Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced Lead Selenide Quantum Dot Solar Cells Utilizing the Light and Carrier Collection Management Architecture

Quantum dot (QD) thin-film solar cells are an exciting new area of solar cell research, as QDs offer the ability to “fine tune” their band gap to suit a particular application. Previous work with QD solar cells has focused on simple planar device structures, with overall efficiencies remaining low compared to other cell types. This work, for the first time, implements QDs as the active absorber material in a nano-structured solar cell. Using lead selenide (PbSe) QDs in the Light and Carrier Collection Management (LCCM) architecture, this thesis studies the performance improvements in LCCM cells over planar cells via computer modeling and numerical analysis. The LCCM uses a periodic array of nano-elements to produce both enhanced light trapping/absorption and photocarrier collection. Superior light capture and improved photogenerated carrier collection are shown to be attainable with ultra-thin QD layers. PbSe QD LCCM devices give, on average, a 40% improvement in short-circuit current density (JSC) and a maximum improvement of 57%, compared with corresponding planar devices. Furthermore, the LCCM architecture was able to increase PbSe QD absorber mass utilization by up to 18%. LCCM unit cell dimensions and various materials systems were studied to produce an optimal design for maximum cell performance. The results of this research will help provide insight into more complex designs for QD solar cells that can attain significantly higher efficiencies.
Activation of Mitogen-activated Protein Kinase by the A2A-adenosine Receptor via a rap1-dependent and via a p21 ras -dependent Pathway*

The A2A-adenosine receptor, a prototypical Gs-coupled receptor, activates mitogen-activated protein (MAP) kinase in a manner independent of cAMP in primary human endothelial cells. In order to delineate signaling pathways that link the receptor to the regulation of MAP kinase, the human A2A receptor was heterologously expressed in Chinese hamster ovary (CHO) and HEK293 cells. In both cell lines, A2A agonist-mediated cAMP accumulation was accompanied by activation of the small G protein rap1. However, rap1 mediates A2A receptor-dependent activation of MAP kinase only in CHO cells, the signaling cascade being composed of Gs, adenylyl cyclase, rap1, and the p68 isoform of B-raf. This isoform was absent in HEK293 cells. Contrary to CHO cells, in HEK293 cells activation of MAP kinase by A2A agonists was not mimicked by 8-bromo-cAMP, was independent of Gαs, and was associated with activation of p21 ras . Accordingly, overexpression of the inactive S17N mutant of p21 ras and of a dominant negative version of mSos (the exchange factor of p21 ras ) blocked MAP kinase stimulation by the A2A receptor in HEK 293 but not in CHO cells. In spite of the close homology between p21 ras and rap1, the S17N mutant of rap1 was not dominant negative because (i) overexpression of rap1(S17N) failed to inhibit A2A receptor-dependent MAP kinase activation, (ii) rap1(S17N) was recovered in the active form with a GST fusion protein comprising the rap1-binding domain of ralGDS after A2A receptor activation, and (iii) A2A agonists promoted the association of rap1(S17N) with the 68-kDa isoform of B-raf in CHO cells. We conclude that the A2A receptor has the capacity two activate MAP kinase via at least two signaling pathways, which depend on two distinct small G proteins, namely p21 ras and rap1. Our observations also show that the S17N version of rap1 cannot be assumed a priori to act as a dominant negative interfering mutant.
Role of Toll-Like Receptors 2 and 4 in Pulmonary Inflammation and Injury Induced by Pneumolysin in Mice

