Miracle-dz/UniFAR-FTUs huggingface dataset:
Configuration management for highly-customisable software

Customisable operating systems, database systems, and communication subsystems have demonstrated many advantages of customisation, including considerable performance improvements. One common approach for constructing customisable software is to implement it as a collection of modules that can be configured in different combinations to provide customised variants of the software. Typically, ad hoc methods are used to determine which modules may be combined. Such methods require intimate knowledge of the modules and their interactions or the configuration will not behave as expected. In this paper, we present a methodology that simplifies the difficult task of constructing correct custom variants of highly customisable software. The methodology is based on identifying relations between software modules that dictate which combinations are correct. We also introduce a configuration support tool that, based on these relations, allows only correct configurations to be created.
A Suspended Six-Port Transformer-Based Power Divider for 2.4 GHz Applications

This paper presents a transformer-based power divider with six-port suspending structure for 2.4 GHz wireless applications. The proposed power divider, which is featured with chip size (2.9 mm × 2.8 mm × 21 μm), was constructed by an 8-μm-thick Cu bottom electrode, a 5 μm-height supporting copper post, and an 8-μm-thick suspended spiral copper conducting layer with a 13 μm air gap. The main structure included two transformers and six input/output matching capacitors for simultaneously achieving two single-to-differential paths so that the chip size of the complex multiple-ports transceiver could be reduced. According to the results, the proposed divider has characteristics of the radio frequency (RF), and its input return losses are around −10 dB, output return losses are beneath −10 dB, and minimum amplitude imbalance is below 1.5 dB and less than 1° phase imbalance at 2.4 GHz operating frequency.
Controlling intestinal colonization of high-risk haematology patients with ESBL-producing Enterobacteriaceae: a randomized, placebo-controlled, multicentre, Phase II trial (CLEAR).

OBJECTIVES We assessed the efficacy and safety of an oral antimicrobial regimen for short- and long-term intestinal eradication of ESBL-producing Escherichia coli and Klebsiella pneumoniae (ESBL-EC/KP) in immunocompromised patients. METHODS We performed a randomized (2:1), double-blind multicentre Phase II study in four haematology-oncology departments. Patients colonized with ESBL-EC/KP received a 7 day antimicrobial regimen of oral colistin (2 × 106 IU 4×/day), gentamicin (80 mg 4×/day) and fosfomycin (three administrations of 3 g every 72 h), or placebo. Faecal, throat and urine specimens were collected on day 0, 6 ± 2, 11 ± 2, 28 ± 4 and 42 ± 4 after treatment initiation, and the quantitative burden of ESBL-EC/KP, resistance genes and changes in intestinal microbiota were analysed. Clinicaltrials.gov: NCT01931592. RESULTS As the manufacture of colistin powder was suspended worldwide, the study was terminated prematurely. Overall, 29 (18 verum/11 placebo) out of 47 patients were enrolled. The short-term intestinal eradication was marginal at day 6 (verum group 15/18, 83.3% versus placebo 2/11, 18.2%; relative risk 4.58, 95% CI 1.29-16.33; Fisher's exact test P = 0.001) and not evident at later timepoints. Quantitative analysis showed a significant decrease of intestinal ESBL-EC/KP burden on day 6. Sustained intestinal eradication (day 28 + 42) was not achieved (verum, 38.9% versus placebo, 27.3%; P = 0.299). In the verum group, mcr-1 genes were detected in two faecal samples collected after treatment. Microbiome analysis showed a significant decrease in alpha diversity and a shift in beta diversity. CONCLUSIONS In this prematurely terminated study of a 7 day oral antimicrobial eradication regimen, short-term ESBL-EC/KP suppression was marginal, while an altered intestinal microbiota composition was clearly apparent.
Real-time Optimization in Aerospace Systems

