Produce is responsible for 46% of all foodborne illnesses in the USA. Salmonella enterica causes 19,000 hospitalizations each year, and has been associated with produce. Presently, chlorine based sanitizers are most often used, however organic matter reduces its antimicrobial activity. Bacteriophage treatments are an all-natural, alternative method for pathogen inactivation. The objective of this study was to determine the efficacy of a five-strain bacteriophage treatment against a S. enterica cocktail in simulated wash waters at different temperatures. Bacteriophage and S. enterica were enumerated in simulated wash water solutions. One set of experiments studied bacteriophage and S. enterica growth in TSB+vegetable solutions. Bacteriophage behavior was not statistically different (p < 0.05) in spinach, romaine, or iceberg lettuce across different concentrations of organic matter. S. enterica reduction was approximately 2 log over 135 minutes for vegetable solutions and for the TSB control. S. enterica reduction was only 0.5 log in water solutions. The next set of experiments studied bacteriophage and S. enterica growth in vegetable solutions. Spinach wash water and tryptone soy broth solutions (TSB) at 20 °C and 37 °C. S. enterica was not reduced in spinach solution studies at 20 °C and 37 °C or at broth solutions at 20 °C. However, S. enterica was effectively reduced 4 log in broth solutions at 37 °C up to 7.5 hours, but grew to high levels after 24 hours. These results indicate that bacteriophage could not effectively control bacteria levels in produce wash water, and may need to be optimized.

Background: Lay press investigations have been published that describe pharmacist errors and the workplace environment in the community pharmacy setting. However, recent studies that explore pharmacists' perceptions of patient safety in the workplace are limited. Objectives: 1) To describe pharmacists' perceptions of workplace patient safety; 2) To compare pharmacists' perceptions of workplace patient safety across practice setting type, pharmacist roles, average hours worked per shift, and average hours worked per week. Methods: Actively licensed Tennessee pharmacists were recruited from January 1 and June 30, 2019 to complete a 13-item survey of workplace patient safety perceptions ( =1391). Descriptive statistics were calculated, and nonparametric statistical tests employed to compare differences in perceptions across practice setting type, pharmacist roles, and hours worked per shift and per week. Results: Statistically significant differences in workplace patient safety perceptions were noted across practice setting type (p values <.001) and pharmacist roles (p values <.001). The extent to which pharmacists agreed/strongly agreed that their employer provides a work environment that allows for safe patient care ranged from 29.7% of chain community pharmacists to 85% of compounding pharmacists. Fifty-two percent of staff pharmacists, 56.5% of relief pharmacists, and 58.5% of managers/pharmacists in charge agreed or strongly agreed that their employer provides a work environment that allows for safe patient care, whereas 89.3% of regional managers/directors/vice-presidents and 72.5% of clinical/specialty pharmacists indicated the same. Average hours per shift was inversely correlated with perceptions of workplace patient safety (p values <.001). Conclusion: Tennessee pharmacists' perceptions of workplace patient safety varied widely across practice setting type and pharmacist roles. Perceptions of safety were notably lower in the chain community pharmacy setting. Additional research is warranted to better understand the relationship between pharmacist perceptions and quantifiable patient safety metrics, particularly in the chain community pharmacy setting.

No description available.

In high- risk industries, such as aviation, safety is a key for organization survivor. Most accidents involve human losses and bring substantial cost to organizations. Accidents can devastate the reputation and profitability of any organization. In aviation, more than 80% of aircraft accidents are related to human errors. Safety culture has substantial impact on the success of any organization. Employees' performance and behaviors are influenced by their perception of safety culture within their organization. In the aviation industry, pilots are considered the last resort to prevent accidents or mishaps in the air or ground. The focus on pilots' perception of safety culture is vital to understand how the airline can influence pilots' behaviors in the flight deck, and provide opportunities to minimize risk or unsafe behavior in the future. The present study examined the effect of safety culture on safety performance among pilots of Saudi Airlines. Safety performance was measured by pilot attitude toward violations and pilot error behavior. The study further analyzed the mediating role of pilot commitment to the airline between safety culture and measures of safety performance. The study used a quantitative approach using survey questionnaire to collect the data. A total of 247 commercial airline pilots, captain and first officer, flying at Saudi Airlines voluntarily participated in the study. Confirmatory factor analysis was conducted to validate each latent construct. The study used structural equation modeling (SEM) to analyze the relationship between all variables in the study using AMOS 22 software. The study results revealed that safety culture had a direct effect on pilot attitude toward violations and indirect effect on pilot error behavior. Moreover, safety culture had strong effect on enhancing pilot commitment to the airline. The mediating role of pilot commitment to the airline was not significant, and could not mediate the relationship between safety culture and measures of safety performance. The present research contributed to the current state of knowledge about the significant role of safety culture as a main predictor of safety performance in civil aviation. The present study contributes to aviation psychology by analyzing the effect of safety culture as a predictor for improving pilot commitment to the airline. In addition, this research analyzed the effect of safety culture on pilot attitude toward violations and pilot error behavior. Study findings can be used by airline management to better identify causes of unsafe behavior inside the cockpit. The outcomes of this research emphasize the role of management in shaping and affecting employees' behaviors and attitudes.

