Miracle-dz/UniFAR-FTUs huggingface dataset:
Effort Estimation in Co-located and Globally Distributed Agile Software Development: A Comparative Study

Context: Agile methods are used both by both co-located and globally distributed teams. Recently separate studies have been conducted to understand how effort estimation is practiced in Agile Software Development (ASD) in co-located and distributed contexts. There is need to compare the findings of these studies. Objectives: The objective of this comparative study is to identify the similarities and differences in how effort estimation is practiced in co-located and globally distributed ASD. Method: We combined the data of the two surveys to conduct this comparative study. First survey was conducted to identify the state of the practice on effort estimation in co-located ASD, while the second one identified the same in globally distributed ASD context. Results: The main findings of this comparative study are: 1) Agile practitioners, both in co-located and distributed contexts, apply techniques that use experts' subjective assessment to estimate effort. 2) Story points are the most frequently used size metrics in both co-located and distributed agile contexts 3) Team's prior experience and skill level are leading cost drivers in both contexts. Distributed agile practitioners cited additional cost drivers related to the geographical distance between distributed teams. 4) In both co-located and distributed agile context, effort is estimated mainly at iteration and release planning levels 5) With regard to the accuracy of effort estimates, underestimation is the dominant for both co-located and distributed agile software development. Conclusions: Similar techniques and size metrics have been used to estimate effort by both co-located and distributed agile teams. The main difference is with regard to the factors that are considered as important cost drivers. Global barriers due to cultural, geographical and temporal differences are important cost and effort drivers for distributed ASD. These additional cost drivers should be considered when estimating effort of a distributed agile project to avoid gross underestimation.
Reducing gradient imperfections for spiral magnetic resonance spectroscopic imaging

Spiral k‐space magnetic resonance spectroscopic imaging (MRSI) requires high performance from gradient hardware systems. During the readout phase, oscillating gradients are continuously played out, which can cause undesired effects. These effects on the quality of SI data are non‐intuitive because of their time‐varying nature. In this work we describe the effects of undesirable gradient performance on SI. Measurements of the true readout trajectories were performed and the results were then used in the reconstruction process. The effects of these imperfections resulted in a spatially and spectrally varying amplitude and frequency modulation. The use of the measured trajectories in the reconstruction process yielded an up to 20% increase in signal amplitude recovery. Magn Reson Med, 2006. © 2006 Wiley‐Liss, Inc.
A Chemical and Thermal Resistant Wafer Bonding Adhesive Simplifying Wafer Backside Processing

A variety of adhesives have been demonstrated for use in thinning and backside processing of III-V substrates. Each process exhibits certain limitations based on the adhesive’s chemical or thermal resistance. As a result, an adhesive’s property limitation may drive up costs or reduce throughput by necessitating the use of additional protective aids or special tooling. A new product developed by Brewer Science, Inc. (BSI), WaferBONDTM adhesive, eliminates the need for such aids by directly simplifying the process. WaferBONDTM adhesive exhibits an unusually high resistance to process conditions, which enables the use of strong acids and bases, stripping solvents, and temperatures in excess of 200oC. Applied with conventional spin-on equipment, the material coats with exceptional uniformity (<0.3% TTV), cures and bonds at relatively low temperatures, and demounts in corrosion-safe chemistries in times that are substantially lower than the competition, which allow an increase in throughput. This paper discusses the benefits of the WaferBONDTM adhesive mounting product and the ease of integrating it into an existing process line.
Derivation of extended Gaussian functions based on the Zak transform

Siohan and Roche introduced recently a new family of modulated filter banks, which was derived from a set of continuous-time orthogonal functions named extended Gaussian functions (EGFs). At first, these EGFs were obtained using the isotropic orthogonal transform algorithm (IOTA), i.e., a two-step orthogonalization procedure of the Gaussian function. As shown recently, using the Zak transform, the IOTA method yields the tight window function canonically associated with the Gaussian. In this letter, it is shown that the Zak transform can also be useful in recovering the series expansion of the EGFs. Practical guidelines are also provided in order to get accurate approximations of the orthogonal EGFs.
The Molecular Adapter Carma1 Controls Entry of IκB Kinase into the Central Immune Synapse

Carma1 (also known as caspase recruitment domain [CARD]11, Bimp3) is a CARD-containing membrane-associated guanylate kinase family protein that plays an essential role in antigen receptor–induced nuclear factor κB activation. We investigated the role of Carma1 in the assembly of signaling molecules at the immune synapse using a peptide-specific system. We report that Carma1 is essential for peptide-induced interleukin 2 and interferon γ production, but dispensable for proliferation in T cells. Recruitment and distribution of T cell receptor, lymphocyte function associated 1, lipid rafts, and protein kinase C (PKC)θ to central and peripheral immune synapse regions occur normally in Carma1 − / − T cells. Carma1 controls entry of IκB kinase (IKK) into lipid raft aggregates and the central region of the immune synapse, as well as activation of IKK downstream of PKC. Our data provide the first genetic evidence on a new class of molecular scaffold that controls entry of defined signaling components, IKK, into the central supramolecular activation cluster at T cell–antigen-presenting cell interfaces without having any apparent effect on the overall organization and formation of immune synapses.
Over-Confidence and Entrepreneurial Choice Under Ambiguity

