Miracle-dz/UniFAR-FTUs huggingface dataset:
Human C-Reactive Protein Activates Monocyte-Derived Dendritic Cells and Induces Dendritic Cell-Mediated T-Cell Activation

Objective—Recent studies proposed a pathogenic role for C-reactive protein (CRP), an independent predictor of cardiovascular disease (CVD), in atherosclerosis. Therefore, we tested whether CRP may modulate dendritic cell (DC) function, because these professional antigen-presenting cells have been implicated in atherogenesis. Methods and Results—Human monocyte-derived immature DCs were cultured with human CRP (0 to 60 &mgr;g/mL) for 24 hours. Thereafter, activation markers were measured by flow-cytometry and DCs were cocultured with CFSE-labeled lymphocytes to measure T-cell proliferation and interferon (IFN)-γ secretion after 8 days. Exposure to 60 &mgr;g/mL CRP (n=5) induced an activated cell morphology and significant (CD40 increase MFI 5.23±0.28, P<0.01 paired t test; CD80 6.18±0.51, P<0.01) to modest (CD83 1.38±0.17, P<0.05, CCR7 1.60±0.29, P=0.05) upregulation of DC activation markers. The expression of CD86 and HLA-DR was high, but not affected. T-lymphocytes incubated with CRP-pulsed DCs displayed increased IFN-γ secretion and proliferation (P<0.001). DC activation was concentration-dependent and detected from 2 &mgr;g/mL CRP; the maximum effect was equivalent to that seen with 0.1 &mgr;g/mL lipopolysaccharide (LPS). Polymyxin B abolished the LPS response, without influencing CRP effects. Finally, immunohistochemistry could demonstrate DC/CRP colocalization in human atherosclerotic lesions. Conclusions—These findings suggest that CRP in plaques or found circulating in CVD patients can influence DC function during atherogenesis.
Voting in Agreeable Societies

When can a majority of voters find common ground, that is, a position they all agree upon? How does the shape of the political spectrum influence the outcome? When mathematical objects have a social interpretation, the associated theorems have social applications. In this article we give examples of situations where sets model preferences and develop extensions of classical theorems about convex sets, such as Helly's theorem, that can be used in the analysis of voting in "agreeable" societies.
Least-squares methods with Poissonian noise: Analysis and comparison with the Richardson-Lucy algorithm

It is well-known that the noise associated with the collection of an astronomical image by a CCD camera is largely Poissonian. One would expect, therefore, that computational approaches that incorporate this a priori information will be more effective than those that do not. The Richardson-Lucy (RL) algorithm, for example, can be viewed as a maximum-likelihood (ML) method for image deblurring when the data noise is assumed to be Poissonian. Least-squares (LS) approaches, on the other hand, are based on the assumption that the noise is Gaussian with fixed variance across pixels, which is rarely accurate. Given this, it is surprising that in many cases results obtained using LS techniques are relatively insensitive to whether the noise is Poissonian or Gaussian. Furthermore, in the presence of Poisson noise, results obtained using LS techniques are often comparable with those obtained by the RL algorithm. We seek an explanation of these phenomena via an examination of the regularization properties of particular LS algorithms. In addition, a careful analysis of the RL algorithm yields an explanation as to why it is more effective than LS approaches for star-like objects, and why it provides similar reconstructions for extended objects. Finally a comparative convergence analysis of the two algorithms is carried out, with a section devoted to the conver- gence properties of the RL algorithm. Numerical results are presented throughout the paper. The subject treated in this paper is not purely academic. In comparison with many ML algorithms, the LS algorithms are much easier to use and to implement, are computationally more efficient, and are more flexible regarding the incorporation of constraints on the solution. Consequently, if little to no improvement is gained in the use of an ML approach over an LS algorithm, the latter will often be the preferred approach.
Multivariate Analysis of Students’ Perception of the Impact of Lecturers’ Ranks on their Performance at the Faculty of Mathematical Sciences, University for Development Studies-Navrongo, Ghana

