Miracle-dz/UniFAR-FTUs huggingface dataset:
Product portfolio planning with customer-engineering interaction

A critical decision that faces companies across all industrial sectors is the selection of an optimal mix of product attributes to offer in the marketplace, namely product portfolio planning. The product portfolio planning problem has to date generally been considered from a marketing perspective, with the focus being on customer concerns i.e., how alternative sets of product attributes and attribute-level options interact and compete among the target customer segments. From the engineering perspective, the operational implications of product portfolio decisions have been tackled with a primary concern about the cost and complexity of interactions among multiple products in a manufacturing environment with increasing variety. Consideration of the customer and engineering interaction in product portfolio planning is becoming increasingly important, manifested by the efforts observed in many industries to improve the coordination of marketing, design and manufacturing activities across product and process platforms. This paper examines the benefits of integrating customer concerns over product offerings with more engineering implications. To leverage both the customer and engineering concerns, a maximizing shared-surplus model that considers customer preferences, choice probabilities and platform-based product costing, is proposed to address the product portfolio planning problem. A heuristic genetic algorithm procedure is applied to solve the mixed-integer combinatorial optimization problem involved in product portfolio planning. Initial findings from a case study on notebook computer portfolio planning suggests the importance of the research problem, as well as the feasibility and potential of the proposed framework.
Development of nutrient-based nutritional standards for foodservice at shelters during disasters in the Republic of Korea

BACKGROUND/OBJECTIVES In times of disaster, simplified and minimized nutritional standards are necessary for a quick response to provide nutritious relief food. This study aimed to develop nutrient-based nutritional standards for foodservice at shelters during disasters in the Republic of Korea (South Korea). SUBJECTS/METHODS The standards were developed in 2 phases. First, nutrients to be included in the standards were selected. Initial candidates were selected considering 3 aspects: preceding standards, insufficient intake during disasters, and inadequate intake among South Koreans. Final selection was made by excluding nutrients for 3 reasons: nutrients for which there is no deficiency concern in South Korea, nutrients whose intake data were not available, or nutrients whose values presented by Dietary Reference Intakes for Koreans are difficult to achieve based on the current diet among South Koreans. Second, the reference values of energy and the selected nutrients were calculated. The reference values for the entire population who were 1-year-old and over were calculated by multiplying the estimated energy requirements or the recommended nutrient intake and the proportion of each age and sex group. Respective reference values were also calculated for 4 different age groups (1–5, 6–11, 12–64, and ≥ 65-year-old). RESULTS The standards for the entire population were 2,000 kcal for energy, 55 g for protein, 650 µg retinol activity equivalents for vitamin A, 95 mg for vitamin C, 1.1 mg for thiamin, 1.3 mg for riboflavin, 14 mg niacin equivalents for niacin, 350 µg dietary folate equivalents for folic acid, 750 mg for calcium, and 11 mg for iron. Four additional standards corresponding to each age group were developed. CONCLUSIONS The nutritional standards during disasters were developed for South Korea, including energy and 9 nutrients with reference values for the entire population and 4 different age groups. The standards will contribute to maintaining the health of disaster evacuees in South Korea.
Emittance measurements at the Bates linac

An emittance measuring system has been installed at the Bates Linear Accelerator Center. The system consists of three wire scanners used to measure the electron beam profile, and a microcomputer for data acquisition and processing. The scanner measures the horizontal and vertical beam size with a possible resolution of 25 mu m. The horizontal and vertical beam phase spaces can then be determined. Results of measurements are presented. Calculations relating the theoretical accuracy of the emittance measurements to the distance separating the scanners and to the beam waist's location and size are also presented. Another technique for measuring emittance has also been used. This technique involves using a wire scanner to measure the beam size at a fixed location, as a function of the strength of an upstream quadrupole. <<ETX>>
Automatic detection of slow-wave-sleep using heart rate variability

In this study, we used heart rate variability parameters to first characterize and then automatically detect slow-wave sleep (SWS). First, a wavelet transform was used to decompose equally sampled R-R interval series into their time-dependent spectral components: very low frequency (VLF) 0.005-0-04Hz, low frequency (LF) 0.04-0.15 Hz, and high frequency (HF) 0.15-0.45Hz. Then, the known decrease in LF power during SWS was confirmed and a linear relation between the average LF/HF balance throughout the night and the balance during SWS was found. Also, similar behaviour was found with the VLF power and the VLF/HF ratio. Finally, a decision algorithm with two criteria was defined using a training set of ECG recordings and applied to a test set. The results amounted to an 80% correct identification of SWS. The limitations of the study, as well as inherent differences between SWS definitions based on EEG and ECG, are discussed.
The Role of CD1 Gene Polymorphism in the Genetic Susceptibility to Spondyloarthropathies in the Moroccan Population and the Possible Cross-Link with Celiac Disease

