Miracle-dz/UniFAR-FTUs huggingface dataset:
Burnout in Nurses Working With Youth With Chronic Pain: A Pilot Intervention

Objective Nurse burnout is a significant issue, with repercussions for the nurse, patients, and health-care system. Our prior mixed-methods analyses helped inform a model of burnout in nurses working with youth with chronic pain. Our aims were to (a) detail the development of an intervention to decrease burnout; (b) evaluate the intervention's feasibility and acceptability; and (c) provide preliminary outcomes on the intervention. Method In total, 33 nurses working on a pediatric inpatient care unit that admits patients with chronic pain conditions participated in the single-session 90-min groups (eight to nine nurses per group). The intervention consisted of four modules including (1) helping patients view pain as multifaceted and shift attention to functioning; (2) teaching problem-solving and reflective listening skills; (3) highlighting positives about patients when venting with coworkers; and (4) improving nurses own self-care practices. Measures provided assessment of feasibility, acceptability, and effectiveness at baseline and 3 months postintervention in a single group, repeated measures design. Results Data support the feasibility and acceptability of the intervention. Pilot outcome results demonstrated improvements in the target behaviors of education on psychosocial influences, self-care, and venting to coworkers as well as self-compassion, general health, and burnout. There were no changes in pain beliefs or the target behaviors of focus on functioning, empathizing with patient, or highlighting positives. Conclusions Our single-session tailored group treatment was feasible and acceptable, and pilot data suggest that it is beneficial, but a more comprehensive approach is encouraged to reduce burnout that might be related to multiple individual, unit, and system factors.
Cigarette smoking increases copy number alterations in nonsmall-cell lung cancer

Cigarette smoking has been a well-established risk factor of lung cancer for decades. How smoking contributes to tumorigenesis in the lung remains not fully understood. Here we report the results of a genome-wide study of DNA copy number and smoking pack-years in a large collection of nonsmall-cell lung cancer (NSCLC) tumors. Genome-wide analyses of DNA copy number and pack-years of cigarette smoking were performed on 264 NSCLC tumors, which were divided into discovery and validation sets. The copy number-smoking associations were investigated in three scales: whole-genome, chromosome/arm, and focal regions. We found that heavy cigarette smokers (>60 pack-years) have significantly more copy number gains than non- or light smokers (≤60 pack-years) (P = 2.46 × 10−4), especially in 8q and 12q. Copy number losses tend to occur away from genes in non/light smokers (P = 5.15 × 10−5) but not in heavy smokers (P = 0.52). Focal copy number analyses showed that there are strong associations of copy number and cigarette smoking pack-years in 12q23 (P = 9.69 × 10−10) where IGF1 (insulin-like growth factor 1) is located. All of the above analyses were tested in the discovery set and confirmed in the validation set. DNA double-strand break assays using human bronchial epithelial cell lines treated with cigarette smoke condensate were also performed, and indicated that cigarette smoke condensate leads to genome instability in human bronchial epithelial cells. We conclude that cigarette smoking leads to more copy number alterations, which may be mediated by the genome instability.
Homeless women and hazardous drinking: screening results in a primary health care setting.

BACKGROUND AND OBJECTIVES Screening for alcohol use in primary care is underutilized, especially for women. The current study implemented systematic women's alcohol use screening in a health care for the homeless primary care program. METHODS All women (n=541) seeking care over 12 months were screened. RESULTS Of the 541 screening forms returned, 80 women refused to answer the alcohol use questions. Of 461 completed screens, over 40% reported no alcohol use, while 43.8% reported hazardous drinking. Hazardous drinking was significantly associated with younger age, African American race, and living on the street or in a shelter. DISCUSSION AND CONCLUSIONS High rates of drinking were identified among women in different housing situations and use of systematic screening was beneficial to providers. SCIENTIFIC SIGNIFICANCE AND FUTURE DIRECTIONS Health care settings are important sites to identify hazardous drinking as well as alcohol disorders among women with unstable housing histories. The growing integration of behavioral health care into primary care, and the medical home concept, both provide opportunities for brief interventions for at-risk drinkers, as well as treatment options for those with alcohol use disorders that may be particularly appealing to women. Findings support further investigation of the relationship of housing stability to drinking, and suggest African American women may need special attention.
Complexity and compositionality in fluid intelligence

