Over the last decade, there has been a renewed interest in oral health workforce planning. The purpose of this review is to examine oral health workforce planning models on supply, demand and needs, mainly in respect to their data sources, modelling technique and use of skill mix. A search was carried out on PubMed, Web of Science, and Google Scholar databases for published scientific articles on oral health workforce planning models between 2010 to 2020. No restrictions were placed on the type of modelling philosophy, and all studies including supply, demand or needs based models were included. Rapid review methods guided the review process. Twenty-three studies from 15 different countries were included in the review. A majority were from high income countries (n=17). Dentists were the sole oral health workforce group modelled in 13 studies; only five studied included skill mix (allied dental personnel) considerations. The most common application of modelling was a workforce to population ratio or a needs-based demand weighted variant. Nearly all studies presented weaknesses in modelling process due to the limitations in data sources and/or non availability of necessary data to inform oral health workforce planning. Skill mix considerations in planning models were also limited to horizontal integration within oral health professionals. Planning for the future oral health workforce is heavily reliant on quality data being available for supply, demand and needs models. Integrated methodologies that expand skill mix considerations and account for uncertainty are essential for future planning exercises.

The frequency of earthquakes in South Korea is increasing. This study aimed to examine and identify the factors influencing the degree of disaster-incident-related shock among Korean nursing students with the disaster experience. The study sample consisted of 153 nursing students who have been living around Phohang-si in Gyeongsang-do, South Korea, and who having the experience of disaster-incident-related shock. Measures were Impact of Event Scale, Perceived health status scale, Psychological Well-Being Scale, and Coping Strategy Indicator in Korean version. The data collection period was from October to December, 2018. The factor that was found to have the most influence on disaster-incident-related shock among Korean nursing students was the perceived health status (β = 0.48), followed by gender (β = -0.28), coping skill (β = 0.18), psychological well-being (β = 0.14), need for disaster education (β = 0.12), and major satisfaction (β = -0.12). This study provides preliminary evidence that perceived health status is a major and primary predictor of disaster-incident-related shock among Korean nursing students, next followed by coping skill, and psychological well-being. The findings can be reflected in the pertinent curriculum by actively considering these influence factors in designing nursing education interventions for disaster-incident-related shock in the Korean nursing students.

The last few decades have witnessed a surge of interest in adventure sports, and an emerging research focus on these activities. However, recent conceptual analyses and scientific reviews have highlighted a major, fundamental question that remains unresolved: what constitutes an adventure sport (and are they ‘sports’ at all)? Despite several proposals for definitions, the field still seems to lack a shared conceptualization. This deficit may be a serious limitation for research and practice, restricting the development of a more nuanced theoretical explanation of participation and prac-tical implications within and across adventure sports. In this article we address another crucial question, how can adventure sports be better understood for research and practice? We briefly summarize previous definitions to address evident confusion and lack of conceptual clarity in the discourse. Alternatively, we propose how an ecological perspective on human behaviors, as in-teractions with the environment, may provide an appropriate conceptualization to guide and enhance future research and practice, using examples from activities such as freeride skiing / snowboarding, white-water kayaking, climbing, mountaineering and the fields of sport science, psychology and avalanche research and education. We draw on ecological dynamics as a trans-disciplinary approach to discuss how this holistic framework presents a more detailed, nuanced, and precise understanding of adventure sports.

Improvements that can be attained in seasonal climate predictions in various parts of Africa using the multimodel supersensemble scheme are presented in this study. The synthetic superensemble (SSE) used follows the approach originally developed at Florida State University (FSU). The technique takes more advantage of the skill in the climate forecast data sets from atmosphere-ocean general circulation models running at many centres worldwide including the WMO global producing centers (GPCs). The module used in this work drew data sets from the Four versions of FSU coupled model system, seven models from the DEMETER project which is the forerun to the current European Ensembles Forecast System, the NCAR Model, and the Predictive Ocean Atmosphere Model for Australia (POAMA), all making a set of 13 individual models. An archive consisting of monthly simulations of precipitation was available over all the 5 regions of Africa, namely Eastern, Central, Northern, Southern, and Western Africa. The results showed that the SSE forecast for precipitation carries a higher skill compared to each of the member models and the ensemble mean. Relative to the ensemble mean (EM), the SSE provides an improvement of 18% in simulation of season cycle of precipitation climatology. In Eastern Africa, during December-February season, a north-south gradient of precipitation prevails between Tropical East Africa and the sector of the region towards Southern Africa. This regional scale climate pattern is a direct influence of the Intertropical Convergence Zone (ITZC) across the African continent during this time of the year. The SSE emerges with superior skill scores such as lowest root mean square error above the EM and the member models, for example in the prediction of spatial location and precipitation magnitudes that characterize the see-saw precipitation pattern in Eastern Africa. In all parts of Africa, and especially Eastern Africa where seasonal precipitation variability is a frequent cause huge human suffering in due to droughts and famine, the multimodel superensemble and its subsequent improvements will always provide a forecast that out weighs the best Atmosphere-Ocean Climate Model.

