Miracle-dz/UniFAR-FTUs huggingface dataset:
Perturbative instabilities in Hǒrava gravity

We investigate the scalar and tensor perturbations in Hořava gravity, with and without detailed balance, around a flat background. Once both types of perturbations are taken into account, it is revealed that the theory is plagued by ghost-like scalar instabilities in the range of parameters which would render it power-counting renormalizable, that cannot be overcome by simple tricks such as analytic continuation. Implementing a consistent flow between the UV and IR limits seems thus more challenging than initially presumed, regardless of whether the theory approaches General Relativity at low energies or not. Even in the phenomenologically viable parameter space, the tensor sector leads to additional potential problems, such as fine-tunings and super-luminal propagation.
On the Lattice Distortion Problem

We introduce and study the \emph{Lattice Distortion Problem} (LDP). LDP asks how "similar" two lattices are. I.e., what is the minimal distortion of a linear bijection between the two lattices? LDP generalizes the Lattice Isomorphism Problem (the lattice analogue of Graph Isomorphism), which simply asks whether the minimal distortion is one. As our first contribution, we show that the distortion between any two lattices is approximated up to a $n^{O(\log n)}$ factor by a simple function of their successive minima. Our methods are constructive, allowing us to compute low-distortion mappings that are within a $2^{O(n \log \log n/\log n)}$ factor of optimal in polynomial time and within a $n^{O(\log n)}$ factor of optimal in singly exponential time. Our algorithms rely on a notion of basis reduction introduced by Seysen (Combinatorica 1993), which we show is intimately related to lattice distortion. Lastly, we show that LDP is NP-hard to approximate to within any constant factor (under randomized reductions), by a reduction from the Shortest Vector Problem.
Information Structures to Secure Control of Rigid Formations with Leader-Follower Structure

This paper is concerned with rigid formations of mobile autonomous agents using a leader-follower structure. A formation is a group of agents moving in real 2or 3dimensional space. A formation is called rigid if the distance between each pair of agents does not change over time under ideal conditions. Sensing/communication links between agents are used to maintain a rigid formation. Two agents connected by a sensing/communication link are called neighbors. There are two types of neighbor relations in rigid formations. In the first type, the neighbor relation is symmetric. In the second type, the neighbor relation is asymmetric. Rigid formations with a leader-follower structure have the asymmetric neighbor relation. A framework to analyze rigid formations with symmetric neighbor relations is given in our previous work. This paper suggests an approach to analyze rigid formations that have a leader-follower structure.
Sociodemographic, health and lifestyle characteristics reported by discrete groups of adult dietary supplement users in Alberta, Canada: findings from The Tomorrow Project

Abstract Objective To determine the extent to which differences in sociodemographic, dietary and lifestyle characteristics exist between users of different types of dietary supplements and supplement non-users. Design We analysed cross-sectional data obtained from self-administered questionnaires completed at baseline by participants in The Tomorrow Project; a prospective cohort study in Alberta, Canada. Participants who used at least one type of dietary supplement at least weekly in the year prior to questionnaire completion were defined as supplement users, while the remainder were classified as non-users. Seven discrete user categories were created: multivitamins (+/− minerals) only, specific nutritional supplements only, herbal/other supplements only, and all possible combinations. Differences in sociodemographic, dietary and lifestyle characteristics between different groups of supplement users and non-users were analysed using Rao–Scott χ2 tests and multinomial logistic regression. Subjects and setting Subjects were 5067 men and 7439 women, aged 35–69 years, recruited by random digit dialling throughout Alberta. Results Supplement use was extensive in this study population (69·8 %). Users of herbal/other supplements only, and women who used multivitamins only, tended to report dietary and lifestyle characteristics that were not significantly different from non-users. In contrast, those who reported using a combination of multivitamins, specific nutritional and herbal/other supplements were more likely than non-users to report behaviours and characteristics consistent with current health guidelines. Conclusions Dichotomizing participants as supplement users or non-users is likely to mask further differences in sociodemographic, dietary and lifestyle characteristics among users of different types of supplements. This may have implications for analysis and interpretation of observational studies.
Examining Spillover Effects From Teach For America Corps Members in Miami-Dade County Public Schools

