Miracle-dz/UniFAR-FTUs huggingface dataset:
Positive Regulatory Role of IL-12 in Macrophages and Modulation by IFN-γ1

Similar to myeloid dendritic cells, murine macrophages and macrophage cell lines were found to express a surface receptor for IL-12. As a result, peritoneal macrophages could be primed by IL-12 to present an otherwise poorly immunogenic tumor peptide in vivo. Using binding analysis and RNase protection assay, we detected a single class of high affinity IL-12 binding sites (Kd of ∼35 pM) whose number per cell was increased by IFN-γ via up-regulation of receptor subunit expression. Autocrine production of IL-12 was suggested to be a major effect of IL-12 on macrophages when the cytokine was tested alone or after priming with IFN-γ in vitro. In vivo, combined treatment of macrophages with IFN-γ and IL-12 resulted in synergistic effects on tumor peptide presentation. Therefore, our findings suggest a general and critical role of IL-12 in potentiating the accessory function of myeloid APC.
Design tool solutions for mixed-signal/RF circuit design in CMOS nanometer technologies

The scaling of CMOS technology into the nanometer era enables the fabrication of highly integrated systems, which increasingly contain analog and/or RF parts. However, scaling into the nanometer era also brings problems of leakage power, increasing variability and degradation, reducing supply voltages and worsening signal integrity conditions, all this in combination with tightening time-to-market constraints. Design methodologies and tools need to be developed to address these problems. This invited paper describes progress in modeling techniques for design and verification of complex integrated systems, in circuit and yield optimization tools for analog/RF circuits, as well as in signal integrity analysis methods such as EMC/EMI analysis.
Goal Recognition Design with Non-Observable Actions

Goal recognition design involves the offline analysis of goal recognition models by formulating measures that assess the ability to perform goal recognition within a model and finding efficient ways to compute and optimize them. In this work we relax the full observability assumption of earlier work by offering a new generalized model for goal recognition design with non-observable actions. A model with partial observability is relevant to goal recognition applications such as assisted cognition and security, which suffer from reduced observability due to sensor malfunction or lack of sufficient budget. In particular we define a worst case distinctiveness (wcd) measure that represents the maximal number of steps an agent can take in a system before the observed portion of his trajectory reveals his objective. We present a method for calculating wcd based on a novel compilation to classical planning and propose a method to improve the design using sensor placement. Our empirical evaluation shows that the proposed solutions effectively compute and improve wcd.
Intuitive annotation of user-viewed objects for wearable AR systems

By realizing augmented reality on wearable computers, it is possible to overlay annotations on the real world based on the user's current position and orientation. However, it is difficult for the user to understand links between annotations and real objects intuitively when the scene is complicated or many annotations are overlaid at the same time. This paper describes a view management method which emphasizes user-viewed real objects and their annotations using 3D models of the real scene. The proposed method highlights the objects viewed by the user. In addition, when the viewed object is occluded by other real objects, the object is complemented by using a synthetic image, which is made from 3D models, on the overlaid image.
Activation of Neurotensin Receptor 1 Facilitates Neuronal Excitability and Spatial Learning and Memory in the Entorhinal Cortex: Beneficial Actions in an Alzheimer's Disease Model

Neurotensin (NT) is a tridecapeptide distributed in the CNS, including the entorhinal cortex (EC), a structure that is crucial for learning and memory and undergoes the earliest pathological alterations in Alzheimer's disease (AD). Whereas NT has been implicated in modulating cognition, the cellular and molecular mechanisms by which NT modifies cognitive processes and the potential therapeutic roles of NT in AD have not been determined. Here we examined the effects of NT on neuronal excitability and spatial learning in the EC, which expresses high density of NT receptors. Brief application of NT induced persistent increases in action potential firing frequency, which could last for at least 1 h. NT-induced facilitation of neuronal excitability was mediated by downregulation of TREK-2 K+ channels and required the functions of NTS1, phospholipase C, and protein kinase C. Microinjection of NT or NTS1 agonist, PD149163, into the EC increased spatial learning as assessed by the Barnes Maze Test. Activation of NTS1 receptors also induced persistent increases in action potential firing frequency and significantly improved the memory status in APP/PS1 mice, an animal model of AD. Our study identifies a cellular substrate underlying learning and memory and suggests that NTS1 agonists may exert beneficial actions in an animal model of AD.
3D crack skeleton extraction from mobile LiDAR point clouds

