Segmentation of post-operative glioblastoma multiforme (GBM) is essential for the planning of Tumor Treating Fields (TTFields) treatment and other clinical applications. Recent methods developed for pre-operative GBM segmentation perform poorly on post-operative GBM MRI scans. In this paper we present a method for the segmentation of GBM in post-operative patients. Our method incorporates an ensemble of segmentation networks and the Kullback–Leibler divergence agreement score in the objective function to estimate the prediction label uncertainty and cope with (...) noisy labels and inter-observer variability. Moreover, our method integrates the surgery type and computes non-tumorous tissue delineation to automatically segment the tumor. We trained and validated our method on a dataset of 340 enhanced T1 MRI scans of patients that were treated with TTFields (270 scans for train and 70 scans for test). For validation, we developed a tool that uses the uncertainty map along with the segmentation result. Our tool allows visualization and fast editing of the tissues to improve the results dependent on user preference. Three physicians reviewed and graded our segmentation and editing tool on 12 different MRI scans. The validation set average (SD) Dice scores were 0.81 (0.11), 0.71 (0.24), 0.64 (0.25), and 0.68 (0.19) for whole-tumor, resection, necrotic-core, and enhancing-tissue, respectively. The physicians rated 72% of the segmented GBMs acceptable for treatment planning or better. Another 22% can be edited manually in a reasonable time to achieve a clinically acceptable result. According to these results, the proposed method for GBM segmentation can be integrated into TTFields treatment planning software in order to shorten the planning process. To conclude, we have extended a state-of-the-art pre-operative GBM segmentation method with surgery-type, anatomical information, and uncertainty visualization to facilitate a clinically viable segmentation of post-operative GBM for TTFields treatment planning. (shrink)

Nowadays decision making is strongly supported by the high-confident point estimations produced by deep learning algorithms. In many activities, they are sufficient for the decision-making process. However, in some other cases, confidence intervals are required too for an appropriate decision-making process. In this work, a first attempt to generate point estimations with confidence intervals for the $^{222}$Rn radiation level time series at Canfranc Underground Laboratory is presented. To predict the low-radiation periods allows correctly scheduling the unshielded periods for maintenance operations (...) in the experiments hosted in this facility. This should minimize the deposition of radioactive dust on the exposed surfaces during these unshielded periods. An approach based on deep learning with stochastic regulation is evaluated in the forecasting of point estimations and confidence intervals of the $^{222}$Rn time series and compared with a second approach based on Gaussian processes. As a consequence of this work, an evaluation of the capacity of Gaussian process and deep learning with stochastic regularization for generating point estimations and their confidence intervals for this time series is stated. (shrink)

This article considers the methods used to estimate the number of abortions before the 1967 Abortion Act came into operation. It suggests that the registration of legal abortions has enabled a new method to be used to calculate the number of illegal operations. The article concludes that the major effect of the Act was to transfer abortions from the illegal to the legal sector and, using the new method of calculation, estimates a total number of abortions immediately before the Act (...) of just over 100,000 a year. (shrink)

There has been increasing interest in recent years in the development of approaches to estimate causal effects when the number of potential confounders is prohibitively large. This growth in interest has led to a number of potential estimators one could use in this setting. Each of these estimators has different operating characteristics, and it is unlikely that one estimator will outperform all others across all possible scenarios. Coupling this with the fact that an analyst can never know which approach is (...) best for their particular data, we propose a synthetic estimator that averages over a set of candidate estimators. Averaging is widely used in statistics for problems such as prediction, where there are many possible models, and averaging can improve performance and increase robustness to using incorrect models. We show that these ideas carry over into the estimation of causal effects in high-dimensional scenarios. We show theoretically that averaging provides robustness against choosing a bad model, and show empirically via simulation that the averaging estimator performs quite well, and in most cases nearly as well as the best among all possible candidate estimators. Finally, we illustrate these ideas in an environmental wide association study and see that averaging provides the largest benefit in the more difficult scenarios that have large numbers of confounders. (shrink)

We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, (...) for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P, P, P, disjunctions: P, P, P, and conditional probabilities P, P, P. They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning. (shrink)

This paper deals with various connections that are found to exist between statistical estimation methods for decision-making and rules of group choice in the social choice area. Initially the aggregation of individual opinions is formulated as a pattern recognition problem; firstly it is shown that individual preferences lead to a natural representation in terms of binary patterns. Then we proceed to show how the search for a group preference pattern can be conducted by classifying the input preference patterns into (...) various ‘pattern classes’ and using the resulting classification boundaries to define the area of mutual agreement over some of the available alternatives. This leads to a decision-theoretic problem which consists in defining a decision rule (for classification) that is least likely to lead to misrecognition of arbitrary preference patterns. A maximum likelihood solution is obtained and compared with some well-known rules of group decision-making. Other solutions are also possible, on the basis of different optimality criteria, and their social choice interpretation is suggested. Finally, a method using Coleman's linear model for attributes is applied to yield group decision rules by feature weighting of election issues. (shrink)

