Prediction of suspended sediment concentration from water quality variables

This study investigates use of water quality (WQ) variables, namely total chromium concentration, total iron concentration, and turbidity for predicting suspended sediment concentration (SSC). For this purpose, the artificial neural networks (ANNs) and regression analysis (RA) models are employed. Seven different RA models are constructed, considering the functional relation between measured WQ variables and SSC. The WQ and SSC data are fortnightly obtained from six monitoring stations, located on the stream Harsit, Eastern Black Sea Basin, Turkey. A total of 132 water samples are collected from April 2009 to February 2010. Model prediction results reveal that ANN is able to predict SSC from WQ data, with mean absolute error (MAE) of 10.30 mg/L and root mean square error (RMSE) of 13.06 mg/L. Among seven RA models, the best one, which has the form including all independent parameters, produces results comparable to those of ANN, with MAE = 14.28 mg/L and RMSE = 15.35 mg/L. The sensitivity analysis results reveal that the most effective parameter on the SSC is total chromium concentration. These results have time- and cost-saving implications.     

The effect of idle time thresholds on computer use time estimations by electronic monitoring

This study examined the effect of idle time setting on the estimation of computer use times by electronic activity monitoring and validated its use by comparing it with video record observations. Twenty-four study subjects were recruited and their work with computers was monitored for 1 h. With the estimates by video record observation as references, the best idle time settings for electronic activity monitoring with the least relative errors were 25, 2.5 and 2.5 s, respectively, for total computer, keyboard and mouse use time estimations. These estimates were highly correlated with the corresponding references (r = 0.918–0.964, p < 0.0001), accompanied by limited mean estimate differences ranging from ?3.0 ± 2.8% to 1.3 ± 1.6%. The estimates by self-report were moderately correlated with the corresponding references (r = 0.387–0.678), with greater mean estimate differences. This study concluded that, for electronic activity monitoring methods, the most appropriate thresholds for idle time setting are 25 s, 2.5 s and 2.5 s for total computer, keyboard and mouse use time estimates, respectively. This method may help evaluate physical work-loading with computer works through a large-scale epidemiological study.     

Constructing a novel mortality prediction model with Bayes theorem and genetic algorithm

Intensive care is one of the most important components of the modern medical system. Healthcare professionals need to utilize intensive care resources effectively. Mortality prediction models help physicians decide which patients require intensive care the most and which do not. The Simplified Acute Physiology System 2nd version (SAPS II) is one of the most popular mortality scoring systems currently available. This study retrospectively collected data on 496 patients admitted to intensive care units from year 2000 to 2001. The average patient age was 59.96 ± 1.83 years old and 23.8% of patients died before discharge. We used these data as training data and constructed an exponential Bayesian mortality prediction model by combining BSM (Bayesian statistical model) and GA (genetic algorithm). The optimal weights and the parameters were determined with GA. Furthermore, we prospectively collected data on 142 patients for testing the new model. The average patient age for this group was 57.80 ± 3.33 years old and 21.8% patients died before discharge. The mortality prediction power of the new model was better than SAPS II (p < 0.001). The new model combining BSM and GA can manage both binary data and continuous data. The mortality rate is predicted to be high if the patient’s Glasgow coma score is less than 5.     

Examining joint loading and self-reported exertion and discomfort during ladder handling

Ladder handling by telecommunications technicians represents an indispensable part of their daily work, but may generate musculoskeletal injury risk. These workers have a high prevalence of shoulder and back injuries, motivating research to quantify postures and loading using different ladders during common handling tasks. Twenty-five participants completed carry, raise (against a wall or free standing), and simulated removal from a van roof tasks using three ladders (8.5m 2-piece wood; 8.5m 2-piece fibreglass, 9.2m 3-piece wood). Data collection included kinematics and kinetics during these ladder handling tasks, as well as perceived discomfort, perceived exertion and post-collection ladder and task preferences. Significant effects depended on task and ladder. Dominant arm (the arm completing the primary action) elevation was higher while extending the ladder (114.7 ± 3.4°) than the carry task (53.5 ± 3.5°) (p < 0.05). Joint moments in the dominant shoulder and trunk were highest for the 2-piece wood ladder (59.0 ± 2.2 Nm and 254.8 ± 8.8 Nm) averaged across all tasks. Joint forces were increased when using the 2-piece wood ladder compared to the 3-piece wood ladder (p < 0.05), while the greatest discomfort in the shoulders occurred using the 2-piece wood ladder in the carry task. Many tasks approached or exceeded strength capability of a 50th percentile male's predicted strength. While no ladder universally mitigated physical demands while lowering perceptual difficulty, construction differences yielded trends toward preferring the 2-piece fibreglass or 3-piece wood ladders over the 2-piece wood ladder. This work has direct relevance to workplaces with ladder handling and provides recommendations for ladder selection and strength requirements across tasks.     

