Optimal technology policy: subsidies versus monitoring

We analyze the optimal technology policy to solve a free-riding problem between the members of a RJV. We assume that when intervening the Government suffers an additional adverse selection problem because it is not able to distinguish the value of the potential innovation. Although subsidies and monitoring may be equivalent policy tools to solve firms' free-riding problem, they imply different social losses if the Government is not able to perfectly distinguish the value of the potential innovation. The supremacy of monitoring tools over subsidies is proved to depend on which type of information the Government is able to obtain about firms' R&D performance.

Optimal monitoring to implement clean technologies when pollution is random

We analyze a model where firms chose a production technology which, together with some random event, determines the final emission level. We consider the coexistence of two alternative technologies: a "clean" technology, and a "dirty" technology. The environmental regulation is based on taxes over reported emissions, and on penalties over unreported emissions. We show that the optimal inspection policy is a cut-off strategy, for several scenarios concerning the observability of the adoption of the clean technology and the cost of adopting it. We also show that the optimal inspection policy induces the firm to adopt the clean technology if the adoption cost is not too high, but the cost levels for which the firm adopts it depend on the scenario.

Terrestrial laser scanning for landslides deformation monitoring

Within last few years a new type of instruments called Terrestrial Laser Scanners (TLS) entered to the commercial market. These devices brought a possibility to obtain completely new type of spatial, three dimensional data describing the object of interest. TLS instruments are generating a type of data that needs a special treatment. Appearance of this technique made possible to monitor deformations of very large objects, like investigated here landslides, with new quality level. This change is visible especially with relation to the size and number of the details that can be observed with this new method. Taking into account this context presented here work is oriented on recognition and characterization of raw data received from the TLS instruments as well as processing phases, tools and techniques to do them. Main objective are definition and recognition of the problems related with usage of the TLS data, characterization of the quality single point generated by TLS, description and investigation of the TLS processing approach for landslides deformation measurements allowing to obtain 3D deformation characteristic and finally validation of the obtained results. The above objectives are based on the bibliography studies and research work followed by several experiments that will prove the conclusions.

Bioluminescent sensor proteins for point-of-care therapeutic drug monitoring.

For many drugs, finding the balance between efficacy and toxicity requires monitoring their concentrations in the patient's blood. Quantifying drug levels at the bedside or at home would have advantages in terms of therapeutic outcome and convenience, but current techniques require the setting of a diagnostic laboratory. We have developed semisynthetic bioluminescent sensors that permit precise measurements of drug concentrations in patient samples by spotting minimal volumes on paper and recording the signal using a simple point-and-shoot camera. Our sensors have a modular design consisting of a protein-based and a synthetic part and can be engineered to selectively recognize a wide range of drugs, including immunosuppressants, antiepileptics, anticancer agents and antiarrhythmics. This low-cost point-of-care method could make therapies safer, increase the convenience of doctors and patients and make therapeutic drug monitoring available in regions with poor infrastructure.

Ambulatory blood pressure monitoring in adolescent untreated hypertensive patients.

Ambulatory blood pressure profiles were obtained with the portable semi-automatic blood pressure recorder Remler M2000 in groups of 20 adolescents, 20 young and 20 middle-aged adults and 20 elderly untreated patients, all considered by their physician to be hypertensive. It was found that adolescents who are hypertensive when seeing their physician are more often normotensive outside the physician's office than adult and elderly patients under similar conditions. The increased heart rate variability which was detected in adolescents was not associated with an enhanced blood pressure variability.

Electronic compliance monitoring in resistant hypertension: the basis for rational therapeutic decisions.

