Coping Styles Of Nurse Practitioners And The Effectiveness Of These Styles In Managing Stress

The purpose of this descriptive correlational study was to identify the coping styles used by nurse practitioners and determine the effectiveness of these styles in managing stress. The Roy Adaptation Model for Nursing was the theoretical framework used for this study. The research question which guided the data collection was what are the coping styles of nurse practitioners and how effective are these styles in managing the stress relative to functioning in the expanded role of nurse practitioner? The sample of convenience consisted of 72 nurse practitioners from Mississippi (30) and Tennessee (42) who completed and returned the survey questionnaire. Data were collected using the Jalowiec Coping Scale (JCS). A demographic questionnaire was used to identify variables such as age, sex, years of employment, and level of education. Major causes of work-related stress and other life stressors were determined by content analysis of two qualitative questions. Statistical analysis of the JCS included descriptive methods of quantitative responses. The most frequently used coping styles utilized by nurse practitioners were confrontive, optimistic, self-reliant, supportant, and emotive. The least used were evasive, fatalistic, and palliative. The most effective coping styles were confrontive, evasive, supportant, and palliative. The least effective were optimistic, fatalistic, self-reliant, and emotive. Additional findings revealed there was no significant correlation between the demographic variables, coping styles, and coping effectiveness. However, there was significant correlations between the coping use and the coping effectiveness scores of the nurse practitioners

Detection of IUPAC and IUPAC-like chemical names

Motivation: Chemical compounds like small signal molecules or other biological active chemical substances are an important entity class in life science publications and patents. Several representations and nomenclatures for chemicals like SMILES, InChI, IUPAC or trivial names exist. Only SMILES and InChI names allow a direct structure search, but in biomedical texts trivial names and Iupac like names are used more frequent. While trivial names can be found with a dictionary-based approach and in such a way mapped to their corresponding structures, it is not possible to enumerate all IUPAC names. In this work, we present a new machine learning approach based on conditional random fields (CRF) to find mentions of IUPAC and IUPAC-like names in scientific text as well as its evaluation and the conversion rate with available name-to-structure tools

Industrial Assessment Center Program

Over the five-year period (2002-2006) the Oklahoma State University Industrial Assessment Center (IAC) performed energy assessments for 106 different clients, writing 835 recommendations, for a total of $23,937,099 in potential estimated annual savings. IAC clients served consisted of small and medium-sized manufacturers ranging from food manufactures to foundries. The OSU IAC served clients in Oklahoma, Kansas, Missouri, Arkansas, and Texas. In addition to client service, student training and instruction was a major accomplishment. The OSU IAC employed (and trained) 12 baccalaureate-level students, 17 masters-level graduate students, and 7 doctoral-level graduate students. Most are practicing in the energy management area. Training was focused on both energy assessment and safety. Safety training was both center-based training as well as on-site training. Energy management related training was focused on classroom (for academic credit) work at both the undergraduate and graduate level. IEM 4923 (Energy and Water Management) was developed to serve both the IAC as well as non-IAC students. It was delivered once per year, with enrollments of typically 10 to 20 students. This course was required for IAC student employees, both undergraduate and graduate. This course was patterned after the AEE CEM (five-day) course for practicing professionals. IEM 4923 required each student to attend at least one on-site assessment and write at least one recommendation for their client’s report. Hence, a hands-on approach was practiced. Advance level courses were used to train graduate students. Two courses played major roles here: IEM 5923 (Advanced Energy and Water Management) and IEM 5943 (Hazardous Material and Waste). Graduate student participation in these courses helped the IAC to gain additional perspectives in on-site assessment and resulting recommendations. Numerous hands-on demonstration/training was conducted by directors and graduate students in order to gain proficiency in using the combustion analyzer, IR camera, logging equipment, light metering equipment, and other equipment. Instruction included usage and basic maintenance. While undergraduate students worked with the coursework and on-the-job training, graduate students were expected to do more. A typical MS student was required to complete a 3-hour independent study in some interesting facet of energy management under the supervision of a director. PhD students were expected to complete from three to six hours of independent study work in the energy management field, as well as center their dissertation research in the general area of energy/productivity/quality management. During the project period, two PhDs were completed, with several more near completion

Leveraging High Resolution Classifications and Random Forests for Hindcasting Decades of Mesic Ecosystem Dynamics in the Landsat Time Series

Mesic ecosystems are fundamental to conservation efforts in semi-arid systems, but are threatened by climate change and development. Newer earth observation datasets, including Sentinel-1 and −2, provide opportunities to monitor mesic ecosystems at meaningful spatial scales, but are insufficient for measuring decadal-scale changes. Conversely, the Landsat time series has decades of data, but images are spatially coarse relative to many of the mesic ecosystem areas that sustain dryland systems, resulting in classifications with mixed pixels inadequate for effective monitoring. We developed a workflow that uses 10-m classifications produced from fusion of the Sentinel-1 and −2 time series (2017–2020) to estimate sub-pixel proportions of Landsat time series observations (2004–2020). Using random forest regression models, we quantified water resource proportions (WRP) of surface water, mesic vegetation, and upland land covers within each 30-m Landsat pixel. We incorporated ancillary covariates to account for varying topographic conditions, land cover, and climate. Results indicate that our approach consistently estimates sub-pixel proportions of Landsat pixels more accurately compared to spectral mixture analysis (SMA). The WRP product for surface water had up to 8% less error than SMA as measured by Mean Absolute Error (MAE) and up to 17% less error as measured by Root Mean Squared Error (RMSE). For mesic vegetation, the WRP product outperformed SMA by up to 4% (MAE) and 7% (RMSE). Finally, we demonstrated the ability of our time series to characterize historical water resource availability at a case study site with a well documented restoration history by qualitatively examining the mesic vegetation dynamics time series to identify system responses to restoration efforts. Our approach allows us to hindcast observations of Sentinel products and measure water resource dynamics with greater precision over larger temporal scales. We envision these WRP data to be useful for measuring the impacts of conservation interventions, disturbance recovery, or land use changes that pre-date the Sentinel time series