Spondyloarthropathies (SpA) are a group of chronic inflammatory disorders usually affecting the axial spine and asymmetrical peripheral joints. Strong evidence links genetic and environmental factors to SpA pathogenesis. The HLA-B27 is the most important genetic factor associated with SpA. Nevertheless, the involvement of other HLA and non-HLA loci has been also reported. Some patients with SpA may also manifest features of celiac disease (CeD), thus suggesting a genetic overlap across these autoimmune diseases. Recently, CD1 glycoproteins, a class of molecules able to bind and present non peptidic antigens to T cells, aroused interest for their contribution to the pathogenesis of CeD. Therefore, to evaluate whether functional polymorphisms of CD1A and E genes also influence susceptibility to SpA, we analyzed 86 patients from Morocco affected by SpA and 51 healthy controls, using direct sequencing analysis. An increase of CD1E*01/01 homozygous genotype (p = 0.046) was found in SpA, compared with controls. CD1E*01/01 genotype was associated particularly to patients with sacroiliac joints/spine/peripheral joints pain (p = 0.0068), while a decrease of CD1E*01/02 genotype was evidenced compared to controls (p = 0.0065). Results from haplotypes analysis demonstrated that CD1A*02-E*02 decreased the risk of SpA, while CD1A*02-E*01 increased risk to develop disease. Our data indicate a relationship between CD1 genes and susceptibility to SpA in the Moroccan population and suggest the existence of shared genetic risk loci across SpA and CeD that might be useful to explain common pathogenetic features and define novel therapeutic strategies.
Underdogs and One-Hit Wonders: When Is Overcoming Adversity Impressive?

Success tends to increase and failure tends to decrease the chances of future success. We show that this impact of past outcomes can change how diagnostic success or failure are regarding the competence of an individual or a firm. Succeeding under adverse circumstances is especially impressive when initial failure reduces the chances of success more for low-quality agents than for high-quality agents. Succeeding after initial failure (being a “successful underdog”) can also indicate higher expected quality than succeeding twice if initial success increases the chances of success of all agents to a high level. In different circumstances, the outcome after success can be especially informative about quality, implying that failing after an initial success (a “one-hit wonder”) indicates lower quality than failing twice does. We find effects consistent with our model in data on Canadian professional hockey players and on data from the Music Laboratory experiment: Initial failure combined with eventual success is associated with high quality. The results help to clarify when failure should be attributed to the person in charge or to the situation, when underdogs and individuals who overcome adversity are especially impressive and when a naïve “more is better” heuristic for evaluating performance can be misleading. This paper was accepted by Isabel Fernandez-Mateo, organizations. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022. 4630 .
Physiological Responses of Agave maximiliana to Inoculation with Autochthonous and Allochthonous Arbuscular Mycorrhizal Fungi

The benefits of mycorrhizal interactions are only known in 8 of 210 recognized Agave taxa. We evaluated the effects of autochthonous and allochthonous arbuscular mycorrhizal fungi (AMF) on growth and nutrient assimilation in Agave maximiliana. The autochthonous consortium (Cn) of eight species was propagated from the rhizospheric soil of A. maximiliana, while Claroideoglomus claroideum (Cc) and Claroideoglomus etunicatum (Ce) were employed as allochthonous AMF. Six treatments were included in the study: Cn, Ce, Cc, Ce + Cc, Tf (fertilized control), and Tn (non-fertilized control, not inoculated). Mycorrhizal colonization increased over time, and the colonization percentages produced by Cn and the allochthonous AMF, both alone and mixed together, were equal at 6, 12, and 18 months. Height increased steadily and was higher in AMF-treated plants from seven months onward. Growth indicators of AMF-treated and AMF-free plants were equal at 6 months, but the beneficial effects of allochthonous and autochthonous AMF were evident in all growth indicators at 18 months and in sugar and mineral (P, K, Ca, Mg, and Fe) content. Arbuscular mycorrhizal fungi significantly improved all growth parameters of A. maximiliana regardless of the origin of the inoculums. This is the first study to report the positive effects of AMF colonization in A. maximiliana.
Testing of a novel questionnaire of Household Exposure to Wood Smoke

