Applying an heuristic approach to lca

Practical analysability of Life Cycle Assessment is high related to data availability and data quality. High costs and many efforts are required for performing traditional high data-quality LCA. An heuristic approach for data collection can provide more useful results than other approaches using quantitative data which already demonstrate errors or improperness which have been recognised. The heuristic approach provides data both cheaply and rapidly which is not surely exact but still accurate enough for practical situations. Although the heuristic approach has some restrictions in comparison to other alternatives, it is a valuable option.     

Decoding the Attentional Demands of Gait through EEG Gamma Band Features

Rehabilitation techniques are evolving focused on improving their performance in terms of duration and level of recovery. Current studies encourage the patient’s involvement in their rehabilitation. Brain-Computer Interfaces are capable of decoding the cognitive state of users to provide feedback to an external device. On this paper, cortical information obtained from the scalp is acquired with the goal of studying the cognitive mechanisms related to the users’ attention to the gait. Data from 10 healthy users and 3 incomplete Spinal Cord Injury patients are acquired during treadmill walking. During gait, users are asked to perform 4 attentional tasks. Data obtained are treated to reduce movement artifacts. Features from δ(1 − 4Hz), θ(4 − 8Hz), α(8 − 12Hz), β(12 − 30Hz), γ_low(30 − 50Hz), γ_high(50 − 90Hz) frequency bands are extracted and analyzed to find which ones provide more information related to attention. The selected bands are tested with 5 classifiers to distinguish between tasks. Classification results are also compared with chance levels to evaluate performance. Results show success rates of ∼67% for healthy users and ∼59% for patients. These values are obtained using features from γ band suggesting that the attention mechanisms are related to selective attention mechanisms, meaning that, while the attention on gait decreases the level of attention on the environment and external visual information increases. Linear Discriminant Analysis, K-Nearest Neighbors and Support Vector Machine classifiers provide the best results for all users. Results from patients are slightly lower, but significantly different, than those obtained from healthy users supporting the idea that the patients pay more attention to gait during non-attentional tasks due to the inherent difficulties they have during normal gait. This study provides evidence of the existence of classifiable cortical information related to the attention level on the gait. This fact could allow the development of a real-time system that obtains the attention level during lower limb rehabilitation. This information could be used as feedback to adapt the rehabilitation strategy.     

The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice

Cognitive impairment, particularly involving dysfunction of circuitry within the prefrontal cortex (PFC), represents a core feature of many neuropsychiatric and neurodevelopmental disorders, including depression, post-traumatic stress disorder, schizophrenia and autism spectrum disorder. Deficits in cognitive function also represent the most difficult symptom domain to successfully treat, as serotonin reuptake inhibitors and tricyclic antidepressants have only modest effects. Functional neuroimaging studies and postmortem analysis of human brain tissue implicate the PFC as being a primary region of dysregulation in patients with these disorders. However, preclinical behavioral assays used to assess these deficits in mouse models which can be readily manipulated genetically and could provide the basis for studies of new treatment avenues have been underutilized. Here we describe the adaptation of a behavioral assay, the attentional set shifting task (AST), to be performed in mice to assess prefrontal cortex mediated cognitive deficits. The neural circuits underlying behavior during the AST are highly conserved across humans, nonhuman primates and rodents, providing excellent face, construct and predictive validity.     

Visual Features Underlying Perceived Brightness as Revealed by Classification Images

Along with physical luminance, the perceived brightness is known to depend on the spatial structure of the stimulus. Often it is assumed that neural computation of the brightness is based on the analysis of luminance borders of the stimulus. However, this has not been tested directly. We introduce a new variant of the psychophysical reverse-correlation or classification image method to estimate and localize the physical features of the stimuli which correlate with the perceived brightness, using a brightness-matching task. We derive classification images for the illusory Craik-O''Brien-Cornsweet stimulus and a “real” uniform step stimulus. For both stimuli, classification images reveal a positive peak at the stimulus border, along with a negative peak at the background, but are flat at the center of the stimulus, suggesting that brightness is determined solely by the border information. Features in the perceptually completed area in the Craik-O''Brien-Cornsweet do not contribute to its brightness, nor could we see low-frequency boosting, which has been offered as an explanation for the illusion. Tuning of the classification image profiles changes remarkably little with stimulus size. This supports the idea that only certain spatial scales are used for computing the brightness of a surface.     

