Miracle-dz/UniFAR-FTUs huggingface dataset:
QUALITY COMPETITION IN BUS SERVICES: SOME WELFARE IMPLICATIONS OF BUS DEREGULATION

A theoretical model is developed based upon the quality of competition to enable the determination of equilibrium quality and fare levels. Competition is where high-quality, high-fare minibuses compete (and co-exist) with lower-fare, lower-quality conventional buses. Competition in the bus industry has increased from the low levels experienced just after deregulation and there has been a very rapid growth of minibus services. The model is used to show that two firms operating bus services of distinct qualities can exist in competitive equilibrium in urban areas. The resulting equilibrium is used to analyse the effect on welfare competition as opposed to the monopoly situation before deregulation. Consumers could benefit from competition if the public monopolist operated at a high profit, but it is likely that all consumers will find their welfare reduced with competition. The model also predicts that, at most, two qualities of service can co-exist, given certain ranges in the income distribution. This suggests that there is very little scope for further bus operations with distinctly different mixes of fare and quality. Where there is already competition between buses and taxis, there may be no scope for minibuses. (TRRL)
Human activity recognition and monitoring for elderly people

Statistics show that the population in Europe is aging and in the near future human assistance for elderly persons will be prohibitive. This paper analyses the possibilities to implement a supervision system, which is capable of monitoring a person's activity in his/her home without violating intimacy. The main idea is to collect information from various sensors placed in house and on mobile devices and infer a most probable sequence of activities performed by the supervised person. A Hidden Markov chain method is adapted for the activity chain recognition.
Dynamic social zone for human safety in human-robot shared workspaces

In this paper, we present an efficient human safety framework of robotic systems that guaranties human safety in human-robot shared workspace. The general framework is composed of three stages: 1) human detection and tracking algorithms are used to detect and track the human in unknown dynamic environments; 2) human social signals is estimated; 3) human states and their social signals are integrated in a estimation model, so-called dynamic social zone (DSZ). The dynamic social zone is embedded into the navigation control guiding the mobile robots to move safely in human populated environments. The experimental results indicate that the proposed framework is able to ensure human safety in human-robot shared workspaces.
Factor Hoarding and the Propagation of Business Cycles Shocks

This paper analyzes the role of variable capital utilization rates in propagating shocks over the business cycle. To this end we formulate and estimate an equilibrium business cycle model in which cyclical capital utilization rates are viewed as a form of factor hoarding. We find that variable capital utilization rates substantially magnify and propagate the impact of shocks to agents' environments. The strength of these propagation effects is evident in the dynamic response functions of various economy wide aggregates to shocks in agents' environments, in the statistics that we construct to summarize the strength of the propagation mechanisms in the model and in the volatility of exogenous technology shocks needed to explain the observed variability in aggregate U.S. output. Other authors have argued that standard Real Business Cycle (RBC) models fail to account for certain features of the data because they do not embody quantitatively important propagation mechanisms. These features include the observed positive serial correlation in the growth rate of output, the shape of the spectrum of the growth rate of real output and the correlation between the forecastable component of real output and various other economic aggregates. Allowing for variable capital utilization rates substantially improves the ability of the model to account for these features of the data.
hypertrophy activates divergent transcriptional programs in cardiac Deficiency of different nitric oxide synthase isoforms

14:25-34, 2003. First published 22 April 2003; Physiol. Genomics Q. Ye, Joe G. N. Garcia and Joshua M. Hare A. Irizarry, Giovanni Parmigiani, Sarfraz Durrani, Tera Lavoie, Eric P. Hoffman, Shui Thomas P. Cappola, Leslie Cope, Amy Cernetich, Lili A. Barouch, Khalid Minhas, Rafael hypertrophy activates divergent transcriptional programs in cardiac Deficiency of different nitric oxide synthase isoforms
Podosomes at a glance

Cells can contact the extracellular matrix (ECM) through a variety of specialized structures. These cell-matrix contacts contain membrane proteins such as integrins, which bind both matrix components and cellular proteins, thus bridging the substratum and the cytoskeleton (reviewed in [Adams, 2001][
Action Space Defined by Natural Language

In this paper, we propose the deep reinforcement relevance network (DRRN), a novel deep architecture, to design a model for handling an action space characterized using natural language with applications to text-based games. For a particular class of games, a user must choose among a number of actions described by text, with the goal of maximizing long-term reward. In these games, the best action is typically what fits the current situation best (modeled as a state in the DRRN), also described by text. Because of the exponential complexity of natural language with respect to sentence length, there is typically an unbounded set of unique actions. Even with a constrained vocabulary, the action space is very large and sparse, posing challenges for learning. To address this challenge, the DRRN extracts separate high-level embedding vectors from the texts that describe states and actions, respectively, using a general interaction function, such as inner product, bilinear, and DNN interaction, between these embedding vectors to approximate the Qfunction. We evaluate the DRRN on two popular text games, showing superior performance over other deep Q-learning architectures.
Reducing sequence artifacts in amplicon-based massively parallel sequencing of formalin-fixed paraffin-embedded DNA by enzymatic depletion of uracil-containing templates.

