Miracle-dz/UniFAR-FTUs huggingface dataset:
When Reform Politicians Eliminate the Goods of other Political Actors

This paper describes the consequences of institutional reforms when these encounter opposition by other political actors. Within the rational institutionalism paradigm, Fritz W. Scharpf has argued that a utility-maximizing actor will violate the norms of formal institutions if the expected gains from breaching institutional arrangements exceed the expected costs of institutional adherence. The theory of the rule-violating actor is tested on the case of the Danish reform of public administration, where 14 counties were consolidated into five regional units, which operate under a new governance structure. Under this new governance structure the regional councilors’ opportunity to pursue substantial and institutional goods is reduced. The hypothesis therefore, is that the regional councilors will violate the institutional norms in order to be better positioned to pursue both substantial and institutional goods. The analysis tends to support Scharpf’s rule-violating theory. The Danish regional councilors violate the stipulation by making cosmetic changes in the mandates in order to continue the work and by ensuring that the “continuing committees” contain the same councilor members as in the preceding year. Regardless of this permanentization the regions attempt to keep the committees temporary in order to ensure that the councilors are financial compensated.
A bottom-up, view-point invariant human detector

We propose a bottom-up human detector that can deal with arbitrary poses and viewpoints. Heads, limbs and torsos are individually detected, and an efficient assembly strategy is used to perform the human detection and the part segmentation. Firstly, a topological model is used to represent the structure of the human body, and the topologically equivalent configurations are ranked with additional priors. Promising results prove the approach efficiency for detecting people in low-resolution and compressed images.
Development of Recovery Rapids - A game for cost effective stroke therapy

Here we discuss the development of a rehabilitation game that targets the upper extremity. Our target is an in-home implementation of Constraint-Induced Movement Therapy (CI Therapy), the current gold standard. Evidence based medicine supports the use of CI Therapy, but the widespread application of the treatment is hindered by the cost and accessibility as well as insurance reimbursement. The factors are driving the need for an affordable, accessible and effective alternative. Individuals with stroke and therapist stakeholders indicated that the following elements were required for effective "gamification" of CI therapy: intuitive game mechanics, proximal and distal motor practice, customization to the user, and the core components of CI therapy. These design considerations are present throughout every aspect of game design from scene selection through gameplay goals and gameplay mechanics. We discuss those decisions in game design including selection of game platform and interface devices, content generation, and game mechanics. We report on feedback regarding feasibility and acceptance and preliminary evidence of treatment efficacy. General Terms Design.
Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network

Effectively modelling hidden structures in a network is very practical but theoretically challenging. Existing relational models only involve very limited information, namely the binary directional link data, embedded in a network to learn hidden networking structures. There is other rich and meaningful information (e.g., various attributes of entities and more granular information than binary elements such as "like" or "dislike") missed, which play a critical role in forming and understanding relations in a network. In this work, we propose an informative relational model (InfRM) framework to adequately involve rich information and its granularity in a network, including metadata information about each entity and various forms of link data. Firstly, an effective metadata information incorporation method is employed on the prior information from relational models MMSB and LFRM. This is to encourage the entities with similar metadata information to have similar hidden structures. Secondly, we propose various solutions to cater for alternative forms of link data. Substantial efforts have been made towards modelling appropriateness and efficiency, for example, using conjugate priors. We evaluate our framework and its inference algorithms in different datasets, which shows the generality and effectiveness of our models in capturing implicit structures in networks.
Recommendation algorithm focused on individual viewpoints

In recommender systems, it is essential to improve the adaptability not for some typical user models but for each individual. In this paper, we propose several personalization methods for content recommendation focused on individual differences in intention to select contents and in the desire to acquire information. We provide multiple content-based algorithms for TV program recommendation having respective different purposes. We then present the results of a field user test for five weeks demonstrating our new method that can enhance the adaptability for each individual, especially the method of personalizing the contribution of each attributes by extracting differences between user preference and common preference. Finally, we discuss about the necessity of dynamic algorithm adaptation depending on the characteristics of the users.
Technical Report : Adaptive Model-Based Control for Underwater Vehicles : Theory and Experimental Evaluation in the Presence of Unmodeled Actuator Dynamics