Background Pneumolysin (PLN) is an intracellular toxin of Streptococcus pneumoniae that has been implicated as a major virulence factor in infections caused by this pathogen. Conserved bacterial motifs are recognized by the immune system by pattern recognition receptors among which the family of Toll-like receptors (TLRs) prominently features. The primary objective of the present study was to determine the role of TLR2 and TLR4 in lung inflammation induced by intrapulmonary delivery of PLN. Methodology/Results First, we confirmed that purified PLN activates cells via TLR4 (not via TLR2) in vitro, using human embryonic kidney cells transfected with either TLR2 or TLR4. Intranasal administration of PLN induced an inflammatory response in the pulmonary compartment of mice in vivo, as reflected by influx of neutrophils, release of proinflammatory cytokines and chemokines, and a rise in total protein concentrations in bronchoalveolar lavage fluid. These PLN-induced responses were dependent in part, not only on TLR4, but also on TLR2, as indicated by studies using TLR deficient mice. Conclusion These data suggest that although purified PLN is recognized by TLR4 in vitro, PLN elicits lung inflammation in vivo by mechanisms that may involve multiple TLRs.
Design and Testing of a Quad Shrouded Rotor Micro Air Vehicle in Hover

Rotor hover performance can be enhanced by enclosing it in a shroud. This paper describes the design and testing of a quad rotor vehicle with a shroud structure incorporated, and the resulting improvements in aerodynamic efficiency over a conventional micro quad rotor are demonstrated. Parametric studies were conducted to study the effect of number of blades and root collective on shrouded rotor performance. Comparison of a 2.6” shrouded rotor with an optimized unshrouded rotor showed a 30% improvement in power loading at a power input of 2W. To minimize shroud weight, the structure consisted of a machined foam diffuser with carbon fiber inlets attached. A fully integrated proof of concept micro air vehicle (MAV) was designed with a gross weight of about 100 grams and a shroud structure weight of 12 grams. The vehicle had maximum dimensions of 6” 6”. Successful hover flight testing of the vehicle was achieved using an onboard attitude feedback controller. Comparison with data from another study (9.5” shrouded rotor) revealed that the hover performance of the shrouded rotor scales satisfactorily with size. The shrouded rotor concept appears feasible in improving the performance of a conventional micro quad rotor.
RECENT FINDINGS AND NEW INITIATIVES FOR EPIDEMIOLOGIC RESEARCH ON BENZENE

Recent epidemiologic research on benzene consists of (1) updated analyses of workers exposed to benzene at two facilities in Ohio, who were involved in the manufacture of Pliofilm; (2) analyses of workers in the petroleum industry in North America, Australia, and Europe, who were exposed to benzene and other petroleum products containing benzene; and (3) workers from a broad spectrum of industries in China, who were exposed to benzene and a wide variety of other chemicals. In this report, recent findings from these studies are summarized and their limitations discussed. Issues to be considered in future research are suggested.
How and When to Use an Injury Prevention Intervention in Soccer

Soccer is a high intensity intermittent contact sport exposing elite level players to contin‐ ual physical, technical, tactical, psychological, and physiological demands (Owen et al, 2011; Dellal et al, 2011). Due to the huge financial rewards of being successful at the elite level of the sport, the demands placed upon the players are ever growing because of increased fixture schedules that generally include less recovery periods between train‐ ing and competitive match play, disposing players to a greater risk of injury (Dellal at al, 2013; Dupont et al, 2010; Rey et al, 2010; Morgan and Oberlander 2001; Junge and Dvorak 2004). The number of competitive matches played by elite European soccer play‐ ers (Table 1) during one season can be >80, with 1.6 to 2 matches per week throughout its entirety (excluding friendly games) (Figure 1). It should be noted that, a player com‐ peting at the higher echelons of world soccer such as Lionel Messi has accumulated be‐ tween 64 to 69 official competitive games throughout seasons 2011-2012, 2010-2011, and 2009-2010 as shown in Table 2. As reported in this context, modern day soccer involves a continued, intensive cycle and predisposes players to greater injury risks due to accu‐ mulative fatigue or overload. Previous research has already found a correlation between low training and match availability due to injury, with decreased team success (Arnason et al, 2004). This is of particular importance for teams unable to replace players due to limited funds or resources, and subsequently highlights the need for all clubs irrespec‐ tive of budgets, resources and funding potential to minimize injury risk of players in or‐ der to be more successful. After all, there seems to be no point in pushing players constantly to be physically, technically and tactically better if they are consistently un‐ available to play.
Online heuristics for monetary-based courier relaying in RFID-Sensor Networks

