Miracle-dz/UniFAR-FTUs huggingface dataset:
A model of costs of RTI case management services in Uttar Pradesh.

This paper develops a model of standardized reproductive tract infection (RTI) management in the public sector using guidelines prepared by the National AIDS Control Organization. It also discusses the costs of upscaling the service to similar sites in Sitapur and Agra districts of Uttar Pradesh, India. The model shown in the paper conceives providing RTI case management services at the block Primary Health Centers (PHC) and Community Health Centers (CHC) levels. It estimates the cost of providing RTI case management at PHC and at CHC and by extension to the district. Furthermore, the model presents differing options according to the level of health system services that are available. The paper concludes that the costs of RTI case management varies widely by the levels of utilization, the levels of infection and the capability of health centers to provide the services. The model of RTI case management indicates that laboratory testing and treatment costs are higher than expected. The estimated cost for RTI management is beyond the existing budgets, and policymakers and program managers need to examine both the initial and continuing costs of the RTI case management in the context of the entire Reproductive and Child Health package.
Tractable Bayesian Learning of Tree Augmented Naive Bayes Classifiers

Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions. In this paper we introduce a classifier taking as basis the TAN models and taking into account uncertainty in model selection. To do this we introduce decomposable distributions over TANs and show that the expression resulting from the Bayesian model averaging of TAN models can be integrated into closed form if we assume the prior probability distribution to be a decomposable distribution. This result allows for the construction of a classifier with a shorter learning time and a longer classification time than TAN. Empirical results show that the classifier is, most of the cases, more accurate than TAN and approximates better the class probabilities.
Depth-based inpainting for disocclusion filling

Depth-based inpainting methods can solve disocclusion problems occurring in depth-image-based rendering. However, inpainting in this context suffers from artifacts along foreground objects due to foreground pixels in the patch matching. In this paper, we address the disocclusion problem by a refined depth-based inpainting method. The novelty is in classifying the foreground and background by using available local depth information. Thereby, the foreground information is excluded from both the source region and the target patch. In the proposed inpainting method, the local depth constraints imply inpainting only the background data and preserving the foreground object boundaries. The results from the proposed method are compared with those from the state-ofthe art inpainting methods. The experimental results demonstrate improved objective quality and a better visual quality along the object boundaries.
Modelling of two-dimensional infiltration experiments of water or diesel oil in an instrumented 2D channel

Abstract This paper reports the modelling of two-dimensional infiltration experiments, with diesel or water as the permeate liquids in an unsaturated dune sand. Also reports the measurements of soil hydraulic properties (retention curve and saturated hydraulic conductivity) in laboratory, and infiltration experiments using a 2D channel. The time ratio (T diesel/T water) for the wetting fronts to reach the tensiometers was consistent with the ratio of mobilities water/diesel, The SEEP/W, a numerical 2D code, modelled well the successive wetting front vertical positions for the liquids. However, the simulations for the lateral spreading were better for diesel, as this experiment was a complete wetting phenomenon, differently for water, that developed unsaturated conditions inside the column. The Philip 1D equation modelled the successive vertical positions for the liquids, using two different sets of parameters. The first set (ϕ, Kñsat , hp = 0): porosity, unsaturated hydraulic conductivity and incipient hydraulic head; and the second set, (ϕ c, Ksat , hp = 0): corrected porosity value to include the plume lateral spreading, saturated hydraulic conductivity and incipient hydraulic head. Although both sets of parameters are adequate to model the vertical component of the infiltration experiments, the first set is more efficient as it is independent of the corrected porosity, a value known afterwards.
Sophia: Local Trust for Securing Routing in DHTs

Distributed Hash Tables (DHTs) have been used as a common building block in many distributed applications, including Cloud and Grid. However, there are still important security vulnerabilities that hinder their adoption in today'slarge-scale computing platforms. For instance, routing vulnerabilities have been a subject of intensive research but existing solutions rely on redundancy in lieu of improving the quality of routing paths. In this paper, we present Sophia, a novel generic security technique which combines iterative routing with local trust to fortify routing in DHTs. Sophia strictly benefits from first-hand observations about the success/failure of a node's own lookups to improve forwarding paths. Moreover, unlike redundant routing, Sophia dynamically protects routing without introducing additional network overhead. To the best of our knowledge, this is the first work which exploits a local trust system to fortify routing in DHTs. We compared the performance of Sophia with redundant routing in Kademlia DHT. We obtained significant improvements regarding routing resilience, self-adjustment and network traffic reduction.
Authentication of Smartphone Users Based on the Way They Walk Using k-NN Algorithm

