Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Robust New Products Under Variability: Marketing Meets Design

In designing consumer durables such as appliances and power tools, it is important to account for variations in product performance across different usage situations and conditions. Since the specific usage of the product and the usage conditions can vary, the resultant variations in product performance also can impact consumer preferences for the product. Therefore, any new product that is designed should be robust to these variations – both in product performances and consumer preferences. This article refers to a robust product design as a design that has (1) the best possible (engineering and market) performance under the worst-case variations and (2) the least possible sensitivity in its performance under the variations. Achieving these robustness criteria, however, implies consideration of a large number of design factors across multiple functions. This article’s objectives are (1) to provide a tutorial on how variations in product performance and consumer preferences can be incorporated in the generation and comparison of design alternatives and (2) to apply a multi-objective genetic algorithm (MOGA) that incorporates multifunction criteria in order to identify better designs while incorporating the robustness criteria in the selection process. Since the robustness criteria is based on variations in engineering performance as well as consumer preferences, the identiﬁed designs are robust and optimal from different functional perspectives, a significant advantage over extant approaches that do not consider robustness issues from multifunction perspectives. This study’s approach is particularly useful for product managers and product development teams, who are charged with developing prototypes. They may ﬁnd the approach helpful for obtaining customers’ buy-in as well as internal buy-in early on in the product development cycle and thereby for reducing the cost and time involved in developing prototypes. This study’s approach and its usefulness are illustrated using a case-study application of prototype development for a handheld power tool.
Topological characterization of the DnaA–oriC complex using single-molecule nanomanipuation

In most bacteria, the timing and synchrony of initiation of chromosomal replication are determined by the binding of the AAA+ protein DnaA to a set of high- and low-affinity sites found within the origin of chromosomal replication (oriC). Despite the large amount of information on the role and regulation of DnaA, the actual structure of the DnaA–oriC complex and the mechanism by which it primes the origin for the initiation of replication remain unclear. In this study, we have performed magnetic tweezers experiments to investigate the structural properties of the DnaA–oriC complex. We show that the DnaA-ATP–oriC complex adopts a right-handed helical conformation involving a variable amount of DNA and protein whose features fit qualitatively as well as quantitatively with an existing model based on the crystal structure of a truncated DnaA tetramer obtained in the absence of DNA. We also investigate the topological effect of oriC’s DNA unwinding element.
Association of DNA Repair and Steroid Metabolism Gene Polymorphisms with Clinical Late Toxicity in Patients Treated with Conformal Radiotherapy for Prostate Cancer

Objective: To explore the possible relationship between single nucleotide polymorphisms (SNP) in candidate genes encoding DNA damage recognition/repair/response and steroid metabolism proteins with respect to clinical radiation toxicity in a retrospective cohort of patients previously treated with three-dimensional conformal radiotherapy (3-DCRT) for prostate cancer. Experimental Design: One hundred twenty-four patients with prostate cancer underwent 3-DCRT at our institution between September 1996 and December 2000. Of these, 83 consented for follow-up of blood sampling and SNP analysis. Twenty-eight patients were documented as having experienced grade ≥2 late bladder or rectal toxicity (scoring system of Radiation Therapy Oncology Group) on at least one follow-up visit. We analyzed 49 SNPs in BRCA1, BRCA2, ESR1, XRCC1, XRCC2, XRCC3, NBN, RAD51, RAD52, LIG4, ATM, BCL2, TGFB1, MSH6, ERCC2, XPF, NR3C1, CYP1A1, CYP2C9, CYP2C19, CYP3A5, CYP2D6, CYP11B2, and CYP17A1 genes using the Pyrosequencing technique. Results: Significant univariate associations with late rectal or bladder toxicity (grade ≥2) were found for XRCC3 (A>G 5′ untranslated region NT 4541), LIG4 (T>C Asp568Asp), MLH1 (C>T, Val219Ile), CYP2D6*4 (G>A splicing defect), mean rectal and bladder dose, dose to 30% of rectum or bladder, and age <60 years. On Cox multivariate analysis, significant associations with toxicity were found for LIG4 (T>C, Asp568Asp), ERCC2 (G>A, Asp711Asp), CYP2D6*4 (G>A, splicing defect), mean bladder dose >60 Gy, and dose to 30% of rectal volume >75 Gy. Conclusions: In this study, we identified SNPs in LIG4, ERCC2, and CYP2D6 genes as putative markers to predict individuals at risk for complications arising from radiation therapy in prostate cancer.
Simplified Design of I-P Controllers for Two-Inertia Speed Control Systems

