Miracle-dz/UniFAR-FTUs huggingface dataset:
A Critique of Popper's Views on Scientific Method

This paper considers objections to Popper's views on scientific method. It is argued that criticism of Popper's views, developed by Kuhn, Feyerabend, and Lakatos, are not too damaging, although they do require that Popper's views be modified some-what. It is argued that a much more serious criticism is that Popper has failed to provide us with any reason for holding that the methodological rules he advocates give us a better hope of realizing the aims of science than any other set of rules. Consequently, Popper cannot adequately explain why we should value scientific theories more than other sorts of theories; which in turn means that Popper fails to solve adequately his fundamental problem, namely the problem of demarcation. It is suggested that in order to get around this difficulty we need to take the search for explanations as a fundamental aim of science.
Habits of practice, habits of thought

The years since the launch of this journal in 2000 have been as bountiful for scholars of journalism as they have been painful for practitioners scrambling to keep up with the dizzying pace of change. Our observations and explorations over time suggest that journalistic activities – what we might call ‘habits of practice’ – seem to be changing far more dramatically than practitioners’ ‘habits of thought’, or the ways in which they conceptualise what they do or why they do it. To put it another way: The evidence we have amassed suggests dramatic change in what journalism is, offset by an equally striking resilience of core perceptions of what journalism should be.
Economic inequality enhances inferences that the normative climate is individualistic and competitive

In addition to the negative effects of economic inequality on a range of health and social outcomes, we propose that inequality should also affect how people perceive the broader normative climate in society. We predicted that people living in a more unequal (vs. equal) society are more likely to appraise the social context as one where individualism determines people's behavior. We tested this idea in three experiments by manipulating the degree of economic inequality in a fictional society. We showed that, compared to the low-inequality condition, participants in the high-inequality condition were more likely to project individualistic norms onto society. Furthermore, Experiments 2 and 3 showed that in the high- (vs. low-) economic-inequality condition, participants inferred more competition and less cooperation between people. Our results are discussed in light of the importance of the perception of a broader normative climate to explain the consequences of economic inequality.
Differential-Flatness-Based Planning and Control of a Wheeled Mobile Manipulator—Theory and Experiment

This paper presents a differential-flatness-based integrated point-to-point trajectory planning and control method for a class of nonholonomic wheeled mobile manipulator (WMM). We demonstrate that its kinematic model possesses a feedback-linearizable description due to the flatness property, which allows for full-state controllability. Trajectory planning can then be simplified and achieved by polynomial fitting method in the flat output space to satisfy the terminal conditions, while control design reduces to a pole-placement problem for a linear system. The method is then deployed on our custom-constructed WMM hardware to evaluate its effectiveness and to highlight various aspects of the hardware implementation.
The Lower Shifting of the Thresholds between 802.11a PHY Rate Modes Selection over Frequency Selective Fading Channels

Due to channel fading effects, the SNR (signal-to-noise ratio) of receiving packets forms a probabilistic distribution with the target SNR of the mobile station as the approximate mean. Performance of the packet error rates (PERs) of different received SNR values, given that the target SNR is fixed, is investigated over frequency selective fading channels. Both an analytical upper bound and a statistical average (via simulation) of the PER of individual received SNR value were obtained. This paper demonstrates that lower target SNR values gives better PER performance under the same received SNR This observation has a significant impact on the determinations of the SNR thresholds for 802.11a link adaptation. Numerical results have shown that the link adaptation thresholds between two comparative rate modes should be decreased with the lowering of target SNR values. Finally, the lower shifting of the thresholds between PHY rate modes selection of 802.11a link adaptation for different target SNR values over ETSI/BRAN channel-A model is presented.
Size reduction using Mirror Visual Feedback (MVF) reduces phantom pain

Following limb amputation patients continue to feel the vivid presence of a phantom limb. A majority of patients also experience pain in the phantom and sometimes (as in our case DS) the pain is severe. Remarkably we find that optically ‘resurrecting’ the phantom with a mirror and using a lens to make the phantom appear to shrink caused the pain to ‘shrink’ as well.
Image Colorization using Residual Networks

Given a grayscale image of a natural scene, this paper presents an approach to the estimation of a recolorization of that image. While the approach presented here is fully automatic, it has an easy insertion point for human interaction to finetune results and train improved colorizers. The system as presented is a feed-forward operation in a CNN augmented with residual connections, explicitly estimating a downsampled color histogram or color palette then using this color palette to estimate a plausible coloring of an image.
Molecular mimicry in multiple sclerosis

