Miracle-dz/UniFAR-FTUs huggingface dataset:
Holistic Privacy Impact Assessment Framework for Video Privacy Filtering Technologies

In this paper, we present a novel Holistic Framework for Privacy Protection Level Performance Evaluation and Impact Assessment (H-PIA) to support the design and deployment of privacy-preserving filtering techniques as may be co-evolved for video surveillance through user-centred participative engagement and collectively negotiated solution seeking for privacy protection. The proposed framework is based on the UI-REF normative ethno-methodological framework for Privacy-by-Co-Design which is based on collective-interpretivist and socio-psycho-cognitively rooted Human Judgment and Decision Making (JDM) theory including Pleasure-Pain-Recall (PPR)-theoretic opinion elicitation and analysis. This supports not only the socio-ethically reflective conflicts resolution, prioritisation and traceability of privacy-preserving requirements evolving through user-centred co-design but also the integration of Key Holistic Performance Indicators (KPIs) comprising a number of objective and subjective evaluation metrics for the design and operational deployment of surveillance data/-video-analytics from a system-of-system-scale context-aware accountability engineering perspective. For the objective tests, we have proposed five crucial criteria to be evaluated to assess the optimality of the balance of privacy protection and security assurance as may be negotiated with end-users through co-design of a privacy filtering solution. This evaluation is supported by a process of quantitative assessment of some of the KPIs through an automated objective measurement of the functional performance of the given filter. Additionally, a subjective qualitative user study has been conducted to correlate with, and cross-validate, the results obtained from the objective assessment of the KPIs. The simulation results have confirmed the sufficiency, necessity and efficacy of the UI-REF-based methodologically-guided framework for Privacy Protection evaluation to enable optimally balanced Privacy Filtering of the video frame whilst retaining the minimum of the information as negotiated per agreed process logic. Insights from this study have served the co-design and deployment optimisation of privacy-preserving video filtering solutions. This UI-REF-based framework has been successfully applied to the evaluation of MediaEval 2012-2013 Privacy Filtering and as such has served to motivates further innovation in co-design and multi-level, multi-modal impact assessment of multimedia privacy-security-balancing risk mitigation technologies.
Targeting calcium cycling proteins in heart failure through gene transfer

Our understanding of cardiac excitation‐contraction coupling has improved significantly over the last 10 years. Furthermore, defects in the various steps of excitation‐contraction coupling that characterize cardiac dysfunction have been identified in human and experimental models of heart failure. The various abnormalities in ionic channels, transporters, kinases and various signalling pathways collectively contribute to the ‘failing phenotype. ’ However, deciphering the causative changes continues to be a challenge. An important tool in dissecting the importance of the various changes in heart failure has been the use of cardiac gene transfer. To achieve effective cardiac gene transfer a number of obstacles remain, including appropriate vectors for gene delivery, appropriate delivery systems, and a better understanding of the biology of the disease. In this review, we will examine our current understanding of these various factors. Gene transfer provides not only a potential therapeutic modality but also an approach to identifying and validating molecular targets.
Double-Layered Vibratory Grating Scanners for High-Speed High-Resolution Laser Scanning

A novel micromachined electrostatic double-layered vibratory grating scanner has been successfully developed for high-speed high-resolution laser scanning applications. This paper presents its design, modeling, fabrication, and measurement results. A comprehensive dynamic model considering the geometric nonlinearity of the platform suspension flexures is also proposed to predict the dynamic performance of the device at large scanning amplitudes. Compared with previously reported single-layered vibratory grating scanners, double-layered scanners - in which the diffraction grating and its driving actuator are located in different layers - have the potential to scan at large amplitudes and at high scanning speeds with large aperture sizes. We have demonstrated a prototype with a 2-mm-diameter diffraction grating which is capable of scanning at 23.391 kHz with an optical scan angle of around 33° and a resulting θopticalD product (product of the optical scan angle and diameter of the diffraction grating) of 66 deg mm.
Imaging Neuroinflammation – from Bench to Bedside