Significance Tests of fluid intelligence are important for their broad association with effective cognition and lifetime achievement. An enduring question concerns basic cognitive mechanisms measured in such tests. Fluid intelligence is usually measured with complex problem-solving tasks, and in such tests, we suggest that the core limit is one of cognitive segmentation, or managing complex activities by selective attention to separate, simpler parts. Here we modify traditional fluid intelligence problems to test this hypothesis and to minimize the roles of working memory capacity and mental speed. The findings suggest a cognitive interpretation for what it is that fluid intelligence tests measure, based on dynamic attentional control functions of frontal and parietal cortex. Compositionality, or the ability to build complex cognitive structures from simple parts, is fundamental to the power of the human mind. Here we relate this principle to the psychometric concept of fluid intelligence, traditionally measured with tests of complex reasoning. Following the principle of compositionality, we propose that the critical function in fluid intelligence is splitting a complex whole into simple, separately attended parts. To test this proposal, we modify traditional matrix reasoning problems to minimize requirements on information integration, working memory, and processing speed, creating problems that are trivial once effectively divided into parts. Performance remains poor in participants with low fluid intelligence, but is radically improved by problem layout that aids cognitive segmentation. In line with the principle of compositionality, we suggest that effective cognitive segmentation is important in all organized behavior, explaining the broad role of fluid intelligence in successful cognition.
The risks and external effects of diabetic foot ulcer on diabetic patients: A hospital‐based survey in Wuhan area, China

Diabetic foot ulcer (DFU) is a common complication observed in diabetic patients and affects diabetic patients in multiple ways. Severe DFU even leads to amputation in many cases. Early detection and intervention of DFU in diabetic patients can significantly relieve the pain caused by the ulcer and also keep patients from losing limbs in severe cases. In this study, the risks of diabetic patients getting DFU were estimated through a hospital‐based survey. This survey collected information from hospitalized diabetic patients in Wuhan City, Hubei Province, China, using a questionnaire. This investigation includes studies from two stages with 502 diabetic patients from 20 hospitals in Wuhan City. The results suggested that patients with a long history of diabetes are often associated with a high risk of DFU (χ2 = 11.428, p = 0.0007), smoking (χ2 = 8.386, p = 0.0007), diabetic complications (χ2 = 13.484, p < 0.0001), and especially patients with diabetic foot complications (χ2 = 57.6621, p < 0.0001). Foot lesions appeared to be important attributors to DFU since our data demonstrated close correlations between DFU and patients with calluses/corns (χ2 = 4.584, p = 0.0323), tinea pedis (χ2 = 4.030, p = 0.0447), and cracked skin (χ2 = 8.712, p = 0.0032). Only a small number of patients seek for the assistance from specialists, such as trimming toenails (3.4%), removing corn or calluses (1.4%) or treating wounds (11.78%), when they are suffering from foot problems. The findings of this study can potentially be utilized to develop an early DFU diagnostic method in diabetic patients and can provide objective evidence for suggesting that patients who are suffering from foot problems should seek professional help.
Surgical data science: the new knowledge domain

