Calling in the United States: prevalence and the role of source

2018 Spring.Includes bibliographical references.Research on calling as a construct in vocational psychology has grown substantially in the past decade. However, questions pertaining to the prevalence of calling and role of source of calling remain unanswered. The present study used data from Wave 2 of the Portraits of American Life Study: a nationally stratified panel study of religion in the United States. Part One of this study sought to estimate the prevalence of calling in the United States while Part Two investigated whether or not participants' source of calling affected relationships between living a calling, job satisfaction, and well-being correlates. In general, estimates in this study suggest that calling is a relevant concept for many adults throughout the United States, with significant differences in presence of and search for calling being found for age, employment status, and the importance of God or spirituality. Additionally, results demonstrated that source of calling moderated the relationship between living a calling and job satisfaction such that, for those citing an external source of calling, living a calling was not predictive of job satisfaction. Furthermore, importance of God or spirituality was found to be an important predictor of living a calling, purpose in life, and hope for the future. These findings represent the first known population estimates of calling in the United States and extend the existing literature on calling by providing further information pertaining to the relative importance of source of calling and spirituality in predicting relevant work and well-being outcomes

TRIO program: How community college TRIO participation can enhance academic success for university transfer students

The purpose of the current study was to determine if participation in a TRIO program at the community college would lead to academic success for transfer students at the 4-year university. Specifically, the researcher collected data for students who participated in a TRIO program at a community college from 2010-2020 to see if they had higher rates of graduation, higher rates of enrollment and completion, and higher GPAs as compared to similar students who were not involved in TRIO at a community college. The independent variables were TRIO participation, gender, first-generation status, Pell status, transfer GPA, and transfer credit hours earned. A total of 2193 transfer students from two community colleges in the southeastern region of the United States were included in this study. There were 77 transfer students who were involved in a TRIO program at a community college and 2116 transfer students who were not involved in a TRIO program. There were 8 students who were involved in a TRIO program at both institutions. A binary logistic regression was run to determine how TRIO participation affected graduation, enrollment and completion, and GPA for transfer students at the 4-year university. Transfer TRIO participation, gender, and Pell status were not significant predictors of graduation. First-generation status, although research has shown that continuing-generation students graduate at higher rates than first-generation students, was significant in terms of graduation for transfer students. Transfer GPA, and transfer credit hours earned were also found to be significant predictors of graduation for transfer students at the 4-year university. Transfer TRIO participation and Pell status were not significant predictors of enrollment and completion. Gender, in terms of females when compared to males, was a significant factor for whether a student was still enrolled or completed their degree. First-generation status, transfer GPA, and transfer credit hours earned were also significant predictors of enrollment and completion. Transfer TRIO participation, gender, Pell status, and first-generation status were found to be significant for GPA

Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

Face recognition systems are widely deployed in safety-critical applications, including law enforcement, yet they exhibit bias across a range of socio-demographic dimensions, such as gender and race. Conventional wisdom dictates that model biases arise from biased training data. As a consequence, previous works on bias mitigation largely focused on pre-processing the training data, adding penalties to prevent bias from effecting the model during training, or post-processing predictions to debias them, yet these approaches have shown limited success on hard problems such as face recognition. In our work, we discover that biases are actually inherent to neural network architectures themselves. Following this reframing, we conduct the first neural architecture search for fairness, jointly with a search for hyperparameters. Our search outputs a suite of models which Pareto-dominate all other high-performance architectures and existing bias mitigation methods in terms of accuracy and fairness, often by large margins, on the two most widely used datasets for face identification, CelebA and VGGFace2. Furthermore, these models generalize to other datasets and sensitive attributes. We release our code, models and raw data files at https://github.com/dooleys/FR-NAS

When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Tabular data is one of the most commonly used types of data in machine learning. Despite recent advances in neural nets (NNs) for tabular data, there is still an active discussion on whether or not NNs generally outperform gradient-boosted decision trees (GBDTs) on tabular data, with several recent works arguing either that GBDTs consistently outperform NNs on tabular data, or vice versa. In this work, we take a step back and question the importance of this debate. To this end, we conduct the largest tabular data analysis to date, comparing 19 algorithms across 176 datasets, and we find that the 'NN vs. GBDT' debate is overemphasized: for a surprisingly high number of datasets, either the performance difference between GBDTs and NNs is negligible, or light hyperparameter tuning on a GBDT is more important than choosing between NNs and GBDTs. A remarkable exception is the recently-proposed prior-data fitted network, TabPFN: although it is effectively limited to training sets of size 3000, we find that it outperforms all other algorithms on average, even when randomly sampling 3000 training datapoints. Next, we analyze dozens of metafeatures to determine what properties of a dataset make NNs or GBDTs better-suited to perform well. For example, we find that GBDTs are much better than NNs at handling skewed or heavy-tailed feature distributions and other forms of dataset irregularities. Our insights act as a guide for practitioners to determine which techniques may work best on their dataset. Finally, with the goal of accelerating tabular data research, we release the TabZilla Benchmark Suite: a collection of the 36 'hardest' of the datasets we study. Our benchmark suite, codebase, and all raw results are available at https://github.com/naszilla/tabzilla.Comment: NeurIPS Datasets and Benchmarks Track 202

