Working Caregivers: Issues, Challenges, And Opportunities For The Aging Network

This paper provides an overview of the issues associated with working caregivers. We will examine the social and demographic trends influencing the growth of this group, their characteristics and their contributions to elders, and the consequences of caregiving for caregivers and their work. Next, we will briefly describe the various employer-initiated programs currently in place to support working caregivers and the evolution of these programs, followed by federal and state governments’ response to working caregivers, to date. The remainder of the paper details the potential role of the aging network in better supporting working caregivers, including current best practices and other possible strategies. We offer tips for getting started, including ideas and recommendations for internal program consideration, and tips for working with the business community

In vitro methods for generating highly purified EBV associated tumor antigen-specific T cells by using solid phase T cell selection system for immunotherapy

Adoptive cell transfer immunotherapy has been utilized to treat EBV related human malignancies including post-transplant lymphoproliferative diseases, Hodgkin\u27s lymphoma and nasopharyngeal carcinoma. However, there are limited options available for tumor antigen-specific T cell purification. Here we describe a novel solid phase T cell selection system, in which monocytes or EBV transformed B-lymphocytes are immobilized on solid support for antigen-specific T cell purification. We hypothesize and prove that antigen-specific T cells recognize their cognate antigens and bind to them faster than non-antigen specific T cells. Therefore antigen-specific T cells can be concentrated on the surface after removing the non-adherent cells by washing. The optimal selection time for both EBV-specific T cells and LMP2-specific T cells is studied. Our data demonstrate that the frequency of antigen-specific T cells can be increased by \u3e20-fold after selection. Moreover, activated antigen-specific T cells proliferate more rapidly than non-specific T cells, further increasing the frequency and purity of antigen-specific T cells. This new T cell selection system is superior to traditional repeated stimulation methods in generating tumor antigen-specific T cells. We are able to generate large quantities of highly purified T cells of subdominant antigens LMP2 within 2 weeks after T cell activation for adoptive cell transfer immunotherapy with this simple, rapid and inexpensive T cell selection system

Assessing Mission Performance for Technology Reliant Missions

Operators today increasingly rely on technology to accomplish objectives. Although technology can increase mission success and efficiency in a majority of operations, it can simultaneously increase vulnerability prevalence, resulting in a higher exploitation likelihood. Defense methods have been proposed and evaluated based on their ability to ensure network security. However, these evaluation metrics do not fully quantify how network exploitation impacts mission task completion. Our mission performance model links cyber devices to mission tasks utilizing a mission’s mission map and evaluates a mission’s performance as the proportion of completed mission tasks in an agent based simulation. Our model allows for mission mappings with varying degrees of completion to enable a generic and adaptable model. We investigate the impact differing levels of mission map completion have on the mission performance metric for the same mission. Experiments serve to provide quantitative assessment for mission performance in cyber-network mission systems

A bi-criteria evolutionary algorithm for a constrained multi-depot vehicle routing problem

Most research about the vehicle routing problem (VRP) does not collectively address many of the constraints that real-world transportation companies have regarding route assignments. Consequently, our primary objective is to explore solutions for real-world VRPs with a heterogeneous fleet of vehicles, multi-depot subcontractors (drivers), and pickup/delivery time window and location constraints. We use a nested bi-criteria genetic algorithm (GA) to minimize the total time to complete all jobs with the fewest number of route drivers. Our model will explore the issue of weighting the objectives (total time vs. number of drivers) and provide Pareto front solutions that can be used to make decisions on a case-by-case basis. Three different real-world data sets were used to compare the results of our GA vs. transportation field experts’ job assignments. For the three data sets, all 21 Pareto efficient solutions yielded improved overall job completion times. In 57 % (12/21) of the cases, the Pareto efficient solutions also utilized fewer drivers than the field experts’ job allocation strategies

Diphtheria in the Postepidemic Period, Europe, 2000–2009

Efforts must be made to maintain high vaccination coverage

Evolución de reglas de clasificación para el descubrimiento de conocimiento comprensible

Este trabajo, el cual se encuentra dentro del contexto de la minería de datos, propone un método para construir clasificadores basado en la evolución de reglas. El método, denominado REC (Rule Evolution for Classifiers), tiene tres características principales: 1) aplica programación genética (PG) para llevar a cabo una búsqueda en el espacio de potenciales soluciones, 2) un procedimiento permite sesgar la búsqueda hacia regiones de hipótesis comprensibles con alta calidad predictiva, 3) incluye una estrategia para la selección de un subconjunto óptimo de reglas (clasificador), a partir de las reglas obtenidas como resultado del proceso evolutivo. Se lleva a cabo un estudio comparativo entre este método y el algoritmo de inducción de reglas C5.0, para dos problemas de aplicación (conjuntos de datos). Los resultados experimentales muestran las ventajas de usar el método propuesto.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Evolución de reglas de clasificación para el descubrimiento de conocimiento comprensible

