High susceptibility of MDR and XDR Gram-negative pathogens to biphenyl-diacetylene-based difluoromethyl-allo-threonyl-hydroxamate LpxC inhibitors.

OBJECTIVES: Inhibitors of uridine diphosphate-3-O-(R-3-hydroxymyristoyl)-N-acetylglucosamine deacetylase (LpxC, which catalyses the first, irreversible step in lipid A biosynthesis) are a promising new class of antibiotics against Gram-negative bacteria. The objectives of the present study were to: (i) compare the antibiotic activities of three LpxC inhibitors (LPC-058, LPC-011 and LPC-087) and the reference inhibitor CHIR-090 against Gram-negative bacilli (including MDR and XDR isolates); and (ii) investigate the effect of combining these inhibitors with conventional antibiotics. METHODS: MICs were determined for 369 clinical isolates (234 Enterobacteriaceae and 135 non-fermentative Gram-negative bacilli). Time-kill assays with LPC-058 were performed on four MDR/XDR strains, including Escherichia coli producing CTX-M-15 ESBL and Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii producing KPC-2, VIM-1 and OXA-23 carbapenemases, respectively. RESULTS: LPC-058 was the most potent antibiotic and displayed the broadest spectrum of antimicrobial activity, with MIC90 values for Enterobacteriaceae, P. aeruginosa, Burkholderia cepacia and A. baumannii of 0.12, 0.5, 1 and 1 mg/L, respectively. LPC-058 was bactericidal at 1× or 2× MIC against CTX-M-15, KPC-2 and VIM-1 carbapenemase-producing strains and bacteriostatic at ≤4× MIC against OXA-23 carbapenemase-producing A. baumannii. Combinations of LPC-058 with β-lactams, amikacin and ciprofloxacin were synergistic against these strains, albeit in a species-dependent manner. LPC-058's high efficacy was attributed to the presence of the difluoromethyl-allo-threonyl head group and a linear biphenyl-diacetylene tail group. CONCLUSIONS: These in vitro data highlight the therapeutic potential of the new LpxC inhibitor LPC-058 against MDR/XDR strains and set the stage for subsequent in vivo studies.

A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.

Design, fabrication and characterization of resonant waveguide grating based optical biosensors

The absence of rapid, low cost and highly sensitive biodetection platform has hindered the implementation of next generation cheap and early stage clinical or home based point-of-care diagnostics. Label-free optical biosensing with high sensitivity, throughput, compactness, and low cost, plays an important role to resolve these diagnostic challenges and pushes the detection limit down to single molecule. Optical nanostructures, specifically the resonant waveguide grating (RWG) and nano-ribbon cavity based biodetection are promising in this context. The main element of this dissertation is design, fabrication and characterization of RWG sensors for different spectral regions (e.g. visible, near infrared) for use in label-free optical biosensing and also to explore different RWG parameters to maximize sensitivity and increase detection accuracy. Design and fabrication of the waveguide embedded resonant nano-cavity are also studied. Multi-parametric analyses were done using customized optical simulator to understand the operational principle of these sensors and more important the relationship between the physical design parameters and sensor sensitivities. Silicon nitride (SixNy) is a useful waveguide material because of its wide transparency across the whole infrared, visible and part of UV spectrum, and comparatively higher refractive index than glass substrate. SixNy based RWGs on glass substrate are designed and fabricated applying both electron beam lithography and low cost nano-imprint lithography techniques. A Chromium hard mask aided nano-fabrication technique is developed for making very high aspect ratio optical nano-structure on glass substrate. An aspect ratio of 10 for very narrow (~60 nm wide) grating lines is achieved which is the highest presented so far. The fabricated RWG sensors are characterized for both bulk (183.3 nm/RIU) and surface sensitivity (0.21nm/nm-layer), and then used for successful detection of Immunoglobulin-G (IgG) antibodies and antigen (~1μg/ml) both in buffer and serum. Widely used optical biosensors like surface plasmon resonance and optical microcavities are limited in the separation of bulk response from the surface binding events which is crucial for ultralow biosensing application with thermal or other perturbations. A RWG based dual resonance approach is proposed and verified by controlled experiments for separating the response of bulk and surface sensitivity. The dual resonance approach gives sensitivity ratio of 9.4 whereas the competitive polarization based approach can offer only 2.5. The improved performance of the dual resonance approach would help reducing probability of false reading in precise bio-assay experiments where thermal variations are probable like portable diagnostics.

