Miracle-dz/UniFAR-FTUs huggingface dataset:
On the relationship between radiance and irradiance: determining the illumination from images of a convex Lambertian object.

We present a theoretical analysis of the relationship between incoming radiance and irradiance. Specifically, we address the question of whether it is possible to compute the incident radiance from knowledge of the irradiance at all surface orientations. This is a fundamental question in computer vision and inverse radiative transfer. We show that the irradiance can be viewed as a simple convolution of the incident illumination, i.e., radiance and a clamped cosine transfer function. Estimating the radiance can then be seen as a deconvolution operation. We derive a simple closed-form formula for the irradiance in terms of spherical harmonic coefficients of the incident illumination and demonstrate that the odd-order modes of the lighting with order greater than 1 are completely annihilated. Therefore these components cannot be estimated from the irradiance, contradicting a theorem that is due to Preisendorfer. A practical realization of the radiance-from-irradiance problem is the estimation of the lighting from images of a homogeneous convex curved Lambertian surface of known geometry under distant illumination, since a Lambertian object reflects light equally in all directions proportional to the irradiance. We briefly discuss practical and physical considerations and describe a simple experimental test to verify our theoretical results.
The Foundational Model of Anatomy in OWL: Experience and Perspectives

We present the method developed for migrating the Foundational Model of Anatomy (FMA) from its representation with frames in Protégé to its logical representation in OWL and our experience in reasoning with it. Despite the extensive use of metaclasses in Protégé, it proved possible to convert the FMA from Protégé into OWL DL, while capturing most of its original features. The conversion relies on a set of translation and enrichment rules implemented with flexible options. Unsurprisingly, reasoning with the FMA in OWL proved to be a real challenge, due to its sheer size and complexity, and raised significant inference problems in terms of time and memory requirements. However, various smaller versions have been successfully handled by Racer. Some inconsistencies were identified and several classes reclassified. The results obtained so far show the advantage of OWL DL over frames and, more generally, the usefulness of DLs reasoners for building and maintaining the large-scale biomedical ontologies of the future Semantic Web.
Parvalbumin, a Neuronal Protein in Brain Cell Cultures

Abstract: Dissociated brain cell cultures were derived from 14‐day‐old embryonic as well as from newborn mice. The cells were grown in a medium containing 10% fetal calf serum. Indirect immunofluorescence was performed using antisera directed against the Ca + ‐binding protein parvalbumin (M., 12,000). In embryonic cultures a large proportion of cells was intensely stained by anti‐ parvalbumin. In double‐labelling experiments involving the simultaneous application of antisera against parvalbumin and the neuron‐specific enolase, the enolase‐con‐ taining cells were also parvalbumin‐positive and both antisera revealed identical intracellular staining patterns. Conversely, almost no parvalbumin‐ and enolase‐positive cells were present in cultures derived from newbornmice. However, in these cultures many cells were immunoreactive toward the myelin basic protein, an accepted marker for oligodendrocytes. The presence of parvalbumin within the embryonic brain cell cultures was confirmed by analyses of the culture extracts (4 mM EDTA, pH 7.5) by HPLC on reverse‐phase supports, two‐dimensional polyacrylamide gel electrophoresis, and immunoblotting. The present study suggests that in mouse brain cell cultures, parvalbumin is localized in neurons.
ZNNi: Maximizing the Inference Throughput of 3D Convolutional Networks on CPUs and GPUs

Sliding window convolutional networks (ConvNets) have become a popular approach to computer vision problems such as image segmentation and object detection and localization. Here we consider the parallelization of inference, i.e., the application of a previously trained ConvNet, with emphasis on 3D images. Our goal is to maximize throughput, defined as the number of output voxels computed per unit time. We propose CPU and GPU primitives for convolutional and pooling layers, which are combined to create CPU, GPU, and CPU-GPU inference algorithms. The primitives include convolution based on highly efficient padded and pruned FFTs. Our theoretical analyses and empirical tests reveal a number of interesting findings. For example, adding host RAM can be a more efficient way of increasing throughput than adding another GPU or more CPUs. Furthermore, our CPU-GPU algorithm can achieve greater throughput than the sum of CPU-only and GPU-only throughputs.
Local Greedy Approximation for Scheduling in Multihop Wireless Networks

In recent years, there has been a significant amount of work done in developing low-complexity scheduling schemes to achieve high performance in multihop wireless networks. A centralized suboptimal scheduling policy, called Greedy Maximal Scheduling (GMS) is a good candidate because its empirically observed performance is close to optimal in a variety of network settings. However, its distributed realization requires high complexity, which becomes a major obstacle for practical implementation. In this paper, we develop simple distributed greedy algorithms for scheduling in multihop wireless networks. We reduce the complexity by relaxing the global ordering requirement of GMS, up to near zero. Simulation results show that the new algorithms approximate the performance of GMS, and outperform the state-of-the-art distributed scheduling policies.
Using Provenance for Personalized Quality Ranking of Scientific Datasets