Doubly robust (DR) estimators are an important class of statistics derived from a theory of semiparametric efficiency. They have become a popular tool in causal inference, including applications to dynamic treatment regimes. The doubly robust estimators for the mean response to a dynamic treatment regime may be conceived through the augmented inverse probability weighted (AIPW) estimating function, defined as the sum of the inverse probability weighted (IPW) estimating function and an augmentation term. The IPW estimating function of the causal estimand (...) via marginal structural model is defined as the complete-case score function for those subjects whose treatment sequence is consistent with the dynamic regime in question divided by the probability of observing the treatment sequence given the subject's treatment and covariate histories. The augmentation term is derived by projecting the IPW estimating function onto the nuisance tangent space and has mean-zero under the truth. The IPW estimator of the causal estimand is consistent if (i) the treatment assignment mechanism is correctly modeled and the AIPW estimator is consistent if either (i) is true or (ii) nested functions of intermediate and final outcomes are correctly modeled.Hence, the AIPW estimator is doubly robust and, moreover, the AIPW is semiparametric efficient if both (i) and (ii) are true simultaneously. Unfortunately, DR estimators can be inferior when either (i) or (ii) is true and the other false. In this case, the misspecified parts of the model can have a detrimental effect on the variance of the DR estimator. We propose an improved DR estimator of causal estimand in dynamic treatment regimes through a technique originally developed by [4] which aims to mitigate the ill-effects of model misspecification through a constrained optimization.In addition to solving a doubly robust system of equations, the improved DR estimator simultaneously minimizes the asymptotic variance of the estimator under a correctly specified treatment assignment mechanism but misspecification of intermediate and final outcome models. We illustrate the desirable operating characteristics of the estimator through Monte Carlo studies and apply the methods to data from a randomized study of integrilin therapy for patients undergoing coronary stent implantation. The methods proposed here are new and may be used to further improve personalized medicine, in general. (shrink)

This study introduces visual cognition into Lithium-ion battery capacity estimation. The proposed method consists of four steps. First, the acquired charging current or discharge voltage data in each cycle are arranged to form a two-dimensional image. Second, the generated image is decomposed into multiple spatial-frequency channels with a set of orientation subbands by using non-subsampled contourlet transform. NSCT imitates the multichannel characteristic of the human visual system that provides multiresolution, localization, directionality, and shift invariance. Third, several time-domain indicators of (...) the NSCT coefficients are extracted to form an initial high-dimensional feature vector. Similarly, inspired by the HVS manifold sensing characteristic, the Laplacian eigenmap manifold learning method, which is considered to reveal the evolutionary law of battery performance degradation within a low-dimensional intrinsic manifold, is used to further obtain a low-dimensional feature vector. Finally, battery capacity degradation is estimated using the geodesic distance on the manifold between the initial and the most recent features. Verification experiments were conducted using data obtained under different operating and aging conditions. Results suggest that the proposed visual cognition approach provides a highly accurate means of estimating battery capacity and thus offers a promising method derived from the emerging field of cognitive computing. (shrink)

With the widespread application of electric vehicles, the study of the power lithium-ion battery has broad prospects and great academic significance. The state of charge is one of the key parts in battery management system, which is used to provide guarantee for the safe and efficient operation of LIB. To obtain the reliable SOC estimation result under the influence of simple model and measurement noise, a novel estimation method with adaptive feedback compensator is presented in this paper. The (...) simplified dynamic external electrical characteristic of LIB is represented by the one-order Thevenin equivalent circuit model and then the ECM parameters are identified by the forgetting factor recursive least squares method. Fully taking into account the feedback effect of terminal voltage innovation, the combination of adaptive extended Kalman filter and innovation vector-based proportional-integral-derivative feedback is proposed to estimate the LIB SOC. The common single proportional feedback of Kalman filter is replaced by the innovation vector-based PID feedback, which means that the multiple prior terminal voltage innovation is used in the measurement correction step of KF. The results reveal that the AEKF with PID feedback compensation strategy can improve the SOC estimation performance compared with the common AEKF, and it reveals good robust capability and rapid convergence speed for initial SOC errors. The maximum absolute error and average absolute error for SOC estimation are close to 4% and 2.6%, respectively. (shrink)

In this article, we investigated a deterministic model of pneumonia-meningitis coinfection. Employing the Atangana–Baleanu fractional derivative operator in the Caputo framework, we analyze a seven-component approach based on ordinary differential equations. Furthermore, the invariant domain, disease-free as well as endemic equilibria, and the validity of the model’s potential results are all investigated. According to controller design evaluation and modelling, the modulation technique devised is effective in diminishing the proportion of incidences in various compartments. A fundamental reproducing value is generated by (...) exploiting the next generation matrix to assess the properties of the equilibrium. The system’s reliability is further evaluated. Sensitivity analysis is used to classify the impact of each component on the spread or prevention of illness. Using simulation studies, the impacts of providing therapy have been determined. Additionally, modelling the appropriate configuration demonstrated that lowering the fractional order from 1 necessitates a rapid initiation of the specified control technique at the largest intensity achievable and retaining it for the bulk of the pandemic’s duration. (shrink)

The common view of the transition between subitizing and numerosity estimation regimes is that there is a hard bound on the subitizing range, and beyond this range, people estimate. However, this view does not adequately address the behavioral signatures of enumeration under conditions of attentional load or in the immediate post-subitizing range. The possibility that there might exist a numerosity range where both processes of subitizing and estimation operate in conjunction has so far been ignored. Here, we investigate (...) this new proposal, that people strategically combine the processes of subitizing and estimation to maximize accuracy and precision, given time or attentional constraints. We present a process-level account of how subitizing and estimation can be combined through strategic deployment of attention to maximize the precision of perceived numerosity given time constraints. We then describe a computational model of this account and apply it in two experimental simulations to demonstrate how it can explain key findings in prior enumeration research. While recent modeling work has argued that the behavioral signatures of enumeration can best be explained through a single numerosity system with a single form of representation, we argue that our model demonstrates how the traditional two-systems view of numerical representation accounts for behavioral data through coordination with a unified attentional mechanism, rather than a unified representation. (shrink)

