Η ΛΑΪΚΗ ΥΠΟΣΤΗΡΙΞΗ ΤΟΥ ΕΑΜ ΣΤΟ ΤΕΛΟΣ ΤΗΣ ΚΑΤΟΧΗΣ

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Barriers and Promoters of Retention of Direct Care Workers in Community Mental Health Agencies

Demand for behavioral health direct-care providers is increasing due to shortage of licensed behavioral health providers. However, high turnover has been reported among them with limited exploratory research. The present study aimed to identify a wide variety of barriers and promoters of retention and strategies to retain direct care workers. An online, self-administered survey designed to measure demographics, job satisfaction, perceived importance of various job aspects, intention to leave, perceived stress and sources of stress was administered among 179 direct care workers from four agencies. Multiple logistic regression exhibited higher odds of intending to leave for those who had higher general perceived stress (OR=1.3, CI=1.1-1.7) and those who experienced stress from supervisor (OR=5.0, CI=1.7-14.4) and organizational culture (OR=4.2, CI=1.1-18.4). Work-related stress is a prevalent issue among direct-care providers and may be associated with turnover. Policy formulation and implementation directed at strategies to reduce stress may be warranted to improve retention.https://digitalcommons.unmc.edu/bhecn_report/1000/thumbnail.jp

Shape from Projections via Differentiable Forward Projector for Computed Tomography

In computed tomography, the reconstruction is typically obtained on a voxel grid. In this work, however, we propose a mesh-based reconstruction method. For tomographic problems, 3D meshes have mostly been studied to simulate data acquisition, but not for reconstruction, for which a 3D mesh means the inverse process of estimating shapes from projections. In this paper, we propose a differentiable forward model for 3D meshes that bridge the gap between the forward model for 3D surfaces and optimization. We view the forward projection as a rendering process, and make it differentiable by extending recent work in differentiable rendering. We use the proposed forward model to reconstruct 3D shapes directly from projections. Experimental results for single-object problems show that the proposed method outperforms traditional voxel-based methods on noisy simulated data. We also apply the proposed method on electron tomography images of nanoparticles to demonstrate the applicability of the method on real data

Emotional and emotive language: modal particles and tags in unified Berlin

This paper endeavours to show the relationship between emotion and language, in particular with respect to the use of modal particles in German. Modal particles have long been considered insignificant fillers without a specific function and as such, not worthy of linguistic investigation. This is clearly a view which cannot be sustained. Modal particles have been found to illustrate the speaker’s opinion of what is being said; in addition, they may add emphasis. Certain German modal particles (especially halt and eben) are examined as they occur in a corpus of utterances containing accounts of highly emotional events, related to East and West Berliners’ experiences after the fall of the Berlin Wall and German unification. By reviewing spoken accounts of events which were life-changing for one side, but only nominal for the other, thereby producing different emotions, the article demonstrates the use of these modal particles. The analysis suggests that there is a direct link between emotion and the way these speakers of German use their language

The Prognostic Value of Serum Biomarkers in Localized Bone Sarcoma

AbstractOBJECTIVE: Certain biomarkers such as the C-reactive protein, serum albumin, and the neutrophils to lymphocyte ratio are of prognostic significance regarding survival in different types of cancers. Data from sarcoma patients are sparse and mainly derived from soft tissue sarcoma and/or metastatic cases. Adjusting for confounders such as comorbidity and age is an essential safeguard against erroneous conclusions regarding the possible prognostic value of these biomarkers. The aim of this study was to assess the prognostic value of a battery of pretreatment biomarkers in the serum of patients with localized bone sarcomas and to adjust for potential confounders. MATERIAL AND METHODS: All patients diagnosed with localized intermediate and high-grade bone sarcoma during 1994 to 2008 were extracted from the Aarhus Sarcoma Registry. The serum levels of albumin, C-reactive protein, hemoglobin, neutrophils, lymphocytes, and sodium were collected from the patient records. The prognostic values of overall and disease-specific mortality were tested for each individual biomarker as well as for the Glasgow prognostic score (GPS) and for a new composite score incorporating five biomarkers (Aarhus composite biomarker score: ACBS). Adjustments were made for comorbidity as well as other possible prognostic factors, such as size, histological type, margin, chemotherapy, and soft tissue extension, using the Cox proportional hazard model. RESULTS: A total of 172 patients with high- or intermediate-grade localized bone sarcoma were included. Of these patients, 63 were diagnosed with chondrosarcoma and 109 patients with Ewing/osteosarcoma. The median age was 55 years for chondrosarcoma and 19 years for Ewing/osteosarcoma patients. The overall 5-year mortality was 31% [95% confidence interval (CI): 21-44] and 41% (95% CI: 33-51), whereas the 5-year disease-specific mortality was 21% (95% CI: 12-34) and 39% (95% CI: 31-49) for chondrosarcoma and Ewing/osteosarcoma, respectively. Comorbidities were present in 12% of the Ewing/osteosarcoma patients and in 24% of the chondrosarcoma patients. After adjustment for comorbidity and other confounders, it was found that elevated levels of CRP, low hemoglobin, low sodium, high GPS, and high ACBS were associated with increased overall mortality. Furthermore, elevated levels of CRP, low hemoglobin, high GPS, and high ACBS were associated with increased disease-specific mortality. CONCLUSION: Elevated levels of CRP, low hemoglobin, high GPS, and high ACBS were all independent prognostic factors for both overall and disease-specific mortality. ACBS is a new three-level score of five biomarkers, but its value has to be confirmed in an independent data set

