Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association Between Physical Function and Elder Mistreatment Among Community-Dwelling Chinese Older Adults in the Greater Chicago Area

Background Physical function (PF) impairment and elder mistreatment (EM) are alarming public health issues facing by many older adults. Prior studies have not generated uniform findings on the associations between PF and EM. This study aimed to address the research gap of this association among U.S. Chinese aging population. Methods Three thousand one hundred fifty-eight community-dwelling Chinese older adults in the Greater Chicago Area were surveyed. Independent variables included both self-reported and performance-based PF measurements. Dependent variable was EM, assessed by a 10-item instrument that has been widely used in social studies. Results The mean age of study participants was 76.3 years (SD ± 8.4) and 58.0% were female. After adjusting for potential covariates, higher scores of activities of daily living (odds ratio [OR] = 0.85, 95% confidence interval [CI] = 0.73-0.98), instrumental activities of daily living (OR = 0.87, 0.82-0.92), and Rosow-Breslau reversely coded (OR = 0.85, 0.75-0.96) were associated with lower risk of EM. Also, lower scores of observed PF performance measurements, including tandem stand (OR = 0.78, 0.70-0.88), measured walk (OR = 0.84, 0.77-0.91), and the overall measurement (OR = 0.93, 0.89-0.97) have significant associations with lower risk of EM. Conclusions Findings from this study suggested that greater levels of PF impairment were associated with lower risk of EM among U.S. Chinese older adults in the Greater Chicago Area. Longitudinal studies are needed to obtain a more comprehensive understanding of the pathways between PF and EM and its subtypes among Chinese aging populations.
Learning Item/User Vectors from Comments for Collaborative Recommendation

Collaborative Filtering (CF) has been widely used in many recommender systems over the past decades. Conventional CF-based methods mainly consider the ratings given to items via users and suffer from the sparsity and cold-start problems very much. Comments written by users contain much more information about item/user profiles than ratings. And a lot of comment-based methods have been developed in recent years. In this paper, we propose a fresh framework which represents item/user profiles as vectors learned from comments. We represent comments with word embedding vectors which are widely used by deep learning methods nowadays. Sufficient experiments with different datasets show that our method is feasible and much more effective for sparsity and cold-start problems than rating-only-based methods.
Novel RpoS-Dependent Mechanisms Strengthen the Envelope Permeability Barrier during Stationary Phase

ABSTRACT Gram-negative bacteria have effective methods of excluding toxic compounds, including a largely impermeable outer membrane (OM) and a range of efflux pumps. Furthermore, when cells become nutrient limited, RpoS enacts a global expression change providing cross-protection against many stresses. Here, we utilized sensitivity to an anionic detergent (sodium dodecyl sulfate [SDS]) to probe changes occurring to the cell's permeability barrier during nutrient limitation. Escherichia coli is resistant to SDS whether cells are actively growing, carbon limited, or nitrogen limited. In actively growing cells, this resistance depends on the AcrAB-TolC efflux pump; however, this pump is not necessary for protection under either carbon-limiting or nitrogen-limiting conditions, suggesting an alternative mechanism(s) of SDS resistance. In carbon-limited cells, RpoS-dependent pathways lessen the permeability of the OM, preventing the necessity for efflux. In nitrogen-limited but not carbon-limited cells, the loss of rpoS can be completely compensated for by the AcrAB-TolC efflux pump. We suggest that this difference simply reflects the fact that nitrogen-limited cells have access to a metabolizable energy (carbon) source that can efficiently power the efflux pump. Using a transposon mutant pool sequencing (Tn-Seq) approach, we identified three genes, sanA, dacA, and yhdP, that are necessary for RpoS-dependent SDS resistance in carbon-limited stationary phase. Using genetic analysis, we determined that these genes are involved in two different envelope-strengthening pathways. These genes have not previously been implicated in stationary-phase stress responses. A third novel RpoS-dependent pathway appears to strengthen the cell's permeability barrier in nitrogen-limited cells. Thus, though cells remain phenotypically SDS resistant, SDS resistance mechanisms differ significantly between growth states. IMPORTANCE Gram-negative bacteria are intrinsically resistant to detergents and many antibiotics due to synergistic activities of a strong outer membrane (OM) permeability barrier and efflux pumps that capture and expel toxic molecules eluding the barrier. When the bacteria are depleted of an essential nutrient, a program of gene expression providing cross-protection against many stresses is induced. Whether this program alters the OM to further strengthen the barrier is unknown. Here, we identify novel pathways dependent on the master regulator of stationary phase that further strengthen the OM permeability barrier during nutrient limitation, circumventing the need for efflux pumps. Decreased permeability of nutrient-limited cells to toxic compounds has important implications for designing new antibiotics capable of targeting Gram-negative bacteria that may be in a growth-limited state.
Turtle Guard: Helping Android Users Apply Contextual Privacy Preferences