Echoic Sensory Substitution Information in a Single Obstacle Circumvention Task.

Accurate motor control is required when walking around obstacles in order to avoid collisions. When vision is unavailable, sensory substitution can be used to improve locomotion through the environment. Tactile sensory substitution devices (SSDs) are electronic travel aids, some of which indicate the distance of an obstacle using the rate of vibration of a transducer on the skin. We investigated how accurately such an SSD guided navigation in an obstacle circumvention task. Using an SSD, 12 blindfolded participants navigated around a single flat 0.6 x 2 m obstacle. A 3-dimensional Vicon motion capture system was used to quantify various kinematic indices of human movement. Navigation performance under full vision was used as a baseline for comparison. The obstacle position was varied from trial to trial relative to the participant, being placed at two distances 25 cm to the left, right or directly ahead. Under SSD guidance, participants navigated without collision in 93% of trials. No collisions occurred under visual guidance. Buffer space (clearance between the obstacle and shoulder) was larger by a factor of 2.1 with SSD guidance than with visual guidance, movement times were longer by a factor of 9.4, and numbers of velocity corrections were larger by a factor of 5 (all p<0.05). Participants passed the obstacle on the side affording the most space in the majority of trials for both SSD and visual guidance conditions. The results are consistent with the idea that SSD information can be used to generate a protective envelope during locomotion in order to avoid collisions when navigating around obstacles, and to pass on the side of the obstacle affording the most space in the majority of trials.Vision and Eye Research Unit, Postgraduate Medical Institute at Anglia Ruskin University; Medical Research Council (Grant ID: G0701870)This is the final version of the article. It first appeared from the Public Library of Science via http://dx.doi.org/10.1371/journal.pone.016087

Integrated evolutionary computation neural network quality controller for automated systems

With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time

Time series modeling of system self-assessment of survival

Self-assessment of survival for a system, subsystem or component is implemented by assessing conditional performance reliability in real-time, which includes modeling and analysis of physical performance data. This paper proposes a time series analysis approach to system self-assessment (prediction) of survival. In the approach, physical performance data are modeled in a time series. The performance forecast is based on the model developed and is converted to the reliability of system survival. In contrast to a standard regression model, a time series model, using on-line data, is suitable for the real-time performance prediction. This paper illustrates an example of time series modeling and survival assessment, regarding an excessive tool edge wear failure mode for a twist drill operation

Auditory distance perception in humans: a review of cues, development, neuronal bases, and effects of sensory loss.

Auditory distance perception plays a major role in spatial awareness, enabling location of objects and avoidance of obstacles in the environment. However, it remains under-researched relative to studies of the directional aspect of sound localization. This review focuses on the following four aspects of auditory distance perception: cue processing, development, consequences of visual and auditory loss, and neurological bases. The several auditory distance cues vary in their effective ranges in peripersonal and extrapersonal space. The primary cues are sound level, reverberation, and frequency. Nonperceptual factors, including the importance of the auditory event to the listener, also can affect perceived distance. Basic internal representations of auditory distance emerge at approximately 6 months of age in humans. Although visual information plays an important role in calibrating auditory space, sensorimotor contingencies can be used for calibration when vision is unavailable. Blind individuals often manifest supranormal abilities to judge relative distance but show a deficit in absolute distance judgments. Following hearing loss, the use of auditory level as a distance cue remains robust, while the reverberation cue becomes less effective. Previous studies have not found evidence that hearing-aid processing affects perceived auditory distance. Studies investigating the brain areas involved in processing different acoustic distance cues are described. Finally, suggestions are given for further research on auditory distance perception, including broader investigation of how background noise and multiple sound sources affect perceived auditory distance for those with sensory loss.The research was supported by MRC grant G0701870 and the Vision and Eye Research Unit (VERU), Postgraduate Medical Institute at Anglia Ruskin University.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.3758/s13414-015-1015-

Bark beetle population dynamics in the Anthropocene: Challenges and solutions

Tree-killing bark beetles are the most economically important insects in conifer forests worldwide. However, despite N200 years of research, the drivers of population eruptions and crashes are still not fully understood and the existing knowledge is thus insufficient to face the challenges posed by the Anthropocene. We critically analyze potential biotic and abiotic drivers of population dynamics of an exemplary species, the European spruce bark beetle (ESBB) (Ips typographus) and present a multivariate approach that integrates the many drivers governing this bark beetle system. We call for hypothesis-driven, large-scale collaborative research efforts to improve our understanding of the population dynamics of this and other bark beetle pests. Our approach can serve as a blueprint for tackling other eruptive forest insects