This paper examines students’ perception of the impact of lecturers’ ranks on their performance across departments in the Faculty of Mathematical Sciences (FMS) of the University for Development Studies (UDS), Navrongo Campus. The study used a self-designed structured questionnaire administered to 160 respondents (students) of the Faculty. All the 160 questionnaires were retrieved, which represents 100% response rate. The data were analyzed using Statistical Package for Social Sciences (SPSS) version 25.0 for windows. Multivariate Analysis of Variance (MANOVA) results showed that (at P<0.05) Senior Lecturers received higher ratings followed by Lecturers and then Assistant Lecturers, indicating that the ranks of Teaching Staff significantly influenced their performance across the various departments of the Faculty. Recommendations and implications for management of Higher Institutions of Learning (HIL) have been discussed. The paper contributes to the literature in the area of supervision and evaluation of the performance of teaching staff in the HIL context.
Prédiction de performance des start-ups de haute technologie : Approche quantitative à partir de la théorie des mathématiques floues

Pourquoi des start-ups high-tech reussissent-elles et d'autres pas ? Cette question de « performance » de start-ups high-tech attire l'attention des nombreux auteurs dans la litterature recente et surtout de la part des praticiens de terrain. Les etudes bibliographiques traitent ce questionnement de deux manieres: (1) a partir des approches holistiques qualitatives et (2) a partir des modeles partiels quantitatifs. Cependant, une meilleure prediction de performances necessiterait une combinaison entre approche "holistique et quantitative". Cette combinaison est prospectee dans la presente etude par l'exploration de methodes alternatives pour la prediction des perspectives globales d'une start-up high-tech, incluant une demarche specifique pour sa capacite de lever de fonds. Dans cet objectif, les facteurs pertinents indicateurs de la performance et leurs interactions ont ete recherches, y integrant des relations non lineaires. Une analyse de 124 start-ups high-tech europeennes a ete realisee a l'aide de trois methodes differentes : la regression lineaire, une analyse cluster et une analyse a partir de la Theorie du Flou. La comparaison entre les trois methodes montre que l'approche integree est mieux quantifiee a l'aide de la Theorie du Flou. Les modeles « flous » donnent une precision superieure a celle de la regression et de l'analyse cluster. Deuxiemement, leur generalisation et leur puissance de prediction depasse celle des methodes statistiques. Il est ainsi demontre que des methodes analytiques alternatives peuvent ameliorer la performance predictive sur les facteurs de succes des start-up high-tech. Les resultats de l'etude confirment que la performance de start-ups high-tech est mieux explicitee par une vision holistique. La prediction la plus performante provient (1) des modeles bases sur l'ensemble des domaines de la start-up, (2) integrant les interactions entre ces domaines et (3) incluent des relations non lineaires. Les resultats sont utilises pour le developpement d'un outil de diagnostic et d'aide a la decision pour les start-ups high-tech : le « Venture Coach ». Cette etude permet de progresser pour la theorie d'entreprenariat et trouvera des applications de terrain aupres des entrepreneurs et des personnes qui accompagnent les start-ups.
PHENOTYPIC PLASTICITY IN THE SAILFIN MOLLY, POECILIA LATIPINNA (PISCES: POECILIIDAE). II. LABORATORY EXPERIMENT

Field studies indicate that the influence of environmental factors on growth rate and size and age at maturity in sailfin mollies (Poecilia latipinna) is inconsistent over time and suggest that the marked interdemic variation in male body size in this species is the result of genetic variation. However, the role of specific environmental factors in generating phenotypic variation must be studied under controlled conditions unattainable in nature. We raised newborn sailfin mollies from four populations in laboratory aquaria under all possible combinations of two temperatures, three salinities, and two food levels to examine explicitly the influence of these environmental factors. Males were much less susceptible than females to temperature variation and were generally less plastic than females in terms of all three traits. Members of both sexes matured at larger sizes and at later ages in less saline and in cooler environments. Food levels were not sufficiently different to affect the traits we studied. The effects of temperature and salinity were not synergistic. Males from different populations exhibited different average ages and sizes at maturity, but females did not. The magnitudes of the effects we found were not substantial enough to account for the consistent interdemic differences in male and female body size that have been observed previously. Our results also indicate that no single environmental factor is solely responsible for the environmental effects observed in field experiments on growth and development. These studies, together with other work, indicate that the strongest sources of interdemic variation are genetic differences in males and differences in postmaturation growth and survivorship in females.
Towards Autonomous Situation Awareness

