Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceived Expressed Emotion, Emotional and Behavioral Problems and Self-Esteem in Obese Adolescents: A Case-Control Study

Objective: Obesity is a chronic disease which leads to medical and psychiatric complications. Family climate is a critical factor in the treatment of obesity and comorbid psychiatric disorders. In our study, perceived expressed emotion (EE), psychopathology, self-esteem and emotional and behavioural problems (BP) among obese adolescents were investigated and compared with their non-obese peers. Methods: The subjects were 49 obese adolescents and 47 non-obese adolescents served as the control group. All participants were requested to fill out the Socio-demographic Data Form, Shortened Level of Expressed Emotion Scale, Rosenberg Self-Esteem Scale, Strength and Difficulties Questionnaire-Adolescent Form. Results: In our study, obese adolescents showed a significant difference in perceived EE (p<0.001). Subscales of EE, such as Lack of Emotional Support (p<0.001), intrusiveness (p<0.001), irritability (p<0.001), self-esteem (p<0.001), emotional and BP (p<0.001), attention deficit-hyperactivity disorder (p<0.001), problems in peer relationships (p<0.001) and social skills (p<0.001) were significantly worse when compared with the control group. There was a strong relationship between EE and emotional and BP and self-esteem. Conclusion: The higher rate of perceived EE, psychopathology and low self-esteem among obese adolescents showed that obesity prevention and treatment are also crucial for good mental health in adolescents. The important role of the family in mental health of obese adolescents was emphasized. It was shown that identification of risk factors in childhood that promote obesity should be done so that targeted intervention and prevention programs can be developed.
Incidence of Type 1 Diabetes in Children Aged Below 18 Years during 2013-2015 in Northwest Turkey

Objective: To assess the incidence of type 1 diabetes mellitus (T1DM) in children under 18 years of age in the northwest region of Turkey during 2013-2015. Methods: All newly diagnosed T1DM cases were recorded prospectively during 2013-2015. Total, as well as gender and age group specific (0-4, 5-9, 10-14 and 15-17 age) mean incidences per 100,000 per year were calculated. Results: There were 1,773 patients diagnosed during 2013-2015 (588 cases in 2013, 592 cases in 2014, 593 cases in 2015). Of these, 862 (48.6%) were girls and 911 (51.4%) were boys. The mean age at diagnosis was 9.2±4.2 years and it was not significantly different between girls (9.0±4.1 years) and boys (9.4±4.4 years) (p=0.052). The crude mean incidence was 8.99/100.000 confidence interval (CI) (95% CI: 8.58-9.42). Although mean incidence was similar between boys [8.98/100.000 (CI: 8.40 to 9.58)] and girls [9.01/100.000 (CI: 8.42 to 9.63)], there was male predominance in all groups except for 5-9 year age group. The standardized mean incidence was 9.02/100.000 according to the World Health Organization standard population. The mean incidence for the 0-4, 5-9, 10-14 and 15-17 age groups was 6.13, 11.68, 11.7 and 5.04/100.000 respectively. The incidence of T1DM was similar over the course of three years (p=0.95). A significant increase in the proportion of cases diagnosed was observed in the autumn-winter seasons. Conclusion: The northwest region of Turkey experienced an intermediate incidence of T1DM over the period of the study.
Properties of the Social Discount Rate and Intertemporal Negative Externality in the Utility or Production Function

This study examines the role of the social discount rate, as applied to the efficient allocation of carbon dioxide (CO2) emissions, which provokes serious intertemporal negative externalities such as global warming. Two approaches exist in introducing the intertemporal negative externality brought about by such emissions into economic theory. One is the utility-function approach, and the other is the production-function approach. The former is well-suited to the case in which climate change directly threatens the living standard of human, for example, through a drastic degradation of the environment. The latter approach becomes relevant to case in which global warming is expected to lead to productivity stagnation particular to the additional costs of adaptation.
ncreased home size and hardscape decreases urban forest cover in os Angeles County ’ s single-family residential neighborhoods u