OBJECTIVE: Incomplete compliance is one of several possible causes of uncontrolled hypertension. Yet, non-compliance remains largely unrecognized and is falsely interpreted as treatment resistance, because it is difficult to confirm or exclude objectively. The goal of this study was to evaluate the potential benefits of electronic monitoring of drug compliance in the management of patients with resistant hypertension. METHODS: Forty-one hypertensive patients resistant to a three-drug regimen (average blood pressure 156/ 106 +/- 23/11 mmHg, mean +/- SD) were studied prospectively. They were informed that for the next 2 months, their presently prescribed drugs would be provided in electronic monitors, without any change in treatment, so as to provide the treating physician with a measure of their compliance. Thereafter, patients were offered the possibility of prolonging the monitoring of compliance for another 2 month period, during which treatment was adapted if necessary. RESULTS: Monitoring of compliance alone was associated with a significant improvement of blood pressure at 2 months (145/97 +/- 20/15 mmHg, P < 0.01). During monitoring, blood pressure was normalized (systolic < 140 mmHg or diastolic < 90 mmHg) in one-third of the patients and insufficient compliance was unmasked in another 20%. When analysed according to tertiles of compliance, patients with the lowest compliance exhibited significantly higher achieved diastolic blood pressures (P = 0.04). In 30 patients, compliance was monitored up to 4 months and drug therapy was adapted whenever necessary. In these patients, a further significant decrease in blood pressure was obtained (from 150/100 +/- 18/15 to 143/94 +/- 22/11 mmHg, P = 0.04/0.02). CONCLUSIONS: These results suggest that objective monitoring of compliance using electronic devices may be a useful step in the management of patients with refractory hypertension, as it enables physicians to take rational decisions based on reliable and objective data of drug compliance and hence to improve blood pressure control.

Using active learning for monitoring networks design: The example of wind power plants sites evaluation

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highly nonlinear and related to complex topographical features. In this paper, we propose both a nonparametric model to estimate wind speed at different time instants and a procedure to discover underrepresented topographic conditions, where new measuring stations could be added. Compared to space filling techniques, this last approach privileges optimization of the output space, thus locating new potential measuring sites through the uncertainty of the model itself.

Benchmarking therapeutic drug monitoring software: A review of available computer tools

Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

Diagnostic yield of short-term video-EEG monitoring for epilepsy and PNESs: a European assessment.

INTRODUCTION: Although long-term video-EEG monitoring (LVEM) is routinely used to investigate paroxysmal events, short-term video-EEG monitoring (SVEM) lasting <24 h is increasingly recognized as a cost-effective tool. Since, however, relatively few studies addressed the yield of SVEM among different diagnostic groups, we undertook the present study to investigate this aspect. METHODS: We retrospectively analyzed 226 consecutive SVEM recordings over 6 years. All patients were referred because routine EEGs were inconclusive. Patients were classified into 3 suspected diagnostic groups: (1) group with epileptic seizures, (2) group with psychogenic nonepileptic seizures (PNESs), and (3) group with other or undetermined diagnoses. We assessed recording lengths, interictal epileptiform discharges, epileptic seizures, PNESs, and the definitive diagnoses obtained after SVEM. RESULTS: The mean age was 34 (±18.7) years, and the median recording length was 18.6 h. Among the 226 patients, 127 referred for suspected epilepsy - 73 had a diagnosis of epilepsy, none had a diagnosis of PNESs, and 54 had other or undetermined diagnoses post-SVEM. Of the 24 patients with pre-SVEM suspected PNESs, 1 had epilepsy, 12 had PNESs, and 11 had other or undetermined diagnoses. Of the 75 patients with other diagnoses pre-SVEM, 17 had epilepsy, 11 had PNESs, and 47 had other or undetermined diagnoses. After SVEM, 15 patients had definite diagnoses other than epilepsy or PNESs, while in 96 patients, diagnosis remained unclear. Overall, a definitive diagnosis could be reached in 129/226 (57%) patients. CONCLUSIONS: This study demonstrates that in nearly 3/5 patients without a definitive diagnosis after routine EEG, SVEM allowed us to reach a diagnosis. This procedure should be encouraged in this setting, given its time-effectiveness compared with LVEM.