Two main etiological components are considered important in human autoimmune diseases including multiple sclerosis (MS), first the immunogenetic background and second environmental factors. Among the latter, infectious organisms are probably the most relevant, and epidemiological studies in MS firmly support that viral infections often precede disease exacerbations or the onset of MS. Infectious agents can contribute to disease development or phenotypic expression in different ways. Our focus will be directed on molecular mimicry, i.e. antigenic similarity between structural epitopes or peptide sequences from infectious organisms with those found in self proteins of the host. The intriguing concept of molecular mimicry has evolved substantially since its introduction over 20 years ago. We will summarize the most important developments and discuss puzzling questions, which remain open despite many claims that molecular mimicry is involved in the development of human autoimmune disease after infections or vaccinations.
XML query-update independence analysis revisited

XML transformations can be resource-costly in particular when applied to very large XML documents and document sets. Those transformations usually involve lots of XPath queries and may not need to be entirely re-executed following an update of the input document. In this context, a given query is said to be independent of a given update if, for any XML document, the results of the query are not affected by the update. We revisit Benedikt and Cheney's framework for query-update independence analysis and show that performance can be drastically enhanced, contradicting their initial claims. The essence of our approach and results resides in the use of an appropriate logic, to which queries and updates are both succinctly translated. Compared to previous approaches, ours is more expressive from a theoretical point of view, equally accurate, and more efficient in practice. We illustrate this through practical experiments and comparative figures.
On Detection of Storm Botnets

A botnet, which is a group of compromised and remotelycontrolled computers (also called bots), poses a serious threat to the Internet. The commonly-used command and control (C&C) channel for a botnet is used by a central server, such as IRC or HTTP. Recently, Storm botnet, a P2Pbased botnet with a decentralized C&C channel has appeared in the wild. In this paper, we propose a distributed approach to detection of Storm botnets at the network level. Our approach is composed of two stages. First, we identify P2P and SMTP packets from each host’s traffic. Second, we use a machine learning technique to differentiate Storm fro benign P2P traffic based on several distinguishing traffic at tributes. Both of the two stages only require packet header information without analyzing payloads. Our evaluation ha s shown the detection strategy to be effective with low false alarm rates.
Integrating Social Trust and Reputation in Resource Filtering and Recommendation Services

The amount of data and resources available on the web to- day exceeds by far any other information repository in the history of human beings. The non-central nature of web re- sources allows these resources to keep expanding endlessly. This is manifested by the enormous amount of entries any simple query can return in any search engine, which makes it impossible to be utilized as a whole by an individual user. Many domains seek minimizing these returns by using dif- ferent methods, such as prioritizing relevant resources (in- formation retreival- recommender systems), or detecting ir- relevant resources (spam detection). Although these domains look far from each other in terms of techniques used and the way results are presented, we can safely say that they all share the same goal: Information ﬁltering. In everyday life, reliability of information depends largely on the credibility of the sources from which they come. We tend to not question information that come from credible sources (people, TV Stations, Newspapers, websites.etc). Trust- ing a news outlet comes either from a personal experience (i.e.: previous interaction with this source), or from other sources citing this source as credible. This credibility can be a promising basis, on which we can build an eﬀective ﬁltering system. We take into account two levels of social trust: the relationship between information supplier and receiver, and the reputation of the supplier within the community. We are proposing an information ﬁltering model that is aware of these two levels.
A New Rounding Method Based on Parallel Remainder Estimation for Goldschmidt and Newton-Raphson Algorithms

Newton-Raphson and Goldschmidt algorithms can be sped up by using variable latency hardware architectures for rounding division, square root and their reciprocals. A new approach based on a rounding method with remainder estimate calculated concurrently with the algorithm was proposed in [5]. This paper presents an study of the hardware implementation of this approach and shows that does not suppose additional latency and avoids conventional remainder calculation most of the times. By using a CMOS 90 nm technology library different hardware architectures are presented. The results show that the expected performance improvements are obtained with reasonable increments in area (up to 5.6%), critical path (up to 6.7%) and better power performance (up to -24%).
Productive life evaluations: calculation, accuracy, and economic value.