Current mobile platforms provide privacy management interfaces to regulate how applications access sensitive data. Prior research has shown how these interfaces are insuﬃcient from a usability standpoint: they do not account for context . In allowing for more contextual decisions, machine-learning techniques have shown great promise for designing systems that automatically make privacy decisions on behalf of the user. However, if such decisions are made automatically, then feedback mechanisms are needed to empower users to both audit those decisions and correct any errors. In this paper, we describe our user-centered approach towards designing a fully functional privacy feedback interface for the Android platform. We performed two large-scale user studies to research the usability of our design. Our second, 580-person validation study showed that users of our new interface were signiﬁcantly more likely to both understand and control the selected set of circumstances under which applications could access sensitive data when compared to the default Android privacy settings interface.
Genetic Diversity, Population Structure, and Genetic Correlation with Climatic Variation in Chickpea (Cicer arietinum) Landraces from Pakistan

Cultivated landraces may harbor “genomic gems” for crop improvement. Covariation between genomes and environments can prioritize crop accessions for study. Genomics, modeling, and genetics can unlock the potential of landraces. Pakistan's historical landraces are a source of variation for limited water and high heat.
Building knowledge-enabled cloud robotics applications using the ubiquitous network robot platform

In this paper, we discuss how networked robot architectures can facilitate the development, deployment, management and adaptation of distributed robotic applications. Our aim is to modularize applications by factoring out environment, task-, domain-, and robot-specific knowledge components and representing them explicitly in a formal knowledge base that is shared between the robots and service applications. Robot control decisions can then be formulated in terms of inference tasks that are evaluated based on this knowledge during task execution. The explicit and modular knowledge representation allows human operators with different areas of expertise to adapt the respective parts of the knowledge independently. We implemented this concept by integrating knowledge representation methods of the RoboEarth project with the distributed task execution capabilities of the Ubiquitous Network Robot Platform.
Adipokines and inflammation markers and risk of differentiated thyroid carcinoma: The EPIC study

Other than the influence of ionizing radiation and benign thyroid disease, little is known about the risk factors for differentiated thyroid cancer (TC) which is an increasing common cancer worldwide. Consistent evidence shows that body mass is positively associated with TC risk. As excess weight is a state of chronic inflammation, we investigated the relationship between concentrations of leptin, adiponectin, C‐reactive protein, interleukin (IL)‐6, IL‐10 and tumor necrosis factor (TNF)‐α and the risk of TC. A case‐control study was nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) study and included 475 first primary incident TC cases (399 women and 76 men) and 1,016 matched cancer‐free cohort participants. Biomarkers were measured in serum samples using validated and highly sensitive commercially available immunoassays. Odds ratios (ORs) of TC by levels of each biomarker were estimated using conditional logistic regression models, adjusting for BMI and alcohol consumption. Adiponectin was inversely associated with TC risk among women (ORT3vs.T1 = 0.69, 95% CI: 0.49–0.98, Ptrend = 0.04) but not among men (ORT3vs.T1 = 1.36, 95% CI: 0.67–2.76, Ptrend = 0.37). Increasing levels of IL‐10 were positively associated with TC risk in both genders and significantly so in women (ORT3vs.T1 = 1.59, 95% CI: 1.13–2.25, Ptrend = 0.01) but not in men (ORT3vs.T1 = 1.78, 95% CI: 0.80–3.98, Ptrend = 0.17). Leptin, CRP, IL‐6 and TNF‐α were not associated with TC risk in either gender. These results indicate a positive association of TC risk with IL‐10 and a negative association with adiponectin that is probably restricted to women. Inflammation may play a role in TC in combination with or independently of excess weight.
Interventions that Enhance Breastfeeding Initiation, Duration, and Exclusivity: A Systematic Review