Neuroinflammation plays a central role in a variety of neurological diseases, including stroke, multiple sclerosis, Alzheimer’s disease, and malignant CNS neoplasms, among many other. Different cell types and molecular mediators participate in a cascade of events in the brain that is ultimately aimed at control, regeneration and repair, but leads to damage of brain tissue under pathological conditions. Non-invasive molecular imaging of key players in the inflammation cascade holds promise for identification and quantification of the disease process before it is too late for effective therapeutic intervention. In this review, we focus on molecular imaging techniques that target inflammatory cells and molecules that are of interest in neuroinflammation, especially those with high translational potential. Over the past decade, a plethora of molecular imaging agents have been developed and tested in animal models of (neuro)inflammation, and a few have been translated from bench to bedside. The most promising imaging techniques to visualize neuroinflammation include MRI, positron emission tomography (PET), single photon emission computed tomography (SPECT), and optical imaging methods. These techniques enable us to image adhesion molecules to visualize endothelial cell activation, assess leukocyte functions such as oxidative stress, granule release, and phagocytosis, and label a variety of inflammatory cells for cell tracking experiments. In addition, several cell types and their activation can be specifically targeted in vivo, and consequences of neuroinflammation such as neuronal death and demyelination can be quantified. As we continue to make progress in utilizing molecular imaging technology to study and understand neuroinflammation, increasing efforts and investment should be made to bring more of these novel imaging agents from the “bench to bedside. ”
Yersinia pestis Orientalis in Remains of Ancient Plague Patients

Yersinia pestis DNA was recently detected in human remains from 2 ancient plague pandemics in France and Germany. We have now sequenced Y. pestis glpD gene in such remains, showing a 93-bp deletion specific for biotype Orientalis. These data show that only Orientalis type caused the 3 plague pandemics.
Average model of dual active bridge interfacing ultra-capacitor in electrical vehicle

In this paper a new bidirectional DC-DC converter is proposed to transfer energy between ultra-capacitor and DC bus in electric vehicle. We present the average model of this converter. This model is used to calculate the small signal and transient characteristics of the converter. The derived small signal model can be developed and the transfer function between the output voltage and the duty cycle is calculated. This function is used to design a PI controller to regulate the output voltage at desired voltage in the closed loop under load and input voltage variations with at short time response.
Illustrated guide to the classification of banana seeds and embryos

Abstract Considering there is no illustrated scale of the principle anomalies observed for banana seeds, the objective of this guide is to cover in detail, for the first time, the categories to classify the most common types of anomalies observed in banana embryos and seeds, as well as in vitro embryo rescue and culture, taking into account the experience acquired by the banana breeding program at Embrapa in Brazil. Four classes to classify the seeds were proposed and with regards to classifying the embryos, eight classes were established.
Serial study of CD5+ and CD5‐ B cell subpopulations in 335 HIV seropositive patients

B cell subpopulations, as defined by double‐labelling techniques with CD5 and CD19 monoclonal antibodies (MoAbs), were serially studied in 335 HIV‐1 seropositive patients. At the time of the first consultation, no important modifications in either CD5+ or CD5‐ subpopulations were observed, whatever the stage of the disease. However, in 18 out of the 335 patients (5.37%), a sharp increase in 8 cells exceeding 20% and 300/mm3 was observed. This increase in B cells was mainly accounted for CD5‐CD19+ B cell subpopulations and was associated with: (i) evolution of the disease, since only four patients presented it at their first consultation (one lymphadenopathy‐associated syndrome (LAS) and three AIDS); (ii) advanced stages of disease since, at the time of B cell augmentation, two patients were staged as LAS, four as ARC and 12 as AIDS; (iii) a high incidence of non‐Hodgkin's lymphomas(NHL) since three out of the 18 patients presented a histologically confirmed NHL and three others a clinical pattern compatible with this diagnosis. However, in three patients with B hyperlymphocytosis, polymerase chain reaction (PCR) studies of immunoglobulin gene rearrangement revealed the existence of a polyclonal expansion of B cells. These results justify inclusion of a pan‐B cell marker in routine phenotypic studies of HIV‐infected individuals, as well as the search for NHL among patients presenting this abnormality.
An Attention-based Neural Network Approach for Single Channel Speech Enhancement

