34 research outputs found
Setting targets with interval data envelopment analysis models via wang method
Get PDFData envelopment analysis (DEA) is a mathematical programming for evaluating the relative efficiency of decision making units (DMUs). The first DEA model (CCR model) assumed for exact data, later some authors introduced the applications of DEA which the data was imprecise. In imprecise data envelopment analysis (IDEA) the data can be ordinal, interval and fuzzy. Data envelopment analysis also can be used for the future programming of organizations and the response of the different policies, which is related to the target setting and resource allocation. The existing target model that conveys performance based targets in line with the policy making scenarios was defined for exact data. In this paper we improved the model for imprecise data such as fuzzy, ordinal and interval data. To deal with imprecise data we first established an interval DEA model. We used one of the methods to convert fuzzy and ordinal data into the interval data. A numerical experiment is used to illustrate the application to our interval model
High efficacy and low toxicity of weekly docetaxel given as first-line treatment for metastatic breast cancer
Get PDFBackground: Docetaxel is one of the most effective antitumor agents currently available for the treatment of metastatic breast cancer (MBC). This phase II multicenter study prospectively analyzed the efficacy and toxicity of docetaxel given on a weekly schedule as first-line treatment of metastatic breast cancer. Patients and Methods: All patients received docetaxel, 35 mg/m(2) weekly for 6 weeks, followed by 2 weeks of rest. Subsequent cycles ( 3 weeks of treatment, 2 weeks of rest) were given until a maximum of 5 cycles or disease progression. Premedication consisted of 8 mg dexamethasone intravenously 30 min prior to the infusion of docetaxel. Results: Fifty-four patients at a median age of 58 years with previously untreated MBC were included in the study. A median of 10 doses ( median cumulative dose 339 mg/m(2)) was administered ( range: 2 - 18). The overall response rate was 48.1% ( 95% CI: 34 - 61%, intent-to-treat). Median survival was 15.8 months and median time to progression was 5.9 months ( intent-to-treat). Hematological toxicity was mild with absence of neutropenia-related complications. Grade 3 neutropenia was observed in 3.7% of patients and grade 3 and 4 anemia was observed in 5.6 and 1.9% of patients, respectively. Conclusion: The weekly administration of docetaxel is highly efficient and safe as first-line treatment for MBC and may serve as an important treatment option specifically in elderly patients and patients with a reduced performance status. Copyright (C) 2005 S. Karger AG, Basel
ASSESSMENT AND DEVELOPMENT OF EMERGENCY TRANSPORTATION INDICATORS (CASE STUDY: INFRASTRUCTURES OF TEHRAN MUNICIPALITY, DISTRICT NO.1
No full textIn densely populated urban areas, at the time of earthquake, how to accurately determine the risky zone, to take effective measures to evacuate inhabitants quickly out of dangerous areas and to minimize the unexpected losses are major concerns of urban managers and government authorities. Over the last two decades, there has been considerable interest in modeling emergency transportation and evacuation for a well-defined zone and event scenario. Emergency transportation is one of the issues that become significantly important after a disaster. Once a disaster occurs (particularly earthquakes), the demand for infrastructure reaches its maximum and often leads to a heavy traffic. On the other hand, due to the resulted damages, the roads resiliency is reduced. To expedite the emergency transportation, the most optimal routes should be taken into account. The emergency transportation aims to transfer the affected population to the safe area, keeps the traffic in order and recovers
the normal status in time. Efficiency parameters can embody and affect the emergency transportation and evacuation efficiency in the emergency evacuation, including evacuation time, mean evacuation speed, travel time and vehicle quality. By determining the optimal routes for emergency transportation in the possible shortest time, the highest possible services will be provided resulting in an increase in the capacity for the urban crisis management. The significance of determining and optimizing emergency ransporting routes, however, has not been fully appreciated in Iran. The present analytical-descriptive study is aimed at determining the parameters influencing the determination of optimal routes for emergency. Therefore, analytical hierarchy process is used to extract such parameters and implement them in Tehran district No. 1.As a result, 17 parameters affect on the determining the optimal paths. The major parameters include safety, traffic, length of path and culture. Population density is the most significant factor with 23.55 percent, and the quality of vehicles is the least significant one with 2.13 percent of significance
337 Pallidocortical Beta Coherence Decreases with Pallial Deep Brain Stimulation in Parkinson Disease
No full textEvaluation of debonding in CFRP-epoxy adhesive single-lap joints using eddy current pulse-compression thermography
No full textFarm-based cropping pattern optimization and conjunctive use planning using piece-wise genetic algorithm (PWGA): a case study
No full textApplicability of HEC-RAS & GFMS tool for 1D water surface elevation/flood modeling of the river: a Case Study of River Yamuna at Allahabad (Sangam), India
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Imaging versus electrographic connectivity in human mood-related fronto-temporal networks
No full textBackgroundThe efficacy of psychiatric DBS is thought to be driven by the connectivity of stimulation targets with mood-relevant fronto-temporal networks, which is typically evaluated using diffusion-weighted tractography.ObjectiveLeverage intracranial electrophysiology recordings to better predict the circuit-wide effects of neuromodulation to white matter targets. We hypothesize strong convergence between tractography-predicted structural connectivity and stimulation-induced electrophysiological responses.MethodsEvoked potentials were elicited by single-pulse stimulation to two common DBS targets for treatment-resistant depression - the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VCVS) - in two patients undergoing DBS with stereo-electroencephalographic (sEEG) monitoring. Evoked potentials were compared with predicted structural connectivity between DBS leads and sEEG contacts using probabilistic, patient-specific diffusion-weighted tractography.ResultsEvoked potentials and tractography showed strong convergence in both patients in orbitofrontal, ventromedial prefrontal, and lateral prefrontal cortices for both SCC and VCVS stimulation targets. Low convergence was found in anterior cingulate (ACC), where tractography predicted structural connectivity from SCC targets but produced no evoked potentials during SCC stimulation. Further, tractography predicted no connectivity to ACC from VCVS targets, but VCVS stimulation produced robust evoked potentials.ConclusionThe two connectivity methods showed significant convergence, but important differences emerged with respect to the ability of tractography to predict electrophysiological connectivity between SCC and VCVS to regions of the mood-related network. This multimodal approach raises intriguing implications for the use of tractography in surgical targeting and provides new data to enhance our understanding of the network-wide effects of neuromodulation
Insights from an Initial Exploration of Cognitive Biases in Spatial Decisions
No full textThe need and interest to consider cognitive and motivational biases has been recognized in many different disciplines (e.g. economics, operational research, decision theory, finance) and has recently reached environmental decision-making. Within this domain, the intrinsic presence of a spatial dimension of both alternatives and criteria calls for the use of geographical maps throughout the decision-making process to properly represent the spatial distribution of the features under analysis. This makes Spatial Multi Criteria Decision Aiding (SMCDA) a particularly interesting domain to explore new implications of cognitive and motivational biases. The present chapter presents and discusses the results of a literature review of recent applications of Spatial Multi Criteria Decision Aiding across different domains. The objective of the study is to enlighten possible biases in both the design of spatial MCDA models and in the interpretation of their results. The proposed review and classification of the relevant literature is expected to have important implications for spatial decision-making procedures, by generating better awareness on (i) the meta-choices available to model builders when designing Spatial Multi Criteria Decision Aiding processes and (ii) the consequences of these meta-choices on human judgment for both the facilitators of the modeling processes and the users of the models