Abstract Healthcare in general, and surgery/interventional care in particular, is evolving through rapid advances in technology and increasing complexity of care, with the goal of maximizing the quality and value of care. Whereas innovations in diagnostic and therapeutic technologies have driven past improvements in the quality of surgical care, future transformation in care will be enabled by data. Conventional methodologies, such as registry studies, are limited in their scope for discovery and research, extent and complexity of data, breadth of analytical techniques, and translation or integration of research findings into patient care. We foresee the emergence of surgical/interventional data science (SDS) as a key element to addressing these limitations and creating a sustainable path toward evidence-based improvement of interventional healthcare pathways. SDS will create tools to measure, model, and quantify the pathways or processes within the context of patient health states or outcomes and use information gained to inform healthcare decisions, guidelines, best practices, policy, and training, thereby improving the safety and quality of healthcare and its value. Data are pervasive throughout the surgical care pathway; thus, SDS can impact various aspects of care, including prevention, diagnosis, intervention, or postoperative recovery. The existing literature already provides preliminary results, suggesting how a data science approach to surgical decision-making could more accurately predict severe complications using complex data from preoperative, intraoperative, and postoperative contexts, how it could support intraoperative decision-making using both existing knowledge and continuous data streams throughout the surgical care pathway, and how it could enable effective collaboration between human care providers and intelligent technologies. In addition, SDS is poised to play a central role in surgical education, for example, through objective assessments, automated virtual coaching, and robot-assisted active learning of surgical skill. However, the potential for transforming surgical care and training through SDS may only be realized through a cultural shift that not only institutionalizes technology to seamlessly capture data but also assimilates individuals with expertise in data science into clinical research teams. Furthermore, collaboration with industry partners from the inception of the discovery process promotes optimal design of data products as well as their efficient translation and commercialization. As surgery continues to evolve through advances in technology that enhance delivery of care, SDS represents a new knowledge domain to engineer surgical care of the future.
A non-invasive approach to investigation of ventricular blood pressure using cardiac sound features

Heart sounds (HSs) are produced by the interaction of the heart valves, great vessels, and heart wall with blood flow. Previous researchers have demonstrated that blood pressure can be predicted by exploring the features of cardiac sounds. These features include the amplitude of the HSs, the ratio of the amplitude, the systolic time interval, and the spectrum of the HSs. A single feature or combinations of several features have been used for prediction of blood pressure with moderate accuracy. Experiments were conducted with three beagles under various levels of blood pressure induced by different doses of epinephrine. The HSs, blood pressure in the left ventricle and electrocardiograph signals were simultaneously recorded. A total of 31 records (18 262 cardiac beats) were collected. In this paper, 91 features in various domains are extracted and their linear correlations with the measured blood pressures are examined. These features are divided into four groups and applied individually at the input of a neural network to predict the left ventricular blood pressure (LVBP). The analysis shows that non-spectral features can track changes of the LVBP with lower standard deviation. Consequently, the non-spectral feature set gives the best prediction accuracy. The average correlation coefficient between the measured and the predicted blood pressure is 0.92 and the mean absolute error is 6.86 mmHg, even when the systolic blood pressure varies in the large range from 90 mmHg to 282 mmHg. Hence, systolic blood pressure can be accurately predicted even when using fewer HS features. This technique can be used as an alternative to real-time blood pressure monitoring and it has promising applications in home health care environments.
On the existence of fuzzy solutions for partial hyperbolic functional differential equations

AbstractIn this paper, we consider the boundary valued problems for fuzzy partial hyperbolic functional differential equations with local and integral boundary conditions. A new weighted metric is used to investigate the existence and uniqueness of fuzzy solutions for these problems in a complete fuzzy metric space. Our results are demonstrated in some numerical examples in which we use the same strategy as Buckley-Feuring to build fuzzy solutions from fuzzifying the deterministic solutions. Then by using the continuity of the Zadeh’s extension principle combining with numerical simulations for α−cuts of fuzzy solutions, we give some representations of the surfaces of fuzzy solutions.
Incidence and Treatment of Developmental Hip Dysplasia in Mongolia: A Prospective Cohort Study