Single-family residential neighborhoods make up large areas within cities and are undergoing change as residences are renovated and redeveloped. We investigated the effects of such residential redevelopment on land cover (trees/shrubs, grass, building, and hardscape) in the 20 largest cities in the Los Angeles Basin from 2000 to 2009. We identified spatially stratified samples of single-family home lots for which additional square footage was recorded and for which additional construction was not recorded by the tax assessor. We then digitized land cover on high-resolution color imagery for two points in time to measure land cover change. Redevelopment of single-family homes in Los Angeles County resulted in a significant decrease in tree/shrub and grass cover and a significant increase in building and hardscape area. Over 10 years, urban green cover (trees/shrubs and grass) declined 14–55% of green cover in 2000 on lots with additional recorded development and 2–22% of green cover in 2000 for single-family lots for which new permits were not recorded. Extrapolating the results to all single-family home lots in these cities indicate a 1.2 percentage point annual decrease in tree/shrub cover (5.6% of existing tree/shrub cover) and a 0.1 percentage point annual decrease in grass cover (2.3% of existing grass cover). The results suggest that protection of existing green cover in neighborhoods is necessary to meet urban forest goals, a factor that is overlooked in existing programs that focus solely on tree planting. Also, changing social views on the preferred size of single-family homes is driving loss of tree cover and increasing impervious surfaces, with potentially significant ramifications for the functioning of urban ecosystems. © 2017 Elsevier GmbH. All rights reserved.
Does biological sex impact intestinal epithelial injury, small intestine permeability, gastrointestinal symptoms and systemic cytokine profile in response to exertional-heat stress?

ABSTRACT This study aimed to determine the influence of biological sex on intestinal injury, permeability, gastrointestinal symptoms, and systemic cytokine profile in response to exertional-heat stress. Male (n= 13) and eumenorrheic female (n= 11) endurance runners completed 2 h running at 60% V̇O2max in 35°C. Blood samples were collected pre- and post-exercise and during recovery to determine plasma intestinal fatty-acid binding protein (I-FABP) and systemic cytokine profile. Urinary lactulose:L-rhamnose ratio was used to determine small intestine permeability. I-FABP increased 479% pre- to post-exercise (p< 0.001), with no difference between sexes (p= 0.432). No differences between sexes were observed for small intestine permeability (p= 0.808), gut discomfort, total, upper- and lower-gastrointestinal symptoms. However, males reported significantly higher flatulence (p= 0.049) and abdominal stitch (p= 0.025) compared to females. IL-6, IL-8, IL-10 and IL-1ra increased pre- to post-exercise (p< 0.05), with no difference between sexes. However, IL-1β increased post-exercise in males only, and was higher in males compared to females (p= 0.044). Findings suggest that when females are in the follicular phase of the menstrual cycle, biological sex has no effect on intestinal epithelial injury and permeability, and minimal effect on gastrointestinal symptoms and systemic cytokine profile in response to exertional-heat stress.
Robotic Parathyroid Surgery: Current Perspectives and Future Considerations

Robotic parathyroidectomy represents a novel surgical approach in the treatment of primary hyperparathyroidism when the parathyroid adenoma has been pre-operatively localised. It represents the “fourth generation” in the evolution of parathyroid surgery following a process of surgical evolution from cervicotomy and 4-gland exploration to a variety of minimally invasive, open and endoscopic, targeted approaches. The existing evidence (levels 2–3) supports it as a feasible and safe technique with equivalent results to targeted open parathyroidectomy for primary hyperparathyroidism in carefully selected patients. However, it takes longer to perform and is more costly than conventional parathyroidectomy. It offers superior cosmesis by completely avoiding a neck scar making it a valid option for those patients who for biological and/or cultural reasons may wish to avoid a neck scar. Robotic parathyroidectomy is not for every patient, surgeon, or hospital. Its application should be confined to high-volume centres and experienced surgeons. Intensive training and proctorship are required for its safe implementation combined with careful patient selection. This particularly relates to the patient’s body habitus (BMI < 30 kg/m2) and concordance among the different imaging modalities used pre-operatively. With robotic market competition driving down costs, its role may change. For now, robotic parathyroidectomy occupies a niche role and can only be justified in a select subset of patients.
Psychometric evaluation of the Smartphone for Clinical Work Scale to measure nurses’ use of smartphones for work purposes

