Miracle-dz/UniFAR-FTUs huggingface dataset:
HOW DO SUPPLIERS BENEFIT FROM IT USE IN SUPPLY CHAIN RELATIONSHIPS ?

Supply chain management systems (SCMS) championed by network leaders in their supplier networks are now ubiquitous. While prior studies have examined the benefits to network leaders from these systems, little attention has been paid to the benefits to supplier firms. This study draws from organizational theories of learning and action and transaction cost theory to propose a model relating suppliers’ use of SCMS to benefits. It proposes that two patterns of SCMS use by suppliers– exploitation and exploration–create contexts for suppliers to make relationship-specific investments in business processes and domain knowledge. These, in turn, enable suppliers to both create value and to retain a portion of the value created by the use of these systems in interfirm relationships. Data from 131 suppliers using an SCMS implemented by one large retailer support hypotheses that relationship-specific intangible investments play a mediating role linking SCMS use to benefits. Evidence that patterns of IT use are significant determinants of relationship-specific investments in business processes and domain expertise provides a finer-grained explanation of the logic of IT-enabled electronic integration. The results support the vendors-to-partners thesis that IT deployments in supply chains leads to closer buyer-supplier relationships (Bakos and Brynjyolfsson 1993). The results also suggest the complementarity of the transaction-cost and resource-based views, elaborating the logic by which specialized assets can also be strategic assets.
A Review of Recent Advances in Speaker Diarization with Bayesian Methods

This chapter aims to present some of the recent Bayesian approaches to speaker diarization (SD). SD is the task of grouping an audio document into homogenous regions, where each region should ideally correspond to the complete set of utterances that belong to a single speaker. Rich transcription, speaker adaptation of speech recognition systems and speaker recognition are some of the applications that require such a clustering procedure. Broadcast News, meeting, and telephone conversations are the main domains that SD is applied to. SD is a fully unsupervised clustering task. Not only we are not allowed to use any target-speaker enrollment data to detect the target speakers through the acoustic stream, but the number of speakers should be considered as an unknown, too. Moreover, text-independence should also be assumed, meaning that no transcript is available, either. Despite the effectiveness of several approaches and frameworks that have been proposed and tested in literature, the most natural and systematic approach to SD is to treat it as a model’s order selection task. Once the order is estimated (i.e. the number of speakers) the task reduces to a familiar (but not trivial at all) machine learning task where the latent variables (i.e. the speaker indicators of each utterance) of given cardinality should be estimated from the observations. Therefore, a major issue we deal with is how to assess the number of speakers in a way that is simultaneously robust and efficient. Bayesian machine learning is a highly principled paradigm and can naturally tackle model selection problems. It does so by applying consistently the rules of probability in order to infer the desired quantities, including the order of the model. Its superiority over the frequentistic statistical framework (e.g. Maximum Likelihood estimates, Classical Hypothesis testing) or semi-Bayesian approaches (e.g. MAP estimation, penalized maximum likelihood criteria) in model selection, averaging and density estimation has been verified in most (if not all) of the speaker related tasks, including identification and verification. Several drawbacks however still exist, most of which stem from the intractability of the majority of the ideal Bayesian solutions. Many well known and effective machine learning tools cannot be applied or require severe adaptation that may drastically increase their computational complexity. Nevertheless, the introduction of powerful approximate inference method (e.g. Variational Bayes, Expectation Propagation), novel Markov-Chain Monte Carlo techniques, along with the rapid development of the Bayesian nonparametric models 11
Reconstitution of Retrograde Transport from the Golgi to the ER In Vitro

