Miracle-dz/UniFAR-FTUs huggingface dataset:
Game choices : the intersection of real options and game theory

Introduction Leslie Rahl Part 1: OVERVIEW 1 Risk Budgeting: The Next Step of the Risk Management Journey - The Veteran's Prospective Leslie Rahl 2 Crisis and Risk Management Myron Scholes PART 2: UNDERSTANDING RISK BUDGETING 3 Risk Budgeting: Managing Active Risk at the Total Fund Level Kurt Winkelmann 4 The Dangers of Historical Hedge Fund Data Andrew B. Weisman and Jerome Abernathy 5 Value-at-Risk for Asset Managers Christopher L. Culp, Ron Mensink and Andrea M.P. Neves 6 Risk Budgeting fore Pension Funds and Investment Managers using VAR Michelle McCarthy 7 Risk Budgeting for Active Investment Managers Robert Litterman, Jacques Longerstaey, Jacob Rosengarten and Kurt Winkelmann 8 Risk Obsession: Does it Lead to Risk Aversion? Amy B. Hirsch 9 Market Neutral and Hedged Strategies Joseph G. Nicholas 10 The Infrastructure Challenge: Empowering the Stakeholder through the Successful Deployment of Technology and Data Gabriel Bousbib PART 3: PRACTITIONERS' THOUGHTS: CASE STUDIES IN RISK BUDGETING 11 Risk Budgeting in a Pension Fund Leo de Bever, Wayne Kozun and Barbara Zvan 12 Risk Budgeting with Conditional Risk Tolerance Michael de Marco and Todd E. Petzel 13 VAR for Fund Managers Stephen Rees
Development of Intelligent Surveillance System Focused on Comprehensive Flow

Surveillance cameras are today a common sight in public spaces and thoroughfares, where they are used to prevent crime and monitor traffic. However, human operators have limited attention spans and may miss anomalies. Here, we develop an intelligent surveillance system on the basis of spatio-temporal information in comprehensive flow of human traffic. The comprehensive flow is extracted from optical flows, and anomalies are identified on the basis of the spatiotemporal distribution. Because our system extracts only a few anomalies from many surveillance cameras, operators will not miss the important scenes. In experiment, we confirmed effectiveness of our intelligent surveillance system.
Spatially-aware indexing for image object retrieval

The success of image object retrieval systems relies on the visual bag-of-words paradigm, which allows image retrieval systems to adopt a retrieval strategy analogous to text retrieval. In this paper we propose two spatially-aware retrieval strategies for image object retrieval that replaces the vector space model. The advantage of the proposed spatially-aware indexing and retrieval strategies are threefold: (1) It allows for the deployment of small visual vocabularies, (2) the number of images evaluated at retrieval time is significantly reduced, and (3) it eliminates the need for a post-retrieval phase, which is normally used to test the spatial composition of the visual words in the retrieved images. The first spatially-aware retrieval strategy explores the direct neighbourhood of two local features for common visual words to determine the similarity of the region surrounding the local features. The second strategy embeds the spatial composition of its neighbourhood directly in the index using edge signatures. Both strategies rely on the coherence of the neighbourhood of points in different images containing similar objects. The comparison of the spatially-aware retrieval strategies against the vector space baseline shows a significant improvement in terms of early precision, and at the same time significantly reduce the number of candidates to be considered at retrieval time.
Crossing the boundary-Why putting the e in Government is the easy part

eGovernment is maturing but as the latest academic research and practitioners' experience shows, challenges rather lie in the managerial and political domain. Cross boundary collaboration, therefore, crossing jurisdictional and organisational boundaries is the next step for government. I offer recommendations and insights from around the globe. This working paper is aimed at administrative and industry professionals who are interested in current trends and challenges in eGovernment.
Application of the Cre recombinase/loxP system further enhances antitumor effects in cell type-specific gene therapy against carcinoembryonic antigen-producing cancer.