Objective This study reports the development and psychometric evaluation of the Smartphone for Clinical Work Scale (SCWS) to measure nurses' use of smartphones for work purposes. Methods Items were developed based on literature review and a preliminary study. After expert consultations and pilot testing, a 20-item scale was administered in January-June 2017 to 517 staff nurses from 19 tertiary-level general hospitals in Metro Manila, Philippines. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to evaluate construct validity. Structural equation modeling (SEM) was used to test the predictive validity of SCWS on perceived work productivity. Results EFA results show that 15 out of 20 items loaded on five factors: communication with clinicians via call and text, communication with doctors via instant messaging, information seeking, communication with nurses via instant messaging, and communication with patients via call and text. CFA results suggest that the five factors that form SCWS have adequate fit to the data, thus supporting construct validity. SEM results suggest predictive validity since SCWS was positively associated with perceived work productivity. Conclusions The 15-item SCWS showed satisfactory psychometric properties for use in future studies. These studies can focus on identifying factors associated with nurses' use of smartphones for work purposes.
Palynological evidence for late Miocene stepwise aridification on the northeastern Tibetan Plateau

Abstract. Holding a climatically and geologically key position both regionally and globally, the northeastern Tibetan Plateau provides a natural laboratory for illustrating the interactions between tectonic activity and the evolution of the Asian interior aridification. Determining when and how the late Miocene climate evolved on the northeastern Tibetan Plateau may help us better understand the relationships among tectonic uplift, global cooling and ecosystem evolution. Previous paleoenvironmental research has focused on the western Longzhong Basin. Late Miocene aridification data derived from pollen now require corroborative evidence from the eastern Longzhong Basin. Here, we present a late Miocene pollen record from the Tianshui Basin in the eastern Longzhong Basin. Our results show that a general trend toward dry climate was superimposed by stepwise aridification: a temperate forest with a rather humid climate existed in the basin between 11.4 and 10.1 Ma, followed by a temperate open forest environment with a less humid climate between 10.1 and 7.4 Ma, then giving way to an open temperate forest–steppe environment with a relatively arid climate between 7.4 and 6.4 Ma. The vegetation succession demonstrates that the aridification of the Asian interior occurred after ∼ 7–8 Ma, which is confirmed by other evidence from Asia. Furthermore, the aridification trend on the northeastern Tibetan Plateau parallels the global cooling of the late Miocene; the stepwise vegetation succession is consistent with the major uplift of the northeastern Tibetan Plateau during this time. These integrated environmental proxies indicate that the long-term global cooling and the Tibetan Plateau uplift caused the late Miocene aridification of the Asian interior.
Optimal Sensor Collaboration for Parameter Tracking Using Energy Harvesting Sensors

In this paper, we design an optimal sensor collaboration strategy among neighboring nodes while tracking a time-varying parameter using wireless sensor networks in the presence of imperfect communication channels. The sensor network is assumed to be self-powered, where sensors are equipped with energy harvesters that replenish energy from the environment. In order to minimize the mean square estimation error of parameter tracking, we propose an online sensor collaboration policy subject to real-time energy harvesting constraints. The proposed energy allocation strategy is computationally light and only relies on the second-order statistics of the system parameters. For this, we first consider an offline nonconvex optimization problem, which is solved exactly when using semidefinite programming. Based on the offline solution, we design an online power allocation policy that requires minimal online computation and satisfies the dynamics of energy flow at each sensor. We prove that the proposed online policy is asymptotically equivalent to the optimal offline solution and show its convergence rate and robustness. We empirically show that the estimation performance of the proposed online scheme is better than that of the online scheme when channel state information about the dynamical system is available in the low SNR regime. Numerical results demonstrate the effectiveness of our approach.
Estimating probabilistic context-free grammars for proteins using contact map constraints