This paper reports a comparative experimental evaluation of proportional derivative and adaptive modelbased control for underwater vehicles. To the best of the authors’ knowledge, this is the first such evaluation of modelbased adaptive tracking control for underwater vehicles during simultaneous dynamic motion in all 6 degrees-of-freedom. This experimental evaluation revealed the presence of unmodeled thruster dynamics arising during reversals of the vehicle’s thrusters, and that the unmodeled thruster dynamics can destabilize parameter adaptation. The three major contributions of this paper are: an experimental analysis of how unmodeled thruster dynamics can destabilize parameter adaptation, a twostep adaptive model-based control algorithm which is robust to the thruster modeling errors present, and a comparative experimental evaluation of adaptive model-based control and proportional derivative control for fully-actuated underwater vehicles preforming simultaneous 6 degree-of-freedom trajectory tracking.
A Metabolic Operon in Extraintestinal Pathogenic Escherichia coli Promotes Fitness under Stressful Conditions and Invasion of Eukaryotic Cells

ABSTRACT We identified a carbohydrate metabolic operon (frz) that is highly associated with extraintestinal pathogenic Escherichia coli (ExPEC) strains. The frz operon codes for three subunits of a phosphoenolpyruvate:carbohydrate phosphotransferase system (PTS) transporter of the fructose subfamily, for a transcriptional activator of PTSs of the MgA family, for two type II ketose-1,6-bisphosphate aldolases, for a sugar-specific kinase (repressor, open reading frame, kinase family [ROK]), and for a protein of the cupin superfamily. We proved that the frz operon promotes bacterial fitness under stressful conditions, such as oxygen restriction, late stationary phase of growth, or growth in serum or in the intestinal tract. Furthermore, we showed that frz is involved in adherence to and internalization in human type II pneumocytes, human enterocytes, and chicken liver cells by favoring the ON orientation of the fim operon promoter and thus acting on the expression of type 1 fimbriae, which are the major ExPEC adhesins. Both the PTS activator and the metabolic enzymes encoded by the frz operon are involved in these phenotypes.
Extending the E-Z Reader Model of Eye Movement Control to Chinese Readers

Chinese readers' eye movements were simulated in the context of the E-Z Reader model, which was developed to account for the eye movements of readers of English. Despite obvious differences between English and Chinese, the model did a fairly good job of simulating the eye movements of Chinese readers. The successful simulation suggests that the control of eye movements in reading Chinese is similar to that in an alphabetic language such as English.
Improving response to critical laboratory results with automation: results of a randomized controlled trial.

OBJECTIVE To evaluate the effect of an automatic alerting system on the time until treatment is ordered for patients with critical laboratory results. DESIGN Prospective randomized controlled trial. INTERVENTION A computer system to detect critical conditions and automatically notify the responsible physician via the hospital's paging system. PATIENTS Medical and surgical inpatients at a large academic medical center. One two-month study period for each service. MAIN OUTCOMES Interval from when a critical result was available for review until an appropriate treatment was ordered. Secondary outcomes were the time until the critical condition resolved and the frequency of adverse events. METHODS The alerting system looked for 12 conditions involving laboratory results and medications. For intervention patients, the covering physician was automatically notified about the presence of the results. For control patients, no automatic notification was made. Chart review was performed to determine the outcomes. RESULTS After exclusions, 192 alerting situations (94 interventions, 98 controls) were analyzed. The intervention group had a 38 percent shorter median time interval (1.0 hours vs. 1.6 hours, P = 0.003; mean, 4.1 vs. 4.6 hours, P = 0.003) until an appropriate treatment was ordered. The time until the alerting condition resolved was less in the intervention group (median, 8.4 hours vs. 8.9 hours, P = 0.11; mean, 14.4 hours vs. 20.2 hours, P = 0.11), although these results did not achieve statistical significance. The impact of the intervention was more pronounced for alerts that did not meet the laboratory's critical reporting criteria. There was no significant difference between the two groups in the number of adverse events. CONCLUSION An automatic alerting system reduced the time until an appropriate treatment was ordered for patients who had critical laboratory results. Information technologies that facilitate the transmission of important patient data can potentially improve the quality of care.
Individual differences predict sensitivity to the uncanny valley

