Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Statics Analysis of Some Operations Management Problems

We propose a novel analytic approach for the comparative statics analysis of operations management problems on the capacity investment decision and the influenza (flu) vaccine composition decision. Our approach involves exploiting the properties of the underlying mathematical models, and linking those properties to the concept of stochastic orders relationship. The use of stochastic orders allows us to establish our main results without restriction to a specific distribution. A major strength of our approach is that it is “scalable,” i.e., it applies to capacity investment decision problem with any number of non-independent (i.e., demand or resource sharing) products and resources, and to the influenza vaccine composition problem with any number of candidate strains, without a corresponding increase in computational effort. This is unlike the current approaches commonly used in the operations management literature, which typically involve a parametric analysis followed by the use of the implicit function theorem. Providing a rigorous framework for comparative statics analysis, which can be applied to other problems that are not amenable to traditional parametric analysis, is our main contribution. We demonstrate this approach on two problems: (1) Capacity investment decision, and (2) influenza vaccine composition decision. A comparative statics analysis is integral to the study of these problems, as it allows answers to important questions such as, “does the firm acquire more or less of the different resources available as demand uncertainty increases? does the firm benefit from an increase in demand uncertainty? how does the vaccine composition change as the yield uncertainty increases? ” Using our proposed approach, we establish comparative statics results on how the newsvendor’s expected profit and optimal capacity decision change with demand risk and demand dependence in multi-product multi-resource newsvendor networks; and how the societal vaccination benefit, the manufacturer’s profit, and the vaccine output change with the risk of random yield of strains.
A New Methodology Based on Kano Model for the Evaluation of a New Product Acceptability during the Front-End Phases

Companies, which work on innovative products development, encounter difficulties to launch and commercialize new ideas. Many ideas, considered by companies as innovative, turn out to be commercial failures. Knowing customers needs and desires help companies preventing this situation and proposing successful products (products in their general definition, either material goods or services). Moreover, the earlier they know these needs, the greater their succeeding chances will be. This paper proposes a new methodology within three steps, to identify major stakeholderspsila needs, to classify and evaluate them and finally to compare several concepts. Kano model is used for requirement assessment and classification within four categories. This method can be used as decision aid tool for selecting the needs that should be fulfilled, according to their importance for the company.
Temporal encoded F-formation system for social interaction detection

In the context of a social gathering, such as a cocktail party, the memorable moments are generally captured by professional photographers or by the participants. The latter case is often undesirable because many participants would rather enjoy the event instead of being occupied by the photo-taking task. Motivated by this scenario, we propose the use of a set of cameras to automatically take photos. Instead of performing dense analysis on all cameras for photo capturing, we first detect the occurrence and location of social interactions via F-formation detection. In the sociology literature, F-formation is a concept used to define social interactions, where each detection only requires the spatial location and orientation of each participant. This information can be robustly obtained with additional Kinect depth sensors. In this paper, we propose an extended F-formation system for robust detection of interactions and interactants. The extended F-formation system employs a heat-map based feature representation for each individual, namely Interaction Space (IS), to model their location, orientation, and temporal information. Using the temporally encoded IS for each detected interactant, we propose a best-view camera selection framework to detect the corresponding best view camera for each detected social interaction. The extended F-formation system is evaluated with synthetic data on multiple scenarios. To demonstrate the effectiveness of the proposed system, we conducted a user study to compare our best view camera ranking with human's ranking using real-world data.
Mapping beta diversity from space: Sparse Generalised Dissimilarity Modelling (SGDM) for analysing high‐dimensional data

