Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Barriers to Medication Adherence in Underserved Patients With Diabetes in Texas

Purpose The purpose of this study was to assess (1) medication adherence in individuals with diabetes, (2) barriers to adherence, and (3) what factors were related to medication nonadherence. Methods A self-administered anonymous survey was provided to adults with diabetes (N = 59) who used a grocery store chain pharmacy or a community clinic for the underserved. Participants were recruited by pharmacy staff to complete a 10- to 15-minute survey to assess adherence, access, barriers, medication use, and demographics. Adherence was measured using the 8-item Morisky Medication Adherence Scale (MMAS), which is a reliable and valid self-report adherence instrument. Access (eg, use medications from Mexico, transportation), barriers (eg, cost, language difficulties), medication use (eg, complementary and alternative medicine, prescription medication), and demographics were also measured. The survey was available in English and Spanish. Data collection occurred from December 2010 through February 2011. Results Fifty-nine participants completed the survey. Approximately 57% of study participants were male, 85% were Hispanic, and the mean age was 50.4 ± 10.3 years. Over 50% of participants had hypertension or dyslipidemia and were taking 3 or more medications. Participants (52.6%) reported their health status as good or excellent and over one-half (56%) of the participants were nonadherent (score 0-6). The following factors were significantly (P < .05) related to nonadherence: cost, no refills, poor health status, fewer disease states, and any reason. Conclusions This study increased awareness of barriers to medication adherence in a predominantly Hispanic underserved patient population. This may lead to more informed recommendations and perhaps address gaps in health disparities.
Building Capacity to Reduce Disparities in Diabetes

Purpose The purpose of this study is to determine whether an innovative interactive distance training program is an effective modality to train community health workers (CHWs) to become members of the diabetes health care team. The University of New Mexico Health Sciences Center has developed a rigorous diabetes training program for CHWs involving both distance and hands-on learning as part of Project ECHO™ (Extension for Community Healthcare Outcomes). Methods Twenty-three diverse CHW participants from across New Mexico were enrolled in the first training session. Participants completed surveys at baseline and at the end of the program. They attended a 3-day hands-on training session, followed by weekly participation in tele/video conferences for 6 months. Wilcoxon signed-rank statistics were used to compare pre- and posttest results. Results Participants demonstrated significant improvements in diabetes knowledge (P = .002), diabetes attitudes (P = .04) and confidence in both clinical and nonclinical skills (P < .001 and P = .04, respectively). Additionally, during focus group discussions, participants reported numerous benefits from participation in the program. Conclusions Community health worker participation in the Project ECHO diabetes training program resulted in significant increases in knowledge, confidence, and attitudes in providing care to patients with diabetes. Studies are ongoing to determine whether the training has a positive impact on patient outcomes.
Effect of a Short-Duration, Culturally Tailored, Community-Based Diabetes Self-management Intervention for Korean Immigrants

Purpose The purpose of this pilot study was to assess the effectiveness, feasibility, and acceptability of a short-duration, culturally tailored, community-based diabetes self- management program (CTCDSP) for Korean immigrants with type 2 diabetes delivered at a non-clinic-affiliated community center. Methods Forty-one Korean adults with type 2 diabetes participated in a 2-session CTCDSP delivered by a bilingual nurse practitioner at a Korean community center. Outcome measures included biological, behavioral, and general health well-being; diabetes knowledge; and self-efficacy assessed at baseline, post-education, and 3-month follow-up. Repeated-measures analyses of variance were used to explore mean differences in outcomes across the 3 assessment points. Results From baseline to 3-month follow-up assessment, participants exhibited significant improvement on several physiological and behavioral measures. Mean levels of hemoglobin A1c and waist circumference decreased, whereas high-density lipoprotein levels increased. Additionally, participants reported an increase in weekly feet checks, and there was a trend increase in participants’ reported frequency of exercise activities. The feasibility of the CTCDSP was established, and participant satisfaction with the program was high. Conclusions A short-duration CTCDSP may be an effective, feasible, and favorably received approach to improving diabetes outcomes in Korean and potentially other underserved ethnic minority immigrants who have limited access to mainstream clinic-based diabetes self-management programs.
A study for the dynamic system of coupled cable-driven structure in surgical robot instrument