Chemical Sensor Based on a Long-Period Fibre Grating Modified by a Functionalized Polydimethylsiloxane Coating

A chemical sensor based on a coated long-period grating has been prepared and characterized. Designer coatings based on polydimethylsiloxane were prepared by the incorporation of diphenylsiloxane and titanium cross-linker in order to provide enhanced sensitivity for a variety of key environmental pollutants and optimal refractive index of the coating. Upon microextraction of the analyte into the polymer matrix, an increase in the refractive index of the coating resulted in a change in the attenuation spectrum of the long-period grating. The grating was interrogated using ring-down detection as a means to amplify the optical loss and to gain stability against misalignment and power fluctuations. Chemical differentiation of cyclohexane and xylene was achieved and a detection limit of 300 ppm of xylene vapour was realized.

Axis Mapping: The Estimation of Surface Orientations and its Applications in Vehicle Localization and Structural Geology

The map representation of an environment should be selected based on its intended application. For example, a geometrically accurate map describing the Euclidean space of an environment is not necessarily the best choice if only a small subset its features are required. One possible subset is the orientations of the flat surfaces in the environment, represented by a special parameterization of normal vectors called axes. Devoid of positional information, the entries of an axis map form a non-injective relationship with the flat surfaces in the environment, which results in physically distinct flat surfaces being represented by a single axis. This drastically reduces the complexity of the map, but retains important information about the environment that can be used in meaningful applications in both two and three dimensions. This thesis presents axis mapping, which is an algorithm that accurately and automatically estimates an axis map of an environment based on sensor measurements collected by a mobile platform. Furthermore, two major applications of axis maps are developed and implemented. First, the LiDAR compass is a heading estimation algorithm that compares measurements of axes with an axis map of the environment. Pairing the LiDAR compass with simple translation measurements forms the basis for an accurate two-dimensional localization algorithm. It is shown that this algorithm eliminates the growth of heading error in both indoor and outdoor environments, resulting in accurate localization over long distances. Second, in the context of geotechnical engineering, a three-dimensional axis map is called a stereonet, which is used as a tool to examine the strength and stability of a rock face. Axis mapping provides a novel approach to create accurate stereonets safely, rapidly, and inexpensively compared to established methods. The non-injective property of axis maps is leveraged to probabilistically describe the relationships between non-sequential measurements of the rock face. The automatic estimation of stereonets was tested in three separate outdoor environments. It is shown that axis mapping can accurately estimate stereonets while improving safety, requiring significantly less time and effort, and lowering costs compared to traditional and current state-of-the-art approaches.

Achievable rates and outage probability of cognitive radio with dynamic frequency hopping under imperfect spectrum sensing

In this study, the authors propose simple methods to evaluate the achievable rates and outage probability of a cognitive radio (CR) link that takes into account the imperfectness of spectrum sensing. In the considered system, the CR transmitter and receiver correlatively sense and dynamically exploit the spectrum pool via dynamic frequency hopping. Under imperfect spectrum sensing, false-alarm and miss-detection occur which cause impulsive interference emerged from collisions due to the simultaneous spectrum access of primary and cognitive users. That makes it very challenging to evaluate the achievable rates. By first examining the static link where the channel is assumed to be constant over time, they show that the achievable rate using a Gaussian input can be calculated accurately through a simple series representation. In the second part of this study, they extend the calculation of the achievable rate to wireless fading environments. To take into account the effect of fading, they introduce a piece-wise linear curve fitting-based method to approximate the instantaneous achievable rate curve as a combination of linear segments. It is then demonstrated that the ergodic achievable rate in fast fading and the outage probability in slow fading can be calculated to achieve any given accuracy level.

