Miracle-dz/UniFAR-FTUs huggingface dataset:
What-If Analysis with Conflicting Goals: Recommending Data Ranges for Exploration

What-if analysis is a data-intensive exploration to inspect how changes in a set of input parameters of a model influence some outcomes. It is motivated by a user trying to understand the sensitivity of a model to a certain parameter in order to reach a set of goals that are defined over the outcomes. To avoid an exploration of all possible combinations of parameter values, efficient what-if analysis calls for a partitioning of parameter values into data ranges and a unified representation of the obtained outcomes per range. Traditional techniques to capture data ranges, such as histograms, are limited to one outcome dimension. Yet, in practice, what-if analysis often involves conflicting goals that are defined over different dimensions of the outcome. Working on each of those goals independently cannot capture the inherent trade-off between them. In this paper, we propose techniques to recommend data ranges for what-if analysis, which capture not only data regularities, but also the trade-off between conflicting goals. Specifically, we formulate a parametric data partitioning problem and propose a method to find an optimal solution for it. Targeting scalability to large datasets, we further provide a heuristic solution to this problem. By theoretical and empirical analyses, we establish performance guarantees in terms of runtime and result quality.
Effects of low sample mean values and small sample size on the estimation of the fixed dispersion parameter of Poisson-gamma models: A Bayesian Perspective

There has been considerable research conducted on the development of statistical models for predicting motor vehicle crashes on highway facilities. Many of these developments were performed for the likelihood-based or frequentist modeling approach. Over the last few years, there has been a significant increase in the application hierarchical Bayes method for modeling motor vehicle crashes. Whether the inferences are estimates using the likelihood-based or the Bayesian method, the most common probabilistic structure used for modeling this type of data remains the traditional Poisson-gamma (or Negative Binomial) distribution. Crash data collected for highway safety studies often have the unusual attributes of being characterized by low sample mean values and, due to the prohibitive costs of collecting data, small sample sizes. Previous studies have shown that the dispersion parameter of Poisson-gamma models can be seriously mis-estimated when the coefficients are estimated using the maximum likelihood method (MLE) for these extreme conditions. Despite important work done on this topic for the MLE, nobody has so far examined how low sample mean values and small sample sizes affect the posterior mean of the dispersion parameter of Poisson-gamma models estimated using the hierarchical Bayes method. The inverse dispersion parameter (posterior mean) plays an important role in various types of highway safety studies, such as building confidence intervals for comparing the safety performance of different highway design alternatives and the application of the empirical Bayes (EB) method for refining the long-term mean of a highway entity, and is particularly important for practitioners who are not familiar with Bayesian methods. It is therefore vital to determine the conditions in which the inverse dispersion parameter may be mis-estimated for this category of models. To accomplish the objectives of this study, a series of Poisson-gamma distributions are simulated using different values describing the mean, the dispersion parameter, the sample size, and the prior specification. Non-informative and informative prior specifications are tested for determining the magnitude of the biases introduced by low sample mean values and small sample sizes. A series of Poisson-lognormal distributions are also simulated, in the light of recent work done by statisticians on this mixed distribution. The study shows that a dataset characterized by a low sample mean combined with a small sample size can seriously affect the estimation of the posterior mean of the dispersion parameter when a non-informative prior specification is used to characterize the gamma hyper-parameter. The risk of a mis-specified posterior mean can be greatly minimized when an appropriate informative prior distribution is used. Finally, the study shows that Poisson-lognormal models are recommended over Poisson-gamma models whenever crash data characterized by low sample mean values are used for developing crash prediction models.
A markov chain-based probability vector approach for modeling spatial uncertainties of soil classes

Due to our imperfect knowledge of soil distributions acquired from techniques may represent an optimal guess based on field surveys, spatial uncertainties inevitably arise in mapping soils at unobserved locations.Providing spatial uncertaintyinformation along the dataset and the interpolation method used, but does with survey maps is crucial for risk assessment and decision-making. not reflect the real spatial variation characteristics beThis paper introduces a novel probability vector approach for spatial cause of uneven smoothing effects (Goovaerts, 1997, uncertainty modeling of soil classes based on an existing two-dimen- p. 369–370). As Journel (1997, p. viii) pointed out: “The sional Markov chain model for conditional simulation. The objective very reason for geostatistics and the future of the disis to find an accurate and efficient way to represent spatial uncertaint- cipline lie in the modeling of uncertainty, at each node ies that arise in mapping soil classes. Joint conditional probability through conditional distribution and globally through distribution (JCPD) represented by a set of occurrence probability stochasticimages(conditional simulations). ”Therefore, vectors (PVs) of soil classes is directly calculated from conditional soil survey maps should be accompanied by related spaMarkov transition probabilities, rather than the conventional approxitial uncertainty information. Data reflecting spatial un
The Elements of Investing