Spatial patterns of community composition turnover (beta diversity) may be mapped through generalised dissimilarity modelling (GDM). While remote sensing data are adequate to describe these patterns, the often high‐dimensional nature of these data poses some analytical challenges, potentially resulting in loss of generality. This may hinder the use of such data for mapping and monitoring beta‐diversity patterns. This study presents Sparse Generalised Dissimilarity Modelling (SGDM), a methodological framework designed to improve the use of high‐dimensional data to predict community turnover with GDM. SGDM consists of a two‐stage approach, by first transforming the environmental data with a sparse canonical correlation analysis (SCCA), aimed at dealing with high‐dimensional data sets, and secondly fitting the transformed data with GDM. The SCCA penalisation parameters are chosen according to a grid search procedure in order to optimise the predictive performance of a GDM fit on the resulting components. The proposed method was illustrated on a case study with a clear environmental gradient of shrub encroachment following cropland abandonment, and subsequent turnover in the bird communities. Bird community data, collected on 115 plots located along the described gradient, were used to fit composition dissimilarity as a function of several remote sensing data sets, including a time series of Landsat data as well as simulated EnMAP hyperspectral data. The proposed approach always outperformed GDM models when fit on high‐dimensional data sets. Its usage on low‐dimensional data was not consistently advantageous. Models using high‐dimensional data, on the other hand, always outperformed those using low‐dimensional data, such as single‐date multispectral imagery. This approach improved the direct use of high‐dimensional remote sensing data, such as time‐series or hyperspectral imagery, for community dissimilarity modelling, resulting in better performing models. The good performance of models using high‐dimensional data sets further highlights the relevance of dense time series and data coming from new and forthcoming satellite sensors for ecological applications such as mapping species beta diversity.
The blame game: performance analysis of speaker diarization system components

In this paper we discuss the performance analysis of a speaker diarization system similar to the system that was submitted by ICSI at the NIST RT06s evaluation benchmark. The analysis that is based on a series of oracle experiments, provides a good understanding of the performance of each system component on a test set of twelve conference meetings used in previous NIST benchmarks. Our analysis shows that the speech activity detection component contributes most to the total diarization error rate (23%). The lack of ability to model verlapping speech is also a large source of errors (22%) followed by the component that creates the initial system models (15%).
Robust motion segmentation via refined sparse subspace clustering

In this paper, a new refined sparse subspace clustering (RSSC) method is proposed for robust motion segmentation. Given a set of trajectories of tracked feature points from multiple moving object, RSSC aims at seeking a sparse representation (SR) for each trajectory with respect to a recovered low-rank dictionary. The segmentation of motion is obtained by applying spectral clustering to the affinity matrix built by this SR. Compared to the conventional sparse subspace clustering (SSC) algorithm, our RSSC integrates sparse representation and low-rank subspace structures recovery into a unified framework. Furthermore, SR is obtained from the recovered dictionary instead of the initial given dictionary built by contaminated data, making RSSC more robust to data noise. Experiments on toydata and real video sequences (Hopkins 155 database) show the superiority of our approach over several current state of the art methods.
Phosphorylation of SET Protein at Ser171 by Protein Kinase D2 Diminishes Its Inhibitory Effect on Protein Phosphatase 2A

We previously reported that protein kinase D2 (PKD2) in T cells is promptly activated after T-cell receptor (TCR) stimulation and involved in the activation of interleukin-2 promoter and T cell death, and that one of its candidate substrate is SET protein, a natural inhibitor for protein phosphatase 2A (PP2A). In this study, we investigated the target amino acid residues of SET phosphorylated by PKD2 and the effects of phosphorylation of SET on PP2A phosphatase activity. In vitro kinase assay using various recombinant SET mutants having Ser/Thr to Ala substitutions revealed that Ser171 of SET is one of the sites phosphorylated by PKD2. Recombinant SET with phosphorylation-mimic Ser171 to Glu substitution reduced its inhibitory effects on PP2A phosphatase activity compared with Ser171 to Ala substituted or wild-type SET. In addition, knockdown of PKD2 in Jurkat cells by RNAi or treatment of human CD4+ T cell clone with the PKD2 inhibitor Gö6976 resulted in reduced PP2A activity after TCR-stimulation judged from phosphorylation status of Tyr307 of the catalytic subunit of PP2A. These results suggest that PKD2 is involved in the regulation of PP2A activity in activated T cells through phosphorylation of Ser171 of SET.
Antibody Tracking Demonstrates Cell Type-Specific and Ligand-Independent Internalization of Guanylyl Cyclase A and Natriuretic Peptide Receptor C