This paper proposes an attention-based neural network approach for single channel speech enhancement. Our work is inspired by the recent success of attention models in sequence-to-sequence learning. It is intuitive to use attention mechanism in speech enhancement as humans are able to focus on the important speech components in an audio stream with "high attention" while perceiving the unimportant region (e.g., noise or interference) in "low attention", and thus adjust the focal point over time. Specifically, taking noisy spectrum as input, our model is composed of an LSTM based encoder, an attention mechanism and a speech generator, resulting in enhanced spectrum. Experiments show that, as compared with OM-LSA and the LSTM baseline, the proposed attention approach can consistently achieve better performance in terms of speech quality (PESQ) and intelligibility (STOI). More promisingly, the attention-based approach has better generalization ability to unseen noise conditions.
Magnitude and velocity of proximal vergence.

Until recently proximal vergence was considered to play only a minor role in the eye alignment changes that occur when looking between distant and near targets. We measured the magnitude and velocity of proximal vergence using infrared limbal sensing to record vergence responses between two untextured luminous horizontal rods which lacked disparity and accommodative cues. The magnitude of proximal vergence responses averaged 3.9 degrees for convergence and 3.8 degrees for divergence, about 70% of the total vergence "demand. " Peak velocities for proximal convergence and divergence averaged 69 and 53 deg/sec, substantially faster than the velocities of comparably sized disparity or accommodative vergence responses. Its rapid velocity makes proximal vergence well suited to initiate the eye alignment changes between distant and near targets.
Acoustic Influence of Vehicles on a Protected Natural Area in the Southwest of the Iberian Peninsula

Natural sounds are essential elements for ecosystems, and therefore necessary for many ecological functions, forming what is called “natural soundscapes”. The Natural Reserve Laguna del Portil (NRLP), located in the southwest of the Iberian Peninsula, is an ecosystem which was declared by Spanish authorities as Protected Natural Reserve. In the south area of the NRLP, there is a regional road with high traffic intensity, which affects the soundscapes of this natural reserve. In this study, the road potential noise impact on the natural sounds of the NLRP is analysed. This analysis was done both in winter and summer, and also using two independent methods: 1) spatial sampling measures in 43 different points of the NRL; and 2) noise mapping using noise levels prediction software. From the comparison of the results of both methods and seasons the following conclusions were reached: 1) an approach to the natural soundscape of NRLP both in winter and summer, 2) the acoustic impact of the road on the NRLP, and 3) the variation of the traffic noise depending on the distance to the road, and its seasonal variation. This study could be to improve the management of the NRLP and to help to preserve the natural soundscape of the reserve.
Human Metapneumovirus Glycoprotein G Disrupts Mitochondrial Signaling in Airway Epithelial Cells