Accelerometer-based biometric gait recognition offers a convenient way to authenticate users on their mobile devices. Modern smartphones contain in-built accelerometers which can be used as sensors to acquire the necessary data while the subjects are walking. Hence, no additional costs for special sensors are imposed to the user. In this publication we extract several features from the gait data and use the k-Nearest Neighbour algorithm for classification. We show that this algorithm yields a better biometric performance than the machine learning algorithms we previously used for classification, namely Hidden Markov Models and Support Vector Machines. We implemented the presented method on a smartphone and demonstrate that it is efficient enough to be applied in practice.
Galaxy And Mass Assembly (GAMA): the dependence of the galaxy luminosity function on environment, redshift and colour

We use 80 922 galaxies in the Galaxy And Mass Assembly (GAMA) survey to measure the galaxy luminosity function (LF) in different environments over the redshift range 0.04 < z < 0.26. The depth and size of GAMA allows us to define samples split by colour and redshift to measure the dependence of the LF on environment, redshift and colour. We find that the LF varies smoothly with overdensity, consistent with previous results, with little environmental dependent evolution over the last 3 Gyr. The modified GALFORM model predictions agree remarkably well with our LFs split by environment, particularly in the most overdense environments. The LFs predicted by the model for both blue and red galaxies are consistent with GAMA for the environments and luminosities at which such galaxies dominate. Discrepancies between the model and the data seen in the faint end of the LF suggest too many faint red galaxies are predicted, which is likely to be due to the over-quenching of satellite galaxies. The excess of bright blue galaxies predicted in underdense regions could be due to the implementation of AGN feedback not being sufficiently effective in the lower mass haloes.
Mechanotransduction from the ECM to the genome: Are the pieces now in place?

A multitude of biochemical signaling processes have been characterized that affect gene expression and cellular activity. However, living cells often need to integrate biochemical signals with mechanical information from their microenvironment as they respond. In fact, the signals received by shape alone can dictate cell fate. This mechanotrasduction of information is powerful, eliciting proliferation, differentiation, or apoptosis in a manner dependent upon the extent of physical deformation. The cells internal “prestressed” structure and its “hardwired” interaction with the extra‐cellular matrix (ECM) appear to confer this ability to filter biochemical signals and decide between divergent cell functions influenced by the nature of signals from the mechanical environment. In some instances mechanical signaling through the tissue microenvironment has been shown to be dominant over genomic defects, imparting a normal phenotype on cells that otherwise have transforming genetic lesions. This mechanical control of phenotype is postulated to have a central role in embryogenesis, tissue physiology as well as the pathology of a wide variety of diseases, including cancer. We will briefly review studies showing physical continuity between the external cellular microenvironment and the interior of the cell nucleus. Newly characterized structures, termed nuclear envelope lamina spanning complexes (NELSC), and their interactions will be described as part of a model for mechanical transduction of extracellular cues from the ECM to the genome. J. Cell. Biochem. 104: 1964–1987, 2008. © 2007 Wiley‐Liss, Inc.
Participation of IHF and a distant UP element in the stimulation of the phage λ PL promoter

We have previously identified a UP element in the phage λ PL promoter, centred at position −90 from the transcription start site. Integration host factor (IHF), a heterodimeric DNA‐binding and ‐bending protein, binds upstream of the λ PL promoter in a region overlapping the UP element. Stimulation of transcription by IHF requires an intact αCTD and affects the initial binding of RNA polymerase to the promoter. We propose a model for the stimulation of PL by IHF in which IHF bends the DNA to bring the distal UP sequence in closer proximity to the promoter core sequences to allow the docking of the αCTD of RNA polymerase. Furthermore, IHF may also participate in protein–protein interactions with the αCTD. In support of this model, we found that alanine substitutions in αCTD at positions 265, 268, 270 and 275 reduced PL promoter activity. Mutations in the IHF DNA binding site, as well as IHF mutant proteins exhibiting a decreased ability to bend the DNA, were both defective in stimulating the PL promoter. In addition, some of the mutated IHF residues are clustered at a protein surface that interacts with the UP DNA sequence. These residues may also participate in protein–protein interactions with the αCTD.
Stroop Color and Word Test

A mobile crane has a boom comprising a plurality of telescopic boom sections. Each boom section is fabricated of solid steel plates with the top plate being wider than the bottom plate and the side plates welded therebetween and sloped inwardly. Side plate stiffeners welded between the bottom plate and the side plates run the length of the boom section. This configuration results in a boom section of minimum weight with a bottom plate of relatively increased buckling strength and maximum interior space for boom operating components.
A comparison of RDB-to-RDF mapping languages