Atrial natriuretic peptide (ANP) binds guanylyl cyclase-A (GC-A) and natriuretic peptide receptor-C (NPR-C). Internalization of GC-A and NPR-C is poorly understood, in part, because previous studies used 125I-ANP binding to track these receptors, which are expressed in the same cell. Here, we evaluated GC-A and NPR-C internalization using traditional and novel approaches. Although HeLa cells endogenously express GC-A, 125I-ANP binding and cross-linking studies only detected NPR-C, raising the possibility that past studies ascribed NPR-C-mediated processes to GC-A. To specifically measure internalization of a single receptor, we developed an 125I-IgG-binding assay that tracks extracellular FLAG-tagged versions of GC-A and NPR-C independently of each other and ligand for the first time. FLAG-GC-A bound ANP identically with wild-type GC-A and was internalized slowly (0.5%/min), whereas FLAG-NPR-C was internalized rapidly (2.5%/min) in HeLa cells. In 293 cells, 125I-ANP and 125I-IgG uptake curves were superimposable because these cells only express a single ANP receptor. Basal internalization of both receptors was 8-fold higher in 293 compared with HeLa cells and ANP did not increase internalization of FLAG-GC-A. For FLAG-NPR-C, neither ANP, BNP, nor CNP increased its internalization in either cell line. Prolonged ANP exposure concomitantly reduced surface and total GC-A levels, consistent with rapid exchange of extracellular and intracellular receptor pools. We conclude that ligand binding does not stimulate natriuretic peptide receptor internalization and that cellular environment determines the rate of this process. We further deduce that NPR-C is internalized faster than GC-A and that increased internalization is not required for GC-A down-regulation.
Games, Social Simulations, and Data—Integration for Policy Decisions

In this article, the authors discuss the development of the SUDAN GAME, an interactive model of the country in the time period leading up to the Sudanese referendum on the secession of the South. While many simulations are designed to educate about their subjects, the SUDAN GAME is intended to be a prototype for policy making via gameplay. It is implemented within COSMOPOLIS, a massively multiplayer online game that is currently undergoing development. In this article, the authors discuss the game’s design and how it can be used for policy development, with a focus on the underlying model and some discussion of the COSMOPOLIS implementation. They situate the game relative to other games that have crowdsourced serious problems and discuss the meaning of the policy solutions and collaboration witnessed along players. They conclude with a discussion of future development to be done to improve and expand upon the concepts used in their game.
Incidence, natural history and cardiovascular events in symptomatic and asymptomatic peripheral arterial disease in the general population.

BACKGROUND Intermittent claudication is associated with a poor prognosis, but less is known of the risks associated with asymptomatic peripheral arterial disease. The aims of this study were to determine the incidence and natural history of claudication, and the incidence of cardiovascular events in symptomatic and asymptomatic peripheral arterial disease. METHODS In 1988, 1592 subjects aged 55-74 years were selected randomly from the age-sex register of 10 general practices in Edinburgh, Scotland. The presence of peripheral arterial disease was determined by the World Health Organization questionnaire on intermittent claudication, the ankle brachial pressure index and a reactive hyperaemia test. This cohort was followed prospectively over 5 years for subsequent cardiovascular events and death. RESULTS One hundred and sixteen new cases of claudication were identified (incidence density 15.5 per 1000 person-years). Of those with claudication at baseline, 28.8% and still had pain after 5 years, 8.2% underwent vascular surgery or amputation, and 1.4% developed leg ulceration. Claudicants had a significantly increased risk of developing angina compared with normals (RR: 2.31, 95% CI: 1.04-5.10), and asymptomatic subjects had a slightly increased risk of myocardial infarction and stroke. Deaths from cardiovascular disease were more likely in both claudicants (RR: 2.67, 95% CI: 1.34-5.29) and subjects with major (RR: 2.08, 95% CI: 1.13-3.83) or minor asymptomatic disease (RR: 1.74, 95% CI: 1.09-2.76). Subjects with major asymptomatic disease also had an increased risk of non-cardiovascular death (RR: 2.19, 95% CI: 1.33-3.59), and therefore had the highest overall risk of death (RR: 2.44, 95% CI: 1.59-3.74). CONCLUSIONS Subjects with asymptomatic peripheral arterial disease appear to have the same increased risk of cardiovascular events and death found in claudicants.
Serum Selenium Concentrations and Hypertension in the US Population

