Miracle-dz/UniFAR-FTUs huggingface dataset:
Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia.

Executive Summary Introduction Methodology Used to Prepare the Guideline Epidemiology Incidence Etiology Major Epidemiologic Points Pathogenesis Major Points for Pathogenesis Modifiable Risk Factors Intubation and Mechanical Ventilation Aspiration, Body Position, and Enteral Feeding Modulation of Colonization: Oral Antiseptics and Antibiotics Stress Bleeding Prophylaxis, Transfusion, and Glucose Control Major Points and Recommendations for Modifiable Risk Factors Diagnostic Testing Major Points and Recommendations for Diagnosis Diagnostic Strategies and Approaches Clinical Strategy Bacteriologic Strategy Recommended Diagnostic Strategy Major Points and Recommendations for Comparing Diagnostic Strategies Antibiotic Treatment of Hospital-acquired Pneumonia General Approach Initial Empiric Antibiotic Therapy Appropriate Antibiotic Selection and Adequate Dosing Local Instillation and Aerosolized Antibiotics Combination versus Monotherapy Duration of Therapy Major Points and Recommendations for Optimal Antibiotic Therapy Specific Antibiotic Regimens Antibiotic Heterogeneity and Antibiotic Cycling Response to Therapy Modification of Empiric Antibiotic Regimens Defining the Normal Pattern of Resolution Reasons for Deterioration or Nonresolution Evaluation of the Nonresponding Patient Major Points and Recommendations for Assessing Response to Therapy Suggested Performance Indicators
Refugee pathways out of homelessness in urban Alberta, Canada: implications for social justice-oriented counselling

Abstract Although refugees flee their homelands in search of a better life, they often face continued displacement and homelessness after arrival in their host countries. This constructivist grounded theory study investigated pathways out of homelessness through interviews with a mixed sample of 19 adult refugees from Afghanistan, Congo, Ethiopia, Iraq, Pakistan, Rwanda, Somalia, Sudan and Syria who had experienced short or long-term homelessness after their arrival in Canada and who were subsequently adequately settled for at least 6 months. Data analysis yielded a theoretical framework consisting of four interrelated pathways for exiting the cycle of homelessness: (a) drawing on religiosity to replace the lack of one’s own physical dwelling with a virtual spiritual shelter, promoting resilience in dealing with housing obstacles; (b) creative problem-solving to move up the income ladder to make housing affordable; (c) crying out for help and stumbling on a housing advocate; and (d) engaging in self-advocacy. Social justice-oriented counselling with refugees can facilitate satisfaction of their basic needs after migration in order to realize their fundamental human right to access safe shelter.
The development of the adaptive traffic signal control system

Agents refer to self-contained and identifiable computer programs that can migrate along the network and can act on behalf of the user or other agents. Agents often work on heterogeneous network and operating system environment. Therefore, an integrated logical process to access physical structure via agent application is become more and more urgent. The adaptive urban traffic signal control (TSC) system has become a development trend of intelligent transportation system (ITS). In this paper, we proposed a tracking and persistent agent-based mobility management system in case of adaptive urban traffic signal control (TSC) system. We investigated the vision based surveillance and to keep sight of the unpredictable and hardly measurable disturbances may perturb the traffic flow. We integrated and performed the vision based methodologies that include the object segmentation, classify and tracking methodologies to know well the real time measurements in urban road. According to the real time traffic measurement, we derived agent communication and the adaptive traffic signal control strategy to adapt the traffic signal time. By comparing the experimental result obtained by traditional traffic signal control system which improves the traffic queuing situation, we confirmed the efficiency of our vision based adaptive TSC approach.
The VLA Low-Frequency Sky Survey

The VLA Low-frequency Sky Survey (VLSS) has imaged 95% of the 3π sr of sky north of δ = -30° at a frequency of 74 MHz (4 m wavelength). The resolution is 80″ (FWHM) throughout, and the typical rms noise level is ⟨σ⟩ ≈ 0.1 Jy beam-1. The typical point-source detection limit is 0.7 Jy beam-1, and so far nearly 70,000 sources have been cataloged. This survey used the 74 MHz system added to the VLA in 1998. It required new imaging algorithms to remove the large ionospheric distortions at this very low frequency throughout the entire ∼11.9° field of view. This paper describes the observation and data reduction methods used for the VLSS and presents the survey images and source catalog. All of the calibrated images and the source catalog are available from the VLSS Web site for use by the astronomical community.
A Highly Integrated 60-GHz 6-Channel Transceiver Chip in 0.35 &#181;m SiGe Technology for Smart Sensing and Short-Range Communications