Household air pollution from wood smoke (WS), contributes to adverse health effects in both low- and high-income countries. However, measurement of WS exposure has been limited to expensive in-home monitoring and lengthy face-to-face interviews. This paper reports on the development and testing of a novel, self-report nine-item measure of WS exposure, called the Household Exposure to Wood Smoke (HEWS). A sample of 149 individuals using household wood stoves for heating from western states in the U.S., completed the HEWS during the winter months (November to March) of 2013 through 2016 with 30 subjects having in-home particle monitoring. Hard copy or online surveys were completed. Cronbach’s alpha (α), intraclass correlations (ICC), exploratory factor analysis (EFA) and tests of associations were done to evaluate reliability and validity of the HEWS. Based on initial analysis, only 9 of the 12 items were retained and entered in the EFA. The EFA did not support a unitary scale as the 9 items demonstrated a 3-factor solution (WS exposure duration, proximity, and intensity) with Cronbach’s α of 0.79, 0.91, and 0.62, respectively. ICC was 0.86 of the combined items with single items ranging from 0.46 to 0.95. WS intensity was associated with symptoms and levoglucosan levels, while WS duration was associated with stove and flume maintenance. The three-dimensional HEWS demonstrated internal consistency and test-retest reliability, structural validity, and initial criterion and construct validity.
PyuARF16/33 Are Involved in the Regulation of Lignin Synthesis and Rapid Growth in Populus yunnanensis

(1) Background: Lignin is a unique component of the secondary cell wall, which provides structural support for perennial woody plants. ARFs are the core factors of the auxin-signaling pathway, which plays an important role in promoting plant growth, but the specific relationship between auxin response factors (ARFs) and lignin has not been fully elucidated with regard to rapid plant growth in forest trees. (2) Objectives: This study aimed to investigate the relationship between ARFs and lignin with regard to rapid plant growth in forest trees. (3) Methods: We used bioinformatics analysis to investigate the PyuARF family, find genes homologous to ARF6 and ARF8 in Populus yunnanensis, and explore the changes in gene expression and lignin content under light treatment. (4) Results: We identified and characterized 35 PyuARFs based on chromosome-level genome data from P. yunnanensis. In total, we identified 92 ARF genes in P. yunnanensis, Arabidopsis thaliana, and Populus trichocarpa, which were subsequently divided into three subgroups based on phylogenetic analysis and classified the conserved exon–intron structures and motif compositions of the ARFs into the same subgroups. Collinearity analysis suggested that segmental duplication and whole-genome duplication events were majorly responsible for the expansion of the PyuARF family, and the analysis of Ka/Ks indicated that the majority of the duplicated PyuARFs underwent purifying selection. The analysis of cis-acting elements showed that PyuARFs were sensitive to light, plant hormones, and stress. We analyzed the tissue-specific transcription profiles of PyuARFs with transcriptional activation function and the transcription profiles of PyuARFs with high expression under light in the stem. We also measured the lignin content under light treatment. The data showed that the lignin content was lower, and the gene transcription profiles were more limited under red light than under white light on days 1, 7, and 14 of the light treatments. The results suggest that PyuARF16/33 may be involved in the regulation of lignin synthesis, thereby promoting the rapid growth of P. yunnanensis. (5) Conclusions: Collectively, this study firstly reports that PyuARF16/33 may be involved in the regulation of lignin synthesis and in promoting the rapid growth in P. yunnanensis.
Monte Carlo Comparison of Four Methods for Estimation of Genetic Parameters in the Univariate Case

Abstract Computer simulation was used to generate replicates of two-way mixed model data sets for comparing Henderson's Method 3, maximum likelihood, restricted maximum likelihood, and minimum norm quadratic unbiased estimation methods of variance component estimation. Estimates of sire and error variances and heritabilities by these statistical procedures were compared with parameters in both unselected and selected data. Selection of records across fixed effects and selection within fixed effects were considered. Under a model of no selection, restricted and quadratic estimators of sire variances and heritability agreed more closely with parameters than those by maximum likelihood or Method 3. The mean square error for sire variance components was greater for Method 3 than for mixed model procedures, because random effect of sire was treated as fixed by Method 3 in obtaining the sum of squares for sire. Maximum likelihood estimators of error variance were biased downward, thus resulting in overestimation of heritability. Skewed distribution of sire effects did not seem to affect relative accuracy of estimates. Both selection across fixed effects and selection within fixed effects reduced estimates in the univariate case regardless of estimation procedure. Selection within fixed effects affected estimates more seriously than selection across fixed effects. The restricted procedure generally converged faster than the maximum likelihood procedure.
Si incorporation from the seed into Ge stripes crystallized using rapid melt growth

Ge stripes grown by rapid melt growth (RMG) have produced defect free single crystals with excellent device characteristics. However, in some cases significant Si concentrations have been observed in the stripes, far from the seed region. In this paper, we anneal Ge RMG stripes at temperatures ranging from 950 °C to 1150 °C for different time periods and show that the measured composition profiles match a model in which complete mixing in the melt is assumed. The model also assumes that the average Si concentration in the RMG stripe equals the equilibrium liquidus concentration at the annealing temperature. This paper outlines a method to predict the profile of Si absorbed from the seed region during RMG. The conclusions from this paper have important implications for minimizing Si contamination in RMG grown stripes.
Estimation of thermophysic properties of a bimaterial by temperature field measurement and finite element model updating