Field measurement of hand forces of palm oil harvesters and evaluating the risk of work-related musculoskeletal disorders (WMSDs) through biomechanical analysis

Hand force data is critical in evaluating work-related musculoskeletal disorders (WMSDs). Nevertheless, earlier studies on oil palm workers relied on estimated or laboratory measurements, which may not accurately reflect the actual hand forces. This study is the first report on the field measurement of hand forces for palm oil harvesters using a chisel and sickle to harvest low and tall palm trees, respectively. The dynamic hand forces and ground reaction forces were measured using instrumented harvesting tools and force plates, while wearable motion (IMU) and electromyography (EMG) sensors were incorporated for quantifying postural angles and muscle activations, respectively. Additionally, the spinal loadings, continuous Rapid Entire Body Assessment (REBA) scores, and subjective pain scores were determined to evaluate the risk of WMSDs. A total of 10 harvesters were recruited to perform the palm pruning tasks using a chisel and sickle. Resultantly, the sickle and chisel recorded a maximum cutting force of 1601.23 ± 424.26 N and 420.80 ± 96.00 N, respectively. All pruning tasks were found to be highly risky to harvesters, with a peak REBA score of 12. Likewise, all investigated muscles were activated for over 40% MVC, thus inducing moderate pain in the muscles. The peak L5-S1 compression forces for all tasks exceeded the safety threshold (>3400 N), but the values were not significantly different. The shear force of the L5-S1 was extreme in pruning with a sickle (1446.10 ± 411.00 N) compared to using a chisel. In conclusion, palm harvesters were at a high risk of developing WMSDs following poor postures, high physical exertion and muscle activity, and excessive spinal loads.     

A detection problem: Sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation

Sustainable management of groundwater-dependent vegetation (GDV) requires the accurate identification of GDVs, characterisation of their water use dynamics and an understanding of associated errors. This paper presents sensitivity and uncertainty analyses of one GDV mapping method which uses temperature differences between time-series of modelled and observed land surface temperature (LST) to detect groundwater use by vegetation in a subtropical woodland. Uncertainty in modelled LST was quantified using the Jacobian method with error variances obtained from literature. Groundwater use was inferred where modelled and observed LST were significantly different using a Student's t-test. Modelled LST was most sensitive to low-range wind speeds (<1.5 m s⁻¹), low-range vegetation height (<=0.5 m), and low-range leaf area index (<=0.5 m² m⁻²), limiting the detectability of groundwater use by vegetation under such conditions. The model-data approach was well-suited to detection of GDV because model-data errors were lowest for climatic conditions conducive to groundwater use.     

Risk of slaughterhouse workers developing work-related musculoskeletal disorders in different organizational working conditions

Job rotation is defined as workers rotating between tasks with different exposure levels and occupational demands. The aim of the present study was to analyze the risk factors for the development of upper-limb work-related musculoskeletal disorders (UL-WMSDs) in poultry slaughterhouse workers as well as compare the score of the OCRA Checklist in different organizational working conditions. In this cross-sectional study, 118 workers were involved, 68 women (32.3 ± 10.7 years) and 50 men (29.5 ± 10.5 years). Three organizational configurations (“without job rotation”, “with job rotation – tasks >1h” and “with job rotation - tasks <1h”) were evaluated using the OCRA Checklist method, totaling 36 tasks and 28 job rotation schemes composed of 2–3 tasks. The OCRA score of the right upper limbs (17.8 ± 3.2) was significantly higher (p = 0.046) relative to the left upper limbs (16.4 ± 3.6). The median score was significantly lower in the “with job rotation - tasks <1h” condition (18.6) when compared to the “job rotation – tasks >1h” (19.4) (p < 0.001) and the “without job rotation” (19.0) (p = 0.038) conditions. However, there was no significant difference between the condition “with job rotation - tasks >1h” and “without job rotation” (p = 0.155). Thus, job rotations with intervals <1h reduced the risk of developing UL-WMSDs. Job rotations with <1 h intervals in poultry slaughterhouses are recommended along with further studies to verify the effectiveness of rotations with more than two tasks, involving mild or non-repetitive tasks.     

