Miracle-dz/UniFAR-FTUs huggingface dataset:
Incremental Policy Iteration with Guaranteed Escape from Local Optima in POMDP Planning

Partially observable Markov decision processes (POMDPs) provide a natural framework to design applications that continuously make decisions based on noisy sensor measurements. The recent proliferation of smart phones and other wearable devices leads to new applications where, unfortunately, energy efficiency becomes an issue. To circumvent energy requirements, finite-state controllers can be applied because they are computationally inexpensive to execute. Additionally, when multi-agent POMDPs (e.g. Dec-POMDPs or I-POMDPs) are taken into account, finite-state controllers become one of the most important policy representations. Online methods scale the best; however, they are energy demanding. Thus methods to optimize finite-state controllers are necessary. In this paper, we present a new, efficient approach to bounded policy interaction (BPI). BPI keeps the size of the controller small which is a desirable property for applications, especially on small devices. However, finding an optimal or near optimal finite-state controller of a bounded size poses a challenging combinatorial optimization problem. Exhaustive search methods clearly do not scale to larger problems, whereas local search methods are subject to local optima. Our new approach solves all of the common benchmarks on which local search methods fail, yet it scales to large problems.
Products of stochastic matrices: Large deviation rate for Markov chain temporal dependencies

We find the large deviation rate I for convergence in probability of the product Wk ---W1W0 of temporally dependent random stochastic matrices. As the model for temporal dependencies, we adopt the Markov chain whose set of states is the set of all possible graphs that support the matrices Wk. Such model includes, for example, 1) token-based protocols, where a token is passed among nodes to determine the order of processing; and 2) temporally dependent link failures, where the temporal dependence is modeled by a Markov chain. We characterize the rate I as a function of the Markov chain transition probability matrix P. Examples further reveal how the temporal correlations (dependencies) affect the rate of convergence in probability I.
Force characterization of live cells in automated transportation with robot-tweezers manipulation system

Optical trap provides a new and unique tool for manipulation in micro/nano scale and have wide applications in biological fields. Increasing demands for both accuracy and efficiency in cell manipulation highlight the need for automation process that integrates robotics and optical tweezers technologies. A clear understanding of the forces exerted on cells, i.e., trapping and viscous drag forces, is essential to enable automated manipulation using optical tweezers. In this paper, we propose a method to characterize the forces exerted on the live cell moved by optical trap, where the cell is bound to a micro polystyrene bead. Experiment of the cell falling to the focus of the optical trap is performed to show that the proposed force calibration method exhibit better accuracy than the traditional ray-optic numerical method based on the transparent-bead model. Further, automated transportation of the yeast cell is performed to demonstrate the effectiveness in applying the proposed force characterization approach to automated cell manipulation.
Efficacy and safety of infliximab in very early onset inflammatory bowel disease: a national comparative retrospective study

Background Very few data regarding the use of infliximab in children with very early-onset inflammatory bowel disease (VEO-IBD) have been reported. Objective We aimed to assess the efficacy and the safety of infliximab in children with VEO-IBD compared with older children. Methods Children treated with infliximab were identified within the Italian IBD registry. The primary outcome was the rate of clinical remission at weeks 14 and 54. Secondary outcomes included the proportion of partial clinical response, treatment duration, and incidence of adverse events. Results Forty-two children with VEO-IBD were compared with 130 children with IBD. Despite significantly higher infliximab withdrawals in VEO-IBD patients during induction (42.9% vs 7.7% p < 0.01), remission rates at week 14 were similar (28.6% vs 43.8%, p = 0.10). At week 54 fewer VEO-IBD children were in remission (15.8% vs 54.3%, p < 0.01). The treatment duration was shorter in VEO-IBD (median 12.0 vs 18.4 months, p < 0.01). During the induction phase, adverse events were more common in the VEO-IBD group (p < 0.01). Conclusion Compared with older children, VEO-IBD patients have higher rates of infliximab failures, lower remission rates at one year, and more often experience adverse events during induction.
A Constructive Confrontation Approach to Managing Organizational Culture

The goal of this paper is to present the constructive confrontation approach to management of organizational culture. The approach provides for transformation of confrontation caused by differences between the new values of a declared organizational culture and the current values of employees in constructive process. Constructive confrontation allows for the concentration of energies and capacities of employees induced by confrontation in their productive adoption of new organizational cultural values. The approach development intends planning of organizational cultural change, and managing the adoption of new organizational cultural values by employees. Planning involves: building a structure of desired organizational values, setting the order of adoption of the new values, and determination of interrelated actions of employees generated by the new organizational values in accordance to the set order. Managing the adoption of new values involves forming a dynamic managerial team, receiving feedback on value adoption as a result of determining value adoption measure, and responding to feedback through complex and flexible use of the constructive confrontation tools.
Sentence-Level Opinion Analysis by CopeOpi in NTCIR-7

