Lift Index Research Articles

Botulinum Toxin Injection Technique for Reducing the Masseter Size and Enhancing the Jawline.

The injection of botulinum toxin into the masseter muscle is an important method for improving hypertrophy. However, some patients may experience adverse reactions, such as sagging of the lower jaw. Therefore, we proposed a method of injecting botulinum toxin into the masseter and platysma muscles that would reduce masseter size and enhance the jawline. The aim of this study was to reduce the masseter size while enhancing the jawline. Twenty patients received botulinum toxin injections into the masseter and platysma muscles. Pain levels were evaluated with the visual analog scale. All patients were photographed before and 6 months after treatment. Evaluations were performed based on standardized criteria. The lift index, reduction index, and symmetry index were performed to assess the degree of jawline elevation, masseter size reduction, and jawline symmetry before and after treatment. The mean visual analog scale score of the 20 patients was 2.80 (±1.24). The mean lift index score decreased from 4.93 (±0.34) to 4.53 (±0.37), P < .05. The mean reduction index score decreased from 3.13 (±0.27) to 2.74 (±0.27), P < .05. The mean symmetry index score changed from 0.0393 (±0.0296) to 0.0257 (±0.0246), P < .05. Botulinum toxin injections into the masseter and platysma muscles through nerve block reduced the masseter size, elevated the jawline, and improved symmetry.

A high-performance voting-based ensemble model of graph convolutional extreme learning machines for identifying geochemical anomalies related to mineralization

How to effectively identify mineralization anomalies from geochemical survey data is one of the key problems that must be properly solved in geochemical exploration. Although supervised machine learning and deep learning techniques have been adopted to solve this problem, the performance of the established mineralization anomaly identification models is not satisfactory because the mutual relationship between neighborhood data points is not taken into account in the modeling of geochemical exploration data. The graph convolutional extreme learning machines (GCELMs) provide a new technique for modeling the graph data transformed from geochemical exploration data. To improve the performance of mineralization anomaly identification algorithms, the GCELM techniques were adopted to establish the supervised classification models for identifying mineralization anomalies from geochemical exploration data. To improve the robustness of the GCELM models in mineralization anomaly identification, an ensemble classification model called voting-based GCELM (V-GCELM) model was established by voting the outputs of multiple GCELM models. The Baishan area of Jilin Province (China) was taken as the study area for carrying out an experiment of mineralization anomaly identification from geochemical exploration data. The synthetic minority over-sampling technique (SMOTE) was used to alleviate the class-imbalance of the training data. The GCELM model, V-GCELM model and extreme learning machine (ELM) model were established for identifying mineralization anomalies, and their performances were compared in terms of the receiver operating characteristic (ROC) curves, area under the curves (AUCs) and lift indices. The results show that the V-GCELM model has the best performance, and its AUC and lift index are 0.9989 and 28.6, respectively. The GCELM model has the second-best performance, and its AUC and lift index are 0.9977 and 20.1, respectively. The ELM model has the worst but still high performance, its AUC and lift index are 0.9402 and 9.2, respectively. The mineralization anomalies identified by the three models have close spatial correlation with the polymetallic deposits found in the study area, and spatially controlled by the main controlling factors in the study area. Therefore, GCELM and V-GCELM are promising techniques for building the high-performance classification models for identifying mineralization anomalies from geochemical exploration data.

Meteorological drought assessment and prediction in association with combination of atmospheric circulations and meteorological parameters via rule based models

The development of data-driven models along with the data that are recorded from satellites has made the study of water engineering more attractive. In this study, SPEI values were calculated with the meteorological variables and then a combination of the meteorological variables as well as atmospheric circulation values was considered as a data mining model input for estimating the droughts. The series of the SPEI values for 3-, 6-, 9-, 12-, 24- and 48-month time scales were obtained during 1988-2016. In this study, both M5 Tree model and Associate Rules were used to predict and analyze the meteorological drought at 6 synoptic stations in the basin considering both the atmospheric circulations (NAO, SO, MOgi, MOac, WeMO, Mediterranean, Red, Black, Caspian, and Persian Gulf SSTs) and the meteorological variables (lagged relative humidity, evapotranspiration, average temperature, minimum-maximum temperature and pressure). The results showed that making use of a combination of the atmospheric circulation indices and meteorological variables in the models increases the accuracy of the model and improves the results in a long term period. The best result in the study of drought in Urmia Lake basin is related to SPEI48 (R = 0.85, RMSE = 0.08, MAE = 0.11) and in the association rules the value of the lift index of best rule is 1.32. Although both approaches provided acceptable results, M5 Tree model had a comparative advantage due to simple and practical linear relationships.

