a single passage. Drawing from Kramer’s (1988) concept of “gestural time,” Hatten’s (2004) theory of gesture, segmentation theories, and scholarship on intensity and temporal function, I show how temporal multiplicity in the piano solo arises through conflict between gestural energetics and contextual segmentation. I then expand my analysis to the full concerto, arguing that the orchestra’s cyclic and naturalistic sonic ecosystem causes the piano gestures to take on representative functions in addition to their energetic syntax, creating what Sciarrino (2001) calls “dimensional intermittence” as they reference distant temporal realms both within and beyond the concerto. I conclude by arguing that while the intensity profile of the earliest gestures and phrases is eventually reproduced across the form of the entire work, the concerto’s form nevertheless resists reductive understanding. Instead, listeners are invited to hear form through the complex mechanics and idiosyncrasies of “gestural behavior” (Sciarrino 1998)
Non-native \u3cem\u3eRhizophora mangle\u3c/em\u3e as Sinks for Coastal Contamination on Moloka’i, Hawai’i
Get PDFCoastal mangrove forests provide a suite of environmental services, including sequestration of anthropogenic contamination. Yet, research lags on the environmental fate and potential human health risks of mangrove-sequestered contaminants in the context of mangrove removal for development and range shifts due to climate change. To address this, we conducted a study on Moloka\u27i, Hawai\u27i, comparing microplastic and pesticide contamination in coastal compartments both at areas modified by non-native red mangroves (Rhizophora mangle) and unmodified, open coastline. Sediment, porewater, and mangrove plant tissues were collected to quantify microplastic and pesticide concentrations across ecosystem type. Average microplastics were similar between mangrove (8.89 items/kg) and non-mangrove areas (9.01 items/kg) in sediment and porewater, but mangrove roots were a substantial reservoir of microplastics (2004 items/kg). Additionally, there was a strong relationship between proximity to urban development and microplastics detected. Six pesticides were detected, most commonly the insecticide bifenthrin, found in most sediment samples (11.3 ng/g), all root samples (243.3 ng/g), and one propagule sample (8.60 ng/g). Other pesticides detected with appreciable concentrations include the neonicotinoid insecticide imidacloprid and the legacy insecticide transformation product, p,p’-DDE. The other detections, all at concentrations \u3c 1 ng/g, were p,p’-DDT, trifluralin, and permethrin. The high concentrations of bifenthrin in roots compared to lower concentrations detected in sediment suggest that mangrove roots strongly accumulate some pesticides, indicating mangrove roots as a sink for organic contaminants. Study methods could be applied to other Hawaiian Islands and other locations where mangroves have been introduced to further examine the observed trends. Additional information is needed to investigate the fate and cycling of pesticides and microplastics adhered to mangrove roots, to better inform non-native mangrove removal efforts on Moloka\u27i and elsewhere
Product Specification: Distributed Control Module (DOE-PSU-0000922-5)
Get PDFThis product specification describes the architecture, implementation, and hardware descriptions of a Distributed Control Module (DCM) prototype. A DCM is an enabling technology for distributed energy resources (DER). DERs are grid-enabled generation, storage, and load devices that are owned by utility customers. DCMs enable information exchange between a distributed energy resource management system (DERMS) and DERs for the purpose of networking large numbers of DERs. The DCM prototype described within this document enables DER participation in a service-oriented aggregation system. A DERMS server provides IEEE 2030.5 smart energy resource services to DCM clients using a request/response information exchange process. DCMs serve as gateways between the DERMS and the DERs, and they act as agents on behalf of the DER owners to provide intelligent management of the DERs
On the Need to Address Fixed-Parameter Issues Before Applying Random Parameters: A Simulation-Based Study
No full textCount regression models have been applied to model expected crash frequency at individual roadway locations. Random parameters have been increasingly integrated into these models to account for unobserved heterogeneity. However, the introduction of random parameters might also mask issues in the model specification, leading to inaccurate relationships and model interpretation. Two of these specification-related issues are: (1) not considering the appropriate functional form of explanatory variables; and, (2) ignoring the best set of significant explanatory variables. To better examine the need for careful model specification, this study uses synthetic data to demonstrate that the consideration of random parameters does not address the two model specification issues identified. The results from the simulation study illustrate that (a) model specification issues cannot be circumvented by random parameters alone and (b) random parameter models including the exhaustive set of explanatory variables available offer significant model improvements