The rapid growth of eScience has lead to an explosion in the creation and availability of scientific datasets that includes raw instrument data and derived datasets from model simulations. A large number of these datasets are surfacing online in public and private catalogs, often annotated with XML metadata, as part of community efforts to foster open research. With this rapid expansion comes the challenge of filtering and selecting datasets that best match the needs of scientists. We address a key aspect of the scientific data discovery process by ranking search results according to a personalized data quality score based on a declarative quality profile to help scientists select the most suitable data for their applications. Our quality model is resilient to missing metadata using a novel strategy that uses provenance in its absence. Intuitively, our premise is that the quality score for a dataset depends on its provenance – the scientific task and its inputs that created the dataset – and it is possible to define a quality function based on provenance metadata that predicts the same quality score as one evaluated using the user‟s quality profile over the complete metadata. Here, we present a model and architecture for data quality scoring, apply machine learning techniques to generate a quality function that uses provenance as proxy for missing metadata, and empirically test the prediction power of our quality function. Our results shown that for some scientific tasks, quality scores based on provenance closely track the quality scores based on complete metadata properties, with error margins between 1 – 29% .
Finite element analysis of rotating electrical machines — An educational approach

The paper presents the application of the Finite element method in teaching the fundamental theoretical aspects of rotating electrical machines to undergraduate students. The scope of the paper is to highlight the fundamental principles of electromagnetic field computation and analysis using two dimensional Finite element method. This is suitable for teaching students at undergraduate level, as the problem formulation is based on the direct integration of Maxwell's equations for firstorder elements, avoiding the use of a complex mathematical treatment. The preparation of a model of the machine and analysis of the obtained results are presented in a simplified manner in order to be more affordable to students. The throughout explanation is supported by various results, that students can directly obtain, observe and analyze, using Finite element analysis. The application of the Finite element method for modeling makes it possible to explain and discuss the behavior of rotating electrical machines for healthy and faulty conditions.
Gene signatures of pulmonary metastases of renal cell carcinoma reflect the disease‐free interval and the number of metastases per patient

Our understanding of metastatic spread is limited and molecular mechanisms causing particular characteristics of metastasis are largely unknown. Herein, transcriptome‐wide expression profiles of a unique cohort of 20 laser‐resected pulmonary metastases (Mets) of 18 patients with clear‐cell renal cell carcinoma (RCC) were analyzed to identify expression patterns associated with two important prognostic factors in RCC: the disease‐free interval (DFI) after nephrectomy and the number of Mets per patient. Differentially expressed genes were identified by comparing early (DFI ≤ 9 months) and late (DFI ≥ 5 years) Mets, and Mets derived from patients with few (≤8) and multiple (≥16) Mets. Early and late Mets could be separated by the expression of genes involved in metastasis‐associated processes, such as angiogenesis, cell migration and adhesion (e.g., PECAM1, KDR). Samples from patients with multiple Mets showed an elevated expression of genes associated with cell division and cell cycle (e.g., PBK, BIRC5, PTTG1) which indicates that a high number of Mets might result from an increased growth potential. Minimal sets of genes for the prediction of the DFI and the number of Mets per patient were identified. Microarray results were confirmed by quantitative PCR by including nine further pulmonary Mets of RCC. In summary, we showed that subgroups of Mets are distinguishable based on their expression profiles, which reflect the DFI and the number of Mets of a patient. To what extent the identified molecular factors contribute to the development of these characteristics of metastatic spread needs to be analyzed in further studies. © 2009 UICC
Foundations of Trust and Distrust in Networks: Extended Structural Balance Theory

Modeling trust in very large social networks is a hard problem due to the highly noisy nature of these networks that span trust relationships from many different contexts, based on judgments of reliability, dependability, and competence. Furthermore, relationships in these networks vary in their level of strength. In this article, we introduce a novel extension of structural balance theory as a foundational theory of trust and distrust in networks. Our theory preserves the distinctions between trust and distrust as suggested in the literature, but also incorporates the notion of relationship strength that can be expressed as either discrete categorical values, as pairwise comparisons, or as metric distances. Our model is novel, has sound social and psychological basis, and captures the classical balance theory as a special case. We then propose a convergence model, describing how an imbalanced network evolves towards new balance, and formulate the convergence problem of a social network as a Metric Multidimensional Scaling (MDS) optimization problem. Finally, we show how the convergence model can be used to predict edge signs in social networks and justify our theory through extensive experiments on real datasets.
Increased sexual desire with exogenous testosterone administration in men with obstructive sleep apnea: a randomized placebo‐controlled study