BACKGROUND Formalin-fixed, paraffin-embedded (FFPE) tissues are routinely used for detecting mutational biomarkers in patients with cancer. A previous intractable challenge with FFPE DNA in genetic testing has been the high number of artifactual single-nucleotide changes (SNCs), particularly for the detection of low-level mutations. Pretreatment of FFPE DNA with uracil-DNA glycosylase (UDG) can markedly reduce these C:G>T:A SNCs with a small panel of amplicons. This procedure has implications for massively parallel sequencing approaches to mutation detection from DNA. We investigated whether sequence artifacts were problematic in amplicon-based massively parallel sequencing and what effect UDG pretreatment had on reducing these artifacts. METHODS We amplified selected amplicons from lung cancer FFPE DNAs using the TruSeq Cancer Panel. SNCs occurring at a frequency <10% were considered most likely to represent sequence artifacts and were enumerated for both UDG-treated and -untreated DNAs. RESULTS Massively parallel sequencing of FFPE DNA samples showed multiple SNCs, predominantly C:G>T:A changes, with a significant proportion occurring above the background sequencing error (defined as 1%). UDG pretreatment markedly reduced C:G>T:A SNCs without affecting the detection of true somatic mutations. However, C:G>T:A changes within CpG dinucleotides were often resistant to the UDG treatment as a consequence of 5-methyl cytosine being deaminated to thymine rather than uracil. CONCLUSIONS UDG pretreatment greatly facilitates the accurate discrimination of mutations in FFPE samples by use of amplicon-based approaches. This is particularly important when working with samples with low tumor purity or for the assessment of mutational heterogeneity in tumors.
Bayesian Approaches to Optimal Information Gathering

The problem of gathering information in an ecient manner is critical in a wide range of elds. Animals and robots must keep track of rapidly changing environments with limited number of sensors in real-time. Therefore, choosing the right place to look at or to sense is important. Similarly in statistical modeling, selecting data to label or experiments to test hypotheses in an ecient manner is essential, especially when the labels and experiments are expensive. In this paper, we survey Bayesian approaches on optimal information gathering developed in various elds including experiment design, sensor placement, active sensing, and active learning. In particular, we cover the classical solutions for linear problems as well as new approximate methods emerging from the reinforcement learning and optimal control literature.
Evidence of a Vocalic Proto-System in the Baboon (Papio papio) Suggests Pre-Hominin Speech Precursors

Language is a distinguishing characteristic of our species, and the course of its evolution is one of the hardest problems in science. It has long been generally considered that human speech requires a low larynx, and that the high larynx of nonhuman primates should preclude their producing the vowel systems universally found in human language. Examining the vocalizations through acoustic analyses, tongue anatomy, and modeling of acoustic potential, we found that baboons (Papio papio) produce sounds sharing the F1/F2 formant structure of the human [ɨ æ ɑ ɔ u] vowels, and that similarly with humans those vocalic qualities are organized as a system on two acoustic-anatomic axes. This confirms that hominoids can produce contrasting vowel qualities despite a high larynx. It suggests that spoken languages evolved from ancient articulatory skills already present in our last common ancestor with Cercopithecoidea, about 25 MYA.
Semantic type disambiguation for Japanese verbs

The interest has been increasing in recent years in extracting and analyzing evaluations and opinions of service or products from large bodies of text. It is important to classify predicates according to sense because whether or not a statement includes the speaker's opinion depends strongly on its predicate. It is generally assumed that Japanese part-of-speech (POS) for predicates is classified according to sense; however, the POS classifications differ from their semantic classification. On this subject, semantic types, which aim to classify predicates, have been proposed. In this paper, we describe semantic types and present our construction of a disambiguator for Japanese verbs. Specifically, we constructed this disambiguator using a support vector machine by building feature vectors. We used semantic categories of noun and results of morphological analysis for the feature vectors. We then achieved 69.9% accuracy of disambiguation for newspaper articles using 10-fold cross-validation.
Enhanced Patterns of Oriented Edge Magnitudes for Face Recognition and Image Matching

