Learning by Not Doing: Subsidy Disciplines in Services Trade

This paper explores the hitherto futile quest for developing disciplines on the trade- and investment-distorting effects of services subsidies. It sheds light on the multiplicity of factors that have weighed on the conduct of negotiations on subsidy disciplines in a services trade context at both the global and preferential levels, and advances a few thoughts on what the future may hold for the adoption of such disciplines. The analysis suggests that it is rather unlikely that WTO Members will any time soon reach a consensus on the matter of subsidy disciplines for services beyond those that currently (and timidly) obtain in the GATS and in many preferential trade agreements. The main reason behind such a conclusion stems from a marked rise in the value of preserving policy space in a trading environment characterized by considerably greater global market contestability than two decades ago.

Learning by the Dendritic Prediction of Somatic Spiking

Recent modeling of spike-timing-dependent plasticity indicates that plasticity involves as a third factor a local dendritic potential, besides pre- and postsynaptic firing times. We present a simple compartmental neuron model together with a non-Hebbian, biologically plausible learning rule for dendritic synapses where plasticity is modulated by these three factors. In functional terms, the rule seeks to minimize discrepancies between somatic firings and a local dendritic potential. Such prediction errors can arise in our model from stochastic fluctuations as well as from synaptic input, which directly targets the soma. Depending on the nature of this direct input, our plasticity rule subserves supervised or unsupervised learning. When a reward signal modulates the learning rate, reinforcement learning results. Hence a single plasticity rule supports diverse learning paradigms.

Rationale, scope, and 20-year experience of vascular surgical training with lifelike pulsatile flow models

Vascular surgical training currently has to cope with various challenges, including restrictions on work hours, significant reduction of open surgical training cases in many countries, an increasing diversity of open and endovascular procedures, and distinct expectations by trainees. Even more important, patients and the public no longer accept a "learning by doing" training philosophy that leaves the learning curve on the patient's side. The Vascular International (VI) Foundation and School aims to overcome these obstacles by training conventional vascular and endovascular techniques before they are applied on patients. To achieve largely realistic training conditions, lifelike pulsatile models with exchangeable synthetic arterial inlays were created to practice carotid endarterectomy and patch plasty, open abdominal aortic aneurysm surgery, and peripheral bypass surgery, as well as for endovascular procedures, including endovascular aneurysm repair, thoracic endovascular aortic repair, peripheral balloon dilatation, and stenting. All models are equipped with a small pressure pump inside to create pulsatile flow conditions with variable peak pressures of ~90 mm Hg. The VI course schedule consists of a series of 2-hour modules teaching different open or endovascular procedures step-by-step in a standardized fashion. Trainees practice in pairs with continuous supervision and intensive advice provided by highly experienced vascular surgical trainers (trainer-to-trainee ratio is 1:4). Several evaluations of these courses show that tutor-assisted training on lifelike models in an educational-centered and motivated environment is associated with a significant increase of general and specific vascular surgical technical competence within a short period of time. Future studies should evaluate whether these benefits positively influence the future learning curve of vascular surgical trainees and clarify to what extent sophisticated models are useful to assess the level of technical skills of vascular surgical residents at national or international board examinations. This article gives an overview of our experiences of >20 years of practical training of beginners and advanced vascular surgeons using lifelike pulsatile vascular surgical training models.

Distance measures for image segmentation evaluation

The task considered in this paper is performance evaluation of region segmentation algorithms in the ground-truth-based paradigm. Given a machine segmentation and a ground-truth segmentation, performance measures are needed. We propose to consider the image segmentation problem as one of data clustering and, as a consequence, to use measures for comparing clusterings developed in statistics and machine learning. By doing so, we obtain a variety of performance measures which have not been used before in image processing. In particular, some of these measures have the highly desired property of being a metric. Experimental results are reported on both synthetic and real data to validate the measures and compare them with others.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior. But behavioral decision making is likely to involve the integration of many synaptic events in space and time. So in using a single reinforcement signal to modulate synaptic plasticity a twofold problem arises. Different synapses will have contributed differently to the behavioral decision and, even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward but by a population feedback signal as well. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second one involves an action sequence which is itself extended in time and reward is only delivered at the last action, as is the case in any type of board-game. The third is the inspection game that has been studied in neuroeconomics. It only has a mixed Nash equilibrium and exemplifies that the model also copes with stochastic reward delivery and the learning of mixed strategies.

Soil conservation in Swiss agriculture - Approaching abstract and symbolic meanings in farmers' life-worlds

This paper explores the significance of ‘life-worlds’ for better understanding why farmers adopt or reject soil conservation measures and for identifying basic dimensions to be covered by social learning processes in Swiss agricultural soil protection. The study showed that farmers interpret soil erosion and soil conservation measures against the background of their entire life-world. By doing so, farmers consider abstract and symbolic meanings of soil conservation. This is, soil conservation measures have to be feasible and practical in the everyday farming routine, however, they also have to correspond with their aesthetic perception, their value system and their personal and professional identities. Consequently, by switching to soil conservation measures such as no-tillage farmers have to adapt not only the routines of their daily farming life, but also their perception of the aesthetics of cultivated land, underlying values and images of themselves. Major differences between farmers who adopt and farmers who reject no-tillage were found to depend on the degree of coherence they could create between the abstract and symbolic meanings of the soil conservation measure. From this perspective, implementation of soil protection measures faces the challenge of facilitating interactions between farmers, experts and scientists at a ‘deeper’ level, with an awareness of all significant dimensions that characterise the life-world. The paper argues that a certain level of shared symbolic meaning is essential to achieving mutual understanding in social learning processes.