It can be creepy to notice that something human-looking is not real. But can sensitivity to this phenomenon, known as the uncanny valley, be predicted from superficially unrelated traits? Based on results from at least 489 participants, this study examines the relation between nine theoretically motivated trait indices and uncanny valley sensitivity, operationalized as increased eerie ratings and decreased warmth ratings for androids presented in videos. Animal Reminder Sensitivity, Neuroticism, its Anxiety facet, and Religious Fundamentalism significantly predicted uncanny valley sensitivity. In addition, Concern over Mistakes and Personal Distress significantly predicted android eerie ratings but not warmth. The structural equation model indicated that Religious Fundamentalism operates indirectly, through robot-related attitudes, to heighten uncanny valley sensitivity, while Animal Reminder Sensitivity increases eerie ratings directly. These results suggest that the uncanny valley phenomenon may operate through both sociocultural constructions and biological adaptations for threat avoidance, such as the fear and disgust systems. Trait indices that predict uncanny valley sensitivity warrant investigation by experimental methods to explicate the processes underlying the uncanny valley phenomenon.
Distributed Cognition: A Perspective from Social Choice Theory

Distributed cognition refers to processes which are (i) cognitive and (ii) distributed across multiple agents or devices rather than performed by a single agent. Distributed cognition has attracted interest in several fields ranging from sociology and law to computer science and the philosophy of science. In this paper, I discuss distributed cognition from a social-choice-theoretic perspective. Drawing on models of judgment aggregation, I address two questions. First, how can we model a group of individuals as a distributed cognitive system? Second, can a group acting as a distributed cognitive system be ‘rational’ and ‘track the truth’ in the outputs it produces? I argue that a group’s performance as a distributed cognitive system depends on its ‘aggregation procedure’ – its mechanism for aggregating the group members’ inputs into collective outputs – and I investigate the properties of an aggregation procedure that matter.
A fine-grained performance model for GPU architectures

The increasing programmability, performance, and cost/effectiveness of GPUs have led to a widespread use of such many-core architectures to accelerate general purpose applications. Nevertheless, tuning applications to efficiently exploit the GPU potentiality is a very challenging task, especially for inexperienced programmers. This is due to the difficulty of developing a SW application for the specific GPU architectural configuration, which includes managing the memory hierarchy and optimizing the execution of thousands of concurrent threads while maintaining the semantic correctness of the application. Even though several profiling tools exist, which provide programmers with a large number of metrics and measurements, it is often difficult to interpret such information for effectively tuning the application. This paper presents a performance model that allows accurately estimating the potential performance of the application under tuning on a given GPU device and, at the same time, it provides programmers with interpretable profiling hints. The paper shows the results obtained by applying the proposed model for profiling commonly used primitives and real codes.
Assessing tracking performance in complex scenarios using mean time between failures

Existing measures for evaluating the performance of tracking algorithms are difficult to interpret, which makes it hard to identify the best approach for a particular situation. As we show, a dummy algorithm which does not actually track scores well under most existing measures. Although some measures characterize specific error sources quite well, combining them into a single aggregate measure for comparing approaches or tuning parameters is not straightforward. In this work we propose `mean time between failures' as a viable summary of solution quality - especially when the goal is to follow objects for as long as possible. In addition to being sensitive to all tracking errors, the performance numbers are directly interpretable: how long can an algorithm operate before a mistake has likely occurred (the object is lost, its identity is confused, etc.)? We illustrate the merits of this measure by assessing solutions from different algorithms on a challenging dataset.
Controlling development and chemotaxis of soft-bodied multicellular animats with the same gene regulatory network

The ability to actively forage for resources is one of the defining properties of animals, and can be seen as a form of minimal cognition. In this paper we model soft-bodied robots, or “animats”, which are able to swim in a simulated twodimensional fluid environment toward food particles emitting a diffusive chemical signal. Both the multicellular development and behaviour of the animats are controlled by a gene regulatory network (GRN), which is encoded in a linear genome. Coupled with the simulated physics, the activity of the GRN affects cell divisions and cell movements during development, as well as the expansion and contraction of filaments connecting the cells in the swimming adult body. The global motion that emerges from the dynamics of the animat relies on the spring-like filaments and drag forces created by the fluid. Our study shows that it is possible to evolve the animat’s genome (through mutations, duplications and deletions) to achieve directional motion in this environment. It also suggests that a “minimally cognitive” behaviour of this kind can emerge without a central control or nervous system.
GaN Technology for Radars

Microwave GaN technology is now in production and poised to revolutionize many of today’s radar and communication systems. Simultaneously, mm-wave GaN processes are rapidly being matured to meet the growing needs of high power and efficiency, at higher frequencies. In this paper, we present an overview of GaN development, focusing on reliability and affordability for defense applications.
Female cleaner fish cooperate more with unfamiliar males