Background—Selenium is an antioxidant micronutrient with potential interest for cardiovascular disease prevention. Few studies have evaluated the association between selenium and hypertension, with inconsistent findings. We explored the relationship of serum selenium concentrations with blood pressure and hypertension in a representative sample of the US population. Methods and Results—We undertook a cross-sectional analysis of 2638 adults ≥40 years old who participated in the 2003 to 2004 National Health and Nutrition Examination Survey. Serum selenium was measured by inductively coupled plasma-dynamic reaction cell-mass spectrometry. Hypertension was defined as blood pressure ≥140/90 mm Hg or current use of antihypertensive medication. Mean serum selenium was 137.1 μg/L. The multivariable adjusted differences (95% CIs) in blood pressure levels comparing the highest (≥150 μg/L) to the lowest (<122 μg/L) quintile of serum selenium were 4.3 (1.3 to 7.4), 1.6 (−0.5 to 3.7), and 2.8 (0.8 to 4.7) mm Hg for systolic, diastolic, and pulse pressure, respectively. The corresponding odds ratio for hypertension was 1.73 (1.18 to 2.53). In spline regression models, blood pressure levels and the prevalence of hypertension increased with increasing selenium concentrations up to 160 μg/L. Conclusions—High serum selenium concentrations were associated with higher prevalence of hypertension. These findings call for a thorough evaluation of the risks and benefits associated with high selenium status in the United States.
Aristotle's Nicomachean Ethics: An Introduction

1. Reading Aristotle's 'Ethics' 2. An outline of the goal of human life 3. Character-related virtue 4. Actions as signs of character 5. Some particular character-related virtues 6. Justice as a particular character-related virtue 7. Thinking-related virtue 8. Arkrasia, or failure of self-control 9. Friendship 10. Pleasure 11. Happiness in outline.
Cell Cycle– and Chaperone-Mediated Regulation of H3K56ac Incorporation in Yeast

Acetylation of histone H3 lysine 56 is a covalent modification best known as a mark of newly replicated chromatin, but it has also been linked to replication-independent histone replacement. Here, we measured H3K56ac levels at single-nucleosome resolution in asynchronously growing yeast cultures, as well as in yeast proceeding synchronously through the cell cycle. We developed a quantitative model of H3K56ac kinetics, which shows that H3K56ac is largely explained by the genomic replication timing and the turnover rate of each nucleosome, suggesting that cell cycle profiles of H3K56ac should reveal most first-time nucleosome incorporation events. However, since the deacetylases Hst3/4 prevent use of H3K56ac as a marker for histone deposition during M phase, we also directly measured M phase histone replacement rates. We report a global decrease in turnover rates during M phase and a further specific decrease in turnover at several early origins of replication, which switch from rapidly replaced in G1 phase to stably bound during M phase. Finally, by measuring H3 replacement in yeast deleted for the H3K56 acetyltransferase Rtt109 and its two co-chaperones Asf1 and Vps75, we find evidence that Rtt109 and Asf1 preferentially enhance histone replacement at rapidly replaced nucleosomes, whereas Vps75 appears to inhibit histone turnover at those loci. These results provide a broad perspective on histone replacement/incorporation throughout the cell cycle and suggest that H3K56 acetylation provides a positive-feedback loop by which replacement of a nucleosome enhances subsequent replacement at the same location.
POSITION PAPER: Modularizing Global Variable In Climate Simulation Software

