A Computerized Medical Standards System to Help Place Impaired Employees

1996 ◽  
Vol 35 (04/05) ◽  
pp. 317-323
Author(s):  
M. Halpern
Keyword(s):  
Knowledge Base ◽  
Distribution System ◽  
Work Conditions ◽  
Rehabilitation Program ◽  
Task Demands ◽  
Physical Ability ◽  
Medical Standards ◽  
Physical Abilities ◽  
The Impact ◽  
Job Profile

Abstract:The paper describes a knowledge-distribution system that supports decisions on placement of impaired employees. The knowledge base consists of job profiles and medical profiles. The job profiles list tasks and the physical abilities they require. Twenty-one abilities describe the task demands. Active workers rated the exertion, frequency and importance of the physical ability required for each task. Thirty-nine work conditions were rated this way. Using identical scales, experts assessed the impact of impairments on the physical abilities of individuals and the tolerance of work conditions. The screening matches the job profile against the impairment profile. This process has been automated. The program lists tasks and work conditions that may compromise an impaired employee. This information can be used to accommodate employees, restrict duties or design a rehabilitation program. Also, the paper discusses the impact of the system on the operations of medical services within an organization.

Impact of Particulate Matter on Distribution System Disinfection Efficacy

2008 ◽  
Vol 43 (1) ◽  
pp. 55-62 ◽  
Author(s):  
Linda Wojcicka ◽  
Carole Baxter ◽  
Ron Hofmann
Keyword(s):  
Helicobacter Pylori ◽  
Particulate Matter ◽  
Distribution System ◽  
Contact Time ◽  
Water Disinfection ◽  
Sphingomonas Paucimobilis ◽  
Soil Corrosion ◽  
Log Reduction ◽  
Drinking Water Disinfection ◽  
The Impact

Abstract Microorganisms have been shown to survive drinking water disinfection and remain viable in disinfected waters despite the presence of disinfectant residuals. This may be partially attributed to protection by particulate matter. The aim of this study was to determine the effects of the presence of particulate matter on disinfection kinetics. Sphingomonas paucimobilis ATCC 10829 and Helicobacter pylori ATCC 43504 were used in inactivation experiments in the presence and absence of soil, corrosion, and wastewater particles. The results showed that the presence of such particles tended to inhibit chlorine and monochloramine inactivation, although the magnitude of the impact under the conditions tested was small (e.g., 1-log reduction in inactivation for several minutes of contact time in the presence of less than 1 mg/L of disinfectant).

043 Sleep Restriction Affects Memory in Healthy Adults: Preliminary Findings

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A18-A19
Author(s):  
Molly Zimmerman ◽  
Christiane Hale ◽  
Adam Brickman ◽  
Lok-Kin Yeung ◽  
Justin Cochran ◽  
...  
Keyword(s):  
Working Memory ◽  
Negative Impact ◽  
Positive Impact ◽  
Healthy Adults ◽  
Task Demands ◽  
Sleep Restriction ◽  
Neuropsychological Function ◽  
Wake Time ◽  
Sleep Condition ◽  
The Impact

Abstract Introduction Sleep loss has a range of detrimental effects on cognitive ability. However, few studies have examined the impact of sleep restriction on neuropsychological function using an experimental design. The goal of this study was to examine the extent to which maintained insufficient sleep affects cognition in healthy adults compared to habitual adequate sleep. Methods This study used a randomized, crossover, outpatient sleep restriction design. Adults who regularly slept at least 7 h/night, verified by 2 weeks of screening with actigraphy, completed 2 phases of 6 weeks each: habitual sleep (>7 h of sleep/night) or sleep restriction (habitual sleep minus 1.5 h) separated by a 6-week washout period. During the sleep restriction phase, participants were asked to delay their bedtime by 1.5 hours/night while maintaining their habitual wake time. Neuropsychological function was evaluated with the NIH Toolbox Cognition Battery at baseline (week 0) and endpoint (week 6) of each intervention phase. The NIH Toolbox evaluates a range of cognitive abilities, including attention, executive functioning, and working memory. General linear models with post hoc paired t-tests were used to assess demographically-adjusted test scores prior to and following each sleep condition. Results At the time of analyses, 16 participants were enrolled (age 34.5□14.5 years, 9 women), 10 of whom had completed study procedures. An interaction between sleep condition and testing session revealed that individuals performed worse on List Sorting, a working memory test, after sleep restriction but improved slightly after habitual sleep (p<0.001). While not statistically reliable, the pattern of test results was similar on the other tests of processing speed, executive function, and attention. Conclusion In these preliminary results from this randomized experimental study, we demonstrated that sleep restriction has a negative impact while stable habitual adequate sleep has a positive impact on working memory, or the ability to temporarily hold information in mind while executing task demands. This finding contributes to our understanding of the complex interplay between different aspects of sleep quality (i.e., both sleep restriction as well as the maintenance of stable sleep patterns) on cognition and underscores the importance of routine sleep screening as part of medical evaluations. Support (if any):

scholarly journals Network Attack Path Selection and Evaluation Based on Q-Learning