Decline in the growth rate of worker productivity as well as the failure of other types of organizational development strategies to improve productivity has resulted in considerable interest in strategies to change employee behavior. This situation has led to the rapid growth of organizational behavior modification (OBM) as an approach to organizational change. Performance feedback interventions have been used in numerous settings to improve work behaviors (Prue & Fairbanks, 1981). OBM has worked especially well in improving safe work behavior in the work place. However, when new approaches are used in dealing with human behavior, much systematic, thorough research must be conducted to ascertain the benefits of the components of that approach. OBM has basically four components: observation, measurement feedback, and reinforcement. The focus of this study is the component of feedback. Many studies, which will be discussed in more detail later, have dealt with feedback in conjunction with other factors, such as supervisory praise, training, and goal-setting. These other factors have confounded the value of feedback. Therefore, the purpose of this study is to ascertain the value of feedback to OBM.

No description available.

The construction industry leads the private sector with the most fatalities of any industry in the United States. With an expected growth of the industry in the next century, safe work environments are imperative. They will impact the bottom line of the industry through the reduction of fatal and non-fatal injuries. Although the causes of injuries and illnesses in construction have long been tracked, reported and researched, the industry continues to lead in occupational related fatal and non-fatal injuries. It is critical to understand if a tradeoff exists between safety and productivity to avoid shortcut behaviors in the field. This is specifically important due to the number of contractors, subcontractors and laborers that participate in the different projects. The overall objective of this research was to increase the understanding of the relationship between perceived and observed safety and productivity and to understand the variability in perception and behavior between crews working for the same general contractor in the homebuilding construction industry. For this research, questionnaires and behavioral observations were employed. The results demonstrated a significant moderate positive relationship between safety climate and perceived risk behavior at the crew level. A model was developed that suggests that safety climate and work ownership are predictors of perceived risk behaviors. This relationship is important to understand since employee attitudes, safety commitment and organizational factors may affect acceptability of safety processes and procedures. The differences among construction crews were evaluated at two levels, individual crews and critical path groups. All tests were significant for differences among crews. To further understand these differences, crews were grouped in accordance with the critical path of a homebuilding schedule. A significant difference existed for risk behavior, productivity loss and work ownership. Behavioral observations were used to evaluate crew performance. Top contributing behaviors of productivity, safety and waste were identified. The top behaviors provide improvement areas for productivity, safety and waste. Overall, learning from this research provided insight into the relationships between safety climate, risk behavior, productivity and work ownership. Understanding this relationship can contribute to the design of safety interventions, and consequently, the reduction of injuries and fatalities. / Ph. D.

Guardrails were designed to deter vehicle access to off-road areas and consequently prevent hitting rigid fixed object alongside the road (e.g., trees, utility poles, traffic barriers, etc.). However, guardrails cause 10% of deaths of vehicle-to-fixed object crashes which has attracted attention in the highway safety community on the vehicle-based injury criteria used in guardrail regulations. The objectives of this study were 1) to develop and validate a Finite Element (FE) model of the ET-Plus, a commonly used energy-absorbing guardrail end terminal; 2) to examine the conditions of in-service end terminals, and to evaluate the performance of the damaged relative to undamaged end terminals in simulated impacts; 3) to investigate both full-body and body region driver injury probabilities during car-to-end terminal crashes using dummy and human body FE models; to analyze the relationship between the vehicle-based crash severity metrics used currently in regulations and the injury probabilities assessed using biomechanics injury criteria; and 4) to quantify the influence of pre-impact conditions on injury probabilities. In this dissertation, an ET-Plus FE model was developed based on publicly available data on ET-Plus dimensions and material properties. The model was validated against the NCHRP-350 crash tests. The developed ET-Plus model was used to develop to five damaged ET-Plus whose damage patterns were identified based on an investigation of in-service end terminals mounted along U.S. roads. It was observed that damaged end terminals usually increase collision severity compared to undamaged end terminals. Meanwhile, a total of 40 FE impact simulations between a car with a dummy/human body model in the driver seat and an end terminal model were performed in various configurations. The vehicle-based severity metrics were observed to be correlated to full-body and certain body-region injury risks while no head injury risk could be predicted. The results pointed out that more advanced vehicle-based metrics should be proposed and investigated to improve the predictability in terms of occupant injury risks in the crash tests. The simulation models could also supplement crash compliance tests of new hardware designs, by investigating their safety performance for a large variety of pre-impact conditions, observed in traffic accidents, but not included the compliance tests. / Doctor of Philosophy / Guardrails were designed to deter vehicle access to off-road areas and consequently prevent hitting rigid fixed object alongside the road (e.g., trees, utility poles, traffic barriers, etc.). However, guardrails cause 10% of deaths of vehicle-to-fixed object crashes which has attracted attention in the highway safety community on the vehicle-based injury criteria used in guardrail regulations. The objectives of this study were 1) to develop and validate a Finite Element (FE) model of the ET-Plus, a commonly used energy-absorbing guardrail end terminal; 2) to examine the conditions of in-service end terminals, and to evaluate the performance of the damaged relative to undamaged end terminals in simulated impacts; 3) to investigate both full-body and body region driver injury probabilities during car-to-end terminal crashes using dummy and human body FE models; to analyze the relationship between the vehicle-based crash severity metrics used currently in regulations and the injury probabilities assessed using biomechanics injury criteria; and 4) to quantify the influence of pre-impact conditions on injury probabilities. In this dissertation, an ET-Plus FE model was developed based on publicly available data on ET-Plus dimensions and material properties. The model was validated against the NCHRP-350 crash tests. The developed ET-Plus model was used to develop to five damaged ET-Plus whose damage patterns were identified based on an investigation of in-service end terminals mounted along U.S. roads. It was observed that damaged end terminals usually increase collision severity compared to undamaged end terminals. Meanwhile, a total of 40 FE impact simulations between a car with a dummy/human body model in the driver seat and an end terminal model were performed in various configurations. The vehicle-based severity metrics were observed to be correlated to full-body and certain body-region injury risks while no head injury risk could be predicted. The results pointed out that more advanced vehicle-based metrics should be proposed and investigated to improve the predictability in terms of occupant injury risks in the crash tests. The simulation models could also supplement crash compliance tests of new hardware designs, by investigating their safety performance for a large variety of pre-impact conditions, observed in traffic accidents, but not included the compliance tests.

