Miracle-dz/UniFAR-FTUs huggingface dataset:
Complexity results and practical algorithms for logics in knowledge representation

Description Logics (DLs) are used in knowledge-based systems to represent and reason about terminological knowledge of the application domain in a semantically well-defined manner. In this thesis, we establish a number of novel complexity results and give practical algorithms for expressive DLs that provide different forms of counting quantifiers. We show that, in many cases, adding local counting in the form of qualifying number restrictions to DLs does not increase the complexity of the inference problems, even if binary coding of numbers in the input is assumed. On the other hand, we show that adding different forms of global counting restrictions to a logic may increase the complexity of the inference problems dramatically. We provide exact complexity results and a practical, tableau based algorithm for the DL SHIQ, which forms the basis of the highly optimized DL system iFaCT. Finally, we describe a tableau algorithm for the clique guarded fragment (CGF), which we hope will serve as the basis for an efficient implementation of a CGF reasoner.
Benchmark of Damage Localisation Algorithms Using Mode Shape Data

This paper presents a comparative study of three enhanced signal processing methods to locate damage on mode shape data. The first method called curvature mode shape is used as a reference. The second tool uses wavelet transform and singularity detection theory to locate damage. Finally we introduce the windowed fractal dimension of a signal as a tool to easily measure the local complexity of a signal. Our benchmark aims at comparing the crack detection using optimal spatial sampling under different severity, beam boundary conditions (BCs) and added noise measurements.
Trinocular: understanding internet reliability through adaptive probing

Natural and human factors cause Internet outages---from big events like Hurricane Sandy in 2012 and the Egyptian Internet shutdown in Jan. 2011 to small outages every day that go unpublicized. We describe Trinocular, an outage detection system that uses active probing to understand reliability of edge networks. Trinocular is principled: deriving a simple model of the Internet that captures the information pertinent to outages, and populating that model through long-term data, and learning current network state through ICMP probes. It is parsimonious, using Bayesian inference to determine how many probes are needed. On average, each Trinocular instance sends fewer than 20 probes per hour to each /24 network block under study, increasing Internet "background radiation" by less than 0.7%. Trinocular is also predictable and precise: we provide known precision in outage timing and duration. Probing in rounds of 11 minutes, we detect 100% of outages one round or longer, and estimate outage duration within one-half round. Since we require little traffic, a single machine can track 3.4M /24 IPv4 blocks, all of the Internet currently suitable for analysis. We show that our approach is significantly more accurate than the best current methods, with about one-third fewer false conclusions, and about 30% greater coverage at constant accuracy. We validate our approach using controlled experiments, use Trinocular to analyze two days of Internet outages observed from three sites, and re-analyze three years of existing data to develop trends for the Internet.
Structural and mechanistic insights into MICU1 regulation of mitochondrial calcium uptake

Mitochondrial calcium uptake is a critical event in various cellular activities. Two recently identified proteins, the mitochondrial Ca2+ uniporter (MCU), which is the pore‐forming subunit of a Ca2+ channel, and mitochondrial calcium uptake 1 (MICU1), which is the regulator of MCU, are essential in this event. However, the molecular mechanism by which MICU1 regulates MCU remains elusive. In this study, we report the crystal structures of Ca2+‐free and Ca2+‐bound human MICU1. Our studies reveal that Ca2+‐free MICU1 forms a hexamer that binds and inhibits MCU. Upon Ca2+ binding, MICU1 undergoes large conformational changes, resulting in the formation of multiple oligomers to activate MCU. Furthermore, we demonstrate that the affinity of MICU1 for Ca2+ is approximately 15–20 μM. Collectively, our results provide valuable details to decipher the molecular mechanism of MICU1 regulation of mitochondrial calcium uptake.
Assessing the impact of adherence to anti-retroviral therapy on treatment failure and resistance evolution in HIV

