Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved reachability analysis of large finite state machines

BDD-based symbolic traversals are the state-of-the-art technique for reachability analysis of finite state machines. They are currently limited to medium-small circuits for two reasons: peak BDD size during image computation and BDD explosion for representing state sets. Starting from these limits, this paper presents can optimized traversal technique particularly oriented to the exact exploration of the state space of large machines. This is possible thanks to: temporary simplification of a finite state machine by removing some of its state elements; and a "divide-and-conquer" approach based on state set decomposition. An effective use of secondary memory allows us to store relevant portions of BDDs and to regularize access to memory, resulting in less page faults. Experimental results show that this approach is particularly effective on the larger ISCAS'89 and ISCAS'89-addendum'93 circuits.
Depletion of calcium from the lumen of endoplasmic reticulum reversibly inhibits passive diffusion and signal-mediated transport into the nucleus

Nuclear pore complexes provide channels for molecular transport across the nuclear envelope. Translocation of most proteins and RNAs through the pore complex is mediated by signal- and ATP-dependent mechanisms, while transport of small molecules is accomplished by passive diffusion. We report here that depletion of calcium from the lumen of the endoplasmic reticulum and nuclear envelope with ionophores or the calcium pump inhibitor thapsigargin rapidly and potently inhibits signal mediated transport of proteins into the nucleus. Lumenal calcium depletion also inhibits passive diffusion through the pore complex. Signal-mediated protein import and passive diffusion are rapidly restored when the drugs depleting lumenal calcium are removed and cells are incubated at 37 degrees C in calcium-containing medium. These results indicate that loss of calcium from the lumen of the endoplasmic reticulum and nuclear envelope reversibly affects properties of pore complex components located on the nuclear/cytoplasmic membrane surfaces, and they provide direct functional evidence for conformational flexibility of the pore complex. These methods will be useful for achieving reversible inhibition of nucleocytoplasmic trafficking for in vivo functional studies, and for studying the structure of the passive diffusion channel(s) of the pore complex.
FlashTier: a lightweight, consistent and durable storage cache

The availability of high-speed solid-state storage has introduced a new tier into the storage hierarchy. Low-latency and high-IOPS solid-state drives (SSDs) cache data in front of high-capacity disks. However, most existing SSDs are designed to be a drop-in disk replacement, and hence are mismatched for use as a cache. This paper describes FlashTier, a system architecture built upon solid-state cache (SSC), a flash device with an interface designed for caching. Management software at the operating system block layer directs caching. The FlashTier design addresses three limitations of using traditional SSDs for caching. First, FlashTier provides a unified logical address space to reduce the cost of cache block management within both the OS and the SSD. Second, FlashTier provides cache consistency guarantees allowing the cached data to be used following a crash. Finally, FlashTier leverages cache behavior to silently evict data blocks during garbage collection to improve performance of the SSC. We have implemented an SSC simulator and a cache manager in Linux. In trace-based experiments, we show that FlashTier reduces address translation space by 60% and silent eviction improves performance by up to 167%. Furthermore, FlashTier can recover from the crash of a 100GB cache in only 2.4 seconds.
Finite-time consensus and stability of networked nonlinear systems

This paper considers the finite-time consensus and stability problems of networked nonlinear systems under an undirected fixed graph. A nonlinear system takes a general form of a controlled first-order differential equation with/without drift term. Sufficient conditions for finite-time consensus and stabilization of networked nonlinear systems are achieved. In multi-system formation, the proposed theoretical approach generalizes the literature results for multi-agent stability and consensus. Heterogenous/homogeneous multi-system formation is a direct application of the given analysis. Some examples are integrated for illustration.
Simulating adaptive service-oriented software systems