Recent advances in wireless data transmission technology have the potential to revolutionize clinical neuroscience. Today sensing-capable electrical stimulators, known as “bidirectional devices”, are used to acquire chronic brain activity from humans in natural environments. However, with wireless transmission come potential failures in data transmission, and not all available devices correctly account for missing data or provide precise timing for when data losses occur. Our inability to precisely reconstruct time-domain neural signals makes it difficult to apply subsequent neural signal processing techniques (...) and analyses. Here, our goal was to accurately reconstruct time-domain neural signals impacted by data loss during wireless transmission. Towards this end, we developed a method termed Periodic Estimation of Lost Packets. PELP leverages the highly periodic nature of stimulation artifacts to precisely determine when data losses occur. Using simulated stimulation waveforms added to human EEG data, we show that PELP is robust to a range of stimulation waveforms and noise characteristics. Then, we applied PELP to local field potential recordings collected using an implantable, bidirectional DBS platform operating at various telemetry bandwidths. By effectively accounting for the timing of missing data, PELP enables the analysis of neural time series data collected via wireless transmission—a prerequisite for better understanding the brain-behavior relationships underlying neurological and psychiatric disorders. (shrink)

Tautology is interpreted as a necessary condition for the workability of an operations system. This condition suggests the following possibilities: the stable solvability of balance equations between available resources and requests for them; the calculation of potential and kinetic of the system together with the estimation of the contribution of every operation to the kinetic of the system; the construction of a deadlockless infinite cyclic process for performance of some works.

Of all the different types of public buildings, hospitals are the biggest energy consumers. Cooling systems for air conditioning and healthcare uses are particularly energy intensive. Forecasting hospital thermal-cooling demand is a remarkable and innovative method capable of improving the overall energy efficiency of an entire cooling system. Predictive models allow users to forecast the activity of water-cooled generators and adapt power generation to the real demand expected for the day ahead, while avoiding inefficient subcooling. In addition, the maintenance costs (...) related to unnecessary starts and stops and power-generator breakdowns occurring over the long term can be reduced. This study is based on the operations of a real hospital facility and details the steps taken to develop an optimal and efficient model based on a genetic methodology that searches for low-complexity models through feature selection, parameter tuning and parsimonious model selection. The methodology, called GAparsimony, has been tested with neural networks, support vector machines and gradient boosting techniques. Finally, a weighted combination of the three best models was created. The new operational method employed herein can be replicated in similar buildings with similar water-cooled generators. (shrink)

The purpose of the simultaneous measurement of noncommuting quantum observables can be viewed as the joint estimation of parameters of the density operator of the quantum system. Joint estimation involves the application of a multiply parameterized operator-valued measure. An example related to the simultaneous estimation of the position and velocity of a particle is given. Conceptual difficulties attending simultaneous measurement of noncommuting observables are avoided by this formation.

Corrupt regulatory environment encourages firms to deploy middlemen for speedy and assured acquisition of different services from regulatory agencies. Using a World Bank dataset of 2210 Indian manufacturing firms, this article examines how firms with middlemen deal with corrupt governmental agencies for its operational efficiency. Our results demonstrate that deployment of middlemen by the firms is often accompanied by a substantial increase in operational delay, relatively trigger more consumption of senior management’s time on regulatory disentanglement, enhance the likelihood/tendency to pay (...) bribe, and likely to face more court cases as a means of restitution of legal rights. As firm-specific attributes may contaminate our preliminary results, we utilized the propensity score framework to examine relationships among variables of interests. Our study contributes to the inconspicuous part of the corruption literature by attempting to present a comprehensive but indirect assessment of the functions of middlemen that predominantly remained unattended except some scattered descriptive, case-based anecdotal presentations. (shrink)

Risk management is a well-known method to face technological challenges through a win–win combination of protective and proactive approaches, fostering the collaboration of operators, researchers, regulators, and industries for the exploitation of new markets. In the field of autonomous and unmanned aerial systems, or UAS, a considerable amount of work has been devoted to risk analysis, the generation of ground risk maps, and ground risk assessment by estimating the fatality rate. The paper aims to expand this approach with a tool (...) for managing data protection risks raised by drones through the design of flight maps. The tool should allow UAS operators choosing the best air corridor for their drones based on the so-called privacy by design principle pursuant to Article 25 of the EU data protection regulation, the GDPR. Among the manifold applications of this approach, the design of fly zones for drones can be tailored for public authorities in the phase of authorization of new operations, much as for national Data Protection authorities that have to control the lawfulness of personal data processing by UAS operations. The overall aim is to present the first win–win approach to data protection issues, aerospace engineering challenges, and risk management methods for the threats posed by this technology. (shrink)

Risk management is a well-known method to face technological challenges through a win–win combination of protective and proactive approaches, fostering the collaboration of operators, researchers, regulators, and industries for the exploitation of new markets. In the field of autonomous and unmanned aerial systems, or UAS, a considerable amount of work has been devoted to risk analysis, the generation of ground risk maps, and ground risk assessment by estimating the fatality rate. The paper aims to expand this approach with a tool (...) for managing data protection risks raised by drones through the design of flight maps. The tool should allow UAS operators choosing the best air corridor for their drones based on the so-called privacy by design principle pursuant to Article 25 of the EU data protection regulation, the GDPR. Among the manifold applications of this approach, the design of fly zones for drones can be tailored for public authorities in the phase of authorization of new operations, much as for national Data Protection authorities that have to control the lawfulness of personal data processing by UAS operations. The overall aim is to present the first win–win approach to data protection issues, aerospace engineering challenges, and risk management methods for the threats posed by this technology. (shrink)