The adherence of patients to therapy is a crucial factor for successful HIV anti-retroviral therapy. Imperfect adherence may lead to treatment failure, which can cause the emergence of resistance within viral populations. We have developed a stochastic model that incorporates compartments of latently infected cells and virus genotypes with different susceptibilities to three simultaneously used drugs. With this model, we study the impact of several key parameters on the probability of treatment failure, i.e. insufficient viral suppression, and the emergence of resistance. Specifically, we consider the impact of drug dosage, drug half-lives, fitness costs for resistance, different basic reproductive numbers of the virus and the influence of pre-existing mutations under various levels of adherence. Furthermore, we also investigate the influence of different temporal distributions of non-adherent days (drug holidays) during a treatment. Factors that promote resistance evolution include a high reproductive number, extended drug holidays and poor adherence. Pre-existing mutations only have a substantial effect if they confer resistance against more than one drug. Overall, our study highlights the importance of the interactions between imperfect adherence, pharmacodynamics, pharmacokinetics and latently infected cells for our understanding of drug resistance and therapy failure in HIV anti-retroviral therapy.
Investigation into the Feasibility of Highly Enriched Uranium Detection by External Neutron Stimulation (Expanded Study)

Abstract : This report studied the detectability of 1kg of HEU in a cargo container, whose dimensions are 20'x8'x8', by stimulating the HEU with neutron source located external to the container and counting the neutrons that would be produced with a high sensitivity thermal neutron detector. This project examined a wide variety of different energy sources, counting options, and the effect of different cargo materials present within the container. The study considered solution approaches using both deterministic and Monte Carlo techniques. The major project conclusion is that this approach would be successful in all common environments except one, if a pulsed 14MeV neutron source with a strength of 10E12 neutrons/sec was used and the delayed fission neutron are counted between pulses. The study also developed different facility designs, which included a shielding analysis, container activation and storage requirements, and overall concept economic feasibility using the Port of Baltimore as a benchmark.
Securing Dataverse with an Adapted Command Design Pattern

In order to bake security into application design, we introduce an adaptation to the Command pattern: command instances are tagged with the permissions required to perform them for each object they manipulate. Prior to executing a command instance issued by a given user, an execution engine validates the user has the required permissions over the objects the command is about to operate on. Stating the required permissions can often be declarative. In addition to the usual advantages offered by the command pattern (such as standardized operation handling), this adaptation creates a single checkpoint for validating permissions throughout the application. This, in turn, enhances application security and reduces code duplication, for example between the API and UI controllers. Disadvantages include the lack of framework support, and a learning curve for existing developers. We have used this design in implementing Dataverse, a widely-used institutional data repository developed at Harvard University, which has been in production use since May 2015. As this design differs significantly from common web application design, we also look at how the development team adapted to it, and at how using it affected our development process.
A novel speech enhancement approach based on Singular Value Decomposition and Genetic Algorithm

The Singular Value Decomposition (SVD) is a powerful tool used for subspace division. In this paper a novel approach for speech signal enhancement is presented which is based on SVD and Genetic Algorithm (GA). The method is derived from the effects of environmental noises on the singular vectors as well as the singular values of a clean speech. This article reviews the existing approaches for subspace estimation and proposes novel techniques for effectively enhancing the singular values and vectors of a noisy speech. The proposed approach clearly results in a considerable attenuation of the noise as well as retrieving the quality of the original speech. The efficiency of our proposed method is affected by a number of crucial parameters which are optimally set by utilizing the GA. Extensive sets of experiments have been carried out for both of additive white Gaussian noise as well as different types of realistic colored noise cases. The results of applying six superior speech enhancement methods are then evaluated by the objective (SNR) and subjective (PESQ) measures.
Oral Community Interactions of Filifactor alocis In Vitro

