Maximizing biogas production from the anaerobic digestion

This paper presents an optimal control law policy for maximizing biogas production of anaerobic digesters. In particular, using a simple model of the anaerobic digestion process, we derive a control law to maximize the biogas production over a period T using the dilution rate as the control variable. Depending on initial conditions and constraints on the actuator (the dilution rate D(·)), the search for a solution to the optimal control problem reveals very different levels of difficulty. In the present paper, we consider that there are no severe constraints on the actuator. In particular, the interval in which the input flow rate lives includes the value which allows the biogas to be maximized at equilibrium. For this case, we solve the optimal control problem using classical tools of differential equations analysis. Numerical simulations illustrate the robustness of the control law with respect to several parameters, notably with respect to initial conditions. We use these results to show that the heuristic control law proposed by Steyer et al., 1999 [20] is optimal in a certain sense. The optimal trajectories are then compared with those given by a purely numerical optimal control solver (i.e. the “BOCOP” toolkit) which is an open-source toolbox for solving optimal control problems. When the exact analytical solution to the optimal control problem cannot be found, we suggest that such numerical tool can be used to intuiter optimal solutions.     

Comparing interpolation techniques for monthly rainfall mapping using multiple evaluation criteria and auxiliary data sources: A case study of Sri Lanka

Interpolating climatic variables such as rainfall is challenging due to the highly variable nature of meteorological processes, the effects of terrain and geography, and the difficulty in establishing a representative network of stations. While interpolation models are being adapted to include these effects, often the rainfall data contain significant gaps in coverage. In this paper, we evaluated rainfall data from an agro-ecological monitoring network for producing maps of total monthly rainfall in Sri Lanka. We compared four spatial interpolation techniques: inverse distance weighting, thin-plate splines, ordinary kriging, and Bayesian kriging. Error metrics were used to validate interpolations against independent data. Satellite data were used to assess the spatial pattern of rainfall. Results indicated that Bayesian kriging and splines performed best in low and high rainfall, respectively. Rainfall maps generated from the agro-ecological network were found to have accuracies consistent with previous studies in Sri Lanka.     

The contribution of proteomics towards deciphering the enigma of Coxiella burnetii

Coxiella burnetii, the causative agent of Q fever, is an intracellular bacterium and a potential weapon for bioterrorism. The widespread throughout the world, zoonosis is manifested clinically as a self-limited febrile illness, as pneumonia (acute Q fever) or as a chronic illness with endocarditis being its major complication. The recent Netherlands Q fever outbreak has driven the bacterium from a relatively cryptic, underappreciated, “niche” microorganism on the sideline of bacteriology, to one of possibly great impact on public health. Advances in the study of this microorganism proceeded slowly, primarily due to the, until recently, obligatory intracellular nature of the pathogen that in its virulent phase I must be manipulated under biosafety level-3 conditions. Proteomic studies, in particular, have generated a vast amount of information concerning several aspects of the bacterium such as virulence factors, detection/diagnostic and immunogenic biomarkers, inter-/intraspecies variation, resistance to antibiotics, and secreted effector proteins with significant clinical impact. The phenomenon observed following the genomics era, that of generation and accumulation of huge amount of data that ultimately end up unexploited on several databases, begins to emerge in the proteomics field as well. This review will focus on the advances in the field of C. burnetii proteomics through MS, attempting in parallel to utilize some of the proteomics findings by suggesting future directions for the improvement of Q fever diagnosis and therapy.     

An exploration of pen tail gestures for interactions

In this paper, we performed an exploration on the design and evaluation of pen tail gesture, an interaction method that allows the use of pen tail movement to initiate interactions. Based on our interviews with some designers and researchers who regularly used pen-based tools, we conducted three experiments to establish baseline criteria to distinguish intentional pen tail gestures from incidental pen tail movements, and to understand the basic movement behaviors in pen tail gestures. We developed designs and recognition methods of pen gestures, and implemented three application prototypes based on them. Our research can inspire some new designs of pen-based tools and enrich the design repertoire of pen-based user interfaces.     

Scenario analysis and management options for sustainable river basin management: Application of the Elbe DSS

We developed a decision support system (DSS) for sustainable river basin management in the German Elbe catchment (～100,000 km²), called Elbe-DSS. The system integrates georeferenced simulation models and related data sets with a user friendly interface and includes a library function. Design and content of the DSS have been developed in close cooperation with end users and stakeholders. The user can evaluate effectiveness of management actions like reforestation, improvement of treatment plant technology or the application of buffer strips under the influence of external constraints on climate, demographic and agro-economic changes to meet water management objectives such as water quality standards and discharge control. The paper (i) describes the conceptual design of the Elbe-DSS, (ii) demonstrates the applicability of the integrated catchment model by running three different management options for phosphate discharge reduction (reforestation, erosion control and ecological-farming) under the assumption of regional climate change based on IPCC scenarios, (iii) evaluates the effectiveness of the management options, and (iv) provides some lessons for the DSS-development in similar settings. The georeferenced approach allows the identification of local inputs in sub-catchments and their impact on the overall water quality, which helps the user to prioritize his management actions in terms of spatial distribution and effectiveness.     

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.     

Improving pedestrians’ navigation safety at night by enhancing legibility of foreground and background information on the display

Traffic intersections are dangerous areas for pedestrians at night, primarily when people use their mobile phones while walking; pedestrians’ line of sight switches between their phones and the environment, which causes inattentional blindness during emergencies. The salience of the foreground and background information is different by the lightness conditions; therefore, identifying the lightness level of the foreground and background is critical. In this study, the brightness of urban traffic intersection scenes in the nighttime was analyzed, and improved color tones of the navigation interface for enhancing information recognition were identified. Moreover, identify the balance of visual attention by adjusting lightness and color treatment between foreground and background information. A glance legibility experiment indicated that a warm color tone with contrast and gamma correction under a lighting value of 65 in the LAB color mode is the optimal recognition combination. The results of this study indicated that low gamma under high lighting effectively reduced glare-related distractions and resulted in the lowest error rate in background information recognition. This paper proposes increasing the visual attention of urban pedestrians during nighttime navigation through the balancing of the lighting of the foreground interface and the color treatment of the background. Navigating at nighttime can be safer when their attention toward the environment increases and decreases attention distraction.     

Establishment-level occupational safety analytics: Challenges and opportunities

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the “big” data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.