Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing the fault tolerance capabilities of distributed real-time systems

Industrial real-time systems typically have to satisfy complex requirements, mapped to the task attributes, eventually guaranteed by a fixed priority scheduler in a distributed environment. These systems consist of a mix of hard and soft tasks with varying criticality, as well as associated fault tolerance requirements. Time redundancy techniques are often preferred in industrial applications and, hence, it is extremely important to devise resource efficient methodologies for scheduling real-time tasks under failure assumptions. In this paper, we propose a methodology to provide a priori guarantees in distributed real-time systems with redundancy requirements. We do so by identifying temporal feasibility windows for all task executions and reexecutions, as well as allocating them on different processing nodes. We then use optimization theory to derive the optimal feasibility windows that maximize the utilization on each node, while avoiding overloads. Finally on each node, we use Integer Linear Programming (ILP) to derive fixed priority task attributes that guarantee the task executions within the derived feasibility windows, while keeping the associated costs minimized.
Smooth Formation Navigation of Multiple Mobile Robots for Avoiding Moving Obstacles

This paper addresses a formation navigation issue for a group of mobile robots passing through an environment with either static or moving obstacles meanwhile keeping a fixed formation shape. Based on Lyapunov function and graph theory, a NN formation control is proposed, which guarantees to maintain a formation if the formation pattern is , k C 1. k ≥ In the process of navigation, the leader can generate a proper trajectory to lead formation and avoid moving obstacles according to the obtained information. An evolutionary computational technique using particle swarm optimization (PSO) is proposed for motion planning so that the formation is kept as 1 C function. The simulation results demonstrate that this algorithm is effective and the experimental studies validate the formation ability of the multiple mobile robots system.
Phylogeny of Morella rubra and Its Relatives (Myricaceae) and Genetic Resources of Chinese Bayberry Using RAD Sequencing

Phylogenetic relationships among Chinese species of Morella (Myricaceae) are unresolved. Here, we use restriction site-associated DNA sequencing (RAD-seq) to identify candidate loci that will help in determining phylogenetic relationships among Morella rubra, M. adenophora, M. nana and M. esculenta. Three methods for inferring phylogeny, maximum parsimony (MP), maximum likelihood (ML) and Bayesian concordance, were applied to data sets including as many as 4253 RAD loci with 8360 parsimony informative variable sites. All three methods significantly favored the topology of (((M. rubra, M. adenophora), M. nana), M. esculenta). Two species from North America (M. cerifera and M. pensylvanica) were placed as sister to the four Chinese species. According to BEAST analysis, we deduced speciation of M. rubra to be at about the Miocene-Pliocene boundary (5.28 Ma). Intraspecific divergence in M. rubra occurred in the late Pliocene (3.39 Ma). From pooled data, we assembled 29378, 21902 and 23552 de novo contigs with an average length of 229, 234 and 234 bp for M. rubra, M. nana and M. esculenta respectively. The contigs were used to investigate functional classification of RAD tags in a BLASTX search. Additionally, we identified 3808 unlinked SNP sites across the four populations of M. rubra and discovered genes associated with fruit ripening and senescence, fruit quality and disease/defense metabolism based on KEGG database.
Clostridial Glucosylating Toxins Enter Cells via Clathrin-Mediated Endocytosis

Clostridium difficile toxin A (TcdA) and toxin B (TcdB), C. sordellii lethal toxin (TcsL) and C. novyi α-toxin (TcnA) are important pathogenicity factors, which represent the family of the clostridial glucosylating toxins (CGTs). Toxin A and B are associated with antibiotic-associated diarrhea and pseudomembraneous colitis. Lethal toxin is involved in toxic shock syndrome after abortion and α-toxin in gas gangrene development. CGTs enter cells via receptor-mediated endocytosis and require an acidified endosome for translocation of the catalytic domain into the cytosol. Here we studied the endocytic processes that mediate cell internalization of the CGTs. Intoxication of cells was monitored by analyzing cell morphology, status of Rac glucosylation in cell lysates and transepithelial resistance of cell monolayers. We found that the intoxication of cultured cells by CGTs was strongly delayed when cells were preincubated with dynasore, a cell-permeable inhibitor of dynamin, or chlorpromazine, an inhibitor of the clathrin-dependent endocytic pathway. Additional evidence about the role of clathrin in the uptake of the prototypical CGT family member toxin B was achieved by expression of a dominant-negative inhibitor of the clathrin-mediated endocytosis (Eps15 DN) or by siRNA against the clathrin heavy chain. Accordingly, cells that expressed dominant-negative caveolin-1 were not protected from toxin B-induced cell rounding. In addition, lipid rafts impairment by exogenous depletion of sphingomyelin did not decelerate intoxication of HeLa cells by CGTs. Taken together, our data indicate that the endocytic uptake of the CGTs involves a dynamin-dependent process that is mainly governed by clathrin.
Lactobacillus fermentum Postbiotic-induced Autophagy as Potential Approach for Treatment of Acetaminophen Hepatotoxicity