Yes / Machine learning (ML) is increasingly employed for automating complex tasks, specifically in autonomous driving. While ML applications bring us closer to fully autonomous systems, they simultaneously introduce security and safety risks specific to safety-critical systems. Existing methods of software development and systems based on ML are fundamentally different. Moreover, the existing certification methods for automotive systems cannot fully certify the safe operation of ML-based components and subsystems. This is because existing safety certification criteria were formulated before the advent of ML. Therefore, new or adapted methods are needed to certify ML-based systems. This article analyses the existing safety standard, ISO26262, for automotive applications, to determine the certifiability of ML approaches used in low-risk automotive applications. This will contribute towards addressing the task of assuring the security and safety of ML-based autonomous driving systems, particularly for low-risk automotive applications, to gain the trust of regulators, certification agencies, and stakeholders.

The increasingly urbanized world needs a solution to solve one of the most difficult problems – traffic congestion and safety. Researchers, consultants, and local officials are all attempting to solve these problems with different methods. However, it is apparent that understanding the driving behaviors on the roadway network and implementing roadway configurations accordingly is one of the great solutions. Therefore, the modeling of driving behavior would be the focus of this two-part thesis. Chapter two of this thesis will elaborate on the modeling of various driving behavior types in the microsimulation software by providing an easier-to-calibrate alternative for the driver behavior model in the microsimulation. The calibration method would leverage VISSIM, its highly customizable External driver model (EDM) API, JMP Pro's experiment design and sensitivity analysis, and SSAM's trajectory analysis. Then a set of driver model parameters are produced through sensitivity analysis, which is effective in producing a set of traffic conflicts that matches a preset target. Chapter three of this thesis focuses on simulating aggressive driving behaviors in a microsimulation and driving simulator co-simulation environment. Two co-simulation platforms are demonstrated, and the data collection are done in the VISSIM-Unity platform to collect microscopic driving data and trajectory data from the aggressive driver. Data analysis are performed on both datasets and determine the aggressive driver's safety impact. / Master of Science / The increasingly urbanized world needs a solution to solve one of the most difficult problems – traffic jams and safety. Researchers, engineers, and local officials are all attempting to solve these problems with different methods. However, it is apparent that understanding people's driving behavior on the road and designing the roads and policies to cater to these driving behaviors is one of the great solutions. Therefore, the modeling of driving behavior would be the focus of this two-part thesis. Chapter two of this thesis will experiment with a traffic simulator (which is a tool used for designing and simulating different road configurations like roundabouts and numbers of lanes) and provide an easier and more accurate way to represent various driving styles in the traffic simulator. The calibration method would leverage a driving simulator called VISSIM, an adjustable driver behavior model, a vehicle route tracker, and a vehicle route conflict analysis tool. Then a set of driving behavior parameters would be produced to match the possible traffic accident count in the traffic simulator. Chapter three of this thesis focuses on simulating aggressive driving behaviors in a traffic simulator and driving simulator (like that of those with a steering). Two driving simulator platforms are tested, and the data collection are done in one of the platforms to collect driving data and vehicle route tracker data from the aggressive driver. Data analysis are performed on both types of data and determine the aggressive driver's safety impact.