Many surgical robots adopt a tendon driven mechanism using cable and pulley to transmit the power. However, although tension is the main medium of power structurally, it is directly related with cable material characteristics including not only elastic region which make it able to use fixed spring constant but also nonlinear elastic and yielding one. Therefore, in the view point of control, it is difficult to control the force on end-effect with the torque generated from driving motor and pulley located on other place. In addition, interference between links can occur in small size and multi DOF system as surgical robot instrument. In surgical operation, both motion and force are important element for successful result. Thus, to make it possible to force control of surgical robot instrument, this paper derives dynamic governing model of coupled cable pulley structure. And the dynamic analysis and equation is proven by both simulation and experimental test.
Robust visual ℓ2-regularized least squares tracker with Bayes classifier and coding error

Abstract. Visual object tracking is a challenging task due to the existence of significant illumination change, appearance variation, and occlusion. We propose a structured collaborative representation-based visual tracking algorithm by using both the generative appearance model and the discriminative model. First, a structured collaborative representation model based on ℓ2-regularized least squares is used to exploit both holistic and local information of the target. In the structured collaborative representation framework, a new over-complete dictionary containing both target and background templates is proposed to enhance the robustness of the tracking algorithm. Second, the tracking task is treated as a binary classification problem, and a Bayes classifier is trained online by the use of structured collaborative representation coefficients of positive and negative samples. Furthermore, a residual error score is constructed to improve the detective ability of the tracker. Finally, target templates are updated by combining incremental subspace learning and collaborative representation together, and background templates are subsequently updated by samples around latest results. Compared with four state-of-the-art tracking algorithms in 12 challenging video sequences, the proposed tracking algorithm demonstrates a better performance overall in terms of experimental results.
Patient-Provider Relationships Across the Transition From Pediatric to Adult Diabetes Care

Purpose The purpose of this study was to explore perceptions that emerging adults with type 1 diabetes (T1D) have of their patient-provider relationships across the transition from pediatric to adult care. Methods Twenty-six emerging adults with T1D (mean age 26.2 ± 2.5 years) participated in 5 focus groups stratified by current level of glycemic control (A1C). Coded audio-recorded data were analyzed using thematic analysis and aided by NVivo software. Results Three major themes emerged from the analysis: (1) loss and gain in provider relationships across the transition—patients expressed 3 key responses to leaving pediatric providers that differed by A1C levels: sad reluctance and “natural progression” (mean A1C ± SD 7.4% ± 0.6%) and wanting to go (mean A1C ± SD 9.8% ± 1.0%); (2) partners in care versus on one’s own—patients valued how adult providers’ collaborative conversations promoted their involvement and accountability compared to “parent-centric” interactions with pediatric providers, but they also expressed ambivalence over increased independence in adult care; (3) improving provider approaches to transition—patients recommended that pediatric providers actively promote emerging adults’ autonomy while maintaining parental support, communication with adult providers, and follow-up with transitioning patients. Conclusions Findings highlight the importance of enhanced provider awareness of T1D emerging adults’ complex feelings about the transition in care. Improved integration of individual- and family-centered approaches to developmentally tailored diabetes care is needed to augment patient and provider relationships.
Improving a rough set theory-based segmentation approach using adaptable threshold selection and perceptual color spaces

Abstract. We propose a color image segmentation approach based on rough set theory elements. Main contributions of the proposed approach are twofold. First, by using an adaptive threshold selection, the approach is automatically adjustable according to the image content. Second, a region-merging process, which takes into account both features and spatial relations of the resulting segments, lets us minimize over-segmentation issues. These two proposals allow our method to overcome some performance issues shown by previous rough set theory-based approaches. In addition, a study to determine the best suited color representation for our segmentation approach is carried out, determining that the best results are obtained using a perceptually uniform color space. A set of qualitative and quantitative tests over a comprehensive image database shows that the proposed method produces high-quality segmentation outcomes, better than those obtained using the previous rough set theory-based and standard segmentation approaches.
Actin depolymerisation and crosslinking join forces with myosin II to contract actin coats on fused secretory vesicles

ABSTRACT In many secretory cells actin and myosin are specifically recruited to the surface of secretory granules following their fusion with the plasma membrane. Actomyosin-dependent compression of fused granules is essential to promote active extrusion of cargo. However, little is known about molecular mechanisms regulating actin coat formation and contraction. Here, we provide a detailed kinetic analysis of the molecules regulating actin coat contraction on fused lamellar bodies in primary alveolar type II cells. We demonstrate that ROCK1 and myosin light chain kinase 1 (MLCK1, also known as MYLK) translocate to fused lamellar bodies and activate myosin II on actin coats. However, myosin II activity is not sufficient for efficient actin coat contraction. In addition, cofilin-1 and &agr;-actinin translocate to actin coats. ROCK1-dependent regulated actin depolymerisation by cofilin-1 in cooperation with actin crosslinking by &agr;-actinin is essential for complete coat contraction. In summary, our data suggest a complementary role for regulated actin depolymerisation and crosslinking, and myosin II activity, to contract actin coats and drive secretion.
A Home-Visiting Diabetes Prevention and Management Program for American Indian Youth