Simulation of dynamic service-based software systems is important for studying services that may change their composition and thus interactions at run-time. An approach based on Service Oriented Architecture-compliant DEVS (SOAD) and Dynamic Structure DEVS (DSDEVS) modeling approaches is developed to support structural changes in service model composition. To achieve this goal, a broker–executive model is devised based on the broker model defined for SOAD and the executive model defined for DSDEVS. The capability to simulate dynamic services is incorporated to the DEVS-Suite simulator. To demonstrate modeling of dynamic service-based software systems, a real voice communication system and a model of this system have been developed. The importance of enabling simulation-based design for adaptable systems is briefly discussed.
Sparse and shift-Invariant representations of music

Redundancy reduction has been proposed as the main computational process in the primary sensory pathways in the mammalian brain. This idea has led to the development of sparse coding techniques, which are exploited in this article to extract salient structure from musical signals. In particular, we use a sparse coding formulation within a generative model that explicitly enforces shift-invariance. Previous work has applied these methods to relatively small problem sizes. In this paper, we present a subset selection step to reduce the computational complexity of these methods, which then enables us to use the sparse coding approach for many real world applications. We demonstrate the algorithm's potential on two tasks in music analysis: the extraction of individual notes from polyphonic piano music and single-channel blind source separation.
Why It Pays to Hire Workers with Developmental Disabilities

a job coach to assist him in learning to do the job. On Michael’s first day of work, the district manager made a surprise visit to the restaurant. After questioning Michael’s immediate supervisor about him, the manager directed the supervisor to fire him on the spot, stating, &dquo;We don’t need those kind of people working for the company&dquo; (Miller, 1999). The supervisor refused to fire Michael and attempted to contact the company’s public relations director. The company never responded, and the supervisor ultimately quit in protest of the company’s decision. The Equal Employment Opportunity Commission has filed an Americans with
Fault accommodation for linear systems with time-varying delay

ABSTRACT This paper studies the fault accommodation problem for linear systems with time-varying delay, system uncertainties and external disturbances. A novel intermediate estimator-based fault tolerant control (FTC) scheme is proposed, where an intermediate estimator is constructed to estimate the states and the faults simultaneously, based on the estimation; an FTC compensation scheme is designed to eliminate the effects of faults, system uncertainties and time-varying delay. It is proved that the states of the closed-loop system are uniformly ultimately bounded. A simulation example shows the effectiveness of the proposed method.
Dynamical Models and Mechanistic Explanations

Philosophers of science increasingly believe that cognitive phenomena are explained by describing the mechanisms that produce those phenomena, rather than by subsuming them under laws. With respect to the increasingly influential dynamical approach to cognition, however, it has been claimed that only certain kinds of dynamical models (in particular, connectionist dynamical models) satisfy the requirements for mechanistic explanation. This article evaluates this claim. In particular, here it is argued that in the field of evolutionary robotics, several non-connectionist dynamical models have been developed that provide mechanistic explanations of “minimally cognitive” phenomena. Accordingly, the dynamical approach to cognition is conceived as a scientific approach unified by the common employment of a certain body of mathematical tools and concepts, rather than by a common explanatory method.
The Role of Inhibition in Theory of Mind Performance: Evidence for a Non-Modular View of Theory of Mind

As the modularity of Theory of Mind continues to be debated, the present study sought to investigate the relationship between inhibitory control and performance on a linguistic Theory of Mind (ToM) task. Performance on ToM tasks that relied on inhibitory control was contrasted with performance on ToM tasks that did not rely on inhibitory control. In addition, a range of executive function tasks were administered to all participants. It was hypothesized that if Theory of Mind shares resources with the executive process of inhibition, performance on the ToM task would diminish when inhibition demands were high. Results indicated that performance on the ToM task was significantly lower when participants were required to inhibit superficial discrepancies in the Theory of Mind stories. Moreover, performance on the ToM task correlated with the ability to resist non-linguistic interference. These findings challenge the modular views of Theory of Mind, and suggest that Theory of Mind and executive functions may rely on common cognitive resources.
Workload-Aware Scheduling Across Geo-distributed Data Centers