This work presents a highly integrated 57-64 GHz 4-channel receiver (Rx) 2-channel transmitter (Tx) chip targeting short range sensing and large bandwidth communications. The chip features a wide tuning range integrated VCO with a measured phase noise lower than 80 dBc/Hz at 100 kHz offset. Each of the differential Tx channels shows a measured output power of 2-5dBm over the complete frequency range. In addition one Tx channel features a modulator that can be digitally programmed to operate in either radar or communication mode. Each of the receiver channels has a measured conversion gain (CG) of 19 dB, a single-sideband noise figure (NFssb) of less than 10 dB and an input referred 1-dB compression point (P-1dB) of less than 10 dBm. With all channels turned on the chip consumes a current of 300mA from a 3.3V supply.
Neuronal and Molecular Adaptations of GABA Neurons in the Ventral Tegmental Area to Chronic Alcohol

NEURONAL AND MOLECULAR ADAPTATIONS OF GABA NEURONS IN THE VENTRAL TEGMENTAL AREA TO CHRONIC ALCOHOL Kimberly Hales Department of Physiology and Developmental Biology Master of Neuroscience The purpose of this thesis project was to examine the effects of chronic alcohol on the excitability and molecular adaptation of GABA neurons of the ventral tegmental area (VTA). GABA neurons are of interest with regards to ethanol intoxication, reinforcement, and dependence due to their widespread distribution and connectivity to mesocorticolimbic dopamine (DA) neurons implicated in alcohol reward and addiction. Since we have previously shown adaptation of VTA GABA neuron firing rate to chronic ethanol (Gallegos, Criado et al. 1999) and suppression of gap-junction (GJ) mediated coupling between these neurons by acute ethanol (Stobbs, Ohran et al. 2004), we wanted to further characterize the effects of chronic ethanol on VTA GABA neuron excitability, electrical coupling and molecular adaptation. In particular, we analyzed the GJ mediated coupling and protein regulation of VTA GABA neurons following a three week period of continuous ethanol exposure via liquid diet. Although some animals showed tolerance,
The Practice of Agent-Based Model Visualization

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.
Adaptive hybrid precoding and combining in MmWave multiuser MIMO systems based on compressed covariance estimation

In this paper we propose an adaptive multi user (MU) single-cell hybrid precoding strategy that iteratively designs the precoders/combiners exploiting the reciprocity of time division duplex (TDD) millimeter wave systems. The minimum mean square error (MMSE) criterion is considered to design the combiners, which relies on second order statistics of the channel. The covariance of the received signal at the antenna array is estimated online from compressed measurements, leveraging the sparse nature of mmWave channels. The proposed method avoids the explicit estimation of the channel matrix associated to each user, reducing the training overhead, and achieving sum spectral efficiencies comparable to the ones obtained with block diagonalization.
A Distributed Target Tracking Algorithm Based on Particle Filter ⋆

A distributed target tracking algorithm based on particle filter is presented to improve the tracking accuracy. By integrating the maximum likelihood estimation algorithm into particle filter model, an optimum weight selection algorithm can be used to reduce overall energy consumption of some sample calculations activities in wireless sensor network. Evaluation results prove that the improved solution can effectively increase the tracking accuracy while overcoming the degradation.
Perceptions of Self-Efficacy among STEM Students with Disabilities.

Numerous studies examine the relationship between self-efficacy and positive outcomes for postsecondary students. Collectively they echo that self-efficacy is an essential component to positive outcomes. Relatively few studies focused on students with disabilities majoring in STEM fields. Twenty postsecondary students with disabilities participated in focus groups organized around Bandura’s key factors leading to self-efficacy: mastery experiences, vicarious experiences, social persuasion, and physiological reaction. By pairing participant-response devices, commonly known as “clickers,” with traditional qualitative methods, students provided their individual perspectives as well as reacted to collective responses. Several cross-cutting themes emerged from the study. Instructors set the tone for learning and consequently highly influence confidence, motivation, anxiety and stress, and ultimately success. Applied learning is important, especially in team settings. A student’s sense of self influences his or her perceptions of self-efficacy. The results offer insight into designing support services and measuring self-efficacy with this population.
Automated design of application specific superscalar processors: an analytical approach

Analytical modeling is applied to the automated design of application-specific superscalar processors. Using an analytical method bridges the gap between the size of the design space and the time required for detailed cycle-accurate simulations. The proposed design framework takes as inputs the design targets (upper bounds on execution time, area, and energy), design alternatives, and one or more application programs. The output is the set of out-of-order superscalar processors that are Pareto-optimal with respect to performance-energy-area. The core of the new design framework is made up of analytical performance and energy activity models, and an analytical model-based design optimization process. For a set of benchmark programs and a design space of 2000 designs, the design framework arrives at all performance-energy-area Pareto-optimal design points within 16 minutes on a 2 GHz Pentium-4. In contrast, it is estimated that a naíve cycle-accurate simulation-based exhaustive search would require at least two months to arrive at the Pareto-optimal design points for the same design space.
ULTRASTRUCTURE OF THE PELLICULAR COMPLEX OF PLASMODIUM FALLAX