Real-time Optimization in Aerospace Systems Daniel Dueri Chair of the Supervisory Committee: Behçet Açıkmeşe William E. Boening Department Aeronautics & Aeronautics Algorithm design for autonomous vehicles has been attracting immense research interest, and with the proliferation of self-driving cars, autonomous drone delivery systems, and the increasing availability of commercial off–the–shelf UAVs, interest will only continue growing. The goal of this dissertation is to leverage recent advances in optimal control theory and optimization to provide methods that aid in the design and safe operation of autonomous vehicles (i.e., operating vehicles without violating mission constraints or hardware limits). To this end, we leverage convex optimization and a recent result from optimal control theory called lossless convexification, whereby problems with non-convex control constraints are cast into equivalent convex ones. Convex optimization is then applied to all stages of a mission: from top level vehicle design, to high-level autonomy onboard the vehicle, to trajectory planning, and finally down to allocating desired controls to individual actuators. This dissertation first presents an architecture for generating customized C solvers that were designed specifically for use onboard systems with limited computational resources. Solver customization exploits knowledge of the problem structure to generate solvers that are 2-3 orders of magnitude more efficient than generic solvers. One such customized solver was flight tested onboard Masten’s Xombie rocket during the summers of 2012 and 2013. For mission planning and high-level autonomy, this document develops a convex optimization based method for approximating constrained, finite-time-horizon reachable and controllable sets with inner and outer bounding polytopes. These sets can be used to quickly understand the impact of different design parameters during the design process, or to determine the feasibility of goal states once in flight. Then, the document extends the theory of lossless convexification to cover maximal divert trajectories with simultaneously active thrust pointing and velocity constraints, and develops a method for computing locally optimal trajectories that avoid obstacles. Finally, for a momentum control system, this document presents a convex optimization based real-time control allocation algorithm to optimally utilize multiple actuators without violating their physical constraints.
Influence of Chronic Obstructive Pulmonary Disease and Moderate-To-Severe Sleep Apnoea in Overnight Cardiac Autonomic Modulation: Time, Frequency and Non-Linear Analyses

Chronic obstructive pulmonary disease (COPD) is one of the most prevalent lung diseases worldwide. COPD patients show major dysfunction in cardiac autonomic modulation due to sustained hypoxaemia, which has been significantly related to higher risk of cardiovascular disease. Obstructive sleep apnoea syndrome (OSAS) is a frequent comorbidity in COPD patients. It has been found that patients suffering from both COPD and OSAS simultaneously, the so-called overlap syndrome, have notably higher morbidity and mortality. Heart rate variability (HRV) has demonstrated to be useful to assess changes in autonomic functioning in different clinical conditions. However, there is still little scientific evidence on the magnitude of changes in cardiovascular dynamics elicited by the combined effect of both respiratory diseases, particularly during sleep, when apnoeic events occur. In this regard, we hypothesised that a non-linear analysis is able to provide further insight into long-term dynamics of overnight cardiovascular modulation. Accordingly, this study is aimed at assessing the usefulness of sample entropy (SampEn) to distinguish changes in overnight pulse rate variability (PRV) recordings among three patient groups while sleeping: COPD, moderate-to-severe OSAS, and overlap syndrome. In order to achieve this goal, a population composed of 297 patients were studied: 22 with COPD alone, 213 showing moderate-to-severe OSAS, and 62 with COPD and moderate-to-severe OSAS simultaneously (COPD+OSAS). Cardiovascular dynamics were analysed using pulse rate (PR) recordings from unattended pulse oximetry carried out at patients’ home. Conventional time- and frequency- domain analyses were performed to characterise sympathetic and parasympathetic activation of the nervous system, while SampEn was applied to quantify long-term changes in irregularity. Our analyses revealed that overnight PRV recordings from COPD+OSAS patients were significantly more irregular (higher SampEn) than those from patients with COPD alone (0.267 [0.210–0.407] vs. 0.212 [0.151–0.267]; p < 0.05) due to recurrent apnoeic events during the night. Similarly, COPD + OSAS patients also showed significantly higher irregularity in PRV during the night than subjects with OSAS alone (0.267 [0.210–0.407] vs. 0.241 [0.189–0.325]; p = 0.05), which suggests that the cumulative effect of both diseases increases disorganization of pulse rate while sleeping. On the other hand, no statistical significant differences were found between COPD and COPD + OSAS patients when traditional frequency bands (LF and HF) were analysed. We conclude that SampEn is able to properly quantify changes in overnight cardiovascular dynamics of patients with overlap syndrome, which could be useful to assess cardiovascular impairment in COPD patients due to the presence of concomitant OSAS.
Dictionary learning with log-regularizer for sparse representation

We propose a fast and efficient algorithm for learning overcomplete dictionary for sparse representation of signals using the nonconvex log-regularizer for sparsity. The special importance of log-regularizer has been recognized in recent studies on sparse modeling. The log-regularizer, however, leads to a nonconvex and nonsmooth optimization problem that is difficult to solve efficiently. In this paper, We propose a method based on a decomposition scheme and alternating optimization that can turn the whole problem into a set of subminimizations of univariate functions, each of which is dependent on only one dictionary atom or the coefficient vector. Although the subproblem with respects to the coefficient vector is still nonsmooth and nonconvex, remarkably, it becomes much simpler and it has a closed-form solution by introducing a novel technique that is log-thresholding operator. The main advantages of the proposed algorithm is that, as suggested by our analysis and simulation study, it is more efficient than state-of-the-art algorithms with different sparsity constraints.
A Template for Miniature Legged Robots in Quasi-Static Motion

