LLukas22/scidocs huggingface dataset:
Leadership practices and staff nurses' intent to stay: a systematic review.

AIM
The aim of the present study was to describe the findings of a systematic review of the literature that examined the relationship between managers' leadership practices and staff nurses' intent to stay in their current position.


BACKGROUND
The nursing shortage demands that managers focus on the retention of staff nurses. Understanding the relationship between leadership practices and nurses' intent to stay is fundamental to retaining nurses in the workforce.


METHODS
Published English language articles on leadership practices and staff nurses' intent to stay were retrieved from computerized databases and a manual search. Data extraction and quality assessments were completed for the final 23 research articles.


RESULTS
Relational leadership practices influence staff nurses' intentions to remain in their current position.


CONCLUSION
This study supports a positive relationship between transformational leadership, supportive work environments and staff nurses' intentions to remain in their current positions. Incorporating relational leadership theory into management practices will influence nurse retention. Advancing current conceptual models will increase knowledge of intent to stay. Clarifying the distinction between the concepts intent to stay and intent to leave is needed to establish a clear theoretical foundation for further intent to stay research.


IMPLICATIONS FOR NURSE MANAGERS
Nurse managers and leaders who practice relational leadership and ensure quality workplace environments are more likely to retain their staff. The findings of the present study support the claim that leadership practices influence staff nurse retention and builds on intent to stay knowledge.
Wireless pulmonary artery pressure monitoring guides management to reduce decompensation in heart failure with preserved ejection fraction.

BACKGROUND
No treatment strategies have been demonstrated to be beneficial for the population for patients with heart failure (HF) and preserved ejection fraction (EF).


METHODS AND RESULTS
The CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III Heart Failure Patients (CHAMPION) trial was a prospective, single-blinded, randomized controlled clinical trial testing the hypothesis that hemodynamically guided HF management decreases decompensation leading to hospitalization. Of the 550 patients enrolled in the study, 119 had left ventricular EF ≥40% (average, 50.6%), 430 patients had low left ventricular EF (<40%; average, 23.3%), and 1 patient had no documented left ventricular EF. A microelectromechanical system pressure sensor was permanently implanted in all participants during right heart catheterization. After implant, subjects were randomly assigned in single-blind fashion to a treatment group in whom daily uploaded pressures were used in a treatment strategy for HF management or to a control group in whom standard HF management included weight-monitoring, and pressures were uploaded but not available for investigator use. The primary efficacy end point of HF hospitalization rate >6 months for preserved EF patients was 46% lower in the treatment group compared with control (incidence rate ratio, 0.54; 95% confidence interval, 0.38-0.70; P<0.0001). After an average of 17.6 months of blinded follow-up, the hospitalization rate was 50% lower (incidence rate ratio, 0.50; 95% confidence interval, 0.35-0.70; P<0.0001). In response to pulmonary artery pressure information, more changes in diuretic and vasodilator therapies were made in the treatment group.


CONCLUSIONS
Hemodynamically guided management of patients with HF with preserved EF reduced decompensation leading to hospitalization compared with standard HF management strategies.


CLINICAL TRIAL REGISTRATION URL
http://www.clinicaltrials.gov. Unique identifier: NCT00531661.
A Comparison of Logistic Regression, Classification and Regression Tree, and Neural Networks Models in Predicting Violent Re-Offending

Previous studies that have compared logistic regression (LR), classification and regression tree (CART), and neural networks (NNs) models for their predictive validity have shown inconsistent results in demonstrating superiority of any one model. The three models were tested in a prospective sample of 1225 UK male prisoners followed up for a mean of 3.31 years after release. Items in a widely-used risk assessment instrument (the Historical, Clinical, Risk Management-20, or HCR-20) were used as predictors and violent reconvictions as outcome. Multi-validation procedure was used to reduce sampling error in reporting the predictive accuracy. The low base rate was controlled by using different measures in the three models to minimize prediction error and achieve a more balanced classification. Overall accuracy of the three models varied between 0.59 and 0.67, with an overall AUC range of 0.65–0.72. Although the performance of NNs was slightly better than that of LR and CART models, it did not demonstrate a significant improvement.
Influence of environment, disturbance, and ownership on forest vegetation of coastal Oregon.

