Miracle-dz/UniFAR-FTUs huggingface dataset:
Azimuth and elevation angle estimation without any eigen decomposition

Recently, Wu et al. proposed a scheme for twodimensional (2-D) direction of arrival angle estimation (DOA) for azimuth and elevation angles, using the propagator method (PM). An advantage of this method over the classical subspace based algorithms, such as ESPRIT and MUSIC, is that it does not apply any eigenvalue decomposition (EVD) to the cross spectral matrix or singular value decomposition (SVD) to the received data. This significantly reduces the computational complexity, compared to the EVD and SVD. However, Wu’s method has some drawbacks such as pair matching between the azimuth and elevation angle estimations for multiple different sources. And furthermore, Wu’s method has an estimation failure problem in the range of practical mobile elevation angles. The objective of this paper is to overcome these two problems with less arithmetic operation counts than Wu used, and to improve the performance significantly. To achieve these objectives, we propose an antenna array configuration which avoids these problems. Simulation results verify that the proposed scheme can remove these problems and give much better performance.
The Treatment of Melioidosis

Melioidosis is a complex bacterial infection, treatment of which combines the urgency of treating rapidly fatal Gram negative septicaemia with the need for eradication of long-term persistent disease in pulmonary, soft tissue, skeletal and other organ systems. Incremental improvements in treatment have been made as a result of multicentre collaboration across the main endemic region of Southeast Asia and northern Australia. There is an emerging consensus on the three main patterns of antimicrobial chemotherapy; initial (Phase 1) treatment, subsequent eradication (Phase 2) therapy and most recently post-exposure (Phase 0) prophylaxis. The combination of agents used, duration of therapy and need for adjunct modalities depends on the type, severity and antimicrobial susceptibility of infection. New antibiotic and adjunct therapies are at an investigational stage but on currently available data are unlikely to make a significant impact on this potentially fatal infection.
A framework for hybrid control design

This paper presents a hybrid system framework which considers simultaneously the control and decision-making issues. This reconfigurable framework can accommodate a wide range of situations, from aircraft control systems to mobile manipulators. A continuous-state plant is supervised by a discrete-event system which is based on a theory of linked finite state machines. The composite system is viewed as an iterative process where a task is carried out by changing the structure of the continuous-state plant. An algorithm for a hybrid control design is provided and illustrated through a mobile manipulator example.
An activity-based costing approach for detecting inefficiencies of healthcare processes

Purpose – The purpose of this paper is to set out a methodological framework to investigate how the integration of an activity-based costing (ABC) logic into the pre-existent accounting system supports healthcare organizations in identifying the inefficiencies related to their diagnostic therapeutic pathways (DTP) and related reengineering interventions. Design/methodology/approach – The BPM-ABC methodological framework has been applied to the case of a specific surgery pathway, at the Orthopaedic Division of a University Hospital in Italy. Findings – The case-study described in the paper points out: first, how the Business Process Management (BPM)-ABC methodology is able to produce significant information about consumed resources and the costs of the activities, useful to highlight opportunities for DTPs improvement; second, the barriers related to a pre-existing accounting system based on cost centres that can hinder the implementation of the BPM-ABC model. Practical implications – The case study points.
Can We Trust Our Results? A Mapping Study on Data Quality

Background: The quality of data sets used in software engineering research is of the utmost importance. To ensure credibility of results obtained from use of data sets, the quality of the data must be examined. Objective: This study provides an overview of recent research(2008-2012) involving data quality in software engineering datasets, with the goal of generally understanding what research there is that addresses data quality, and in particular to determine to what degree researchers have addressed any data quality issues in order to evaluate the trustworthiness of their results. Method: We performed a systematic mapping study to investigate treatment of data quality issues in software engineering research. A total of 64 papers published from 2008 to 2012explicitly address issues with the quality of data and use software engineering data sets. These studies were classified according to the data quality topic, data set and data quality problem. Results: We found only 31 studies gave serious consideration for how the quality of the data affected their results. We observed that there is a lack of clear and consistent terminology regarding data quality, especially with respect to the kinds of quality problems a data set might have. As a first step to address this problem, we propose a model that describes the lifecycle that research data goes through when used in research. Conclusions: The results suggest that researchers should give more attention to the quality of data sets in order to produce trustworthy data for reliable empirical research, and that the research community needs to better understand and communicate issues with data quality.
Harnessing battery recovery effect in wireless sensor networks: Experiments and analysis