In integrated RFID and Wireless Sensor Networks (RSNs), the abundance of wirelessly enabled mobile devices facilitates forwarding data packets. This presents a beneficial alternative to offload transmission from relay nodes to access points. However, there is no incentive for such mobile devices to carry the relaying task. Hence, we introduce heuristics for Monetary-based Courier Relaying (MCR) that incorporates price negotiation for relaying from source nodes to access points via mobile couriers in RSN architectures. Our heuristics employ a threshold price for each packet prior to transmission. Whether to forward the packet to a courier or to directly transmit it to access points depends on a criticalness function, in addition to the courier's charge with respect to the packet's threshold price. We compare our MCR model with other dominant mobile Ad hoc delivery schemes; eliciting its efficiency in terms of energy, cost and delivery rate.
Perception-based energy functions in seam-cutting

Image stitching is challenging in consumer-level photography, due to alignment difficulties in unconstrained shooting environment. Recent studies show that seam-cutting approaches can effectively relieve artifacts generated by local misalignment. Normally, seam-cutting is described in terms of energy minimization, however, few of existing methods consider human perception in their energy functions, which sometimes causes that a seam with minimum energy is not most invisible in the overlapping region. In this paper, we propose a novel perception-based energy function in the seam-cutting framework, which considers the nonlinearity and the nonuniformity of human perception in energy minimization. Our perception-based approach adopts a sigmoid metric to characterize the perception of color discrimination, and a saliency weight to simulate that human eyes incline to pay more attention to salient objects. In addition, our seam-cutting composition can be easily implemented into other stitching pipelines. Experiments show that our method outperforms the seam-cutting method of the normal energy function, and a user study demonstrates that our composed results are more consistent with human perception.
Detection of a Novel Mechanism of Acousto-Optic Modulation of Incoherent Light

A novel form of acoustic modulation of light from an incoherent source has been detected in water as well as in turbid media. We demonstrate that patterns of modulated light intensity appear to propagate as the optical shadow of the density variations caused by ultrasound within an illuminated ultrasonic focal zone. This pattern differs from previous reports of acousto-optical interactions that produce diffraction effects that rely on phase shifts and changes in light directions caused by the acoustic modulation. Moreover, previous studies of acousto-optic interactions have mainly reported the effects of sound on coherent light sources via photon tagging, and/or the production of diffraction phenomena from phase effects that give rise to discrete sidebands. We aimed to assess whether the effects of ultrasound modulation of the intensity of light from an incoherent light source could be detected directly, and how the acoustically modulated (AOM) light signal depended on experimental parameters. Our observations suggest that ultrasound at moderate intensities can induce sufficiently large density variations within a uniform medium to cause measurable modulation of the intensity of an incoherent light source by absorption. Light passing through a region of high intensity ultrasound then produces a pattern that is the projection of the density variations within the region of their interaction. The patterns exhibit distinct maxima and minima that are observed at locations much different from those predicted by Raman-Nath, Bragg, or other diffraction theory. The observed patterns scaled appropriately with the geometrical magnification and sound wavelength. We conclude that these observed patterns are simple projections of the ultrasound induced density changes which cause spatial and temporal variations of the optical absorption within the illuminated sound field. These effects potentially provide a novel method for visualizing sound fields and may assist the interpretation of other hybrid imaging methods.
Fabrication and Characterization of Electrospun Semiconductor Nanoparticle—Polyelectrolyte Ultra-Fine Fiber Composites for Sensing Applications