Performance comparison of artificial neural network and logistic regression model for differentiating lung nodules on CT scans

PurposeTo compare the diagnostic performances of artificial neural networks (ANNs) and multivariable logistic regression (LR) analyses for differentiating between malignant and benign lung nodules on computed tomography (CT) scans.MethodsThis study evaluated 135 malignant nodules and 65 benign nodules. For each nodule, morphologic features (size, margins, contour, internal characteristics) on CT images and the patient’s age, sex and history of bloody sputum were recorded. Based on 200 bootstrap samples generated from the initial dataset, 200 pairs of ANN and LR models were built and tested. The area under the receiver operating characteristic (ROC) curve, Hosmer–Lemeshow statistic and overall accuracy rate were used for the performance comparison.ResultsANNs had a higher discriminative performance than LR models (area under the ROC curve: 0.955 ± 0.015 (mean ± standard error) and 0.929 ± 0.017, respectively, p < 0.05). The overall accuracy rate for ANNs (90.0 ± 2.0%) was greater than that for LR models (86.9 ± 1.6%, p < 0.05). The Hosmer–Lemeshow statistic for the ANNs was 8.76 ± 6.59 vs. 6.62 ± 4.03 (p > 0.05) for the LR models.ConclusionsWhen used to differentiate between malignant and benign lung nodules on CT scans based on both objective and subjective features, ANNs outperformed LR models in both discrimination and clinical usefulness, but did not outperform for the calibration.     

Examining kinematics and muscle activity of the upper extremity while performing cleaning tasks: A pre-post shift evaluation

Custodians engage in strenuous manual labour throughout their workday. Uncertainty exists on whether kinematics or muscle activation changes as workers progress through their shift. The purpose of this study was to examine muscle activation and upper extremity kinematics during typical custodial tasks performed at the start and end of the work shift. Electromyography (EMG) of 8 torso and upper extremity muscles and motion capture of the corresponding region were collected for 10 custodial participants while they completed garbage removal, dry mopping, and vacuuming tasks at the start and end of a work shift. The start of shift assessment demonstrated larger anterior deltoid, posterior deltoid and extensor digitorum activation by up to 12.6 %maximal voluntary contraction (%MVC) (p < 0.001–0.023). Task affected mean and peak EMG in all muscles except flexor digitorum (p < 0.001–0.0293), and the greatest activation was found during vacuuming (peak <55%MVC in anterior and middle deltoid) and the heaviest garbage removal task (84% MVC peak in upper trapezius). Mopping created the lowest amounts of activation for almost all muscles. Joint range of motion (p < 0.001–0.031) in the shoulder was highest in vacuuming, while trunk flexion was largest in garbage removal tasks. This work replicated common custodial tasks in a laboratory, using actual custodial workers at times relevant to their typical work shifts. The information presented is useful for ergonomists, work tasks designers and custodial administration staff to develop guidelines for injury prevention.     

Prior knowledge-supported aerosol optical depth retrieval over land surfaces at 500 m spatial resolution with MODIS data