Background In Mongolia, adequate early diagnosis and treatment of developmental hip dysplasia (DDH) have been unavailable and its incidence was unknown. We determined the incidence of ultrasonographic DDH in newborns and established adequate procedures for diagnosis and treatment of DDH at the largest maternity hospital in Ulaanbaatar, Mongolia. Methodology/Principal Findings During one year (Sept 2010 – Aug 2011) we assessed the hips newborns using ultrasound and Graf’s classification of DDH. 8,356 newborns were screened; median age at screening was 1 day. We identified 14,873 Type 1 (89.0%), 1715 Type 2a (10.3%), 36 Type 2c (0.2%), 70 Type D (0.4%), 14 Type 3 (0.08%), and 4 Type 4 hips (0.02%). Children with Type 1 hips (normal) were discharged. Children with Type 2a hips (physiologically immature) received follow-up ultrasounds at monthly intervals. Children with Type 2c to 4 (DDH; deformed or misaligned hip joint) hips were treated with a Tubingen hip flexion splint and also followed up. The hip abnormalities resolved to mature hips in all children who were followed up. There was no evidence for severe treatment related complications. Conclusion/Significance This study suggests that the incidence of DDH in Mongolian neonates is comparable to that in neonates in Europe. Early ultrasound-based assessment and splinting treatment of DDH led to mature hips in all children followed up. Procedures are feasible and will be continued.
Role of Polymeric Additives in Formulation, Shelf-life and Bioefficacy of Liquid Inoculant of Pseudomonas fluorescens

In the present study liquid inoculant formulation of Pseudomonas fluorescens were developed with the use of polymeric additives to study the shelf-life and to evaluate the bioefficacy of Pseudomonas fluorescens. The polymeric additives were used in different combinations and the prepared liquid inoculant formulations of Pseudomonas fluorescens were assessed for their shelf-life at monthly intervals and were evaluated for their bioefficacy against the Fusarium (Fusarium oxysporum f.sp.lycopersici) wilt of Tomato under greenhouse conditions. Polymeric additives used were cell protectants viz., polyvinlypyrrolidone (PVP, 2%), polyethylene glycol (PEG, 1%), gum arabic (0.8%) and sodium alginate (0.1%); adjuvants viz., xanthan gum (0.3%) and carboxymethyl cellulose (CMC, 0.1%); surfactant used was Tween-20 (0.5%) and preservative was potassium sorbate (0.2%). LIF (Liquid inoculant formulation; T5) retained 1.76 X 10 10 CFU/ml upto 180 days of storage. Even the tomato seedlings treated with the LIF T5 showed best results in all the growth and yield parameters studied including the disease incidence in these plants. The formulated liquid inoculants were found to have enhanced shelflife and improved viability.
Experimental Research on the Performance of UHMWPE Fiber Reinforced Concrete Multiply Impacted by Bullets

Based on the engineering projection against multiple impacts, the test of anti-multiple impacts was carried out towards UHMWPE fiber reinforced concrete, in which five kinds of fiber volume fraction (0%, 0.3%, 0.5%, 0.7% 1.0%) were designed. The damage patterns were analyzed and the penetration depth was fitted by empirical formula. Excellent effect of UHMWPE fiber reinforced concrete for reducing the damage under multiple impacts was studied. Appropriate fiber volume fraction can effectively improve the anti-penetration performance of concrete. When the fiber volume fraction was between 0.3% and 0.5%, the improvement was the most remarkable.
Colistin-Resistant mcr-1-Positive Escherichia coli on Public Beaches, an Infectious Threat Emerging in Recreational Waters

ABSTRACT The emergence and rapid spread of colistin-resistant Escherichia coli carrying the mcr-1 gene have generated an urgent need to strengthen surveillance. We performed a meticulous investigation of strains of this sort, which resulted in the identification of international clones of E. coli carrying IncX4-plasmid-mediated mcr-1 and blaCTX-M genes in recreational waters of public urban beaches in cities with high tourist turnover, highlighting a new environmental reservoir.
In Vivo Optogenetic Control of Striatal and Thalamic Neurons in Non-Human Primates