Many applications of wireless sensor networks rely on batteries. But most batteries are not simple energy reservoirs, and can exhibit battery recovery effect. That is, the deliverable energy in a battery can be self-replenished, if left idling for sufficient time. As a viable approach for energy optimisation, we made several contributions towards harnessing battery recovery effect in sensor networks. 1) We empirically examine the gain of battery runtime of sensor devices due to battery recovery effect, and affirm its significant benefit in sensor networks. We also observe a saturation threshold, beyond which more idle time will contribute only little to battery recovery. 2) Based on our experiments, we propose a Markov chain model to capture battery recovery considering saturation threshold and random sensing activities, by which we can study the effectiveness of duty cycling and buffering. 3) We devise a simple distributed duty cycle scheme to take advantage of battery recovery using pseudo-random sequences, and analyse its trade-off between the induced latency of data delivery and duty cycle rates.
Lazy Schema: An Optimal Sampling Frequency Assignment for Real-Time Sensor Systems

How to reasonably allocate and schedule resources of wireless sensor system to maximum its potential capability has been an important area for research. In this paper, we focus on the Optimal Sampling Frequency Assignment (OSFA) in a real-time wireless sensor networks (RTWSN). An appropriate OSFA should both guarantee a good quality of real-time service and efficiently utilize the limited network resources as well. We propose a distributed optimization algorithm, called Lazy Schema (LySa), to obtain the optimal sampling rates of source nodes with low cost. The central idea is that redundancy reporting and constant adjust step size result in the excessive communicate overhead in iteration process. LySa adopts self-adaptive reporting rates and dynamically adjusts step size to reduce the traffic cost and accelerate the convergence of optimal solution. We have evaluated LySa together with related mainstream algorithms. The results demonstrate that LySa outperforms current state-of-art approaches in terms of low cost, high efficiency and scalability in RTWSN.
Cellular Pharmacokinetics and Pharmacodynamics of the Glycopeptide Antibiotic Oritavancin (LY333328) in a Model of J774 Mouse Macrophages

ABSTRACT The intracellular pharmacokinetics and pharmacodynamics of oritavancin (LY333328) were studied in cultured cells. Oritavancin was avidly accumulated by J774 and THP-1 macrophages and rat fibroblasts and to a lesser extent by LLC-PK1 and Caco-2 cells. In J774 macrophages, the level of accumulation reached a plateau (at 370-fold the extracellular concentration) within 24 h and was partly defeated by a rise in serum protein levels. Efflux was incomplete (with a plateau at two-thirds of the original level at 6 h). In short-term kinetic studies, oritavancin uptake was linear for up to 4 h (as was the case for horseradish peroxidase and small latex beads, used as markers of the fluid phase and adsorptive endocytosis, respectively), which was in contrast to azithromycin and chloroquine uptake (which accumulate in cells by diffusion and segregation). The rates of clearance of oritavancin and latex beads were comparable (150 and 120 μl × mg of protein−1 × h−1, respectively) and were approximately 200 times higher than that of horseradish peroxidase. Oritavancin accumulation was partially reduced by monensin but was unaffected by acidic pH (these conditions abolished chloroquine accumulation). Cell-associated oritavancin was found in lysosomal fractions after homogenization of J774 macrophages and fractionation by isopycnic centrifugation. Oritavancin was bactericidal against intracellular Staphylococcus aureus (phagolysosomal infection) but was unable to control the intracellular growth of Listeria monocytogenes (cytosolic infection), even though its cellular concentration largely exceeded the MIC (0.02 mg/liter) and minimal bactericidal concentration (2 mg/liter). We conclude that oritavancin enters cells by adsorptive endocytosis (favored by its lipophilic side chain and/or the presence of three protonatable amines), which drives it to lysosomes, where it exerts antibiotic activity.
Bayesian classification and active learning using lp-priors. Application to image segmentation

In this paper we utilize Bayesian modeling and inference to learn a softmax classification model which performs Supervised Classification and Active Learning. For p <; 1, lp-priors are used to impose sparsity on the adaptive parameters. Using variational inference, all model parameters are estimated and the posterior probabilities of the classes given the samples are calculated. A relationship between the prior model used and the independent Gaussian prior model is provided. The posterior probabilities are used to classify new samples and to define two Active Learning methods to improve classifier performance: Minimum Probability and Maximum Entropy. In the experimental section the proposed Bayesian framework is applied to Image Segmentation problems on both synthetic and real datasets, showing higher accuracy than state-of-the-art approaches.
Transformation, Ranking, and Clustering for Face Recognition Algorithm Comparison