Retrograde transport from the Golgi to the ER is an essential process. Resident ER proteins that escape the ER and proteins that cycle between the Golgi and the ER must be retrieved. The interdependence of anterograde and retrograde vesicle trafficking makes the dissection of both processes difficult in vivo. We have developed an in vitro system that measures the retrieval of a soluble reporter protein, the precursor of the yeast pheromone α-factor fused to a retrieval signal (HDEL) at its COOH terminus (Dean, N., and H.R.B Pelham. 1990. J. Cell Biol. 111:369–377). Retrieval depends on the HDEL sequence; the α-factor precursor, naturally lacking this sequence, is not retrieved. A full cycle of anterograde and retrograde transport requires a simple set of purified cytosolic proteins, including Sec18p, the Lma1p complex, Uso1p, coatomer, and Arf1p. Among the membrane-bound v-SNAP receptor (v-SNARE) proteins, Bos1p is required only for forward transport, Sec22p only for retrograde trafficking, and Bet1p is implicated in both avenues of transport. Putative retrograde carriers (COPI vesicles) generated from Golgi-enriched membranes contain v-SNAREs as well as Emp47p as cargo.
Femal Representation - Is it Important for Policy Decisions?

This paper studies whether the degree of female representation in Swedish local councils affects local public expenditure patterns. Theoretically, the individual preferences of elected representatives may impact public expenditure if full policy commitment is not feasible. To empirically address the question I first analyze the preferences expressed by elected local council representatives using survey data. This permits me to make precise predictions about the effects of female representation on spending. The subsequent panel study on the composition of public spending in Swedish municipalities supports the predictions derived from the survey.
Weighting of the k-Nearest-Neighbors

This paper presents two distribution independent weighting schemes for k-Nearest-Neighbors (kNN). Applying the first scheme in a Leave-One-Out (LOO) setting corresponds to performing complete b-fold cross validation (b-CCV), while applying the second scheme corresponds to performing bootstrapping in the limit of infinite iterations. We demonstrate that the soft kNN errors obtained through b-CCV can be obtained by applying the weighted kNN in a LOO setting, and that the proposed weighting schemes can decrease the variance and improve the generalization of kNN in a CV setting.
Optical flares from the faint mid-dM star 2MASS J00453912+4140395

We present B and V light curves of a large stellar flare obtained with the Wide Field Camera at the Isaac Newton 2.5-m telescope (La Palma). The source object is a faint (mV = 21.38) foreground star in the field of the Andromeda galaxy, with its most probable spectral type being dM4. We provide an estimate of the total flare energy in the optical range and find it to be of the order of 1035 erg. The cooling phase of the large flare shows three additional weak flare-like events, which we interpret as results of a triggering mechanism also observed on the Sun during large coronal mass ejections. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
The Impact of Economic Development on Land Mortgage Financing in Nigeria

This study examined the impact of economic development on land mortgage financing in Nigeria using Delta State as a case. The main aim is to ascertain the contributions of predictor variables such as Year, Gross Domestic Product (GDP), Money in Circulation (MC), Lending Rate (LR), Headline inflation rate (HI) and Core inflation rate (CI) on the variations on land mortgage transactions in Delta State. Secondary source of data collection was employed in this study and the multiple regression analysis was used to fit the model assuming a 95% confidence level. The result of the study revealed that the independent variables were able to explain most behavior of the dependent variable (number of land mortgage transaction) within the observed period. It was also found that the explanatory factors contributed to the model significantly. In addition, it was observed that the factors responsible for the significant contribution were variable Year and lending rate. However, variables such as Gross domestic product (GDP), volume of Money in circulation (MC), Headline Inflation (HI) and Core Inflation (CI) did not contribute significantly to the characteristics of land mortgage transaction in Delta state. The model obtained has strong reliability since the coefficient of determination of the model obtained was about 91.2% which validates strong prediction power of the model. It was observed that as land mortgage transaction increases lending rate decreases by 20.76 coefficient measure.
Use of Duplex Reactor in an Oil Refinery

