Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavioral/systems/cognitive Functional Magnetic Resonance Imaging of Delay and Trace Eyeblink Conditioning in the Primary Visual Cortex of the Rabbit

The primary sensory cortices have been shown in recent years to undergo experience-and learning-related plasticity under a variety of experimental circumstances. In this study, we used functional magnetic resonance imaging (fMRI) in parallel with both delay and trace eyeblink conditioning to image the learning-related functional activation within the primary visual cortex (V1) of awake, behaving rabbits. We expected that the differing level of forebrain dependence between these two conditioning paradigms should produce a differential blood oxygenation level-dependent (BOLD) functional response in V1. Our results showed a significant expansion of activated volume within V1, particularly early in learning, after training with the more cognitively demanding trace paradigm. In contrast, the simpler delay paradigm produced an increase in the magnitude of the BOLD response in activated voxels, but no significant change in activated volume. No accompanying learning-related changes were observed in the primary somatosensory cortex, which mediates the unconditioned stimulus. These results suggest that the recruitment of additional neurons within V1 is necessary to support the more demanding memory imposed by the trace interval. To our knowledge, this work is the first functional imaging study to compare directly trace and delay eyeblink conditioning in an animal model.
Inference of Plant Diseases from Leaf Images through Deep Learning

1Digital Epidemiology Lab, EPFL, Switzerland; 2School of Life Sciences, EPFL, Switzerland; 3Department of Entomology, College of Agricultural Sciences, Penn State University, USA; 4Department of Biology, Eberly College of Sciences, Penn State University, USA; 5Center for Infectious Disease Dynamics, Huck Institutes of Life Sciences, Penn State University, USA; 6School of Computer and Communication Sciences, EPFL, Switzerland
Tumorigenicity and Validity of Fluorescence Labelled Mesenchymal and Epithelial Human Oral Cancer Cell Lines in Nude Mice

Tumorigenicity and metastatic activity can be visually monitored in cancer cells that were labelled with stable fluorescence. The aim was to establish and validate local and distant spread of subcutaneously previously injected fluorescence transduced human tongue cancer cell lines of epithelial and mesenchymal phenotype in nude mice. A total of 32 four-week-old male athymic Balb/c nude mice were randomly allocated into 4 groups (n = 8). A single dose of 0.3 mL PBS containing 1 × 107 of four different cancer cell-lines (UM1, UM1-GFP, UM2, and UM2-RFP) was injected subcutaneously into the right side of their posterolateral back. Validity assessment of the labelled cancer cells' tumorigenicity was assessed by physical examination, imaging, and histology four weeks after the injection. The tumor take rate of cancer cells was similar in animals injected with either parental or transduced cancer cells. Transduced cancer cells in mice were easily detectable in vivo and after cryosection using fluorescent imaging. UM1 cells showed increased tumor take rate and mean tumor volume, presenting with disorganized histopathological patterns. Fluorescence labelled epithelial and mesenchymal human tongue cancer cell lines do not change in tumorigenicity or cell phenotype after injection in vivo.
An Entrance for the Uninterested: Who Watches Soft News and How Does It Affect Their Political Participation?

As soft news shows in television present politics in an entertaining format, they are likely to attract and grab the attention of people who do not have a high interest in politics. Consequently, soft news might mobilize these citizens to engage in politics. This study tests this potential by using a 2-wave panel survey among a national sample of voters (N = 2,680) collected in relation to the 2015 National Election in Denmark. The results show that people with lower political interest were indeed more likely to increase their use of soft news during the election campaign and that, as a consequence, these low-motivated people also increased their passive participation, such as seeking additional information about the election. Further, the results show that this type of passive participation is likely to function as a stepping-stone to active forms of participation, such as attending political events or contacting politicians.
A Cloud Service for Adaptive Digital Music Streaming

In this paper we present an adaptive digital music streaming cloud service based on the Amazon Web Services; the players are applications running on mobile devices connected to the Internet via cellular or via wireless networks. Adaptive streaming means that the data rate is determined dynamically function of the available network bandwidth, as well as power reserves of the mobile device. The service applies lossy compression to high quality audio files stored on the cloud to lower the data rate at a level determined by the resources available. We analyze the results of experiments with real-time data conversion for adaptation to the bandwidth available to mobile devices such as smart phones and tablets.
Important Variables When Screening for Students at Suicidal Risk: Findings from the French Cohort of the SEYLE Study