The performance of face recognition algorithms is recently of increased interest. Empirical analyses of algorithms have traditionally been limited to rank-based scores such as cumulative match and receiver operating characteristics. This restriction to performance measures based on rank-based statistics arises because it is not possible to directly compare similarities output by algorithms. This paper presents the Phi-PIT transformation that makes it possible to compare such heterogeneous outputs, and allows a large body of classical statistical methods to be used to measure and analyze performance. These statistical techniques inclucde multiple comparison techniques, analysis of variance (ANOVA), and regression techniques. This paper presents ANOVA, graphical ANOVA, and StudentNewman-Keuls clustering analyses of the transformed outputs of fifteen face recognition algorithms.
GEOMETRY AND TOPOLOGY IN CONCURRENT COMPUTING

1. Introduction. This is a short introduction to a geometric model for concurrent computing. Except for Proposition 3.1, there is nothing new here. It is probably well known to most mathematicians, that graph theory is used in computer science to describe for instance the different options for a process (see Figure 1.1). It can enter a loop and stay there for a number of rounds, it can skip the loop, there may be a choice between different branches in the graph, etc. This is a nice model, and it works well when one process is living in a world of its own, meaning that it will not share information or interact in other ways with other processes. When there is more than one process, and these interact, it is not quite clear, which model to use. Some problems, that one has to face are: (1) Not all processes can be allowed access to a shared resource at the same time: • If two people, T 1 and T 2 , are allowed to access a bank account at the same time, and they both want to check if there is any money, then withdraw it and update the status of the account, there is clearly a problem (for the bank at least) if T 1 checks the status, T 2 checks the status, then T 1 withdraws all the money she saw and so does T 2 , before T 1 updates. • If a printer server has access to three printers, only three processes can print at a time. (2) The execution of two (or more) concurrent processes may have different results depending on which process gets the shared resource first, for example, who gets the money from the bank account.
Human Evolution and Osteoporosis-Related Spinal Fractures

The field of evolutionary medicine examines the possibility that some diseases are the result of trade-offs made in human evolution. Spinal fractures are the most common osteoporosis-related fracture in humans, but are not observed in apes, even in cases of severe osteopenia. In humans, the development of osteoporosis is influenced by peak bone mass and strength in early adulthood as well as age-related bone loss. Here, we examine the structural differences in the vertebral bodies (the portion of the vertebra most commonly involved in osteoporosis-related fractures) between humans and apes before age-related bone loss occurs. Vertebrae from young adult humans and chimpanzees, gorillas, orangutans, and gibbons (T8 vertebrae, n = 8–14 per species, male and female, humans: 20–40 years of age) were examined to determine bone strength (using finite element models), bone morphology (external shape), and trabecular microarchitecture (micro-computed tomography). The vertebrae of young adult humans are not as strong as those from apes after accounting for body mass (p<0.01). Human vertebrae are larger in size (volume, cross-sectional area, height) than in apes with a similar body mass. Young adult human vertebrae have significantly lower trabecular bone volume fraction (0.26±0.04 in humans and 0.37±0.07 in apes, mean ± SD, p<0.01) and thinner vertebral shells than apes (after accounting for body mass, p<0.01). Since human vertebrae are more porous and weaker than those in apes in young adulthood (after accounting for bone mass), even modest amounts of age-related bone loss may lead to vertebral fracture in humans, while in apes, larger amounts of bone loss would be required before a vertebral fracture becomes likely. We present arguments that differences in vertebral bone size and shape associated with reduced bone strength in humans is linked to evolutionary adaptations associated with bipedalism.
A critical investigation of the role of teacher research and its relationship to teacher professionalism, knowledge and identity

The thesis examines the related concepts of teacher knowledge, professionalism and identity through the lens of teacher research, and in the context of a teacher-research network. The mechanism for exploration was through teacher voice. As the research unfolded, what was revealed was that accessing teacher voice presented a major obstacle as teachers struggled to articulate their own views on knowledge, professionalism and identity, in part because there seemed to be no language to discuss such concepts. The question of discourse thus became a key theme. The research methods developed to address this issue include a card sort as a way of addressing the teacher silences: this approach revealed that teachers were able to engage with ideas around knowledge, professionalism, identity and research when given a language in this way. However, what emerged was far from a cohesive narrative but rather diverse and at times contradictory accounts of associated teacher beliefs and values. Faced with inconsistency and paradox, a new theoretical lens of post-modernism was used to explore the fragmented and splintered narratives which had emerged, and a different account of knowledge, professionalism, identity and research is offered.
Equations for Drainage Component of the Field Water Balance