Risk management is a well-known method to face technological challenges through a win–win combination of protective and proactive approaches, fostering the collaboration of operators, researchers, regulators, and industries for the exploitation of new markets. In the field of autonomous and unmanned aerial systems, or UAS, a considerable amount of work has been devoted to risk analysis, the generation of ground risk maps, and ground risk assessment by estimating the fatality rate. The paper aims to expand this approach with a tool (...) for managing data protection risks raised by drones through the design of flight maps. The tool should allow UAS operators choosing the best air corridor for their drones based on the so-called privacy by design principle pursuant to Article 25 of the EU data protection regulation, the GDPR. Among the manifold applications of this approach, the design of fly zones for drones can be tailored for public authorities in the phase of authorization of new operations, much as for national Data Protection authorities that have to control the lawfulness of personal data processing by UAS operations. The overall aim is to present the first win–win approach to data protection issues, aerospace engineering challenges, and risk management methods for the threats posed by this technology. (shrink)

Precise global solar radiation data are indispensable to the design, planning, operation, and management of solar radiation utilization equipment. Some examples prove that the uncertainty of the prediction of solar radiation provides more value than deterministic ones in the management of power systems. This study appraises the potential of random forest, V-support vector regression, and a resilient backpropagation artificial neural network for daily global solar radiation point prediction from average relative humidity, daily average temperature, and daily sunshine duration. To acquire (...) more accurate predictions of DGSR and examine the influence of historical DGSR on the performance of point prediction models, two different model inputs are considered: three meteorological variables and the lags of DGSR and three meteorological variables. Then, two interval prediction methods are developed by introducing the KDE to out-of-bag, introducing kernel density estimation to split conformal based on the three machine learning models. The two methods for interval prediction are denoted as OOB-KDE and SC-KDE. The mean absolute error, mean relative error, and Kendall rank correlation are used to assess the point prediction models. The performance of interval prediction methods is evaluated by the prediction interval coverage probability, prediction interval normalized average width, and coverage width criteria. The following conclusions are drawn from this study. First, the V-SVR model performs best with the lowest mean absolute error of 0.016 and mean relative error of 0.001. Second, the lags of DGSR improve the prediction accuracy by about 30%. Third, the OOB-KDE and SC-KDE methods improved the quality of the prediction interval. OOB-KDE improved CWC by 81%, and SC-KDE improved CWC by 99.99%. Fourth, the best interval prediction result is obtained using the SC-KDE method using the V-SVR model. The average difference between its PICP and prediction interval nominal coverage is only 3% of the PINC, and its PINAW is less than 0.007. (shrink)

Conflicts have arisen between communities and operators of confined animal feeding as farms have become bigger in order to maintain their competitiveness. These conflicts have been difficult to resolve because measuring and allocating the benefits and costs of livestock production is difficult. This papers demonstrates a policy tool for promoting compromise whereby the community gets reduced negative impacts from livestock while at the same time continues to benefit from livestock jobs, taxes, and related economic activity. Public economic benefits and public (...) economic costs of confined animal feeding operations are estimated for every farm and affected house in Craven County, North Carolina. The results show public economic benefits of $5.7 million and public economic costs of $2.2 million, but that the ratio of benefits to costs for individual farm-house pairs varies in important ways across the 26 hog farms in Craven County. (shrink)

. With an overall objective of establishing association between air pollutants and incidence of respiratory diseases, the environmental professionals and medical practitioners have made significant contribution, using statistical mechanics in modelling epidemiological data, population characteristics, and pollution parameters. Broadly speaking, the studies have shown that the increase in vehicular traffic has been one of the causes of respiratory diseases. However, the WHO Centre for Environment and Health, Europe in its 2005 document states: “There is little evidence for a causal relationship (...) between asthma prevalence/incidence and air pollution in general, though the evidence is suggestive of a causal association between the prevalence/incidence of asthma symptoms and living in close proximity to traffic”. Decision making process in a real world is invariably based on perceptions which are expressed in words or may be in numeric terms and not in probability terms. In the paper, we made an attempt to model the perceptions of experienced pulmonologists in arriving at their combined degree of belief/plausibility/ignorance for all the possible combinations of identified respiratory diseases, using evidence theory and fuzzy relational calculus without collecting sizeable parametric data accumulated over a period of years. Tightening pollution norms by the regulatory authorities is an overall objective of the global efforts on greenhouse gases reduction in general, and air pollution mitigation in particular. The concept of solar battery operated electric vehicles for road transport is advocated, initially for two/three wheelers, and extending it to four wheelers, especially in the developing countries. (shrink)

As moral injury is a still-emerging concept within the area of military mental health, prevalence estimates for moral injury and its precursor, potentially morally injurious events (PMIEs), remain unknown for many of the world’s militaries. The present study sought to estimate the prevalence of PMIEs in the Canadian Armed Forces (CAF), using data collected from CAF personnel deployed to Afghanistan, via logistic regressions controlling for relevant sociodemographic, military, and deployment characteristics. Analyses revealed that over 65% of CAF members reported exposure (...) to at least one event that would be considered a PMIE. The most commonly PMIEs individuals reported included seeing ill or injured women and children they were unable to help (48.4%), being unable to distinguish between combatants and non-combatants (43.6%), and finding themselves in a threatening situation where they were unable to respond due to the rules of engagement under which they were required to operate (35.4%). These findings provide support for both the presence of exposure to PMIEs in CAF members and the need for formal longitudinal data collection regarding PMIE exposure and moral injury development. (shrink)