A simplified design of I-P controller by the concept of model order reduction of a higher-order plant and by the CRA method with less number of characteristic ratios ai is presented in this paper. Two model order reduction techniques are employed to obtain the reduced order models of a higher-order plant first. Then the I-P controllers are designed for the reduced order models by using CRA method with the appropriate values of characteristic ratios and of the generalized time constant in order to obtain the closed-loop step responses without overshoots. Finally, the designed I-P controllers are employed to control the original higher-order plant. The acceptable performances of the speed control of a two-inertia system employing the proposed I-P controllers designed from the reduced order models are still obtained as verified by the simulation results. Tracking the retarded motor speed and disturbance rejection are also investigated.
IEC61850–Based Systems—Functional Testing and Interoperability Issues

This paper presents a proposal for functional testing of protection and automation systems based on the IEC61850 standard. The proposed methodology is based on the development of tests scenarios which properly represent the actual systems and their operative conditions. It includes the selection of hardware and software that are used to simulate the operational events and acquire data for further analysis. This methodology was developed to evaluate the protection and automation systems of large-sized substations mainly regarding the interoperability between intelligent electronic devices of different manufacturers. This paper explains in detail the proposed methodology and an actual case study.
STINGER: Spatio-Temporal Interaction Networks and Graphs (STING) Extensible Representation

In this document, we propose a dynamic graph data structure that can serve as a common data structure for multiple real-world applications. The extensible representation for dynamic complex networks is space-eﬃcient, allows parallelism over vertices and edges independently, and can be used for eﬃcient checkpoint/restart of the data.
Muslims in the Netherlands: Tensions and Violent Conflict

he release of the anti-Islam movie “Fitna” by the Dutch Member of Parliament Geert Wilders, early 2008, aroused anxious fears of angry responses by Muslims communities. As happened in the Danish cartoon crisis, people expected the movie to trigger violent demonstrations, boycotts, the burning of flags and other aggressive responses by Muslim communities, both in the Netherlands and around the world. Months prior to the actual release of the movie, the Dutch prime minister already spoke of a crisis, predicting violent confrontations between Muslims and non- Muslims, and devastating consequences for Muslim integration in Dutch society. Contrary to the wide anticipation that Muslims would respond violently to the movie, there were few incidents. In the Netherlands, there were no noticeable incidents at all. Eloquent young Muslims stepped forward as representatives for their communities and of Islam, explicitly distancing themselves from radical or violent action by Muslims in answer to the film. Likewise, orthodox Muslims made strong pleas to react in a non-violent and dignified way to “Fitna”. Outside the Netherlands, there were only a few incidents, like the attack on a Dutch consulate in Indonesia by a group of students and the expected burning of the Dutch flag in countries like Afghanistan. Nevertheless, the Dutch fear of violence involving Muslims typifies the implicit association that people easily seem to make between Muslims and violence. Almost irrespective of the actual level of violent incidents, Muslims seem to project an image of responding violently to every political incident. How did this image come into being? In the Netherlands, what types of incidents and developments have occurred that led to potentially violent tensions and conflicts in which Muslims were involved?
A spatial FCM color quantization algorithm with pyramid data structure

Fuzzy C-Means (FCM) algorithm is an important color quantization technology. Though it is widely used, its runtime is long and its quantization result is not good enough. In the paper, a spatial FCM color quantization algorithm which uses pyramid data structure for the hierarchical analysis of a color image is proposed. Experiments show that the algorithm has better quantization result and shorter runtime than the conventional FCM algorithm and the spatial FCM algorithm before.
Statistical discovery of signaling pathways from an ensemble of weakly informative data sources

Brief introduction. Signaling pathways are complex biological mechanisms. For instance, consider the Mitogen-activated protein (MAP) kinase pathway, available on Kyoto Encyclopedia of Genes and Genomes (KEGG) (Kanehisa et al., 2006). It involves 55 genes/proteins, it sub-divides into four interconnected modules (pheromone response, high osmolarity glycerol response, hypotonic shock response, and starvation response), and their circuitry is currently instantiated by 104 directed interactions with various meanings (e.g. activation, phosphorylation, binding, and inhibition)
Patient cost-sharing for health care in Europe

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On Combining Reference Data to Improve Imputation Accuracy