A considerable number of studies of cancer have shown that the cell type-specific promoter is an effective tool for selective expression of foreign genes in tumor cells. However, few reports have demonstrated significant in vivo antitumor effects using this strategy thus far, possibly because the low activity of such a promoter results in insufficient expression of genes in cancer cells as well as in insignificant antitumor effects, even when the cells are infected by highly efficient gene transfer methods. To overcome this problem, we used the Cre/loxP system for the cell type-specific gene therapy against carcinoembryonic antigen (CEA)-producing cancer. We constructed a pair of recombinant Ads. One expresses the Cre recombinase (Cre) gene under the control of the CEA promoter (Ad.CEA-Cre). The other contains the herpes simplex virus thymidine kinase (HSV-TK) gene separated from the strong CAG promoter by insertion of the neomycin resistance (neo) gene (Ad.lox-TK). The HSV-TK gene of the latter Ad is designed to be activated through excisional deletion of the neo gene by Cre enzyme released from the former one only when CEA-producing cells are infected simultaneously with these Ads. Coinfection by these Ads rendered a human CEA-producing cancer cell line 8.4-fold more sensitive to ganciclovir (GCV) compared with infection by Ad.CEA-TK alone, the HSV-TK gene of which is directly regulated by the CEA promoter. On the other hand, coinfection with these Ads did not significantly change the GCV sensitivity of non-CEA-producing cells. Intratumoral injection of Ad.CEA-Cre combined with Ad.lox-TK followed by GCV treatment almost completely eradicated CEA-producing tumors established in the subcutis of athymic mice, whereas intratumoral injection of Ad.CEA-TK with GCV administration at most retarded the growth of inoculated tumors. These results suggest distinct advantages of the Cre/loxP system applied in the conventional cell type-specific gene therapy against cancer.
Understanding Critical Quality Attributes for Nanocrystals from Preparation to Delivery

Poor solubility of active pharmaceutical ingredients (APIs) is a great challenge for the pharmaceutical industry and, hence, drug nanocrystals are widely studied as one solution to overcome these solubility problems. Drug nanocrystals have comparatively simple structures which make them attractive for the formulation for poorly soluble drugs, and their capability to improve the dissolution in vitro is easily demonstrated, but turning the in vitro superior properties of nanocrystals to success in vivo, is often demanding: controlled (including enhanced) drug dissolution followed by successful permeation is not guaranteed, if for example, the dissolved drug precipitates before it is absorbed. In this review critical quality attributes related to nanocrystal formulations from production to final product performance in vivo are considered. Many important parameters exist, but here physical stability (aggregation tendency and solid state form), solubility properties influencing dissolution and supersaturation, excipient use to promote the maintenance of supersaturation, and finally the fate of nanocrystals in vivo are the main subjects of our focus.
Regional Location and Identification Using Sparse Stations

Abstract : Locating events in Southern California is quite simple since we have about 500 stations, with a large fraction broadband (TriNet). We locate and identify within minutes. Thus, we have an opportunity to test hybrid methods against the full array estimate. Here we report on three projects addressing these issues; (1) locating events using one calibrated station with waveform data plus a few other stations with travel-time and polarity information, (2) particularly complex sub-regions where the depth phases such as pPn and sPn prove ineffective, and (3) calibrating paths using a combination of sparse regional waveforms and radar. In previous efforts (last years report) we presented results using waveforms from one-station (PAS) and a few polarities from the array (3 to 5). The model employed a grid-search over mechanism (strike, dip and rake) with the depth fixed. Along most paths the method proved effective when comparing against the entire network. Here we present results of letting the depth vary as well so that the single station must use pPn and sPn and the ratio of body waves to surface waves to fix the depth. Only about half the paths still work, but in those situations, the location is greatly improved over just travel-time fitting because of the whole seismogram matching procedure. Our method uses an adaptive grid search over location with calibrated Pnl and surface wave time shifts. However, the corrections to 1-D models are only applicable to areas in which the velocity structure does not vary drastically. Refracted phases, like Pn, at distances over 200 km provide most P arrival times. When the velocity structure begins to vary drastically near the source, the receiver, or along the propagation path, the arrival times vary greatly. Moreover, the structure modifies the waveform shape such that it makes identification of Pn and its associated depth phases exceedingly difficult. Such an area occurs beneath the high Southern Sierras through Owens Valley and int
A Continuous-time Inventory Model with Procurement from Spot Market 283