Fluorescent composite fibrous assembles of nanoparticle-polyelectrolyte fibers are useful multifunctional materials, utilized in filtration, sensing and tissue engineering applications, with the added benefits of improved mechanical, electrical or structural characteristics over the individual components. Composite fibrous mats were prepared by electrospinning aqueous solutions of 6 wt% poly(acrylic acid) (PAA) loaded with 0.15 and 0.20% v/v, carboxyl functionalized CdSe/ZnS nanoparticles (SNPs). The resulting fluorescent composite fibrous mats exhibits recoverable quenching when exposed to high humidity. The sensor response is sensitive to water concentration and is attributed to the change in the local charges around the SNPs due to deprotonation of the carboxylic acids on the SNPs and the surrounding polymer matrix.
Title Approximation for minimum triangulation of convex polyhedra

The minimum triangulation of a convex polyhedron is a triangulation that contains the minimum number of tetrahedra over all its possible triangulations. Since finding the minimum triangulation of convex polyhedra was recently shown to be NP-hard, it becomes significant to find algorithms that give good approximation. In this paper, we give a new triangulation algorithm with an im1 proved approximation ratio 2 f l ( ~ ) . We also show that this is best possible for algorithms that only consider the combinatorial structure of the polyhedra. 1 I n t r o d u c t i o n Triangulation is the subdivision of ddimensional polyhedron into simplices. In this paper we are concerned with triangulations of 3-dimensional convex polyhedra with vertices in general position. Triangulation has important applications in computer-aided design, computer graphics, finite element analysis, etc. Triangulation in 3-D has many interesting properties. Convex polyhedra can always be triangulated, but non-convex polyhedra may not: the SchSnhardt polyhedron [8] is such an example. It is even NP-complete to determine whether a given non-convex polyhedron can be tr iangulated [7]. Different triangulations of convex polyhedra may result in different numbers of tetrahedra, and finding the minimum triangulation was recently *This work is supported by I~GC grant HKU 7019/00E. tThis work is supported by NSEI~C grant OPG0041629. shown to be NP-hard [2], [3]. Thus designing good approximation algorithms for this problem becomes significant. We modified a well-known tr iangulat ion heuristic to obtain a bet ter bound of 2 ~ ( ~ ) on the approximat ion ratio in Section 3. On the other hand, it is shown in [1] that the min imum triangulation of polyhedra is not an invariant of the face lattice. In Section 4 we extend this to show that any algori thm that only considers the combinatorial s t ructure of polyhedra cannot give an approximation ratio bet ter than 2 O( 1 ) Thus our algori thm is best possi-
Using Machine Learning to Design and Interpret Gene-Expression Microarrays

Gene-expression microarrays, commonly called gene chips, make it possible to simultaneously measure the rate at which a cell or tissue is expressing--translating into a protein--each of its thousands of genes. One can use these comprehensive snapshots of biological activity to infer regulatory pathways in cells; identify novel targets for drug design; and improve the diagnosis, prognosis, and treatment planning for those suffering from disease. However, the amount of data this new technology produces is more than one can manually analyze. Hence, the need for automated analysis of microarray data offers an opportunity for machine learning to have a significant impact on biology and medicine. This article describes microarray technology, the data it produces, and the types of machine learning tasks that naturally arise with these data. It also reviews some of the recent prominent applications of machine learning to gene-chip data, points to related tasks where machine learn-Lug might have a further impact on biology and medicine, and describes additional types of interesting data that recent advances in biotechnology allow biomedical researchers to collect.
pRNA

Promoter-associated RNAs (pRNAs) are a family of ~90–100 nt-long divergent RNAs overlapping the promoter of the rRNA (rDNA) operon. pRNA transcripts interact with TIP5, a component of the chromatin remodeling complex NoRC, which recruits enzymes for heterochromatin formation and mediates silencing of rRNA genes. Here we present a comprehensive analysis of pRNA homologs, including different versions per species, as result of in silico studies in available metazoan genome assemblies. Comparative sequence analysis and secondary structure prediction ended up in two possible secondary structures, which let us assume a possible dual function of pRNAs for regulation of rRNA operons. Furthermore, we validated parts of our computational predictions experimentally by RT-PCR and sequencing. A representative seed alignment of the pRNA family, annotated with possible secondary structures was released to the Rfam database.
Rock types detection and classification through the use of orthogonal subspace projection approach