Mapping Relational Databases (RDB) to RDF is an active field of research. The majority of data on the current Web is stored in RDBs. Therefore, bridging the conceptual gap between the relational model and RDF is needed to make the data available on the Semantic Web. In addition, recent research has shown that Semantic Web technologies are useful beyond the Web, especially if data from different sources has to be exchanged or integrated. Many mapping languages and approaches were explored leading to the ongoing standardization effort of the World Wide Web Consortium (W3C) carried out in the RDB2RDF Working Group (WG). The goal and contribution of this paper is to provide a feature-based comparison of the state-of-the-art RDB-to-RDF mapping languages. It should act as a guide in selecting a RDB-to-RDF mapping language for a given application scenario and its requirements w.r. t. mapping features. Our comparison framework is based on use cases and requirements for mapping RDBs to RDF as identified by the RDB2RDF WG. We apply this comparison framework to the state-of-the-art RDB-to-RDF mapping languages and report the findings in this paper. As a result, our classification proposes four categories of mapping languages: direct mapping, read-only general-purpose mapping, read-write general-purpose mapping, and special-purpose mapping. We further provide recommendations for selecting a mapping language.
Honey Bee Gut Microbiome Is Altered by In-Hive Pesticide Exposures

Honey bees (Apis mellifera) are the primary pollinators of major horticultural crops. Over the last few decades, a substantial decline in honey bees and their colonies have been reported. While a plethora of factors could contribute to the putative decline, pathogens, and pesticides are common concerns that draw attention. In addition to potential direct effects on honey bees, indirect pesticide effects could include alteration of essential gut microbial communities and symbionts that are important to honey bee health (e.g., immune system). The primary objective of this study was to determine the microbiome associated with honey bees exposed to commonly used in-hive pesticides: coumaphos, tau-fluvalinate, and chlorothalonil. Treatments were replicated at three independent locations near Blacksburg Virginia, and included a no-pesticide amended control at each location. The microbiome was characterized through pyrosequencing of V2–V3 regions of the bacterial 16S rRNA gene and fungal ITS region. Pesticide exposure significantly affected the structure of bacterial but not fungal communities. The bee bacteriome, similar to other studies, was dominated by sequences derived from Bacilli, Actinobacteria, α-, β-, γ-proteobacteria. The fungal community sequences were dominated by Ascomycetes and Basidiomycetes. The Multi-response permutation procedures (MRPP) and subsequent Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis indicated that chlorothalonil caused significant change to the structure and functional potential of the honey bee gut bacterial community relative to control. Putative genes for oxidative phosphorylation, for example, increased while sugar metabolism and peptidase potential declined in the microbiome of chlorothalonil exposed bees. The results of this field-based study suggest the potential for pesticide induced changes to the honey bee gut microbiome that warrant further investigation.
A Situation-aware and Social Computational Trust Model

Computational trust modeling is a research field with a fast growing development since the last decade, mainly in the scientific area of distributed artificial intelligence and multi-agent systems, and its potential applicability spreads from social networks to distributed resource sharing and electronic markets. The earliest approaches to computational trust addressed the development of algorithms to aggregate the evidence on any given agent under evaluation into an estimated score of this agent’s trustworthiness. More recently, the research on computational trust has shifted to the inclusion of third-party information about the trustee under evaluation, including opinions and reputation. However, one important aspect of computational trust has being neglected all these years by the majority of the scholars on computational trust, with a few relevant exceptions: trust is a social construct with a cognitive and an emotional account, and it strongly depends on the relationship existing between the agent that trusts and the one that is trusted. In this thesis, we address the topic of social trust and its consideration for application in computational trust. We first present a thorough multidisciplinary view of trust, and derive important propositions that will guide our work throughout the thesis. Based on these propositions, we present the SOLUM model, our proposal to computational trust comprised of two distinct parts. The first part is a general framework of computational trust that is based on two fundamental characteristics of trust: trust is more than trustworthiness and other important antecedents to trust, such as the truster’s disposition and emotional state, must be considered when estimation the truster’s trust; and trustworthiness is a multi-dimensional construct that includes the ability, integrity, and benevolence dimensions. This framework can be instantiated and applied to a wide range of trust-based problems and applications, and is seen here as the first main contribution of this thesis. The second part of the SOLUM model includes a set of distinct computational components that (partially) instantiate the framework, namely:
Aldosterone Induces Renal Fibrosis and Inflammatory M1-Macrophage Subtype via Mineralocorticoid Receptor in Rats

