An Exploration of Financial Management Programming for Residents in One Homeless Shelter: A Qualitative Institutional Case Study

Introduction: Homelessness affects the economy, societies, and individuals’ physical, mental, and emotional well-being. Occupational therapy is a holistic profession that works with all populations across the lifespan. Financial management is a life skill that many Americans struggle with. Evidence on financial management skill development within homeless shelters and occupational therapy is sparse. Occupational justice is a theoretical framework that supports the right for residents in a homeless shelter to have direct interventions toward skill development, such as education in financial management. Methods: This institutional case study explored a homeless shelter to gain knowledge of real-life program phenomena, with focus on financial management. The primary location for this study was an emergency homeless shelter in the midwestern United States. Five employee participants were recruited through purposeful selection. Results: Participants felt that financial management was an effective intervention for residents in a homeless shelter, although success related to an overall comprehensive program. Conclusion: This study proposes financial management as an important intervention area for homeless shelters and OT practice and suggests the OT profession is qualified to fill roles in a homeless shelter setting

Measurements or Static Analysis or Both?

To date, measurement-based WCET analysis and static analysis have largely been seen as being at odds with each other. We argue that instead they should be considered complementary, and that the combination of both represents a promising approach that provides benefits over either individual approach. In this paper we discuss in some detail how we aim to improve on our probabilistic measurement-based technique by adding static cache analysis. Specifically we are planning to make use of recent advances within the functional languages research community. The objective of this paper is not to present finished or almost finished work. Instead we hope to trigger discussion and solicit feedback from the community in order to avoid pitfalls experienced by others and to help focus our research

Pumping Capacity of Pitched Blade Impellers in a Tall Vessel with a Draught Tube

A study was made of the pumping capacity of pitched blade impellers (two, three, four, five and six blade pitched blade impellers with pitch angles α = 35° and 45°) coaxially located in a cylindrical pilot plant vessel with cylindrical draught tube provided with a standard dished bottom. The draught tube was equipped with four equally spaced radial baffles above the impeller pumping liquid upwards towards the liquid surface. In all investigated cases the liquid aspect ratio H/T = 1.2 - 1.5, the draught tube / vessel diameter ratios DT /T = 0.2 and 0.4 and the impeller / draught tube diameter ratio D/DT = 0.875. The pumping capacity of the impeller was calculated from the radial profile of the axial component of the mean velocity in the draught tube below the impeller at such an axial distance from the impeller that the rotor does not affect the vorticity of the flow. The mean velocity was measured using a laser Doppler anemometer with forward scatter mode in a transparent draught tube and a transparent vessel of diameter T = 400 mm. Two series of experiments were performed, both of them under a turbulent regime of flow of the agitated liquid. First, the optimum height of the dished bottom was sought, and then the dependences of the dimensionless flow rate criterion and the impeller power number on the number of impeller blades were determined for both pitch angles tested under conditions of optimum ratio HT /DT. It follows from the results of the experiments that the optimum ratio HT /DT = 0.25 when the cross sectional areas of the horizontal flow around the bottom and the vertical inflow to the draught tube are the same. For all the tested pitched blade impellers the impeller power number when α = 45° exceeds the value of this quantity when pitch angle α  =   35°, while the flow rate number when α = 35° exceeds this quantity when α = 45°. On the other hand, the absolute values of the impeller power number when the draught tube was introduced correspond fairly well to the dimensionless impeller power input measured in a system without a draught tube. However, the absolute values of the flow rate number found in the former system are significantly lower than the dimensionless impeller pumping capacity determined in the latter system. The hydraulic efficiency of pitched blade impellers N3Qp/Po for the investigated geometry of the agitated systems does not depend on the number of impeller blades, but it is significantly lower than the quantity determined in an agitated system with a dished bottom but without the draught tube

Ancient DNA reveals the timing and persistence of organellar genetic bottlenecks over 3,000 years of sunflower domestication and improvement