Entrepreneurship studies have attributed to over-confidence decisions to start a new venture. Many decision situations, through which over-confidence is measured, entail some degrees of uncertainty, (e.g., related to own skill or to competition). The aspect of uncertainty is largely neglected in over-confidence studies or entrepreneurial research. Both uncertainty and over-confidence influence individuals’ likelihood perceptions. Nevertheless, these two aspects are seldom jointly investigated, and the little evidence provides inconclusive results. In this study, we experimentally investigate how uncertainty, as a property of the situation, and over-confidence, as a characteristic of decision makers’ beliefs, influence choice behavior. Our findings with Executive MBA participants show that over-confident decision makers choose less uncertain options for low likelihood outcomes and more uncertain options for high likelihood outcomes, contrary to neutral confidence decision makers, whose choices are in line with standard Prospect Theory predictions
Organizational collaboration: effects of rank on collaboration

Motivation -- Organizational change initiatives often fail resulting in wasted time, money, and human resources. Many organizational changes such as the implementation of new technology are driven by high ranking personnel. However, these changes are often executed by junior ranking personnel. Thus, potential conflicts can arise if there are mismatches between these groups regarding organizational perceptions. The present study sought to understand if different levels of rank influenced perceptions of organizational collaboration in an Air Force domain. Research approach -- Participants (N=236) from a military logistics Command and Control (C2) center participated in an organizational questionnaire which included a measure of organizational collaboration. Based on their rank, participants were categorized into senior, mid-level, and junior groups. Group differences in collaboration perceptions were tested. Findings/Design -- The findings suggested that rank effects perceived quality of organizational collaboration. Overall, junior ranking personnel reported lower organizational collaboration perceptions compared to senior ranking personnel. Research limitations/Implications -- Due to the exploratory nature of this study and the paucity of collaboration research in general, the generalizability of the results beyond the domain of knowledge work are unclear. Though just a pilot study, the results of this research suggest that organizational leaders must be aware of and acknowledge different perspectives from the range of personnel in their organizations prior to planning organizational changes, such as new technology, policies, and job design. Such changes may have a very different impact on military personnel depending on their organizational beliefs, which in turn, appear to be influenced by their hierarchical status in the organization (i.e., rank). Take away message -- The results suggest that rank does play a significant role in the perceived quality of organizational collaboration across several factors including, general collaboration attitudes, adaptability to new technology, collaboration enablers, as well as job characteristics.
Trade and the Comovement of Stock Returns: Evidence from Japan

In April 2000, in one day, 30 stocks were replaced in the Nikkei 225 index in Japan. We analyze the change in comovement of returns of stocks added to and deleted from the index with the returns of stocks remaining in the index. A simple model shows that upon inclusion into (deletion from) a stock index, stocks should begin to comove more (less) with the index, due to a change in their trading pattern. The empirical findings provide sound support for these predictions: In the sample, daily index betas of the added stocks rose by an average of 0.60, while the average beta of the deleted stocks fell by 0.71. Our results confirm additional predictions of the model for changes in R2, turnover, and the autocorrelation of returns upon index inclusion and deletion, and hold at daily, weekly and bi-weekly return horizons. Fundamentals based explanations fail to account for these findings. We conclude that correlated trading of index stocks causes excess comovement of stock returns. We argue that the distinct trading mechanism on the Tokyo Stock Exchange contributes to the significance and magnitude of our results.
A Numerical Simulation of Transport and Biodegradation in Saturated Porous Media

The present paper describes a numerical model, which allows to compute solute transport and biodegradation in a saturated porous media. Mathematical formulation of such processes leads to a set of non- linear partial differential equations coupled to ordinary differential equations. The transport equation is approximated by a finite volume scheme whereas biodegradation equations are treated separately as a system of ordinary differential equations. Numerical results for biorestoration using Monod kinetics are presented.
Current Experience in Testing Mitochondrial Nutrients in Disorders Featuring Oxidative Stress and Mitochondrial Dysfunction: Rational Design of Chemoprevention Trials