Electrical and pharmacological stimulation methods are commonly used to study neuronal brain circuits in vivo, but are problematic, because electrical stimulation has limited specificity, while pharmacological activation has low temporal resolution. A recently developed alternative to these methods is the use of optogenetic techniques, based on the expression of light sensitive channel proteins in neurons. While optogenetics have been applied in in vitro preparations and in in vivo studies in rodents, their use to study brain function in nonhuman primates has been limited to the cerebral cortex. Here, we characterize the effects of channelrhodopsin-2 (ChR2) transfection in subcortical areas, i.e., the putamen, the external globus pallidus (GPe) and the ventrolateral thalamus (VL) of rhesus monkeys. Lentiviral vectors containing the ChR2 sequence under control of the elongation factor 1α promoter (pLenti-EF1α -hChR2(H134R)-eYFP-WPRE, titer 109 particles/ml) were deposited in GPe, putamen and VL. Four weeks later, a probe combining a conventional electrode and an optic fiber was introduced in the previously injected brain areas. We found light-evoked responses in 31.5% and 32.7% of all recorded neurons in the striatum and thalamus, respectively, but only in 2.5% of recorded GPe neurons. As expected, most responses were time-locked increases in firing, but decreases or mixed responses were also seen, presumably via ChR2-mediated activation of local inhibitory connections. Light and electron microscopic analyses revealed robust expression of ChR2 on the plasma membrane of cell somas, dendrites, spines and terminals in the striatum and VL. This study demonstrates that optogenetic experiments targeting the striatum and basal ganglia-related thalamic nuclei can be successfully achieved in monkeys. Our results indicate important differences of the type and magnitude of responses in each structure. Experimental conditions such as the vector used, the number and rate of injections, or the light stimulation conditions have to be optimized for each structure studied.
A two-phase escape analysis for parallel Java programs

Thread escape analysis conservatively determines which objects may be accessed in more than one thread. Thread escape analysis is useful for a variety of purposes — finding races in multi-threaded programs, removing useless synchronization, allocating data to thread-local heaps, and compiling to target more strict consistency models. Thread escape analyses are often interprocedural, and interprocedural analyses are generally either too slow to perform at runtime in dynamic systems, or trade-off significant amounts of precision for speed. This paper describes a two-phase offline/online interprocedural and inter-thread escape analysis that is faster and more accurate, on average, than previously published analyses. By performing an offline pre-analysis followed by a dynamic online analysis that integrates offline results with dynamic information, significant improvements in performance and accuracy are achieved. For compiling Java programs under a sequentially consistent memory model, our approach enables application executions that are, on average, 1.5 times faster than those using the previous fastest online algorithm, with only 80% of the online compilation time.
An Automated Script to Acquire Gas Uptake Data from Molecular Simulation of Metal Organic Frameworks

Attention worldwide has been placed towards reducing the global carbon footprint. To this end the scientific community has been involved in improving many of the available methods of carbon capture and storage (CCS). CCS involves scrubbing flue gases of greenhouse gases and safely storing them deep underground. MOFs, a family of functionally tunable three dimensional nanoporous frameworks, have been shown to adsorb gases with great selectivity and capacity. Investigating these frameworks using computational simulations, although faster than in-lab synthetic methods, involves a tedious and meticulous input preparation process which is subject to human error. This thesis presents Dave's Occupancy Automation Package (DOAP), a software which provides a means to automatically determine the gas uptake of many three dimensional frameworks. By providing atomic coordinates for a unit simulation cell, the software acts to performs the necessary calculations to construct and execute a Grand Canonical Monte Carlo simulation, determining the gas uptake in a metal organic framework. Additionally an analysis of different convergence assessment tests for describing the end point of the GCMC simulation is presented.
Scoring Models for Insurance Risk Sharing Pool Opimization

We introduce a flexible scoring model that can be used by property and casualty insurers that have access to a risk-sharing pool to better select the insureds to transfer to the pool. The model discriminates between insureds whose transfer is likely to be profitable under the pool regulations against those paying a fair premium. This model makes use of feature selection methods to automatically discover the most relevant model inputs, yet is robust to overfitting due to the use of a rank averaging technique. By analogy to the knapsack problem, we show what should be the most suitable sorting criterion depending on the pool regulations. We illustrate the performance of the approach by testing against the historical data of a mid-sized Canadian insurer.