Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring social cognition and mirror systems in schizophrenia and bipolar disorder

Schizophrenia and bipolar disorder show some overlap in genetics, epidemiology and clinical features. Individuals with these disorders often have poor social and vocational functional outcomes and reduced quality of life, even during times of symptom remission. Social cognition comprises a number of processes including emotion recognition, empathy and theory of mind (ToM), and recent research has indicated that these skills may be reduced in schizophrenia and bipolar disorder, and contribute to their reduced function. Despite this, the exact nature of these social cognitive deficits, their impact on quality of life, and possible underlying neural substrates, have not yet been established in these disorders. One brain network implicated in social cognition is the mirror system, however, research into this system in schizophrenia or bipolar disorder has been very limited to date. The goal of this thesis was to better understand the nature and impact of social cognitive deficits in schizophrenia and euthymic bipolar disorder, and comprehensively assess mirror system function as a possible contributor to these deficits. In this thesis, I first assessed a number of aspects of social cognition (emotion recognition, empathy and ToM), as well as cognitive, clinical, and quality of life variables in a schizophrenia, euthymic bipolar disorder, and healthy control group. The three groups were then compared using two putative measures of mirror system function (EEG and TMS). I found a significant reduction in cognitive ToM in both disorders, with the addition of a deficit in the recognition of anger in the schizophrenia sample, indicating some likely shared underlying brain pathology but also disorder-specific differences. Quality of life was not related to these social cognitive deficits in this sample, possibly due to other mediating factors. There was some evidence for underactive mirror systems in euthymic bipolar disorder but not schizophrenia, however, mirror system function was not strongly related to any of the social cognitive measures utilised in this study. The findings of this thesis make a valuable contribution to the understanding of social cognition in schizophrenia and bipolar disorder, and challenge the proposed importance of mirror systems for social cognition. Our findings indicate that social cognitive deficits should be considered in assessment and treatment planning in schizophrenia and bipolar disorder. In addition, this thesis highlights the need for further research aimed at understanding the neurobiology and true impact of social cognitive deficits. It is hoped that this knowledge will lead to better treatments targeting these deficits at both neurophysiological and behavioural levels, and ultimately improve patient outcomes and wellbeing.
Using Links to Aid Web Classification

In this paper, we will present a new approach of using link information to improve the accuracy and efficiency of web classification. However, different from others, we only use the mappings between linked documents and their own class or classes. In this case, we only need to add a few features called linked-class features into the datasets. We apply SVM and BoosTexter for classification. We show that the classification accuracy can be improved based on mixtures of ordinary word features and out-linked-class features. We analyze and discuss the reason of this improvement.
Impact of pronunciation variation in speech recognition

Mapping the acoustic sequence to lexical units is an issue in speech recognition. To address this, multiple pronunciations are included in the pronunciation dictionary. However, the number of lexical variants required for improved recognition is not clear as pronunciation varies significantly across dialects. This can lead to poor recognition sometimes. In this paper, a systematic study is carried out to observe the effect of pronunciation variation on recognition accuracy. In particular, a data-driven approach is employed to observe pronunciation variation at syllable level. The acoustic cue about the syllable boundaries are obtained from Group Delay (GD) segmentation. The preliminary experiments carried out for TIMIT corpus reveal that the use of prominent pronunciation variants for each dialect leads to an improved recognition performance.
Feasibility of Mobile Cellular Communications at Millimeter Wave Frequency

High data rate at high mobile speed will still be an essential requirement for the future 5G mobile cellular system. High frequency bands above 6 GHz are particularly promising for the 5G system because of large signal bandwidths such high frequencies can offer. By using high gain beamforming antennas, the problem of high propagation loss at high frequencies can be overcome. However, the use of beamforming antennas at such high frequencies requires a significant change in the design of a cellular system. In particular, it requires a significant change in key functions such as cell search, random access, measurement of beams for fast beam adaptation, and various physical control and data channels. In this paper, we propose a new radio frame structure for the future mobile cellular communications system at millimeter wave frequency that addresses such challenges. A testbed was built at Samsung Electronics, Korea, based on the proposed frame structure at 28 GHz with bandwidth of 800 MHz. It attained the downlink (DL) data rate of 7.5 Gbps by delivering four streams of 64 QAM data with code rate of 3/4 to two mobile stations (MSs) located in a close distance to the base station antennas at fixed positions. It also achieved the DL data rate of 1.2 Gbps by delivering single stream of 16 QAM data with code rate of 3/4 to an MS moving at 110 km/h in a single cell of up to 800 m in a line-of-sight environment. Finally, it implemented handover and achieved an average handover interruption time of 21 ms in a three-cell environment, and demonstrated feasibility of mobile cellular communications at millimeter wave frequency.
IL-1 , α Neonatal White Matter Glia: Role of TNF- Acute Lipopolysaccharide-Mediated Injury in