Genotype imputation is an important tool in human genetics studies, which uses reference sets with known genotypes and prior knowledge on linkage disequilibrium and recombination rates to infer un-typed alleles for human genetic variations at a low cost. The reference sets used by current imputation approaches are based on HapMap data, and/or based on recently available next-generation sequencing (NGS) data such as data generated by the 1000 Genomes Project. However, with different coverage and call rates for different NGS data sets, how to integrate NGS data sets of different accuracy as well as previously available reference data as references in imputation is not an easy task and has not been systematically investigated. In this study, we performed a comprehensive assessment of three strategies on using NGS data and previously available reference data in genotype imputation for both simulated data and empirical data, in order to obtain guidelines for optimal reference set construction. Briefly, we considered three strategies: strategy 1 uses one NGS data as a reference; strategy 2 imputes samples by using multiple individual data sets of different accuracy as independent references and then combines the imputed samples with samples based on the high accuracy reference selected when overlapping occurs; and strategy 3 combines multiple available data sets as a single reference after imputing each other. We used three software (MACH, IMPUTE2 and BEAGLE) for assessing the performances of these three strategies. Our results show that strategy 2 and strategy 3 have higher imputation accuracy than strategy 1. Particularly, strategy 2 is the best strategy across all the conditions that we have investigated, producing the best accuracy of imputation for rare variant. Our study is helpful in guiding application of imputation methods in next generation association analyses.
Detection limits for linear non-Gaussian state-space models

The performance of nonlinear fault detection schemes is hard to decide objectively, so Monte Carlo simulations are often used to get a subjective measure and relative performance for comparing different algorithms. There is a strong need for a constructive way of computing an analytical performance bound, similar to the Cramer-Rao lower bound for estimation. This paper provides such a result for linear non-Gaussian systems. It is first shown how a batch of data from a linear state-space model with additive faults and non-Gaussian noise can be transformed to a residual described by a general linear non-Gaussian model. This also involves a parametric description of incipient faults. The generalized likelihood ratio test is then used as the asymptotic performance bound. The test statistic itself may be impossible to compute without resorting to numerical algorithms, but the detection performance scales analytically with a constant that depends only on the distribution of the noise. It is described how to compute this constant, and a simulation study illustrates the results.
Using Payments to Promote Cooperation in Anonymity Protocols

Like many peer-to-peer applications, anonymous communication systems are vulnerable to freeriders, peers that use the system while providing little or no service to others. To complicate matters, the identity of the free-rider is obscured by the very anonymity such systems are designed to provide, imposing challenging design constraints for incentive mechanisms to discourage free-riding. We argue that these constraints are well addressed by requiring currency to be exchanged in return for service. Based on this idea, we propose a novel technique to allow anonymous digital cash payments to be made to those who provide service. We incorporate this technique into a class of peer-peer anonymous protocols that are based on Chaumian mixes while introducing modest message delay overheads and preserving their architectural simplicity. Finally, we formulate an abstract model of self-interested users in such a system and show that a payment based incentive mechanism can significantly improve the degree of anonymity by fostering greater cooperation among peers.
Transaction Services, Inflation, and Welfare

This paper is motivated by empirical observations on the comovements of currency velocity, inflation, and the relative size of the credit services sector. We document these comovements and incorporate into a monetary growth model a credit services sector that provides services that help people economize on money. Our model makes two new contributions. First, we show that direct evidence on the appropriately defined credit service sector for the United States is consistent with the welfare cost measured using an estimated money demand schedule. Second, we provide estimates of the welfare cost of inflation that have some new features.
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In this paper, a novel approach for expression invariant face recognition is proposed. It's implemented by common vector and the feature extraction is based on Curvelet transform, which is one of the multiscale geometric transforms and has better sparsity than the other transforms, especially for the edges. We assume the different images of the same subject as an interrelated ensemble with expression variations which could be viewed as sparse respectively. Then, each subject can be represented by a common feature vector, capturing its essential features, and an innovation feature vector, corresponding to the expression variations. By keeping the two feature vectors of each subject, we can use them to classify an image by the minimum reconstruction error.
Toward finer-grained sentiment identification in product reviews through linguistic and ontological analyses

We propose categories of finer-grained polarity for a more effective aspect-based sentiment summary, and describe linguistic and ontological clues that may affect such fine-grained polarity. We argue that relevance for satisfaction, contrastive weight clues, and certain adver-bials work to affect the polarity, as evidenced by the statistical analysis.
A hybrid PSO-GA based Pi sigma neural network (PSNN) with standard back propagation gradient descent learning for classification