As the rapid development of big data applications, more and more data analytics are based on geographically distributed data centers. Recent works mainly focus on task and data placement to reduce data transmission among these geodistributed data centers. In this paper, we argue that the task execution delay may also impact the response time, especially in the hot-spot data centers. We define geo-distributed workloadaware scheduling problem, aiming to minimize the overall delay of data transmission and task execution. And then, we prove it to be NP-complete and propose an on-line heuristic to effectively re-distribute dataset and tasks, which potentially balances the workload among data centers and optimizes the overall response time. Experiments show that our algorithm has a significant performance improvement which covers wide range of data distribution, and could reduce up to 55% job response time on average.
Recent Developments in the Analysis of Nucleotide Sequences by using Nucleotide Genomic Signals

The nucleotide genomic signal (NuGS) methodology allows to use powerful signal processing methods in the analysis of genomic data. The method reveals surprising global regularities in the distribution of nucleotides and pairs of nucleotides along genomic sequences in archaea, bacteria and eukarya. Both manifest and hidden regularities can be detected, the method being also effective for the local study of nucleotide sequences, such as in the analysis of pathogen variability. This is important for detecting the development of pathogen resistance to treatment. Keywords-Nucleotide genomic signals, Nucleotide imbalance, Nucleotide pair imbalance, Genomic symmetries.
The proximal point method revisited

In this short survey, I revisit the role of the proximal point method in large scale optimization. I focus on three recent examples: a proximally guided subgradient method for weakly convex stochastic approximation, the prox-linear algorithm for minimizing compositions of convex functions and smooth maps, and Catalyst generic acceleration for regularized Empirical Risk Minimization.
Pattern Classification using Simplified Neural Networks

In recent years, many neural network models have been proposed for pattern classification, function approximation and regression problems. This paper presents an approach for classifying patterns from simplified NNs. Although the predictive accuracy of ANNs is often higher than that of other methods or human experts, it is often said that ANNs are practically "black boxes", due to the complexity of the networks. In this paper, we have an attempted to open up these black boxes by reducing the complexity of the network. The factor makes this possible is the pruning algorithm. By eliminating redundant weights, redundant input and hidden units are identified and removed from the network. Using the pruning algorithm, we have been able to prune networks such that only a few input units, hidden units and connections left yield a simplified network. Experimental results on several benchmarks problems in neural networks show the effectiveness of the proposed approach with good generalization ability.
Convolutional Neural Networks in Automatic Recognition of Trans-differentiated Neural Progenitor Cells under Bright-Field Microscopy

The study of cell morphology changes leads the investigation of the cell fate decision and its function. Bright-field imaging analysis allow us to use a labeling free and non-invasive approach to measure the morphological dynamics during cellular reprogramming, which includes induced pluripotent stem cells (iPSCs), and trans-differentiated neural progenitor cells (NPCs) from somatic cell source. However, the traditional method to study the NPC differentiation and its related function involves staining, and cell lysis, which can not materialized further for the clinical uses. In order to automatically, non-invasively, non-labelled analyze and cultivate cells, a system classifying NPCs under bright-field microscopic imaging is necessary. In this paper, we propose a novel recognition system based on convolutional neural networks, which could pre-process images and classify NPCs and non-NPCs. Experimental results prove that the proposed system provides a new tool for fundamental research in iPSCs and NPCs based generation medicine.
Reflections Through the Looking‐glass: the story of a Course of Writing as a Reflexive Practitioner

ABSTRACT Writing as a reflexive practitioner, a marriage of the accepted praxis of reflective practice and the craft of creative writing, can enable dynamic learning from practice. Professionals are under increased pressure: roles have become more complex, demand has increased, staffing levels have decreased and constant accountability is essential. Stress levels are unsurprisingly higher. The examination of practice can improve understanding, knowledge, skills and therefore delivery. Writing as a reflective practitioner can lead to professional development, decrease stress by enabling problems to be discussed and dealt with, and can also support the building of team work. This paper offers a discussion of this, the background of reflective practice and professional development, and a description of the reflexive writing and group process, through the example of a course for primary health care professionals.
Introduction. Extent, processes and evolutionary impact of interspecific hybridization in animals