Technological advances in communication and computing coupled with low costs of sensors have enabled large-scale deployment of video camera networks in our environment nowadays. They are increasingly being used by decision-makers for perceiving elements of an environment in real-time, comprehending their meaning and predicting their status in the near future. Such situational awareness is crucial in dynamic scenarios that arise in military command and control, facility security and emergency services such as policing and fire-fighting. While human perception driven situation awareness has worked well in constrained settings, it is unfortunately not scalable. Furthermore, scenarios such as security and surveillance commonly involve highly complex cognitive tasks that can quickly become monotonous and mentally taxing for human operators. In this thesis, we present new frameworks for automating the perception stage of situation awareness.We begin this thesis with the development of a system that is capable of categorizing objects and landmarks in an efficient and distributed manner. Our system is designed to operate with net- works of wireless smart cameras for local perception, and a central station for global inference. We demonstrate that this decoupling of the algorithm pipeline can drastically minimize the power and bandwidth consumed by the wireless cameras. Further, we experimentally validate that our multiple-view inference framework can significantly improve the performance of object and land- mark categorization over traditional single-view settings.In the second part of the thesis we extend our distributed object categorization framework to address the problem of automatic human activity detection and categorization. We are particularly interested in the development of rich representations for human motion that are invariant to perspective, scale and the speed at which actions are performed. We propose a generalized framework to perform spatiotemporal fusion of dynamic imagery from multiple wireless smart cameras, and validate the efficacy of our fusion framework on both publicly available, and novel datasets.In most realistic scenarios that require situation awareness, objects and people occur in cluttered scenes and exhibit immense variability in their appearance, shape and pose. In the final part of this thesis, we analyze the interplay between computer vision tasks such as segmentation and categorization and present joint frameworks that significantly improve the performance of each task. Our experimental analysis demonstrates that detection and categorization hypotheses help provide good segmentation results, and that segmentation can be used to prune errors in the hypothesis.
Differential Changes in Heat Shock Protein-, Lipoarabinomannan-, and Purified Protein Derivative-Specific Immunoglobulin G1 and G2 Isotype Responses during Bovine Mycobacterium aviumsubsp. paratuberculosis Infection

ABSTRACT Bovine paratuberculosis is caused by infection of young calves withMycobacterium avium subsp. paratuberculosis. In some of the chronically infected cows the long asymptomatic stage (2 to 4 years) is followed by a rapid progression to a clinical stage due to protein-losing enteropathy, which will ultimately be fatal. The current dogma is that in early stages of disease the cell-mediated responses predominate, whereas in the clinical stage of the disease the humoral responses prevail, possibly signaling a switch in immune reactivity related to disease progression. We developed immunoglobulin M (IgM)-, IgA-, and IgG1- and IgG2-isotype-specific enzyme-linked immunosorbent assays for M. avium subsp.paratuberculosis-derived antigens (heat shock proteins of 70 kDa [Hsp70] and 65 kDa [Hsp65], lipoarabinomannan [LAM], andM. avium subsp. paratuberculosis purified protein derivative PPD [PPDP]). The serological responses of cows in different stages of paratuberculosis were used to evaluate the putative shift in immune responsiveness. In the clinical stage the PPDP-specific IgG1 responses were increased compared to those in the asymptomatic stage. However, total IgG1 and IgG2 and the Hsp70-, Hsp65-, and LAM-specific isotype responses were decreased in the clinical stage were decreased compared to those in the asymptomatic stage of disease. Thus, the classical pattern was found only for PPDP antigens and the IgG1 isotype. For other antigens and isotypes and the total IgG levels, the response pattern is different and indicates that there is no uniform association with increased antibody responses during the progression from the asymptomatic stage to the clinical stage of bovine paratuberculosis.
Cophylogenetic relationships between penguins and their chewing lice