2020 ◽  
Vol 11 (1) ◽  
pp. 285
Author(s):  
Runze Wu ◽  
Jinxin Gong ◽  
Weiyue Tong ◽  
Bing Fan
Keyword(s):  
Distribution System ◽  
Path Selection ◽  
Cyber Attacks ◽  
Power Distribution System ◽  
Q Learning ◽  
Attack Model ◽  
Cross Domain ◽  
Time Operation ◽  
Attack Path ◽  
The Impact

As the coupling relationship between information systems and physical power grids is getting closer, various types of cyber attacks have increased the operational risks of a power cyber-physical System (CPS). In order to effectively evaluate this risk, this paper proposed a method of cross-domain propagation analysis of a power CPS risk based on reinforcement learning. First, the Fuzzy Petri Net (FPN) was used to establish an attack model, and Q-Learning was improved through FPN. The attack gain was defined from the attacker’s point of view to obtain the best attack path. On this basis, a quantitative indicator of information-physical cross-domain spreading risk was put forward to analyze the impact of cyber attacks on the real-time operation of the power grid. Finally, the simulation based on Institute of Electrical and Electronics Engineers (IEEE) 14 power distribution system verifies the effectiveness of the proposed risk assessment method.

scholarly journals Electric Vehicles in Jordan: Challenges and Limitations

2021 ◽  
Vol 13 (6) ◽  
pp. 3199
Author(s):  
Laith Shalalfeh ◽  
Ashraf AlShalalfeh ◽  
Khaled Alkaradsheh ◽  
Mahmoud Alhamarneh ◽  
Ahmad Bashaireh
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Distribution Systems ◽  
Environmental Benefits ◽  
System Stability ◽  
Loading Conditions ◽  
Stability Margins ◽  
High Penetration ◽  
Node Distribution ◽  
The Impact

An increasing number of electric vehicles (EVs) are replacing gasoline vehicles in the automobile market due to the economic and environmental benefits. The high penetration of EVs is one of the main challenges in the future smart grid. As a result of EV charging, an excessive overloading is expected in different elements of the power system, especially at the distribution level. In this paper, we evaluate the impact of EVs on the distribution system under three loading conditions (light, intermediate, and full). For each case, we estimate the maximum number of EVs that can be charged simultaneously before reaching different system limitations, including the undervoltage, overcurrent, and transformer capacity limit. Finally, we use the 19-node distribution system to study these limitations under different loading conditions. The 19-node system is one of the typical distribution systems in Jordan. Our work estimates the upper limit of the possible EV penetration before reaching the system stability margins.

scholarly journals A new meta-heuristic pathfinder algorithm for solving optimal allocation of solar photovoltaic system in multi-lateral distribution system for improving resilience

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Varaprasad Janamala
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Voltage Stability ◽  
Optimal Allocation ◽  
Photovoltaic System ◽  
Solar Photovoltaic ◽  
Voltage Profile ◽  
Pv System ◽  
Solar Photovoltaic System ◽  
The Impact

AbstractA new meta-heuristic Pathfinder Algorithm (PFA) is adopted in this paper for optimal allocation and simultaneous integration of a solar photovoltaic system among multi-laterals, called interline-photovoltaic (I-PV) system. At first, the performance of PFA is evaluated by solving the optimal allocation of distribution generation problem in IEEE 33- and 69-bus systems for loss minimization. The obtained results show that the performance of proposed PFA is superior to PSO, TLBO, CSA, and GOA and other approaches cited in literature. The comparison of different performance measures of 50 independent trail runs predominantly shows the effectiveness of PFA and its efficiency for global optima. Subsequently, PFA is implemented for determining the optimal I-PV configuration considering the resilience without compromising the various operational and radiality constraints. Different case studies are simulated and the impact of the I-PV system is analyzed in terms of voltage profile and voltage stability. The proposed optimal I-PV configuration resulted in loss reduction of 77.87% and 98.33% in IEEE 33- and 69-bus systems, respectively. Further, the reduced average voltage deviation index and increased voltage stability index result in an improved voltage profile and enhanced voltage stability margin in radial distribution systems and its suitability for practical applications.

scholarly journals The Impact of Work Characteristics on Social Distancing: Implications at the Time of COVID-19