Objective:The purpose of this review was to evaluate breastfeeding interventions trialed to date and recommend directions for future needs in breastfeeding research. Methods:A literature review was conducted using PubMed, CINAHL Plus, and PsycINFO databases to identify studies that evaluated efficacy or effectiveness of breastfeeding interventions on breastfeeding initiation, duration, or exclusivity as a primary, secondary, or tertiary outcome. Combinations of search terms included breastfeeding, feeding behavior, prenatal/patient education, health promotion, social support, perinatal/prenatal/intrapartum/postnatal care, and postpartum period. Results:Six studies were included in this review, using PRISMA guidelines. Acquisition of knowledge and skills, emotional support by healthcare providers, and self-efficacy over maternal confidence in her ability to breastfeed were factors the intervention studies relied on to affect breastfeeding practices. Although these factors were addressed in the studies, breastfeeding mothers had difficulty transferring what they gained from interventions into their real-life breastfeeding practices as evidenced by the highest drop-off rate of exclusive breastfeeding in the early postpartum. Conclusions:There were conceptual limitations to the reviewed studies: (1) lack of understanding of maternal perception of infant behavior and (2) perceived insufficient milk as a remaining primary reason for breastfeeding discontinuation. There were methodological limitations: (1) lack of theory-based interventions and (2) lack of intervention fidelity. Future studies involving breastfeeding should focus on the causes of the problems driven by theory-based interventions integrated with intervention fidelity.
Bootstrapping interactions with objects from raw sensorimotor data: A novelty search based approach

Determining in advance all objects that a robot will interact with in an open environment is very challenging, if not impossible. It makes difficult the development of models that will allow to perceive and recognize objects, to interact with them and to predict how these objects will react to interactions with other objects or with the robot. Developmental robotics proposes to make robots learn by themselves such models through a dedicated exploration step. It raises a chicken-and-egg problem: the robot needs to learn about objects to discover how to interact with them and, to this end, it needs to interact with them. In this work, we propose Novelty-driven Evolutionary Babbling (NovEB), an approach enabling to bootstrap this process and to acquire knowledge about objects in the surrounding environment without requiring to include a priori knowledge about the environment, including objects, or about the means to interact with them. Our approach consists in using an evolutionary algorithm driven by a novelty criterion defined in the raw sensorimotor flow: behaviours, described by a trajectory of the robot end effector, are generated with the goal to maximize the novelty of raw perceptions. The approach is tested on a simulated PR2 robot and is compared to a random motor babbling.
Survey for Correlation between Biofilm Formation and Virulence Determinants in a Collection of Pathogenic and Fecal Enterococcus faecalis Isolates