In large-scale simulation codes, such as climate models, variables represent a large number of characteristics of earth surface and atmosphere for a single multi-dimensional celland are distributed over a multitude of cores in the supercomputers where these simulations run. The hundreds of variables allow different parts of simulation representing specific sub-models, for example the photosynthesis, to interact with other sub-models of the simulation. The scientists of each domain write the simulation code for the sub-model representing their sub-domain. To integrate their code into the entire simulation, they need to deal with hundreds of unfamiliar variables of which only a small subset is relevant to their work.Designing such variables in a modular fashion, so that the scientists could interact only with the variables relevant to their sub-model is likely to increase the productivity of the scientists and to increase accuracy of the simulation codes.A natural way to group the variables into modules is by using a language feature that group them together, such as, struct construct in C language or a class in C$++$ language. Each scientist would then need to familiarize themselves with only a small subset of modules that contain variables used in their simulations. For example, Community Earth System Model (CESM) code v1.06 has 51 such modules (structures) that contain 1479 variables.The methods proposed below can be used to assess the modularity of the existing set of structures and to generate alternative modularizations that improve upon it.In a nutshell, the approach minimizes the number of variablesexposed to other domains by the modules used in each domain.
Evaluation of an 18-Micron Filter for Use in Reptile Blood Transfusions Using Blood from American Alligators (Alligator mississippiensis)

Abstract: Blood transfusions are a common therapeutic procedure in small animal medicine and have been investigated in some exotic species but little information is available about their safety and efficacy in reptiles. In human pediatrics and small animal practice, the Hemo-Nate®18-μ filter is used to prevent embolic clots and particulate waste from entering the recipient during a transfusion. The goal of this study was to determine the hemolytic effect of an 18-μ Hemo-Nate filter for whole blood cell transfusions in reptiles using the American alligator (Alligator mississippiensis) as a reptilian model. Results revealed no significant difference in free plasma hemoglobin between the unfiltered and filtered samples (P = 0.21). There was no difference in the prefiltration and postfiltration packed cell volume (PCV) (P = 0.41). Results suggest that an 18-μ Hemo-Nate filter does not cause hemolysis or decrease the PCV of small quantities of alligator blood.
An Overview of Hierarchical Task Network Planning

Hierarchies are the most common structure used to understand the world better. In galaxies, for instance, multiple-star systems are organised in a hierarchical system. Then, governmental and company organisations are structured using a hierarchy, while the Internet, which is used on a daily basis, has a space of domain names arranged hierarchically. Since Artificial Intelligence (AI) planning portrays information about the world and reasons to solve some of world’s problems, Hierarchical Task Network (HTN) planning has been introduced almost 40 years ago to represent and deal with hierarchies. Its requirement for rich domain knowledge to characterise the world enables HTN planning to be very useful, but also to perform well. However, the history of almost 40 years obfuscates the current understanding of HTN planning in terms of accomplishments, planning models, similarities and dierences among hierarchical planners, and its current and objective image. On top of these issues, attention attracts the ability of hierarchical planning to truly cope with the requirements of applications from the real world. We propose a framework-based approach to remedy this situation. First, we provide a basis for defining dierent formal models of hierarchical planning, and define two models that comprise a large portion of HTN planners. Second, we provide a set of concepts that helps to interpret HTN planners from the aspect of their search space. Then, we analyse and compare the planners based on a variety of properties organised in five segments, namely domain authoring, expressiveness, competence, performance and applicability. Furthermore, we select Web service composition as a real-world and current application, and classify and compare the approaches that employ HTN planning to solve the problem of service composition. Finally, we conclude with our findings and present directions for future work.