A preliminary national evaluation of productive life was computed from records of 11 million Holsteins. Data were a mixture of projected and completed months in milk by 7 yr of age. Data were analyzed with the animal model programs currently used for yield traits. Genetic trend for productive life was positive as a correlated response to past selection for yield and type traits. Phenotypic trend was slightly negative. Active AI bulls had PTA that ranged from -1.7 to +4.3 mo and mean reliability of 56%; 3-yr-old cows had mean reliability of 29%. Yield and type PTA were almost uncorrelated with productive life PTA for active AI bulls but had positive correlations (.25 to .36) for all bulls born since 1980. An index that combines yield and productive life PTA with relative weights 2.5:1 can increase economic progress by up to 4%. Nearly identical progress can result from an index that combines yield and productive life adjusted for yield. Multitrait evaluations might produce higher reliabilities for productive life by inclusion of correlated traits measured earlier in life such as yield, type, and somatic cell score.
Learning Styles, Culture and Inclusive Instruction in the Multicultural Classroom: A Business and Management Perspective

This article examines the learning style profile exhibited by students in a multicultural class of international business management, and how cultural conditioning is reflected in the learning style preferences of home and international students. Using the Felder and Soloman's Index of Learning Styles , this study finds that each learning style dimension measured by the instrument is amply represented and that the scores reported by international students on all but one learning style dimension show much wider measures of dispersion compared to those of home students suggesting that greater variations in learning preferences are likely to co-exist in culturally heterogeneous cohorts. Suggestions on how to move toward a multistyle teaching approach to business management education so as to enfranchise all students in the multicultural classroom are then put forward. Finally, a discussion of the implications of these findings with respect to the business management curriculum design is provided.
Software Process Recovery: Recovering Process from Artifacts

Often stakeholders, such as developers, managers, or buyers, want to find out what software development processes are being followed within a software project. Their reasons include: CMM and ISO 9000 compliance, process validation, management, acquisitions, and business intelligence. Recovering the software development processes from an existing project is expensive if one must rely upon manual inspection of artifacts and interviews of developers and their managers. Researchers have suggested live observation and instrumentation of a project to allow for more measurement, but this is costly, invasive, and also requires a live running project. Instead, we propose an after the fact analysis: software process recovery. This approach analyzes version control systems, bug trackers and mailing list archives using a variety of supervised and unsupervised techniques from machine learning, topic analysis, natural language processing and statistics. We can combine all of these methods to recover process events that we map back to software development processes like the Unified Process. We can produce diagrams called Recovered Unified Process Views (RUPV) that are similar to the Unified Process diagram, a time-line of effort per parallel discipline occurring across time. We then validate these methods using case studies of multiple open source software systems.
Sparsity as Cellular Objective to Infer Directed Metabolic Networks from Steady-State Metabolome Data: A Theoretical Analysis

Since metabolome data are derived from the underlying metabolic network, reverse engineering of such data to recover the network topology is of wide interest. Lyapunov equation puts a constraint to the link between data and network by coupling the covariance of data with the strength of interactions (Jacobian matrix). This equation, when expressed as a linear set of equations at steady state, constitutes a basis to infer the network structure given the covariance matrix of data. The sparse structure of metabolic networks points to reactions which are active based on minimal enzyme production, hinting at sparsity as a cellular objective. Therefore, for a given covariance matrix, we solved Lyapunov equation to calculate Jacobian matrix by a simultaneous use of minimization of Euclidean norm of residuals and maximization of sparsity (the number of zeros in Jacobian matrix) as objective functions to infer directed small-scale networks from three kingdoms of life (bacteria, fungi, mammalian). The inference performance of the approach was found to be promising, with zero False Positive Rate, and almost one True positive Rate. The effect of missing data on results was additionally analyzed, revealing superiority over similarity-based approaches which infer undirected networks. Our findings suggest that the covariance of metabolome data implies an underlying network with sparsest pattern. The theoretical analysis forms a framework for further investigation of sparsity-based inference of metabolic networks from real metabolome data.
Apologiae Ontologiae

Treatment of meaning in NLP is greatly facilitated if semantic analysis and generation systems rely on a language-neutral, independently motivated world model, or ontology. However, the beneﬁts of the ontology are somewhat offset in practice by the difﬁculty of its acquisition. This is why a number of computational linguists make a conscious choice to bypass ontology in their semantic deliberations. This decision is often jus-tiﬁed by questioning the principles underlying ontologies and by challenging the ontology-based semantic enterprise on the grounds of its ostensible irreproducibility. In this paper we illustrate, on the example of the lexicon entry for the Spanish verb dejar , the expressive power of lexical-semantic descriptions based on the ontology used in the Mik-rokosmos machine translation project. This expressive power is compared with that of some of the non-ontological approaches to lexical semantics. We argue that these approaches in reality rely on ontologies in everything but name. We offer a view of ontologies as theories of lexical-semantic descriptions. We posit that no underlying principles for ontologies are possible and explain why the charge of irreproducibility is not valid.
Testing by means of inductive program learning