Conflicts have arisen between communities and operators of confined animal feeding as farms have become bigger in order to maintain their competitiveness. These conflicts have been difficult to resolve because measuring and allocating the benefits and costs of livestock production is difficult. This papers demonstrates a policy tool for promoting compromise whereby the community gets reduced negative impacts from livestock while at the same time continues to benefit from livestock jobs, taxes, and related economic activity. Public economic benefits and public (...) economic costs of confined animal feeding operations are estimated for every farm and affected house in Craven County, North Carolina. The results show public economic benefits of $5.7 million and public economic costs of $2.2 million, but that the ratio of benefits to costs for individual farm-house pairs varies in important ways across the 26 hog farms in Craven County. (shrink)

?German warplanes fired on two hijacked military fuel trucks in the northern province of Kunduz killing an estimated 90 villagers?.? While the debate over what is now known as the Kunduz Air Strike in 2009 has by no means ended, it has ? or so I shall argue ? missed a key point. By allowing the media's witchlike hunt for a scapegoat to dominate the military debate, a critical consideration concerning the ethics of network-enabled operations has been overlooked. As such, (...) I take the tragedy of the Kunduz air strikes as a case study of the failure of network-enabled operations, focusing on the ethical questions that this raises. To do so, I will begin with a description of what happened before, during and after the air strike. Following this, I consider three ethical concerns that arise as a result of network-enabled operations. I end with a proposal to increase the possibility of ethically reflective decision-making in network-enabled operations, which calls for a relational type of thinking and a complementary form of training. (shrink)

This month the American Journal of Bioethics examines the intersectionality of medicine, ethics, and race. In “Race, Power, and COVID-19: A Call for Advocacy Within Bioethics,” Mithani and colleagu...

Nowadays, many countries are promoting entrepreneurial education or the “innovation, entrepreneurship, and creativity” education. Entrepreneurial education can enhance a nation’s economic competitiveness and give rise to new business. At the moment, entrepreneurial courses are mostly designed by school teachers; however, while school teachers may possess business experience, they lack in entrepreneurial experience. Hence, entrepreneurial education courses call for experts with entrepreneurial experience to contribute to course designs and assist with course teachings. Entrepreneurial education not only improves a student’s entrepreneurial skills, (...) but also enables each student to explore their personal characteristics in order to advance the collaboration efficacy of the team as a whole. This study asked six experts with entrepreneurial experience in the information industry to work with school teachers in course design as well as teaching collaboration. The course design starts with three talk sessions given by professionals who share with students their thoughts and experiences in entrepreneurial products, team organization, fund raising, and profit calculation. Following that, each student is asked to share their own thoughts on entrepreneurial products and start searching for team members and planning their project. During the course, each team receives six individual advising sessions from the professionals, with topics ranging from product modeling, feasibility, product market estimation, fundraising methods, and profit calculation. The experts also provide each team member with personal trait analysis. Last but not least, the course invites five management-level industry professionals to play the role of venture capital investor and evaluate each team’s product modeling based on their presentation. This study reviews the grades given by the experts as well as the evaluations given by the three industry managers to assess whether the entrepreneurial education course’s student entrepreneur teams satisfy the industry’s expectations. (shrink)

The current study sought to assess the mediating role of green market orientation dimensions in the relationship between social risk and new product performance among European Multinational Enterprises (EMNEs). We also assessed the moderating role of entrepreneurial orientation in the relationship between green market orientation and new product performance. The study was based on primary data gathered from 317 EMNEs in Ghana. After various validity and reliability checks, ordinary least squares (OLS) analysis was performed to estimate the various relationships hypothesized (...) in the study. The study finds that social risk has a negative effect on the success of EMNEs' new products. This negative effect is however nullified by the positive mediating effects of strategic green market orientation, tactical green market orientation and internal green market orientation. Entrepreneurial orientation also played a significant moderating effect in the relationship between green market orientation dimensions and EMNEs' new product performance. Based on this, theoretical and managerial contributions were made. (shrink)

The method of evaluation of technical and economic indicators for the development of gas condensate field tested in the branch system of enterprises of PJSC "Ukrgazvydobuvannya" is considered, which is supplemented and simplified for obtaining approximate estimates in the case of annual natural or artificial changes in the gas condensate factor and thermobaric states of the extracted fluid during the operational period of the late stage. Targeted changes in the algorithms of calculations of basic technical and economic indicators, especially for (...) partially exhausted deposits, which have become permanent in operation with compressed compressor stations and fixed pressure on the wells, are used, dry gas is used for returning to the formation or dehumidification of the hinterland. The main factors of influence on the final results of the technical and economic evaluation are determined. Improvement of the technique of an approximate estimation of technical and economic indicators of the development of the gas condensate deposit facility for the possibility of adaptation of calculations at the late stage, which usually involves the operation of the SCS, the use of PPE technologies, the drying of the faces by high-pressure gas, and artificial adjustment of the working pressures of wells. The changes in the results of technical and economical calculations are taken into account when taking into account the parameters of the DKS, PPD, thermobaric intensification for the possibility of use in production and in the educational process. (shrink)

Intelligence estimates based on models keyed to frequency and recency of past occurrences make people less secure even if they predict most harmful events. The U.S. presidential commission on WMDs, the 9/11 commission, and Spain's comisión 11-M have condemned the status quo mentality of the intelligence community, which they see as being preoccupied with today's “current operations” and tactical requirements, and inattentive to tomorrow's far-ranging problems and strategic solutions. But the overriding emphasis in these commissions' recommendations is on further vertically (...) integrating intelligence collection, analysis, and operations. Such proposals to further centralize intelligence and unify command and control are not promising given recent transformations in Jihadist networks to a somewhat “leaderless resistance” in the wake of Al Qaeda's operational demise. To defeat terrorist networks requires grasping novel relations between an englobing messianic moral framework, the rootless intellectual and physical mobility of immigrant and diaspora communities, and the overarching conceptual, emotional, and logistical afford- ances of the Internet. Britain's WWII experience provides salutary lessons for think- ing creatively with decentralized expertise and partially autonomous approaches. (shrink)