Bacterial infection is implicated in the selective CNS white matter injury associated with cerebral palsy, a common birth disorder. Exposure to the bacterial endotoxin LPS produced death of white matter glial cells in isolated neonatal rat optic nerve (RON) (a model white matter tract), over a 180-min time course. A delayed intracellular Ca 2 (cid:3) concentration ([Ca 2 (cid:3) ] i ) rise preceded cell death and both events were prevented by removing extracellular Ca 2 (cid:3) . The cytokines TNF- (cid:1) or IL-1 (cid:2) , but not IL-6, mimicked the cytotoxic effect of LPS, whereas blocking either TNF- (cid:1) with a neutralizing Ab or IL-1 with recombinant antagonist prevented LPS cytotoxicity. Ultrastructural examination showed wide-scale oligodendroglial cell death in LPS-treated rat optic nerves, with preservation of astrocytes and axons. Fluorescently conjugated LPS revealed LPS binding on microglia and astrocytes in neonatal white and gray matter. Astrocyte binding predominated, and was particularly intense around blood vessels. LPS can therefore bind directly to developing white matter astrocytes and microglia to evoke rapid cell death in neighboring oligodendroglia via a calcium- and cytokine-mediated pathway. In addition to direct toxicity, LPS increased the degree of acute cell death evoked by ischemia in a calcium-dependent manner. The Journal of Immunology, 2005, 175: 155–161. in in The and are investigated and the cell of
Idioms and extended transducers

There is a tension between the idea that idioms can be both listed in the lexicon, and the idea that they are themselves composed of the lexical items which seem to inhabit them in the standard way. In other words, in order to maintain the insight that idioms actually contain the words they look like they contain, we need to derive them syntactically from these words. However, the entity that should be assigned a special meaning is then a derivation, which is not the kind of object that can occur in a lexicon (which is, by definition, the atoms of which derivations are built), and thus not the kind of thing that we are able to assign meanings directly to. Here I will show how to resolve this tension in an elegant way, one which bears striking similarities to those proposed by psychologists and psycholinguists working on idioms.
Facial blood vessels activity in drunk persons using thermal infrared

In this work, the activity of the facial blood vessels of drunk persons is studied using thermal infrared images. Nonlinear anisotropic diffusion is applied to enhance the vessels on the images and after that top-hat transformation is used for isolating them from the rest information on the face. Simple thresholding is applied to raise the more active vessels. Registration procedures are employed to easily compare the vessel activity on the face of the drunk person with that on the sober person. In drunk persons, vessels around nose and eyes as well as on the forehead become more active. This work constitutes a preliminary study, which aims at qualitative and not quantitative results. Basically, the restricted number of the 20 persons that participated in the experiment is not considered adequate for statistical inference. (5 pages)
Isolation of Brain Tumor Segment using HMGMM

of images holds an important position in the area of image processing. It becomes more important while typically dealing with medical images, magnetic resonance (MR) imaging offers more accurate information for medical examination than other medical images such as X-ray, ultrasonic and CT images. Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts when compared with modern day's high speed computing machines which enable us to visually observe the volume and location of unwanted tissues.One of the reasons behind the inferior segmentation efficiency is the presence of artifacts in the MR images. One such artifact is the extracranial tissues (skull). These extracranial tissues often interfere with the normal tissues during segmentation that accounts for the inferior segmentation efficiency. This paper deals with an efficient segmentation algorithm for extracting brain tumors in magnetic resonance images using hidden Markov Gauss Mixture Model (HMGMM) with Genetic algorithm (GA). HMGMMs incorporate supervised learning, fitting the observation probability distribution given by each class using Gaussian mixture model. The GA and Expectation Maximization (EM) algorithms are used to obtain an HMM model with optimized number of states in the HMM models and its model parameters brain tumor extraction.
Exposure to acetylcholinesterase-inhibiting pesticides and chronic renal failure.

Recent reports show an increase in the incidence of end-stage renal disease of unknown aetiology from the North-Central Province of Sri Lanka [1]. As the majority of the patients are from rural farming communities, pesticide exposure is suspected as a cause, although it is not a proven aetiological factor for chronic renal failure (CRF). Acetylcholinesterase (AChE)-inhibiting insecticides are the most widely used pesticides in Sri Lanka. Although nephrotoxicity is not recognised as a clinical feature of anticholinesterase poisoning, there are reports of acute renal failure provoked by acute tubular necrosis [2] and rabdomyolysis [3] following high dose OP exposure. This preliminary study was conducted to determine if there is an association between CRF of unknown aetiology and organophosphate (OP) exposure.
Longitudinal effects of working memory on L2 grammar and reading abilities