Abstract Not only the amount of product demand but also the prices of the product have a strong impact on a manufacturer’s revenue. In this paper we consider a continuous-time inventory model where the spot price of the product stochastically fluctuates according to a Brownian motion. Should information of the spot price be available, the manufacturer wishes to buy the product from the spot market if profitable. The purpose of this paper is to find an optimal procurement policy so as to minimize the total expected discounted costs over an infinite planning horizon. We extend Sulem(1986) model into the one in which not only demand but also the market price of the product follows geometric Brownian motions. Then we obtain the optimal cost as the solution of Quasivariational inequality, and show that there exists an optimal procurement policy as (s, S) policy. We shall clarify the dependence of such optimal (s, S) policy on the spot price at the procurement epoch. These values of (s, S) policy can be used and revised in the succeeding ordering cycles. Finally, some numerical examples are provided to investigate analytical properties of the expected cost function as well as of the optimal policy.
The pentatricopeptide repeat MTSF1 protein stabilizes the nad4 mRNA in Arabidopsis mitochondria

Gene expression in plant mitochondria involves a complex collaboration of transcription initiation and termination, as well as subsequent mRNA processing to produce mature mRNAs. In this study, we describe the function of the Arabidopsis mitochondrial stability factor 1 (MTSF1) gene and show that it encodes a pentatricopeptide repeat protein essential for the 3′-processing of mitochondrial nad4 mRNA and its stability. The nad4 mRNA is highly destabilized in Arabidopsis mtsf1 mutant plants, which consequently accumulates low amounts of a truncated form of respiratory complex I. Biochemical and genetic analyses demonstrated that MTSF1 binds with high affinity to the last 20 nucleotides of nad4 mRNA. Our data support a model for MTSF1 functioning in which its association with the last nucleotides of the nad4 3′ untranslated region stabilizes nad4 mRNA. Additionally, strict conservation of the MTSF1-binding sites strongly suggests that the protective function of MTSF1 on nad4 mRNA is conserved in dicots. These results demonstrate that the mRNA stabilization process initially identified in plastids, whereby proteins bound to RNA extremities constitute barriers to exoribonuclease progression occur in plant mitochondria to protect and concomitantly define the 3′ end of mature mitochondrial mRNAs. Our study also reveals that short RNA molecules corresponding to pentatricopeptide repeat-binding sites accumulate also in plant mitochondria.
Théorie économique de l'urbanisation discontinue

Although it is frequent, discontinuous (leapfrog) development has rarely been addressed by the literature, because traditional models are unable to conceive diverse urban forms. This article is a survey of theoretical explanations of discontinuous development. It follows two parts. First, taking in account uncertainty on future returns drives to include an option value in land prices. Landlords speculate on the future value of the land and may leave vacant their plot in order to take advantage of high future returns. Second, discontinuous development is the product of a preference for open space. Natural amenities are included in land prices and provoke a dispersion of developed lots. These mechanisms are reinforced by a vote “against growth” by the inhabitants, which drives to a severe control of new developments.
NATURE VS . MATH : INTERPRETING INDEPENDENT COMPONENT ANALYSIS IN LIGHT OF COMPUTATIONAL HARMONIC ANALYSIS

ICA has recently been applied to naturally-occurring data to uncover hidden fundamental components. Harmonic analysis has long been used to uncover hidden fundamental components of mathematically-defined objects. In my talk I will explore some recent parallelisms between ICA and CHA – fascinating similarities in the “hidden components” that the two subjects are uncovering. I will suggest that recent work on the independent components of images can best be interepreted in the light of recent constructions in harmonic analysis – such as ridgelets and curvelets. These mathematical objects exhibit surprising similarities to the results of ICA on certain naturally-occurring data.
ANALYZING A VEHICLE ROUTING PROBLEM WITH STOCHASTIC DEMANDS USING ANT COLONY OPTIMIZATION