In order to reduce short-circuit level in a power augmentation generation project in an oil refinery, it installed a duplex reactor as an alternative solution when comparing to usual techniques. Duplex reactor concept was born in the beginning of XX century, and its application is similar to conventional series reactors: limiting system maximum short-circuit current to match rated equipment short-circuit duty, protecting personal and electrical installations. However, in some electrical networks, duplex reactors have best performances than conventional ones. Selection of duplex reactor instead of other classical options is discussed in this paper. Technical and economic characteristics about the duplex reactor are also presented along this paper.
Fair and Comprehensive Performance Evaluation of 14 Second Round SHA-3 ASIC Implementations

Hardware implementation quality will be considered as an important factor for evaluating the NIST SHA-3 competition candidates in the second round. The most traditional and popular hardware im­ plementation method is designing ASICs with standard cells. However, to benchmark 14 second round SHA-3 ASIC designs based on a fair and comprehensive methodology can be very challenging because of the unde­ fined application scenarios, various choices of technologies and multiple optimization goals. In this paper we describe a consistent and system­ atic approach to move a SHA-3 hardware benchmark process from FPGA prototyping to ASIC implementation, and we present our latest results for ASIC evaluation of the 14 second round SHA-3 candidates. The ef­ fort reported in this paper is complementary to the effort reported in the SHA-3 conference submission ”How can we conduct fair and consistent hardware evaluation for SHA-3 candidates? ” [4].
A LITERATURE REVIEW OF ONLINE TRUST IN BUSINESS TO CONSUMER E-COMMERCE TRANSATIONS, 2001-2006

The purpose of this research is to examine previous literatures which focus on trust in Business to Consumer (B2C) of e-commerce transactions between 2001 and 2006. All selected papers are analyzed through a conceptual framework to recognize the context and nature of trust. The working process includes three primary phases: selecting and focusing phase, analyzing phase, and concluding and outcome-converging phase, which enhance the fulfillment of analysis and the accumulation of knowledge in the domain of B2C trust researches. In the future, the research in this area need clearly indicate how proposed models are tested base on theory, and the nature of B2C trust researches must be identified more detailed, additionally, improving the oversimplification of the trust nature. Moreover, the researchers should associate the focal point with comprehensive in the future.
LHIP : Interpreting Extended DCGs for Applied Grammar Development

This paper describes LHIP (Left-Head corner Island Parser), a parser designed for broadcoverage handling of unrestricted text. The system interprets an extended DCG formalism to produce a robust analyser that nds parses of the input made from \islands" of terminals (corresponding to terminals consumed by successful grammar rules). It is currently in use for processing dialogue transcripts from the HCRCMap Task Corpus (Anderson et al., 1991), although we expect its eventual applications to be much wider. 1 Transcribed natural speech contains a number of frequent characteristic `ungrammatical' phenomena: lled pauses, repetitions, restarts, etc. (as in e.g. Right I'll have : : :you know, like I'll have to : : : so I'm going between the picket fence and
Development of a Visual Service Design Tool providing a mapping from BPMN to JIAC

Although they have been topic to academic research for several years and although they are often seen as the next step towards truly reusable and modular programs, multi-agent systems are still underrepresented in the industry. At the same time web-services and service oriented architectures are adopted much faster in the same domain. A possible reason for this can be found in the lack of easy-to-use tools for the model driven creation of multi-agent systems. In this thesis a tool for the model driven development of programs for the multi-agent system JIAC will be presented. For this purpose a mapping from business process diagrams based on the Business Process Modeling Notation to JIAC IV has been developed. Based on the Eclipse framework a visual editor for the creation of BPMN diagrams has been implemented. Diagrams created with this editor can be validated and translated to executable JIAC programs using a rule based transformation tool.
Sensing Action and Knowledge Reasoning Independent of Designer