Interactions between amino acids that are close in the spatial structure, but not necessarily in the sequence, play important structural and functional roles in proteins. These non-local interactions ought to be taken into account when modeling collections of proteins. Yet the most popular representations of sets of related protein sequences remain the profile Hidden Markov Models. By modeling independently the distributions of the conserved columns from an underlying multiple sequence alignment of the proteins, these models are unable to capture dependencies between the protein residues. Non-local interactions can be represented by using more expressive grammatical models. However, learning such grammars is difficult. In this work, we propose to use information on protein contacts to facilitate the training of probabilistic context-free grammars representing families of protein sequences. We develop the theory behind the introduction of contact constraints in maximum-likelihood and contrastive estimation schemes and implement it in a machine learning framework for protein grammars. The proposed framework is tested on samples of protein motifs in comparison with learning without contact constraints. The evaluation shows high fidelity of grammatical descriptors to protein structures and improved precision in recognizing sequences. Finally, we present an example of using our method in a practical setting and demonstrate its potential beyond the current state of the art by creating a grammatical model of a meta-family of protein motifs. We conclude that the current piece of research is a significant step towards more flexible and accurate modeling of collections of protein sequences. The software package is made available to the community.
Sleep Disorders, Including Sleep Apnea and Hypertension

There is mounting evidence for an association between sleep disorders and hypertension. In obstructive sleep apnea (OSA), there are plausible biological reasons for the development of hypertension, and treatment of OSA results in modest (2-3 mm Hg), adherence-dependent decreases in blood pressure, with larger effects evident in those with resistant hypertension. However, prospective, population-based cohort studies have not yet convincingly demonstrated a link between OSA and incident hypertension, and adequately powered controlled trials of CPAP for the prevention or treatment or hypertension are lacking. While associations have been identified between short sleep duration, insomnia, restless legs syndrome (RLS), shift work, and hypertension, the causative role of these conditions/circumstances is not proven, and further well-designed pathophysiological and/or interventional studies are needed. Particular emphasis should be placed on defining subgroups of hypertensive OSA patients that stand to benefit most from OSA treatment and in understanding the link between sleep apnea and hypertensive disorders of pregnancy. Well-controlled intervention studies are needed in populations with short sleep duration, insomnia, shift work sleep disorder, and RLS to confirm their putative links with hypertension.
Predicting Intensive Care Unit Readmission with Machine Learning Using Electronic Health Record Data

&NA; Rationale: Patients transferred from the intensive care unit to the wards who are later readmitted to the intensive care unit have increased length of stay, healthcare expenditure, and mortality compared with those who are never readmitted. Improving risk stratification for patients transferred to the wards could have important benefits for critically ill hospitalized patients. Objectives: We aimed to use a machine‐learning technique to derive and validate an intensive care unit readmission prediction model with variables available in the electronic health record in real time and compare it to previously published algorithms. Methods: This observational cohort study was conducted at an academic hospital in the United States with approximately 600 inpatient beds. A total of 24,885 intensive care unit transfers to the wards were included, with 14,962 transfers (60%) in the training cohort and 9,923 transfers (40%) in the internal validation cohort. Patient characteristics, nursing assessments, International Classification of Diseases, Ninth Revision codes from prior admissions, medications, intensive care unit interventions, diagnostic tests, vital signs, and laboratory results were extracted from the electronic health record and used as predictor variables in a gradient‐boosted machine model. Accuracy for predicting intensive care unit readmission was compared with the Stability and Workload Index for Transfer score and Modified Early Warning Score in the internal validation cohort and also externally using the Medical Information Mart for Intensive Care database (n = 42,303 intensive care unit transfers). Results: Eleven percent (2,834) of discharges to the wards were later readmitted to the intensive care unit. The machine‐learning‐derived model had significantly better performance (area under the receiver operating curve, 0.76) than either the Stability and Workload Index for Transfer score (area under the receiver operating curve, 0.65), or Modified Early Warning Score (area under the receiver operating curve, 0.58; P value < 0.0001 for all comparisons). At a specificity of 95%, the derived model had a sensitivity of 28% compared with 15% for Stability and Workload Index for Transfer score and 7% for the Modified Early Warning Score. Accuracy improvements with the derived model over Modified Early Warning Score and Stability and Workload Index for Transfer were similar in the Medical Information Mart for Intensive Care‐III cohort. Conclusions: A machine learning approach to predicting intensive care unit readmission was significantly more accurate than previously published algorithms in both our internal validation and the Medical Information Mart for Intensive Care‐III cohort. Implementation of this approach could target patients who may benefit from additional time in the intensive care unit or more frequent monitoring after transfer to the hospital ward.
Target Focused Sentiment Extraction Framework