Radio Galaxy Zoo: Towards building the first multi-purpose foundation model for radio astronomy with self-supervised learning

In this work, we apply self-supervised learning with instance differentiation to learn a robust, multi-purpose representation for image analysis of resolved extragalactic continuum images. We train a multi-use model which compresses our unlabelled data into a structured, low dimensional representation which can be used for a variety of downstream tasks (e.g. classification, similarity search). We exceed baseline supervised Fanaroff-Riley classification performance by a statistically significant margin, with our model reducing the test set error by up to half. Our model is also able to maintain high classification accuracy with very few labels, with only 7.79% error when only using 145 labels. We further demonstrate that by using our foundation model, users can efficiently trade off compute, human labelling cost and test set accuracy according to their respective budgets, allowing for efficient classification in a wide variety of scenarios. We highlight the generalizability of our model by showing that it enables accurate classification in a label scarce regime with data from the new MIGHTEE survey without any hyper-parameter tuning, where it improves upon the baseline by ~8%. Visualizations of our labelled and un-labelled data show that our model's representation space is structured with respect to physical properties of the sources, such as angular source extent. We show that the learned representation is scientifically useful even if no labels are available by performing a similarity search, finding hybrid sources in the RGZ DR1 data-set without any labels. We show that good augmentation design and hyper-parameter choice can help achieve peak performance, while emphasising that optimal hyper-parameters are not required to obtain benefits from self-supervised pre-training

TNF-Receptor Inhibitor Therapy for the Treatment of Children with Idiopathic Pneumonia Syndrome. A Joint Pediatric Blood and Marrow Transplant Consortium and Children's Oncology Group Study (ASCT0521)

AbstractIdiopathic pneumonia syndrome (IPS) is an acute, noninfectious lung disorder associated with high morbidity and mortality after hematopoietic cell transplantation. Previous studies have suggested a role for TNFα in the pathogenesis of IPS. We report a multicenter phase II trial investigating a soluble TNF-binding protein, etanercept (Enbrel, Amgen, Thousand Oaks, CA), for the treatment of pediatric patients with IPS. Eligible patients were < 18 years old, within 120 days after transplantation, and with radiographic evidence of a diffuse pneumonitis. All patients underwent a pretherapy broncho-alveolor lavage (BAL) to establish the diagnosis of IPS. Systemic corticosteroids (2.0 mg/kg/day) plus etanercept (.4 mg/kg twice weekly × 8 doses) were administered. Response was defined as survival and discontinuation of supplemental oxygen support by day 28 of study. Thirty-nine patients (median age, 11 years; range, 1 to 17) were enrolled, with 11 of 39 patients nonevaluable because of identification of pathogens from their pretherapy BAL. In the remaining 28 patients, the median fraction of inspired oxygen at study entry was 45%, with 17 of 28 requiring mechanical ventilation. Complete responses were seen in 20 (71%) patients, with a median time to response of 10 days (range, 1 to 24). Response rates were higher for patients not requiring mechanical ventilation at study entry (100% versus 53%, P = .01). Overall survival at 28 days and 1 year after therapy were 89% (95% confidence interval [CI], 70% to 96%) and 63% (95% CI, 42% to 79%), respectively. Plasma levels of proinflammatory cytokines were significantly increased at onset of therapy, subsequently decreasing in responding patients. The addition of etanercept to high-dose corticosteroids was associated with high response rates and survival in children with IPS

Upregulation of the cell-cycle regulator RGC-32 in Epstein-Barr virus-immortalized cells