It is generally thought that the evolution of obligate parasites should be linked intimately to the evolution of their hosts and that speciation by the hosts should cause speciation of their parasites. The penguins and their chewing lice present a rare opportunity to examine codivergence between a complete host order and its parasitic lice. We estimated a phylogeny for all 15 species of lice parasitising all 17 species of penguins from the third domain of the mitochondrial 12S ribosomal rRNA gene, a portion of the mitochondrial cytochrome oxidase subunit 1 gene and 55 morphological characters. We found no evidence of extensive cospeciation between penguins and their chewing lice using TreeMap 2. 02β. Despite the paucity of cospeciation, there is support for significant congruence between the louse and penguin phylogenies due to possible failure to speciate events (parasites not speciating in response to their hosts speciating).
Blind estimation and mitigation of nonlinear channels

Nonlinear distortions in the analog frontend are becoming a growing problem. With rising requirements it becomes more expensive to provide components with sufficient linearity. Especially in the receiver, where out-of-band radiation is not an issue, relaxing the requirements on the analog components could significantly reduce development and production costs as well as increase the energy efficiency. There are numerous algorithms to mitigate the effects caused by nonlinearities. This paper presents a method for the blind estimation of nonlinearity parameters which can be applied to a large class of nonlinearities. The estimator is integrated in an OFDM system with nonlinearity mitigation and it shows that there is negligible performance degradation compared to perfect knowledge. The Cramer-Rao lower bound is derived and it is shown that the estimator reaches it in the high SNR region. Special care was taken to provide a solution with low computational complexity that can be readily implemented on current platforms.
Genetic Dissection of the Neural Circuitry Underlying Memory Stability in Drosophila: A Dissertation

Understanding how memory is formed requires looking beyond the genes involved to the neural circuitry and temporal aspects of memory. In this dissertation I have focused my investigation on Dorsal Paired Medial (DPM) neurons, two modulatory neurons essential for memory in Drosophila. DPM neurons highly express the amnesiac (amn) gene, which encodes for a putative pre-pro-neuropeptide. amn function in DPM neurons is required for memory. Here I provide evidence that DPM neurons are cholinergic and that acetylcholine (ACh) and AMN act as cotransmitters essential for DPM function. In order to investigate the temporal requirements of DPM output I blocked transmitter release during discrete intervals in the memory process using shibirets1 and tested flies for shock and sugar-reinforced memory. These experiments demonstrated that stable memory requires persistent transmitter release from DPM neurons. Furthermore these results suggest AMN and DPM neurons act as general stabilizers of mushroom body dependent memory. To further investigate the neural circuitry underlying DPM function I disrupted DPM projections onto the mushroom body lobes by ectopically expressing DScam17-2::GFP in DPM neurons. Flies with DPM neurons that predominantly project to the mushroom body α ́/β ́ lobes exhibit normal memory, and blocking transmitter release from the mushroom
The Compoundness and Sequentiality of Digital Inequality

Through a survey with a representative sample of Dutch Internet users, this article examines compound digital exclusion: whether a person who lacks a particular digital skill also lacks another kind of skill, whether a person who does not engage in a particular way online is also less likely to engage in other ways, and whether a person who does not achieve a certain outcome online is also less likely to achieve another type of outcome. We also tested sequential digital exclusion: whether a lower level of digital skills leads to lower levels of engagement with the Internet, resulting in a lower likelihood for an individual to achieve tangible outcomes. Both types of digital exclusion are a reality. Certain use can have a strong relation with an outcome in a different domain. Furthermore, those who achieve outcomes in one domain do not necessarily achieve outcomes in another domain. To get a comprehensive picture of the nature of digital exclusion, it is necessary to account for different domains in research.
BOOM: Enabling mobile memory based low-power server DIMMs