This paper proposes a method for action reasoning independent of designer. It is needed that the external designer writes out axioms for the agents when expressing their sensing actions and knowledge reasoning in traditional situation calculus action theory, and agent's knowledge in action reasoning is described by an accessibility relation K(s', s). Because K(s', s) must be defined by the designer in advance, this kind of knowledge expression is dependent of the. designer. So, the action reasoning including sensing actions and knowledge is a kind of reasoning depending on the designer. In this paper, the traditional situation calculus action theory is expanded in proper way. A formal expression for sensors is added into the formal language of the action theory, and agentpsilas knowledge is defined as the contents of its knowledge base. The agentpsilas knowledge base can be updated automatically by formal describing for sensors and substituting instances for variables in the action effect axioms (or successor state axioms). Then agent can do action reasoning independent of the designer.
A Nonintrusive and In-Service Motor Efficiency Estimation Method using Air-Gap Torque with Considerations of Condition Monitoring

Energy usage evaluation and condition monitoring for electric machines are important in industry for overall energy savings. They are often expected to be implemented in an integrated product because of many common requirements such as data collection. Because of the uninterrupted characteristic of industrial processes, traditional methods defined in IEEE Standard 112 cannot be used for these in-service motors. This paper proposes a truly nonintrusive method for in-service motor efficiency estimation based on air-gap torque using only motor terminal quantities and nameplate information, with special considerations of motor condition monitoring requirements. Rotor speed and stator resistance, the stumbling blocks of most in-service testing methods, are extracted from motor input currents instead of being measured. The no-load test, which is required for calculating the rotational loss and core loss, is eliminated by using empirical values. Stray-load loss is assumed according to the motor horse power as suggested in IEEE Standard 112. Finally, the proposed method is validated by testing three induction motors with different configurations. Experimental results show that the proposed method can estimate motor efficiencies with less than 2% errors under normal load conditions
Author retrospective for adaptive reduction parallelization techniques

Modern applications are dynamic and input dependent and algorithm performance is input and environment sensitive. This potential mismatch between algorithmic choice and performance is exacerbated in the case of parallel programs because the penalty for less than optimal locality is grows with the size of the machine. Reductions, e.g., map-reduce are one of the most important algorithms used in parallel codes are also input sensitive. This led us to develop an adaptive framework that used a statistical method to learn how to select the best algorithm for every execution instance. We applied it to parallel reduction algorithm selection. The importance of better reduction methods as well as adaptive selection methods has only increased since the time this paper was first published. Original paper:http://dx.doi. org/10.1145/335231.335238
A 4.8mW inductorless CMOS frequency divider-by-4 with more than 60% fractional bandwidth up to 70GHz

Frequency synthesizers at mm-waves would benefit from wide-band low-power dividers with large division factors. This work proposes a divider-by-4 based on clocked differential amplifiers working as dynamic CML latches. The clock modulates both the tail current and the load resistance of the differential pair, allowing a wide locking range. Prototypes, realized in 32nm CMOS, operate between 14GHz and 70GHz demonstrating a fractional bandwidth in excess of 60% in the entire range, 4.8mW of maximum power consumption and 55×18μm2 occupied area.
Volatility: Expectations and Realizations

Embedded in option prices are market expectations regarding future volatility. While the assumption of rational expectations has been a popular paradigm, it is difficult to ignore the subjective nature of expectations. The objective of this paper is to make market expectations visible as they evolve over time, and to price options in line with prevailing expectations, be they rational or non-rational. We put forward an analytically convenient option pricing framework that accommodates both stochastic volatility and asymmetric volatility. Daily estimates of the implied pdf of volatility are obtained by estimating the option pricing model one day at a time. We do not impose too much structure on how expectations are updated over time, but allow market expectations to take their course.
Agent-based computational modeling of wounded epithelial cell monolayers