Aerosol optical depth (AOD) values at a spatial resolution of 500 m were retrieved over terrain areas by applying a time series of Moderate resolution Imaging Spectroradiometer (MODIS) 500 m resolution data in the Heihe region (36–42° N, 97–104° E) of Gansu Province, China; in the Pearl River Delta (18–30° N, 108–122° E), China; and in Beijing (39–41° N, 115–118° E), China. A novel prior knowledge scheme was used in the algorithm that performs cloud screening, simultaneous AOD and surface reflectance retrieval from the MODIS 500 m Level 1B data. This prior knowledge scheme produced a new Ångström exponent α, utilizing a Terra pass time α and an Aqua pass time α to better satisfy the invariant α assumption. The retrieved AOD data were compared with AOD data observed with the ground-based, automatic Sun-tracking photometer CE318 at corresponding bands in the Heihe region and with Aerosol Robotic Network (AERONET) data in the Pearl River Delta and in Beijing. Validation experiments demonstrated the potential of applying the algorithm to MODIS 500 m AOD retrieval on land; validation showed the uncertainty of Δτ = ±0.1±0.2τ over various types of underlying land surface, including cities, where τ is the aerosol optical depth. The root mean square errors (RMSEs) were around 0.1 for inland regions and up to 0.24 for cities by the sea, such as Hong Kong and Zhongshan, China.     

R2: Drilling into concrete: Effect of feed force on handle vibration and productivity

Approximately 1.6 million commercial construction workers in the US use rotary hammer drills for drilling into concrete to insert anchor bolts or rebar. The exposure to vibration may lead to hand-arm vibration syndrome and other musculoskeletal disorders depending on handle vibration acceleration level, hand grip force, and duration of exposure. There is little information on the relationship between feed force (FF), e.g., the push force applied by the worker, and handle vibration. A robotic test bench for rotary hammer drills was used to evaluate the effects of different FF on handle vibration and productivity (e.g., penetration rate and holes drilled). Increasing FF from 95 to 163 N was associated with an increase in total weighted handle vibration (a_hv) of 7.2–8.5 m/s² (slope, p < 0.001) but from 163 to 211 N there was no change in vibration level (slope, p = 0.17). Increasing FF from 95 to 185 N was associated with an increase in penetration rate of 7.2–8.5 m/s² (slope, p < 0.001) but from 185 to 211 N there was no change in penetration rate (slope, p = 0.49). Based on the maximum allowable duration of exposure to hand vibration, specified by the ISO and ACGIH Action Limits, and the penetration rate, the drilling productivity, in m drilled per day, is greatest for the lowest FF tested. Contractors and construction workers should be informed that when drilling into concrete, the lowest exposure to harmful hand vibration and the best overall productivity occurs when the lowest operational FF is applied during hammer drilling.     

Posture and lifting exposures for daycare workers

Daycare employees, specifically caregivers, are a distinct population that may experience increased risk of injury due to the high exposure to bent postures, lifting conditions and high stress associated with their work. The objectives of the study were to collect up to date data on daycare workers and to compare the data between groups working with children of different ages (Infant, Toddler and Preschool). The study consisted of two distinct phases: Phase 1 – Questionnaire distribution, Phase 2 – Observation and analysis involving three dimensional postural monitoring and video recording as well as an analysis of the low back forces and moments in lifting. Phase 1: Consisted of the distribution of questionnaires to all employees in each of the participating daycares (n = 73). Of the 73 questionnaires distributed 32 responses were obtained (44%). Of the 32 employees who completed the questionnaires, 19 caregivers volunteered to participate in Phase 2 of the study. An additional 5 caregivers participated in phase 2 of the study, but did not complete any questionnaires. The questionnaires indicated 81% of the workers have experienced low back pain. Phase 2: Observational data were collected on site in five local daycares, throughout the first half of each subject's shift (∼3.5 h). Caregivers from each of the three classroom age groups were recruited for participation in the direct observation (Infant: n = 7, Toddler: n = 7, Preschool: n = 8). Posture analysis revealed that on average, workers adopted trunk flexion angles greater than 55°, for 10% of the collection time, and greater than 70°, for 5% of the collection time. These postures correspond to both moderate and severe flexed postures respectively. The lifting analysis (completed using the data recorded in phase 2) revealed that workers lifted with frequencies of 0.25 lifts/minute, lifted a total weight of 501 kg (over 3.3 h) and experienced average compression and shear forces of 3323 N and 371 N, respectively. A between-group comparison showed that when compared to the Preschool group, the Infant (p = 0.008) and Toddler (p = 0.001) groups demonstrated higher relative flexed postures and lifting frequencies, and the Toddler group (p = 0.023) demonstrated higher total weight lifted. Results suggested that these employees experience an elevated risk of low back injury caused by their occupational tasks and thus, further research is required to determine appropriate worker accommodations and safe work practices to help mediate these risks for all daycare caregivers.Relevance to industryIt is thought that the results from this study could lead to the development of safe working and job sharing guidelines for daycare workers.     