This paper presents a novel algorithm for extracting 3D crack skeletons from 3D point clouds acquired by a mobile Light Detection and Ranging (LiDAR) system. This algorithm uses intensity information of cloud clouds to identify pavement cracks that usually exhibit lower intensities compared to their surroundings. First, crack candidates are extracted by applying the Otsu thresholding algorithm. Then, a spatial density filter is used to remove outliers. Next, crack points are grouped into crack-lines using a Euclidean distance clustering method. Finally, crack skeletons are extracted based on an L1-medial skeleton extraction method. The proposed algorithm has been tested on a set of mobile LiDAR point clouds acquired by a state-of-the-art RIEGL VMX-450 mobile LiDAR system. The results demonstrate the efficiency and reliability of the proposed algorithm in extracting 3D crack skeletons.
A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases

Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent experimental validations as found post-facto in the literature.
Combining flow cytometry and gfp reporter gene for quantitative evaluation of Pectpbacterium carotovorum ssp. carotovorum in Ornithogalum dubium plantlets

Aims: Ornithogalum dubium is a natural host of the soft rot pathogen Pectobacterium carotovorum ssp. carotovorum (Pcc). The present study was aimed to develop a quantification system for Pcc expressing a gfp reporter gene, using fluorescent activated cell sorter (FACS) in planta.
A new solid-state HVDC circuit breaker topology for offshore wind farms

This paper presents a new topology for solid-state HVDC circuit breakers which does not require MOV for fault energy absorption. Due to its simple yet robust design, it offers a reliable and cost effective solution for isolating faults in HVDC lines connecting remote generating stations to the grid. Since the proposed design does not contain a mechanical breaker or a metal-oxide varistor (MOV), problems resulting from wear and tear of moving parts, arc faults, and degradation or catastrophic failure of surge arrestors are entirely eliminated. This design has inherently a very fast response and is particularly suitable for voltage source converters that are vulnerable against dc faults. To verify the performance and dependability of the proposed circuit breaker, a computer simulation has been developed to handle faults occurring at a 300 kV submarine transmission line that connects a typical 250 MW offshore wind farm to the grid.
Positive OCA Criteria: Microfundations for the Rose Effect

Since Rose (2000), many scholars have found empirical evidence linking trade to exchange rate volatility and currency unions. Our paper takes a first step toward providing theoretical underpinnings for this "Rose effect". In our Melitz-like trade model, reduced volatility boosts trade by inducing existing exporters to export more and by inducing more firms to begin exporting. Specifically, volatility is a greater hindrance to export for small firms, so reduced volatility especially promotes small firms' exports. Because most firms are small, the extra exports induced by a marginal reduction in volatility may increase as the level of volatility falls - a result that can account for the convexity of the trade-volatility link implied by the Rose effect. We derive and test three new empirical hypothesis generated by our model. We find some support for two of them using data on Eurozone aggregate bilateral trade, but have insufficient data to test the third in a convincing manner.
IgG2a-producing variants of an IgG2b-producing mouse myeloma cell line

12 variant cell lines producing an IgG2a (kappa) immunoglobulin derived via different routes from the IgG2b (kappa) synthesizing MPC 11 were studied. These variants all have the parental MPC 11 idiotype as shown by a radioimmunoassay. A comparison of the variants by charge, peptide maps, and assembly patterns has shown that most of them differ from one another, and some can be grouped. One group consists of three primary variants generated with two mutagenic agents: these three have almost indistinguishable peptide maps. Two other primary variants which arose in a similar fashion differ markedly from each other and from this group. A second group is comprised of the four secondary variants which arose from two short heavy chain producing primary variants. Other secondary variants and the one spontaneously arising variant cannot be grouped. Possible genetic mechanisms such as translocation, expression of previously silent genes and recombination are discussed.
Process simulations for 3D turning using uniform and variable microgeometry PCBN tools

In this paper, uniform and variable edge microgeometry design inserts are utilised and tested for 3D turning process. In 3D tool engagement with workpiece, thickness of the chip varies from a maximum equal to the feed rate (at primary cutting edge) to a minimum on the tool's corner radius (at trailing cutting edge). The ideal tool edge preparation should posses a variable configuration which has larger edge radius at the primary cutting edge than at the trailing cutting edge. Here the key parameter is the ratio of uncut chip thickness to edge radius. If a proper ratio is chosen for given cutting conditions, a variable cutting edge along the corner radius can be designed or 'engineered'. In this study, Finite Element Modelling (FEM)-based 3D process simulations are utilised to predict forces and temperatures on various uniform and variable edge microgeometry tools. Predicted forces are compared with experiments. The temperature distributions on the tool demonstrate the advantages of variable edge microgeometry design.
Comparison of contrast sensitivity in eyes with toric and aspheric intraocular lenses