Adults demonstrate difficulty and pronounced variability when developing second language (L2) grammatical knowledge and reading skills. We examine explanations in terms of individual differences in working memory (WM). Despite numerous studies, the association between WM and adult second language (L2) acquisition remains unclear, and longitudinal studies are scarce and contradictory. This study investigates whether WM affects L2 grammar and reading development in beginning classroom learners, using WM tests with (Waters and Caplan’s 1996 test) and without (Daneman and Carpenter’s 1980 test) a demanding processing task. In Experiment 1, 82 beginning first language (L1) English learners of Spanish completed Daneman and Carpenter’s test, and grammar and reading pretests and posttests one year apart. In Experiment 2, 330 beginning English learners of Spanish completed the same tests as in Experiment 1 and Waters and Caplan’s test. The results reveal that only Waters Caplan’s test (response time, recall span) yielded WM effects, and that response time (processing) negatively correlated with recall span (storage). These findings reveal longitudinal WM effects on L2 grammar and reading development at early acquisition stages, support resource-sharing WM models, and urge scholars to adopt WM tests with a processing task performed under timed conditions, and to analyse response time.
Towards Visualization Recommendation - A Semi- Automated Domain-Specific Learning Approach

Information visualization is important in science as it helps scientists in exploring, analysing, and presenting both the obvious and less obvious features of their datasets. However, scientists are not typically visualization experts. It is therefore difficult and time-consuming for them to choose the optimal visualization to convey the desired message. To provide a solution for this problem of visualization selection, we propose a semi-automated, context aware visualization recommendation model. In the model, information will be extracted from data and metadata, the latter providing relevant context. This information will be annotated with suitable domain specific operations (like rank abundance), which will be mapped to the relevant visualizations. We also propose an interactive learning workflow for visualization recommendation that will enrich the model from the knowledge gathered from the interaction with the user. We will use biodiversity research as the application domain to guide the concrete instantiation of our approach and its evaluation.
Acoustic Geo-Sensing: Recognising cyclists' route, route direction, and route progress from cell-phone audio

We introduce the discipline of Acoustic Geo-Sensing (AGS) that deals with the connection of acoustics and geoposition, i. e. , `local audio' - focussing on spatial rather than on temporal aspects. We motivate this field of research, and give an example by automatic determination of a cyclist's route between determined start and endpoints, the direction she advances on this route, and the progress made from cell-phone audio. The Graz Cell-phone Cycle Corpus of 16 hours audio is introduced to this end. A standardised acoustic feature set ensures reproducibility throughout extensive experimentation aiming to reveal maximal spatiotemporal resolution. In the result, principle feasibility is shown by unsupervised clustering and all presented tasks can be solved at high accuracies and correlation within Random Forest classification and Additive Regression.
A Slip-Line Field for Ploughing During Orthogonal Cutting

Under normal machining conditions, the cutting forces are primarily due to the bulk shearing of the workpiece material in a narrow zone called the shear zone. However, under finishing conditions, when the uncut chip thickness is of the order of the cutting edge radius, a ploughing component of the forces becomes significant as compared to the shear forces. Predicting forces under these conditions requires an estimate of ploughing. A slip-line field is developed to model the ploughing components of the cutting force. The field is based on other slip-line fields developed for a rigid wedge sliding on a half-space and for negative rake angle orthogonal cutting. It incorporates the observed phenomena of a small stable build-up of material adhered to the edge and a raised prow of material formed ahead of the edge. The model shows how ploughing forces are related to cutter edge radius — a larger edge causing larger ploughing forces. A series of experiments were run on 6061-T6 aluminum using tools with different edge radii — including some exaggerated in size – and different levels of uncut chip thickness. Resulting force measurements match well to predictions using the proposed slip-line field. The results show great promise for understanding and quantifying the effects of edge radius and worn tool on cutting forces.
Architecturally-efficient computation of shortest paths for a mobile robot

The computation of shortest path for a mobile robot to get to a destination is considered in this paper. An architecturally-efficient solution is presented for this problem. Results of implementation in Xilinx Virtex FPGA are promising: the solution operates at approximately 72 MHz and the implementation for a graph with 40 nodes and 52 edges fits in one XCV3200E-FG1156 device.
Restriction Site Extension PCR: A Novel Method for High-Throughput Characterization of Tagged DNA Fragments and Genome Walking