Background Enterococcus faecalis is an opportunistic pathogen that causes most of the enterococcal infections. Among the different factors implicated in the pathogenesis of these organisms, biofilm formation and antibiotic resistance are the most important. The ability for biofilm formation has been attributed to the presence of some virulence genes. However, no definite correlation has been found. This study aimed to detect biofilm formation and antibiotic resistance patterns in E. faecalis isolates collected from clinical and fecal samples, and to investigate possible correlation between some virulence genes (esp, cyl, gelE) and biofilm formation. Materials and Methods A collection of 123 E. faecalis isolates were investigated for antibiotic resistance and production of hemolysin, gelatinase, and biofilm using phenotypic methods. The esp, gelE and cyl genes were detected using polymerase chain reaction. Results Thirty-eight pathogenic isolates (37%) were positive for biofilm formation. Additionally, the gelE, esp, and cyl genes were detected in 74 (71.8%), 79 (76.7%) and 42 (40.8%) isolates, respectively. In the fecal samples, 18 (90%) isolates were biofilm producers and 11 (55%), 17 (85%) and 8 (40%) isolates were positive for gelE, esp, and cyl, respectively. There were significant differences in biofilm production between pathogenic and fecal isolates (P <0.001). Multidrug resistance (MDR) was found among 32% (n = 33) and 15% (n = 3) of the clinical and fecal isolates, respectively. However, no significant difference was seen between MDR and biofilm formation. Five pathogenic and two fecal isolates were negative for all investigated genes while they were they were biofilm producers. In contrast, 22 pathogenic isolates and 1 fecal isolate were positive for the tested genes, but did not form any biofilm. No significant differences were observed between biofilm formation and the presence of the esp, gelE and cyl genes in the pathogenic and fecal isolates (P ˃0.05). Conclusion The presence of the esp, gelE and cyl genes might not be determining factors for biofilm formation in enterococci and other mechanisms might be involved in this process.
Numerical Solution of Multiphysics Large Deflection Plates for Ionic Polymeric Artificial Muscle Applications

Recent advances in the manufacturing of new materials that can by activated by multifield excitation have introduced the need for modeling their multiphysics behavior. In responding to this need the special case of electric multihygrothermoelasticity is being considered as the closest multiphysics theory for modeling the behavior electro-hygrothermo-elasto-active materials utilized in artificial muscle applications. Furthermore, the system of governing partial differential equations describing the state evolution of large deflection plates made from such materials is derived as a twodimensional specialization of the above mentioned theory. These electro-hygro-thermally modified Von-Karman nonlinear equations are solved numerically through an adaptive finite element approach and preliminary results are presented for the case of a rectangular ionic polymeric material plate under various boundary conditions. Finally, various issues associated with the regimes of applicability of this theory and approach are also presented. © 2003 ASME
Beneficial Effect of an Oral Antioxidant Supplementation (Fertimax2) on IVF-ICSI Outcomes: A Preliminary Clinical Study

Background: Considerable evidence points towards a significant role of oxidative stress (OS) in the pathogenesis of sperm dysfunction. OS as a result of an inappropriate balance between oxidants and antioxidants in the semen can cause DNA damage and lipid peroxidation leading to failure of conception, miscarriage or potentially even childhood cancer. The objective of this study was to investigate whether a male antioxidant therapy can improve semen parameters and the results of in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI). Methods: A total of forty eight infertile couples were considered. Male participants were administrated Fertimax2 antioxidant treatment for at least two months prior to their partner’s IVF-ICSI cycle. Sperm parameters (volume, concentration, progressive motility) and the IVF-ICSI outcomes were compared before and after the antioxidant treatment. The primary outcome measures were oocyte fertilization, cleavage and good embryo quality rates; the secondary outcomes were biochemical pregnancies, clinical pregnancies and implantation rates. Results: The principal finding that emerged from this study was that antioxidant therapy resulted in significant improvements in fertilization (p = 00.2), cleavage (p = 0.004) and good-embryo quality (p = 0.002) rates accompanied by a marked increase in clinical pregnancy (18.7% versus 2.5%) and implantation (11.8% versus 1.02%) rates. No significant changes in routine sperm parameters were observed. Conclusion: The Fertimax2 antioxidant therapy appears to influence favorably chances of conception in couples undergoing assisted reproduction treatment (ART).
Prehospital End-tidal Carbon Dioxide Predicts Mortality in Trauma Patients