Accurate estimates of the drainage component of the field water balance are needed to achieve improved management of drainage in irrigated crop production systems and obtain improved estimates of evapotranspiration (ET) from soil water measurements. Estimating drainage for numerous soil and field conditions necessitates the use of simple, yet accurate, drainage equations containing easily measured parameters. The Wilcox drainage model is a relatively simple mathematical equation with a high degree of accuracy and applicability to field conditions. Our objectives were to develop Wilcox-type drainage rate equations for three coarse-textured soils of the west-central Great Plains and assemble previously determined, but fragmented, Wilcox-type drainage equations and supporting information for three medium-textured soils of the region. Drainage plots for collection of data for development of Wilcox-type drainage equations were established on two coarse-textured soil profiles in 2008 near Garden City, Kansas. Total water content of the soil profiles was measured over time during ~48-day drainage events. Total water was plotted against drainage time on log-log scales, and the linear regression equation relating the two variables was determined. These linear equations of profile water (log10) vs. drainage time (log10) were used to develop Wilcox-type drainage equations in which drainage rate (dW/dT in mm/day) is expressed as a function of soil profile water content (in mm). Drainage rate equations in this article can be used to estimate the drainage component of the field water balance for improved irrigation water management and more accurate estimates of ET from soil water measurements.
Perisynaptic Location of Metabotropic Glutamate Receptors mGluR1 and mGluR5 on Dendrites and Dendritic Spines in the Rat Hippocampus

Ionotropic and metabotropic (mGluR1a) glutamate receptors were reported to be segregated from each other within the postsynaptic membrane at individual synapses. In order to establish whether this pattern of distribution applies to the hippocampal principal cells and to other postsynaptic metabotropic glutamate receptors, the mGluR1a/b/c and mGluR5 subtypes were localized by immunocytochemistry. Principal cells in all hippocampal fields were reactive for mGluR5, the strata oriens and radiatum of the CA1 area being most strongly immunolabelled. Labelling for mGluR1b/c was strongest on some pyramids in the CA3 area, weaker on granule cells and absent on CA1 pyramids. Subpopulations of non‐principal cells showed strong mGluR1 or mGluR5 immunoreactivity. Electron microscopic pre‐embedding immunoperoxidase and both pre‐ and postembedding immunogold methods consistently revealed the extrasynaptic location of both mGluRs in the somatic and dendritic membrane of pyramidal and granule cells. The density of immunolabelling was highest on dendritic spines. At synapses, immunoparticles for both mGluR1 and mGluR5 were found always outside the postsynaptic membrane specializations. Receptors were particularly concentrated in a perisynaptic annulus around type I synaptic junctions, including the invaginations at ‘perforated’synapses. Measurements of immunolabelling on dendritic spines showed decreasing levels of receptor as a function of distance from the edge of the synaptic specialization. We propose that glutamatergic synapses with an irregular edge develop in order to increase the circumference of synaptic junctions leading to an increase in the metabotropic to ionotropic glutamate receptor ratio at glutamate release sites. The perisynaptic position of postsynaptic metabotropic glutamate receptors appears to be a general feature of glutamatergic synaptic organization and may apply to other G‐protein‐coupled receptors.
Leveraging repeated games for solving complex multiagent decision problems

Making good decisions in multiagent environments is a hard problem in the sense that the presence of several decision makers implies conflicts of interests, a lack of coordination, and a multiplicity of possible decisions. If, then, the same decision makers interact continuously through time, they have to decide not only what to do in the present, but also how their present decisions may affect the behavior of the others in the future. Game theory is a mathematical tool that aims to model such interactions as strategic games of multiple players. Therefore, multiagent decision problems are often studied using game theory. In this context, and being restricted to dynamic games, complex multiagent decision problems can be algorithmically approached. The contribution of this thesis is three-fold. First, this thesis contributes an algorithmic framework for distributed planning in non-cooperative dynamic games. The multiplicity of possible plans is a matter of serious complications for any planning approach. We propose a novel approach based on the concept of learning in repeated games. Our approach permits overcoming the aforementioned complications by means of communication between players. We then propose a learning algorithm for repeated game self-play. Our algorithm allows players to converge, in an initially unknown repeated game, to a joint behavior optimal in a certain, well-defined sense, without communication between players. Finally, we propose a family of algorithms for approximately solving dynamic games, and for extracting equilibrium strategy profiles. In this context, we first propose a method to compute a nonempty subset of approximate subgame-perfect equilibria in repeated games. We then demonstrate how to extend this method for approximating all subgame-perfect equilibria in repeated games, and also for solving more complex dynamic games.