Filifactor alocis is a gram positive anaerobe that is emerging as an important periodontal pathogen. In the oral cavity F. alocis colonizes polymicrobial biofilm communities; however, little is known regarding the nature of the interactions between F. alocis and other oral biofilm bacteria. Here we investigate the community interactions of two strains of F. alocis with Streptococcus gordonii, Fusobacterium nucleatum, Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans, organisms with differing pathogenic potential in the oral cavity. In an in vitro community development model, S. gordonii was antagonistic to the accumulation of F. alocis into a dual species community. In contrast, F. nucleatum and the type strain of F. alocis formed a synergistic partnership. Accumulation of a low passage isolate of F. alocis was also enhanced by F. nucleatum. In three species communities of S. gordonii, F. nucleatum and F. alocis, the antagonistic effects of S. gordonii superseded the synergistic effects of F. nucleatum toward F. alocis. The interaction between A. actinomycetemcomitans and F. alocis was strain specific and A. actinomycetemcomitans could either stimulate F. alocis accumulation or have no effect depending on the strain. P. gingivalis and F. alocis formed heterotypic communities with the amount of P. gingivalis greater than in the absence of F. alocis. However, while P. gingivalis benefited from the relationship, levels of F. alocis in the dual species community were lower compared to F. alocis alone. The inhibitory effect of P. gingivalis toward F. alocis was dependent, at least partially, on the presence of the Mfa1 fimbrial subunit. In addition, AI-2 production by P. gingivalis helped maintain levels of F. alocis. Collectively, these results show that the pattern of F. alocis colonization will be dictated by the spatial composition of microbial microenvironments, and that the organism may preferentially accumulate at sites rich in F. nucleatum.
Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network

This paper introduces an event-driven feedforward categorization system, which takes data from a temporal contrast address event representation (AER) sensor. The proposed system extracts bio-inspired cortex-like features and discriminates different patterns using an AER based tempotron classifier (a network of leaky integrate-and-fire spiking neurons). One of the system's most appealing characteristics is its event-driven processing, with both input and features taking the form of address events (spikes). The system was evaluated on an AER posture dataset and compared with two recently developed bio-inspired models. Experimental results have shown that it consumes much less simulation time while still maintaining comparable performance. In addition, experiments on the Mixed National Institute of Standards and Technology (MNIST) image dataset have demonstrated that the proposed system can work not only on raw AER data but also on images (with a preprocessing step to convert images into AER events) and that it can maintain competitive accuracy even when noise is added. The system was further evaluated on the MNIST dynamic vision sensor dataset (in which data is recorded using an AER dynamic vision sensor), with testing accuracy of 88.14%.
Further analysis of latent affective mapping for naturally expressive speech synthesis

An essential step in the generation of expressive speech synthesis is the automatic detection and classification of emotions most likely to be present in textual input. At last Interspeech, we introduced latent affective mapping, a new emotion analysis approach which leverages two separate levels of semantic information: one that encapsulates the foundations of the domain considered, and one that specifically accounts for the overall affective fabric of the language [1]–[2]. The ensuing framework exposes the emergent relationship between these two levels in order to advantageously inform the emotion classification process. This paper presents further validation of latent affective mapping, as well as a detailed analysis of its behavior given the attendant richer emotional description. The various mapping instantiations supported compare favorably with more conventional techniques based on expert knowledge. In particular, representative case studies point to a better approximation of the true probability distribution across the range of standard emotions.
TEMPERATURE AND STRAIN CONTROLLED OPTIMIZATION OF STABILIZATION OF POLYACRYLONITRILE PRECURSOR FIBERS

OF THESIS TEMPERATURE AND STRAIN CONTROLLED OPTIMIZATION OF STABILIZATION OF POLYACRYLONITRILE PRECURSOR FIBERS Carbon fiber is one of the leading materials for high strength and modulus, and light weight applications. Improvements in carbon fiber properties are directly dependent on all aspects of manufacture, especially the process of stabilization. Therefore, it is the goal of this thesis to study the effects of the temperature and strain profile of the stabilization process, and the resulting carbon fiber tensile properties. In addition, the precursor fibers used were spun under two different draw ratios, to study the effects of the spinning parameters. Results indicated through DMA studies that completeness of stabilization reactions can be gauged by the peak and leveling of induced stress while fibers are stabilized in isostrain conditions. Through this method, carbon fiber tensile properties were maintained from the prior methods, but saved significant time for processing. Stress vs. strain tests throughout the stabilization process created a baseline for understanding the maximum capable strain on fibers throughout the stabilization process. Lastly, this information was summarized, combined, and basic mechanical engineering principles discussed for a continuous stabilization furnace with strain control, so that further research into the stabilization process can incorporate carbon fibers made with in situ stretch control.
The design of a smartphone-based fall detection system