Semantic feature-based visual attention model for pedestrian detection

Objective
Pedestrian detection under video surveillance systems has always been a hot topic in computer vision research. These systems are widely used in train stations, airports, large commercial plazas, and other public places. However, pedestrian detection remains difficult because of complex backgrounds. Given its development in recent years, the visual attention mechanism has attracted increasing attention in object detection and tracking research, and previous studies have achieved substantial progress and breakthroughs. We propose a novel pedestrian detection method based on the semantic features under the visual attention mechanism.
Method
The proposed semantic feature-based visual attention model is a spatial-temporal model that consists of two parts: the static visual attention model and the motion visual attention model. The static visual attention model in the spatial domain is constructed by combining bottom-up with top-down attention guidance. Based on the characteristics of pedestrians, the bottom-up visual attention model of Itti is improved by intensifying the orientation vectors of elementary visual features to make the visual saliency map suitable for pedestrian detection. In terms of pedestrian attributes, skin color is selected as a semantic feature for pedestrian detection. The regional and Gaussian models are adopted to construct the skin color model. Skin feature-based visual attention guidance is then proposed to complete the top-down process. The bottom-up and top-down visual attentions are linearly combined using the proper weights obtained from experiments to construct the static visual attention model in the spatial domain. The spatial-temporal visual attention model is then constructed via the motion features in the temporal domain. Based on the static visual attention model in the spatial domain, the frame difference method is combined with optical flowing to detect motion vectors. Filtering is applied to process the field of motion vectors. The saliency of motion vectors can be evaluated via motion entropy to make the selected motion feature more suitable for the spatial-temporal visual attention model.
Result
Standard datasets and practical videos are selected for the experiments. The experiments are performed on a MATLAB R2012a platform. The experimental results show that our spatial-temporal visual attention model demonstrates favorable robustness under various scenes, including indoor train station surveillance videos and outdoor scenes with swaying leaves. Our proposed model outperforms the visual attention model of Itti, the graph-based visual saliency model, the phase spectrum of quaternion Fourier transform model, and the motion channel model of Liu in terms of pedestrian detection. The proposed model achieves a 93% accuracy rate on the test video.
Conclusion
This paper proposes a novel pedestrian method based on the visual attention mechanism. A spatial-temporal visual attention model that uses low-level and semantic features is proposed to calculate the saliency map. Based on this model, the pedestrian targets can be detected through focus of attention shifts. The experimental results verify the effectiveness of the proposed attention model for detecting pedestrians.

Secure Full-Duplex Small-Cell Networks in a Spectrum Sharing Environment

In this paper, we propose three relay selection schemes for full-duplex heterogeneous networks in the presence of multiple cognitive radio eavesdroppers. In this setup, the cognitive small-cell nodes (secondary network) can share the spectrum licensed to the macro-cell system (primary network) on the condition that the quality-of-service of the primary network is always satisfied subjected to its outage probability constraint. The messages are delivered from one small-cell base station to the destination with the help of full-duplex small-cell base stations, which act as relay nodes. Based on the availability of the network’s channel state information at the secondary information source, three different selection criteria for full-duplex relays, namely: 1) partial relay selection; 2) optimal relay selection; and 3) minimal self-interference relay selection, are proposed. We derive the exact closed-form and asymptotic expressions of the secrecy outage probability for the three criteria under the attack of non-colluding/colluding eavesdroppers. We demonstrate that the optimal relay selection scheme outperforms the partial relay selection and minimal self-interference relay selection schemes at the expense of acquiring full channel state information knowledge. In addition, increasing the number of the full-duplex small-cell base stations can improve the security performance. At the illegitimate side, deploying colluding eavesdroppers and increasing the number of eavesdroppers put the confidential information at a greater risk. Besides, the transmit power and the desire outage probability of the primary network have great influences on the secrecy outage probability of the secondary network. 

