Miracle-dz/UniFAR-FTUs huggingface dataset:
Do You Receive a Lighter Prison Sentence Because You Are a Woman? An Economic Analysis of Federal Criminal Sentencing Guidelines

The Federal criminal sentencing guidelines struck down by the U.S. Supreme Court in 2005 required that males and females who commit the same crime and have the same prior criminal record be sentenced equally. Using data obtained from the United States Sentencing Commission’s records, we examine whether there exists any gender-based bias in criminal sentencing decisions. We treat months in prison as a censored variable in order to account for the frequent outcome of no prison time. Additionally, we control for the self-selection of the defendant into guilty pleas through use of an endogenous switching regression model. A new decomposition methodology is employed. Our results indicate that women receive more lenient sentences even after controlling for circumstances such as the severity of the offense and past criminal history.
Distributed Collaborative Visualization Using Light Field Rendering

Interactive distributed visualization is an emerging technology with numerous applications. However, many of the present approaches of interactive distributed visualization are based on the traditional polygonal processing graphics pipeline. Our research is centred on investigating an alternative method using Image-Based Rendering (IBR) which uses (multiple) images of the scene instead of a 3D geometrical representation. A key advantage to the use of IBR techniques is that the bandwidth required is independent of scene complexity and is therefore predictable given knowledge of the desired final image resolution. In this paper, we describe our IBR based interactive distributed visualization platform involving Light Field rendering and present results which indicate the scalability of our approach to accommodate multiple collaborative users. To our knowledge this is the first system to demonstrate deployment of interactive Light Field rendering to large numbers of distributed users.
Hydrogen fluoride phase behavior and molecular structure: Ab initio derived potential models

Several variations of ab initio based molecular models for hydrogen fluoride (HF) are examined by Monte Carlo molecular simulation to determine their bulk-phase properties. The models are taken from the literature, and represent fits of functional forms to the potential energy surface of the HF dimer as given by ab initio computational chemistry calculations. For one of these models, we examine three variations for bulk-phase modeling. In particular, we consider first the effect of including versus neglecting an Ewald sum for the long-range dipole–dipole interactions; second, we examine a modification of the form for the short range repulsive region of the potential; and third, we add three-body contributions to the energy via an available 12-dimensional potential for the trimer, again representing a fit to ab initio energy calculations. The simulations examine the density (via isothermal–isobaric simulation) and radial distribution function (via canonical–ensemble simulations) each at two state points wh.
Mediaded. : A study on Community Video as a tool for Empowerment in rural India.

This thesis explores the potential of community video for rural development work in India. It addresses the topic via a process-oriented approach, looking into the individual steps from the creation of a video until its dissemination. Considering it as a form of storytelling, it goes beyond research projects which are finite and only focus on the final product. Storytelling in urban settings has been studied with an emphasis on the individual. Development work however goes beyond the individual, aiming for a broader influence. Thus, community video was studied in the context of developmental organizations which create films along with groups. As far as empowerment as a necessary basis for development is concerned, the study analyzes whether community video fosters or even creates the feeling of empowerment. In order to do justice to both- the medium community video and the storytelling process of it, the aspects of empowerment were examined through narrative analysis of videos and ethnographic field research combined with interviews and discussions. The connections which were discovered between narrative elements and empowerment were discussed with production teams and audiences. These discussions revealed that the communities were well aware of the power of community video and saw it as a tool for increasing knowledge within their own groups. This knowledge encompasses informational content as well as experience-sharing. It came to the fore that especially sharing has an empowering nature. The communities also see it as a mouthpiece to make the world aware of their issues and at the same time show society that they are capable of much more than what stereotypes suggest. The empowering effects of community video go beyond a simple feeling of empowerment and furthermore enable the communities to take action for their own progress. The field observations showed that with the help of organizations, the triggers for empowerment within the individual storytelling stages, from creation to dissemination, can be enhanced. Interviews with the heading organizations indicated that a balance has to be found between teaching techniques and contextual influence. This means that models for effective community video use can be useful but at the same time, the immense creative potential of the communities has be preserved. The very experience of creating something is the core of empowerment in community videos for rural Indian communities.
Geographies of Securitized Catastrophe Risk and the Implications of Climate Change