The aim of this study was to introduce a new activity-based balance index by using accelerometer data. Twenty-seven junior soccer players from the Iranian premier league were selected. Four functional tests, consisting of one leg stance, dynamic Y balance, running and dribbling tests, were conducted to assess the players’ balance, activity and skill. During these four tests, besides their relative scores, the acceleration of their body center was also recorded. Activity-based balance index (ABI) was calculated using these acceleration data. The results showed positive correlations between ABI and both static and dynamic balance scores. Additionally, negative correlations were found between ABI and dribbling scores, which demonstrate the agility required for this skill. It seems that this new index achieves the evaluation of both the balance and the skill level of soccer players. Perhaps this is a new way of talent identification and also a re-development of balance tests from traditional to modern.

Background: There is a high bureaucratic and administrative burden associated with health care tasks (test requesting, visits scheduling, supporting documents provision) that has historically largely fallen on health care professionals, which is one among the factors contributing to low job satisfaction and lower productivity. Incorporating new professional roles that help to better respond to the needs of both patients and professionals can increase the quality and efficiency of service provision. Objective: To evaluate the impact of the clinical assistant’s introduction in the Sant Joan de Déu Barcelona Children’s Hospital’s pediatric oncology department, in terms of displacement of activity loads carried out by this new professional role and the consequent time freed up for physicians. Methodology: Observational and retrospective study using administrative data based on the analysis of the type of activity performed by clinical assistants and the measurement of the time freed up in favor of the physicians, based on in situ timekeeping, to approximate the potential skill mix productivity increase. Results: Since its implementation in the pediatric oncology department, clinical assistants have performed 13,553 requests (69.93% of the total), representing a total saving of 266.83 hours or 6.67 workweeks of 40 hours. They performed 74.25% of outpatient surgical requests in the oncology department, 87.5% of day hospital requests and 54.13% of total requests in the outpatient consultations area. Conclusion: The introduction of clinical assistants in the oncology department could be efficient to the extent that it displaces a good part of the bureaucratic and administrative tasks previously performed by health care professionals. This delegation allows them to work more closely to the maximum of their competences and the physicians to have more time for higher added value clinical tasks. In terms of efficiency, this role change enables to optimize the clinical process, reducing the cost by 56% compared to the conventional model.

Learning dental procedures is a complex task involving the development of fine motor skills. The reported use of theories and/ or evidence for designing learning activities to develop the fine motor skills needed for dental practice is limited. The aim of this review is to explore the available body of knowledge related to learning fine motor skills in dentistry. Evidence from studies investigating motor skill learning highlights the negative impact of self-focus and self-regulation on learning outcomes, particularly during the early stages of learning. The development of activities and schedules that enable novices to demonstrate characteristics similar to experts, without the reported long period of ‘deliberate practice’, is clearly of value. Outcomes of learning implicitly are important in dentistry because working under stressful conditions is common, either during undergraduate study or in practice. It is suggested that learning implicitly in the simulation stage can reduce disrupted performance when transitioning to clinical settings. Therefore, further investigation of effective methods for learning dental fine motor skills is indicated, using approaches that result in robust performance, even under stressful conditions.

From the perspective of individual resource and social capital, this paper aims to explain how employees’ political skill affect their job satisfaction and turnover intention, through the mediating role of popularity. Using a sample of 237 dyad surveys from supervisors and employees in the Yangtze River Delta of China, we found that: 1) political skill is positively correlated with job satisfaction and negatively correlated with turnover intention, and that these correlations are partially mediated by individual popularity; 2) positive affect (PA) moderates the relationship between political skill and job satisfaction, and negative affect (NA) moderates the relationship between political skill and turnover intention. The implications of our findings and future research directions are discussed.