Albany’s Target Focused Sentiment Extraction Framework consists of a step-wise approach to analyze the sentiment components incorporated into the social aspects of dialogue. We build an extensible modular framework that extracts sentiment from nat-ural language text, along with the sentiment holder and the sentiment target. It improves our previous work [DWW + 16] regarding sentiment extraction by tackling the problem of generating proper sentiment holder and target pairs, thus leading to an increased Recall measure.
Contextualising Maximal Fat Oxidation During Exercise: Determinants and Normative Values

Using a short-duration step protocol and continuous indirect calorimetry, whole-body rates of fat and carbohydrate oxidation can be estimated across a range of exercise workloads, along with the individual maximal rate of fat oxidation (MFO) and the exercise intensity at which MFO occurs (Fatmax). These variables appear to have implications both in sport and health contexts. After discussion of the key determinants of MFO and Fatmax that must be considered during laboratory measurement, the present review sought to synthesize existing data in order to contextualize individually measured fat oxidation values. Data collected in homogenous cohorts on cycle ergometers after an overnight fast was synthesized to produce normative values in given subject populations. These normative values might be used to contextualize individual measurements and define research cohorts according their capacity for fat oxidation during exercise. Pertinent directions for future research were identified.
Lifetime Smoking History and Risk of Lung Cancer: Results From the Framingham Heart Study

Background The relative risk of lung cancer decreases with years since quitting (YSQ) smoking, but risk beyond 25 YSQ remains unclear. Current lung cancer screening guidelines, which exclude smokers with more than 15 YSQ, may not detect lung cancers in this population. Methods We analyzed data from Framingham Heart Study Original (n = 3905) and Offspring cohort (n = 5002) participants for lifetime smoking and lung cancer incidence from 1954 to 1958 (Exam 4) and 1971 to 1975 (Exam 1), respectively, through 2013. We used multivariable-adjusted Cox proportional hazards regression models to compare current, former, and never smokers and lung cancer risk. Smoking status and covariates were time-updated every two years (Original) or four years (Offspring). Primary analyses were restricted to heavy ever smokers with more than 21.3 pack-years; additional analyses included all ever smokers. Results On follow-up (median = 28.7 years), 284 lung cancers were detected: incidence rates/1000 person-years in current, former, and never smokers were 1.97 (95% confidence interval [CI] = 1.66 to 2.33), 1.61 (95% CI = 1.34 to 1.93), and 0.26 (95% CI = 0.17 to 0.39), respectively. Heavy former (vs never) smokers had elevated lung cancer risk at all YSQ (<5: hazard ratio [HR] = 12.12, 95% CI = 6.94 to 21.17; 5-9: HR = 11.77, 95% CI = 6.78 to 20.45; 10-14: HR = 7.81, 95% CI = 3.98 to 15.33; 15-24: HR = 5.88, 95% CI = 3.19-10.83; ≥25: HR = 3.85, 95% CI = 1.80 to 8.26). Heavy former (vs current) smokers had 39.1% lower lung cancer risk within five YSQ. Among all former smokers, 40.8% of lung cancers occurred after more than 15 YSQ. Conclusions Among heavy former smokers, lung cancer risk drops within five YSQ relative to continuing smokers, yet it remains more than threefold higher than never smokers after 25 YSQ. Four of ten lung cancers occurred in former smokers with more 15 YSQ, beyond the screening window of the current guideline.