Due to early detection of mental ill-health being an important suicide preventive strategy, the multi-centre EU funded “Saving and Empowering Young Lives in Europe” (SEYLE) study compared three school-based mental health promotion programs to a control group. In France, 1007 students with a mean age of 15.2 years were recruited from 20 randomly assigned schools. This paper explores the French results of the SEYLE’s two-stage screening program (ProfScreen) and of the cross-program suicidal emergency procedure. Two-hundred-thirty-five ProfScreen students were screened using 13 psychopathological and risk behaviour scales. Students considered at risk because of a positive finding on one or more scales were offered a clinical interview and, if necessary, referred for treatment. A procedure for suicidal students (emergency cases) was set up to detect emergencies in the whole cohort (n = 1007). Emergency cases were offered the same clinical interview as the ProfScreen students. The interviewers documented their reasons for referrals in a short report. 16,2% of the ProfScreen students (38/235) were referred to treatment and 2,7% of the emergency cases (27/1007) were also referred to treatment due to high suicidal risk. Frequent symptoms in those students referred for evaluation were depression, alcohol misuse, non-suicidal self-injuries (NSSI), and suicidal behaviours. According to the multivariate regression analysis of ProfScreen, the results show that the best predictors for treatment referral were NSSI (OR 2.85), alcohol misuse (OR 2.80), and depressive symptoms (OR 1.13). Analysis of the proportion for each scale of students referred to treatment showed that poor social relationships (60%), anxiety (50%), and suicidal behaviours (50%) generated the highest rate of referrals. Qualitative analysis of clinician’s motivations to refer a student to mental health services revealed that depressive symptoms (51%), anxiety (38%), suicidal behaviours (40%), and negative life events (35%) were the main reasons for referrals. Thus, not only the classical psychopathological symptoms, such as depression, anxiety, and suicidal behaviours, but also negative life events and poor social relationships (especially isolation) motivate referrals for treatment.
Reflowing digital ink annotations

Annotating paper documents with a pen is a familiar and indispensable activity across a wide variety of work and educational settings. Recent developments in pen-based computing promise to bring this experience to digital documents. However, digital documents are more flexible than their paper counterparts. When a digital document is edited, or displayed on different devices, its layout adapts to the new situation. Freeform digital ink annotations made on such a document must likewise adapt, or "reflow. " But their unconstrained nature yields only vague guidelines for how these annotations should be transformed. Few systems have considered this issue, and still fewer have addressed it from a user's point of view. This paper reports the results of a study of user expectations for reflowing digital ink annotations. We explore user reaction to reflow in common cases, how sensitive users are to reflow errors, and how important it is that personal style survive reflow. Our findings can help designers and system builders support freeform annotation more effectively.
A new Image compression technique using principal component analysis and Huffman coding

Principal component analysis (PCA) is one of the most widely used techniques for dimension reduction. It exploits the dependencies among the variables and represents the higher dimensional data in the lower dimensional with more amenable form, without losing a countable information. In this paper, we present a new image compression technique that uses PCA and Huffman coding. The input image is first compressed by using PCA, few of the principal components (PCs) are used to reconstruct the image, while the other less significant PCs are ignored. The reconstructed image is further quantized with dither to reduce contouring, occurred due to less number of PCs are used in image reconstruction. Finally, the Huffman coding is applied on quantized image to remove coding redundancy. The proposed image compression technique is applied on several test images and results are compared with JPEG2000. Comparative analysis and visual results clearly show that the proposed technique performs better than the JPEG2000.
Efficient curve-sensitive features for offline signature verification

A novel system that is based on the efficient detection of curved lines within an input image is proposed for the purpose of offline signature verification. This is achieved by first trans­forming the signature image into five different representations of said image in polar coordinates, where each polar representation originates at a different strategic point. A modified version of the standard discrete Radon transform (sDRT) is subsequently applied to each polar representation. An ensemble of classifiers (for detecting curved lines), where each individual (base) classifier is associated with a different polar representation, is therefore constructed. An additional classifier (for detecting straight lines) is obtained through the calculation of the sDRT of the original signature image and is subsequently appended to said ensemble. It is shown that when signatures from different writers are considered, different base classifiers are the most proficient. An average equal error rate (EER) of 9.73% is reported for the majority vote decision of the six base classifiers in question, which represents an effective improvement of 4.37% on the average EER of the most proficient individual classifier.
Sequential non Bayesian network traffic flows anomaly detection and isolation

Sequential detection (and isolation) of unusual and significant changes in network Origin-Destination (OD) traffic volumes from simple link load measurements is considered in the paper. The ambient traffic, i.e. the OD traffic matrix corresponding to the non-anomalous network state, is unknown and it is considered here as a nuisance parameter because it can mask the anomalies. Since the OD traffic matrix is not recoverable from the simple link load measurements, the anomaly detection is an ill-posed decision-making problem. The method discussed in this paper consists of finding a linear parsimonious model of ambient traffic (nuisance parameter) and detecting/isolating anomalies by using an invariant decision algorithm. An optimal sequential algorithm has been discussed in our previous publication, the main goal of the actuel paper is to discuss a simple ``snapshot'' algorithm based on the last vector of observations.
Retargeting Images and Video for Preserving Information Saliency