Information about how vegetation composition and structure vary quantitatively and spatially with physical environment, disturbance history, and land ownership is fundamental to regional conservation planning. However, current knowledge about patterns of vegetation variability across large regions that is spatially explicit (i.e., mapped) tends to be general and qualitative. We used spatial predictions from gradient models to examine the influence of environment, disturbance, and ownership on patterns of forest vegetation biodiversity across a large forested region, the 3-million-ha Oregon Coast Range (USA). Gradients in tree species composition were strongly associated with environment, especially climate, and insensitive to disturbance, probably because many dominant tree species are long-lived and persist throughout forest succession. In contrast, forest structure was strongly correlated with disturbance and only weakly with environmental gradients. Although forest structure differed among ownerships, differences were blurred by the presence of legacy trees that originated prior to current forest management regimes. Our multi-ownership perspective revealed biodiversity concerns and benefits not readily visible in single-ownership analyses, and all ownerships contributed to regional biodiversity values. Federal lands provided most of the late-successional and old-growth forest. State lands contained a range of forest ages and structures, including diverse young forest, abundant legacy dead wood, and much of the high-elevation true fir forest. Nonindustrial private lands provided diverse young forest and the greatest abundance of hardwood trees, including almost all of the foothill oak woodlands. Forest industry lands encompassed much early-successional forest, most of the mixed hardwood-conifer forest, and large amounts of legacy down wood. The detailed tree- and species-level data in the maps revealed regional trends that would be masked in traditional coarse-filter assessment. Although abundant, most early-successional forests originated after timber harvest and lacked legacy live and dead trees important as habitat and for other ecological functions. Many large-conifer forests that might be classified as old growth using a generalized forest cover map lacked structural features of old growth such as multilayered canopies or dead wood. Our findings suggest that regional conservation planning include all ownerships and land allocations, as well as fine-scale elements of vegetation composition and structure.
Epidemiology of falls in residential aged care: analysis of more than 70,000 falls from residents of bavarian nursing homes.

OBJECTIVE
Falls and fall-related injuries are leading problems in residential aged care facilities. The objective of this study was to provide descriptive data about falls in nursing homes.


DESIGN/SETTING/PARTICIPANTS
Prospective recording of all falls over 1 year covering all residents from 528 nursing homes in Bavaria, Germany.


MEASUREMENTS
Falls were reported on a standardized form that included a facility identification code, date, time of the day, sex, age, degree of care need, location of the fall, and activity leading to the fall. Data detailing homes' bed capacities and occupancy levels were used to estimate total person-years under exposure and to calculate fall rates. All analyses were stratified by residents' degree of care need.


RESULTS
More than 70,000 falls were recorded during 42,843 person-years. The fall rate was higher in men than in women (2.18 and 1.49 falls per person-year, respectively). Fall risk differed by degree of care need with lower fall risks both in the least and highest care categories. About 75% of all falls occurred in the residents' rooms or in the bathrooms and only 22% were reported within the common areas. Transfers and walking were responsible for 41% and 36% of all falls respectively. Fall risk varied during the day. Most falls were observed between 10 am and midday and between 2 pm and 8 pm.


CONCLUSION
The differing fall risk patterns in specific subgroups may help to target preventive measures.
Emotional controller (BELBIC) for electric drives — A review

Artificial intelligence (AI) and Biologically-inspired techniques, particularly the neural networks, are recently having significant impact on power electronics and electric drives. Neural networks have created a new and advancing frontier in power electronics, which is already a complex and multidisciplinary technology that is going through dynamic evolution in the recent years. But recently, a new type of the intelligent techniques, for control and decision making processes, was introduced that is based on the emotion processing mechanism in brain, and is essentially an action selection, which is based on sensory inputs and emotional cues. This intelligent control is inspired by the limbic system of mammalian brain. The proposed controller is called brain emotional learning based intelligent controller (BELBIC). This paper gives a comprehensive introduction and perspective of its applications in the intelligent control for electric drives area. The principal topologies of neural networks that are currently most relevant for applications in power electronics have been reviewed including the detailed description of their properties. Both feedforward and feedback or recurrent architectures have been covered in the description. The application examples that are discussed in this paper include different electric drives control as: Direct Current Motors (DC), Alternative Current Motors (AC) and Special Motors (SRM). In addition, almost all of the selected applications in the literature are included in the references. In the experimental and simulation works, novel and simple implementations of the drives system were achieved by using the intelligent controller, which control the motor speed accurately in different operating points. This emotional intelligent controller has simple structure with high auto learning feature that does not require any motor parameters, for self performance. The proposed emotional controller has been experimentally implemented in some of the laboratory electric drives, and shows excellent promise for industrial scale utilization.
Deriving physical connectivity from neuronal morphology

 A model is presented that allows prediction of the probability for the formation of appositions between the axons and dendrites of any two neurons based only on their morphological statistics and relative separation. Statistics of axonal and dendritic morphologies of single neurons are obtained from 3D reconstructions of biocytin-filled cells, and a statistical representation of the same cell type is obtained by averaging across neurons according to the model. A simple mathematical formulation is applied to the axonal and dendritic statistical representations to yield the probability for close appositions. The model is validated by a mathematical proof and by comparison of predicted appositions made by layer 5 pyramidal neurons in the rat somatosensory cortex with real anatomical data. The model could be useful for studying microcircuit connectivity and for designing artificial neural networks.
The impact of social and conventional media on firm equity value: A sentiment analysis approach