The eldercare problem becomes important due to population ageing. A fall accident may cause serious injury to the elderly. How to automatically detect a fall and quickly launch a help message becomes crucial, particularly for those elders living alone. The smartphone that is frequently carried by a person has the potential to be a natural tool to provide this fall detection service. In this paper, a string matching based algorithm is applied to recognize all possible fall events from the acceleration values sensed by the smartphone. A corresponding application is also implemented on the android-based platform.
Expression of Regulatory T Cells in Jejunum, Colon, and Cervical and Mesenteric Lymph Nodes of Dogs Naturally Infected with Leishmania infantum

ABSTRACT Using flow cytometry, we evaluated the frequencies of CD4+ and CD8+ T cells and Foxp3+ regulatory T cells (Tregs) in mononuclear cells in the jejunum, colon, and cervical and mesenteric lymph nodes of dogs naturally infected with Leishmania infantum and in uninfected controls. All infected dogs showed chronic lymphadenitis and enteritis. Despite persistent parasite loads, no erosion or ulcers were evident in the epithelial mucosa. The colon harbored more parasites than the jejunum. Frequencies of total CD4+, total Foxp3, and CD4+ Foxp3+ cells were higher in the jejunum than in the colon. Despite negative enzyme-linked immunosorbent assay (ELISA) serum results for cytokines, levels of interleukin-10 (IL-10), gamma interferon (IFN-γ), transforming growth factor beta (TGF-β), and tumor necrosis factor alpha (TNF-α) were higher in the jejunum than in the colon for infected dogs. However, IL-4 levels were higher in the colon than in the jejunum for infected dogs. There was no observed correlation between clinical signs and histopathological changes or immunological and parasitological findings in the gastrointestinal tract (GIT) of canines with visceral leishmaniasis. However, distinct segments of the GIT presented different immunological and parasitological responses. The jejunum showed a lower parasite load, with increased frequencies and expression of CD4, Foxp3, and CD8 receptors and IL-10, TGF-β, IFN-γ, and TNF-α cytokines. The colon showed a higher parasite load, with increasing expression of IL-4. Leishmania infantum infection increased expression of CD4, Foxp3, IL-10, TGF-β, IFN-γ, and TNF-α and reduced CD8 and IL-4 expression in both the jejunum and the colon.
Seismic Reflection Tomography: A Case Study of a Shallow Lake Survey in Lake Balaton

Shallow seismic reflection marine profiles were collected in the area of Balaton Lake in Hungary using high frequency boomer techniques, in order to get information about the stratigraphy of the sedimentary layers. The noise in these shallow marine seismic reflection data is analyzed, and a series of traditional seismic data processing techniques is applied to improve the S/N ratio and coherence. These are bandpass filtering, muting, spectrum analysis, gain, deconvolution and migration. The single fold of the survey did not allow velocity analysis to be done. Navigation control was derived from global positioning system. The shipboard GPS antenna positions were recorded for each shot at the time of trigger. In addition, the geometry and the geophysical characteristics of the sediments are reconstructed by calculating the forward and inverse model. The inverse problem is solved by using the LSQR algorithm. In order to speed up convergence and stabilize the inversion several approaches are adopted, such as "damping" or "smoothing".
UTILIZATION OF SIDOARJO MUD AS THE RAW MATERIAL OF MAKKING PORTLAND CEMENT