Abstract Background: End-tidal carbon dioxide (EtCO2) measurement has been shown to have prognostic value in acute trauma. Objective: Evaluate the association of prehospital EtCO2 and in-hospital mortality in trauma patients and to assess its prognostic value when compared to traditional vital signs. Methods: Retrospective, cross-sectional study of patients transported by a single EMS agency to a level one trauma center. We evaluated initial out-of-hospital vital signs documented by EMS personnel including EtCO2, respiratory rate (RR), systolic BP (SBP), diastolic BP (DBP), pulse (P), and oxygen saturation (O2) and hospital data. The main outcome measure was mortality. Results: 135 trauma patients were included; 9 (7%) did not survive. The mean age of patients was 40 (SD17) [Range 16–89], 97 (72%) were male, 76 (56%) were admitted to the hospital and 15 (11%) went to the ICU. The mean EtCO2 level was 18 mmHg (95%CI 9–28) [Range 5–41] in non-survivors compared to 34 mmHg (95%CI 32–35) [Range 11–51] in survivors. The area under the ROC curve (AUC) for EtCO2 in predicting mortality was 0.84 (0.67–1.00) (p = 0.001), RR was 0.82 (0.63–1.00), SBP was 0.72 (0.49–0.96), DBP was 0.72 (0.47–0.97), pulse was 0.51 (0.26–0.76), and O2 was 0.64 (0.37–0.91). Cut-off values at 30 mmHg yielded sensitivity = 89% (51–99), specificity = 68% (59–76), PPV = 13% (6–24) and NPV = 99% (93–100) for predicting mortality. There was no correlation between RR and EtCO2 (correlation 0.16; p = 0.06). Conclusion: We found an inverse association between prehospital EtCO2 and mortality. This has implications for improving triage and assisting EMS in directing patients to an appropriate trauma center.
Why Do Defaults Affect Behavior? Experimental Evidence from Afghanistan

We report on an experiment examining why default options impact behavior. By randomly assigning employees to different varieties of a salary-linked savings account, we find that default enrollment increases participation by 40 percentage points—an effect equivalent to providing a 50 percent matching incentive. We then use a series of experimental interventions to differentiate between explanations for the default effect, which we conclude is driven largely by present-biased preferences and the cognitive cost of thinking through different savings scenarios. Default assignment also changes employees’ attitudes toward saving, and makes them more likely to actively decide to save after the study concludes. (JEL C93, D14, D91, O12)
Stream Data Mining and Comparative Study of Classification Algorithms Ms .

Stream Data Mining is a new emerging topic in the field of research. Today, there are number of application that generate Massive amount of stream data. Examples of such kind of systems are Sensor networks, Real time surveillance systems, telecommunication systems. Hence there is requirement of intelligent processing of such type of data that would help in proper analysis and use of this data in other task even. Mining stream data is concerned with extracting knowledge structures represented in models and patterns in non stopping streams of information [1] . Such massive data are handled with software such as MOA (Massive Online Analysis) or other open sources like Data Miner. In this paper we present some theoretical aspects of stream data mining and certain experimental results obtained on that basis with the use of
Cultivating Skills for Success in Learning Health Systems Learning to Lead

F ellows-in-training (FITs) and early career professionals (ECPs) are currently practicing in a complex health care environment. Indeed, there are multiple foci of interaction in a 21st-century academic medical center (AMC) extending beyond the traditional commitment to the tripartite mission of patient care, education, and research (1). These include interactions with community medical practices, post-acute care facilities, health information technology vendors, research institutes and industry, and public health agencies (2). Therefore, it is imperative for ECPs to have an in-depth understanding of the complex interplay among the regulatory, political, and socioeconomic components of the health care systems in which they work. Moreover, with the advent of the learning health system (LHS), investing in formal training pathways that simultaneously develop leadership skills in patient safety, health care quality, and health informatics—the quintessential building blocks of an LHS—can be pivotal in helping FITs and ECPs carve a career path in academic cardiovascular medicine as a clinician-administrator or an LHS expert. Attaining leadership skills in patient safety, health care quality, and health informatics is necessary for FITs and ECPs interested in transforming an AMC into an LHS. According to a recent American Heart