An extensive number of pathologies are associated with mitochondrial dysfunction (MDF) and oxidative stress (OS). Thus, mitochondrial cofactors termed “mitochondrial nutrients” (MN), such as α-lipoic acid (ALA), Coenzyme Q10 (CoQ10), and l-carnitine (CARN) (or its derivatives) have been tested in a number of clinical trials, and this review is focused on the use of MN-based clinical trials. The papers reporting on MN-based clinical trials were retrieved in MedLine up to July 2014, and evaluated for the following endpoints: (a) treated diseases; (b) dosages, number of enrolled patients and duration of treatment; (c) trial success for each MN or MN combinations as reported by authors. The reports satisfying the above endpoints included total numbers of trials and frequencies of randomized, controlled studies, i.e., 81 trials testing ALA, 107 reports testing CoQ10, and 74 reports testing CARN, while only 7 reports were retrieved testing double MN associations, while no report was found testing a triple MN combination. A total of 28 reports tested MN associations with “classical” antioxidants, such as antioxidant nutrients or drugs. Combinations of MN showed better outcomes than individual MN, suggesting forthcoming clinical studies. The criteria in study design and monitoring MN-based clinical trials are discussed.
EXPECTATIONS OF IMPROVED STUDENT LEARNING: GENERAL EDUCATION ASSESSMENT IN AQIP COMMUNITY COLLEGES

This qualitative multi-case study identified institutional structures and assessment processes that support general education learning outcomes assessment initiatives at three community colleges accredited by the Higher Learning Commission under the Academic Quality Improvement Program (AQIP). In support of this purpose, data collection involved semi-structured interviews with three types of positions – Chief Academic Officer, lead administrator for assessment, and faculty holding a leadership position in support of general education assessment. Documents related to assessment and accreditation status were also reviewed to allow for comprehensive collection of evidence and triangulation of data. Primary topics within the five guiding questions for this study included (a) institutional structures that support assessment, (b) processes to accomplish assessment of general education learning outcomes, (c) ways senior leaders support assessment, (d) elements that allowed an institution to reach the results and implementation stages of assessment, and (e) steps taken to improve student learning based on assessment results. Upon analysis of the data gathered, four strategies emerged as ways community colleges could be better prepared to use assessment results, implement improvement efforts, and document subsequent changes in student learning. These strategies are to (a) spread and connect responsibilities for assessment to adjunct faculty and administrators across the institution, (b) locate where general education learning outcomes are present in the curriculum, (c) link resources invested in assessment efforts
Analysis of Emotion Recognition System through Speech Signal Using KNN & GMM Classifier

In machine interaction with human being is yet challenging task that machine should be able to identify and react to human non-verbal communication such as emotions which makes the human computer interaction become more natural. In present research area automatic emotion recognition using speech is an essential task which paid close attention. Speech signal is a rich source of information and it is an attractive and efficient medium due to its numerous features of expressing approach & extracting emotions through speech is possible. In this paper emotions is recognized through speech using spectral features such as Mel frequency cepstrum coefficient prosodic features like pitch , energy and were utilized & study is carried out using K- Nearest Neighbor classifiers and Gaussian mixture model classifier which is used for detection of six basic emotional states of speaker's such as anger ,happiness , sadness , fear , disgust and neutral using Berlin emotional speech database.
Functional Complementation of sir2Δ Yeast Mutation by the Human Orthologous Gene SIRT1

Sirtuins, class III histone deacetylases, are proteins homologous to the yeast protein Sir2p. Mammalian Sirt1 has been shown to be involved in energy metabolism, brain functions, inflammation and aging through its deacetylase activity, acting on both histone and non-histone substrates. In order to verify whether Sirt1 can replace Sir2p in the yeast cells, we expressed the full-length human Sirt1 protein in S.cerevisiae sir2Δ mutant strain. The structure of chromatin is basically maintained from yeast to human. Thus, yeast chromatin is a favourable environment to evaluate, inhibit or activate an ectopic histone deacetylase activity in an in vivo substrate. Mutant sir2Δ shows a series of different phenotypes, all dependent on the deacetylase activity of Sir2p. We analyzed the three silent loci where normally Sir2p acts: ribosomal DNA, telomeres and the mating type loci. Moreover, we verified extrachromosomal ribosomal DNA circles production and histone hyperacetylation levels, typical marks of sir2Δ strains. By strong SIRT1 overexpression in sir2Δ cells, we found that specific molecular phenotypes of the mutant revert almost to a wild-type condition. In particular, transcriptional silencing at rDNA was restored, extrachromosomal rDNA circles formation was repressed and histone acetylation at H3K9 and H4K16 decreased. The complementation at the other studied loci: HM loci, telomere and sub-telomere does not occur. Overall, our observations indicate that: i) SIRT1 gene is able to complement different molecular phenotypes of the sir2Δ mutant at rDNA ii) the in vivo screening of Sirt1 activity is possible in yeast.
Duty cycle adapted MAC for Wireless Sensor Networks with energy harvesting