In this paper the classical Vehicle Routing Problem (VRP) is extended to cover the more realistic case of uncertainty about customer demands. This case is modelled as a VRP with stochastic demands and tackled with a heuristic solution approach based on Ant Colony Optimization (ACO). The main issues studied in this paper are the modelling of the uncertainty (i) in terms of its influence on the performance of the algorithm and (ii) in terms of the structure and quality of the solutions with respect to different risk measures.
Individual Responses to a Computer Virus Threat

Research on individual behavior and decision making in a virus infection situation is important for developing information security protection. We have previously reported experimental studies that gathered basic information on awareness and behavior in a virus infection situation. In the present study, using a questionnaire and an experiment, we have found that individual behavior in a virus infection situation differs from what the questionnaire responses indicate. Analyzing the experimental data in combination with questionnaire results, we have investigated the correlation between the personal profile and the actions of a person in taking antivirus measures. Multivariate logistic regression analysis of the results showed that "multimedia skill", "group norm", and "altruism" in the personal profile are related to coping behavior in a virus infection situation. We also discuss some possible improvements in our experimental system.
C9orf72 ablation in mice does not cause motor neuron degeneration or motor deficits

How hexanucleotide (GGGGCC) repeat expansions in C9ORF72 cause amyotrophic lateral sclerosis (ALS) remains poorly understood. Both gain‐ and loss‐of‐function mechanisms have been proposed. Evidence supporting these mechanisms in vivo is, however, incomplete. Here we determined the effect of C9orf72 loss‐of‐function in mice.
Fit-for-Purpose: Species Distribution Model Performance Depends on Evaluation Criteria – Dutch Hoverflies as a Case Study

Understanding species distributions and the factors limiting them is an important topic in ecology and conservation, including in nature reserve selection and predicting climate change impacts. While Species Distribution Models (SDM) are the main tool used for these purposes, choosing the best SDM algorithm is not straightforward as these are plentiful and can be applied in many different ways. SDM are used mainly to gain insight in 1) overall species distributions, 2) their past-present-future probability of occurrence and/or 3) to understand their ecological niche limits (also referred to as ecological niche modelling). The fact that these three aims may require different models and outputs is, however, rarely considered and has not been evaluated consistently. Here we use data from a systematically sampled set of species occurrences to specifically test the performance of Species Distribution Models across several commonly used algorithms. Species range in distribution patterns from rare to common and from local to widespread. We compare overall model fit (representing species distribution), the accuracy of the predictions at multiple spatial scales, and the consistency in selection of environmental correlations all across multiple modelling runs. As expected, the choice of modelling algorithm determines model outcome. However, model quality depends not only on the algorithm, but also on the measure of model fit used and the scale at which it is used. Although model fit was higher for the consensus approach and Maxent, Maxent and GAM models were more consistent in estimating local occurrence, while RF and GBM showed higher consistency in environmental variables selection. Model outcomes diverged more for narrowly distributed species than for widespread species. We suggest that matching study aims with modelling approach is essential in Species Distribution Models, and provide suggestions how to do this for different modelling aims and species’ data characteristics (i.e. sample size, spatial distribution).
Social Networks Visualization : A Brief Survey

Visualization has always played a major role in “social networks analysis”, the discipline that studies the connections between social actors (humans, communities, companies) to understand how they organize and evolve. The recent development of computer-based interactive visualizations, however, opened the doors to a series of new capabilities that promise to enrich and facilitate the analysis of such networks. The main contribution of these tools is that they allows for interactive exploration, thus promoting and facilitating the analysis of open-ended questions. In this paper, we analyze the state of the art, providing background knowledge and commenting on benefits, remaining challenges, and trends.
THE UTILITY OF PLEASURE IS A PAIN FOR DECISION THEORY*