A nonphotorealistic algorithm for retargeting images adapts large images so that important objects in the image are still recognizable when displayed at a lower target resolution. Unlike existing image manipulation techniques such as cropping and scaling, the retargeting algorithm can handle multiple important objects in an image. To identify the important objects in an image, we must first segment the image. We use mean-shift image segmentation to decompose an image into homogeneous regions.
Distinct mechanisms for the representation of moving and static objects

The visual system has been suggested to integrate different views of an object in motion. We investigated differences in the way moving and static objects are represented by testing for priming effects to previously seen ("known") and novel object views. We showed priming effects for moving objects across image changes (e.g., mirror reversals, changes in size, and changes in polarity) but not over temporal delays. The opposite pattern of results was observed for objects presented statically; that is, static objects were primed over temporal delays but not across image changes. These results suggest that representations for moving objects are: (1) updated continuously across image changes, whereas static object representations generalize only across similar images, and (2) more short-lived than static object representations. These results suggest two distinct representational mechanisms: a static object mechanism rather spatially refined and permanent, possibly suited for visual recognition, and a motion-based object mechanism more temporary and less spatially refined, possibly suited for visual guidance of motor actions.
Brief report: sleep in children with sickle cell disease: an analysis of daily diaries utilizing multilevel models.

OBJECTIVE To investigate the pain-sleep relationship in children with sickle cell disease (SCD) and the influence of stress and pain medication use on this relationship. METHOD Children with SCD (n = 20; aged 8-12 years) completed daily diaries assessing sleep, pain, stress, and pain medication use for up to 2 months. Data analyzed using multilevel modeling. RESULTS High daily pain was related to poor sleep quality that night and poor sleep quality was related to high pain the following day. High stress was related to less sleep. High same-day pain and pain medication attenuated the impact of pain on sleep quality. CONCLUSION Results highlight the importance of sleep in addressing functioning in children with chronic pain, knowledge which may help patients and their families better manage the child's pain. Behavioral pain interventions may be improved by the inclusion of strategies to encourage proper sleep hygiene and address sleep issues.
ECONOMIC CONSEQUENCES OF THE SARBANES-OXLEY ACT ON E-COMMERCE FIRMS

Regulators and practitioners are concerned about whether SOX Sections 302 and 404 IT-related implementation costs affect the market value of firms in the IT industry. Prior studies indicate that network advantages are the key feature of information-based industries and that E-commerce firms are a major segment of that industry. SOX Section 404 was expected to have significant impact on firms with primary E-commerce risks. In this paper, we find that SOX enactment results in a significant market value decline for these E-commerce firms.
Addressing Student Resilience in Post-Baccalaureate Programs: A Review of the Literature

The purpose of this review is to capture the scope of literature with regard to the current state of supports addressing student resilience. More specifically, this researcher is interested in those structures and interventions that are in place for post-baccalaureate students in higher education plans of study. In its infancy, research and intervention addressing this topic occurred at the K-12 level of education and later moved into baccalaureate programs of study for the most part. In addition, this research investigates the literature in order to explore the desired state in terms of student resilience. A deeper understanding of these two factors will drive future research in terms of the development and evaluation of appropriate interventions to address post-baccalaureate student resilience in higher education.
Bark Classification Using RBPNN Based on Gabor Filter in Different Color Space

This paper proposed a new method of extracting texture features based on Gabor wavelet in different color space. In addition, the application of these features for bark classification applying radial basis probabilistic network (RBPNN) and SVM (support vector machine) has been used. To extract the bark texture features, Gabor filter the image has been filtered with four orientations and six scales filters, and then the mean and standard deviation of the image output are computed. In addition, apart from these features of parameter of Gabor filter features, other features such as color distribution angles were also extracted. Finally, the combined Gabor feature vectors and color distribution angles are fed up into RBPNN and SVM for classification. The performance of colour space features is found to be better than that of the features which just extracted from grey image. Experimental results show that features extracted using the proposed approach can be used for bark texture classification.
Strategy, culture and institutional logics : a multi-layered view of community investment at a large housing association

