On- and Off-Responses in the Inferior Colliculus of the Greater Horseshoe Bat to Pure Tones

1. The auditory threshold curve of averaged evoked potentials of the colliculus inferior in Rhinolophus /errum equinum to pure tone stimulation from 1 to 100 kHz is presented (Fig. 1). For pure tone frequencies lower than 14 ktIz thresholds steeply rise from 20 to 110 db. The steepness of the acoustical filter for 83.3 kHz signals and the frequency of the echoes heard by Greater Horseshoe Bats is accentuated by averaging methods. Because of averaging, evoked potentials thresholds are lowered by about 20 db compared to those obtained by non-averaging methods. 2. Prominent off-responses in evoked potentials appear for three stimulus frequency ranges: 3-10 kHz with a peak at 5 ktIz, 20-40 kHz with a peak at 20 kHz and 80.0-82.6 kHz with a peak at 81.5 kHz (Fig. 2). 3. It is unlikely that beat note frequencies play any role for echolocation. 4. The relevance of these results to echolocation in Horseshoe Bats is discussed, especially as to Doppler shift information contained in the constant frequency part of echoes

Efficient Recognition of authentic dynamic facial expressions on the FEEDTUM database

In order to allow for fast recognition of a user’s affective state we discuss innovative holistic and self organizing approaches for efficient facial expression analysis. The feature set is thereby formed by global descriptors and MPEG based DCT coefficients. In view of subsequent classification we compare modelling by pseudo multidimensional Hidden Markov Models and Support Vector Machines. Within the latter case super-vectors are constructed based on Sequential Floating Search Methods. Extensive test-runs as a proof of concept are carried out on our publicly available FEEDTUM database consisting of elicited spontaneous emotions of 18 subjects within the MPEG-4 emotion-set plus added neutrality. Maximum recognition performance reaches the benchmark-rate gained by a human perception test with 20 test-persons and manifest the effectiveness of the introduced novel concepts. 1

Speech recognition in noisy environments using a switching linear dynamic model for feature enhancement

The performance of automatic speech recognition systems strongly decreases whenever the speech signal is disturbed by background noise. We aim to improve noise robustness focusing on all major levels of speech recognition: feature extraction, feature enhancement, and speech modeling. Different auditory modeling concepts, speech enhancement techniques, training strategies, and model architectures are implemented in an in-car digit and spelling recognition task. We prove that joint speech and noise modeling with a global Switching Linear Dynamic Model (SLDM) capturing the dynamics of speech, and a Linear Dynamic Model (LDM) for noise, prevails over state-of-theart speech enhancement techniques. Furthermore we show that the baseline recognizer of the Interspeech Consonant Challenge 2008 can be outperformed by SLDM feature enhancement for almost all of the noisy testsets

Investigating NMF Speech Enhancement for Neural Network based Acoustic Models

In the light of the improvements that were made in the last years with neural network-based acoustic models, it is an interesting question whether these models are also suited for noise-robust recognition. This has not yet been fully explored, although first experiments confirm this question. Furthermore, preprocessing techniques that improve the robustness should be re-evaluated with these new models. In this work, we present experimental results to address these questions. Acoustic models based on Gaussian mixture models (GMMs), deep neural networks (DNNs), and long short-term memory (LSTM) recurrent neural networks (which have an improved ability to exploit context) are evaluated for their robustness after clean or multi-condition training. In addition, the influence of non-negative matrix factorization (NMF) for speech enhancement is investigated. Experiments are performed with the Aurora-4 database and the results show that DNNs perform slightly better than LSTMs and, as expected, both beat GMMs. Furthermore, speech enhancement is capable of improving the DNN result. Index Terms: robust speech recognition, long short-term memory, speech enhancemen

Effect of carbon nanofibre orientation on fatigue properties of carbon fibre-reinforced polymers

Nano-reinforcements in carbon fibre-reinforced polymer (CFRP) have proven to enhance the mechanical properties considering quasi-static, as well as fatigue load and, are a promising option with regard to CFRP performance optimisation. While general knowledge about the nanofiller content and its influence in CFRP is well documented, the use of alignment techniques for a specific orientation of the nano-reinforcements is still insufficiently studied. In this work, the influence of oriented carbon nanofibres (CNF) on the mechanical properties of bidirectional CFRP is investigated. CFRP was produced CNF-reinforced with and without orientation using a hot press, where an electric field was applied during curing. The laminates were characterised with respect to dispersion quality, pore volume, quasi-static properties (tensile and bending tests) and dynamic properties (fatigue tests). Electrical resistance measurement was applied together with digital image correlation and in situ computed tomography to generate knowledge about the fatigue-related damage evolution and evaluate the sensors for viable use of condition monitoring. Results show that the orientation of CNF has a significant impact on both quasi-static and fatigue properties, increasing the strength while reducing and slowing down the introduced damage. Orientation of nanofillers thus shows large optimization potential of mechanical properties of CFRP components

In vivo inhibition of neutrophil activity by a FAS (CD95) stimulating module: arterial in-line application in a porcine cardiac surgery model

AbstractObjectiveCardiac surgery with cardiopulmonary bypass is associated with aberrant neutrophil activation and potentially severe pathogenic sequelae. This experimental study was done to evaluate a leukocyte inhibition module that rapidly inactivates neutrophils through CD95 stimulation.MethodsGerman landrace pigs (4 groups, each n = 5) underwent cardiac surgery without cardiopulmonary bypass (group I), with cardiopulmonary bypass (group II), with cardiopulmonary bypass plus a leukocyte filter (group III), and with cardiopulmonary bypass plus a leukocyte inhibition module (group IV). The leukocyte filter or leukocyte inhibition module was introduced into the arterial line of the heart-lung machine.ResultsLeukocyte counts were decreased by up to 43% in group IV compared with values in group II (P = .023). In group IV, but not in groups I to III, no delay in spontaneous neutrophil apoptosis was observed after annexin V–propidium iodide staining. Late apoptotic (11.7%) or necrotic neutrophils (9.3%) were detected in 2 animals (group IV). Tumor necrosis factor α serum levels increased over time in groups I to III (>2-fold) but remained at baseline levels in group IV (P < .05). Interleukin 8–mediated chemotactic neutrophil transmigration activity increased over time in groups I to III but was totally abrogated in group IV at any time point. The perioperative increase of creatine kinase and creatine kinase MB levels was lower in groups III (1.5-fold and 1.3-fold, respectively) and IV (1.2-fold and 1.5-fold, respectively) compared with values in group II (both 1.9-fold).ConclusionsThe leukocyte inhibition module downregulated cardiopulmonary bypass–related neutrophil activity and thus might be beneficial in cardiac surgery and other clinical settings with unappreciated neutrophil activation