Computational modeling of biological systems, or in silico biology, is an emerging tool for understanding structure and order in biological tissues. Computational models of the behavior of epithelial cells in monolayer cell culture have been developed and used to predict the healing characteristics of scratch wounds made to urothelial cell cultures maintained in low- and physiological [Ca/sup 2+/] environments. Both computational models and in vitro experiments demonstrated that in low exogenous [Ca/sup 2+/], the closure of 500-/spl mu/m scratch wounds was achieved primarily by cell migration into the denuded area. The wound healing rate in low (0.09 mM) [Ca/sup 2+/] was approximately twice as rapid as in physiological (2 mM) [Ca/sup 2+/]. Computational modeling predicted that in cell cultures that are actively proliferating, no increase in the fraction of cells in the S-phase would be expected, and this conclusion was supported experimentally in vitro by bromodeoxyuridine incorporation assay. We have demonstrated that a simple rule-based model of cell behavior, incorporating rules relating to contact inhibition of proliferation and migration, is sufficient to qualitatively predict the calcium-dependent pattern of wound closure observed in vitro. Differences between the in vitro and in silico models suggest a role for wound-induced signaling events in urothelial cell cultures.
Measuring Transient Performance of a Multistage Interconnection Network Using Ethernet Networking Equipment ∗

Multistage interconnection networks (Banyan networks, MINs) are frequently proposed as connections in multiprocessor systems or in highbandwidth network switches. Using off-the-shelf Ethernet networking components, a small multistage interconnection network was re-created and several measurements concerning delay times and throughput were conducted on this setup using Poisson as well as selfsimilar input traffic. The analysis of the transient measurements reveals a dependency of the delays’ variance on the offered input load.
RMiCS: a robust approach for mining coherent subgraphs in edge-labeled multi-layer graphs

Detecting dense subgraphs in a large graph is an important graph mining problem and various approaches have been proposed for its solution. While most existing methods only consider unlabeled and one-dimensional graph data, many real-world applications provide far richer information. Thus, in our work, we consider graphs that contain different types of edges -- represented as different layers/dimensions of a graph -- as well as edge labels that further characterize the relations between two vertices. We argue that exploiting this additional information supports the detection of more interesting clusters. In general, we aim at detecting clusters of vertices that are densely connected by edges with similar labels in subsets of the graph layers. So far, there exists only a single method that tries to detect clusters in such graphs. This method, however, is highly sensitive to noise: already a single edge with a deviating label can completely hinder the detection of interesting clusters. In this paper, we present the RCS (Robust Coherent Subgraph) model which enables us to detect clusters even in noisy data. This robustness greatly enhances the applicability on real-world data. In order to obtain interpretable results, RCS avoids redundant clusters in the result set. We present the algorithm RMiCS for an efficient detection of RCS clusters and we analyze its behavior in various experiments on synthetic and real-world data.
Mosquito homolog of the La autoantigen binds to Sindbis virus RNA

We have isolated a 50-kDa mosquito protein that binds with high affinity to a riboprobe representing the 3' end of the minus strand of Sindbis virus RNA. The isolated protein has been used to obtain cDNA clones encoding this protein that have been sequenced and used to express the protein in large amounts. Sequence comparisons make clear that this protein is the mosquito homolog of the La autoantigen. The N-terminal half of the protein shares considerable sequence identity with the human La protein, the rat La protein, and the recently identified Drosophila melanogaster homolog. There is one stretch of 100 amino acids in the N-terminal domain in which 48 residues are identical in all four proteins. In contrast, the C-terminal domain of the mosquito protein shares little identity with any of the other three proteins. We have also shown that the mosquito protein, the human protein, and a putative chicken homolog of the La protein cross-react immunologically and, thus, all share antigenic epitopes. The mosquito La protein is primarily nuclear in location, but significant amounts are present in the cytoplasm, as is the case for the La proteins of other species. The equilibrium constant for the binding of the expressed mosquito La protein to the Sindbis virus riboprobe is 15.4 nM, and thus the affinity of binding is high enough to be physiologically relevant. Furthermore, the conservation of this protein in the animal kingdom may be significant, because Sindbis virus utilizes mosquitoes, birds, and mammals as hosts. We propose that the interactions we observe between the La protein and toes, birds, and mammals as hosts. We propose that the interactions we observe between the La protein and a putative promoter in the Sindbis virus genome are significant for Sindbis virus RNA replication.