Virtue reliabilists argue that an agent can only gain knowledge if she responsibly employs a reliable belief-forming process. This in turn demands that she is either aware that her process is reliable or is sensitive to her process’s reliability in some other way. According to a recent argument in the philosophy of mind, sometimes a cognitive mechanism (i.e. precision estimation) can ensure that a belief-forming process is only employed when it’s reliable. If this is correct, epistemic responsibility can sometimes (...) be explained entirely on the subpersonal level. In this paper, I argue that the mechanism of precision estimation–the alleged new variety of epistemic responsibility–is a more ubiquitous phenomenon than epistemic responsibility. I show that precision estimation operates at levels that are not always concerned with the epistemic domain. Lastly, I broaden this argument to explain how all subpersonal epistemologies are likely to fall prey to the problem of demarcating cognitive agency and the problem of attributing beliefs. (shrink)

On estime souvent que les Grecs avaient des phénomènes économiques une approche triviale et non scientifique. Ce point de vue est en partie motivé par ce que l’économiste et historien de la pensée économique J.A. Schumpeter et l’historien de la Grèce antique M.I. Finley considèrent être l’excessive préoccupation des penseurs grecs pour les « vaines » considérations domestiques de nature matérielle, au détriment de l’analyse scientifique des phénomènes économiques. Contre une telle interprétation, l’hypothèse présentée ici est que cette préoccupation répond (...) au souci de la conservation des biens qui, avec leur acquisition et leur bon usage, est l’une des trois activités principales de l’art économique ou oikonomique. L’examen détaillé des deux opérations de conservation que sont le rangement et la gestion, en lien avec les divers aspects du Bien économique qui leur sont associés, permet de le montrer. (shrink)

Making decisions can be hard, but it can also be facilitated. Simple heuristics are fast and frugal but nevertheless fairly accurate decision rules that people can use to compensate for their limitations in computational capacity, time, and knowledge when they make decisions [Gigerenzer, G., Todd, P. M., & the ABC Research Group (1999). Simple Heuristics That Make Us Smart. New York: Oxford University Press.]. These heuristics are effective to the extent that they can exploit the structure of information in the (...) environment in which they operate. Specifically, they require knowledge about the predictive value of probabilistic cues. However, it is often difficult to keep track of all the available cues in the environment and how they relate to any relevant criterion. This problem becomes even more critical if compound cues are considered. We submit that knowledge about the causal structure of the environment helps decision makers focus on a manageable subset of cues, thus effectively reducing the potential computational complexity inherent in even relatively simple decision-making tasks. We review experimental evidence that tested this hypothesis and report the results of a simulation study. We conclude that causal knowledge can act as a meta-cue for identifying highly valid cues, either individual or compound, and helps in the estimation of their validities. (shrink)

This paper presents a kernel density estimation method by means of real-coded crossovers. Functions of real-coded crossover operators are composed of probabilistic density estimation from parental populations and sampling from estimated models. Real-coded Genetic Algorithm (RCGA) does not explicitly estimate probabilistic distributions, however, probabilistic model estimation is implicitly included in algorithms of real-coded crossovers. Based on this understanding, we exploit the implicit estimation of probabilistic distribution of crossovers as a kernel density estimator. We also propose an (...) application of crossover kernels to Expectation-Maximization estimation (EM) of Gaussian mixtures. (shrink)

Background and Objective: Understanding how trauma impacts the self-structure of individuals suffering from the Post-Traumatic Stress Disorder (PTSD) symptoms is a complex matter and despite several attempts to explain the relationship between trauma and the “Self”, this issue still lacks clarity. Therefore, adopting a new theoretical perspective may help understand PTSD deeper and to shed light on the underlying psychophysiological mechanisms. Methods: In this study, we employed the “three-dimensional construct model of the experiential selfhood” where three major components of selfhood (...) (phenomenal first-person agency, embodiment, and reflection/narration) are related to three Operational Modules (OMs) of the self-referential brain network. These modules can be reliably estimated through operational synchrony analysis of the Electroencephalogram (EEG). Six individuals with PTSD symptoms and twenty-nine sex-, age- and demographic- (race, education, marital status) matched healthy controls underwent resting state EEG signal acquisition with the following estimation of the synchrony strength within every OM. Results: Our results indicate that subjects with PTSD symptoms had significantly stronger EEG operational synchrony within anterior and right posterior OMs as well as significantly weaker EEG operational synchrony within left posterior OM compared to healthy controls. Moreover, increased the functional integrity of the anterior OM was positively associated with hyperactivity symptoms, reduced synchrony of the left posterior OM was associated with greater avoidance, and increased right posterior OM integrity was positively correlated with intrusion and mood symptoms. Conclusion: The results are interpreted in light of the triad model of selfhood and its theoretical and clinical implications (including a new treatment approach) are discussed. (shrink)

We present strategies how to reconstruct (estimate) properties of a quantum channel described by the map E based on incomplete measurements. In a particular case of a qubit channel a complete reconstruction of the map E can be performed via complete tomography of four output states E[ρj] that originate from a set of four linearly independent “test” states ρj (j = 1,2,3,4) at the input of the channel. We study the situation when less than four linearly independent states are transmitted (...) via the channel and measured at the output. We present strategies how to reconstruct the channel when just one, two or three states are transmitted via the channel. In particular, we show that if just one state is transmitted via the channel then the best reconstruction can be achieved when this state is a total mixture described by the density operator ρ = I/2. To improve the reconstruction procedure one has to send via the channel more states. The best strategy is to complement the total mixture with pure states that are mutually orthogonal in the sense of the Bloch-sphere representation. We show that unitary transformations (channels) can be uniquely reconstructed (determined) based on the information of how three properly chosen input states are transformed under the action of the channel. (shrink)

