Ideabook: Libraries for Families

The IDEABOOK is a research-based framework to guide and broaden family engagement in libraries.The framework helps libraries move beyond thinking of family engagement as random, individual activities or programs, but rather as a system where library leadership, activities, and resources that are linked to goals. The framework represents a theory of change that begins with a set of elements—leadership, engagement, and support services—that build a pathway for meaningful family engagement beginning in the early childhood years and extending through young adulthood.This IDEABOOK was developed for anyone who works in a library setting—from library directors and children's and youth librarians, to volunteers and support staff—and shares many innovative ways that libraries support and guide families in children's learning and development

Culture Counts: Examinations of Recent Applications of the Penn Resiliency Program or, Toward a Rubric for Examining Cultural Appropriateness of Prevention Programming

It is imperative that researchers pay close attention to the influences of culture on mental health, and acknowledge a cultural context of illness and change when designing prevention programming. Researchers E. V. Cardemil, K. J. Reivich, and M. E. P. Seligman (2002) and D. L. Yu and M. E. P. Seligman (2002) have made attempts at adapting the existing Penn Resiliency Program (PRP) for culturally appropriate use cross-culturally and interculturally. The success of these modifications is discussed within a framework of guidelines designed to remind scientists how much culture counts. Finally, informative resources and a rubric are shared with prevention scientists for use in future development of culturally appropriate prevention programming

The Penn Haptic Texture Toolkit for Modeling, Rendering, and Evaluating Haptic Virtual Textures

The Penn Haptic Texture Toolkit (HaTT) is a collection of 100 haptic texture and friction models, the recorded data from which the models were made, images of the textures, and the code and methods necessary to render these textures using an impedance-type haptic device such as a SensAble Phantom Omni. This toolkit was developed to provide haptics researchers with a method by which to compare and validate their texture modeling and rendering methods. The included rendering code has the additional benefit of allowing others, both researchers and designers, to incorporate our textures into their virtual environments, which will lead to a richer experience for the user

A review of the Caregiver\u27s Feeding Style Questionnaire (CFSQ): Differences in parent-child feeding styles across geographic location, caregiver roles, and Head Start samples

Introduction: The Caregiver’s Feeding Style Questionnaire (CFSQ) is a measure of parent feeding styles developed for low-income minority families. It is made up of four main categories which are associated with different child outcomes including childhood obesity. This review sought to describe the differences in child outcomes among international populations, maternal caregivers, and Head Start samples. Method: This review examined 683 publications that cited the 2005 Hughes article introducing the CFSQ measure. Of these, only 44 were relevant to our review because they met the inclusion criteria of 1) using the CFSQ measure and 2) providing a categorical breakdown of feeding styles. Results: A handful of these studies (k=5) were made up of international populations including England, Sri Lanka, and Mexico. The categorical breakdown for these studies was as follows (Authoritative=14.34%, Authoritarian=40.73%, Indulgent=30.01%, Uninvolved=14.94%). Studies including mothers (k=11) were categorized into different parent-feeding styles: (Michigan mothers: Authoritative=25%,American Indian mothers: Indulgent=52.2%). For studies involving populations of Head Start children there was a clear polarization where participants mainly fell into the categories of Authoritarian (30.8%) and Indulgent (32.5%). Discussion: The authoritative feeding style is associated with the most positive outcomes and Indulgent parenting styles are most consequential in terms of obesity risk. For many studies included in this review, parents less often fell into the category of authoritative, thus pointing to the importance in working with these populations to develop more effective and healthy feeding patterns

The Engagement Model of Person-Environment Interaction

This article focuses on growth-promoting aspects in the environment, and the authors propose a strength-based, dynamic model of person-environment interaction. The authors begin by briefly discussing the typical recognition of contextual variables in models that rely on the concept of person-environment fit. This is followed by a review of recent approaches to incorporating positive environmental factors in conceptualizations of human functioning. These approaches lead to an alternative model of person-environment interaction in which the engagement construct (i.e., the quality of a person-environment relationship determined by the extent to which negotiation, participation, and evaluation processes occur during the interaction) replaces the static notion of fit. Finally, the authors outline recommendations for overcoming environmental neglect in research, practice, and training

Dataset of why inclusion matters for Alzheimer's disease biomarker discovery in plasma

Here we present a plasma proteomics dataset that was generated to understand the importance of self-reported race for biomarker discovery in Alzheimer's disease. This dataset is related to the article “Why inclusion matters for Alzheimer's disease biomarker discovery in plasma” [1]. Plasma samples were obtained from clinically diagnosed Alzheimer's disease and cognitively normal adults of African American/Black and non-Hispanic White racial and ethnic backgrounds. Plasma was immunodepleted, digested, and isobarically tagged with commercial reagents. Tagged peptides were fractionated using high pH fractionation and resulting fractions analysed by liquid chromatography – mass spectrometry (LC-MS/MS & MS3) analysis on an Orbitrap Fusion Lumos mass spectrometer. The resulting data was processed using Proteome Discoverer to produce a list of identified proteins with corresponding tandem mass tag (TMT) intensity information

Crop biophysical parameter retrieval from Sentinel-1 SAR data with a multi-target inversion of Water Cloud Model

Estimation of bio-and geophysical parameters from Earth observation (EO) data is essential for developing applications on crop growth monitoring. High spatio-temporal resolution and wide spatial coverage provided by EO satellite data are key inputs for operational crop monitoring. In Synthetic Aperture Radar (SAR) applications, a semi-empirical model (viz., Water Cloud Model (WCM)) is often used to estimate vegetation descriptors individually. However, a simultaneous estimation of these vegetation descriptors would be logical given their inherent correlation, which is seldom preserved in the estimation of individual descriptors by separate inversion models. This functional relationship between biophysical parameters is essential for crop yield models, given that their variations often follow different distribution throughout crop development stages. However, estimating individual parameters with independent inversion models presume a simple relationship (potentially linear) between the biophysical parameters. Alternatively, a multi-target inversion approach would be more effective for this aspect of model inversion compared to an individual estimation approach. In the present research, the multi-output support vector regression (MSVR) technique is used for inversion of the WCM from C-band dual-pol Sentinel-1 SAR data. Plant Area Index (PAI, m2 m−2) and wet biomass (W, kg m−2) are used as the vegetation descriptors in the WCM. The performance of the inversion approach is evaluated with in-situ measurements collected over the test site in Manitoba (Canada), which is a super-site in the Joint Experiment for Crop Assessment and Monitoring (JECAM) SAR inter-comparison experiment network. The validation results indicate a good correlation with acceptable error estimates (normalized root mean square error–nRMSE and mean absolute error–MAE) for both PAI and wet biomass for the MSVR approach and a better estimation with MSVR than single-target models (support vector regression–SVR). Furthermore, the correlation between PAI and wet biomass is assessed using the MSVR and SVR model. Contrary to the single output SVR, the correlation between biophysical parameters is adequately taken into account in MSVR based simultaneous inversion technique. Finally, the spatio-temporal maps for PAI and W at different growth stages indicate their variability with crop development over the test site.This research was supported in part by Shastri Indo-Candian Institute, New Delhi, India and the Spanish Ministry of Economy, Industry and Competitiveness, in part by the State Agency of Research (AEI), in part by the European Funds for Regional Development under project TEC2017-85244-C2-1-P