Abstract This article analyzes the drivers and implications of catastrophe bonds’ growing popularity as an alternative asset class. As investor demand for bonds outpaces their supply from reinsurers, the study asks how the place-based physical vulnerabilities of fixed capital have been rendered into assets deemed increasingly desirable by growing blocks of financial capital. Combining data from extended interviews with industry datasets and market reports, the study demonstrates how this securitization pathway allows mobile capital on a search for yield to reframe spatial liabilities as tradable assets, thus accessing new “returns on place. ” By aggregating and analyzing data on approximately $37 billion in catastrophe bond transactions since 1997, the study reveals both the ongoing concentration of capital in so-called “peak perils” such as U.S. hurricane and earthquake risks, and the fragmentation and recombination of peak perils to create new risk/return profiles. These purposive, scalable, and selective financial engagements with catastrophic risks depend upon the avoidance of the fixed costs and relational entanglements borne by (re)insurers. This ambivalent relationship with geographical liabilities is reaching its logical apogee in recent proposals to expand the catastrophe bond market to capitalize on growing climate change risks. This movement to “underwrite to securitize” intentionally emulates the “originate to securitize” model pioneered in mortgage-backed securities. This study argues that such developments could ultimately yield a built environment that is both more dependent on the state as an insurer of last resort and less adapted to climate extremes.
Challenges of multi‐actor involvement in the public sector front‐end innovation processes

Purpose – Studies with a user approach in a public service context are still rare, making the contribution of this study worthwhile. This paper aims to present a case of facilitating innovativeness by involving stakeholder groups in the development of service production in the public sector. The case is related to the provision of housing and well‐being services to ageing people. The study proposes focusing on the front‐end stage of an innovation process: the ideation phase in a virtual idea generation environment, in which fruitful and fresh ideas that are based on customers' needs are sought for in order to support the innovation process.Design/methodology/approach – A constructive research approach is applied in this study. Central theoretical building blocks are provided by the extended SECI model as presented by Uotila, Melkas and Harmaakorpi, Amabile's componential theory of creativity and Burt's and Granovetter's arguments regarding structural holes and weak ties.Findings – Based on the evaluation,.
A Practical Simulation Method for Social Networks

With the increasing popularity of social networks, it is becoming more and more crucial for the decision makers to analyze and understand the evolution of these networks in order to identify e.g., potential business opportunities. Unfortunately, understanding social networks, which are typically complex and dynamic, is not an easy task. In this paper, we propose an effective and practical approach for simulating social networks. We first develop a social network model that considers the addition and deletion of nodes and edges. We consider the nodes' in-degree, inter-nodes' close degree, which indicates how close the nodes are in the social network, and the limit of the network size in the social network model. We then develop a graph-based stratified random sampling algorithm for generating an initial network. To obtain the snapshots of a social network of the past, current and the future, we further develop a close degree algorithm and a close degree of estimation algorithm. The degree distribution of our model follows a power-law distribution with a "fat-tail". Experimental results using real-life social networks show the effectiveness of our proposed simulation method.
Probing the dynamics of cell di erentiation in a model of DrosophilaneurogenesisGeorge

We have formulated a computational model of Drosophila early neurogenesis, the process by which neu-roblasts and sensory organ precursor (SOP) cells differentiate from within proneural clusters of cells. The model includes intracellular gene regulatory interactions as well as lateral cell-cell signalling. It makes predictions about how the interplay of factors like proneural cluster shape and size, gene expression levels, and strength of cell-cell signalling determines the timing and position of appearance of neuroblasts and SOP cells; and about the robustness of this process and the eeects of gene product level perturbations on cell diierentiation.
Polyphonic Instrument Recognition for exploring semantic Similarities in Music

Similarity is a key concept for estimating associations amo ng a set of objects. Music similarity is usually exploited to retrie ve relevant items from a dataset containing audio tracks. In this work, w e approach the problem of semantic similarity between short pie ces of music by analysing their instrumentations. Our aim is to lab e audio excerpts with the most salient instruments (e.g. piano, human voice, drums ) and use this information to estimate a semantic relation (i.e. similarity) between them. We present 3 differe nt methods for integrating along an audio excerpt frame-based clas sifier decisions to derive its instrumental content. Similarity b etween audio files is then determined solely by their attached label s. We evaluate our algorithm in terms of label assignment and simi larity assessment, observing significant differences when compar ing it to commonly used audio similarity metrics. In doing so we tes t on music from various genres of Western music to simulate rea l world scenarios.
Spectrum Hole Identification in IEEE 802.22 WRAN using Unsupervised Learning