Convolution filtering of continuous signed distance fields for polygonal meshes

Signed distance fields obtained from polygonal meshes are commonly used in various applications. However, they can have C1 discontinuities causing creases to appear when applying operations such as blending or metamorphosis. The focus of this work is to efficiently evaluate the signed distance function and to apply a smoothing filter to it while preserving the shape of the initial mesh. The resulting function is smooth almost everywhere, while preserving the exact shape of the polygonal mesh. Due to its low complexity, the proposed filtering technique remains fast compared to its main alternatives providing C1-continuous distance field approximation. Several applications are presented such as blending, metamorphosis and heterogeneous modelling with polygonal meshes

Coarse-to-fine skeleton extraction for high resolution 3D meshes

This paper presents a novel algorithm for medial surfaces extraction that is based on the density-corrected Hamiltonian analysis of Torsello and Hancock [1]. In order to cope with the exponential growth of the number of voxels, we compute a first coarse discretization of the mesh which is iteratively refined until a desired resolution is achieved. The refinement criterion relies on the analysis of the momentum field, where only the voxels with a suitable value of the divergence are exploded to a lower level of the hierarchy. In order to compensate for the discretization errors incurred at the coarser levels, a dilation procedure is added at the end of each iteration. Finally we design a simple alignment procedure to correct the displacement of the extracted skeleton with respect to the true underlying medial surface. We evaluate the proposed approach with an extensive series of qualitative and quantitative experiments

A geometric network model of intrinsic grey-matter connectivity of the human brain

Network science provides a general framework for analysing the large-scale brain networks that naturally arise from modern neuroimaging studies, and a key goal in theoretical neuro- science is to understand the extent to which these neural architectures influence the dynamical processes they sustain. To date, brain network modelling has largely been conducted at the macroscale level (i.e. white-matter tracts), despite growing evidence of the role that local grey matter architecture plays in a variety of brain disorders. Here, we present a new model of intrinsic grey matter connectivity of the human connectome. Importantly, the new model incorporates detailed information on cortical geometry to construct ‘shortcuts’ through the thickness of the cortex, thus enabling spatially distant brain regions, as measured along the cortical surface, to communicate. Our study indicates that structures based on human brain surface information differ significantly, both in terms of their topological network characteristics and activity propagation properties, when compared against a variety of alternative geometries and generative algorithms. In particular, this might help explain histological patterns of grey matter connectivity, highlighting that observed connection distances may have arisen to maximise information processing ability, and that such gains are consistent with (and enhanced by) the presence of short-cut connections

A competitive strategy for atrial and aortic tract segmentation based on deformable models

Multiple strategies have previously been described for atrial region (i.e. atrial bodies and aortic tract) segmentation. Although these techniques have proven their accuracy, inadequate results in the mid atrial walls are common, restricting their application for specific cardiac interventions. In this work, we introduce a novel competitive strategy to perform atrial region segmentation with correct delineation of the thin mid walls, and integrated it into the B-spline Explicit Active Surfaces framework. A double stage segmentation process is used, which starts with a fast contour growing followed by a refinement stage with local descriptors. Independent functions are used to define each region, being afterward combined to compete for the optimal boundary. The competition locally constrains the surface evolution, prevents overlaps and allows refinement to the walls. Three different scenarios were used to demonstrate the advantages of the proposed approach, through the evaluation of its segmentation accuracy, and its performance for heterogeneous mid walls. Both computed tomography and magnetic resonance imaging datasets were used, presenting results similar to the state-of-the-art methods for both atria and aorta. The competitive strategy showed its superior performance with statistically significant differences against the traditional free-evolution approach in cases with bad image quality or missed atrial/aortic walls. Moreover, only the competitive approach was able to accurately segment the atrial/aortic wall. Overall, the proposed strategy showed to be suitable for atrial region segmentation with a correct segmentation of the mid thin walls, demonstrating its added value with respect to the traditional techniques.The authors acknowledge Fundacao para a Ciencia e a Tecnologia (FCT), in Portugal, and the European Social Found, European Union, for funding support through the "Programa Operacional Capital Humano" (POCH) in the scope of the PhD grants SFRH/BD/95438/2013 (P. Morais) and SFRH/BD/93443/2013 (S. Queiros).Authors gratefully acknowledge the funding of projects NORTE-01-0145-FEDER-000013 and NORTE-01-0145-FEDER-000022, co-financed by "Programa Operacional Regional do Norte" (NORTE2020), through "Fundo Europeu de Desenvolvimento Regional" (FEDER).info:eu-repo/semantics/publishedVersio

Energy-based dissolution simulation using SPH sampling

A novel unified particle-based method is proposed for real-time dissolution simulation that is fast, predictable, independent of sampling resolution, and visually plausible. The dissolution model is derived from collision theory and integrated into a smoothed particle hydrodynamics fluid solver. Dissolution occurs when a solute is submerged in solvent. Physical laws govern the local excitation of solute particles based on kinetic energy: when the local excitation energy exceeds a user-specified threshold (activation energy), the particle will be dislodged from the solid. Solute separation during dissolution is handled using a new Graphics Processing Unit (GPU)-based region growing method. The use of smoothed particle hydrodynamics sampling for both solute and solvent guarantees a predictable and smooth dissolution process and provides user control of the volume change during the phase transition. A mathematical relationship between the activation energy and dissolution time allows for intuitive artistic control over the global dissolution rate. We demonstrate this method using a number of practical examples, including antacid pills dissolving in water, hydraulic erosion of nonhomogeneous terrains, and melting