The aim of this study is to identify simultaneously the thermal conductivity tensor and the heat capacity per unit volume of a bimaterial, whose heat conduction obeys Fourier’s law. This approach is validated by numerical simulation. The simulated temperature fields are obtained by the direct resolution of the heat conduction equation solved numerically with the help of finite element method formulation. To identify the parameters, an inverse method is developed by using the finite element model updating (FEMU) based on the Levenberg-Marquardt algorithm. This inverse finite element method approach allowed us to estimate the thermophysical parameters sought. We validated the numerical procedure by using noiseless temperature fields at different time and space steps and two types of material: an homogeneous and a bimaterial one. To be close to real conditions, the influence of the noise on the temperature fields is also studied and shows the efficiency of the inverse method. The results of this procedure show that the identified parameters are very less sensitive to the number of infra-red images varying from 40 to 80 and the number of elements ranging from 20 to 50 for a specimen size equals to 36.6 × 36.6 mm2.
All the President’s Media: How the Traditional Press Responded to New Communications Technology Adopted by US Presidents

Both Franklin D. Roosevelt and John F. Kennedy mastered new forms of mass media communications, ridding themselves of formal gatekeepers to communicate directly to US citizens. For Roosevelt, mastering radio airwaves would allow him to navigate past traditional presidential rhetorical tropes and print journalists’ interpretations of his presidential messages to speak directly to the American public. For Kennedy, television meant advertising spots, late-night talk show appearances, and hour-long specials with his family as a way of pushing the medium beyond televised speeches in his campaigns. This study attempts to understand how the traditional press reacted to these unfiltered messages. Findings suggest that newspaper editorials and magazine stories initially praised these men’s innovative approaches to new technology, but over time, legacy media became disillusioned as it began to view presidential uses of new media as a nuisance that hampered legitimate reporting.
A matrix pencil based numerical method for the computation of the GCD of polynomials

The authors present a novel numerical method for the computation of the greatest common divisor (GCD) of an m-set of polynomials of R(s), P/sub m,d/, of maximal degree d. It is based on a procedure that characterizes the GCD of P/sub m,d/ as the output decoupling zero polynomial of a linear system that may be associated with P/sub m,d/. The computation of the GCD is thus reduced to finding the finite zeros of a certain pencil. An error analysis proving the stability of the described procedures is given. Three numerical results that demonstrate the effectiveness of the method are presented. <<ETX>>
A Novel Nonisolated Buck–Boost DC–DC Converter With Low Voltage Stress on Components

This article proposes a new nonisolated dc–dc buck–boost converter with low voltage stress on components and enhanced voltage gain. This converter has a high voltage gain in boost mode and is capable of reducing the voltage level significantly in the buck mode, which makes it suitable for renewable energy and other industrial applications. Moreover, the number of components in this converter is low and the input current is continuous. Operational principles of the proposed converter in both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) are presented, efficiency analysis is discussed, and a small-signal model is derived. Comparisons between the presented converter and related buck–boost converters are given in terms of voltage gain, voltage stress on components, number of elements, etc. Besides, a single-input multioutput converter based on the proposed topology is presented. Experimental results from a lab-scale prototype are given for both buck and boost modes in order to verify the performance of the converter.
Bayesian Forecasting for Complex Systems Using Computer Simulators

Although computer models are often used for forecasting future outcomes of complex systems, the uncertainties in such forecasts are not usually treated formally. We describe a general Bayesian approach for using a computer model or simulator of a complex system to forecast system outcomes. The approach is based on constructing beliefs derived from a combination of expert judgments and experiments on the computer model. These beliefs, which are systematically updated as we make runs of the computer model, are used for either Bayesian or Bayes linear forecasting for the system. Issues of design and diagnostics are described in the context of forecasting. The methodology is applied to forecasting for an active hydrocarbon reservoir.
Data-Driven State of Charge Estimation for Power Battery With Improved Extended Kalman Filter

Accurately monitoring battery state of charge (SOC) is essential for battery system safety. However, single and open-loop combination algorithms are mainly used for SOC estimation currently, which may have the problems of low accuracy and poor reliability. Here, a closed-loop combination algorithm with the variance-compensation extended Kalman filter (VCEKF) and back-propagation (BP) neural network is developed for SOC estimation. First, the second-order resistance–capacitance model is established, and the model’s parameters are identified by the forgetting factor recursive least square (FFRLS). Second, the extended Kalman filter (EKF), the variance compensation algorithm, and the BP neural network are merged under a closed-loop structure. Specifically, the variance compensation algorithm updates the process noise covariance of the EKF algorithm in real-time, while the BP neural network simultaneously provides compensation value to obtain the finally estimated SOC. Afterward, the proposed algorithm is testified under different driving schedules. Experimental results show that the accurate SOC estimation under different driving schedules is realized using the proposed algorithm and also illustrate a better performance than the commonly used open-loop algorithm and EKF-based algorithms.