We introduce a low-dimensional kinematic abstraction—i.e., template—for miniature legged robots that can be used for quasi-static motion planning in the horizontal plane. The template comprises a rigid torso and four rigid legs which engage in an alternating tetrapod gait. As the gait is executed, the torso and the legs form two switching four-bar linkages, parameterized by the leg touchdown and liftoff angles, as well as the leg angular velocity. The template captures on average the experimentally observed behavior of an eight-legged miniature robot crawling at low speeds in a quasi-static fashion.
Part 6 : Advanced Cardiovascular Life Support Section 7 : Algorithm Approach to ACLS 7 C : A Guide to the International ACLS Algorithms

The ILCOR algorithm presents the actions to take and decisions to face for all people who appear to be in cardiac arrest±unconscious, unresponsive, without signs of life. The victim is not breathing normally, and no rescuer can feel a carotid pulse within 10 to 15 seconds. Since 1992 the resuscitation community has examined and recon®rmed the wisdom of most recommendations formulated by international groups through the 1990s. Sophisticated clinical trials provided high-level evidence on which to base several new drugs and interventions. Finally, we have learned that we should continue to place a strong emphasis after 2000 on building a base of critically appraised, international scienti®c evidence. Evidence-based review opened many eyes; only a small proportion of resuscitation care rests on a base of solid evidence. Note: The numbers below, such as `1 (Fig. 1),' match numbers in the algorithms.
Revealed Preference, Rational Inattention, and Costly Information Acquisition

We develop a revealed preference test for optimal acquisition of costly information. The test encompasses models of rational inattention, sequential signal processing, and search. We provide limits on the extent to which attention costs can be recovered from choice data. We experimentally elicit state dependent stochastic choice data of the form the tests require. In simple cases, tests confirm that subjects adjust their attention in response to incentives as the theory dictates.
A biologically inspired assurance definition and specification in heterogeneous autonomous decentralized systems

In near future, billions of computers and intelligent sensors will be connected through networks, each computer/application have its own autonomy, heterogeneity, and always in changing environments. We call these systems as heterogeneous autonomous decentralized systems (HADS). Assurance is a hot research topic in HADS. In this paper the conventional viewpoint towards assurance and the biological viewpoint for assurance are reviewed. Based on the biologically inspired matters, we view the assurance problem of HADS from system perspective, data perspective, communication perspective, and application perspective. An assurance definition in HADS is defined and its technical vision is figured out. It will help researchers for their research on assurance in HADS.
Reflections of L1 reading comprehension skills in university academic grades for an undergraduate translation programme

ABSTRACT Concerns about poor L1 reading skills in undergraduate students have been expressed in several contexts. These skills form a basis for building robust L2 reading comprehension skills, vital for translators. This study, which is part of a larger organization-based action research study to improve L1 reading levels, aimed to explore how L1 reading comprehension skills were reflected and predicted the overall academic performance of students on a South American undergraduate translator training programme using regression modelling. Seventy-nine students from second, third and fourth year of the programme were recruited for this study. They were asked to take a standardized Spanish reading comprehension test measuring word-level comprehension, sentence-level comprehension and text-level comprehension. Also, participants’ final grades for all completed courses were obtained, as well as students’ scores in a pre-entry English test providing a baseline level L2 knowledge prior to being formally trained on English. The results showed that students’ overall grades were predicted by and correlated with lower order sentence-level reading skills, rather than higher-order text-level skills, which was found to be of some concern inasmuch as the translation process demands reading skills that go well beyond the sentence boundary. Given the impact that evaluation can have on student learning, and that the connection between reading comprehension and academic results on translation programs does not appear to have been considered in the literature previously, the study may highlight a need for other institutions wishing to improve L1 reading skills to similarly examine their summative evaluation practices.
Bone marrow-derived stromal cells home to and remain in the infarcted rat heart but fail to improve function: an in vivo cine-MRI study

Basic and clinical studies have shown that bone marrow cell therapy can improve cardiac function following infarction. In experimental animals, reported stem cell-mediated changes range from no measurable improvement to the complete restoration of function. In the clinic, however, the average improvement in left ventricular ejection fraction is around 2% to 3%. A possible explanation for the discrepancy between basic and clinical results is that few basic studies have used the magnetic resonance (MR) imaging (MRI) methods that were used in clinical trials for measuring cardiac function. Consequently, we employed cine-MR to determine the effect of bone marrow stromal cells (BMSCs) on cardiac function in rats. Cultured rat BMSCs were characterized using flow cytometry and labeled with iron oxide particles and a fluorescent marker to allow in vivo cell tracking and ex vivo cell identification, respectively. Neither label affected in vitro cell proliferation or differentiation. Rat hearts were infarcted, and BMSCs or control media were injected into the infarct periphery (n = 34) or infused systemically (n = 30). MRI was used to measure cardiac morphology and function and to determine cell distribution for 10 wk after infarction and cell therapy. In vivo MRI, histology, and cell reisolation confirmed successful BMSC delivery and retention within the myocardium throughout the experiment. However, no significant improvement in any measure of cardiac function was observed at any time. We conclude that cultured BMSCs are not the optimal cell population to treat the infarcted heart.
Governance and Management of Horizontal Business Networks: An Analysis of Retail Networks in Germany