This project is an ESRC CASE study of one of the largest housing associations in England. The aim of the study was to take a multi-layered view of the organisation to explore its changing identity, by tracking its evolving community investment strategy over a 2 year period as an examination of shifting sub-cultures and driving institutional logics. The underlying theme of a multi-layered approach led to a research design sub-dividing the organisation horizontally and vertically into management strata and functional and geographical sampling points. The focus on ‘strategy, culture, logics and community investment’ was derived from a research cycle which integrated both macro level issues and the organization’s internal agenda reflecting the inherent paradoxes characterising the hybrid third sector of social housing. The thesis builds on earlier work on competing institutional logics in social housing and links this to changing organisations cultures to show how hybridity is enacted over time. The author concludes that a dominant corporate sub-culture, tied into a commercial, customer-driven logic has been displacing more regional, local community cultures derived from the pre-merger organisations. This enactment process is exemplified by the centralisation and consumerisation of CI services depicted in the author’s logics-culture matrix.
Integrating symbolic techniques in ATPG-based sequential logic optimization

This paper presents a new integrated approach to logic optimization for sequential circuits. The approach is based on the redundancy addition and removal algorithm, which is based on automatic test pattern generation (ATPG) techniques, and improves it using symbolic techniques based on BDDs. The advantage of the integrated approach lies in the ability of Symbolic Techniques to provide exact and extensive information about the sequential behavior of the portion of the circuit that is of interest to the logic optimization algorithm. Experimental results are provided that show the superiority of the approach to the original ATPG-based optimization approach.
Mm-wave MIMO systems for high data-rate mobile communications

In this paper, the performance of 60 GHz MIMO system is analyzed based on experimental data. The mutual information (MI) of the measured channel is compared to the MI of an iid MIMO Rayleigh channel. It is seen that the mean MI of the channels are quite close to each other. Then, the MI of the MIMO system is compared to the one of a MIMO system with antenna selection. It is found that, when considering switching networks with realistic losses, the performance decreases drastically and, in most cases, MIMO antenna selection leads to lower MI than traditional MIMO with the same number of RF chains. Finally, the achievable data-rate of a realistic 4×4 MIMO system is calculated, based on the experimental data. It is shown that with 500 MHz bandwidth such a system can provide multigigabit communications at distance up to 10m.
Rule induction based on rough sets from possibilistic information under Lipski's approach

How rules are induced on the basis of rough sets under Lipski's approach has been examined in a possibilistic information system where attribute values in information tables are expressed by normal possibility distributions. In Lipski's approach possible tables are created from the original information table and each possible table has a possibilistic degree with which it is the actual information table. In each possible table, rough approximations are obtained for a set of objects. The possible membership degree of an object is the maximum of possibilistic degrees of possible tables where the object is included in the rough approximations. The certain membership degree is one minus the maximum of possibilistic degrees of possible tables where the object is not included in the rough approximations. Therefore, the certain and possible membership degrees are the lower and upper bounds of the membership degree that the object actually has. This leads an object to have membership degrees expressed by not a single, but an interval value for rough approximations, which is essential in possibilistic information systems. For the rough approximations, the complementarity property holds, as is so in complete information systems. This gives justification for dealing with possibilistic information under Lipski's approach. It is required to use rough approximations whose element consists of a pair of an object and a rule that it supports in order to induce rules from an information table. Criterion are introduced for whether or not objects validly supports rules, because they support lots of rules with low degrees in possibilistic information systems. By using the criterions, only rules that are validly supported can be selected from lots of rules.
Emergency resource redistribution in the developing world: towards a practical evolutionary/meta-heuristic scheduling system

The problem of logistics in aid projects in the developing world can hardly be understated. One problem that arises is the occurrence of regional imbalances in supply. Such imbalances can seriously compromise the effectiveness of a relief program. A system is required that can suggest a workable redistribution plan. Initial results for a prototype system based on a heuristic plan generator and evolutionary/meta-heuristic optimisers, on real data, were encouraging; however more work still needs to be undertaken before the system can be deployed in the real-world. This paper describes some ongoing work to address some of these issues.
Liquid phase production of graphene by exfoliation of graphite in surfactant/water solutions

We have demonstrated a method to disperse and exfoliate graphite to give graphene suspended in water-surfactant solutions. Optical characterisation of these suspensions allowed the partial optimisation of the dispersion process. Transmission electron microscopy showed the dispersed phase to consist of small graphitic flakes. More than 40% of these flakes had <5 layers with ~3% of flakes consisting of monolayers. These flakes are stabilised against reaggregation by Coulomb repulsion due to the adsorbed surfactant. However, the larger flakes tend to sediment out over ~6 weeks, leaving only small flakes dispersed. It is possible to form thin films by vacuum filtration of these dispersions. Raman and IR spectroscopic analysis of these films suggests the flakes to be largely free of defects and oxides. The deposited films are reasonably conductive and are semi-transparent. Further improvements may result in the development of cheap transparent conductors.