A good feature descriptor is desired to be discriminative, robust, and computationally inexpensive in both terms of time and storage requirement. In the domain of face recognition, these properties allow the system to quickly deliver high recognition results to the end user. Motivated by the recent feature descriptor called Patterns of Oriented Edge Magnitudes (POEM), which balances the three concerns, this paper aims at enhancing its performance with respect to all these criteria. To this end, we first optimize the parameters of POEM and then apply the whitened principal-component-analysis dimensionality reduction technique to get a more compact, robust, and discriminative descriptor. For face recognition, the efficiency of our algorithm is proved by strong results obtained on both constrained (Face Recognition Technology, FERET) and unconstrained (Labeled Faces in the Wild, LFW) data sets in addition with the low complexity. Impressively, our algorithm is about 30 times faster than those based on Gabor filters. Furthermore, by proposing an additional technique that makes our descriptor robust to rotation, we validate its efficiency for the task of image matching.
Cooperative target tracking algorithm for a couple of UAVs under communication constraints

One integrated algorithm for a couple of Unmanned Aerial Vehicles (UAVs) to follow a ground target cooperatively is presented. By introducing the funnel function and parameter freezing methods, communication and detection constraints are steadily maintained. Besides, cooperative strategy for measurement fusion purifies the noised geolocation data of the target. A simulation combining all proposed schemes is executed and the effectiveness is verified.
Procesy grupowe a rozwiazywanie antagonistycznych konfliktów: Czy idea demokracji deliberatywnej może mieć psychologiczny sens?

Social psychological research suggest that under certain conditions social groups can engender powerful “synergic tendencies” that facilitate development of shared cognitions among group members. As a result of these processes, the groups can reach an agreement. The purpose of this research was to identify these conditions and test their effects. The research consisted of a series of group debates concerning important issues that evoked strong controversies among the participants, i.e. parents of school children who discussed sex education in schools (20 PROCESY GRUPOWE A ROZWIĄZYWANIE ANTAGONISTYCZNYCH KONFLIKTÓW. 119 debates, 195 participants), politicians representing right wing and left-wing parties who discussed the same topic (7 debates, 35 participants), and residents of a county at the east part of Poland who argued about the site of a garbage collection (10 debates, 100 participants). Six to 13 persons took part in each debate, which usually lasted 100-110 minutes. The debates were conducted by a facilitator according to specially prepared scenarios. Before and after the debate, participants filled out special questionnaires measuring their attitudes and some psychological variables. The debates were recorded on videotape. The obtained data support the contention that social groups tend to engender synergic forces inducing group members to seek agreements in spite of differences. They also indicate that under specific conditions (perceived importance of common tasks, induction of deliberative norms, group authority that supports the task and the norms) the groups can reach agreements even in situations of serious ideological conflict or conflict of interests. The experience of working for agreement can influence participants’ attitudes not only toward the debated issues but also toward the more general strategies of dealing with political disagreements. On the basis of the obtained data a general model of the relationship between synergic and antagonistic tendencies in groups has been formulated.
Acoustic characteristics of ejectives in amharic

In this paper, a preliminary investigation of the acoustic characteristics of Amharic ejectives in comparison with their unvoiced conjugates is presented. The normalized error from linear prediction residual and a zero frequency resonator output are used to locate the instant of release of the oral closure and the instant of the start of voicing, respectively. Amharic ejectives are found to have longer closure duration and smaller VOT than their unvoiced conjugates. Cross-linguistic comparisons reveal that no ejectives of two languages behave acoustically in a similar manner despite similarity in their articulation. Index Terms: Amharic, ejectives, glottalized stops
Nonsteroidal Anti-Inflammatory Drugs and Peroxisome Proliferator-Activated Receptor-γ Agonists Modulate Immunostimulated Processing of Amyloid Precursor Protein through Regulation of β-Secretase

Long-term treatment with nonsteroidal anti-inflammatory drugs (NSAIDs) reduces the risk for Alzheimer's disease (AD). To determine the mechanisms by which inflammation affects AD and how NSAIDs protect against it, we stimulated neuroblastoma cells stably transfected with amyloid precursor protein (APP) with proinflammatory cytokines, which increased the secretion of amyloid-β and APP ectodomain. Addition of ibuprofen, indomethacin, peroxisome proliferator-activated receptor-γ (PPARγ) agonists, or cotransfection with PPARγ cDNA reversed this effect. The inhibitory action of ibuprofen and indomethacin was suppressed by PPARγ antagonists. Finally, we observed that the mRNA levels, expression, and enzymatic activity of β-secretase were increased by immunostimulation and normalized by NSAIDs. In conclusion, proinflammatory cytokines activate β-secretase, and NSAIDs inhibit this effect through PPARγ.
Towards a Privacy Framework

The increasing capture of more detailed personal data by organisations in the 21st century has given rise to increasing consumer privacy concerns, which undermine profitable buyer-seller relationships. As a result, there has been increasing academic interest in the notion of privacy, due to a growing inability by consumers to control their personal data and rising countermeasures by customers to protect their privacy. However, progress in this area has been hampered by the persistence of numerous and differing definitions of the term. In response to this, this paper proposes a framework of privacy as a subjective function based on 7 elements of privacy identified through the critical review of conceptual and empirical literature. This comprehensive framework allows privacy to be operationalised and help marketers to reduce potential consumer privacy intrusion.
Pragmatic Axiomatization Techniques