A low overhead error confinement method based on application statistical characteristics

Reliability has emerged as a critical design constraint especially in memories. Designers are going to great lengths to guarantee fault free operation of the underlying silicon by adopting redundancy-based techniques, which essentially try to detect and correct every single error. However, such techniques come at a cost of large area, power and performance overheads which making many researchers to doubt their efficiency especially for error resilient systems where 100% accuracy is not always required. In this paper, we present an alternative method focusing on the confinement of the resulting output error induced by any reliability issues. By focusing on memory faults, rather than correcting every single error the proposed method exploits the statistical characteristics of any target application and replaces any erroneous data with the best available estimate of that data. To realize the proposed method a RISC processor is augmented with custom instructions and special-purpose functional units. We apply the method on the proposed enhanced processor by studying the statistical characteristics of the various algorithms involved in a popular multimedia application. Our experimental results show that in contrast to state-of-the-art fault tolerance approaches, we are able to reduce runtime and area overhead by 71.3% and 83.3% respectively.

The relationship between early and intermediate level spatial vision during typical development and in autism spectrum disorder

Certaines recherches ont investigué le traitement visuel de bas et de plus hauts niveaux chez des personnes neurotypiques et chez des personnes ayant un trouble du spectre de l’autisme (TSA). Cependant, l’interaction développementale entre chacun de ces niveaux du traitement visuel n’est toujours pas bien comprise. La présente thèse a donc deux objectifs principaux. Le premier objectif (Étude 1) est d’évaluer l’interaction développementale entre l’analyse visuelle de bas niveaux et de niveaux intermédiaires à travers différentes périodes développementales (âge scolaire, adolescence et âge adulte). Le second objectif (Étude 2) est d’évaluer la relation fonctionnelle entre le traitement visuel de bas niveaux et de niveaux intermédiaires chez des adolescents et des adultes ayant un TSA. Ces deux objectifs ont été évalué en utilisant les mêmes stimuli et procédures. Plus précisément, la sensibilité de formes circulaires complexes (Formes de Fréquences Radiales ou FFR), définies par de la luminance ou par de la texture, a été mesurée avec une procédure à choix forcés à deux alternatives. Les résultats de la première étude ont illustré que l’information locale des FFR sous-jacents aux processus visuels de niveaux intermédiaires, affecte différemment la sensibilité à travers des périodes développementales distinctes. Plus précisément, lorsque le contour est défini par de la luminance, la performance des enfants est plus faible comparativement à celle des adolescents et des adultes pour les FFR sollicitant la perception globale. Lorsque les FFR sont définies par la texture, la sensibilité des enfants est plus faible comparativement à celle des adolescents et des adultes pour les conditions locales et globales. Par conséquent, le type d’information locale, qui définit les éléments locaux de la forme globale, influence la période à laquelle la sensibilité visuelle atteint un niveau développemental similaire à celle identifiée chez les adultes. Il est possible qu’une faible intégration visuelle entre les mécanismes de bas et de niveaux intermédiaires explique la sensibilité réduite des FFR chez les enfants. Ceci peut être attribué à des connexions descendantes et horizontales immatures ainsi qu’au sous-développement de certaines aires cérébrales du système visuel. Les résultats de la deuxième étude ont démontré que la sensibilité visuelle en autisme est influencée par la manipulation de l’information locale. Plus précisément, en présence de luminance, la sensibilité est seulement affectée pour les conditions sollicitant un traitement local chez les personnes avec un TSA. Cependant, en présence de texture, la sensibilité est réduite pour le traitement visuel global et local. Ces résultats suggèrent que la perception de formes en autisme est reliée à l’efficacité à laquelle les éléments locaux (luminance versus texture) sont traités. Les connexions latérales et ascendantes / descendantes des aires visuelles primaires sont possiblement tributaires d’un déséquilibre entre les signaux excitateurs et inhibiteurs, influençant ainsi l’efficacité à laquelle l’information visuelle de luminance et de texture est traitée en autisme. Ces résultats supportent l’hypothèse selon laquelle les altérations de la perception visuelle de bas niveaux (local) sont à l’origine des atypies de plus hauts niveaux chez les personnes avec un TSA.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

From global advocacy to local resistance. Benin's experience of competency-based school curriculum

In the vein of the "Education for All" campaign to promote access to education, a wave of curriculum revision along the competency-based approach has swept francophone countries in sub-Sahara Africa, thus Benin. The current study documents local actors' various interactions with the curricular reform in the course of its implementation. Secondary data supplemented with qualitative research techniques such as semi-structured interviews with teachers, and focus group discussions with parents enable to relate the patterns of change, the challenges and resistance to change. The actors spectrum generated illustrates advocacy on one hand and resistance on the other. Advocacy of local actors reflects the global optimistic discourse on education and resistance is favoured by disappointing policy outcomes as well as contextual constraints. (DIPF/Orig.)