We aimed to evaluate macrophages heterogeneity and structural, functional and inflammatory alterations in rat kidney by aldosterone + salt administration. The effects of treatment with spironolactone on above parameters were also analyzed. Male Wistar rats received aldosterone (1 mgkg-1d-1) + 1% NaCl for 3 weeks. Half of the animals were treated with spironolactone (200 mg kg-1d-1). Systolic and diastolic blood pressures were elevated (p<0.05) in aldosterone + salt–treated rats. Relative kidney weight, collagen content, fibronectin, macrophage infiltrate, CTGF, Col I, MMP2, TNF-α, CD68, Arg2, and SGK-1 were increased (p<0.05) in aldosterone + salt–treated rats, being reduced by spironolactone (p<0.05). Increased iNOS and IFN-γ mRNA gene expression (M1 macrophage markers) was observed in aldosterone + salt rats, whereas no significant differences were observed in IL-10 and gene ArgI mRNA expression or ED2 protein content (M2 macrophage markers). All the observed changes were blocked with spironolactone treatment. Macrophage depletion with liposomal clodronate reduced macrophage influx and inflammatory M1 markers (INF-γ or iNOS), whereas interstitial fibrosis was only partially reduced after this intervention, in aldosterone plus salt-treated rats. In conclusion, aldosterone + salt administration mediates inflammatory M1 macrophage phenotype and increased fibrosis throughout mineralocorticoid receptors activation.
Dichotomous Pedagogies and the Promise of Comparative Research.

Naive dichotomous representations of complex realities persist in part because there is unfilled political and conceptual space in which they can flourish. Dichotomous representations of pedagogy have been popular and linger even though more discerning educators have abandoned this kind of rhetoric. Comparative perspective might contribute to the development of a nondichotomizing pedagogy. In support of this position, three propositions are drawn from the author's own comparative research. Across cultures, one can find a recurrence of many more than two contrasting bedrock views of what teaching is about. As these viewpoints surface in different combinations, they extend the range of pedagogical orientations and possibilities. Beyond these are primordial values about the relationships of individuals to each other and two society that have a direct bearing on how teachers think and how they act. The identification of such values, value concordances, and dissonances in everyday classroom practice is greatly aided if there is a coherent model or framework for conceptualizing teaching itself. One way of breaking free of bipolar models of teaching is to devise frameworks for making sense of educational values and practices that make such bipolarity as difficult as possible. (Contains 36 endnotes.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document.
Medicine Is a Science and a Normative Practice

I tend to agree with Hillel Braude’s thesis that alleviation of suffering is not an aim, at least not the primary aim, of medicine. However, this thesis needs to be refined and reformulated, because it at best expresses half the truth. The other half is that it is not justifiable for doctors to pay no attention to suffering. In other words, the thesis I would have liked Braude to defend is that it is true that doctors are no experts in existential issues and concerns and that it is equally true that they cannot ignore these existential issues and concerns without harming the relationship with their patients.
IDEAL-Q, an Automated Tool for Label-free Quantitation Analysis Using an Efficient Peptide Alignment Approach and Spectral Data Validation*

In this study, we present a fully automated tool, called IDEAL-Q, for label-free quantitation analysis. It accepts raw data in the standard mzXML format as well as search results from major search engines, including Mascot, SEQUEST, and X! Tandem, as input data. To quantify as many identified peptides as possible, IDEAL-Q uses an efficient algorithm to predict the elution time of a peptide unidentified in a specific LC-MS/MS run but identified in other runs. Then, the predicted elution time is used to detect peak clusters of the assigned peptide. Detected peptide peaks are processed by statistical and computational methods and further validated by signal-to-noise ratio, charge state, and isotopic distribution criteria (SCI validation) to filter out noisy data. The performance of IDEAL-Q has been evaluated by several experiments. First, a serially diluted protein mixed with Escherichia coli lysate showed a high correlation with expected ratios and demonstrated good linearity (R2 = 0.996). Second, in a biological replicate experiment on the THP-1 cell lysate, IDEAL-Q quantified 87% (1,672 peptides) of all identified peptides, surpassing the 45.7% (909 peptides) achieved by the conventional identity-based approach, which only quantifies peptides identified in all LC-MS/MS runs. Manual validation on all 11,940 peptide ions in six replicate LC-MS/MS runs revealed that 97.8% of the peptide ions were correctly aligned, and 93.3% were correctly validated by SCI. Thus, the mean of the protein ratio, 1.00 ± 0.05, demonstrates the high accuracy of IDEAL-Q without human intervention. Finally, IDEAL-Q was applied again to the biological replicate experiment but with an additional SDS-PAGE step to show its compatibility for label-free experiments with fractionation. For flexible workflow design, IDEAL-Q supports different fractionation strategies and various normalization schemes, including multiple spiked internal standards. User-friendly interfaces are provided to facilitate convenient inspection, validation, and modification of quantitation results. In summary, IDEAL-Q is an efficient, user-friendly, and robust quantitation tool. It is available for download.
A particle swarm with selective particle regeneration for multimodal functions

This paper proposes an improved particle swarm optimization (PSO). In order to increase the efficiency, suggestions on parameter settings is made and a mechanism is designed to prevent particles fall into the local optimal. To evaluate its effectiveness and efficiency, this approach is applied to multimodal function optimizing tasks. 16 benchmark functions were tested, and results were compared with those of PSO, HNMPSO and GA-PSO. It shows the proposed method is both robust and suitable for multimodal function optimization.