Foreword. Introduction. It All Starts with Saving. I. Save. First Do No Harm. Start Saving Early: Time Is Money. The Amazing Rule of 72. Savvy Savings. Small Savings Tips. Big Ways to Save. Let the Government Help You Save. Own Your Home. How Do I Catch Up? II. Index. Nobody Knows More Than the Market. The Index Fund Solution. Don't Some Beat the Market? Index Bonds. Index Internationally. Index Funds Have Big Advantages. One Warning. Confession. III. Diversify. Diversify Across Asset Classes. Diversify Across Markets. Diversify Over Time. Rebalance. IV. Avoid Blunders. Overconfidence. Beware of Mr. Market. The Penalty of Timing. More Mistakes. Minimize Costs. V. Keep It Simple. Review of Basic Rules. Asset Allocation. Asset Allocation Ranges. Investing in Retirement. KISS Investing A Super Simple Summary. Appendix: Save on Taxes Legally. Individual Retirement Accounts (IRAs). Roth IRAs. Pension Plans. Tax-Advantaged Saving for Education. Recommended Reading. Acknowledgments. About the Authors. Index.
Enhancing software development process using automated adaptation of object ensembles

Software development has been changing rapidly. This development process can be influenced through changing developer friendly approaches. We can save time consumption and accelerate the development process if we can automatically guide programmer during the software development. There are some approaches that recommend relevant code snippets and API-items to the developer. Some approaches apply general code, searching techniques and some approaches use an online based repository mining strategies. But it gets quite difficult to help programmers when they need particular type conversion problems especially when they want to adapt existing interfaces according to their expectation. One of the familiar triumphs to guide developers in such situation is adapting collections and arrays through automated adaptation of object ensembles. But how does it help a novice developer in real time software development that is not explicitly specified. In this paper, we have developed a system that works as a plug-in tool integrated with a particular Data Mining Integrated environment (DMIE) to recommend relevant interface while they seek for a type conversion situation. We have a mined repository of respective adapter classes and related APIs from where developer, search their query and get their result using the relevant transformer classes. The system that recommends developers titled automated objective ensembles (AOE plug-in). From the investigation as we have ever made, we can see that our approach much better than some of the existing approaches.
Rehabilitation exercise game model for post-stroke using Microsoft Kinect camera

The purpose of rehabilitation is to improve the movement of stroke patients so that they can independently perform daily tasks on their own. Conventional therapy is a tedious exercise which usually reduces the motivation of the patient to do the exercises. Video game is a way that can motivate and help patients recover their motor skills, and also act as a deterrent pain. Video games have been used in physiotherapy, occupational therapy, and psychotherapy. In order to increase mental satisfaction and physical vitality in rehabilitation therapy, some therapists have tried to use the off-the-shelf digital game devices in rehabilitation and have found effective treatment outcomes in addition to enhancing patients' treatment motivation. Although many studies have been done in this field, there is still lacking the existing recovery game, because too many different demands must be met for each type of therapy. There is one disadvantage at the beginning of the game because patients have difficulty understanding how to use it. The current recovery games are less fun and participative for the user, while the popular games have fewer components to use in rehabilitation training. Furthermore, post-stroke patients find it difficult to get a friend to play or spend time with them every day, which will make them feel isolated. Therefore, rehabilitation exercise games that support multi-player will provide a higher motivation than the single-player. Since most stroke patients suffer from cognitive impairment, cognitive challenge levels are also the key factors in the design of the game so that it does not become an obstacle for the recovery process. Therefore, this study develops a prototype of a rehabilitation exercise game that contains aspects of the social context, the type of movement and cognitive challenges. It also provides usability in game design, according to a post-stroke stage so that they can perform recovery activities based on their ability. In addition, this study highlights technology and rehabilitation exercise games in Malaysia.
Stress-resistant Translation of Cathepsin L mRNA in Breast Cancer Progression*