The aim of this study was to investigate the potential of postbiotics originated from Lactobacillus fermentum BGHV110 strain (HV110) to counteract acetaminophen (APAP)-induced hepatotoxicity in HepG2 cells. This strain was selected according to its autophagy inducing potential, based on previous studies reporting protective role of autophagy in APAP caused cellular damage. Cell viability was assessed using MTT and LDH assays, while autophagy was monitored by qPCR analysis of BECN1, Atg5, p62/SQSTM1, and PINK1 mRNA expression and by Western blot analysis of p62/SQSTM1 and lipidated LC3 accumulation. Our results showed that detrimental effect of APAP on cell viability was suppressed in the presence of HV110 which was linked with increased conversion of LC3 protein and p62/SQSTM1 protein degradation. Additionally, higher p62/SQSTM1 and PINK1 mRNA transcription were noticed in cells co-treated with APAP/HV110, simultaneously. In conclusion, this study suggests that HV110 enhances activation of PINK1-dependent autophagy in HepG2 cells and its eventual co-supplementation with APAP could be potentially used for alleviation of hepatotoxic side effects caused by APAP overdose.
Behavior of the partial correlation coefficients of a least squares lattice filter in the presence of a nonstationary chirp input

This paper studies the performance of the a posteriori recursive least squares lattice filter in the presence of a nonstationary chirp signal. The forward and backward partial correlation (PARCOR) coefficients for a Wiener-Hopf optimal filter are shown to be complex conjugates for the general case of a nonstationary input with constant power. Such an optimal filter is compared to a minimum mean square error based least squares lattice adaptive filter. Expressions are found for the behavior of the first stage of the adaptive filter based on the least squares algorithm. For the general nth stage, the PARCOR coefficients of the previous stages are assumed to have attained Wiener-Hopf optimal steady state. The PARCOR coefficients of such a least squares adaptive filter are compared with the optimal coefficients for such a nonstationary input. The optimal lattice fitter is seen to track a chirp input without any error, and the tracking lag in such an adaptive filter is due to the least squares update procedure. The expression for the least squares based PARCOR coefficients are found to contain two terms: a decaying convergence term due to the weighted estimation procedure and a tracking component that asymptotically approaches the optimal coefficient value. The rate of convergence is seen to depend inversely on the forgetting factor. The tracking lag of the filter is derived as a function of the rate of nonstationarity and the forgetting factor. It is shown that for a given chirp rate there is a threshold adaptation constant below which the total tracking error is negligible. For forgetting factors above this threshold, the error increases nonlinearly. Further, this threshold forgetting factor decreases with increasing chirp rate. Simulations are presented to validate the analysis. >
Sustainability : ethical foundations and economic properties

The author interprets development to be sustainable if it involves a nondecreasing quality of life. He introduces a concept of justice, and shows that a development path must be sustainable to prevent injustice. He argues, and illustrates through growth models, that altruism alone does not - even in the context of an economically efficient market economy - ensure sustainability. In particular, technologies with complementarity between manmade and natural capital represent cases where sustainability need not result. Thus, policies aimed at economic efficiency, such as internalizing external effects, need not generate sustainable development. The author argues that a positive interest rate is not inconsistent with sustainable development. He also maintains that, even in a perfect market economy, prices may not convey whether investments in manmade capital are sufficient to compensate for the depletion of natural capital. In particular, a non-negative market value of net investment is not sufficient for the present quality of life to be sustainable. Finally, he emphasizes that public policy aimed at sustainable development should strengthen the mechanisms for redistribution from the present to the future.
Symbolic regression, parsimony, and some theoretical considerations about GP search space

Universal Consistency, the convergence to the minimum possible er- ror rate in learning through genetic programming (GP), and Code bloat, the ex- cessive increase of code size, are important issues in GP. This paper proposes a theoretical analysis of universal consistency and code bloat in the fr amework of symbolic regression in GP, from the viewpoint of Statistical Learning The- ory, a well grounded mathematical toolbox for Machine Learning. Two kinds of bloat must be distinguished in that context, depending whether the target f unction has finite description length or not. Then, the Vapnik-Chervonenkis dimen sion of programs is computed, and we prove that a parsimonious fitness ensur es Uni- versal Consistency (i.e. the fact that the solution minimizing the empirical e rror does converge to the best possible error when the number of examples goes to infinity). However, it is proved that the standard method consisting in choo sing a maximal program size depending on the number of examples might still re- sult in programs of infinitely increasing size with their accuracy; a fitness b iased by parsimony pressure is proposed. This fitness avoids unnecessar y bloat while nevertheless preserving the Universal Consistency.
A Task-based Evaluation of French Morphological Resources and Tools