This paper is about domain-independent theoretical generalizations derived in the process of formalizing aspects of commonsense reasoning. One of the generalizations is a qualitative model that has a template structure, can be applied to multiple reasoning tasks. Another model reduces to a composition of linear orders, making it easy to argue its formal properties. These models allow the population of a knowledge base (KB) by non-logicians. We present experimental results on evaluation of these, and other, models by subject matter experts (SMEs).
The security operations center based on correlation analysis

With the development of the information technology, the network threats are rampant day by day. In order to protect company and organization network, They have deployed a variety of network security products, such as IDS (intrusion detection system), firewalls, VPN and AVS (anti-virus system). Because of the lack of data exchange mechanism, security product cannot share the security information each other and causes the large volume of alarm message or false alarm. In this case, we need a platform or system to solve this problem The security operations center can collect and manage these security events and analyzes the related information, can reduce the false positives and false negatives, and improve security of network system. In this paper, we do some research on the event correlation analysis, introduce the processes of the analysis and the method of rule extraction, and then introduce the system architecture of security operations center.
A program for calculating and displaying compatibility matrices as an aid in determining reticulate evolution in molecular sequences

Reticulate evolution in molecular sequences is caused by recombination or gene conversion, and may interfere with the reconstruction of evolutionary history. This paper presents a program which calculates compatibility matrices for detecting reticulate evolution. In addition to visual inspection of matrices, they can be analysed statistically for clustering. The method is demonstrated using human and chimpanzee gamma-globin sequences.
Control of Networked Systems Using the Scattering Transformation

In a networked control system (NCS), the plant and the controller are spatially separated and the control loop is closed through a communication network. Communication time delay in an NCS degrades the performance and may lead to instability. In this paper, the scattering transformation is applied to NCS, for the first time, in order to guarantee stability in the presence of unknown constant time delay. The scattering transformation approach in its original version relies on the assumption that all subsystems are passive. This paper extends the approach to nonpassive, static-output-feedback-stabilizable plants. We consider linear time-invariant (LTI) systems here. It is furthermore shown that no knowledge of the time delay value is necessary for the analysis and design of the closed-loop system. Lastly, experimental validation shows that the proposed approach is superior to a delay-dependent controller and the Smith predictor, as far as stability, performance, and sensitivity to time delay are concerned.
Structure, Function and Dynamics in Adenovirus Maturation

Here we review the current knowledge on maturation of adenovirus, a non-enveloped icosahedral eukaryotic virus. The adenovirus dsDNA genome fills the capsid in complex with a large amount of histone-like viral proteins, forming the core. Maturation involves proteolytic cleavage of several capsid and core precursor proteins by the viral protease (AVP). AVP uses a peptide cleaved from one of its targets as a “molecular sled” to slide on the viral genome and reach its substrates, in a remarkable example of one-dimensional chemistry. Immature adenovirus containing the precursor proteins lacks infectivity because of its inability to uncoat. The immature core is more compact and stable than the mature one, due to the condensing action of unprocessed core polypeptides; shell precursors underpin the vertex region and the connections between capsid and core. Maturation makes the virion metastable, priming it for stepwise uncoating by facilitating vertex release and loosening the condensed genome and its attachment to the icosahedral shell. The packaging scaffold protein L1 52/55k is also a substrate for AVP. Proteolytic processing of L1 52/55k disrupts its interactions with other virion components, providing a mechanism for its removal during maturation. Finally, possible roles for maturation of the terminal protein are discussed.
Trade-off between resolution and interactivity in spatial task performance

Virtual reality displays usually lag far behind classical computer graphics displays in static image quality parameters, such as resolution. Both the popular press and scientific papers often stress that resolution will have to increase greatly before users can experience virtual environments as "the real thing". Nevertheless, it is already possible to do some useful work in VR environments. The point we experimentally demonstrate here is that resolution is much less important for interactive tasks that employ immersive VR, where users can explore the environment by moving their heads and bodies, than it is in classical computer graphics applications, where users can only explore by gazing at a single picture. In the context of unmanned aerial vehicles, frame rate (read: passive camera movement) is more important than resolution for target detection, recognition, designation, and tracking. In the experiments reported here, we investigated the relative importance of various image parameters like spatial resolution (number of pixels per video frame), intensity resolution (number of gray levels per pixel), and temporal resolution (number of frame updates per second). Most experimental data concerning these resolutions come from classical psychophysics. However, experimental conditions in classical psychophysics feature stationary observers looking at short-term, pointlike flashes on stationary displays, and are thus far more representative of human interaction with pictures and photographs than with highly interactive systems like those employed in virtual reality. >