Minimizing the costs that others impose upon oneself and upon those in whom one has a fitness stake, such as kin and allies, is a key adaptive problem for many organisms. Our ancestors regularly faced such adaptive problems (including homicide, bodily harm, theft, mate poaching, cuckoldry, reputational damage, sexual aggression, and the infliction of these costs on one's offspring, mates, coalition partners, or friends). One solution to this problem is to impose retaliatory costs on an aggressor so that the aggressor (...) and other observers will lower their estimates of the net benefits to be gained from exploiting the retaliator in the future. We posit that humans have an evolved cognitive system that implements this strategy – deterrence – which we conceptualize as a revenge system. The revenge system produces a second adaptive problem: losing downstream gains from the individual on whom retaliatory costs have been imposed. We posit, consequently, a subsidiary computational system designed to restore particular relationships after cost-imposing interactions by inhibiting revenge and motivating behaviors that signal benevolence for the harmdoer. The operation of these systems depends on estimating the risk of future exploitation by the harmdoer and the expected future value of the relationship with the harmdoer. We review empirical evidence regarding the operation of these systems, discuss the causes of cultural and individual differences in their outputs, and sketch their computational architecture. (shrink)

Dr. Vukov analyzing patients with disorders of consciousness, proposed that medical well-regarded policy recommendations cannot be justified by looking solely to patients’ actual levels of consciousness (minimally conscious state – MCS versus vegetative state – VS), but that they can be justified by looking to patients’ potential for consciousness. One objective way to estimate this potential (actual physical possibility) is to consider a neurophysiologically informed strategy. Ideally such strategy would utilize objective brain activity markers of consciousness/unconsciousness. The Operational Architectonics (OA) (...) theory of brain-mind functioning is an example of such a strategy. Besides being mathematically simple, neurophysiologically accurate, and compatible with the cognitive/phenomenal perspectives on consciousness, application of OA strategy to quantitative EEG analysis of patients in VS and MCS revealed that the absence of consciousness in VS is paralleled by impairment of overall EEG operational architecture. Specifically, neuronal assemblies become smaller, their life span shortened, and they became highly unstable and functionally disconnected (desynchronized). At the same time, fluctuating (minimal) awareness in patients in MCS was paralleled by partial restoration of EEG operational architecture (increased size, life span, and stability of neuronal assemblies, together with an increased number and strength of functional connections among them), approaching the level found in healthy fully conscious participants. Moreover OA strategy to EEG analysis allowed predicting the emergence of consciousness in VS patients after six years following the brain trauma. Therefore, the OA methodology could reliably predict which patients may regain consciousness, and thus determine which patients may have the potential for consciousness. (shrink)

It has been estimated that U.S. companies with global business operations can reduce their U.S. tax bill by up to 10 percentage points if they reincorporate in a zero or low tax offshore jurisdiction. But this activity, at a time of national crisis following the September 11 terrorists' attacks and recent spate of corporate scandals, has received a less than sympathetic response from the U.S. media, ordinary taxpayers, shareholders and politicians as concerns are raised about the reduction of the tax (...) base and the lack of oversight and regulation in offshore centres. Offshore reincorporation has been condemned as immoral, unconscionable, dishonest and unpatriotic, accusations that cast doubt on the legitimacy of the companies concerned. In question is their right to conduct business in the U.S. and in particular, their right to still be viewed as American. Their legitimacy once bestowed so readily by the company's shareholders is now being questioned not only by shareholders but also the media, politicians, government regulators, pension funds and labour unions. Expatriate companies have been slow to respond to questions of their legitimacy, viewing their offshore move as a financial decision needing only the consent of their shareholders. However, times have changed and corporate legitimacy is now in the hands of all the company's stakeholders. Companies will need to explicitly consider the determinants of their legitimacy and the implications of the implied social contract under which they operate, to remain relevant in the days ahead. (shrink)