Given a program P and a set of alternative programs //’, we generate a sequence of test cases that are adequate, in the sense that they distinguish the given program from all alternatives The, m(,thod is related to fault-based approaches to test case generation, but programs in P need not he s]mp]e mutations of P. The technique for generating an adequate test set is based on the inductive learning of programs from finite sets of input-output examples: given a partial test set. we generate inductively a program P’ E P which is consistent with P on those input values; then we look for an input value that distinguishes P from P’, and we repeat the process until no program except P can be induced from the generated examples. We show that the obtained test set is adequate with respect to the alternatives belonging to P. The method IS made possible by a program induction procedure which has evolved from recent research in mnchine Iei]rnlng and inductive logic programming. An implemented version of the test case ~encration procedure is demonstrated on simple and more complex list-processing programs. and tb(, scalability of’ the approach is discussed,
How mental simulation evokes negative affective misforecasting of hedonic experiences

Purpose The purpose of this paper is to investigate the relationship between mental simulation and affective misforecasting of hedonic consumption experiences. Design/methodology/approach The authors present a series of lab and field studies that manipulate mental simulation and experience type (ordinary versus extraordinary) and measure affective misforecasting and mindfulness. Data were analyzed using a combination of ANOVA and PROCESS. Findings Mental simulation before an experience causes negative affective misforecasting to occur for extraordinary experiences but not ordinary experiences. The authors further show that mindfulness mediates the effect of mental simulation on affective misforecasting. Practical implications The findings provide insight into how thinking about experiences before consumption affects consumers’ actual engagement with the experience. This paper suggests that, by encouraging consumers to mentally simulate their experiences before consumption, marketers may cause consumers to miss out on enjoying their experiences to the fullest. Instead, marketers may want to maintain some mystique by encouraging consumers to “come see for themselves”. Originality/value The authors demonstrate a novel cause of affective misforecasting: mental simulation before the experience and provide initial evidence in support of a novel psychological process explanation (i.e. mindfulness) for the effect of mental simulation on affective misforecasting.
Anticipatory routing for highly mobile endpoints

We consider the problem of routing to endpoints with very high "effective" mobility, i.e, when the period between changes in an endpoint's location is comparable to the time it takes for the location tracking mechanism to converge. This could happen due to increased endpoint speed, increased control message latency, or decreased cell size. When this happens, conventional location tracking approaches fail - by the time such mechanisms converge, the endpoint has already moved to a new location, and we say the "reactive limit" has been reached. When mobility exceeds the reactive limit, prediction techniques are required for network control. We describe "anticipatory routing", a mechanism that uses a limited history of past movement of the endpoint to predict its future locations. In particular, we use linear regression to predict future locations and affiliation/departure times of the endpoint. Using a simulation model of a multi-hop wireless network, we study the performance of anticipatory routing. Our results indicate that above a certain mobility threshold, anticipatory routing significantly outperforms conventional location tracking mechanisms. Its magnitude of improvement increases with higher mobility - in particular, its rate of throughput degradation with speed is 56% better.
An ontology semantic tree based natural language interface

As more and more ontology knowledge bases have been published, every user may have access to a wealth of knowledge. However, to acquire the information in ontologies, users have to be familiar with ontologies and its formal query language. Therefore, natural language interfaces (NLI) have been proposed in recent years to bridge the gap between ontologies and non-expert users. Traditional approaches have pretty broad coverage of natural language (NL) and good performance on wellorganised NL queries. But they are subject to the word order, due to the lack of original semantic information of queries. This paper proposes a NLI which accepts NL as input and generates SPARQL (SPARQL Protocol and RDF Query Language) queries as output. To analyze the NL queries, the ontology semantic tree has been used to represent the semantic conceptual structure of NL queries with the support of ontology. Our results show that the proposed system can make use of semantic structure effectively and has a better performance than the baseline system on the queries with flexible word order.
A Parallel Q-Method for a Semiconductor Laser Array Model

A time-dependent, two-dimensional model of a semiconductor laser array is numerically studied by means of Θand Newton-Raphson methods. A parallel version of the BiCGSTAB algorithm for the solution of the linear equations resulting from the Newton-Raphson technique is presented. It is shown that the proposed method reduces by half the number of messages and, by means of communications overlapping, allows to achieve a near-to-perfect speedup in the computations.