This article examines Teach For America’s (TFA) placement strategy in Miami-Dade County Public Schools, in which large numbers of TFA corps members are placed as clusters into a targeted set of disadvantaged schools, to investigate whether the large-scale infusion of TFA corps members into these schools induced broader improvements across the school. Using 6 years of administrative data from the district, we exploit variation in TFA density over time within schools to measure the extent to which increases in density were associated with improvements in student test scores. We find that many of the schools chosen to participate in the cluster strategy experienced large subsequent gains in mathematics achievement. These gains were driven in part by the direct effect of having larger numbers of classrooms staffed by effective TFA teachers. However, we do not find any evidence that the clustering strategy led to any spillovers on schoolwide performance.
A Fuzzy Cache Replacement Policy and Its Experimental Performance Assessment

Caching is one of the most effective techniques for improving the performance of 10 accesses between computing units and memories. The cache replacement policy determines which objects remain in cache and which are evicted to make room for new objects. We have proposed a new fuzzy algorithm called fuzzy page replacement (FPR) in this paper. The performance of this algorithm is compared with the well-known cache replacement algorithms through simulation. Simulation results show that this fuzzy approach outperforms the other algorithms and has the potential to be considered in future researches
Simultaneous human-robot adaptation for effective skill transfer

In this paper, we propose and implement a human-in-the loop robot skill synthesis framework that involves simultaneous adaptation of the human and the robot. In this framework, the human demonstrator learns to control the robot in real-time to make it perform a given task. At the same time, the robot learns from the human guided control creating a non-trivial coupled dynamical system. The research question we address is how this system can be tuned to facilitate faster skill transfer or improve the performance level of the transferred skill. In the current paper we report our initial work for the latter. At the beginning of the skill transfer session, the human demonstrator controls the robot exclusively as in teleoperation. As the task performance improves the robot takes increasingly more share in control, eventually reaching full autonomy. The proposed framework is implemented and shown to work on a physical cart-pole setup. To assess whether simultaneous learning has advantage over the standard sequential learning (where the robot learns from the human observation but does not interfere with the control) experiments with two groups of subjects were performed. The results indicate that the final autonomous controller obtained via simultaneous learning has a higher performance measured as the average deviation from the upright posture of the pole.
High-Voltage Insulation Power Modules-SystemDesign and Qualification One of the substantial causes of reliability

One of the substantial causes of reliability deficiencies in soldered-base power modules is the soldering between the substrate and the base plate. This is owing to the surface area of this interface, which is very large in comparison to other soldered areas, and the large mismatches between the Coefficient of Thermal Expansion of the insulator and the base plate materials. But not all failures can be attributed solely to this factor. Others such as wire bond lift-off, die attach failure, insulator cracking and power terminals detachment are main contributors. A real design for a cost-efficient module with no compromise in system reliability will be introduced here, where design reliability has been verified in accordance with industrial standards. Luca Casolino, Process Engineer, Semikron Srl, Italy
Examination of the Seasonal Dynamics of the Toxic Dinoflagellate Alexandrium catenella at Redondo Beach, California, by Quantitative PCR

ABSTRACT The presence of neurotoxic species within the genus Alexandrium along the U.S. coastline has raised concern of potential poisoning through the consumption of contaminated seafood. Paralytic shellfish toxins (PSTs) detected in shellfish provide evidence that these harmful events have increased in frequency and severity along the California coast during the past 25 years, but the timing and location of these occurrences have been highly variable. We conducted a 4-year survey in King Harbor, CA, to investigate the seasonal dynamics of Alexandrium catenella and the presence of a particulate saxitoxin (STX), the parent compound of the PSTs. A quantitative PCR (qPCR) assay was developed for quantifying A. catenella in environmental microbial assemblages. This approach allowed for the detection of abundances as low as 12 cells liter−1, 2 orders of magnitude below threshold abundances that can impact food webs. A. catenella was found repeatedly during the study, particularly in spring, when cells were detected in 38% of the samples (27 to 5,680 cells liter−1). This peak in cell abundances was observed in 2006 and corresponded to a particulate STX concentration of 12 ng liter−1, whereas the maximum STX concentration of 26 ng liter−1 occurred in April 2008. Total cell abundances and toxin levels varied strongly throughout each year, but A. catenella was less abundant during summer, fall, and winter, when only 2 to 11% of the samples yielded positive qPCR results. The qPCR method developed here provides a useful tool for investigating the ecology of A. catenella at subbloom and bloom abundances.
Feedback control of combustion instabilities from within limit cycle oscillations using H∞ loop-shaping and the ν-gap metric