Discovering associations between radiological features and COVID-19 patients' deterioration.

Data mining methods are effective and well-known tools for developing predictive models and extracting useful information from various data of patients. The present study aimed to predict the severity of patients with COVID-19 by applying the rule mining method using characteristics of medical images. This retrospective study has analyzed the radiological data from 104 COVID-19 hospitalized patients diagnosed with COVID-19 in a hospital in Iran. A data set containing 75 binary features was generated. Apriori method is utilized for association rule mining on this data set. Only rules with confidence equal to one were generated. The performance of rules is calculated by support, coverage, and lift indexes. Ten rules were extracted with only X-ray-related features on cases referred to ICU. The Support and Coverage index of all of these rules was 0.087, and the Lift index of them was 1.58. Thirteen rules were extracted from only CT scan-related features on cases referred to ICU. The CXR_Pleural effusion feature has appeared in all the rules. The CXR_Left upper zone feature appears in 9 rules out of 10. The Support and Coverage index of all rules was 0.15, and the Lift index of all rules was 1.63. the CT_Adjacent pleura thickening feature has appeared in all rules, and the CT_Right middle lobe appeared in 9 rules out of 13. This study could reveal the application and efficacy of CXR and CT scan imaging modalities in predicting ICU admission to a major COVID-19 infection via data mining methods. The findings of this study could help data scientists, radiologists, and clinicians in the future development and implementation of these methods in similar conditions and timely and appropriately save patients from adverse disease outcomes.

IMPACTOS DO FORTALECIMENTO DO CENTRO ABDOMINAL SOBRE A APTIDÃO FÍSICA NA GINÁSTICA AERÓBICA

ABSTRACT Introduction: The requirements for physical and strength quality of athletes are getting higher and higher, following the advances in the development of modern competitive aerobics. The strengthening of the abdominal center in current exercises is focused only on the superficial musculature, and it is believed that specific strengthening training can impact the fitness of gymnasts. Objective: Analyze the impacts of strengthening the abdominal core on the physical fitness of aerobic gymnasts. Methods: Using the controlled experiment method, abdominal core strength training was added to the traditional training of aerobic gymnastics students, while the control group remained with traditional training methods. The assessment was performed before and after the intervention, and the fitness results were compared and discussed statistically. Results: The mean index of the leaning back activity score in the experimental group increased from 37.750 to 41.582; the index in the bridge activity in the experimental group increased from 6.421 to 16.053; the index in the hanging bridge activity in the experimental group increased from 7.484 to 12.474; the mean overall stability score of the students before and after the experiment increased from 93.090 to 98.148; the mean hip lift index was also changed from 7.046 to 9.676. Conclusion: It was observed that the need for mastery of abdominal core strength to complete aerobic movements of high complexity, where abdominal core strengthening has an important role in stabilizing the center of gravity, force distribution, and preventing fatigue after exercise. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Constructing a high-performance self-training model based on support vector classifiers to detect gold mineralization-related geochemical anomalies for gold exploration targeting

In an area where mineral deposits have been discovered, both anomaly detection algorithms and supervised classification algorithms can be adopted to detect mineralization-related geochemical anomalies for mineral exploration targeting. However, anomaly detection algorithms themselves cannot use known mineral deposits as the supervisors to improve the performance of geochemical anomaly detection models. Supervised classification algorithms can not properly deal with the extreme class-imbalance of geochemical exploration data in the establishment of classification models. Therefore, neither anomaly detection models nor supervised classification models perform well in the detection of mineralization-related geochemical anomalies. In order to obtain a high-performance mineral exploration targeting model, the self-training algorithm was adopted to construct a self-training model based on support vector classifiers to detect gold mineralization-related geochemical anomalies in the Chengde area in Hebei Province (China). The self-training model was compared with the support vector classification model, logistic regression model and five dictionary learning models in terms of area under the curve (AUC) and lift index. The AUC value of the self-training model (0.89) is much higher than those of the two supervised classification models (0.81–0.82) and five anomaly detection models (0.79–0.81). The lift index of the self-training model (11.87) is also much higher than those of the two supervised classification models (2.77–4.04) and five anomaly detection models (2.64–3.48). Therefore, the self-training model performs much better than the two supervised classification models and five anomaly detection models in the detection of gold mineralization-related geochemical anomalies. The gold mineralization-related geochemical anomalies detected by the self-training model highly conform to the metallogenic and geological features in the study area. Therefore, it is a prospective method to establish a self-training model to detect mineralization-related geochemical anomalies in an area where mineral deposits have been discovered.