Epstein-Barr virus (EBV) is implicated in the pathogenesis of multiple human tumours of lymphoid and epithelial origin. The virus infects and immortalizes B cells establishing a persistent latent infection characterized by varying patterns of EBV latent gene expression (latency 0, I, II and III). The CDK1 activator, Response Gene to Complement-32 (RGC-32, C13ORF15), is overexpressed in colon, breast and ovarian cancer tissues and we have detected selective high-level RGC-32 protein expression in EBV-immortalized latency III cells. Significantly, we show that overexpression of RGC-32 in B cells is sufficient to disrupt G2 cell-cycle arrest consistent with activation of CDK1, implicating RGC-32 in the EBV transformation process. Surprisingly, RGC-32 mRNA is expressed at high levels in latency I Burkitt's lymphoma (BL) cells and in some EBV-negative BL cell-lines, although RGC-32 protein expression is not detectable. We show that RGC-32 mRNA expression is elevated in latency I cells due to transcriptional activation by high levels of the differentially expressed RUNX1c transcription factor. We found that proteosomal degradation or blocked cytoplasmic export of the RGC-32 message were not responsible for the lack of RGC-32 protein expression in latency I cells. Significantly, analysis of the ribosomal association of the RGC-32 mRNA in latency I and latency III cells revealed that RGC-32 transcripts were associated with multiple ribosomes in both cell-types implicating post-initiation translational repression mechanisms in the block to RGC-32 protein production in latency I cells. In summary, our results are the first to demonstrate RGC-32 protein upregulation in cells transformed by a human tumour virus and to identify post-initiation translational mechanisms as an expression control point for this key cell-cycle regulator

Drones y el orden legal internacional. Tecnología, estrategia y largas cadenas de acción

The main thesis of this article is that the increasing recourse to the use of unmanned aerial systems in asymmetric warfare and the beginning routinization of U.S. drone operations represent part of an evolutionary change in the spatial ordering of global politics -- Using a heuristic framework based on actor-network theory, it is argued that practices of panoptic observation and selective airstrikes, being in need of legal justification, contribute to a reterritorialization of asymmetric conflicts -- Under a new normative spatial regime, a legal condition of state immaturity is constructed, which establishes a zone of conditional sovereignty subject to transnational aerial policing -- At the same time, this process is neither a deterministic result of the new technology nor a deliberate effect of policies to which drones are merely neutral instruments -- Rather, military technology and political decisions both form part of a long chain of action which has evolved under the specific circumstances of recent military interventionsEste artículo propone que la creciente utilización de sistemas aéreos no tripulados y la rutinización de sus operaciones en guerras asimétricas representan parte de un cambio evolutivo en el ordenamiento espacial de la política global -- Utilizando un marco heurístico basado en la teoría del actor-red, se argumenta que las prácticas de observación panóptica y ataques aéreos selectivos, carentes aún de justificación legal, contribuyen a una reterritorialización de los conflictos asimétricos -- En virtud de un nuevo régimen normativo espacial, se construye una condición legal de inmadurez estatal que facilita el establecimiento de una zona de soberanía condicionada, sometida a la vigilancia aérea transnacional -- Al mismo tiempo, esté proceso no es resultado predeterminado de la nueva tecnología, ni efecto deliberado de decisiones políticas para las que los drones son solo instrumentos neutros -- Antes que ello, la tecnología militar y las decisiones políticas forman parte importante de una larga cadena de acción que se ha desarrollado en las circunstancias específicas de intervenciones militares más reciente

Evidence for the Invalidity of the Wingate Test for the Assessment of Peak Power, Power Decrement and Muscular Fatigue

We hypothesized that the protocol-induced initial cadence of the WAnT is too high to allow high muscle force production and peak power generation. Twenty endurance, strength or power trained subjects (9 male, 11 female) completed two 30 s maximal exertion stationary cycle ergometer tests involving the traditional peak cadence start (TRAD) vs. a stationary start (STAT). Inertia corrected mechanical power, cadence, EMG from the vastus lateralis, and applied force to the pedals were measured continuously throughout both tests. Peak power was higher during TRAD; 11.32 &plusmn;1.41 vs. 10.40 &plusmn;1.35 Watts/kg (p &lt; 0.0001), as was peak cadence; 171.4 &plusmn;16.3 vs. 120.9 &plusmn;15.1 rev/min (p &lt; 0.0001). However, during TRAD EMG root mean squared (rms) increased continuously throughout the test, force applied to the pedals increased from 1 to 3 s (0.73 &plusmn;0.27 vs. 0.90 &plusmn;0.39 N/kg; p = 0.02) and thereafter remained relatively stable. EMG mean frequency also increased from 1 to 3 s, but then decreased throughout the remainder of the test. During TRAD, mechanical power decreased near immediately despite increasing EMG rms, EMGmean frequency and force application to the pedals. The initial 10 s of data from the WAnT is invalid. We recommend that intense cycle ergometer testing should commence with a stationary start