In this paper we present a Cooperative Spectrum Sensing (CSS) algorithm for Cognitive Radios (CR) based on IEEE 802.22 Wireless Regional Area Network (WRAN) standard. The core objective is to improve cooperative sensing efficiency which specifies how fast a decision can be reached in each round of cooperation (iteration) to sense an appropriate number of channels/bands (i.e. 86 channels of 7MHz bandwidth as per IEEE 802.22) within a time constraint (channel sensing time). To meet this objective, we have developed CSS algorithm using unsupervised K-means clustering classification approach. The received energy level of each Secondary User (SU) is considered as the parameter for determining channel availability. The performance of proposed algorithm is quantified in terms of detection accuracy, training and classification delay time. Further, the detection accuracy of our proposed scheme meets the requirement of IEEE 802.22 WRAN with the target probability of falsealrm as 0.1. All the simulations are carried out using Matlab tool. Received on XXXX; accepted on XXXX; published on XXXX
Coordination in CIM:Bringing Database Functionality to Application Systems

1-56555-147-8 c © 1998 Simulation Councils, Inc. Coordination in CIM means enforcing dependencies between autonomous application subsystems. We propose an architecture that generalizes multidatabase technology and consists of a global coordinator and local specialized agents, one for each subsystem to be coordinated. The agent associated to a subsystem not only monitors relevant subsystem activity but also guarantees certain properties of operations executed in a subsystem. Therefore, it has to provide database functionality for subsystems even in cases they do not rest upon databases. The coordination itself is a synthesis of (advanced) transaction models and workflows. Aside from an introduction to the transactional coordination model, we concentrate in this paper on the analysis of different classes of subsystems and elaborate on properties required from the subsystem and its agent to ensure execution guarantees. Furthermore, we examine to which degree database functionality can be provided for application systems with a given set of properties. Our examples are taken from an industrial project in the area of computer integrated manufacturing. ∗This work has been partially supported by the Swiss Commission of Technology and Innovation (KTI) under contract number 3008.2 †Present address: Credit Suisse, Advanced Technologies, Postfach 100, CH–8070 Zurich
E-GOVERNMENT SYSTEM IN WIKINOMICS: STAKEHOLDERS AND CONFLICT

Despite the importance of how information and communication technology (ICT) contributes to public organizational performance is to researchers, managers, and policy makers, there is uncertainty and debate about the e-government (e-Gov) differing from traditional public management information systems (PMIS). In the meantime, the roar of collaborative culture already changes everything. The new world of wikinomics, which is based on four powerful new ideas: openness, peering, sharing, and acting globally is replacing some of the old tenants of business. Our research mainly focuses on several different theories, including transaction cost, barging power, and coordination in developing a new perspective to explain the e-Gov system development in the wikinomic world, and to provide a solution. It is important to understand these complex issues that underlie successful implementations and integrations of the e-Gov. It also explicates the nature of conflict in the design of information system and the reasons why stakeholders resist the systems. We apply the perspective to synthesize what is known about government value and clarify the supposed uncertainty about the relationship between the e-Gov and the traditional public management information systems. Our analysis also facilitates knowledge accumulation and creating concerning the governmental performance impact of ICTs.
A novel technique for object oriented relational database design

This paper reflects on a new method for implementing and designing object oriented relational databases. An introduction of the conventional methods is given initially. This method directly derives the database and its relational tables out of systems' classes and this is the novelty of this algorithm. Systems' class recognition is also embedded within the proposed method. Furthermore, the projected method is presented by means of a case study. Moreover, the already implemented systems are introduced. Other advantages and further works of the new method are outlined.
Allele-Specific Silencing of Mutant Huntingtin in Rodent Brain and Human Stem Cells

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder resulting from polyglutamine expansion in the huntingtin (HTT) protein and for which there is no cure. Although suppression of both wild type and mutant HTT expression by RNA interference is a promising therapeutic strategy, a selective silencing of mutant HTT represents the safest approach preserving WT HTT expression and functions. We developed small hairpin RNAs (shRNAs) targeting single nucleotide polymorphisms (SNP) present in the HTT gene to selectively target the disease HTT isoform. Most of these shRNAs silenced, efficiently and selectively, mutant HTT in vitro. Lentiviral-mediated infection with the shRNAs led to selective degradation of mutant HTT mRNA and prevented the apparition of neuropathology in HD rat's striatum expressing mutant HTT containing the various SNPs. In transgenic BACHD mice, the mutant HTT allele was also silenced by this approach, further demonstrating the potential for allele-specific silencing. Finally, the allele-specific silencing of mutant HTT in human embryonic stem cells was accompanied by functional recovery of the vesicular transport of BDNF along microtubules. These findings provide evidence of the therapeutic potential of allele-specific RNA interference for HD.
Ontological Models To Support Planning Operations