Using Highlighting to Train Attentional Expertise

Acquiring expertise in complex visual tasks is time consuming. To facilitate the efficient training of novices on where to look in these tasks, we propose an attentional highlighting paradigm. Highlighting involves dynamically modulating the saliency of a visual image to guide attention along the fixation path of a domain expert who had previously viewed the same image. In Experiment 1, we trained naive subjects via attentional highlighting on a fingerprint-matching task. Before and after training, we asked subjects to freely inspect images containing pairs of prints and determine whether the prints matched. Fixation sequences were automatically scored for the degree of expertise exhibited using a Bayesian discriminative model of novice and expert gaze behavior. Highlighted training causes gaze behavior to become more expert-like not only on the trained images but also on transfer images, indicating generalization of learning. In Experiment 2, to control for the possibility that the increase in expertise is due to mere exposure, we trained subjects via highlighting of fixation sequences from novices, not experts, and observed no transition toward expertise. In Experiment 3, to determine the specificity of the training effect, we trained subjects with expert fixation sequences from images other than the one being viewed, which preserves coarse-scale statistics of expert gaze but provides no information about fine-grain features. Observing at least a partial transition toward expertise, we obtain only weak evidence that the highlighting procedure facilitates the learning of critical local features. We discuss possible improvements to the highlighting procedure.     

Wild Pigs and Kings Remembered Landscapes in Rajasthan

Based on interviews with elderly persons in rural Rajasthan, in northern India, this essay explores some ways that memories impinge on present and future lives and landscape. Simultaneously it seeks to disclose collaborative research processes through lengthy interview passages. Farmers' memories of wild pigs and local kings are the specific focus: memories remain vivid of the destruction pigs could work on crops, and the rulers who forbid pig killing at the same time exorbitantly taxed the grain pile. Although rapid deforestation has destroyed wild pigs' habitat, and democracy has disempowered former rulers, the politics of ecological deterioration have ongoing consequences.     

Method for Excluding Noise Features in Applying a Learning Machine

Previous works have demonstrated that a computerized learning machine could be successfully applied to predicting the presence or absence of a certain microbial feature in a microorganism. To achieve the prediction, however, the presence or absence of many other features must be examined beforehand. This paper deals with the method for decreasing the number of characters that must be examined prior to the prediction. In the six instances studied, this number could be decreased from 93 to 11 in the most fortunate case and to 26 in the most unfortunate case, without causing deterioration of the prediction results.     

Attentional bias to food images associated with elevated weight and future weight gain: an fMRI study

Behavioral studies reveal that obese vs. lean individuals show attentional bias to food stimuli. Yet research has not investigated this relation using objective brain imaging or tested whether attentional bias to food stimuli predicts future weight gain, which are important aims given the prominence of food cues in the environment. We used functional magnetic resonance imaging (fMRI) to examine attentional bias in 35 adolescent girls ranging from lean to obese using an attention network task involving food and neutral stimuli. BMI correlated positively with speed of behavioral response to both appetizing food stimuli and unappetizing food stimuli, but not to neutral stimuli. BMI correlated positively with activation in brain regions related to attention and food reward, including the anterior insula/frontal operculum, lateral orbitofrontal cortex (OFC), ventrolateral prefrontal cortex (vlPFC), and superior parietal lobe, during initial orientation to food cues. BMI also correlated with greater activation in the anterior insula/frontal operculum during reallocation of attention to appetizing food images and with weaker activation in the medial OFC and ventral pallidum during reallocation of attention to unappetizing food images. Greater lateral OFC activation during initial orientation to appetizing food cues predicted future increases in BMI. Results indicate that overweight is related to greater attentional bias to food cues and that youth who show elevated reward circuitry responsivity during food cue exposure are at increased risk for weight gain.     