Purpose The purpose of this study was to test the feasibility of a family-based, home-visiting diabetes prevention/management intervention for American Indian (AI) youth with or at risk for type 2 diabetes. Methods The Together on Diabetes program, developed through community-based participatory research, enrolled 255 AI youth (aged 10-19 years) with or at risk for type 2 diabetes and 223 support persons. Delivered by local AI paraprofessionals in 4 rural AI communities, the program included home-based lifestyle education and psychosocial support, facilitated referrals, and community-based healthy living activities. Changes in AI youth participants’ knowledge, behavior, psychosocial status, and physiological measurements were assessed over 12 months. Results Over one-half (56.1%) of youth were boys. The median age was 13.2 years. At baseline, 68.0% of youth reported no physical activity in the past 3 days; median percentages of kilocalories from fat (36.18%) and sweets (13.67%) were higher than US Department of Agriculture recommendations. Nearly 40% of participants reported food insecurity in the past month; 17.1% screened positive for depression. Support persons were predominantly family members, few reported having home Internet access (38.6%), and the majority reported being long distances (>30 minutes) from food stores. Whereas support persons were primarily responsible (≥69%) for obtaining medical care for the youth, the youth had a greater role in behavioral outcomes, indicating joint diabetes prevention/management responsibility. Conclusions: Baseline results confirmed the need for family-based youth diabetes prevention interventions in rural AI communities and indicated that enrolling at-risk youth and family members is feasible and acceptable.
Type 2 Diabetes and Depression

Purpose The purpose of the current study was to engage a local primary care clinic community that serves the Latino immigrant population to obtain their input regarding the design and implementation of a proposed integrated behavioral intervention that will simultaneously target T2DM and depression self-management in this high risk patient population. Methods Nine key informant interviews and 3 focus groups were conducted. Key informant interviews were conducted with the medical director, a primary care provider, a diabetes educator, and a medical assistant from each site, as well as the counselor who serves both sites. Fourteen patients with T2DM who screened positive for depression and 7 of their family members participated in the focus groups. Key informants and focus group participants were asked about patient challenges with diabetes management, the role of depression in T2DM, their impressions of the proposed intervention, and motivators and barriers to participation in the intervention. Results Commonly reported challenges with diabetes management included the struggle with healthy eating and information exchange upon diagnosis. T2DM and depression were seen as interrelated and described by many as having a cyclical relationship. Key informants and focus group participants uniformly supported the proposed intervention and recommended the involvement of family members. Conclusions Results of this study support the need and acceptability of individualized behavioral interventions that target T2DM and depression simultaneously.
A Wavelet Transform Based Technique For The Recognition Of The Human Iris

A new approach for the recognition of the iris of human eyes based on the wavelet transform is presented. It specifically uses the zero-crossings of the wavelet transform of the unique features obtained from the grey level profiles of the ins. The recognition process is performed in two stages. The fxst stage consists of building a one-dimensional representation of the grey level profiles of the iris, followed by obtaining the wavelet transform zerocrossings of the resulting representation. The second stage is the matching procedure for iris recognition. The proposed approach uses only a few selected intermediate resolution levels for matching, thus making it computationally efficient while being less sensitive to noise and quantisation errors. A normalisation process is implemented to compensate for size variations due to the possible variations in the camera-to-face distance. The technique has been tested on real images obtained under both noise-free and noisy conditions.
Verification of visual odometry algorithms with an OpenGL-based software tool

Abstract. We present a software tool called a stereovision egomotion sequence generator that was developed for testing visual odometry (VO) algorithms. Various approaches to single and multicamera VO algorithms are reviewed first, and then a reference VO algorithm that has served to demonstrate the program’s features is described. The program offers simple tools for defining virtual static three-dimensional scenes and arbitrary six degrees of freedom motion paths within such scenes and output sequences of stereovision images, disparity ground-truth maps, and segmented scene images. A simple script language is proposed that simplifies tests of VO algorithms for user-defined scenarios. The program’s capabilities are demonstrated by testing a reference VO technique that employs stereoscopy and feature tracking.
New Networks for Perfect Inversion and Perfect Reconstruction