The aim of this study was to determine gender differences in the level of motor skills and effects of a multi-year exercise program on the level of motor skills in 161 preschool children (5-6 yo). Patricipants were deployed into one control and three experimental groups. Motor skills were assessed with the Bruininks-Oseretsky Test of Motor Proficiency (BOT-2). To determine difference in scores for each BOT-2 tests between control and experimental groups, one-way ANOVA was used for girls and boys separately while two-way ANOVA was employed to determine difference between the gender in the overall BOT-2 score. The results indicates that one-year multilateral exercise program has a positive effect on the level of motor skills in preschool children. Interestingly, additional years of participation in exercise program yielded in maintenance of acquired motor skills level. Also, exercise program affected more girls than preschool boys considering both individual and composite BOT-2 scores. According to the findings of this study, presented exercise program could have potential benefits on multilateral development of the motor skills in preschool children which could facilitate balance of locomotor and manipulative skills. Therefore, integration of multilateral program intended for preschool children could be considered for implementation within the kindergarten curriculum.

Innovations in engineering education are undergoing a noticeable transformation. Higher education institutions are practicing distance education, remote laboratories, studio pedagogies and several other approaches in order to increase their students’ retention, success, and preparedness for the job market. In engineering education, maker spaces have become popular in the last ten years in universities as well as community colleges, high-schools and community innovation hubs. A large number of engineering colleges have allocated significant spaces, and at some universities entire buildings as maker spaces to be used for curricular and extracurricular activities. Success stories of these types of spaces are well documented. This paper describes the activities and programs held at Tennessee Tech University’s maker space called ‘iMakerSpace.’ These accomplishments include several workforce development activities. The impact and effectiveness of the iMakerSpace is evaluated through analysis of survey data.

Extant research pays little attention to migrant workers’ skill accumulation/upgrading from the perspective of the labor supply. This paper takes China as an example to explore the factors influencing skill accumulation of rural-urban migrant workers (RUMWs), with a purpose to discover how to sustain or reshape regional competitive advantage through improving RUMWs’ skill accumulation. Structured questionnaire surveys were adopted for data collection in Suzhou City, Jiangsu Province and Taizhou City, Zhejiang Province located in the Yangtze River Delta in the east of China. 900 questionnaires were issued and 491 effective questionnaires were recovered totally. This paper takes a perspective of global production networks, and gets a broad viewpoint containing intra-firm coordination, inter-firm partnership and extra-firm bargaining with non-firm actors, beyond what the extant literature on laborers’ human capital focuses on. The finding indicates that firms’ skill-oriented preference, which concerns about employees’ skills and innovation ability and stimulates them to learn initiatively, have a significant influence on RUMWs’ skill accumulation. In terms of collective efficiency based on co-competitive relationship between local firms, the more intensive interactions are, the more opportunities of skill accumulation RUMWs get. The accessibility of local institutions and favorable policies benefit RUMWs’ skill accumulation. Besides, the place itself, as a synthesized space of labor-management relations inside a firm and inter-organization relations, exerts an influence on and cause the regional differences in RUMWs’ skill accumulation.

Background: Social skills deficits are present in 43.3% of major depressed patients and significantly impact health-related quality of life. However, studies concerning social deficits as state-dependent markers of depression are limited. Objective: To delineate the effects of severity of depression, personality characteristics, family support satisfaction and self-esteem on social skills in clinical depression. Methods: We recruited 150 patients with major depressive disorder or persistent depressive disorder and assessed 1) Beck Depression Inventory-II (BDI-II), 2) Social Skill Inventory (SSI), 3) Family Adaptation, Partnership, Growth, Affection, Resolve (APGAR) Questionnaire 4) Rosenberg Self-Esteem Scale (RSES) and 5) Maudsley Personal Inventory (MPI). Results: Social skills deficits were significantly associated with female gender, age < 40 years, depression severity, introvert / neurotic personality, and lowered family support satisfaction and self-esteem. A large part of the variance (47.2%) in social skills deficits was predicted by satisfaction of family support, introvert personality, and low self-esteem. Exploratory Factor Analysis showed that a bifactorial model best fitted the data with a) a general factor loading highly on BDI-II, SSI emotional and social, APGAR, RSES, MPI_introvert and MPI_neurotic scores, and b) a single-group factor loading on both SSI, RSES, and MPI introvert scores. Conclusion: In clinical depression, social skills deficits covary with increasing severity of depression and thus constitute a state marker of depression, and independently from severity of depression covary with introvert personality features. As such, remission of social skills deficits may emerge as a novel objective for the treatment of depression and prevention of new episodes.