Applying an animal‐centric approach to improve ecological restoration

Traditionally, ecological restoration is based on re‐establishing patterns of vegetation communities with the expectation that wildlife will recolonize, restoring the ecological function. However, in many restoration projects, wildlife fails to recolonize, even when vegetation is restored, in many cases because revegetated habitats lack the critical features required by wildlife. We present a new approach to restoration, based on a detailed understanding of ecological process, the mechanisms by which wildlife respond to landscape patterns. Our animal‐centric approach involves measuring the risk‐sensitive decision‐making of individual animals as they balance searching for food, mates, and breeding sites with avoiding being eaten by predators and relates this to fine‐scale habitat and landscape structure. The outcome of these decisions can be measured in occupancy of habitat, the information on which conventional restoration is based. Incorporating landscape genetics allows retrospective assessment of the outcome of dispersal decisions by individual animals on a deeper time frame and at regional scales. Fine‐scale connectivity models can be parameterized with these multiscale spatial and temporal data to direct restoration efforts. We are translating this novel approach to practice in the large Midlands restoration project (4 years, AUD $6 million) in Tasmania, Australia, in partnership with Greening Australia. More than 200 years of intensive agricultural practice in this National Biodiversity Hotspot has resulted in extensive landscape modification, high densities of feral cats, and decline of many native mammals. Our research–practice partnership will alter the way that restoration is done, leading hopefully to successful restoration of wildlife, gene flow, and ecological function.     

Attentional Switches and Dual-Task Interference

In four experiments, we studied the time course of interference between detection of an oddball orientation target (OT) in an 8-item circular search display, and identification of a letter target (LT) in a central stream of distractor letters. Dual-task performance for different temporal lags between targets was compared to single-task performance. When the LT preceded the OT, dual-task performance levels were reduced at short inter-target intervals of 0 and 166 ms; when the OT preceded the LT, the dual-task interference was unexpectedly stronger and lasted for up to 500 ms. Resource competition due to temporally overlapping target processing cannot account for this result, because the feature search task is easier than the letter identification task, and therefore would have generated less interference when presented first. Two alternative explanations were explored. First, by manipulating the spatial inter-target distance, we investigated to what degree there is a penalty associated with directing the attentional window from a large object (the search display) to a smaller object (the central letter stream). Second, by varying the duration of the OT and subsequent mask, we studied whether the interference was caused by the difficulty of disengaging attention from the search display. Results support this second explanation and thus indicate that switching attention to the letter stream is hampered by the continuing presence of (masked) search display items. This result shows that attentional effects may play a major role in dual-task execution and can easily obscure interference due to other factors such as resource competition.     

Attentional processes link perception and action

Behavioural studies on normal and brain-damaged individuals provide convincing evidence that the perception of objects results in the generation of both visual and motor signals in the brain, irrespective of whether or not there is an intention to act upon the object. In this paper we sought to determine the basis of the motor signals generated by visual objects. By examining how the properties of an object affect an observer's reaction time for judging its orientation, we provide evidence to indicate that directed visual attention is responsible for the automatic generation of motor signals associated with the spatial characteristics of perceived objects.     

Attentional entrainment and perceived event duration

This study considered the contribution of dynamic attending theory (DAT) and attentional entrainment to systematic distortions in perceived event duration. Three experiments were conducted using an auditory oddball paradigm, in which listeners judged the duration of a deviant (oddball) stimulus embedded within a series of identical (standard) stimuli. To test for a role of attentional entrainment in perceived oddball duration, oddballs were presented at either temporally expected (on time) or unexpectedly early or late time points relative to extrapolation of the context rhythm. Consistent with involvement of attentional entrainment in perceived duration, duration judgements about the oddball were least distorted when the oddball occurred on time with respect to the entrained rhythm, whereas durations of early and late oddballs were perceived to be shorter and longer, respectively. This pattern of results was independent of the absolute time interval preceding the oddball. Moreover, as expected, an irregularly timed sequence context weakened observed differences between oddballs with on-time and late onsets. Combined with other recent work on the role of temporal preparation in duration distortions, the present findings allot at least a portion of the oddball effect to increased attention to events that are more expected, rather than on their unexpected nature per se.     

Applying microfluidics to electrophysiology

Microfluidics can be integrated with standard electrophysiology techniques to allow new experimental modalities. Specifically, the motivation for the microfluidic brain slice device is discussed including how the device docks to standard perfusion chambers and the technique of passive pumping which is used to deliver boluses of neuromodulators to the brain slice. By simplifying the device design, we are able to achieve a practical solution to the current unmet electrophysiology need of applying multiple neuromodulators across multiple regions of the brain slice. This is achieved by substituting the standard coverglass substrate of the perfusion chamber with a thin microfluidic device bonded to the coverglass substrate. This was then attached to the perfusion chamber and small holes connect the open-well of the perfusion chamber to the microfluidic channels buried within the microfluidic substrate. These microfluidic channels are interfaced with ports drilled into the edge of the perfusion chamber to access and deliver stimulants. This project represents how the field of microfluidics is transitioning away from proof-of concept device demonstrations and into practical solutions for unmet experimental and clinical needs.