Combustion instabilities arise owing to a two-way coupling between acoustic waves and unsteady heat release. Oscillation amplitudes successively grow, until nonlinear effects cause saturation into limit cycle oscillations. Feedback control, in which an actuator modifies some combustor input in response to a sensor measurement, can suppress combustion instabilities. Linear feedback controllers are typically designed, using linear combustor models. However, when activated from within limit cycle, the linear model is invalid, and such controllers are not guaranteed to stabilize. This work develops a feedback control strategy guaranteed to stabilize from within limit cycle oscillations. A low-order model of a simple combustor, exhibiting the essential features of more complex systems, is presented. Linear plane acoustic wave modelling is combined with a weakly nonlinear describing function for the flame. The latter is determined numerically using a level set approach. Its implication is that the open-loop transfer function (OLTF) needed for controller design varies with oscillation level. The difference between the mean and the rest of the OLTFs is characterized using the ν-gap metric, providing the minimum required ‘robustness margin’ for an H∞ loop-shaping controller. Such controllers are designed and achieve stability both for linear fluctuations and from within limit cycle oscillations.
Buspirone and Sertraline in the Treatment of a Patient with Refractory Obsessive-Compulsive Disorder

Objective: To describe a hospitalized patient with refractory obsessive-compulsive disorder (OCD) and to briefly review the supporting literature. Case Summary: A 33-year-old man was admitted with a diagnosis of depression and OCD. Prior drug therapy included numerous medications, but none improved the OCD. Clonazepam therapy was initiated for treatment of anxiety and propranolol was begun to treat his headaches. Sertraline and buspirone were added sequentially to control the symptoms of depression and OCD. Subjective improvement was noted within a few weeks after the combination therapy was begun. Six and four weeks after starting sertraline and buspirone, respectively, the patient's symptoms remain improved. Discussion: Fluoxetine has been shown to be effective in the management of OCD. Sertraline, another selective serotonin-reuptake inhibitor, also looks promising for OCD therapy. Buspirone is a serotonin1A-receptor agonist, and theoretically could augment the effect of selective serotonin-reuptake inhibitors in the treatment of OCD. Conclusions: This patient's OCD symptoms responded to a combination of sertraline and buspirone therapy. It is difficult to confirm whether buspirone augmented the effects of sertraline in this patient. Clinical trials should be developed to determine whether these regimens are, in fact, beneficial in patients with refractory OCD.
Diversity and Abundance of Nitrate Reductase Genes (narG and napA), Nitrite Reductase Genes (nirS and nrfA), and Their Transcripts in Estuarine Sediments

ABSTRACT Estuarine systems are the major conduits for the transfer of nitrate from agricultural and other terrestrial-anthropogenic sources into marine ecosystems. Within estuarine sediments some microbially driven processes (denitrification and anammox) result in the net removal of nitrogen from the environment, while others (dissimilatory nitrate reduction to ammonium) do not. In this study, molecular approaches have been used to investigate the diversity, abundance, and activity of the nitrate-reducing communities in sediments from the hypernutrified Colne estuary, United Kingdom, via analysis of nitrate and nitrite reductase genes and transcripts. Sequence analysis of cloned PCR-amplified narG, napA, and nrfA gene sequences showed the indigenous nitrate-reducing communities to be both phylogenetically diverse and also divergent from previously characterized nitrate reduction sequences in soils and offshore marine sediments and from cultured nitrate reducers. In both the narG and nrfA libraries, the majority of clones (48% and 50%, respectively) were related to corresponding sequences from delta-proteobacteria. A suite of quantitative PCR primers and TaqMan probes was then developed to quantify phylotype-specific nitrate (narG and napA) and nitrite reductase (nirS and nrfA) gene and transcript numbers in sediments from three sites along the estuarine nitrate gradient. In general, both nitrate and nitrite reductase gene copy numbers were found to decline significantly (P < 0.05) from the estuary head towards the estuary mouth. The development and application, for the first time, of quantitative reverse transcription-PCR assays to quantify mRNA sequences in sediments revealed that transcript numbers for three of the five phylotypes quantified were greatest at the estuary head.
A NeuroIS Platform for Lab Experiments