Identification of protein targets of nevirapine reactive metabolites using click chemistry and mass spectrometry-based differential proteomics

Abstract : Adverse drug reactions (ADRs) are undesirable effects caused after administration of a single dose or prolonged administration of drug or result from the combination of two or more drugs. Idiosyncratic drug reaction (IDR) is an adverse reaction that does not occur in most patients treated with a drug and does not involve the therapeutic effect of the drug. IDRs are unpredictable and often life-threatening. Idiosyncratic reaction is dependent on drug chemical characteristics or individual immunological response. IDRs are a major problem for drug development because they are usually not detected during clinical trials. In this study we focused on IDRs of Nevirapine (NVP), which is a non-nucleoside reverse transcriptase inhibitor used for the treatment of Human Immunodeficiency Virus (HIV) infections. The use of NVP is limited by a relatively high incidence of skin rash. NVP also causes a rash in female Brown Norway (BN) rats, which we use as animal model for this study. Our hypothesis is that idiosyncratic skin reactions associated with NVP treatment are due to post-translational modifications of proteins (e.g., glutathionylation) detectable by MS. The main objective of this study was to identify the proteins that are targeted by a reactive metabolite of Nevirapine in the skin. The specific objectives derived from the general objective were as follow: 1) To implement the click chemistry approach to detect proteins modified by a reactive NVP-Alkyne (NVP-ALK) metabolite. The purpose of using NVP-ALK was to couple it with Biotin using cycloaddition Click Chemistry reaction. 2) To detect protein modification using Western blotting and Mass Spectrometry techniques, which is important to understand the mechanism of NVP induced toxicity. 3) To identify the proteins using MASCOT search engine for protein identification, by comparing obtained spectrum from Mass Spectrometry with theoretical spectrum to find a matching peptide sequence. 4) To test if the drug or drug metabolites can cause harmful effects, as the induction of oxidative stress in cells (via protein glutathionylation). Oxidative stress causes cell damage that mediates signals, which likely induces the immune response. The results showed that Nevirapine is metabolized to a reactive metabolite, which causes protein modification. The extracted protein from the treated BN rats matched 10% of keratin, which implies that keratin was the protein targeted by the NVP-ALK.

Feature-based camera pose estimation

The estimating of the relative orientation and position of a camera is one of the integral topics in the field of computer vision. The accuracy of a certain Finnish technology company’s traffic sign inventory and localization process can be improved by utilizing the aforementioned concept. The company’s localization process uses video data produced by a vehicle installed camera. The accuracy of estimated traffic sign locations depends on the relative orientation between the camera and the vehicle. This thesis proposes a computer vision based software solution which can estimate a camera’s orientation relative to the movement direction of the vehicle by utilizing video data. The task was solved by using feature-based methods and open source software. When using simulated data sets, the camera orientation estimates had an absolute error of 0.31 degrees on average. The software solution can be integrated to be a part of the traffic sign localization pipeline of the company in question.

Second-order cyclostationarity-based detection and classification of LTE SC-FDMA signals for cognitive radio

Cognitive radio (CR) was developed for utilizing the spectrum bands efficiently. Spectrum sensing and awareness represent main tasks of a CR, providing the possibility of exploiting the unused bands. In this thesis, we investigate the detection and classification of Long Term Evolution (LTE) single carrier-frequency division multiple access (SC-FDMA) signals, which are used in uplink LTE, with applications to cognitive radio. We explore the second-order cyclostationarity of the LTE SC-FDMA signals, and apply results obtained for the cyclic autocorrelation function to signal detection and classification (in other words, to spectrum sensing and awareness). The proposed detection and classification algorithms provide a very good performance under various channel conditions, with a short observation time and at low signal-to-noise ratios, with reduced complexity. The validity of the proposed algorithms is verified using signals generated and acquired by laboratory instrumentation, and the experimental results show a good match with computer simulation results.