Concurrently observed actions are represented not as compound actions but as independent actions.

Recent research suggests that we can simultaneously represent the actions of multiple agents in our motor system. However, it is unclear exactly how concurrently observed actions are represented. Here, we tested two competing hypotheses. According to the independence hypothesis, concurrently observed actions are represented as independent actions. According to the compound hypothesis, they are instead integrated, whenever possible, into compound actions. In Experiment 1 (N = 32), we first show that the standard imitation-inhibition task with a single hand can be extended to measure automatic imitation of compound actions. In Experiments 2-5 (NTotal = 368), we then investigated the representation of concurrently observed actions by further extending this task to include two hands. The results showed that two hands performing two different actions (e.g., one hand lifts index finger, one hand lifts middle finger) produced an effect similar to that of both hands performing just one of those actions (e.g., both hands lift index finger) but different from that of both hands performing both actions together (i.e., a compound action; lift both index and middle finger). This indicates that concurrently observed actions are coded as independent actions in the motor system. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Theoretical Prediction on Hydraulic Lift of a Coandă Effect-Based Mining Collector for Manganese Nodule

The undersea collecting vehicle is one of the three main parts in the deep-sea exploitation system. The Coandă effect-based collector picks up manganese nodules by providing an adverse pressure difference over the nodule, through the jet flowing around a curved wall. In order to overcome the drawbacks of repeated prototyping and experimenting in the traditional design procedure of the Coandă effect-based collector, the theoretical guide should be well placed to ensure correct design of the strongly related parameters of the collector. In this paper, a simplified model of curved wall jets was developed and the solution of approximate closed form was obtained to predict the lift force of the nodules. The variational tendencies of velocity, pressure and single-particle lift index perpendicular to the curved wall were investigated and the Coandă effects were found to be stronger with higher initial velocity, higher non-dimensional jet slot height and lower non-dimensional wall height. A CFD-DEM simulation of a number of particles was additionally performed to give more insight into the predictive accuracy of the simplified theory. Target lift force was found to be related to high efficiency in collection of particles, resulting in certain predictability of the theoretical model to the nodule lifting in a pre-prototype hydraulic device based on the Coandă effect.

Sensitivity analysis of weather research and forecasting (WRF) model output variables to the thunderstorm lifecycle and its application

Accurate and timely forecasts of thunderstorms at lead times of more than 6 h can greatly improve the efficiency of air traffic flow management. To achieve this goal, thunderstorms occurring at Urumqi International Airport in 2020 were investigated using Weather Research and Forecasting (WRF) model output variables. An attempt was made to study the sensitivity of WRF output variables to the different stages (cumulus, mature, and dissipating) of the thunderstorm lifecycle. The variables considered in this paper include the wind speed (WSPD), composite radar reflectivity, echo top height, convective available potential energy (CAPE), convective inhibition (CIN), and lift index (LI). It was found that CIN is the most sensitive to an approaching thunderstorm. WSPD is extremely sensitive to the thunderstorm occurrence, closely followed by CIN. CAPE, CIN, and LI are all sensitive to dissipating thunderstorms. To improve thunderstorm forecasts, a simple and practical objective thunderstorm forecasting method, i.e., the thunderstorm probability (TSP) forecasting method, based on the combination of the above-mentioned variables, was proposed. Comparison of objective TSP forecasts and manual subjective forecasts indicated that TSP forecasts performed much better than did manual forecasts over the summer period of 2020.

Outage Cause Detection in Power Distribution Systems Based on Data Mining

Realizing the factors involved in power system outages can be effective in reliability improvement. In this article, we analyze the distribution power network outage data to find dominant factors in occurring vegetation-, animal-, and equipment-related outages. After their integration, real outage, weather, and load as the input data are used to extract associated features. In this article, visualization techniques are initially utilized to show the impact of features on the outage occurrence and then association rule mining is used to find factors correlated with each outage type as well as each other. Association rules are mined using Apriori technique, considering the chi-square and lift index as the measures of interestingness. The outage analyses are also performed for each equipment separately to find the associated rules. The results showing the effectiveness and validity of the proposed method to identify the factors connected with outage occurrences can be used for future planning and the operation schedule of distribution power networks.