In this paper, we introduce our system, CopeOpi, for analyzing opinionated information in NTCIR-7 MOAT task’s document collections. We participated in all tasks except opinion target extraction and submitted three runs for both simplified and traditional Chinese sides. For opinion extraction task, our algorithm was based on the bag-ofcharacter methods proposed in NTCIR-6 and considered morphological structures of Chinese words to extract opinion words more correctly. How distant an opinion word is to the end of the sentence is also considered to adjust its opinion weight. The performance of the opinion extraction, which is the second best of all participants, achieves the fmeasure 0.672 under the lenient metric and 0.783 under the strict metric. The performances of polarity detection and the relevance judgment are both ranked the third.
Inference and Learning in Hybrid Bayesian Networks

We survey the literature on methods for inference and learning in Bayesian Networks composed of discrete and continuous nodes, in which the continuous nodes have a multivariate Gaussian distribution, whose mean and variance depends on the values of the discrete nodes. We also briefly consider hybrid Dynamic Bayesian Networks, an extension of switching Kalman filters. This report is meant to summarize what is known at a sufficient level of detail to enable someone to implement the algorithms, but without dwelling on formalities.
Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks

Deep neural networks have proven to be quite effective in a wide variety of machine learning tasks, ranging from improved speech recognition systems to advancing the development of autonomous vehicles. However, despite their superior performance in many applications, these models have been recently shown to be susceptible to a particular type of attack possible through the generation of particular synthetic examples referred to as adversarial samples. These samples are constructed by manipulating real examples from the training data distribution in order to "fool" the original neural model, resulting in misclassification (with high confidence) of previously correctly classified samples. Addressing this weakness is of utmost importance if deep neural architectures are to be applied to critical applications, such as those in the domain of cybersecurity. In this paper, we present an analysis of this fundamental flaw lurking in all neural architectures to uncover limitations of previously proposed defense mechanisms. More importantly, we present a unifying framework for protecting deep neural models using a non-invertible data transformation--developing two adversary-resilient architectures utilizing both linear and nonlinear dimensionality reduction. Empirical results indicate that our framework provides better robustness compared to state-of-art solutions while having negligible degradation in accuracy.
NRF2 Protection against Liver Injury Produced by Various Hepatotoxicants

To investigate the role of Nrf2 as a master defense against the hepatotoxicity produced by various chemicals, Nrf2-null, wild-type, Keap1-knock down (Keap1-Kd) and Keap1-hepatocyte knockout (Keap1-HKO) mice were used as a “graded Nrf2 activation” model. Mice were treated with 14 hepatotoxicants at appropriate doses, and blood and liver samples were collected thereafter (6 h to 7 days depending on the hepatotoxicant). Graded activation of Nrf2 offered a Nrf2-dependent protection against the hepatotoxicity produced by carbon tetrachloride, acetaminophen, microcystin, phalloidin, furosemide, cadmium, and lithocholic acid, as evidenced by serum alanine aminotransferase (ALT) activities and by histopathology. Nrf2 activation also offered moderate protection against liver injury produced by ethanol, arsenic, bromobenzene, and allyl alcohol but had no effects on the hepatotoxicity produced by D-galactosamine/endotoxin and the Fas ligand antibody Jo-2. Graded Nrf2 activation reduced the expression of inflammatory genes (MIP-2, mKC, IL-1β, IL-6, and TNFα), oxidative stress genes (Ho-1, Egr1), ER stress genes (Gadd45 and Gadd153), and genes encoding cell death (Noxa, Bax, Bad, and caspase3). Thus, this study demonstrates that Nrf2 prevents the liver from many, but not all, hepatotoxicants. The Nrf2-mediated protection is accompanied by induction of antioxidant genes, suppression of inflammatory responses, and attenuation of oxidative stress.
Selling Ourselves Short? How Abbreviated Measures of Personality Change the Way We Think about Personality and Politics

Political scientists who study the interplay between personality and politics overwhelmingly rely on short personality scales. We explore whether the length of the employed personality scales affects the criterion validity of the scales. We show that need for cognition (NfC) increases reliance on party cues, but only when a longer measure is employed. Additionally, while NfC increases reliance on policy information, the effect is more than twice as large when a longer measure is used. Finally, Big Five personality traits that have been dismissed as irrelevant to political ideology yield stronger and more consistent associations when larger batteries are employed. We also show that using high Cronbach’s alpha and factor loadings as indicators of scale quality does not improve the criterion validity of brief measures. Hence, the measurement of personality conditions the conclusions we draw about the role of personality in politics.
Expressiveness of Temporal Logics