Background: Translational regulation might underlie the high expression levels of the protease cathepsin L (CTSL) associated with poor breast cancer prognosis. Results: Translation of CTSL mRNA is highly stress-resistant and promotes metastasis of murine breast cancer. Conclusion: CTSL mRNA circumvents translational shutdown in cancer-associated stress conditions. Significance: High expression of a metastasis promoting protease is maintained by translational regulation. The cysteine protease cathepsin L (CTSL) is often thought to act as a tumor promoter by enhancing tumor progression and metastasis. This goes along with increased CTSL activity in various tumor entities; however, the mechanisms leading to high CTSL levels are incompletely understood. With the help of the polyoma middle T oncogene driven breast cancer mouse model expressing a human CTSL genomic transgene, we show that CTSL indeed promotes breast cancer metastasis to the lung. During tumor formation and progression high expression levels of CTSL are maintained by enduring translation of CTSL mRNA. Interestingly, human breast cancer specimens expressed the same pattern of 5′ untranslated region (UTR) splice variants as the transgenic mice and the human cancer cell line MDA-MB 321. By polyribosome profiling of tumor tissues and human breast cancer cells, we observe an intrinsic resistance of CTSL to stress-induced shutdown of translation. This ability can be attributed to all 5′ UTR variants of CTSL and is not dependent on a previously described internal ribosomal entry site motif. In conclusion, we provide in vivo functional evidence for overexpressed CTSL as a promoter of lung metastasis, whereas high CTSL levels are maintained during tumor progression due to stress-resistant mRNA translation.
A wear-leveling algorithm exploiting k-bitwise operations for flash storage devices

Flash storage devices are widely used for mobile consumer electronics due to small size, low power consumption, and high performance. Generally, the flash storage device consists of NAND flash memories. Compared to traditional magnetic disks, NAND flash memory requires an additional erase operation and its blocks have limited erase cycles. For extending its endurance, various wear-leveling algorithms have been proposed. However, they invoke many read/write/erase operations and use many memory resources for managing their block states because they do not consider the property of the flash translation layer. To solve these problems, a new wear-leveling algorithm for the log-based flash translation layer is proposed in this paper. In the log-based flash translation layer, since log blocks are frequently updated and erased, the cold block rarely removed is reserved for a next log block so that all the blocks are evenly erased. In addition, the proposed algorithm reduces the usage of memory resources by exploiting k-bitwise erase table that only needs small k-bit erase flags for managing its block erase state. Through various experiments with related wear-leveling algorithms, this paper shows the superiority of the proposed wear-leveling algorithm.
Hyperbolic divergence cleaning for the MHD equations

In simulations of magnetohydrodynamic (MHD) processes the violation of the divergence constraint causes severe stability problems. In this paper we develop and test a new approach to the stabilization of numerical schemes. Our technique can be easily implemented in any existing code since there is no need to modify the solver for the MHD equations. It is based on a modified system in which the divergence constraint is coupled with the conservation laws by introducing a generalized Lagrange multiplier. We suggest a formulation in which the divergence errors are transported to the domain boundaries with the maximal admissible speed and are damped at the same time. This corrected system is hyperbolic and the density, momentum, magnetic induction, and total energy density are still conserved. In comparison to results obtained without correction or with the standard "divergence source terms," our approach seems to yield more robust schemes with significantly smaller divergence errors.
Magnetic Vortex Nanorings: A New Class of Hyperthermia Agent for Highly Efficient In Vivo Regression of Tumors

X. L. Liu, Prof. H. M. Fan Shaanxi Key Laboratory of Degradable Biomedical Materials School of Chemical Engineering Northwest University Taibai North Road 229 , Xi’an , Shaanxi 710069 , China E-mail: fanhm@nwu.edu. cn X. L. Liu, Dr. Y. Yang, Prof. J. Ding Department of Materials Science & Engineering Faculty of Engineering National University of Singapore 7 Engineering Drive 1, 117574 , Singapore E-mail: msedingj@nus.edu. sg Dr. C. T. Ng, Prof. B. H. Bay Department of Anatomy Yong Loo Lin School of Medicine National University of Singapore 4 Medical Drive , MD10, 117597 , Singapore Dr. L. Y. Zhao Key Laboratory of Advanced Materials School of Material Science & Engineering Tsinghua University Beijing 100084 , China Dr. Y. Zhang Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing 100190 , China
Demography and Consumption of Spodoptera litura (Lepidoptera: Noctuidae) Reared on Cabbage and Taro

Abstract Spodoptera litura (F.) causes considerable economic damage to multiple agro-crops annually in many countries. In this study, the demography of S. litura reared on cabbage and taro was investigated using the age-stage, two-sex life table at 25 ± 1°C, 60 ± 10% relative humidity, and a photoperiod of 12: 12 (L:D) h. Our results showed that the net reproductive rate, intrinsic rate, and finite rate of population increase on cabbage (1893.1 offspring, 0.2374 d−1, and 1.2679 d−1) were all not significantly different from those on taro (1361.0 offspring, 0.2298 d−1, and 1.2584 d−1). The net consumption rate on cabbage (439.1 cm2) was, however, three times higher than that on taro (141.7 cm2). According to the population parameters, both cabbage and taro are suitable host plants for S. litura. When both the population growth rate and the consumption rate were taken into consideration, the finite consumption rate on cabbage (ω = 3.8054) was significantly higher than that on taro (ω = 1.3184). In Taiwan, taro and cabbage are commonly planted in adjacent farm plots, with taro being grown from March to November and cabbage from October to April. Because of the overlapping growth periods of the two crops, S. litura can easily propagate throughout the year by switching between the adjacent crops during the overlap periods. Pest management strategies for controlling S. litura must be thoroughly reevaluated based on ecological characteristics, including its life table and consumption rate on its major host plants.
Percent Change Was and Is An Embarrassing Mistake