This paper generalizes the simple regret model by Bell in Operations Research 30(5), 961-981 and Loomes and Sugden in The Economic Journal 92(368), 805-824 to cope with the situation in which decision outcomes are multi-attributed. We propose a model that combines the simple regret model for ex ante preferences and the additive difference representation for ex post preferences. We first present a necessary and sufficient axiomatization of our model in Savage’s framework. The proposed model is composed of three types of (...) functions. One is a value function for each attribute. The others are attribute-dependent and holistic regret-rejoicing functions that capture trade-offs among value-differences of chosen and forgone outcomes for each attribute and among all attributes, respectively. We then provide constructive procedures for those functions and methods for consistency checks of the procedures. We, finally, conduct an experiment to estimate those functions in the two attributes case by means of the constructive procedure and give an application of the model and our findings. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Desire of the Analysts: Psychoanalysis and Cultural CriticismVera J. Camden (bio)Desire of the Analysts: Psychoanalysis and Cultural Criticism. Ed. Greg Forter and Paul Allen Miller. New York: SUNY P, 2008. 258 pp.This collection takes up the uses of psychoanalysis for cultural studies in the new millennium. Its editors and contributors ask, “Where is psychoanalysis in contemporary thought?” At a time when the empirically based psychologies have long repudiated (...) the “talking cure” to the extent that the unconscious is not visible or easily measured, and when, on the other hand, psychoanalysis has been associated in the humanities with a radical political and social agenda, disappointed hopes for change have led many to throw the baby of psychoanalysis out with the bathwater of a utopian vision of transformation. The question now remains: “Whither psychoanalysis?” To answer this question (which is also a demand), the editors first acknowledge that the critique and curtailing of psychoanalytic thought in the cultural studies programs across the country in the last decade or so has been influenced by the works of Michel Foucault, his disciples, and the New Historicism. At the same time, they believe that the political, psychological, and moral dangers of embracing a knowing and cynical postmodernism that fosters hollow consumerism premised on modes of subjectivity that “neither ‘express’ interiority nor bear any relation to a lived past” are a real and present danger in contemporary life. “That the triumph of such a view has coincided with intellectuals’ renewed suspicion of psychoanalysis should, we believe, give us pause” (8). The essays that constitute the present volume thus insist on the persistence of the desire of the analyst: for knowledge of self and other, and by those who long for interpretive insight into interior lives and social places. The volume thus poses for its readers twin questions: “Why do we continue to desire psychoanalysis, and what should its role be in the cultural criticism of the new millennium?”This collection grew out of a conference organized around this question and thus reflects the varied but not necessarily interconnected papers offered in that setting. In an effort to provide some interconnections, the collection is divided into four sections grouped around the topics of psychoanalysis and the future of cultural criticism, collectivity, the author, and sexuality. The grouping does not, in my estimation, provide unity or coherence to the volume as a whole; nevertheless, each article emerges on its own terms as a strong contribution to the general field of psychoanalytic cultural criticism and critical theory. Henry Sussman’s “Psychoanalysis, Religion, and Cultural Criticism at the Millennium” provides an anchoring perspective to the volume, addressing with particular urgency the mutually transformative desire of and for analysis modeled on the transference/countertransference clinical encounter. This analogy [End Page 153] suggestively sets the stage for a like transformative intervention by the analyst in a cultural critique, while acknowledging that cultural studies provides the best interpretation and assessment of the ways that psychoanalysis operates historically and clinically in contemporary society. Sussman—and indeed many of the contributors—underscores the editors’ organizing declaration that since psychoanalysis derived from lived human experience it stands to reason that “analysis is both the product of and answer to suffering” (15).Thus it comes as something of a surprise that one of its editors, Greg Forter, in “F. Scott Fitzgerald, Psychobiography, and the Fin-de-Siecle Crisis in Masculinity,” locks the subject of psychoanalysis into a stranglehold with his presuppositions about the limits of history and the origins of psychoanalysis in the modern moment: “Because the theory and techniques of psychoanalysis were developed by analyzing modern men and women, psychoanalysis may be a theory of modern subjectivity rather than of subjectivity as such, and its mode of inquiry may be best suited to analyzing the phenomena of modernity” (148). Contrast this limiting and limited sense of the place of psychoanalysis in history (and the concomitant restriction of its utility expressed ironically in a volume with two major articles on premodern cultural texts!) to recent remarks in a new book by Christopher Bollas: “For thousands of years there has been an unconscious preconception of psychoanalysis. We [...] human beings [...] have been searching for... (shrink)

Genetic Programming is a powerful optimization algorithm, which employs the crossover for genetic operation. Because the crossover operator in GP randomly selects sub-trees, the building blocks may be destroyed by the crossover. Recently, algorithms called PMBGPs based on probabilistic techniques have been proposed in order to improve the problem mentioned above. We propose a new PMBGP employing Bayesian network for generating new individuals with a special chromosome called expanded parse tree, which much reduces a number of possible symbols at each (...) node. Although the large number of symbols gives rise to the large conditional probability table and requires a lot of samples to estimate the interactions among nodes, a use of the expanded parse tree overcomes these problems. Computational experiments on two subjects demonstrate that our new PMBGP is much superior to prior probabilistic models. (shrink)

Nearly all studies of consumers’ willingness to engage in ethical or socially responsible purchasing behavior is based on unconstrained survey response methods. In the present article we ask the question of how well does asking consumers the extent to which they care about a specific social or ethical issue relate to how they would behave in a more constrained environment where there is no socially acceptable response. The results of a comparison between traditional survey questions of “intention to purchase” and (...) estimates of individuals willingness-to-pay for social attributes in products reveal that simple survey questions are too “noisy” to provide operationally meaningful information and overstate intentions to a considerable extent. (shrink)

Corruption has been a major obstacle to economic growth around the world. In this paper, we examine how firms interact with corrupt government officials either to minimize the impact of corruption on their operations or to maximize their benefit of paying a bribe. Our estimates show that firms know exactly what they need and use their limited resources to bribe only relevant government authorities. In other words, firms are rational bribers who know exactly what they need and optimize their bribes (...) to fulfill that need. This type of intentional bribery could be reduced by enhanced institutional environments and improved openness of the economy. (shrink)

Machine learning operates at the intersection of statistics and computer science. This raises the question as to its underlying methodology. While much emphasis has been put on the close link between the process of learning from data and induction, the falsificationist component of machine learning has received minor attention. In this paper, we argue that the idea of falsification is central to the methodology of machine learning. It is commonly thought that machine learning algorithms infer general prediction rules from past (...) observations. This is akin to a statistical procedure by which estimates are obtained from a sample of data. But machine learning algorithms can also be described as choosing one prediction rule from an entire class of functions. In particular, the algorithm that determines the weights of an artificial neural network operates by empirical risk minimization and rejects prediction rules that lack empirical adequacy. It also exhibits a behavior of implicit regularization that pushes hypothesis choice toward simpler prediction rules. We argue that taking both aspects together gives rise to a falsificationist account of artificial neural networks. (shrink)