A tree is as a partially ordered set of nodes s.t. the set of predecessors of any node is finite, totally ordered and with a common minimal element (the root ε). Let Σ be an alphabet. Definition A Σ-labeled tree is a pair 〈T , l〉 where: T is a tree l : T → Σ maps each node with a letter in Σ. Tree-like structure Definition A tree is a set T ⊆ N>0 such that if x · c ∈ T with x ∈ N>0 and c ∈ N>0, we have: x ∈ T for all 1 ≤ c ′ < c , x · c ′ ∈ T
Introducing Traceability and Consistency Checking for Change Impact Analysis across Engineering Tools in an Automation Solution Company: An Experience Report

In today's engineering projects, companies continuously have to adapt their systems to changing customer or market requirements. This requires a flexible, iterative development process in which different parts of the system under construction are built and updated concurrently. However, concurrent engineering is quite problematic in domains where different engineering domains and different engineering tools come together. In this paper, we discuss experiences with Van Hoecke Automation, a leading company in the areas of production automation and product processing, in maintaining the consistency between electrical models and the corresponding software controller when both are subject to continuous change. The paper discusses how we let engineers describe the relationships between electrical model and software code in form of links and consistency rules, and how through continuous consistency checking our approach then notified those engineers of the erroneous impact of changes in either electrical model or code.
Tetraspanin Protein CD9 Is a Novel Paranodal Component Regulating Paranodal Junctional Formation

The axoglial paranodal junction is essential for the proper localization of ion channels around the node of Ranvier. The integrity of this junction is important for nerve conduction. Although recent studies have made significant progress in understanding the molecular composition of the paranodal junction, it is not known how these membrane components are distributed to the appropriate sites and interact with each other. Here we show that CD9, a member of the tetraspanin family, is present at the paranode. CD9 is concentrated in the paranode as myelination proceeds, but CD9 clusters become diffuse, associated with disruption of the paranode, in cerebroside sulfotransferase-deficient mice. Immunohistochemical and Western blot analysis showed that CD9 is distributed predominantly in the PNS. Ablation of CD9 in mutant mice disrupts junctional attachment at the paranode and alters the paranodal components contactin-associated protein (also known as Paranodin) and neurofascin 155, although the frequency of such abnormalities varies among individuals and individual axons even in the same mouse. Electron micrographs demonstrated that compact myelin sheaths were also affected in the PNS. Therefore, CD9 is a myelin protein important for the formation of paranodal junctions. CD9 also plays a role in the formation of compact myelin in the PNS.
Romanian Preschool Teachers Professional Beliefs about Diversity

Contemporary educational systems become more and more pluralistic in terms of ethnicity, social classes or learning abilities of the students. In this context, teachers’ attitudes, beliefs and expectancies could influence their professional behaviors. Preschool educators are the first which are confronted with the issue of diversity. Despite this fact, the kindergarten teachers’ beliefs toward diversity are not often investigated. In this context, the purpose of this study is to cover this gap, investigating Romanian preschool professional beliefs about diversity. We used the Professional Beliefs about Diversity Scale (Pohan & Aguilar, 1999), translated and slightly adapted on Romanian culture. 107 Romanian kindergarten teachers’ responses on their professional beliefs about diversity was associated with age and previous experience with culturally different children. The results show a general slight positive orientation of beliefs about diversity of the subjects. The particular dimensions of beliefs about diversity, reflected in educational approaches of race, social class and disabilities are more nuanced, varying depending on age and cultural experience with different ethnically children. The results show that the youngest preschool teachers (under 22 years old and between 23 and 35 years old) are, the more reluctant toward different ethnic/cultural children than the older teachers (49-61 years old). The implication of the results in educational and formative contexts are discussed.
Effects of Attachment of Plastic Aligner in Closing of Diastema of Maxillary Dentition by Finite Element Method

The aim of this study was to clarify the effect of attachment on tooth movement produced by a plastic aligner. Closing of a diastema, in which the maxillary right and left central incisors moved bodily, was simulated using a finite element method. Long-term orthodontic movements of the maxillary dentition were simulated by accumulating the initial displacement of teeth produced by elastic deformation of the periodontal ligament. The incisor tipped and rotated just after placement of the aligner irrespective of the attachment. After a sufficiently long time, the incisor was upright and moved bodily in the aligner with attachment, but the incisor remained tipped in the aligner without attachment. It was demonstrated that the attachment was effective for achieving bodily movement.
A Simulation-Based Multiobjective Optimization Approach for Health Care Service Management

Hospitals are huge and complex systems. However, for many years, the management was commonly focused on improving the quality of the medical care, while less attention was usually devoted to operation management. In recent years, the need of containing the costs while increasing the competitiveness along with the new policies of National Health Service hospital financing forced hospitals to necessarily improve their operational efficiency. In this paper, we focus on a management problem usually arising in health care. In particular, we deal with optimal resource allocation of a ward of a big hospital. To this aim, we propose a simulation-based optimization approach that makes use of a discrete-event simulation model, reproducing the hospital services and combined with a derivative-free multiobjective optimization method. The results obtained on the obstetrics ward of an Italian hospital are reported, showing the effectiveness of the new approach proposed.
1 Expressive , Efficient Instance Variables