Problem Identification and Motivation NeuroIS research necessitates the collection of high quality empirical data (Dimoka et al. 2012). In particular, research in this domain necessitates the collection of psychophysiological and neuroimaging data synchronized to a subject's current context. Here, context refers to the environment and the behavior of the observed subject, e.g., decisions during an auction, answers on a questionnaire, or the time to complete a control task. Due to the controlled environment, many researchers use lab experiments to conduct their studies and collect the above described data (Falk & Heckman 2009). Software used in these lab experiments, either third-party or customized software, often suffers from a number of limitations, such as (i) a limited set of functionalities, both for the user interface and the experimental structure, (ii) data collection and storage being spread over several different tools, which results in data synchronization problems and time consuming post-experiment data cleaning, (iii) being limited in subject size or possibilities in subject interaction, (iv) requiring to learn new or proprietary programming languages in addition to heavy programming effort, (v) no extensibility to handling emerging and changing software and hardware, e.g., new operating systems or new bio sensor technology, (vi) missing flexibility to handle requirements of experimental economists, IS researchers, or to meet future requirements, such as integrating physiological data to research technostress (Riedl et al. 2012). Objectives of the Solution Following a design science approach (Peffers et al. 2008), we next define broad objectives of a possible solution to address the problems stated above.  Facilitating the creation of lab experiments by reducing development time and cycles  Facilitating individual & group interactions in a controlled lab setting  Integrating measurements of bio sensors and logging of physiological data specific to subject events  Ease of event logging and data storage, enabling experiments to scale in time and subject size  Meeting emerging technical requirements in the field of IS research and experimental economics Design and Development To address these objectives, we herewith present a Java™-based platform, which provides functionalities necessary to run NeuroIS lab experiments while, at the same time, offering flexibility to adapt to experiment specific requirements. The platform implementation is inspired by Smith's (1982) definition of an experimental system. In combination with the integration of bio sensors, the platform can be used in many research disciplines, which seek to apply a NeuroIS approach, e.g., design science (vom Brocke et …
A Machine Learning Approach to Musically Meaningful Homogeneous Style Classification

Recent literature has demonstrated the difficulty of classifying between composers who write in extremely similar styles (homogeneous style). Additionally, machine learning studies in this field have been exclusively of technical import with little musicological interpretability or significance. We present a supervised machine learning system which addresses the difficulty of differentiating between stylistically homogeneous composers using foundational elements of music, their complexity and interaction. Our work expands on previous style classification studies by developing more complex features as well as introducing a new class of musical features which focus on local irregularities within musical scores. We demonstrate the discriminative power of the system as applied to Haydn and Mozart's string quartets. Our results yield interpretable musicological conclusions about Haydn's and Mozart's stylistic differences while distinguishing between the composers with higher accuracy than previous studies in this domain.
Filtered Patent Maps for Predicting Diversification Paths of Inventors and Organizations

In a patent technology network map, almost all pairs of technology classes are connected, whereas most of the connections are extremely weak. This observation suggests the need and also the possibility to filter the network map by removing the negligible and noisy links. But link removal may reduce the power of the network for predicting the cross-field patent portfolio diversification of inventors and inventing organizations. This paper proposes a metric for such predictive power of a patent network, and a method that allows one to objectively choose a best tradeoff between predictive power and the removal of weak links. We show the results that identify filtered networks below the optimal tradeoff, and also remove a degree of arbitrariness compared with other filtering treatments from the literature. On that basis, we further demonstrate the use of filtered technology maps to visualize and analyze the main paths of patent portfolio diversification of a prolific inventor (Leonard Forbes) and a technology company (Google Inc.).
Correlations Of Student Grades And Behavior While Using A Course Management System Under Different Contexts

As the Internet is in widespread use by engineering faculty, the opportunity exists to collect measures of student learning behavior based on their use of the Internet learning tools. One such tool is a course management system (CMS). Data on student use of a CMS is readily available from login records and the web server log file. It has been shown that this data, paired with contextual information about the CMS, such as which files are related to course content or to assignments, can be used to generate measures of student behavior that significantly correlate with the students’ final grades in the course. These measures can add a typically unobtainable set of information about student behavior outside the classroom to the instructor’s overall efforts in evaluating a course. However, measures of student interaction with a CMS must be examined in context of how that CMS is used with the class. Patterns of student interaction may be very different if the CMS is used as a database of information or as an interactive learning tool. A previous study of two courses delivered by a CMS where one was used as a database of information and the other as an interactive learning tool in addition to a database showed that measures had different results and had different correlation patterns with student grades. To further examine patterns of student interaction with a CMS in relation to grades, data were collected for individual students on six measures of student behavior over the entire semester from seven courses delivered by a CMS. These measures are total time logged in to the CMS, average length of visits, total number of logins, total hits on any course content file, total hits on the main course page, and total hits on the course assignments page. The seven courses are categorized according to how the CMS is used in supporting their courses and what functions were employed. For each course, the six measures were paired with final grades for each student and examined in a correlation analysis. The patterns of correlations between courses are discussed in the paper along with implications for making general guidelines for interpreting measures of student behavior as measured through a CMS.