To address the real-time processing needs of large and growing amounts of data, modern software increasingly uses main memory as the primary data store for critical information. This trend creates a new emphasis on high-capacity, high-bandwidth, and high-reliability main memory systems. Conventional and recently-proposed server memory techniques can satisfy these requirements, but at the cost of significantly increased memory power, a key constraint for future memory systems. In this paper, we exploit the low-power nature of another high volume memory component-mobile DRAM-while improving its bandwidth and reliability shortcomings with a new DIMM architecture. We propose Buffered Output On Module (BOOM) that buffers the data outputs from multiple ranks of low-frequency mobile DRAM devices, which in aggregation provide high bandwidth and achieve chipkill-correct or even stronger reliability. Our evaluation shws that BOOM can reduce main memory power by more than 73% relative to the baseline chipkill system, while improving average performance by 5% and providing strong reliability. For memory-intensive applications, BOOM can improve performance by 30-40%.
Targeting 5-lipoxygenase-activating protein in asthma and chronic obstructive pulmonary disease

Introduction: In asthma and chronic obstructive pulmonary disease (COPD), there is an unmet therapeutic need for the anti-inflammatory therapies, and the identification of therapeutic targets and potent corresponding therapies is necessary. Although inhaled corticosteroids and leukotriene modifiers are most effective in asthma they are still not always capable of appropriately controlling the disease. In COPD, the therapeutic gap is even larger because inhaled corticosteroids and other anti-inflammatory therapies are not beneficial in all disease subsets. Areas covered: The role of the 5-lipoxygenase-activating protein (FLAP) in generating proinflammatory molecules such as leukotrienes is discussed, highlighting, in particular, its potential as a therapeutic target in asthma and COPD. The preclinical data on FLAP inhibitors are discussed. The clinical data on the FLAP inhibitors investigated so far for these diseases are analyzed. Expert opinion: FLAP inhibitors have emerged during the past decade as a promising therapeutic class in asthma and COPD, but there exists only a limited amount of data supporting their efficacy in these diseases. This might be due to the fact that the development of some of the molecules discussed was abandoned. Such therapies might be of particular interest in COPD and in asthma-COPD overlap syndrome.
Evaluation of high nutrient diets on litter performance of heat-stressed lactating sows

Objective The present study investigated the litter performance of multiparous sows fed 3% and 6% densified diets at farrowing to weaning during summer with mean maximum room temperature of 30.5°C. Methods A total of 60 crossbred multiparous sows were allotted to one of three treatments based on body weight according to a completely randomized design. Three different nutrient levels based on NRC were applied as standard diet (ST; metabolizable energy, 3,300 kcal/kg), high nutrient level 1 (HE1; ST+3% higher energy and 16.59% protein) and high nutrient level 2 (HE2; ST+6% higher energy and 17.04% protein). Results There was no variation in the body weight change. However, backfat thickness change tended to reduce in HE1 in comparison to ST treatment. Dietary treatments had no effects on feed intake, daily energy intake and weaning-to-estrus interval in lactating sows. Litter size, litter weight at weaning and average daily gain of piglets were significantly greater in sows in HE1 compared with ST, however, no difference was observed between HE2 and ST. Increasing the nutrient levels had no effects on the blood urea nitrogen, glucose, triglyceride, and creatinine at post-farrowing and weaning time. The concentration of follicle stimulating hormone, cortisol and insulin were not affected by dietary treatments either in post-farrowing or weaning time. The concentration of blood luteinizing hormone of sows in ST treatment was numerically less than sows in HE2 treatment at weaning. Milk and colostrum compositions such as protein, fat and lactose were not affected by the treatments. Conclusion An energy level of 3,400 kcal/kg (14.23 MJ/kg) with 166 g/kg crude protein is suggested as the optimal level of dietary nutrients for heat stressed lactating sows with significant beneficial effects on litter size.