The authors present a new network structure that realizes perfect inversion networks (PINs) and perfect reconstruction networks (PRNs). In some applications, such as transform source coders, it is important that the cascade of the forward and the inverse transform give the identity exactly (perfect inversion), although the coefficients and the intermediate results are quantized. In subband coders, for example, the split and merge filter banks should preferably have perfect reconstruction. It is advantageous if perfect reconstruction can be accomplished even when the coefficients and the intermediate results are quantized. The proposed network has a ladderlike shape and a predescribed symmetry between the forward and inverse network or between the split and merge bank. In some parts of this ladder network almost any function is allowed. Due to the prescribed symmetry, the property of perfect inversion or perfect reconstruction is structurally assured. >
Is Perceived Emotional Support Beneficial? Well-Being and Health in Independent and Interdependent Cultures

Previous studies show there is little or no association between perceived emotional support and well-being in European American culture. The authors hypothesized that this paradoxical absence of any benefit of perceived support is unique to cultural contexts that privilege independence rather than interdependence of the self. Study 1 tested college students and found, as predicted, that among Euro-Americans a positive effect of perceived emotional support on subjective well-being (positive affect) was weak and, moreover, it disappeared entirely once self-esteem was statistically controlled. In contrast, among Asians in Asia (Japanese and Filipinos) perceived emotional support positively predicted subjective well-being even after self-esteem was controlled. Study 2 extended Study 1 by testing both Japanese and American adults in midlife with respect to multiple indicators of well-being and physical health. Overall, the evidence underscores the central significance of culture as a moderator of the effectiveness of perceived emotional support.
A Further Report on the Cancer Family of Warthin

The family with numerous deaths from cancer, which was reported by Dr. A. S. Warthin in 1913 (1) and again in 1925 (2), has been referred to wherever the intrinsic factor in the etiology of malignancy has been discussed. Now that twenty-three years have passed since the first study of this family, it is appropriate again to bring its history up to date. Just as Warthin's second report was more complete and more accurate than the first, so it has been possible, by a personal investigation of each branch of this family, to present a more detailed and in a few respects a more exact chart of this large group which in six generations now totals 305 individuals. Although it is convenient to continue to refer to this family as Family G, the present study confirms the fact that the tendency to the development of cancer was present in the family line before the surname of which G is the initial was introduced by marriage. At the time of the first report, in 1913, of the 48 traced descendants of a cancerous grandfather 15 had developed cancer and in 2 others neoplasms had appeared which had not been proved to be malignant. The more complete report of 1925 showed an incidence of 28 neoplasms in a total of 146 individuals comprising the family, but of these only 88 had reached adult life. As now reported (Fig. 1), Family G includes 305 individuals. Since carcinoma has occurred in this family in individuals as young as twenty-five years, that period has been arbitrarily selected as the beginning of the “cancer age” for the family. An age of twenty-five years has been attained by 174 members of this family, of whom 41 have developed malignant neoplasms, an incidence of 23.6 per cent. As will appear later, there are two branches of the family in which malignant disease has never appeared. If the 25 in these two lines, who attained the “cancer age,” are excluded from the total of 174, the incidence of malignant disease in the other eight lines of the family becomes 27.5 per cent. These values for cancer incidence become all the more significant when it is borne in mind that, while it has been necessary to assume a low limit of twenty-five years for the “cancer age,” the average age at which cancer has been diagnosed in this family, or at which death from cancer has occurred, as the case may be, is 48.3 years.
Robust background subtraction to global illumination changes via multiple features-based online robust principal components analysis with Markov random field

Abstract. Background subtraction is an important task for various computer vision applications. The task becomes more critical when the background scene contains more variations, such as swaying trees and abruptly changing lighting conditions. Recently, robust principal component analysis (RPCA) has been shown to be a very efficient framework for moving-object detection. However, due to its batch optimization process, high-dimensional data need to be processed. As a result, computational complexity, lack of features, weak performance, real-time processing, and memory issues arise in traditional RPCA-based approaches. To handle these, a background subtraction algorithm robust against global illumination changes via online robust PCA (OR-PCA) using multiple features together with continuous constraints, such as Markov random field (MRF), is presented. OR-PCA with automatic parameter estimation using multiple features improves the background subtraction accuracy and computation time, making it attractive for real-time systems. Moreover, the application of MRF to the foreground mask exploits structural information to improve the segmentation results. In addition, global illumination changes in scenes are tackled by using sum of the difference of similarity measure among features, followed by a parameter update process using a low-rank, multiple features model. Evaluation using challenging datasets demonstrated that the proposed scheme is a top performer for a wide range of complex background scenes.