A comparative study of classifier techniques for lift index data analysis

PurposeA classifier technique is one of the important tools which may be used to classify the data or information into systematic manner based on certain criteria pertaining to get the accurate statistical information for decision making. It plays a vital role in the various applications, such as business organization, e-commerce, health care, scientific and engineering application. The purpose of this paper is to examine the performance of different classification techniques in lift index (LI) data classification.Design/methodology/approachThe analyses consist of two stages. First, the random data are generated for lifting task through computer programming, which is then put into the National Institute for Occupational Safety and Health equation for LI estimation. Based on the evaluated index, the task may be classified into two groups, i.e. high-risk and low-risk task. The classified task is considered to analyze the performance of different tools like Artificial Neural Network (ANN), discriminant analysis (DA) and support vector machines (SVMs).FindingsThe work clearly demonstrates the accuracy and computational ability of ANN, DA and SVM for data classification problems in general and LI data in particular. From the research it may be concluded that SVM may outperform ANN and DA.Research limitations/implicationsThe research is limited to a particular kind of data that may be further explored by selecting the different controllable parameters and model specification. The study can also be applied to realistic problem of manual loading. It is expected that this will help researchers, designers and practicing engineers by making them aware of the performance of classification techniques in this area.Originality/valueThe objective of this research work is to assess and compare the relative performance of some well-known classification techniques like DA, ANN and SVM, which suggest that data characteristics considerably impact the classification performance of the methods.

Panel Discussion In Honor of Dr Tom Waters The NIOSH Lifting Equation - Part II

With the introduction of the NIOSH Lifting Equation, specifically after the publication of the Revised Lifting Equation (RLE) (Waters et al., 1993), occupational health and safety professionals across the world have successfully utilized the RLE to evaluate the risks associated with lifting and lowering tasks in the workplace. Although the RLE takes into consideration of various job task variables to determine recommended weight limits for a variety of task combinations, a number of articles and peer reviewed publications have appeared with a notion of either extending or modifying the RLE to address manual handling situations that the original equation was not able to assess comprehensively. The purpose of this panel discussion will be to provide an overview to ergonomics practitioners and researchers of these extensions and beyond, thus exploiting the full potential of this lifting equation. The first presentation will discuss the Variable Lift Index (VLI) for highly variable manual lifting tasks, whereas the second presentation describes the Sequential Lift Index (SLI) in assessing a sequence of lifting tasks that workers perform while they rotate to different tasks over a workday. In addition to the inherent variability in lifting tasks assumed by the RLE, we often encounter materials handling scenarios associated with one-handed lifting, team lifting, lifting of people (e.g., patient handling), lifting while seated or kneeling, lifting on improper frictional surfaces, lifting unstable loads, or lifting for more than 8 hours. To this effect, the third presentation examines the wider application of the RLE by adding new multipliers to the equation. Extending further on quantifying typical lifting task-related variables and associated risk on the lower back, the final presentation explores the fatigue failure process experienced by the lumbar spine when performing multiple and varied lifting tasks. This innovative approach is nascent in ergonomics literature, especially in ergonomics risk assessment, and has great potential in injury prevention at the workplace.

Meteorological and hydrological analysis of major floods in NE Iberian Peninsula

This paper analyses the meteorological conditions and the specific peak flows of 24 catastrophic floods that affected NE Iberian Peninsula in the period 1842–2000. We classify these floods according to the affected area, peak flow magnitude, and damages. Additionally, the NOAA 6 Hourly 20th Century V2 Reanalysis Data Composites have been used to analyze the synoptic conditions during each flood and to evaluate several stability indices, such as the convective available potential energy (CAPE), or the lift index. We found a good correlation between stability indices and the season when the flood occurred. For instance, if maximum CAPE is considered, larger values are found for summer floods, moderate for autumn, and low values during winter floods. We select 5 representative episodes occurred in different seasons and areas to describe in detail the synoptic conditions and to show the temporal evolution of the stability indices. In one the summer floods analyzed in detail, the largest instability, according to all the convective indices, is found. On the contrary, the winter case shows very low values of the convective indices, and autumn cases lay in between. During the other analyzed summer flood instability was low but snow thaw played an important role in producing the flood. Regarding hydrological variables, clear differences between floods occurred at the coast or at the Pyrenees are found. Coastal specific peak flows are larger than Pyrenean ones, especially for small catchment areas. We also combine meteorological (rainfall duration, CAPE), hydrological (specific peak flow) and geomorphological (catchment area) variables to show that for many of the analyzed floods these variables are related: the specific peak flow generally shows larger values when CAPE is also large. However some differences appear depending on the season and area. In those summer floods, where snow thaw played doesn’t played any role, either Pyrenean or coastal, specific peak flow seems to be correlated with CAPE. For autumn floods, depending on the area different correlations were found: Pyrenean floods seem to be a correlation between CAPE and specific peak flows, but not for coastal ones. For winter coastal floods we couldn’t find any correlation between CAPE and specific peak flows.