Testosterone (T) deficiency, sexual dysfunction, obesity and obstructive sleep apnea (OSA) are common and often coexist. T prescriptions have increased worldwide during the last decade, including to those with undiagnosed or untreated OSA. The effect of T administration on sexual function, neurocognitive performance and quality of life in these men is poorly defined. The aim of this study was to examine the impact of T administration on sexual function, quality of life and neurocognitive performance in obese men with OSA. We also secondarily examined whether baseline T might modify the effects of T treatment by dichotomizing on baseline T levels pre‐specified at 8, 11 and 13 nmol/L. This was a randomized placebo‐controlled study in which 67 obese men with OSA (mean age 49 ± 1.3 years) were randomized to receive intramuscular injections of either 1000 mg T undecanoate or placebo at baseline, week 6 and week 12. All participants were concurrently enrolled in a weight loss program. General and sleep‐related quality of life, neurocognitive performance and subjective sexual function were assessed before and 6, 12 and 18 weeks after therapy. T compared to placebo increased sexual desire (p = 0.004) in all men, irrespective of baseline T levels. There were no differences in erectile function, frequency of sexual attempts, orgasmic ability, general or sleep‐related quality of life or neurocognitive function (all p = NS). In those with baseline T levels below 8 nmol/L, T increased vitality (p = 0.004), and reduced reports of feeling down (p = 0.002) and nervousness (p = 0.03). Our findings show that 18 weeks of T therapy increased sexual desire in obese men with OSA independently of baseline T levels whereas improvements in quality of life were evident only in those with T levels below 8 nmol/L. These small improvements would need to be balanced against potentially more serious adverse effects of T therapy on breathing.
Impact of the structural integrity of the three-way junction of adenovirus VAI RNA on PKR inhibition

Highly structured RNA derived from viral genomes is a key cellular indicator of viral infection. In response, cells produce the interferon inducible RNA-dependent protein kinase (PKR) that, when bound to viral dsRNA, phosphorylates eukaryotic initiation factor 2α and attenuates viral protein translation. Adenovirus can evade this line of defence through transcription of a non-coding RNA, VAI, an inhibitor of PKR. VAI consists of three base-paired regions that meet at a three-way junction; an apical stem responsible for the interaction with PKR, a central stem required for inhibition, and a terminal stem. Recent studies have highlighted the potential importance of the tertiary structure of the three-way junction to PKR inhibition by enabling interaction between regions of the central and terminal stems. To further investigate the role of the three-way junction, we characterized the binding affinity and inhibitory potential of central stem mutants designed to introduce subtle alterations. These results were then correlated with small-angle X-ray scattering solution studies and computational tertiary structural models. Our results demonstrate that while mutations to the central stem have no observable effect on binding affinity to PKR, mutations that appear to disrupt the structure of the three-way junction prevent inhibition of PKR. Therefore, we propose that instead of simply sequestering PKR, a specific structural conformation of the PKR-VAI complex may be required for inhibition.
GENERALIZED REAL RENOVATION OPTIONS

This paper revisits Williams (1997) on the effect of net rental price, asset quality and variable investment costs on the asset redevelopment decision. This paper develops a quasi-analytical method for solving the generalised real renovation option problem by treating the investment cost as having both a variable and a fixed element and then extends the analysis for the case where both the net rental price and asset quality are stochastic. Analysis on the generalised renovation option shows in common with previous real options analyses on investment opportunities that the renovation decision is triggered when the incremental net rental value exceeds the investment cost by a mark-up factor exceeding unity. The solution to the variable cost investment function is derived from the generalised model as a special case. The quasi-analytical method reveals hitherto latent conditions constraining the scope of values the various parameters can take, and in particular that the net rental price volatility limits the range of the risk-free rate. This result holds also when both net rental price and asset quality are stochastic. The paper finishes by considering the effect of the generalised renovation option on the original option to invest. JEL Classifications: D81, G31
Thematic labeling of Twitter accounts using DBpedia properties

In this paper, we propose an iterative algorithm towards the automatic labeling of Twitter accounts in respect to thematic categories derived from DBpedia properties. We describe the rationale behind the selection of these thematic categories, and discuss their evaluation assessment. Finally, we propose and analyze two generic and adaptable methodologies for discovering the necessary linked data resources for further enhancing the thematic description of Twitter accounts.
Decision-Scaling: A Decision Framework for DoD Climate Risk Assessment and Adaptation Planning