Since the time of Charles Darwin, studies of interspecific hybridization have been a major focus for evolutionary biologists. Although this phenomenon has often been viewed as problematic in the fields of ecology, taxonomy and systematics, it has become a primary source of data for studies on speciation and adaptation. Effects from genetic/evolutionary processes, such as recombination and natural selection, usually develop over extended periods of time; however, they are accelerated in cases of hybridization. Interspecific hybrids exhibit novel genomes that are exposed to natural selection, thus providing a key to unravel the ultimate causes of adaptation and speciation. Here we provide firstly a historic perspective of hybridization research, secondly a novel attempt to assess the extent of hybridization among animals and thirdly an overview of the reviews and case studies presented in this theme issue.
Adaptive Coalition Structure Generation in Cooperative Multi-agent Systems

In multiagent systems a coalition structure is a col- lection of pair-wise disjoint subsets of agents whose union yields the entire population. Given a characteristic funct ion quantifying the worth of agent subsets, searching for optimal coalition structures (i.e. where the sum of subsets' worth i s maximal) is a well-known NP-hard combinatorial optimiza- tion problem. While existing algorithms (either deterministic or stochastic) deal with time-invariant goal functions, th e fo- cus here is on dynamic settings, where the worth of agent sub- sets possibly varies over time in an unknown and unpredictable fashion. The aim is to design an adaptive dynamic process gen- erating coalition structures with high worth most of the times. To this end, detecting variations in the worth of agent sub- sets becomes crucial. The proposed method takes into account such (possible) changes by intensifying the exploration activity whenever they are detected. The performance with respect to the worth of optimal coalition structures is evaluated thro ugh simulations.
A characterization of DNA release in Pseudomonas aeruginosa cultures and biofilms

Pseudomonas aeruginosa produces extracellular DNA which functions as a cell‐to‐cell interconnecting matrix component in biofilms. Comparison of extracellular DNA and chromosomal DNA by the use of polymerase chain reaction and Southern analysis suggested that the extracellular DNA is similar to whole‐genome DNA. Evidence that the extracellular DNA in P. aeruginosa biofilms and cultures is generated via lysis of a subpopulation of the bacteria was obtained through experiments where extracellular β‐galactosidase released from lacZ‐containing P. aeruginosa strains was assessed. Experiments with the wild type and lasIrhlI, pqsA, pqsL and fliMpilA mutants indicated that the extracellular DNA is generated via a mechanism which is dependent on acyl homoserine lactone and Pseudomonas quinolone signalling, as well as on flagella and type IV pili. Microscopic investigation of flow chamber‐grown wild‐type P. aeruginosa biofilms stained with different DNA stains suggested that the extracellular DNA is located primarily in the stalks of mushroom‐shaped multicellular structures, with a high concentration especially in the outer part of the stalks forming a border between the stalk‐forming bacteria and the cap‐forming bacteria. Biofilms formed by lasIrhlI, pqsA and fliMpilA mutants contained less extracellular DNA than biofilms formed by the wild type, and the mutant biofilms were more susceptible to treatment with sodium dodecyl sulphate than the wild‐type biofilm.
Shock mesenteric lymph-induced rat polymorphonuclear neutrophil activation and endothelial cell injury is mediated by aqueous factors.