In most cases especially rock types detection, the pixels in remote sensing image are mixed, and so common methods based on pure pixels to detect target are not appropriate here. Orthogonal Subspace Projection has two important properties: one is to eliminate or suppress the undesired signals by projecting each pixel onto the space orthogonal to interfering signals, another is to detect the presence of desired signal by projecting the residuals onto the space of interesting signal and maximizing the signal-to-noise ratio (SNR). It can be used simultaneously on mixed pixels and the pure ones. Using Thematic Mapper (TM) data to classify different rock types shows OSP to perform well.
Acquisition of visual features through probabilistic spike-timing-dependent plasticity

This paper explores modifications to a feedforward five-layer spiking convolutional network (SCN) of the ventral visual stream [Masquelier, T. , Thorpe, S. , Unsupervised learning of visual features through spike timing dependent plasticity. PLoS Computational Biology, 3(2), 247-257]. The original model showed that a spike-timing-dependent plasticity (STDP) learning algorithm embedded in an appropriately selected SCN could perform unsupervised feature discovery. The discovered features where interpretable and could effectively be used to perform rapid binary decisions in a classifier. In order to study the robustness of the previous results, the present research examines the effects of modifying some of the components of the original model. For improved biological realism, we replace the original non-leaky integrate-and-fire neurons with Izhikevich-like neurons. We also replace the original STDP rule with a novel rule that has a probabilistic interpretation. The probabilistic STDP slightly but significantly improves the performance for both types of model neurons. Use of the Izhikevich-like neuron was not found to improve performance although performance was still comparable to the IF neuron. This shows that the model is robust enough to handle more biologically realistic neurons. We also conclude that the underlying reasons for stable performance in the model are preserved despite the overt changes to the explicit components of the model.
LMI Approach to Stability Analysis of Discrete-Time BAM Neural Networks with Time-Varying Delays 1

In this paper, a discrete-time bidirectional associative memory (BAM) neural network with time-varying delays is considered. The description of the activation functions is more general than the recently commonly used Lipschitz conditions. By using appropriate Lyapunov-Krasovskii functional and linear matrix inequality (LMI) technique, a delay-dependent sufficient condition is obtained to guarantee the global exponential stability of the addressed neural network. The condition is a LMI, hence the stability of the neural network can be checked readily by resorting to the Matlab LMI toolbox. In addition, the proposed stability criterion does not require the monotonicity and differentiability of the activation functions, and a impose condition on the time-varying delays in recent publication is removed. A simulation example is given to show the effectiveness and less conservatism of the obtained condition. Mathematics Subject Classification: 34D20; 37C75; 93D05
A Demonstration of Lusail: Querying Linked Data at Scale

There has been a proliferation of datasets available as interlinked RDF data accessible through SPARQL endpoints. This has led to the emergence of various applications in life science, distributed social networks, and Internet of Things that need to integrate data from multiple endpoints. We will demonstrate Lusail; a system that supports the need of emerging applications to access tens to hundreds of geo-distributed datasets. Lusail is a geo-distributed graph engine for querying linked RDF data. Lusail delivers out- standing performance using (i) a novel locality-aware query decomposition technique that minimizes the intermediate data to be accessed by the subqueries, and (ii) selectivity-awareness and parallel query execution to reduce network latency and to increase parallelism. During the demo, the audience will be able to query actually deployed RDF end- points as well as large synthetic and real benchmarks that we have deployed in the public cloud. The demo will also show that Lusail outperforms state-of-the-art systems by orders of magnitude in terms of scalability and response time.