Available online 30 December 2012
Control of heave-induced pressure fluctuations in managed pressure drilling

Managed pressure drilling is an advanced pressure control method which is intended to meet increasingly high demands in drilling operations in the oil and gas industry. In this method, the circulating drilling fluid, which takes cuttings out of the well, is released at the surface through a controlled choke. This choke is used for active control of the fluid pressure in the well. The corresponding automatic control system keeps the pressure at the bottom of the well at a specified set-point despite various disturbances. One of such disturbances, vertical motion of the drill string, causes severe pressure fluctuations which need to be actively attenuated. In this paper we present two different disturbance rejection strategies based on discretized partial differential equations for the well hydraulic system. The performance of the controllers is shown through simulations both under idealized conditions as well as by simulations on a high fidelity drilling simulator.
First-in-Human Phase I Study of GSK2126458, an Oral Pan-Class I Phosphatidylinositol-3-Kinase Inhibitor, in Patients with Advanced Solid Tumor Malignancies.

PURPOSE
GSK2126458 (GSK458) is a potent inhibitor of PI3K (α, β, γ, and δ), with preclinical studies demonstrating broad antitumor activity. We performed a first-in-human phase I study in patients with advanced solid tumors.


MATERIALS AND METHODS
Patients received oral GSK458 once or twice daily in a dose-escalation design to define the maximum tolerated dose (MTD). Expansion cohorts evaluated pharmacodynamics, pharmacokinetics, and clinical activity in histologically and molecularly defined cohorts.


RESULTS
One hundred and seventy patients received doses ranging from 0.1 to 3 mg once or twice daily. Dose-limiting toxicities (grade 3 diarrhea,n= 4; fatigue and rash,n= 1) occurred in 5 patients (n= 3 at 3 mg/day). The MTD was 2.5 mg/day (MTD with twice daily dosing undefined). The most common grade ≥3 treatment-related adverse events included diarrhea (8%) and skin rash (5%). Pharmacokinetic analyses demonstrated increased duration of drug exposure above target level with twice daily dosing. Fasting insulin and glucose levels increased with dose and exposure of GSK458. Durable objective responses (ORs) were observed across multiple tumor types (sarcoma, kidney, breast, endometrial, oropharyngeal, and bladder cancer). Responses were not associated withPIK3CAmutations (OR rate: 5% wild-type vs. 6% mutant).


CONCLUSIONS
Although the MTD of GSK458 was 2.5 mg once daily, twice-daily dosing may increase duration of target inhibition. Fasting insulin and glucose levels served as pharmacodynamic markers of drug exposure. Select patients achieved durable responses; however,PIK3CAmutations were neither necessary nor predictive of response. Combination treatment strategies and novel biomarkers may be needed to optimally target PI3K.
Geodesic K-means clustering

We introduce a class of geodesic distances and extend the K-means clustering algorithm to employ this distance metric. Empirically, we demonstrate that our geodesic K-means algorithm exhibits several desirable characteristics missing in the classical K-means. These include adjusting to varying densities of clusters, high levels of resistance to outliers, and handling clusters that are not linearly separable. Furthermore our comparative experiments show that geodesic K-means comes very close to competing with state-of-the-art algorithms such as spectral and hierarchical clustering.
Reduction in hospital admissions for pneumonia in non-institutionalised elderly people as a result of influenza vaccination: a case-control study in Spain.

OBJECTIVE
To estimate the effectiveness of influenza vaccine in preventing hospital admission for pneumonia in non-institutionalised elderly people.


DESIGN
This was a case-control study.


SETTING
All three public hospitals in the Castellón area of Spain.


PARTICIPANTS
Cases were people aged 65 or more not living in an institution who were admitted to hospital for pneumonia between November 15, 1994 and March 31, 1995. Each case was matched with two sex matched control subjects aged 65 years or older admitted to hospital in the same week for acute abdominal surgical conditions or trauma. The sampling of incident cases was consecutive. Eighty three cases and 166 controls were identified and included in the study.


MEASUREMENTS
Trained interviewers completed a questionnaire for each subject on the vaccination status, smoking habits, previous diseases, health care use, social contacts, family background, the vaccination status of the family carer, home characteristics, and socioeconomic status.


RESULTS
The adjusted odds ratio of the influenza vaccination preventing admission to hospital for pneumonia was 0.21 (95% confidence interval 0.09, 0.55). The variables which best explained the risk of being a case were age, intensity of social contacts, health care use, previous diseases, and the existence of a vaccinated family carer.


CONCLUSIONS
Influenza vaccination reduced significantly hospital admissions for pneumonia in non-institutionalised elderly people.
Depressive symptoms in PD correlate with higher 5-HTT binding in raphe and limbic structures.