External loading during daily living improves high intensity tasks under load

Tactical athletes (TA) perform high intensity tasks while carrying considerable external loads. This study examined the effects of wearing an external load during daily living (ELDL) on high intensity TA tasks. Nine trained men (21 ± 2 years; 180 ± 1 cm; 91.1 ± 4.4 kg) completed 3 weeks of ELDL which consisted of wearing a weighted vest equal to ∼11%, 13%, and 16% body mass 4 days/week; 8 h/day during weeks 1, 2, and 3 of ELDL phase. Weight vests were not worn during training. A 3 week control phase (CON) commenced after ELDL. Four TA performance tasks were practiced during two familiarization sessions before experimental trials. The tasks included a 5 flight, 53 step stair climb, 44 m zig-zag sprint with 2 points of change in direction and kneeling on one knee, 2 × 25 m casualty drag (84 kg), and 8 × 25 yard shuttle run. All tasks were completed while wearing a 12 kg vest. Percentage change in performance from pre-to post-intervention were compared between ELDL and CON using dependent t-tests, and Cohen's D effect size was calculated for absolute change in performance for each task. All tasks displayed trends of robust improvement from baseline to post ELDL, followed by modest drops in performance during CON (p-value range = 0.03 to < 0.001; ES range 1.1–2.6). The addition of ELDL provides a transient enhancement of occupational anaerobic task performances for TA that exceeds resistance and conditioning training alone.     

Data mining using clinical physiology at discharge to predict ICU readmissions

Patient readmissions to intensive care units (ICUs) are associated with increased mortality, morbidity and costs. Current models for predicting ICU readmissions have moderate predictive value, and can utilize up to twelve variables that may be assessed at various points of the ICU inpatient stay. We postulate that greater predictive value can be achieved with fewer physiological variables, some of which can be assessed in the 24 h before discharge. A data mining approach combining fuzzy modeling with tree search feature selection was applied to a large retrospectively collected ICU database (MIMIC II), representing data from four different ICUs at Beth Israel Deaconess Medical Center, Boston. The goal was to predict ICU readmission between 24 and 72 h after ICU discharge. Fuzzy modeling combined with sequential forward selection was able to predict readmissions with an area under the receiver-operating curve (AUC) of 0.72 ± 0.04, a sensitivity of 0.68 ± 0.02 and a specificity of 0.73 ± 0.03. Variables selected as having the highest predictive power include mean heart rate, mean temperature, mean platelets, mean non-invasive arterial blood pressure (mean), mean spO2, and mean lactic acid, during the last 24 h before discharge. Collection of the six predictive variables selected is not complex in modern ICUs, and their assessment may help support the development of clinical management plans that potentially mitigate the risk of readmission.     

Effects of shoulder rotation combined with elbow flexion on discomfort and EMG activity of ECRB muscle

Work related MusculoSkeletal Disorders (WMSDs) are injuries or dysfunctions caused by occupational or non occupational tasks involving bad postures, high frequency of exertions or high force levels. In the present study, the effects of shoulder flexion/extension combined with elbow flexion angle on discomfort score were investigated for repetitive gripping task. A laboratory experimental simulation was conducted. Ten male participants volunteered in this study. Four levels of shoulder flexion/extension (−45° extension, 0° neutral, 45° & 90° flexion) with three levels of elbow flexion angle (45°, 90° & 135°) were taken as levels of independent variables. There were 12 combinations available for each participant and the experiment was conducted on the basis of random order of experimental combinations for each participant. Discomfort score on 100 mm visual analogue scale (VAS) and Electromyography (EMG) activity of Extensor Carpi Radialis Brevis (ECRB) muscle were dependent variables for the analyses. The task for the experiment was of 150N ± 5N grip force at a frequency of 15 exertions/minute for five minutes duration. After performing the MANOVA on the recorded data, the results showed that the shoulder flexion/extension and elbow flexion both were highly significant (p < 0.001). Also it was found that −45° shoulder extension combined with 45° elbow flexion angle was the most discomfort posture. The practical relevance of the study is that, in industrial tasks such posture should be avoided to minimize risk of WMSDs.Relevance to industryThe findings in terms of relationship between discomfort/EMG vs. shoulder rotation combined with elbowflexion are important to design Industrial tasks with the reduced risk of WMSDs. Such as, sheet metal cutting, fabrication of sheet metal work, die casting, and drilling operations may require the shoulder movements in extenion/flexion combined with elbowflexion.     