Este trabajo, el cual se encuentra dentro del contexto de la minería de datos, propone un método para construir clasificadores basado en la evolución de reglas. El método, denominado REC (Rule Evolution for Classifiers), tiene tres características principales: 1) aplica programación genética (PG) para llevar a cabo una búsqueda en el espacio de potenciales soluciones, 2) un procedimiento permite sesgar la búsqueda hacia regiones de hipótesis comprensibles con alta calidad predictiva, 3) incluye una estrategia para la selección de un subconjunto óptimo de reglas (clasificador), a partir de las reglas obtenidas como resultado del proceso evolutivo. Se lleva a cabo un estudio comparativo entre este método y el algoritmo de inducción de reglas C5.0, para dos problemas de aplicación (conjuntos de datos). Los resultados experimentales muestran las ventajas de usar el método propuesto.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Restoring Native Grasslands

4 pp., 5 color photos, 1 map, 3 graphsMuch of Texas' native grasslands has been converted to improved pastures and cropland, neither of which is suitable for wildlife habitat. Now, many landowners are interested in restoring native grasses because they are cheaper to produce for forage than are improved pastures and they also encourage wildlife. This publication explains how to carry out such restoration and the results to expect

Women and children living in areas of armed conflict in Africa: a geospatial analysis of mortality and orphanhood

Background: The population effects of armed conflict on non-combatant vulnerable populations are incompletely understood. We aimed to study the effects of conflict on mortality among women of childbearing age (15–49 years) and on orphanhood among children younger than 15 years in Africa. Methods: We tested the extent to which mortality among women aged 15–49 years, and orphanhood among children younger than 15 years, increased in response to nearby armed conflict in Africa. Data on location, timing, and intensity of armed conflicts were obtained from the Uppsala Conflict Data Program, and data on the location, timing, and outcomes of women and children from Demographic and Health Surveys done in 35 African countries from 1990 to 2016. Mortality among women was obtained from sibling survival data. We used cluster-area fixed-effects regression models to compare survival of women during periods of nearby conflict (within 50 km) to survival of women in the same area during times without conflict. We used similar methods to examine the extent to which children living near armed conflicts are at increased risk of becoming orphans. We examined the effects of varying conflict intensity using number of direct battle deaths and duration of consecutive conflict exposure. Findings: We analysed data on 1 629 352 women (19286387 person-years), of which 103011 (6·3%) died (534·1 deaths per 100000 women-years), and 2 354 041 children younger than 15 years, of which 204276 (8·7%) had lost a parent. On average, conflict within 50 km increased women’s mortality by 112 deaths per 100 000 person-years (95% CI 97–128; a 21% increase above baseline), and the probability that a child has lost at least one parent by 6·0% (95% CI 3–8). This effect was driven by high-intensity conflicts: exposure to the highest (tenth) decile conflict in terms of conflict-related deaths increased the probability of female mortality by 202% (187–218) and increased the likelihood of orphanhood by 42% compared with a conflict-free period. Among the conflict-attributed deaths, 10% were due to maternal mortality. Interpretation: African women of childbearing age are at a substantially increased risk of death from nearby highintensity armed conflicts. Children exposed to conflict are analogously at increased risk of becoming orphans. This work fills gaps in literature on the harmful effects of armed conflict on non-combatants and highlights the need for humanitarian interventions to protect vulnerable populations. Funding: Bill & Melinda Gates Foundation to the BRANCH Consortium

Unraveling the Complexities of DNA-Dependent Protein Kinase Autophosphorylation

DNA-dependent protein kinase (DNA-PK) orchestrates DNA repair by regulating access to breaks through autophosphorylations within two clusters of sites (ABCDE and PQR). Blocking ABCDE phosphorylation (by alanine mutation) imparts a dominant negative effect, rendering cells hypersensitive to agents that cause DNA double-strand breaks. Here, a mutational approach is used to address the mechanistic basis of this dominant negative effect. Blocking ABCDE phosphorylation hypersensitizes cells to most types of DNA damage (base damage, cross-links, breaks, and damage induced by replication stress), suggesting that DNA-PK binds DNA ends that result from many DNA lesions and that blocking ABCDE phosphorylation sequesters these DNA ends from other repair pathways. This dominant negative effect requires DNA-PK's catalytic activity, as well as phosphorylation of multiple (non-ABCDE) DNA-PK catalytic subunit (DNA-PKcs) sites. PSIPRED analysis indicates that the ABCDE sites are located in the only contiguous extended region of this huge protein that is predicted to be disordered, suggesting a regulatory role(s) and perhaps explaining the large impact ABCDE phosphorylation has on the enzyme's function. Moreover, additional sites in this disordered region contribute to the ABCDE cluster. These data, coupled with recent structural data, suggest a model whereby early phosphorylations promote initiation of nonhomologous end joining (NHEJ), whereas ABCDE phosphorylations, potentially located in a “hinge” region between the two domains, lead to regulated conformational changes that initially promote NHEJ and eventually disengage NHEJ