A fundamental requirement for success with technology such as automated planning is that it needs to operate on valid models or ontologies of the application domain. Making these models is difficult because the data involved are voluminous, dynamic and come from a variety of sources and formats, so manual entry and maintenance is prohibitive. Using an ontological framework such as OWL can greatly alleviate this effort, but domain experts reason in domain terms, not the formal logic of ontologies. This paper describes an editing system that allows NASA domain experts to construct and maintain ontological information, and yet produce a standard form that can be manipulated by automated planners and other AI applications.
CellClassifier: supervised learning of cellular phenotypes

UNLABELLED CellClassifier is a tool for classifying single-cell phenotypes in microscope images. It includes several unique and user-friendly features for classification using multiclass support vector machines AVAILABILITY Source code, user manual and SaveObjectSegmentation CellProfiler module available for download at www.cellclassifier. ethz.ch under the GPL license (implemented in Matlab).
Circuit acyclic clustering with input/output constraints and applications

This article studies a new circuit acyclic clustering problem which divides a combinational circuit into groups of sub-circuits, each of which has limited numbers of inputs and outputs. Several heuristics are proposed to solving this problem. We achieve 300% speedup on logic simulation, with an application of our approach, for finding an input vector that incurs minimum or maximum leakage power dissipation.
Equipment Simulation Training System Based on Virtual Reality

A method of building equipment simulation training system (ESTS) based on virtual reality is put forward. With the method, single equipment model is built by GL studio, and integrated equipment model is built by multigen creator. It adopts Petri Nets to model the operation rules of equipment. All of the models are driven all together by vega prime in the simulation scene at last. Design and key technologies of ESTS are presented. Software prototype of certain integrated communication system is developed based on plug-in framework. Its simulation examples show greatest traits on building similar large-scale simulation system.
Atorvastatin inhibits the immediate-early response gene EGR1 and improves the functional pro of CD4+T-lymphocytes in acute coronary syndromes

Background- Adaptive immune-response is associated with a worse outcome in acute coronary syndromes. Statins have anti-inflammatory activity beyond lowering lipid levels. We investigated the effects of ex-vivo and in-vivo atorvastatin treatment in acute coronary syndromes on CD4+T-cells, and the underlying molecular mechanisms. Approach and results- Blood samples were collected from 50 statin-naïve acute coronary syndrome patients. We assessed CD4+T-cell activation by flow-cytometry, the expression of 84 T-helper transcription-factors and 84 T-cell related genes by RT-qPCR, and protein expression by Western-blot, before and after 24-hours incubation with increasing doses of atorvastatin: 3-10-26 g/ml (corresponding to blood levels achieved with doses of 10-40-80 mg, respectively). After incubation, we found a significant decrease in interferon-? -producing CD4+CD28nullT-cells (P = 0.009) and a significant increase in interleukin-10-producing CD4+CD25highT-cells (P < 0.001). Atorvastatin increased the expression of 2 genes and decreased the expression of 12 genes (in particular, EGR1, FOS,CCR2 and toll like receptor-4; >3-fold changes). The in-vivo effects of atorvastatin were analyzed in 10 statin-free acute coronary syndrome patients at baseline, and after 24h and 48h of atorvastatin therapy (80 mg/daily): EGR1-gene expression decreased at 24h (P = 0.01) and 48h (P = 0.005); EGR1-protein levels decreased at 48h (P = 0.03). Conclusions-In acute coronary syndromes, the effects of atorvastatin on immune system might be partially related to the inhibition of the master regulator gene EGR1. Our finding might offer a causal explanation on why statins improve the early outcome in acute coronary syndromes.
Surface-induced cubic anisotropy in nanomagnets

We investigate the effect of surface anisotropy in a spherical many-spin magnetic nanoparticle. By computing minor loops, two-dimensional (2D) and 3D energyscape, and by investigating the behavior of the net magnetization, we show that in the case of not too strong surface anisotropy the behavior of the many-spin particle may be modeled by that of a macrospin with an effective energy containing uniaxial and cubic anisotropy terms. This holds for both the transverse and N\'eel's surface anisotropy models.
Background Detection by Two Way Technique

Background subtraction is one of the key techniques for automatic video analysis, especially in the domain of video surveillance. Although its importance, evaluations of recent background subtraction methods with respect to the challenges of video surveillance suffer from various short comings. To address this issue, we identify the main challenges of background subtraction in the field of video surveillance. We then compare the performance of two background subtraction methods. First we subtract the background by median value method and then by histogram method. Then we see the result of both methods on Casia NLPR gait database. Keywords— Foreground detection, Median Value, Histogram, Background subtraction