Human metapneumovirus (hMPV) is a recently identified RNA virus belonging to the Paramyxoviridae family. It is a common cause of respiratory tract infections in children, adults, and immunocompromised patients, for which no specific treatment or vaccine is available. Recent investigations in our lab identified hMPV glycoprotein G as an important virulence factor, as a recombinant virus lacking the G protein (rhMPV-ΔG) exhibited enhanced production of important immune and antiviral mediators, such as cytokines, chemokines and type I interferon (IFN) in airway epithelial cells, and expression of G protein alone inhibits cellular signaling dependent on retinoic induced gene (RIG)-I, a RNA helicase with a fundamental role in initiating hMPV-induced cellular responses. In this study, we have further investigated the mechanism underlying the inhibitory role of hMPV G protein on RIG-I-dependent signaling. We found that the interaction of hMPV G with RIG-I occurs primarily through the CARD domains of RIG-I N-terminus, preventing RIG-I association with the adaptor protein MAVS (mitochondrial antiviral signaling protein), recruitment of RIG-I to mitochondria, as well as the interaction between mitochondria and mitochondria-associated membrane (MAM) component of the endoplasmic reticulum (ER), which contains STINGS, an important part of the viral-induced RIG-I/MAVS signaling pathway, leading in the end to the inhibition of cytokine, chemokine and type I IFN expression. Mutagenesis analysis showed that hMPV G protein cytoplasmic domain played a major role in the observed inhibitory activity, and recombinant viruses expressing a G protein with amino acid substitution in position 2 and 3 recapitulated most of the phenotype observed with rhMPV-ΔG mutant upon infection of airway epithelial cells.
E-PHEMT for single supply, no drain switch, and high efficiency cellular telephone power amplifiers

Performance of a newly developed enhancement mode power PHEMT technology is demonstrated for single supply, no drain switch, high efficiency cellular telephone power amplifier applications. The E-PHEMT features Idss=0.5 /spl mu/A/mm, Imax=190 mA/mm, V/sub p/=+0.3 V, Gm=340 mS/mm, and Vbdg=20 V. When matched on-wafer for a compromise between power and efficiency at 900 MHz, the E-PHEMT achieves Pout=100-140 mW/mm with associated PAE=70 % at 3.2 V and Pout=35 mW/mm and PAE=71% at 1.5 V. The new E-PHEMT has high gain, excellent efficiency under linear and 1 dB compressed gain conditions, making it attractive for high efficiency linear power amplifiers. A 10 mm E-PHEMT achieves remarkably similar saturated power and efficiency performance over 0 to 400 mA quiescent bias current range, which allows low power dissipation operation for high reliability.
Direction Preserving Wiener Matrix Filtering for Ambisonic Input-output Systems

We present a spatial matrix filtering framework for noise reduction in the spherical harmonics (ambisonics) domain (SHD), which outputs an SHD signal vector rather than one signal as commonly provided by beamforming approaches. We discuss two spatial matrix filtering methods: A multi-beamformer method using known propagation vectors of the desired signal components and a method preserving the directional information in an optimal way. Parametric multi-channel Wiener filter solutions for both methods are discussed and a performance evaluation is conducted. It is shown that the direction preserving method preserves the spatial distribution of the desired sounds and residual noise at the cost of less noise reduction and higher signal distortion when compared to the multi-beamformer approach. Moreover, no spatial parameters have to be estimated.
Accurate Power Spectrum Estimation of Speech with Spectrum Compensation Based on Prediction Error Filtering

This paper proposes a linear prediction (LP) method to estimate accurately the original power spectrum of the input speech signal. A prediction error filter (PEF) is used as a pre-processor, and the LP based power spectrum estimation is compensated by the frequency characteristics of the designed PEF. Through experiments on synthetic vowels, we show that the proposed spectrum compensation method can estimate the power spectrum more accurately than the direct and pre-emphasis LP methods.
Post-Level Spam Detection for Social Bookmarking Web Sites

Social book marking Web sites have emerged recently for collecting and sharing of interesting Web sites among users. People can add Web pages to such sites as bookmarks and allow themselves as well as others to manipulate them. One of the key features of the social book marking sites is the ability of annotating a Web page when it is being bookmarked. The annotation usually contains a set of words or phrases, which are collectively known as tags, that could reveal the semantics of the annotated Web page. Efficient and effective search of Web pages can then be achieved via such tags. However, spam tags that are irrelevant to the content of Web pages often appear to deceive other users for malicious or commercial purposes. Various techniques have been devised to tackle such tag spam detection problem. Most of these techniques were able to detect a user that always annotate spam tags. However, finer levels of detection are seldom discussed. In this work, we will propose a method based on a text mining approach to discover the relations between Web pages and there tag posts. These relations are then used to compute the similarity between a Web page and its tag post to decide if it is a spam post. Preliminary experiments show that the accuracy of the post-level spam detection task is 83%.
Measuring Learner Satisfaction with Formative e-Assessment Strategies