Variable Lifting Index (VLI): A New Method for Evaluating Variable Lifting Tasks.

Objective:We seek to develop a new approach for analyzing the physical demands of highly variable lifting tasks through an adaptation of the Revised NIOSH (National Institute for Occupational Safety and Health) Lifting Equation (RNLE) into a Variable Lifting Index (VLI).Background:There are many jobs that contain individual lifts that vary from lift to lift due to the task requirements. The NIOSH Lifting Equation is not suitable in its present form to analyze variable lifting tasks.Method:In extending the prior work on the VLI, two procedures are presented to allow users to analyze variable lifting tasks. One approach involves the sampling of lifting tasks performed by a worker over a shift and the calculation of the Frequency Independent Lift Index (FILI) for each sampled lift and the aggregation of the FILI values into six categories. The Composite Lift Index (CLI) equation is used with lifting index (LI) category frequency data to calculate the VLI. The second approach employs a detailed systematic collection of lifting task data from production and/or organizational sources. The data are organized into simplified task parameter categories and further aggregated into six FILI categories, which also use the CLI equation to calculate the VLI.Results:The two procedures will allow practitioners to systematically employ the VLI method to a variety of work situations where highly variable lifting tasks are performed.Conclusions:The scientific basis for the VLI procedure is similar to that for the CLI originally presented by NIOSH; however, the VLI method remains to be validated.Application:The VLI method allows an analyst to assess highly variable manual lifting jobs in which the task characteristics vary from lift to lift during a shift.

Stable isotope variations in precipitation over Deqin on the southeastern margin of the Tibetan Plateau during different seasons related to various meteorological factors and moisture sources

This study investigated the variations of stable isotopes (δ18O and δD) in precipitation at Deqin on the southeastern margin of the Tibetan Plateau. The results show that correlations between stable isotopes in precipitation and temperature vary during different seasons. In comparison, an apparent inverse correlation between stable isotopes and precipitation amount exists throughout different seasons. Hence, the “amount effect” appears to have significantly controlled the stable isotope variations in precipitation over the entire sampling period, rather than the “temperature effect”. The overall temporal variations of δ18O and δD in precipitation from Deqin are similar to those from a southern station at Xishuangbanna. Both stations demonstrate considerably depleted precipitation δ18O values in the summer as a consequence of intense Asian summer monsoon activities. However, at Xishuangbanna, the occurrences of the timing and duration of the depleted δ18O values, as well as the negative surface lift index values, occur earlier and last longer than those at Deqin. These results indicate that the Asian summer monsoon onset is later and that the duration of the monsoon activities is shorter at Deqin relative to Xishuangbanna.

A prospecting cost-benefit strategy for mineral potential mapping based on ROC curve analysis

A prospecting cost-benefit strategy is developed by quantitatively defining the prospecting cost and benefit in mineral potential mapping. Suppose that some mineral deposits have been discovered in a study area of a set of grid cells, the prospecting cost and benefit of a “unique” condition can be defined as the percentage of non-deposit-bearing and deposit-bearing cells within the “unique” condition, respectively. By replacing the false positive and true positive rates in the receiver operating characteristic (ROC) curve analysis with the prospecting cost and benefit, the Youden index, likelihood ratio, and lift index can be computed and used to express the mineral potential of the “unique” condition. Thus, the mineral potential mapping in a study area can be implemented by identifying all the possible “unique” conditions and then computing their mineral potential indicators such as the Youden index, likelihood ratio, and lift index. By integrating an automatic “unique” condition searching algorithm with the techniques for computing the mineral potential indicators for each “unique” condition, the following prospecting cost-benefit strategy is developed for mineral potential mapping: (a) select map patterns closely associated with the discovered mineral deposits using their mineral potential indicators, (b) automatically search for all the possible “unique” conditions, (c) evaluate the mineral potential of each “unique” condition using its mineral potential indicators, and (d) assess mineral potential mapping performance using the mineral potential indicator diagrams. For demonstration purposes, the Baishan district in Southern Jilin Province in China, which has a complex geological setting, is chosen as a case study area. The weights of evidence (WofE) modeling posterior probability, Youden index, likelihood ratio, and lift index are applied in the mineral potential mapping and their performance are assessed using their ROC curves, cumulative lift charts, and Youden and likelihood ratio diagrams. The results show that (a) the likelihood ratio and lift index perform similarly well and (b) the posterior probability performs a little bit worse than the likelihood ratio and lift index while a little bit better than the Youden index. Therefore, the prospecting cost-benefit strategy provides a common paradigm for both mineral potential mapping and the performance assessment.