INTRODUCTION: Study aimed to compare Visual Acuity, ocular Spherical Aberration (SA) and Contrast Sensitivity (CS) in eyes implanted with the AcrySof toric IOL and AcrySof Natural IQ. METHODS: Fifty-eight eyes of 46 patients participated in this prospective randomized study. After phacoemulsification the eyes received the AcrySof toric or AcrySof IQ IOLs depending on their preoperative corneal astigmatism. Three month after surgery, all patients underwent complete ophthalmological examination including corneal topography, best corrected visual acuity, wavefront analysis for 6 mm pupil diameter and CS measurements with the CSV-1000HGT test under photopic (85 cd/m2) and mesopic conditions (5 cd/m2). RESULTS: BCVA in toric group was 0.054±0.043 logMAR and 0.030±0.037 logMAR in aspheric group (all patients achieved a BCVA of 20/25 or better). The mean postoperative SA was higher in the AcrySof toric group than the AcrySof IQ group (0.540±0.887 vs. 0.216±0.047 µm) and this difference was statistically significant (p<0.001). CS results showed no statistically significant differences between the values post-implantation at any lighting condition and spatial frequency (p>0.01). The AcrySof toric lens provided excellent rotational stability in the capsular bag with an average lens rotation of less than 3.3±2.5 degrees. CONCLUSIONS: The AcrySof toric IOL and aspheric AcrySof IQ yield similar and good visual outcomes. However, the AcrySof IQ IOL reduced significantly the SA for large pupils in relation to toric IOL. Surgeons should consider that patients may benefit from aspheric designs. Future studies, should consider direct comparison between spherical and aspheric toric IOLs to analyze properly the benefit in visual performance
The Effect of TDMA Frame Size and the Hidden Node Problem on the Performance of a Neighbor-Aware VANET MAC

Despite various proposed Medium Access Control (MAC) approaches, efficient medium access in VANET remains a significant challenge for the broadcast of safety messages. A key contributing factor, especially with the high node mobility apparent in VANET, is the hidden terminal problem. Since the hidden terminal problem is fundamentally a problem of lack of awareness, increased neighbor awareness at the MAC layer has been suggested as a possible solution. An increased awareness of neighboring nodes' slot allocation requires an increased number of TDMA slots. In this paper we evaluate the impact of TDMA frame size in a neighbor-aware MAC. An analytical model is developed to support the simulation results, based on a geographical probability of RF interference and the slot allocation scheme used in the TDMA MAC. The results show that the packet delivery increases with increased TDMA frame size to support neighbor awareness, as the probability for packet collisions decrease. Packet delivery decreases with increases in neighbor count, since more nodes cause packet collisions. The receiver throughput initially increases as TDMA frame size is increased, since more transmission opportunities occur, and packet delivery increases. However, when the TDMA increases beyond an optimal, throughput is adversely affected by underutilization. Despite the decrease in packet delivery ratio, receiver throughput is higher for more nodes.
Walking robot modelling aspects

The paper describes a walking robot leg modelling process. A six-legged walking robot — the so-called hexapod is concerned. Each leg consists of three links driven by Hitec H S475HB servo motors. The proposed model is used for testing le g kinematics and dynamics of the robot gait. One can examine a number of walking algorithms. The model includes: the identified description of the servo motors, a full state obse rver (position and velocity), forward kinematics of the position and the velocity, inverse kinematics of the position and the leg mov ement visualisation. The model structure is explained and depict ed. The simulation results are shown in a graphical form. The exampl es of model applications are applied and described. The advant ages and disadvantages of the model are listed. Eventual experim ents and applications are announced.
Ieee Transactions on Communications, Accepted for Publication on the Performance of Cognitive Underlay Multihop Networks with Imperfect Channel State Information

—This paper proposes and analyzes cognitive multi-hop decode-and-forward networks in the presence of interference due to channel estimation errors. To reduce interference on the primary network, a simple yet effective back-off control power method is applied for secondary multihop networks. For a given threshold of interference probability at the primary network, we derive the maximum back-off control power coefficient, which provides the best performance for secondary multihop networks. Moreover, it is shown that the number of hops for secondary network is upper-bounded under the fixed settings of the primary network. For secondary multihop networks, new exact and asymptotic expressions for outage probability (OP), bit error rate (BER) and ergodic capacity over Rayleigh fading channels are derived. Based on the asymptotic OP and BEP, a pivotal conclusion is reached that the secondary multihop network offers the same diversity order as compared with the network without back off. Finally, we verify the performance analysis through various numerical examples which confirm the correctness of our analysis for many channel and system settings and provide new insight into the design and optimization of cognitive multihop networks.
A Simple Approach to Engineer SERS Substrates and Plasmonic Thin Film