Wireless Sensor Networking is an important area of research due to its wide and varied applications, especially in environmental monitoring and health monitoring. Battery-powered Wireless Sensor Networks (WSNs) face the problem of limited lifetime due to fast depletion of charge of typical batteries. The incorporation of energy harvesting in WSNs thus becomes crucial for extending the lifetime of battery-powered WSNs, while enhancing the network performance. The Medium Access Control (MAC) protocol has to be properly designed so as to ensure proper operation of the sensor nodes in WSNs with energy harvesting. This paper presents a MAC protocol for energy harvesting WSNs, based on IEEE 802.15. 4 MAC, which takes into account the power consumption of the sensor nodes during operation and the battery discharge characteristics. This MAC protocol also employs duty cycle adaptation based on node energy.
Mining & Optimization of Association Rules Using Effective Algorithm

— Association Rule Mining is generally performed in Generation of frequent item sets & Rule generation. Mining association rules is not full of reward until it can be utilized to improve decision-making process of an organization. This paper is concerned with discovering positive and negative association rules. We present an Apriori-based algorithm that is able to find all valid positive and negative association rules in a support confidence framework. The algorithm can find all valid association rules quickly and overcome some limitations of the previous mining methods. The complexity and large size of rules generated after mining have motivated researchers and practitioners to optimize the rule, for analysis purpose. This optimization can be done using Genetic Algorithm.
Robust line tracking using a particle filter for camera pose estimation

This paper presents a robust line tracking approach for camera pose estimation which is based on particle filtering framework. Particle filters are sequential Monte Carlo methods based on point mass (or "particle") representations of probability densities, which can be applied to any state-space model. Their ability to deal with non-linearities and non-Gaussian statistics allows to improve robustness comparing to existing approaches, such as those based on the Kalman filter. We propose to use the particle filter to compute the posterior density for the camera 3D motion parameters. The experimental results indicate the effectiveness of our approach and demonstrate its robustness even when dealing with severe occlusion.
Why are Americans Addicted to Baseball? An Empirical Analysis of Fandom in Korea and the United States

Theories of rational addiction posit that certain habit -forming goods "characterized by an increasing marginal utility of consumption "generate predictable dynamic patterns of consumer behavior. It has been suggested that attendance at sporting events represents an example of such a good, as evidenced by the pricing strategies of commercial sports interests. In this essay, we provide new evidence in support of rational addiction for the case of Major League Baseball, but fail to find such support in data from the Korean Professional Baseball League. We then review the scientific literature on sports fans from the perspective of human behavioral ecology and propose a theory of endogenous habit formation among sports fans that could explain our findings.
Adaptive Improved RLS Algorithm for Blind Source Separation

Based on an adaptive combination of two RLS-type algorithms with different forgetting factor, an effective scheme is proposed to improve the performance of the RLS-type algorithm for blind source separation. A mixing parameter for adjusting the proportion of the two RLS algorithms is introduced in an attempt to put together the best properties of them, and its adaptive rule is obtained by means of a natural gradient criterion. Experimental results demonstrate the good performance of the proposed approach in different kinds of environments. Streszczenie. W artykule przedstawiono nową, efektywniejszą strukture algorytmu RLS do ślepej separacji sygnalow, bazującą na adaptacyjnej kombinacji dwoch takich algorytmow z roznymi wspolczynnikami wazenia. W celu uzyskania jak najlepszego wykorzystania ich wlasności, zastosowano parametr, ktory pozwala na ich dostrojenie. Wyniki eksperymentalne potwierdzają skutecznośc dzialania. (Ulepszony algorytm adaptacyjny RLS do ślepej separacji sygnalow).
An Analysis of Unified Modeling Language ( UML ) Graphical Constructs Based on BWW Ontology

The Unified Modeling Language (UML) is a visual modeling language dominant in objectoriented software development. This language was adopted by the Object Management Group (OMG) as its standard modeling language in 1997. UML 1.x defines nine diagramming techniques: Class diagram, Object diagram, Component diagram, Deployment diagram, Use Case diagram, State-chart diagram, Activity diagram, Sequence diagram, and Collaboration diagram (Booch et al., 1999). UML 2.x defines thirteen diagramming techniques: Class Diagram, Object diagram, Component diagram, Composite Structure diagram, Package diagram, Deployment diagram, Use Case diagram, Sequence diagram, Communication diagram, State diagram, Activity diagram, Timing diagram, and Interaction Overview diagram (Booch et al., 2005). These diagrams are interrelated and depict different aspects of the problem domain. Since its introduction, UML has been a popular research topic (e.g., Siau & Cao, 2001; Siau & Tan, 2006; Gemino & Parker, 2009; Siau & Tian, 2009; VanderMeer & Dutta, 2009). Many of these research studies evaluate the usability of UML (e.g., Siau & Lee 2004, Siau & Wang, 2007;, Reinhartz-Berger & Sturm, 2008). Evaluation studies on UML have pointed to the difficulty in learning UML ABSTrACT