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The advent of the COVID-19 pandemic has enhanced the complexities of plastic waste management. Our improved, hyper-hygienic way of life in the fear of transmission has conveniently shifted our behavioral patterns like the use of PPE (Personal protective equipment), increased demand for plastic-packaged food and groceries, and the use of disposable utensils. learn more The inadequacies and inefficiencies of our current waste management system to deal with the increased dependence on plastic could aggravate its mismanagement and leakage into the environment, thus triggering a new environmental crisis. Mandating scientific sterilization and the use of sealed bags for safe disposal of contaminated plastic wastes should be an immediate priority to reduce the risk of transmission to sanitation workers. Investments in circular technologies like feedstock recycling, improving the infrastructure and environmental viability of existing techniques could be the key to dealing with the plastic waste fluxes during such a crisis. Tranvernment policy are all necessary to keep us from transitioning from one disaster to another.When making infrastructure policies, decision makers insufficiently consider negative consequences for the environment or health. This lack of multi-sectorial awareness in policymaking triggers poor public health outcomes. To illustrate this issue, this interdisciplinary work presents evidence for the association of road infrastructure investment (as infrastructure policy) with the incidences of deaths due to transport accidents, chronic obstructive pulmonary disease, and pneumonia using nationally aggregated data from the Organisation for Economic Co-operation and Development for 27 countries over an 18-year period (1995-2012). We conduct an explorative analysis using descriptive statistics and fixed-effects panel-data regression models that include the interaction of the policy variable with the Environmental Policy Stringency Index, which proxies the awareness of negative consequences of policies. We show that countries which never achieved a score of 3 or higher for the Environmental Policy Stringency Indaths due to transport accidents and chronic obstructive pulmonary disease.

Posttraumatic epilepsy (PTE) is a common cause of drug-resistant epilepsy, especially in young adults. Nevertheless, such patients are not common candidates for intracranial presurgical evaluation. We investigated the role of stereoelectroencephalography (SEEG) in defining epileptogenicity and surgical strategy in patients with PTE.

We analyzed ictal SEEG recordings from 18 patients. We determined the seizure onset zone (SOZ) by quantifying the epileptogenicity of the sampled structures, using the “epileptogenicity index” (EI). We also identified seizure onset patterns (SOPs) through visual and frequency analysis. Postsurgical outcome was assessed by Engel’s classification.

The SOZ in PTE was most often located in temporal lobes, followed by frontal lobes. The SOZ was network-organized in the majority of the cases. Half of the SOP did not contain fast discharges. Half of the recordings showed SOZ that were less extensive than the posttraumatic lesions seen on brain magnetic resonance imaging (MRI). All but one operated patient benefited from tailored cortectomy. Only 3 patients were contraindicated for surgical resection due to bilateral epileptogenicity. The overall surgical outcome was good in majority of patients (67% Engel I).

Despite the potential risk of bilateral or multifocal epilepsy, patients with PTE may benefit from presurgical assessment in well-selected cases. In this context, SEEG allows guidance of tailored resections adapted to the SOZ.

Despite the potential risk of bilateral or multifocal epilepsy, patients with PTE may benefit from presurgical assessment in well-selected cases. In this context, SEEG allows guidance of tailored resections adapted to the SOZ.

Maladaptive avoidance is a core characteristic of anxiety-related disorders. Its reduction is often promoted using extinction with response prevention (ExRP) procedures, but these effects are often short-lived. Research has shown that pairing a feared stimulus with a stimulus of an incompatible valence (i.e., counterconditioning) may be effective in reducing fear. This laboratory study tested whether positive imagery during ExRP (i.e., imagery counterconditioning protocol) can also reduce avoidance.

In the counterconditioning procedure, participants imagined a positive sound. There were four phases. First, participants were presented with squares on a computer screen of which one (CS+) was paired with an aversive sound and another (CS-) was not. Second, they learned to avoid the negative sound in the presence of the CS+, via a key press. Third, they were assigned to either the Counterconditioning (that was asked to imagine a positive sound during ExRP) or No Counterconditioning group (standard ExRP). Finally, they performed a test phase that consisted of two parts in the first part, avoidance responses were available for each CS and in the second part, these responses were prevented.

The Counterconditioning intervention resulted in a short-lived reduction of distress associated with the CS+. However, groups did not differ in avoidance or distress during the test phases.

US-expectancy ratings were collected only at the end of the experiment.

The results indicate that positive imagery during ExRP may be effective in reducing distress during the intervention. Explanations for the persistence of avoidance and fear are discussed.

The results indicate that positive imagery during ExRP may be effective in reducing distress during the intervention. Explanations for the persistence of avoidance and fear are discussed.

Retinal microaneurysm (MA) is one of the earliest clinical signs of diabetic retinopathy(DR). Its detection is essential for controlling DR and preventing vision loss. However, the spatial scale of MA is extremely small and the contrast to surrounding background is subtle, which make MA detection challenging. The purpose of this work is to automatically detect MAs from fundus images.

Our MA detector involves two stages MA candidate extraction and classification. In MA candidate extraction stage, local minimum region extraction and block filtering are used to exploit the regions where MA may exist. In this way, most of irrelavent background regions are discarded , which subsequently facilitates the training of MA classifier. In the second stage, multiple features are extracted to train the MA classifier. To distinguish MA from vascular regions, we propose a series of descriptors according to the cross-section profile of MA. Specially, as MAs are small and their contrast to surroundings is subtle, we propose local cross-section transformation (LCT) to amplify the difference between the MA and confusing structures.