Portland cement is generally made of clay, lime, iron sand, silica sand and alumina sand, In this research, the manufacture of cement by using the material in the form of Sidoarjo mud because it has a clay content that resembles that of 2,34% CaO, 6,52% Al2O3, SiO2 Fe2O3 67,63% and 4,88%, making it possible to make an manufacture of Portland cement with addition of CaO and through the combustion process, Research done by mixing mud in Sidoarjo in chalk in some variation ratio of 40:60; 37,5:62,5; 35:65; 32,5:67,5 and 30:70, After a homogeneous mixture and then baked in the furnace at a temperature variation 1200o C with the time allowed is 60, 90, 120, 150 and 180 minutes, Cement is then the compressive strength test and analyzed levels of the chemical, Retrieved best conditions on a comparison between proportion of Sidoarjo mud and lime 30:70, 3 hours burning time and compressive strength value of 13,00 kg / cm2 for ages 3 days and 15,08 kg / cm2 to age 7 days,
SVM-based sketch recognition: which hyperparameter interval to try?

Hyperparameters are among the most crucial factors that affect the performance of machine learning algorithms. In general, there is no direct method for determining a set of satisfactory parameters, so hyperparameter search needs to be conducted each time a model is to be trained. In this work, we analyze how similar hyperparameters perform across various datasets from the sketch recognition domain. Results show that hyperparameter search space can be reduced to a subspace despite differences in characteristics of datasets.
THE SATURATION CONJECTURE (AFTER A. KNUTSON

The purpose of this exposition 1 is to give a simple and complete treatment of Knutson and Tao's recent proof of the saturation conjecture [8]. If λ is a partition of length at most n, let V λ denote the corresponding highest weight representation of GL n (C). Define This set is important in numerous areas besides representation theory. In Schubert calculus it describes when an intersection of Schubert cells must be non-empty. In combinatorics, a triple is in T n if and only if there exists a Littlewood-Richardson skew tableau with shape ν/λ and content µ. It is well known that T n ⊂ Z 3n is a semi-group under addition, a fact which Zelevinsky attributes to Brion and Knop [10]. Klyachko has given [7] a nice description of the saturation A triple (λ, µ, ν) is in ¯ T n if and only if the entries of λ, µ, and ν satisfy certain inequalities that come from Schubert calculus (see also [5]). This made the following conjecture particularly important. In other words T n is saturated in Z 3n. Note that the implication ⇒ is a trivial consequence of the fact that T n is a semi-group or of the original Littlewood-Richardson rule. In July 1998, Knutson and Tao gave a proof of this conjecture, using two wonderful new descriptions of Berenstein-Zelevinsky polytopes called the honeycomb and hive models [8]. The goal of this exposition is to present a simple and complete proof based only on the hive model. Since the final version of Knutson and Tao's paper will likely be based on honeycombs alone, we hope that this may be useful. Most constructions used here come directly from the first version of Knutson and Tao's preprint, even if they may be replaced by honeycomb equivalents in their published paper. One innovation, in Section 3, is the construction of a graph from a hive, which is used to simplify their argument. In an appendix of Fulton it is shown that the hive model is equivalent to the original Littlewood-Richardson rule.
Synthesis of Safety Rules for Active Monitoring: Application to an Airport Light Measurement Robot

Safety-critical autonomous systems, like robots working in collaboration with humans, are about to be used in diverse environments such as industry but also public spaces or hospitals. Those systems evolve in complex and dynamic environments and are exposed to a wide variety of hazards. Several techniques may be used to ensure that their misbehavior cannot cause unacceptable damage or harm. One of them is active safety monitoring. A safety monitor is a component responsible for maintaining the system in a safe state despite the occurrence of hazardous situations. In this paper, we study the introduction of safety monitoring into an airport light measurement robot. The specification of the monitor follows a principled approach that starts with a hazard analysis and ends with a set of safety rules synthesized based on formal methods. This study illustrates the benefits of the approach, and shows the impact of safety on the development of an autonomous system.