2021 ◽  
Vol 18 (10) ◽  
pp. 5074
Author(s):  
Keisuke Kokubun ◽  
Yoshinori Yamakawa
Keyword(s):  
Information Processing ◽  
Multiple Regression ◽  
Explanatory Power ◽  
Work Conditions ◽  
Multiple Regression Model ◽  
Social Characteristics ◽  
Work Characteristics ◽  
Social Distancing ◽  
Using Data ◽  
The Impact

The coronavirus disease (COVID-19) continues to spread globally. While social distancing has attracted attention as a measure to prevent the spread of infection, some occupations find it difficult to implement. Therefore, this study aims to investigate the relationship between work characteristics and social distancing using data available on O*NET, an occupational information site. A total of eight factors were extracted by performing an exploratory factor analysis: work conditions, supervisory work, information processing, response to aggression, specialization, autonomy, interaction outside the organization, and interdependence. A multiple regression analysis showed that interdependence, response to aggression, and interaction outside the organization, which are categorized as ”social characteristics,” and information processing and specialization, which are categorized as “knowledge characteristics,” were associated with physical proximity. Furthermore, we added customer, which represents contact with the customer, and remote working, which represents a small amount of outdoor activity, to our multiple regression model, and confirmed that they increased the explanatory power of the model. This suggests that those who work under interdependence, face aggression, and engage in outside activities, and/or have frequent contact with customers, little interaction outside the organization, and little information processing will have the most difficulty in maintaining social distancing.

A neuropsychological group rehabilitation program with institutionalized elderly

2016 ◽  
Vol 33 (S1) ◽  
pp. s235-s235
Author(s):  
L. Lemos ◽  
H. Espírito-Santo ◽  
S. Simões ◽  
F. Silva ◽  
J. Galhardo ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Depressive Symptomatology ◽  
Randomized Study ◽  
Geriatric Depression Scale ◽  
Depression Scale ◽  
Rehabilitation Program ◽  
Post Intervention ◽  
Institutionalized Elderly ◽  
Group Rehabilitation ◽  
The Impact

IntroductionElderly institutionalization involves an emotional adaptation and the research shows that the risk of depression increases.ObjectivesEvaluate the impact of a neuropsychological group rehabilitation program (NGRP) on depressive symptomatology of institutionalized elderly.AimsNGRP influences the decrease of depressive symptoms.MethodsElderly were assessed pre- and post-intervention with the Geriatric Depression Scale (GDS) and divided into a Rehabilitated Group (RG), a Waiting List Group (WLG), and a Neutral Task Group (NTG).ResultsIn this randomized study, before rehabilitation, 60 elderly people (RG; 80.31 ± 8.98 years of age; 74.2% women) had a mean GDS score of 13.33 (SD = 9.21). Five elderly included in the NTG (80.13 ± 10.84 years; 75.0% women) had a mean GDS score of 10.60 (SD = 4.72). Finally, 29 elderly in the WLG (81.32 ± 6.68 years; 69.0% women) had a mean GDS score of 14.93 (SD = 6.02). The groups were not different in GDS baseline scores (F = 0.74; P = 0.478). ANCOVA has shown significant differences (P < 0.05) in GDS scores between the three groups after 10 weeks. Sidak adjustment for multiple comparisons revealed that elderly in the WLG got worse scores in GDS, comparing with elderly in RG (P < 0.01), and with elderly in NTG (P < 0.05).ConclusionsElderly that are not involved in a task get worse in depressive symptomatology. Being involved in a structured group task means lower depressive symptoms and being in a NGRP means even greater results.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Optimal Capacitors Placement of Distribution Systems Using 2nd Order Power Loss Sensitivity Analysis and Hierarchical Clustering

2014 ◽  
Vol 986-987 ◽  
pp. 377-382 ◽  
Author(s):  
Hui Min Gao ◽  
Jian Min Zhang ◽  
Chen Xi Wu
Keyword(s):  
Sensitivity Analysis ◽  
Hierarchical Clustering ◽  
Distribution System ◽  
Power Flow ◽  
Distribution Systems ◽  
Reactive Power ◽  
Digital Simulation ◽  
Second Order ◽  
First Order ◽  
The Impact

Heuristic methods by first order sensitivity analysis are often used to determine location of capacitors of distribution power system. The selected nodes by first order sensitivity analysis often have virtual high by first order sensitivities, which could not obtain the optimal results. This paper presents an effective method to optimally determine the location and capacities of capacitors of distribution systems, based on an innovative approach by the second order sensitivity analysis and hierarchical clustering. The approach determines the location by the second order sensitivity analysis. Comparing with the traditional method, the new method considers the nonlinear factor of power flow equation and the impact of the latter selected compensation nodes on the previously selected compensation location. This method is tested on a 28-bus distribution system. Digital simulation results show that the reactive power optimization plan with the proposed method is more economic while maintaining the same level of effectiveness.

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