Joint group membership is of major importance for cooperation in humans, and close ties or familiarity with a partner are also thought to promote cooperation in other animals. Here, we present the opposite pattern: female cleaner fish, Labroides dimidiatus, behave more cooperatively (by feeding more against their preference) when paired with an unfamiliar male rather than with their social partner. We propose that cooperation based on asymmetric punishment causes this reversed pattern. Males are larger than and dominant to female partners and are more aggressive to unfamiliar than to familiar female partners. In response, females behave more cooperatively with unfamiliar male partners. Our data suggest that in asymmetric interactions, weaker players might behave more cooperatively with out-group members than with in-group members to avoid harsher punishment.
A framework for real time communication in sensor networks

The introduction of real time communication has created additional challenges in the wireless networks area with different communication constraints. Sensor nodes spend most of their lifetime functioning as a small router to deliver packets from one node to another until the packet reaches the sink. Since sensor networks represent a new generation of time-critical applications, it is often necessary for communication to meet real time constraints as well as other constrains. Nevertheless, research dealing with providing QoS guarantees for real time traffic in sensor networks is still in its infancy. This paper presents a novel packet delivery mechanism, namely Multiple Level Stateless Protocol (MLSP), as a real time protocol for sensor networks to guarantee the quality of traffic in wireless Sensor Networks. MLSP improves the packet loss rate and handles holes in sensor networks. This paper also introduces the k-limited polling model. This model is used in a sensor network by the implementation of two queues served according to a 2-limited polling model in a sensor node. Here, two different classes of traffic are considered and the exact packet delay for each corresponding class is calculated. The analytical results are validated through an extensive simulation study.
Polarized dust emission of magnetized molecular cloud cores

We compute polarization maps for molecular cloud cores modeled as magnetized singular isothermal toroids, under the assumption that the emitting dust grains are aspherical and aligned with the large-scale magnetic field. We show that, depending on the inclination of the toroid with the line-of-sight, the bending of the magnetic field lines resulting from the need to counteract the inward pull of gravity naturally produces a depolarization effect toward the centre of the map. We compute the decrease of polarization degree with increasing intensity for different viewing angles and frequencies, and we show that an outward increasing temperature gradient, as expected in starless cores heated by the external radiation field, enhances the decrease of polarization. We compare our results with recent observations, and we conclude that this geometrical effect, together with other mechanisms of depolarization, may significantly contribute to the decrease of polarization degrees with intensity observed in the majority of molecular cloud cores. Finally, we consider the dependence of the polarization degree on the dust temperature gradient predicted for externally heated clouds, and we briefly comment on the limits of the Chandrasekhar-Fermi formula to estimate the magnetic field strength in molecular cloud cores.
Methodology for Evaluating Theproperties of Carbon Nano Tubes for Engineering Applications

Owing to the superior mechanical properties of Carbon Nanotubes (CNTs), research has been initiated to use this nanomaterial in construction industry. The elastic modulus of CNT is of great importance in order to use CNTs in construction industry. For judicious and effective application of CNT in construction industry where mass scale utilization is inevitable, it is important to accurately assess the properties of CNTs since these nano fiber materials are extremely cost sensitive. There is no well established tool or method available for the engineers to determine the properties of CNT, other than to accept the manufacturer’s data. Nanoscale continuum theory uses a representative volume to determine the elastic modulus which does not include the effect of radius and aspect ratio. In the present study, numerical model is developed and the validated one is used to study the effects of geometrical variability’s on the properties of CNT. Further, a methodology has been proposed to determine the mechanical properties, such as tensile stiffness, of the Carbon nanotube with a given structural arrangement (chirality and radius) if the same for the basic configuration, graphene, is known. The procedure discussed in this study will be helpful to the engineers to easily estimate the properties such as elastic modulus or tensile stiffness of CNTs before incorporating into conventional materials for developing new materials with enhanced properties.
Are Real Estate IPOs a Different Species? Evidence from Hong Kong IPOs

It is well documented that in the United States, real estate investment trust (REIT) initial public offerings (IPOs) have an abnormally low initial-day return when compared to that of industrial firm IPOs. Researchers suspect that the abnormal return pattern of REIT IPOs is caused by their unique real estate holdings. Examination of 399 IPOs issued in Hong Kong during the 1986-1997 period reveals strong evidence that suggests that underlying real estate holdings cannot be the sole reason for the observed low initial-day return of REIT IPOs. This investigation indicates that there is a need to re-think the current explanations for the abnormal performance of REIT IPOs.