The decoupling of clients of abstractions from the implementations of those abstractions is a key benefit of objectoriented programming. However, many object-oriented languages provide instance variables in such a way that implementation-level representation decisions seep through interfaces, introducing coupling between clients and abstractions. As part of the Cecil language, we have developed a semantics for flexible instance variables based on the principle that a class should be decoupled from its clients, its subclasses, and its role extensions. We describe our design of instance variables and provide examples where their additional flexibility has been useful. However, implementing our semantics naively can impose significant performance penalties. To achieve reasonable performance, we have developed a number of optimizations that are effective at eliminating many of the costs of our flexible model. We discuss these optimizations and report on the results of experiments to assess the costs of our design under different optimization scenarios.
Function and regulation of Tumbleweed (RacGAP50C) in neuroblast proliferation and neuronal morphogenesis.

Drosophila RacGAP50C and its homologues act as part of a complex with a kinesin-like protein (Pavarotti/Zen-4) that is essential for the formation of the central spindle and completion of cytokinesis [Mishima, M. , Kaitna, S. & Glotzer, M. (2002) Dev. Cell 2, 41-54; Somers, W. G. & Saint, R. (2003) Dev. Cell 4, 29-39; Jantsch-Plunger et al. (2000) J. Cell Biol. 149, 1391-1404]. We report here that RacGAP50C corresponds to the tumbleweed (tum) gene previously identified based on its defects in dendrite development of sensory neurons [Gao, F. B. , Brenman, J. E. , Jan, L. Y. & Jan, Y. N. (1999) Genes Dev. 13, 2549-2561]. Using mushroom body neurogenesis and morphogenesis as a model, we show that Tumbleweed (Tum), Pavarotti, and their association are required for neuroblast proliferation. Tum with a mutation predicted to disrupt the GTPase-activating protein (GAP) activity still largely retains its activity in regulating cell division but is impaired in its activity to limit axon growth. We also provide evidence that Tum and Pavarotti regulate the subcellular localization of each other in postmitotic neurons and that cytoplasmic accumulation of both proteins disrupts axon development in a GAP-dependent manner. Taken together with previous studies of RacGAP50C in regulating cytokinesis, we propose that Tum serves as a scaffolding protein in regulating cell division but acts as a GAP to limit axon growth in postmitotic neurons.
Active Caching for KVS Dynamic Scaling

Load size to a service in the Internet remarkably changes every hour. Thus, it is expected that service system scale should be changed dynamically according to load size. KVS (Key-Value Store) is scalable DBMS (database management system) and widely used in large-scale Internet services. In this paper, we focus on Cassandra, a popular open-source KVS implementation, and discuss methods for improving dynamic scaling performance. First, we evaluate node joining time, which is time to complete adding a node to a running KVS system, and show that its bottleneck process is disk I/O in the existing nodes. Second, we analyze disk accesses in the bottleneck nodes and point it out that some heavily accessed files cause a large number of disk accesses. Third, we propose two methods for decreasing node joining time. One method is to reduce disk accesses significantly by keeping the heavily accessed file in the page cache. The other method is to increase sequential I/O performance by enlarging time slice of I/O scheduler. Lastly, we evaluate our methods and demonstrate that our method can improve scaling-out performance of Cassandra.
Assessing Dependability with Software Fault Injection

With the rise of software complexity, software-related accidents represent a significant threat for computer-based systems. Software Fault Injection is a method to anticipate worst-case scenarios caused by faulty software through the deliberate injection of software faults. This survey provides a comprehensive overview of the state of the art on Software Fault Injection to support researchers and practitioners in the selection of the approach that best fits their dependability assessment goals, and it discusses how these approaches have evolved to achieve fault representativeness, efficiency, and usability. The survey includes a description of relevant applications of Software Fault Injection in the context of fault-tolerant systems.
Extracting Common Sense Knowledge from Wikipedia

Much of the natural language text found on the web contains various kinds of generic or "common sense" knowledge, and this informa- tion has long been recognized by artificial intelligence as an important supplement to more formal approaches to building Semantic Web knowl- edge bases. Consequently, we are exploring the possibility of automati- cally identifying "common sense" statements from unrestricted natural language text and mapping them to RDF. Our hypothesis is that com- mon sense knowledge is often expressed in the form of generic statements such as Coee is a popular beverage , and thus our work has focussed on the challenge of automatically identifying generic statements. We have been using the Wikipedia xml corpus as a rich source of common sense knowledge. For evaluation, we have been using the existing annotation of generic entities and relations in the ace 2005 corpus.