OSEOMorphology is a key component for many Language Technology applications. However, morphological relations, especially those relying on the derivation and compounding processes, are often addressed in a superficial manner. In this article, we focus on assessing the relevance of deep and motivated morphological knowledge in Natural Language Processing applications. We first describe an annotation experiment whose goal is to evaluate the role of morphology for one task, namely Question Answering (QA). We then highlight the kind of linguistic knowledge that is necessary for this particular task and propose a qualitative analysis of morphological phenomena in order to identify the morphological processes that are most relevant. Based on this study, we perform an intrinsic evaluation of existing tools and resources for French morphology, in order to quantify their coverage. Our conclusions provide helpful insights for using and building appropriate morphological resources and tools that could have a significant impact on the application performance.
Emergence of Recombinant Forms of HIV: Dynamics and Scaling

The ability to accelerate the accumulation of favorable combinations of mutations renders recombination a potent force underlying the emergence of forms of HIV that escape multi-drug therapy and specific host immune responses. We present a mathematical model that describes the dynamics of the emergence of recombinant forms of HIV following infection with diverse viral genomes. Mimicking recent in vitro experiments, we consider target cells simultaneously exposed to two distinct, homozygous viral populations and construct dynamical equations that predict the time evolution of populations of uninfected, singly infected, and doubly infected cells, and homozygous, heterozygous, and recombinant viruses. Model predictions capture several recent experimental observations quantitatively and provide insights into the role of recombination in HIV dynamics. From analyses of data from single-round infection experiments with our description of the probability with which recombination accumulates distinct mutations present on the two genomic strands in a virion, we estimate that ∼8 recombinational strand transfer events occur on average (95% confidence interval: 6–10) during reverse transcription of HIV in T cells. Model predictions of virus and cell dynamics describe the time evolution and the relative prevalence of various infected cell subpopulations following the onset of infection observed experimentally. Remarkably, model predictions are in quantitative agreement with the experimental scaling relationship that the percentage of cells infected with recombinant genomes is proportional to the percentage of cells coinfected with the two genomes employed at the onset of infection. Our model thus presents an accurate description of the influence of recombination on HIV dynamics in vitro. When distinctions between different viral genomes are ignored, our model reduces to the standard model of viral dynamics, which successfully predicts viral load changes in HIV patients undergoing therapy. Our model may thus serve as a useful framework to predict the emergence of multi-drug-resistant forms of HIV in infected individuals.
The Pragmatic Web: Preliminary Thoughts

The core mission of the semantic web, namely, to enable information to be shared across the web, faces significant challenges. The challenges come from the difficulty of capturing semantics in a manner that is reusable across applications, the priority of process over data, the importance of interaction, and the critical need for accommodating user context. Overcoming these challenges takes us from the realm of semantics and brings us into the realm of pragmatics, which we view as supervenient upon the semantics. We claim that when the vision of the semantic web is realized, it will be via the pragmatic web. The ideas described herein have been in development for a few years. Most recently, this work was supported by the National Science Foundation under grant ITR-0081742 and by awards from IBM and Cisco. I have benefited from discussions with several colleagues and students, especially including Mike Huhns, Mladen Vouk, Bin Yu, Zhengang Cheng, Ashok Mallya, Mike Maximilien, Raghu Sreenath, and Pinar Yolum. Only I am responsible for the opinions expressed, of course.
Least squares frequency invariant beamforming robust against microphone mismatches

The frequency invariant beamforming for microphone arrays is of great interest in practice for distortionless acoustic signal acquisition. Several design approaches for frequency invariant beamformers (FIBs) have been proposed in the literature. However, most of these approaches assume the ideal microphone characteristics, whose performance deteriorates greatly in the presence of microphone mismatches. To deal with this problem, a robust FIB design approach using least squares criterion is proposed in this paper, which takes the microphone statistical characteristics into consideration. Design examples are shown to demonstrate the effectiveness of the proposed design approach.
A Reasonable Benchmarking Frontier Using DEA : An Incentive Scheme for Managers

This paper constructs on principal-agent theory and its extensions to production theory to propose an incentive system for the agent. The incentive scheme suggested here rewards the agent (hospital manager) on the basis of the distance that separates observed output, the result of past decisions, and the potential output that would maximise principal’s welfare (health authority). But setting up such a scheme is challenging, since we have to estimate potential output and to do this we need to know the production function faced by each hospital, something we ignore. To overcome this difficulty we resort to Data Envelopment Analysis (DEA). This way of using DEA identifies a frontier that sets first-best effort levels; i.e., the level of effort attributed to those hospitals that are successful at delivering the greatest level of outputs for a given consumption of resources. A very delicate issue in this context is the selection of the hospitals that define the frontier. If the frontier contains hospitals whose performance cannot be matched (i.e., outliers), efficiency targets will be distorted for the remaining hospitals, and this may create disincentives rather than incentives. We propose an iterative procedure which allows us to identify a “reasonable frontier” that should set the objectives to be met by agents. The empirical part of the paper is based on data from Spanish public hospitals. From a theoretically point of view, this paper addresses the problem of performance assessment and incentives management in delegated decision making. From an applied point of view, our paper contributes to understand how opportunistic agents will strategically respond to productivity studies, and to know how desired responses can be motivated most efficiently.
Algorithms for minimum-violation planning with formal specifications