BACKGROUND
Depression associated with Parkinson disease (PD) has a different symptom profile to endogenous depression. The etiology of depression in PD remains uncertain though abnormal serotonergic neurotransmission could play a role.


OBJECTIVE
To assess with PET serotonergic function via in vivo serotonin transporter (5-HTT) availability in antidepressant-naive patients with PD.


METHODS
Thirty-four patients with PD and 10 healthy matched control subjects had a clinical battery of tests including the patient-report Beck Depression Inventory-II (BDI-II), the clinician-report Hamilton Rating Scale for Depression (HRSD), and the structured clinical interview for DSM-IV Axis I Disorders (SCID-I). They underwent ¹¹C-DASB PET, a selective in vivo marker of 5-HTT binding in humans.


RESULTS
BDI-II scores correlated with HRSD scores. Ten of 34 patients with PD (29.4%) had BDI-II and HRSD scores above the discriminative cutoff for PD depression though only half of these patients could be classed on SCID-I criteria as having an anxiety/mood disorder. Patients with PD with the highest scores for depression symptoms showed significantly raised ¹¹C-DASB binding in amygdala, hypothalamus, caudal raphe nuclei, and posterior cingulate cortex compared to low score cases, while ¹¹C-DASB binding values in other regions were similarly decreased in depressed and nondepressed patients with PD compared to healthy controls.


CONCLUSION
Depressive symptoms in antidepressant-naive patients with PD correlate with relatively higher 5-HTT binding in raphe nuclei and limbic structures possibly reflecting lower extracellular serotonin levels. Our data are compatible with a key role of abnormal serotonergic neurotransmission contributing to the pathophysiology of PD depression and justify the use of agents acting on 5-HTT.
The lithographic lens: its history and evolution

The history of Nikon’s projection lens development for optical microlithography started with the first “Ultra MicroNikkor” in 1962, which was used for making photo-masks. Nikon’s first wafer stepper “NSR-1010G” was developed with a g-line projection lens in 1980. Since then, many kinds of projection lenses have been developed for each generation of stepper or scanner. In addition to increasing numerical aperture (NA) and field size, there have been many technical transitions for the projection lens, such as shortening the wavelength, controlling Zernike aberrations with phase measurement interferometry (PMI) for low k1 lithography, using aspherical lenses, applying kinematic optomechanical mounts, and utilizing free asphere re-polishing steps in the lens manufacturing process. The most recent advancement in projection lens technology is liquid immersion and polarization control for high NA imaging. NA now exceeds 1.0, which is the theoretical limit for dry (in air) imaging. At each transition, the amount of information that goes through the projection lens has been increased. In this paper, the history of the microlithographic lens is reviewed from several different points of view, such as specification, optical design, lens manufacturing, etc. In addition, future options of the projection lens are discussed briefly.
Teachers' perceptions of students' mathematics proficiency may exacerbate early gender gaps in achievement.

A recent wave of research suggests that teachers overrate the performance of girls relative to boys and hold more positive attitudes toward girls' mathematics abilities. However, these prior estimates of teachers' supposed female bias are potentially misleading because these estimates (and teachers themselves) confound achievement with teachers' perceptions of behavior and effort. Using data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999 (ECLS-K), Study 1 demonstrates that teachers actually rate boys' mathematics proficiency higher than that of girls when conditioning on both teachers' ratings of behavior and approaches to learning as well as past and current test scores. In other words, on average girls are only perceived to be as mathematically competent as similarly achieving boys when the girls are also seen as working harder, behaving better, and being more eager to learn. Study 2 uses mediation analysis with an instrumental-variables approach, as well as a matching strategy, to explore the extent to which this conditional underrating of girls may explain the widening gender gap in mathematics in early elementary school. We find robust evidence suggesting that underrating girls' mathematics proficiency accounts for a substantial portion of the development of the mathematics achievement gap between similarly performing and behaving boys and girls in the early grades.
Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition

A key challenge in fine-grained recognition is how to find and represent discriminative local regions. Recent attention models are capable of learning discriminative region localizers only from category labels with reinforcement learning. However, not utilizing any explicit part information, they are not able to accurately find multiple distinctive regions. In this work, we introduce an attribute-guided attention localization scheme where the local region localizers are learned under the guidance of part attribute descriptions. By designing a novel reward strategy, we are able to learn to locate regions that are spatially and semantically distinctive with reinforcement learning algorithm. The attribute labeling requirement of the scheme is more amenable than the accurate part location annotation required by traditional part-based fine-grained recognition methods. Experimental results on the CUB-200-2011 dataset [1] demonstrate the superiority of the proposed scheme on both fine-grained recognition and attribute recognition.