Physical Fitness of Rugby Umpires Based on Prudential Fitnessgram®

The aim of this study is to assess health related physical fitness of rugby umpires. Besides that, this study also aims to see whether there is any differences based on the health related components of physical fitness according to age group. The samples of this study were 39 umpires who were involved in a tournament, aged between 20 to 45 years. Test battery used in this study is Prudential FITNESSGRAM® by Cooper Institute for Aerobic Research (1992) which includes PACER 20 meter Multistage run, push up, curl up, trunk lift and body mass index (BMI). Data analysis showed that there is significant difference on the different components of health related physical fitness for the different age groups. The results of this study can be used by the Technical Committee of Rugby Tournaments in Malaysia to ensure that umpires involved in any tournaments has excellent fitness level to avoid from making judgmental decision which may cause tense situation among players, coaches and management. The results of this study is hope to convince all umpires on the importance of good physical fitness as it will positively affect the level of umpiring to be more effective and of high quality.

Potential of adjustable height carts in reducing the risk of low back injury in grocery stockers

While the workers of the Wholesale and Retail Trade industrial sector suffer from musculoskeletal disorders at an alarming rate, there have been few investigative studies into potential effective interventions to reduce the ergonomic stress. The objective of the study was to determine whether a cart with an adjustable shelf could reduce awkward postures and motions while stocking products in a grocery store. Fifteen workers at a small grocery store in Puerto Rico completed stocking tasks with two types of carts: traditional and adjustable height cart or Ergo Cart. Trunk kinematics, LBD risk index, NIOSH lifting index, subjective ratings, and productivity indicators were collected during four typical stocking tasks. The Adjustable Ergo Cart reduced the sagittal trunk flexion by 7° and velocity by about 5°/s but increased twisting by about 2° and twist velocity by 4°/s as compared to the traditional cart. The LBD risk index was reduced by a small 2.4% in probability although greater reductions were found for larger items (e.g. bags of dog food and 2-L of Soda). The consensus among workers was that the adjustable cart would be easier to use. Overall, the study provides objective evidence that an ergonomically designed cart (e.g. adjustable height) has some potential to reduce sagittal trunk flexion, LBD risk index, and the NIOSH lift index. Overall, the results indicate that any intervention such as an adjustable cart can only have marginal effectiveness unless the entire systems perspective is considered.

Safe Lifting Programs at Long-Term Care Facilities and Their Impact on Workers' Compensation Costs

To determine the utility of a safe lifting program index and a measure of lift inventory to predict workers' compensation claim frequency and costs in long-term care facilities in 23 states. Workers' compensation claims and cost data were matched to Center for Medicare and Medicaid Services (CMS)-certified facilities (N = 656). Facility safe lifting program index were derived from interviews with directors of nursing in a subset (N = 271). The higher the safe lift index score, the lower the claims and costs. An increase of one lift per 100 residents is associated with a 5% decrease in claims frequency and an 11% decrease in total costs on average. In this national study, we find that a comprehensive safe lift program, endorsed and promoted by directors of nursing, reduces caregiver injury as measured by workers' compensation claims frequency and costs.

Clap and Fling Aerodynamics - An Experimental Evaluation

ABSTRACT The ‘Clap and Fling’ hypothesis, which describes augmentation of lift during the wingbeat of certain insects and birds, was evaluated experimentally in model form. Using induced velocity output as a lift index, and testing at a Reynolds number of roughly 83000, it was learned that: The main ‘Clap and Fling’ aerodynamic effect consists of raising the lift output realized at the beginning of the stroke. After one chord of travel, ‘Clap and Fling’ effects are minor. Considered over a complete stroke, ‘Clap and Fling’ lift output is limited to 1·15 times the lift output of an identical fixed incidence wing undergoing the same jump start trajectory. ‘Clap and Fling’ output is limited by considerations of maximum circulation and circulation persistence. These limitations are not envisioned in current analyses.