Mid-tropospheric cut-off low (COL) pressure systems are linked to severe weather, heavy rainfall and extreme cold conditions over South Africa. They often result in floods and snowfalls in winter disrupting economic activities. This paper examines the evolution and circulation patterns associated with severe COLs over South Africa. We evaluate the performance of the 4.4 km Unified Model (UM) which is currently used operationally by the South African Weather Service to simulate daily rainfall. Circulation variables and precipitation simulated by the UM were compared against ECMWF’s ERA Interim reanalyses and GPM precipitation at 24-hour timesteps. We present five recent (2016-2019) severe COLs that had high impact and found higher model skill when simulating heavy precipitation during the initial stages than the dissipating stages of the systems. A key finding was that the UM underestimated precipitation mainly due to inaccurate placing of COL centers and areas of heavy rainfall by up to 5° of latitude away from the actual location, due to the poor formulating of cumulus and microphysics schemes in the model. Understanding the performance and limitations of the UM model in simulating COL characteristics can benefit severe weather forecasting and contribute to disaster risk reduction in South Africa.

Due to the advantages of wide coverage and continuity, remotely sensed data are widely used for large-scale drought monitoring to compensate the deficiency and discontinuity of meteorological data. However, few researches have focused on the capability of various remotely sensed drought indices (RSDIs) for representing the spatio-temporal variations of the meteorological droughts. In this study, five RSDIs, namely Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Vegetation Health Index (VHI), Modified Temperature Vegetation Dryness Index (MTVDI) and Normalized Vegetation Supply Water Index (NVSWI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) monthly NDVI and LST. The monthly NDVI and LST data were filtered by Savitzky-Golay (S-G) filtering method. Meteorological station-based drought index represented by Standardized Precipitation Evapotranspiration Index (SPEI) was compared with RSDIs. And the dimensionless Skill Score (SS) method was adopted to identify the spatiotemporally optimal RSDIs for presenting the meteorological droughts in the Yellow River basin (YRB) from 2000 to 2015. The results indicated that (1) RSDIs revealed a decreasing trend to the overall YRB consistent with SPEI except for in winter, and different variations of seasonal trends spatially; (2) the optimal RSDIs in spring, summer, autumn and winter were VHI, TCI, MTVDI and VCI, respectively, and the average correlation coefficient between the RSDIs and SPEI was 0.577 (=0.05); (3) different RSDIs have a 0–3 months’ time-lags compared with meteorological drought index.

This article investigated the Automatic Generation Control(AGC) of multi-area multi-source interconnected systems with hydropower plants, thermal power plants, and wind energy. Adaptive Neuro-fuzzy controller integrated with the cascaded proportional-integral-derivative with filter (PIDF-PIDF) is a new cascaded controller (ANF-PIDF-PIDF) that has been presented as a secondary controller for applied hybrid power systems. The recent Skill Optimization Algorithm (SOA) is employed to optimize PIDF- PIDF controller parameter gains and the Adaptive Neuro-Fuzzy controller's inputs and output scaling factors. SOA is used to update the controller parameters with integral square error (ISE) employed as the objective function. A 1% step load disturbance was considered simultaneously in all three areas. The controller's performance is evaluated and compared with and without considering the effects of wind energy sources and non-linearity for ANF-PIDF-PIDF, PIDF-PIDF, and PIDF and it was determined that the ANF-PIDF-PIDF was the most efficient. The dynamic system performance is also compared with parallel high voltage direct current (HVDC) tie-lines. The investigation clearly shows that incorporating HVDC tie-line with multi-area, multi-source provides better dynamic performance in maximum amplitude, oscillation, and settling time. Additionally, sensitivity analysis is done and the optimum controller gains does not need to be reset to uncertain values in system loading conditions. All simulation results were evaluated using MATLAB 2016b.

In order to counter the impending shortage of skilled professionals in the aging societies of our time in many western countries such as Germany, solutions for business and society are urgently needed. Here, artificial intelligence (AI) can play an important role in mitigating the problem with the help of diverse applications. At the same time, it is important to consider both the needs of the respective employee1 and the company to ensure that the use of AI has a positive impact on the organization and finds social acceptance. In this article, we describe the newly developed OSQE model (Optimize, Secure, Qualify, Expand), which for the first time outlines an AI cycle against the shortage of skilled professionals in a holistic approach that focuses equally on people and companies. This can serve organizations as a guide for strategy development, decision-making for and implementation of AI-supported measures in an entire cycle of an employee's affiliation with a company. The model takes three driving forces into account: companies, professionals, and AI applications. In the model, the measures to be implemented are prioritized with ascending numbering based on what would be most urgent for a company to implement. All measures relate to areas of action that place people at the center and can be assigned to the classic cycle of belonging of an employee in the company. In this regard, the opportunities that AI offers to professionals and companies are highlighted.