E~ a VERYBODY agrees that we have intrinsic desires. Obviously, we have desires; many of them are derivative; so, in a kind of analogy to a deductive theory that divides its provable statements into axioms and theorems, some of them must be basic. There is much less agreement about what our intrinsic desires are or should be. Still, no one doubts that we intrinsically desire, among other things, happiness, pleasure, and the absence of pain, certain qualities of our sensations, feelings, moods, and psychological states in general. We desire these things, but without having, or feeling the need to have, a justification for doing so. Desires come in various strengths, and, together with more or less firm beliefs, they guide rational action. The formal counterparts of these concepts in decision theory are utility and probability. The distinction between intrinsic and extrinsic desires is also reflected in decision theory, where each model contains a utility function that is basic (at least relative to that model) and an expected utility function that is derived from the basic utility function and the subjective probability function of the model. ' On the whole, decision theory certainly provides the best formal explication of our intuitive reasoning about desires and beliefs in practical deliberation. A person's intrinsically desired psychological states should thus be in the domain of her utility function. But then, we claim, decision theory fails. More specifically, we shall defend two theses:
Strategies for resolving Norm Conflicts in Practical Reasoning

Norm-governed agents act according to norms such as obligations, permissions or prohibitions. In their practical reasoning, they are not only influenced by what they actually belief, desire and intend, but what they are obliged, permitted or prohibited to do they are governed by norms. When agents adopt such norms, specific care must be taken to avoid conflicts, so that consistency of the set of norms currently held by the agent is preserved. In this paper, a set of conflict scenarios is outlined and strategies presented to solve such conflicts. With such strategies in place, the possible influence of obligations on the consistency of the agent’s currently held norms is analysed. The NoA Normative Agent Architecture is used for these investigations.
A Comparison of Four Methods for the Analysis of N-of-1 Trials

Objective To provide a practical guidance for the analysis of N-of-1 trials by comparing four commonly used models. Methods The four models, paired t-test, mixed effects model of difference, mixed effects model and meta-analysis of summary data were compared using a simulation study. The assumed 3-cycles and 4-cycles N-of-1 trials were set with sample sizes of 1, 3, 5, 10, 20 and 30 respectively under normally distributed assumption. The data were generated based on variance-covariance matrix under the assumption of (i) compound symmetry structure or first-order autoregressive structure, and (ii) no carryover effect or 20% carryover effect. Type I error, power, bias (mean error), and mean square error (MSE) of effect differences between two groups were used to evaluate the performance of the four models. Results The results from the 3-cycles and 4-cycles N-of-1 trials were comparable with respect to type I error, power, bias and MSE. Paired t-test yielded type I error near to the nominal level, higher power, comparable bias and small MSE, whether there was carryover effect or not. Compared with paired t-test, mixed effects model produced similar size of type I error, smaller bias, but lower power and bigger MSE. Mixed effects model of difference and meta-analysis of summary data yielded type I error far from the nominal level, low power, and large bias and MSE irrespective of the presence or absence of carryover effect. Conclusion We recommended paired t-test to be used for normally distributed data of N-of-1 trials because of its optimal statistical performance. In the presence of carryover effects, mixed effects model could be used as an alternative.
Leading to Change: The Challenge of the New Superintendency. Jossey-Bass Education Series.

The Superintendents and School Districts. GREAT EXPECTATIONS. The Promise and Prospect of Leadership. Looking for Leaders. EDUCATIONAL LEADERSHIP. Crafting a Vision. Leading Reform. Engaging School Leaders. POLITICAL LEADERSHIP. Political Contexts and Constituents. The Politics of Equity and Excellence. MANAGERIAL LEADERSHIP. Managing to Lead. Managerial Levers. LEADING TO CHANGE. Toward a New Superintendency.
An Overview of Direct Diagnosis and Repair Techniques in the WeeVis Recommendation Environment

Constraint-based recommenders support users in the identification of items (products) fitting their wishes and needs. Example domains are financial services and electronic equipment. In this paper we show how divide-and-conquer based (direct) diagnosis algorithms (no conflict detection is needed) can be exploited in constraint-based recommendation scenarios. In this context, we provide an overview of the MediaWiki-based recommendation environment WeeVis.