Characterization of a capacitive tactile shear sensor for application in robotic and upper limb prostheses

This paper presents the characterization of a novel tactile sensor designed to measure shear forces. The sensor design is targeted for use in robotic and prosthetic hands, where haptic feedback or ability to detect shear forces associated with slip are critical. The presented sensor utilizes the principle of differential capacitance to measure the mechanical deflection of the sensor element. The dynamic range of the sensor can be varied by encapsulating the sensor terminal within silicone of varying hardness. The design features ease of mass production, low per-unit-cost, novel overload protection and low wire count, while still preserving the ability to achieve reasonable spatial resolutions and array densities. Mathematical and COMSOL multiphysics models of the sensor are presented, in addition to results from practical experiments. Sensors with a full scale displacement range of ±0.525 mm were produced and the differential capacitance was measured. Shear force transduction was characterized over the range of 0 N–4 N with the sense terminal encapsulated by silicone with a shore A hardness of 20. The effect of elastomer hardness on the sensor's dynamic range was analyzed. The differential capacitance, when measured at each fixed interval, was found experimentally to have a maximum standard deviation of 4.28e?16 F over a ±2 N range. A maximum standard deviation of 1.35e?15 F was measured across characterized full scale sensor range of ±4 N. The sensor design has a sensitivity of 1.967 fF/N of applied force and the sensor output was found to be approximately linear. The coefficient of determination, r², was found to be 0.941.     

Anthropogenic impact on spring bloom dynamics in the Yangtze River Estuary based on SeaWiFS mission (1998–2010) and MODIS (2003–2010) observations

Nutrient output from the Yangtze River to the sea has increased dramatically since the 1960s, and over the past 50 years more than 50,000 reservoirs on the Yangtze River basin have had little impact on water discharge, but have drastically reduced the annual river-to-sea sediment flux, especially after 2000. This can be presumed to have a close link with the 73% (accumulated incidences) of algal bloom reported on China's eastern coast which have taken place in the Yangtze River Estuary (YRE) and its adjacent waters from 2000 to 2009. A conceptual view explains that the algal bloom zone varies between the YRE and mid-shelf waters of the East China Sea, where the optimum balance of light availability and nutrient supply exists. A reduction in turbidity with declining river-to-sea sediment load around the YRE would provide a deeper euphotic layer for the growth of phytoplankton, which is stimulated by eutrophication following increased river-to-sea sewage. Although the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) represents an immature state of ocean colour remote sensing, especially in coastal waters, in general, SeaWiFS serves as a useful tool to highlight the geographical spread and intensity of spring bloom dynamics at the basin scale in the YRE. We suggest that the problem of skin effect bias in spaceborne observation is minimal and that satellite-derived pigment data should be mainly from phytoplankton production when estimating Chl-a during the spring bloom season in the YRE by analysis of bio-optical properties of spring bloom waters. Comparisons between in situ and simultaneous SeaWiFS-derived Chl-a suggest that SeaWiFS standard Chl-a data show comparable results with ship survey data, with a mean ratio (in situ to satellite ratio) of 1.28 ± 0.78 (R ² = 0.71, n = 14, p < 0.001) in spring blooms. We took the seasonal average Chl-a in our defined multi-year highly productive zone in the YRE (28°30′–32°N, 122°–123°30′°E, A) compared with its neighbouring region B from 1998 to 2010, and determined a linear least-squares fit to the trend line. Further analysis in the form of t-tests was run for four seasonal periods, March–April, May–June (spring bloom season), July–August, and September–October. The SeaWiFS-derived 13-year Chl-a mean slope in the spring bloom season is significantly (P = 0.012) increasing by 0.212 mg m^?3 per year. However, such a trend in other seasons is not significant and there is also no significant variation in B over all seasons. Our results show that there is a positive relationship between the annual mean of Chl-a in the spring bloom season in A and annual sewage water discharge at the Yangtze River basin, and similarly a negative relationship between Chl-a and annual river sediment flux was found from 1998 to 2010. Variation in 3-year sediment flux, sewage water discharge, and Chl-a was –25% (±18%), 15% (±5%), and 14% (±6%), respectively. This result supports the findings of previous studies that human activity has a measurable effect on coastal phytoplankton biomass and that the eutrophication effect seems to stimulate increased Chl-a in the spring bloom season, but not on the enhancement of annual Chl-a levels in the YRE.     