Solid supported 2D assembly of silver nanocubes was fabricated by Langmuir-Blodgett technique and employed to investigate its surface enhanced Raman scattering (SERS) and surface enhance fluorescence (SEF) activities by detecting Rh6G in solution of varied concentrations, that is, 10−12 M, 10−9 M, 10−6 M, and 10−3 M. SERS was detected from a nanomolar concentration of Rh6G whereas SEF was detected from a picomolar concentration. Further, the substrate was subjected to thermal annealing to fabricate plasmonic thin film. The formation of thin film was followed by monitoring its surface plasmon resonance spectra and atomic force microscopic images. It was observed that the characteristic spectral peaks of silver nanocubes merged into a broad spectral band as the annealing time was increased and the intensity of the band decreased with the formation of thin film. The obtained result implies that thermal annealing could be a simple approach to create nanoscale gaps in SERS substrate and to engineer continuous thin film from the assembly of discrete nanoparticles.
HIV-Infected Adolescent Mothers and Their Infants: Low Coverage of HIV Services and High Risk of HIV Transmission in KwaZulu-Natal, South Africa

Objectives Rates of pregnancy and HIV infection are high among South African adolescents, yet little is known about rates of mother-to-child transmission of HIV (MTCT) in this group. We report a comparison of the characteristics of adolescent mothers and adult mothers, including HIV prevalence and MTCT rates. Methods We examined patterns of health service utilization during the antenatal and early postnatal period, HIV prevalence and MTCT amongst adolescent (<20-years-old) and adult (20 to 39-years-old) mothers with infants aged ≤16 weeks attending immunization clinics in six districts of KwaZulu-Natal between May 2008 and April 2009. Findings Interviews were conducted with 19,093 mothers aged between 12 and 39 years whose infants were aged ≤16 weeks. Most mothers had attended antenatal care four or more times during their last pregnancy (80.3%), and reported having an HIV test (98.2%). A greater proportion of HIV-infected adult mothers, compared to adolescent mothers, reported themselves as HIV-positive (41.2% vs. 15.9%, p<0.0001), reported having a CD4 count taken during their pregnancy (81.0% vs. 66.5%, p<0.0001), and having received the CD4 count result (84.4% vs. 75.7%, p<0.0001). Significantly fewer adolescent mothers received the recommended PMTCT regimen. HIV antibody was detected in 40.4% of 7,800 infants aged 4–8 weeks tested for HIV, indicating HIV exposure. This was higher among infants of adult mothers (47.4%) compared to adolescent mothers (17.9%, p<0.0001). The MTCT rate at 4–8 weeks of age was significantly higher amongst infants of adolescent mothers compared to adult mothers (35/325 [10.8%] vs. 185/2,800 [6.1%], OR 1.7, 95% CI 1.2–2.4). Conclusion Despite high levels of antenatal clinic attendance among pregnant adolescents in KwaZulu-Natal, the MTCT risk is higher among infants of HIV-infected adolescent mothers compared to adult mothers. Access to adolescent-friendly family planning and PMTCT services should be prioritised for this vulnerable group.
Server-based inference of Internet link lossiness

The problem of inferring the packet loss characteristics of Internet links using server-based measurements is investigated. Unlike much of existing work on network tomography that is based on active probing, we make inferences based on passive observation of end-to-end client-server traffic. Our work on passive network tomography focuses on identifying lossy links (i.e., the trouble spots in the network). We have developed three techniques for this purpose based on random sampling, linear optimization, and Bayesian inference using Gibbs sampling, respectively. We evaluate the accuracy of these techniques using both simulations and Internet packet traces. We find that these techniques can identify most of the lossy links in the network with a manageable false positive rate. For instance, simulation results indicate that the Gibbs sampling technique has over 80% coverage with a false positive rate under 5%. Furthermore, this technique provides a confidence indicator on its inference. We also perform inference based on Internet traces gathered at the busy microsoft.com Web site. However, validating these inferences is a challenging problem. We present a method for indirect validation that suggests that the false positive rate is manageable.