Abstract : This research presents and demonstrates a framework for assessing climate change risks to DoD installations and the built environment. The approach, which we call decision-scaling, reveals the core sensitivity of DoD installations to climate change. It is designed to illuminate the sensitivity of installations and their supporting infrastructure systems, including water and energy, to climate changes and other uncertainties without dependence on climate change projections. In this way the analysis and results remain unclouded by the many choices and trade-offs required in the processing of projections from general circulation models (GCMs, also known as global climate models) and their associated uncertainties. The engine of analysis is the climate stress test which is an algorithm designed to stress the target system using systematic and exhaustive exploration of possible climate changes. Climate projections, including simulations from the NARCCAP are then used to inform the level of concern associated with each risk after the risks are identified via the climate stress test. The decision framework was applied to four sectors: water supply, energy costs, training and fire management and evaluated through piloting at four installations. The results show clear answers regarding the climate risks at each installation in each of these sectors, in terms that are quantifiably comparable across sectors. The expectation is the framework and assessment products are appropriate for application to all DoD installations and represent the very best approach for evaluating climate risks.
IL-1 stimulates ceramide accumulation without inducing apoptosis in intestinal epithelial cells.

BACKGROUND: In inflammatory bowel disease (IBD), cytokine levels (such as interleukin-1 (IL-1)) are elevated. We have shown previously that IL-1 activates phospholipid signaling pathways in intestinal epithelial cells (EEC), leading to increased ceramide levels. AIM: To determine whether ceramide induces apoptosis in IEC. METHODS: Apoptosis was evaluated by annexin-V binding or Hoechst nuclear staining. Levels of bcl-2, bcl-x, bax, p53 and p21 were determined by Western blotting, and celi cycle analysis was determined by flow cytometry. RESULTS: IL-1 increased ceramide accumulation in a time-dependent and concentration-dependent manner with a peak response at 4 h, with [IL-1] = 30 ng/ml. Neither IL-1 nor ceramide induced apoptosis in EEC, but they increased bcl-2 levels and decreased bax and p21 levels without affecting bcl-x and p53 levels. They also caused a slight but significant increase in the G2/M phase. These data suggest a role for ceramide in IBD and suggest a possible mechanism for the enhanced tumorigenic activity in IBD patients.
Silencing Threonine Deaminase and JAR4 in Nicotiana attenuata Impairs Jasmonic Acid–Isoleucine–Mediated Defenses against Manduca sexta[W]

Threonine deaminase (TD) catalyzes the conversion of Thr to α-keto butyrate in Ile biosynthesis; however, its dramatic upregulation in leaves after herbivore attack suggests a role in defense. In Nicotiana attenuata, strongly silenced TD transgenic plants were stunted, whereas mildly silenced TD transgenic plants had normal growth but were highly susceptible to Manduca sexta attack. The herbivore susceptibility was associated with the reduced levels of jasmonic acid–isoleucine (JA-Ile), trypsin proteinase inhibitors, and nicotine. Adding [13C4]Thr to wounds treated with oral secretions revealed that TD supplies Ile for JA-Ile synthesis. Applying Ile or JA-Ile to the wounds of TD-silenced plants restored herbivore resistance. Silencing JASMONATE-RESISTANT4 (JAR4), the N. attenuata homolog of the JA-Ile–conjugating enzyme JAR1, by virus-induced gene silencing confirmed that JA-Ile plays important roles in activating plant defenses. TD may also function in the insect gut as an antinutritive defense protein, decreasing the availability of Thr, because continuous supplementation of TD-silenced plants with large amounts (2 mmol) of Thr, but not Ile, increased M. sexta growth. However, the fact that the herbivore resistance of both TD- and JAR-silenced plants was completely restored by signal quantities (0.6 μmol) of JA-Ile treatment suggests that TD's defensive role can be attributed more to signaling than to antinutritive defense.
Fuzzy LPT Algorithms for Flexible Flow Shop Problems with Unrelated Parallel Machines for a Continuous Fuzzy Domain

A flexible flow shop problem can be considered as a generalization of a pure flow shop problem in which the jobs have to go through the stages in the same order. We consider a flexible flow shop problem with unrelated machines and setup times, where the processing times depend on the chosen machine and setup times are sequence-dependent. While for classical problems the processing times for each job are assumed to be known exactly, in many real-world situations processing times vary dynamically due to human factors or operating faults. In this paper, fuzzy concepts are used in an LPT algorithm for managing uncertain scheduling. Given a set of jobs together with a membership function for the standard processing times, the fuzzy LPT algorithms construct a solution by means of a membership function for the final makespan. The proposed algorithms provide a more flexible method of scheduling jobs than conventional scheduling methods. The results show that the fuzzy LPT algorithms give a deviation from the optimal makespan value of about five percent for the small-size test problems. In addition, the fuzzy LPT algorithm by using the average values of the total operating times at the last stage (denoted by FLPT) gives a good solution for both smalland large-test problems.