Due to the strong global optimization capability and fast convergence, PSO has shown its efficiency in solving various real world benchmark applications. But premature convergence is one of the major drawback of PSO. In this paper to address this issue, a hybrid PSO-GA based Pi-sigma neural network with standard back propagation gradient descent learning (PSO-GA-PSNN) has been proposed for classification problems. The adjustment of algorithmic parameters is iteratively used until the error is less than the desired output. The proposed PSO-GA-PSNN has been tested with various benchmark datasets taken from UCI machine learning repository and the simulated results are being tested with the statistical tool ANOVA to show the obtained results are statistically steady and valid.
Hosting Virtual Machines on Distributed Datacenters

Almost of cloud services nowadays are built at top geographically distributed infrastructure for better reliability and performance. These cloud providers need an efficient method to control and direct user workload to suitable datacenter, depending on many factors such as: network traffic cost, operation cost budget, energy consumption, etc. In the virtual machine placement problem, current works mainly focus on the efficiency of packing virtual machines into servers and ignore the distributed scenario of datacenters. In this paper, we consider the problem of placing virtual machines to host applications on a shared resource pool based on distributed cloud platforms. We formulate the problem of hosting virtual machines on distributed datacenters as an optimization problem, and propose a distributed framework DHC that can dynamically direct workload between datacenters to maximize total utility of entire datacenters. We also conduct many case studies to validate our method, and evaluate its effectiveness and practicality, using real-workload traffic traces. The simulation results show that our algorithm can dynamically optimize the total utility, depending on various workload of users.
Failure Mode Screening Using Fuzzy Set Theory

The fuzzy sets possess natural capability to capture measurement uncertainty as a part of experimental data. Therefore the uncertainties of various kinds involved in system failure analysis may be adequately addressed using the concept of fuzzy sets. Fonseca et al developed and implemented fuzzy reasoning algorithm via an expert system to assess the likelihood of equipment failure mode. The algorithm developed by them is a fuzzy mathematical formulation which linearly relates the presence of different failure causing factors (FCFs) categorized as critical, important and related. It has been observed that the failure data may not be collected accurately and ignorance of uncertainty of any sort may lead to substantial errors. Unlike Fonseca et al, we propose that the FCFs should be measured by a fuzzy technique with desired accuracy. Also, it is quite obvious that the weights of FCFs are vital in failure mode screening. Thus the weights of FCFs should be linguistic and to be assigned appropriate fuzzy numbers in place of crisp numbers. The proposed technique is implemented to the same example taken by Fonseca et al.
Numerical investigation of flow separation in the lee side of transverse dunes

We investigate flow separation in the air flow over transverse sand dunes. CFD simulations of the air flow over differently shaped dunes are performed. The length of the recirculation region after the brink of the dune is found to depend strongly on the shape of the dune. A phenomenological expression for the separation length is presented. Suitably non-dimensionalised, it depends linearly on the angle of the dune at the slip face brink. We propose a fit for the shape of the separating streamline, which is well approximated by an ellipse.
Extended effects of evening meal carbohydrate-to-fat ratio on fasting and postprandial substrate metabolism.

BACKGROUND High-fat and high-carbohydrate diets lead to insulin resistance, gastrointestinal adaptation, and high plasma triacylglycerol concentrations. It is unclear, however, how rapidly these changes occur. OBJECTIVE We sought to determine the effects of both high-fat and high-carbohydrate evening meals on parameters of insulin resistance, hypertriglyceridemia, and gastrointestinal hormones. DESIGN Twelve healthy men were studied on 4 separate occasions. On 2 occasions, the subjects received a high-fat evening meal (62% of energy from fat) and on the other 2 occasions the subjects received a low-fat evening meal (16% of energy from fat). The morning after each meal the subjects were administered either an oral-fat-tolerance test or an oral-glucose-tolerance test. Plasma samples were analyzed for glucose, insulin, fatty acids, 3-hydroxybutyrate, triacylglycerol, pancreatic polypeptide, peptide YY, and cholecystokinin. Postchallenge data were analyzed by two-way analysis of variance with interaction and fasting concentrations analyzed by repeated-measures analysis of variance. RESULTS Fasting plasma concentrations of triacylglycerol were significantly elevated 12 h after each evening meal, but fatty acid and 3-hydroxybutyrate concentrations were reduced. No effects on glucose or insulin concentrations were detected. The high-fat evening meals elevated plasma cholecystokinin concentrations, reduced fasting concentrations of pancreatic polypeptide, and had no significant effect on peptide YY concentrations. The ratio of fat to carbohydrate in the evening meal produced significant effects on plasma triacylglycerol and fatty acids during both the oral-fat-tolerance and oral-glucose-tolerance tests. CONCLUSIONS The present study showed that the effects of high-fat and high-carbohydrate evening meals persist at least overnight and suggests that knowledge of recent dietary history is essential to the effective design of metabolic studies.