Background Insertion mutant isolation and characterization are extremely valuable for linking genes to physiological function. Once an insertion mutant phenotype is identified, the challenge is to isolate the responsible gene. Multiple strategies have been employed to isolate unknown genomic DNA that flanks mutagenic insertions, however, all these methods suffer from limitations due to inefficient ligation steps, inclusion of restriction sites within the target DNA, and non-specific product generation. These limitations become close to insurmountable when the goal is to identify insertion sites in a high throughput manner. Methodology/Principal Findings We designed a novel strategy called Restriction Site Extension PCR (RSE-PCR) to efficiently conduct large-scale isolation of unknown genomic DNA fragments linked to DNA insertions. The strategy is a modified adaptor-mediated PCR without ligation. An adapter, with complementarity to the 3′ overhang of the endonuclease (KpnI, NsiI, PstI, or SacI) restricted DNA fragments, extends the 3′ end of the DNA fragments in the first cycle of the primary RSE-PCR. During subsequent PCR cycles and a second semi-nested PCR (secondary RSE-PCR), touchdown and two-step PCR are combined to increase the amplification specificity of target fragments. The efficiency and specificity was demonstrated in our characterization of 37 tex mutants of Arabidopsis. All the steps of RSE-PCR can be executed in a 96 well PCR plate. Finally, RSE-PCR serves as a successful alternative to Genome Walker as demonstrated by gene isolation from maize, a plant with a more complex genome than Arabidopsis. Conclusions/Significance RSE-PCR has high potential application in identifying tagged (T-DNA or transposon) sequence or walking from known DNA toward unknown regions in large-genome plants, with likely application in other organisms as well.
Motion-based counter-measures to photo attacks in face recognition

Identity spoofing is a contender for high-security face recognition applications. With the advent of social media and globalized search, our face images and videos are wide-spread on the internet and can be potentially used to attack biometric systems without previous user consent. Yet, research to counter these threats is just on its infancy – we lack public standard databases, protocols to measure spoofing vulnerability and baseline methods to detect these attacks. The contributions of this work to the area are three-fold: firstly we introduce a publicly available PHOTO-ATTACK database with associated protocols to measure the effectiveness of counter-measures. Based on the data available, we conduct a study on current state-of-the-art spoofing detection algorithms based on motion analysis, showing they fail under the light of these new dataset. By last, we propose a new technique of counter-measure solely based on foreground/background motion correlation using Optical Flow that outperforms all other algorithms achieving nearly perfect scoring with an equal-error rate of 1.52% on the available test data. The source code leading to the reported results is made available for the replicability of findings in this article.
Wavelet Analysis of Middle Latency Auditory Evoked Responses: Calculation of an Index for Detection of Awareness during Propofol Administration

Background Middle latency auditory evoked responses (MLAER) as a measure of depth of sedation are critically dependent on data quality and the analysis technique used. Manual peak labeling is subject to observer bias. This study investigated whether a user-independent index based on wavelet transform can be derived to discriminate between awake and unresponsive states during propofol sedation. Methods After obtaining ethics committee approval and written informed consent, 13 volunteers and 40 patients were studied. In all subjects, propofol was titrated to loss of response to verbal command. The volunteers were allowed to recover, then propofol was titrated again to the same end point, and subjects were finally allowed to recover. From three MLAER waveforms at each stage, latencies and amplitudes of peaks Pa and Nb were measured manually. In addition, wavelet transform for analysis of MLAER was applied. Wavelet transform gives both frequency and time information by calculation of coefficients related to different frequency contents of the signal. Three coefficients of the so-called wavelet detail level 4 were transformed into a single index (Db3d4) using logistic regression analysis, which was also used for calculation of indices for Pa, Nb, and Pa/Nb latencies. Prediction probabilities for discrimination between awake and unresponsive states were calculated for all MLAER indices. Results During propofol infusion, subjects were unresponsive, and MLAER components were significantly depressed when compared with the awake states (P < 0.001). The wavelet index Db3d4 was positive for awake and negative for unresponsive subjects with a prediction probability of 0.92. Conclusion These data show that automated wavelet analysis may be used to differentiate between awake and unresponsive states. The threshold value for the wavelet index allows easy recognition of awake versus unresponsive subjects. In addition, it is independent of subjective peak identification and offers the advantage of easy implementation into monitoring devices.
A study on robustness property of sliding-mode controllers: a novel design and experimental investigations

The robustness property of sliding-mode controllers (SMCs) makes them attractive for industrial control applications. However, this property is valid only under ideal sliding-mode conditions. Additionally, practical SMCs are likely to exhibit high-frequency oscillations in the plant output, called chattering, and to excite unmodeled dynamics. A novel, chattering-free sliding-mode control algorithm design, based on Lyapunov stability criteria, is considered in this paper. The control algorithm developed is experimentally implemented on a direct-drive manipulator for various payload configurations. It is seen that the controller carries a certain amount of robustness property, the trajectory-following performance being only slightly affected by the changes in the payload. A comparison of the experimental results with those obtained by a well-tuned proportional-derivative control is also given.