Learned irrelevance and associative learning is attenuated in individuals at risk for psychosis but not in asymptomatic first-degree relatives of schizophrenia patients: translational state markers of psychosis?

Learned irrelevance (LIrr) refers to a form of selective learning that develops as a result of prior noncorrelated exposures of the predicted and predictor stimuli. In learning situations that depend on the associative link between the predicted and predictor stimuli, LIrr is expressed as a retardation of learning. It represents a form of modulation of learning by selective attention. Given the relevance of selective attention impairment to both positive and cognitive schizophrenia symptoms, the question remains whether LIrr impairment represents a state (relating to symptom manifestation) or trait (relating to schizophrenia endophenotypes) marker of human psychosis. We examined this by evaluating the expression of LIrr in an associative learning paradigm in (1) asymptomatic first-degree relatives of schizophrenia patients (SZ-relatives) and in (2) individuals exhibiting prodromal signs of psychosis ("ultrahigh risk" [UHR] patients) in each case relative to demographically matched healthy control subjects. There was no evidence for aberrant LIrr in SZ-relatives, but LIrr as well as associative learning were attenuated in UHR patients. It is concluded that LIrr deficiency in conjunction with a learning impairment might be a useful state marker predictive of psychotic state but a relatively weak link to a potential schizophrenia endophenotype.

Learning software-maintenance tasks in offshoring projects: a cognitive-load perspective

Individual learning is central to the success of the transition phase in software mainte-nance offshoring projects. However, little is known on how learning activities, such as on-the-job training and formal presentations, are effectively combined during the tran-sition phase. In this study, we present and test propositions derived from cognitive load theory. The results of a multiple-case study suggest that learning effectiveness was highest when learning tasks such as authentic maintenance requests were used. Con-sistent with cognitive load theory, learning tasks were most effective when they imposed moderate cognitive load. Our data indicate that cognitive load was influenced by the expertise of the onsite coordinator, by intrinsic task complexity, by the degree of specifi-cation of tasks, and by supportive information. Cultural and semantic distances may in-fluence learning by inhibiting supportive information, specification, and the assignment of learning tasks.

Patients with mild traumatic brain injury: immediate and long-term outcome compared to intra-cranial injuries on CT scan

BACKGROUND: Mild traumatic brain injury (MTBI) defined as Glasgow Coma Scale (GCS) 14 or 15 has shown contradictory short- and long-term outcomes. The objective of this study was to correlate intra-cranial injuries (ICI) on CT scan to neurocognitive tests at admission and to complaints after 1 year. METHODS: Two hundred and five patients with MTBI underwent a CT scan and were examined with neurocognitive tests. After 1 year complaints were assessed by phone interviews. RESULTS: The neurocognitive tests in 51% of the patients showed significant deficits; there was no difference for patients with GCS 14-15, nor was there a difference between patients with ICI to patients without. After 1 year patients with ICI had significantly more complaints than patients without ICI, the most frequent complaint was headache and memory deficits. CONCLUSIONS: No correlation was found between GCS or ICI and the neurocognitive tests upon admission. After 1 year, patients with ICI have significantly more complaints than patients without ICI. No cost savings resulted by doing immediate CT scan on all.

Microscopic wire guide-based orotracheal mouse intubation: description, evaluation and comparison with transillumination

Airway access is needed for a number of experimental animal models, and the majority of animal research is based on mouse models. Anatomical conditions in mice are small, and the narrow glottic opening allows intubation only with a subtle technique. We therefore developed a microscopic endotracheal intubation method with a wire guide technique in mice anaesthetized with halothane in oxygen. The mouse is hung perpendicularly with its incisors on a thread fixed on a vertical plate. The tongue is placed with a pair of forceps between the left hand's thumb and forefinger and slightly pulled, while the neck and thorax are positioned using the third and fourth fingers. By doing so, the neck can be slightly stretched, which allows optimal visualization of the larynx and the vocal cords. To ensure a safe intubation, a fine wire guide is placed under vision between the vocal cords and advanced about 5 mm into the trachea. An intravenous 22G x 1 in. plastic or Teflon catheter is guided over this wire. In a series of 41 mice, between 21 and 38 g, the success rate for the first intubation attempt was >95%. Certainty of the judgement procedure was 100% and success rate was higher using the described method when compared with a transillumination method in a further series. The technique is safe, less invasive than tracheostomy and suitable for controlled ventilation and pulmonary substance application.

An Enabling Regulatory Environment for Sustainable Investment: The Example of Trade Law

There is broad international agreement that investment flows to the agricultural sector in developing countries need to be increased. But there is also agreement that such investments need to be sustainable. For being sustainable, they must not only be beneficial to the public economy, but also to rural households and to the environment in the short and the long run. Whether sustainable investments take place, not least depends on the legal framework within which these investments are situated. This is true for the domestic legal frameworks of both the home country and of the host country of the investment. But also the international legal frameworks in which home and host states are embedded set either positive or negative incentives for investments to be sustainable. The paper presents an overview on regulatory frameworks which come to focus in this regard. It then elaborates on international agricultural trade regulation, by assuming that sustainable investments in agriculture presume a ‘sustainable trade regime’. By doing so, the paper presents parts of the debate about a sustainable agricultural trade regime, as it has been resumed and further developed by the author in recent years. Key words. Agricultural sector, sustainable investment, regulatory environment, sustainable trade regime.