Shoulder muscle activity in off-axis pushing and pulling tasks

Workspace design can often dictate the muscular efforts required to perform work, impacting injury risk. Within many environments, industrial workers often use sub-maximal forces in offset directions in to accomplish job tasks. The purpose of this research was to develop methods to estimate shoulder muscle activation during seated, static, sub-maximal exertions in off-axis (non-cardinal) directions. Surface EMG signals were recorded from 14 upper extremity muscles in 20 right-handed university aged, right-handed males (age: 22 ± 3 years, weight: 77.5 ± 11.1 kg, height 179.0 ± 7.0 cm) participated in this study. Each participant performed 60 submaximal exertions (40N) directed at 4 off-axis phase angles of 45° (45°, 135°, 225°, and 315°) in 3 planes (frontal, sagittal, and transverse) in 5 hand locations within a right handed reach envelope. The influence of hand location and force direction on muscle activity was evaluated with a forced-entry stepwise regression model. The ability of previously published on-axis prediction equations to predict muscle activity during these off-axis exertions was also evaluated. Within each muscle, activity levels were affected by both hand location and three-dimensional force direction and activation levels ranged from <1 to 37 %MVE. For each force direction there were 75 predictive equations selected and used, and the specific equation that best predicted activation depended on the muscle, exertion direction and hand location evaluated. This work assists ergonomic workplace design to minimize muscle demands during commonly performed off-axis exertions. These estimated demands can be employed to improve workplace design to reduce workplace injuries and enhance worker productivity.     

The uncertainty in conifer plantation growth prediction from multi-temporal lidar datasets

An evaluation of the use of airborne lidar for multi-temporal forest height growth assessment in a temperate mature red pine (Pinus resinosa Ait.) plantation over a five-year period is presented. The objective was to evaluate the level of uncertainty in lidar-based growth estimates through time so that the optimal repeat interval necessary for statistically meaningful growth measurements could be evaluated. Four airborne lidar datasets displaying similar survey configuration parameters were collected between 2000 and 2005. Coincident with the 2002 and 2005 acquisitions, field mensuration for 126 trees within 19 plots was carried out. Field measurements of stem height were compared to both coincident plot-level laser pulse return (LPR) height percentile metrics and stand level raster canopy height models (CHM).The average plot-level field heights were found to be 23.8 m (standard deviation (σ) = 0.4 m) for 2002 and 25.0 m (σ = 0.6 m) for 2005, with an approximate annual growth rate of 0.4 m/yr (σ = 0.5 m). The standard deviation uncertainty for field height growth estimates over the three year period was 41% at the plot-level (n = 19) and 92% at the individual tree level (n = 126). Of the lidar height percentile metrics tested, the 90th (L90), 95th (L95) and maximum (Lmax) LPR distribution heights demonstrated the highest overall correlations with field-measured tree height. While all lidar-based methods, including raster CHM comparison, tended to underestimate the field estimate of growth, Lmax provided the most robust overall direct estimate (0.32 m/yr, σ = 0.37 m). A single factor analysis of variance demonstrated that there was no statistically significant difference between all plot-level field and Lmax mean growth rate estimates (P = 0.38) and, further, that there was no difference in Lmax growth rate estimates across the examined time intervals (P = 0.59). A power function relationship between time interval and the standard deviation of error in growth estimate demonstrated that over a one-year period, the growth uncertainty was in the range of 0.3 m (∼ 100% of total growth) reducing to less than 0.1 m (∼ 6% of total growth) after 5 years. Assuming a 10% uncertainty is acceptable for operational or research-based conifer plantation growth estimates, this can be achieved at a three-year time interval.