The student experience with different aspects of online instructional settings has been the focus of educational practitioners and researchers in many studies. However, concerning technology-enabled formative assessment, little is known about student satisfaction regarding different possible formative e-assessment strategies the students are involved in. Using a 5-point Likert scale questionnaire, a web-based survey was developed to examine students’ satisfaction with the formative e-assessment strategies within an enriched virtual blended course. The results show that, in general, the students were satisfied with the quality of their engagement and the quality of feedback across all the formative e-assessment activities offered. The results also show that the student satisfaction varied between and within the formative e-assessment strategies. However, the gap between the student satisfaction mean ratings across all formative e-assessment strategies was marginal and could not help researchers decide upon which formative e-assessment strategy that stood out as the most preferred one. Learner satisfaction with different formative e-assessment strategies was positively correlated to each other at various levels but no relationship was found between students’ scores on the final course exam and learner satisfaction with formative e-assessment strategies. In the end, the results indicated that a sustained and integrated use of the all three formative e-assessment strategies (online knowledge survey, online student-generated questions and peer-responses, and electronic reflective journals) should be used in the context of hybrid courses. The study also suggests further studies that would widen, diversify both the scope and research instruments to investigate learner satisfaction with formative e-assessment strategies.
Ropivacaine 0.075% and Bupivacaine 0.075% with Fentanyl 2 &mgr;g/mL are Equivalent for Labor Epidural Analgesia

Fifty percent effective dose estimates for ropivacaine and bupivacaine suggest that ropivacaine is 40% less potent than bupivacaine to initiate labor analgesia. At clinically used concentrations, however, the drugs seem indistinguishable for initiating and maintaining labor analgesia. We designed this study to evaluate a concentration near the reported 50% effective dose values for ropivacaine and bupivacaine in an attempt to detect differences between the drugs during routine clinical use. Fifty-nine nulliparous women in labor were randomized to receive 0.075% ropivacaine or bupivacaine, each with fentanyl 2 &mgr;g/mL. After epidural placement and the administration of a lidocaine/epinephrine test dose, 20 mL of study solution was administered and a patient-controlled epidural infusion was initiated with the following settings: 6 mL/h basal rate, 5 mL bolus, 10 min lockout, and 30 mL/h limit. Breakthrough pain was treated with 10-mL boluses of study solution. By using a study design to detect a 40% difference in hourly drug use between groups, we found no statistically significant differences in the amount of local anesthetic used, verbal pain scores, sensory levels, motor blockade, labor duration, mode of delivery, side effects, or patient satisfaction. We conclude that 0.075% ropivacaine and bupivacaine, with fentanyl, are equally effective for labor analgesia using the patient-controlled epidural analgesia technique.
Doctoral Symposium: An Embedded DSL Framework for Distributed Embedded Systems

Programming distributed embedded systems gives rise to a number of challenges. The distributed nodes are typically resource constrained, requiring expert systems programming skills to manage the limited power, communication bandwidth, and memory and computation constraints. The challenge of raising the level of abstraction of programming such systems without incurring too high of an execution performance penalty is thus an important one, and many approaches have been explored in the literature. The work presented in this paper investigates a framework and domain specific language (DSL) to enable programming of such systems at a global network level. The framework enables the compilation, analysis, transformation and interpretation of high-level descriptions of stream processing applications in which information is received and processed in real-time. The ongoing research aims at investigating the following directions. Firstly, a framework to allow the manipulation and multiple interpretations of a stream processor description to support the heterogeneity aspect of devices. Secondly, a language to hide the low-level detail from the developer, while allowing the developer to add hints to enable more efficient compilations. Thirdly, through transformations, different stream processing applications can be fused together to run on the same distributed network to make best of use of available resources.