BACKGROUND After trauma and hemorrhagic shock (T/HS), mesenteric lymph (ML) activates polymorphonuclear neutrophils (PMNs), injures endothelial cells (ECs), and predisposes to lung injury. The involved mediators, however, are unknown. We studied the ability of aqueous (AQ) and lipid (LIP) extracts of rat T/HS ML to activate PMNs and injure ECs. METHODS ML was collected from male rats undergoing trauma (laparotomy) plus hemorrhagic shock (30 mm Hg, 90 minutes) or sham shock. AQ and LIP ML fractions were separated using the Bligh-Dyer technique. Human umbilical vein endothelial cells were incubated 18 hours in 5% LIP or AQ lymph fractions and viability was assessed using the MTT assay. Rat PMNs incubated 5 minutes with 3% LIP or AQ fractions were assessed for respiratory burst (RB) and cytosolic calcium ([Ca(2+)](i)) using dihydrorhodamine 123 and fura-2AM. Human PMN responses to AQ and LIP T/HS lymph were studied similarly. RESULTS EC incubated in AQ showed 19 +/- 4% viability as compared with 65 +/- 11% in LIP (p < 0.001). Whole lymph affected ECs comparably to AQ T/HS lymph. Rat PMN basal [Ca(2+)](i) increased after exposure to AQ but not LIP T/HS lymph extracts. AQ T/HS lymph primed [Ca(2+)](i) responses to macrophage inflammatory protein-2 and platelet-activating factor; neither LIP T/HS nor any trauma and sham shock lymph fraction caused PMN priming. Rat PMN RB was elevated after AQ T/HS lymph incubation when compared with buffer (610 +/- 122 U/s vs. 225 +/- 38 U/s, p = 0.01). Rat PMN incubation in LIP T/HS lymph caused minimal activation (289 +/- 28 U/s, p = NS). Conversely, human PMN showed [Ca(2+)](i) and RB priming by rat T/HS LIP and not AQ extracts. CONCLUSION T/HS mesenteric lymph contains multiple biologically active mediators. Both AQ and LIP extracts of T/HS lymph are toxic to human umbilical vein endothelial cells, with AQ more active than LIP. Only AQ T/HS lymph activates rat PMNs, although LIP rat lymph extract activates human PMNs. These findings demonstrate the complex nature of gut lymph-derived biologic factors as well as species-specific differences on PMN and EC physiology. Therapies directed at any one specific molecule or mediator are therefore unlikely to be successful.
Worst-case execution times analysis of MPEG-2 decoding

Presents the first worst-case execution times (WCET) analysis of MPEG decoding. Solutions for two scenarios-video-on-demand (VoD) and live-are presented, serving as examples for a variety of real-world applications. A significant reduction of over-estimations (down to 17%, including overheads) during WCET analysis of the live scenario can be achieved by using our new two-phase decoder with built-in WCET analysis, which can be universally applied. It is even possible to predict the exact execution times in the VoD scenario. This work is motivated by the fact that media streaming service providers are under great pressure to fulfil the quality of service promised to their customers, preferably in an efficient way.
Inactivation of RARβ inhibits Wnt1-induced mammary tumorigenesis by suppressing epithelial-mesenchymal transition

Retinoic acid receptor β (RARβ) has been proposed to act as a tumor suppressor in breast cancer. In contrast, recent data have shown that RARβ promotes ERBB2-induced mammary gland tumorigenesis through remodeling of the stromal compartment and activation of cancer-associated fibroblasts. However, it is currently unknown whether RARβ oncogenic activity is specific to ERBB2-induced tumors, or whether it influences the initiation and progression of other breast cancer subtypes. Accordingly, we set out to investigate the involvement of RARβ in basal-like breast cancer using mouse mammary tumor virus (MMTV)-wingless-related integration site 1 (Wnt1)-induced mammary gland tumorigenesis as a model system. We found that compared with wild type mice, inactivation of Rarb resulted in a lengthy delay in Wnt1-induced mammary gland tumorigenesis and in a significantly slower tumor growth rate. Ablation of Rarb altered the composition of the stroma, repressed the activation of cancer-associated fibroblasts, and reduced the recruitment of inflammatory cells and angiogenesis. Reduced expression of IGF-1 and activity of its downstream signaling pathway contribute to attenuate EMT in the Rarb-null tumors. Our results show that, in the absence of retinoid signaling via RARβ, reduced IGF-1 signaling results in suppression of epithelial-mesenchymal transition and delays tumorigenesis induced by the Wnt1 oncogene. Accordingly, our work reinforces the concept that antagonizing RARβ-dependent retinoid signaling could provide a therapeutic avenue to treat poor outcome breast cancers.