We consider the problem of control strategy synthesis for robots given a set of complex mission specifications, such as “eventually visit region A and then return to a base”, “periodically survery regions A and B” or “do not enter region D”. We focus on problem instances where there does not exist a strategy that satisfies all the specifications, and we aim to find strategies that satisfy the most important specifications albeit violating the least important ones. We focus on two particular problem formulations, both of which take as input the mission specifications in the form of Linear Temporal Logic (LTL) formulae. In our first formulation we model the robot as a discrete transition system and each of the specifications has a reward associated with its satisfaction. We propose an algorithm for finding the strategy of maximum cumulative reward which has a significantly better computational complexity than that of a brute-force approach. In our second formulation we model the robot as a continuous dynamical system and the specifications are associated with priorities in such a way that a specification with priority i is infinitely more important than one with priority level j, for any i < j. For this purpose, we introduce a functional that quantifies the level of violation of a motion plan and we design an algorithm for asymptotically computing the control strategy of minimum level of violation among all strategies that guide the robot from an initial state to a goal set. For each of our two formulations we demonstrate the usefulness of our algorithms in possible applications through simulations, and in the case of our second formulation we also carry experiments on a real-time autonomous test-bed. This is joint work with Jana Tumova, Pratik Chaudhari and Sertac Karaman. Thesis Supervisor: Emilio Frazzoli Title: Professor of Aeronautics and Astronautics
Applying Hadoop's MapReduce framework on clustering the GPS signals through cloud computing

Year by year, we are considerably witnessing a dramatic increase in the size of data gathered from machines or human interactions. Typically, the data generated by machines is massive, complex and comes from different varieties including sensors collecting climate information, posts being shared in social media sites, videos being posted online, digital pictures, transaction records of online purchases, cell phone GPS signals and so on. Not surprisingly, the amount of data generated by machines is greater than the data generated by human elements. Sensor data (obtained from transportation, logistics, retail, utilities, and telecommunications) has continuously been generated from fleet GPS trans-receivers, RFID tag readers; smart meters, to cell phones. Such data has frequently been used in numerous parallel processing methods so as to optimize operations and drive operational business intelligence (BI) systems scrutinizing immediate business opportunities. Appropriately, MapReduce is a programming model designed for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. In this paper, we enhanced the Hadoop MapReduce for data-intensive computing on massive datasets of GPS signals. We developed an execution framework for large-scale data processing through the cloud system - in order to reduce the execution time of the cluster systems - as well.
Conditional Deletion of Cytochrome P450 Reductase in Osteoprogenitor Cells Affects Long Bone and Skull Development in Mice Recapitulating Antley-Bixler Syndrome: Role of a Redox Enzyme in Development

NADPH-cytochrome P450 oxidoreductase (POR) is the primary electron donor for cytochromes P450, dehydrocholesterol reductase, heme oxygenase, and squalene monooxygenase. Human patients with specific mutations in POR exhibit severe developmental malformations including disordered steroidogenesis, sexual ambiguities and various bone defects, similar to those seen in patients with Antley-Bixler syndrome (ABS). To probe the role of POR during bone development, we generated a conditional knockout mouse (CKO) by cross breeding Por lox/lox and Dermo1 Cre mice. CKO mice were smaller than their littermate controls and exhibited significant craniofacial and long bone abnormalities. Differential staining of the CKO mice skull bases shows premature fusion of the sphenooccipital and basioccipital-exoccipital synchondroses. Class III malocclusion was noted in adult knockout mice with an unusual overgrowth of the lower incisors. Shorter long bones were observed along with a reduction in the bone volume fraction, measured by microCT, in the Por-deleted mice compared to age- and sex-matched littermate controls. Concerted up- or down-regulation of proteins in the FGF signaling pathway observed by immunohistochemistry in the tibia samples of CKO mice compared to wild type controls shows a decrease in the FGF signaling pathway. To our knowledge, this is the first report of a mouse model that recapitulates both skull and long bone defects upon Por deletion, offering an approach to study the sequelae of POR mutations. This unique model demonstrates that P450 metabolism in bone itself is potentially important for proper bone development, and that an apparent link exists between the POR and FGF signaling pathways, begging the question of how an oxidation-reduction flavoprotein affects developmental and cellular signaling processes.