Here, we report a comprehensive paleogenomic study of archaeological and ethnographic sunflower remains that provides significant new insights into the process of domestication of this important crop. DNA from both ancient and historic contexts yielded high proportions of endogenous DNA, and although archaeological DNA was found to be highly degraded, it still provided sufficient coverage to analyze genetic changes over time. Shotgun sequencing data from specimens from the Eden's Bluff archaeological site in Arkansas yielded organellar DNA sequence from specimens up to 3,100 years old. Their sequences match those of modern cultivated sunflowers and are consistent with an early domestication bottleneck in this species. Our findings also suggest that recent breeding of sunflowers has led to a loss of genetic diversity that was present only a century ago in Native American landraces. These breeding episodes also left a profound signature on the mitochondrial and plastid haplotypes in cultivars, as two types were intentionally introduced from other Helianthus species for crop improvement. These findings gained from ancient and historic sunflower specimens underscore how future in-depth gene-based analyses can advance our understanding of the pace and targets of selection during the domestication of sunflower and other crop species

A robust prognostic signature for hormone-positive node-negative breast cancer

BACKGROUND: Systemic chemotherapy in the adjuvant setting can cure breast cancer in some patients that would otherwise recur with incurable, metastatic disease. However, since only a fraction of patients would have recurrence after surgery alone, the challenge is to stratify high-risk patients (who stand to benefit from systemic chemotherapy) from low-risk patients (who can safely be spared treatment related toxicities and costs). METHODS: We focus here on risk stratification in node-negative, ER-positive, HER2-negative breast cancer. We use a large database of publicly available microarray datasets to build a random forests classifier and develop a robust multi-gene mRNA transcription-based predictor of relapse free survival at 10 years, which we call the Random Forests Relapse Score (RFRS). Performance was assessed by internal cross-validation, multiple independent data sets, and comparison to existing algorithms using receiver-operating characteristic and Kaplan-Meier survival analysis. Internal redundancy of features was determined using k-means clustering to define optimal signatures with smaller numbers of primary genes, each with multiple alternates. RESULTS: Internal OOB cross-validation for the initial (full-gene-set) model on training data reported an ROC AUC of 0.704, which was comparable to or better than those reported previously or obtained by applying existing methods to our dataset. Three risk groups with probability cutoffs for low, intermediate, and high-risk were defined. Survival analysis determined a highly significant difference in relapse rate between these risk groups. Validation of the models against independent test datasets showed highly similar results. Smaller 17-gene and 8-gene optimized models were also developed with minimal reduction in performance. Furthermore, the signature was shown to be almost equally effective on both hormone-treated and untreated patients. CONCLUSIONS: RFRS allows flexibility in both the number and identity of genes utilized from thousands to as few as 17 or eight genes, each with multiple alternatives. The RFRS reports a probability score strongly correlated with risk of relapse. This score could therefore be used to assign systemic chemotherapy specifically to those high-risk patients most likely to benefit from further treatment

A comparison of two dissimilarity functions for mixed-type predictor variables in the δ-machine

The δ-machine is a statistical learning tool for classification based on dissimilarities or distances between profiles of the observations to profiles of a representation set, which was proposed by Yuan et al. (J Claasif 36(3): 442–470, 2019). So far, the δ-machine was restricted to continuous predictor variables only. In this article, we extend the δ-machine to handle continuous, ordinal, nominal, and binary predictor variables. We utilized a tailored dissimilarity function for mixed type variables which was defined by Gower. This measure has properties of a Manhattan distance. We develop, in a similar vein, a Euclidean dissimilarity function for mixed type variables. In simulation studies we compare the performance of the two dissimilarity functions and we compare the predictive performance of the δ-machine to logistic regression models. We generated data according to two population distributions where the type of predictor variables, the distribution of categorical variables, and the number of predictor variables was varied. The performance of the δ-machine using the two dissimilarity functions and different types of representation set was investigated. The simulation studies showed that the adjusted Euclidean dissimilarity function performed better than the adjusted Gower dissimilarity function; that the δ-machine outperformed logistic regression; and that for constructing the representation set, K-medoids clustering achieved fewer active exemplars than the one using K-means clustering while maintaining the accuracy. We also applied the δ-machine to an empirical example, discussed its interpretation in detail, and compared the classification performance with five other classification methods. The results showed that the δ-machine has a good balance between accuracy and interpretability.NWOMultivariate analysis of psychological dat