The paper examines two important elements in the development and effectiveness of horizontal business networks: governance and management. Case studies were conducted in three horizontal retailer networks in Germany with the aim of understanding how these networks are structured and which internal governance mechanisms support their development. Through secondary data and in-depth interviews, the study shows that the retail networks developed and implemented their own governance mechanisms and management structures to retain and attract a large number of members, facilitate strategic decision making and increase their effectiveness. The results highlight that governance structures are transitional and adapted according to specific contingencies. In the cases studied, the growth and effectiveness of the business networks have demanded changes in the governance structure, with greater autonomy for professional network managers. Although the retail network keeps its cooperative character, there is a trade-off, in which member-firms agree to delegate greater decision making power to managers in exchange for greater network efficiency and competitiveness.
Speaker segmentation using the MAP-adapted Bayesian information criterion

The Bayesian information criterion (BIC) is a model selection criterion that has previously been applied to speaker segmentation of broadcast news by several researchers. The BIC approach treats speaker segmentation as a model selection problem. As the BIC requires the estimation of the sample covariance matrix, its performance tends to deteriorate as the speaker-turn duration decreases. It is well known that the BIC does not perform well on short segments, making the BIC inappropriate for conversational speech. In this paper, we estimate the hyperparameters of a prior distribution from a disjoint set of speakers and use the prior information to adapt the maximum a-posteriori distribution of the BIC. We show that this results in improved performance for a conversational telephone-speech corpus.
Efficient retrieval of deformable shape classes using local self-similarities

We present an efficient object retrieval system based on the identification of abstract deformable ‘shape’ classes using the self-similarity descriptor of Shechtman and Irani [13]. Given a user-specified query object, we retrieve other images which share a common ‘shape’ even if their appearance differs greatly in terms of colour, texture, edges and other common photometric properties. In order to use the self-similarity descriptor for efficient retrieval we make three contributions: (i) we sparsify the descriptor points by locating discriminative regions within each image, thus reducing the computational expense of shape matching; (ii) we extend [13] to enable matching despite changes in scale; and (iii) we show that vector quantizing the descriptor does not inhibit performance, thus providing the basis of a large-scale shape-based retrieval system using a bag-of-visual-words approach. Performance is demonstrated on the challenging ETHZ deformable shape dataset and a full episode from the television series Lost, and is shown to be superior to appearancebased approaches for matching non-rigid shape classes.
PGR-Net:A Parallel Network Based on Group and Regression for Age Estimation

Age is an important biometric feature of human face. Estimating the specific age of facial images is challenging, because of face aging’s highly nonlinearity and randomness. Commonly age predictors are based on classification or regression method, which may be affected greatly by the category number or data distribution of the labelled samples. In this paper, we design a parallel deep neural network, called PGR-Net. It is a unified learning model which combines the merits of traditional classification methods and regression methods. The model consists of a classification network and several age regressors. The classification network is designed to divide facial images into several age groups, and a regressor is trained for each group separately. We train the classification network and the re-gressors in parallel, and perform age estimation with the regressor of the group predicted by the classification network. Experiments show that the proposed approach is fairly competitive compared with the state-of-the-art methods on two public datasets.
DELPHI style extraction and validation of compact model for a multichip module package

DELPHI style compact model generation for single chip packages is an electronics industry standard proposed by the JEDEC council. Such compact network models are boundary condition independent and ensure that junction temperatures are predicted within 10% [7] compared to the predicted detailed package temperatures. These models replace detailed modeling of packages in system level CFD simulations. With the recent trend of packing more and more functionality onto a single package, multi-chip modules (MCM) kind of packages are becoming more prevalent. MCM packages have more than one functional block (chip) and the DELPHI methodology is no longer applicable directly to MCM packages. In this paper, an extended method has been proposed to extract DELPHI style network models for a multi-chip module packages. ANSYS Icepak is used to model and validate the new method by comparing its temperature predictions with a detailed package. The proposed method uses a combination of the JEDEC proposed method and a linear superposition technique to predict junction temperatures of MCM packages. Linear superposition method takes in to account the interdependency of chips with each other, whereas the DELPHI method is based on a boundary condition-independent technique. Also, an additional study is also carried out to understand the effect of proximity of chips and its impact on the comparisons with the detailed CFD model.