Any fool can predict the future; politicians and investment counselors do it all the time. Modeling past medical and financial events accurately remains a major challenge. Percent change is commonly used in these and other fields of measurement. Quantities in the form of a “percent” are used every day; they are familiar, useful, and generally harmless. But not always. Proportions as a percent, no problem. “Sixty percent of medical students are female. ” Percent as a measure of change: “My tax load has increased by 8% in the past year. ” No problem so far, but begs the question: 8% of what? Percent as a measure of relative change: “The group given “NewDrug™” increased bone density by 5%; 50% more than the group given “OldDrug™. ” This is a gross misrepresentation. “Despite recommendations that bone mineral density precision and followup assessment be based upon absolute measurements (in g/cm2), the use of relative change (in percent) is still frequently encountered. ”1 Two decades ago, I was 60 and my son 30, half my age. Thirty years later he will be 60, having aged 100%. If I survive, I will age only 33%. Clearly, he is aging 300% faster than I. A grandson, who will be 33 years of age at that time, will age 1000% during that same interval. In time I shall stop aging altogether, so they can catch up. Are things better in Boston? In the May 6, 2010, issue of the New England Journal of Medicine , a group from the Brigham and Women’s Hospital report on the use of a technology to reduce medication errors. “. units that did not use [the new technology] reported an 11.5% error rate . versus [a 6.8% error rate] in those that did. — a 41.4% relative reduction”2. (Why not a 4.7% reduction? … Address correspondence to Dr. H.A. Smythe, 2 Heathbridge Park, Toronto, Canada M4G 2Y6. E-mail: hasmythe{at}rogers.com
A Decomposition Method and Its Application to Convex Programming

A method is proposed for minimizing a function of the form q(x − d) + f1(x) + ⋯ + fm(x) where q is definite quadratic and fi are proper closed convex. The key feature of the method is its capability of reducing the problem to a sequence of subproblems of the form: min q(x − z) + fi(x). The method is an extension of the successive projection method given in [Han, S. -P. 1988. A successive projection method. Math. Programming 40 1–14. ] and has some similar features as the partial inverse method of Spingarn [Spingarn, J. E. 1983. Partial inverse of a monotone operator. Appl. Math. Optim. 10 247–265. ]. In combination with the proximal point algorithm [Martinet, B. 1970. Regularisation d'inequations variationelles par approximations successives. Rev. Francaise Inform. Rech. Oper. 154–159; Martinet, B. 1972. Determination approchee d'un point fixe d'une application pseudo-contractante. C.R. Acad. Sci. Paris 274 163–165; Rockafellar, R. T. 1976. Monotone operators and the proximal point algorithm. SIAM J. Control.
Marketing for Hospitality and Tourism

(NOTE: *Chapters 16 and 17 were renumbered from the 3rd edition.) I. UNDERSTANDING THE HOSPITALITY AND TOURISM MARKETING PROCESS. 1. Introduction: Marketing for Hospitality and Tourism. 2. Service Characteristics of Hospitality and Tourism Marketing. 3. The Role of Marketing in Strategic Planning. II. DEVELOPING HOSPITALITY AND TOURISM MARKETINGOPPORTUNITIES AND STRATEGIES. 4. The Marketing Environment. 5. Marketing Information Systems and Marketing Research. 6. Consumer Markets and Consumer Buying Behavior. 7. Organizational Buyer Behavior and Group Markets. 8. Market Segmentation, Targeting, and Positioning. III. DEVELOPING THE HOSPITALITY AND TOURISM MARKETING MIX. 9. Designing and Managing Products. 10. Internal Marketing. 11. Building Customer Loyalty through Quality. 12. Pricing Products: Pricing Considerations, Approaches and Strategy. 13. Distribution Channels. 14. Promoting Products: Communication and Promotion Policy and Advertising. 15. Promoting Products: Public Relations and Sales Promotion. 16. Professional Sales. * IV. MANAGING HOSPITALITY AND TOURISM MARKETING. 17. Electronic Marketing: Internet Marketing, Database Marketing and Direct Marketing. * 18. Destination Marketing. 19. Next Year's Marketing Plan.