The exoerythrocytic merozoites of Plasmodium fallax grown in a tissue-culture system have been investigated by negative staining and thin-sectioning techniques, and the respective results have been compared. Negative staining provided additional information, corroborated findings obtained with thin sectioning, and contributed particularly to the study of the pellicular complex of the merozoites which has been demonstrated as being composed of three layers: a thin outer membrane, a thick interrupted inner membrane, and a partial layer of microtubules. Observations made of negatively stained parasites revealed that the thick, interrupted inner membrane in thin sections is actually a labyrinthine structure and covers the entire surface of the merozoite, except at the regions of the conoid and the cytostome. The microtubules which radiate from the conoid to the posterior end demonstrated a transverse periodicity and filamental subunits parallel to the axis of the microtubule. The detailed structure of the conoid and the cytostome is also described.
Automatic generation of instruction sequences targeting hard-to-detect structural faults in a processor

Testing a processor in native mode by executing instructions from cache has been shown to be very effective in discovering defective chips. In previous work, we showed an efficient technique for generating instruction sequences targeting specific faults. We generated tests using traditional techniques at the module level and then mapped them to instruction sequences using novel methods. However, in that technique, the propagation of module test responses to primary outputs was not automated. In this paper, we present the algorithm and experimental results for a technique which automates the functional propagation of module level test responses. This technique models the propagation requirement as a Boolean difference problem and uses a bounded model checking engine to perform the instruction mapping. We use a register transfer level (RT-Level) abstraction which makes it possible to express Boolean difference as a succinct linear time logic (LTL) formula that can be passed to a bounded model checking engine. This technique fully automates the process of mapping module level test sequences to instruction sequences
Wireless Network Measurement: VoIP and 802.11e

802.11 wireless networks are a convenient way to provide ‘last-hop’ network connections in many environments. However the distributed nature of their operation poses problems in providing quality of service guarantees, which are vital for providing interactive services such as Voice over IP. In this thesis we will review the operation of 802.11 and it’s extended MAC layer, 802.11e. We will then review some analytical models used to explore the behaviour of the 802.11 MAC and test some of the assumptions underlying these models. We confirm that our testbed operates according to the standards before using it to explore the behaviour of VoIP traffic, using it as a test case to examine the provision of quality of service guarantees via the extended 802.11e MAC. This work is based on several papers [9] [19] [10].
Analyzing Factors Affecting U.S. Food Price Inflation

"Since the summer of 2007, U.S. food price inflation has increased dramatically. Given public anxiety over fast-rising food prices, this study attempts to analyze the effects of market factors-prices of energy and agricultural commodities and exchange rate-on U.S. food prices using a cointegration analysis. Results show that the agricultural commodity price and exchange rate play the key roles in determining the short- and long-run movement of U.S. food prices. It is also found that in recent years, energy price has been a significant factor affecting U.S. food prices in the long run, but has little effect in the short run. This implies the strong linkage between energy and agricultural markets in the long run over the recent years. " Copyright (c) 2010 Canadian Agricultural Economics Society.
Anatomical Entity Recognition with a Hierarchical Framework Augmented by External Resources

References to anatomical entities in medical records consist not only of explicit references to anatomical locations, but also other diverse types of expressions, such as specific diseases, clinical tests, clinical treatments, which constitute implicit references to anatomical entities. In order to identify these implicit anatomical entities, we propose a hierarchical framework, in which two layers of named entity recognizers (NERs) work in a cooperative manner. Each of the NERs is implemented using the Conditional Random Fields (CRF) model, which use a range of external resources to generate features. We constructed a dictionary of anatomical entity expressions by exploiting four existing resources, i.e., UMLS, MeSH, RadLex and BodyPart3D, and supplemented information from two external knowledge bases, i.e., Wikipedia and WordNet, to improve inference of anatomical entities from implicit expressions. Experiments conducted on 300 discharge summaries showed a micro-averaged performance of 0.8509 Precision, 0.7796 Recall and 0.8137 F1 for explicit anatomical entity recognition, and 0.8695 Precision, 0.6893 Recall and 0.7690 F1 for implicit anatomical entity recognition. The use of the hierarchical framework, which combines the recognition of named entities of various types (diseases, clinical tests, treatments) with information embedded in external knowledge bases, resulted in a 5.08% increment in F1. The resources constructed for this research will be made publicly available.
First results in detecting and avoiding frontal obstacles from a monocular camera for micro unmanned aerial vehicles

Obstacle avoidance is desirable for lightweight micro aerial vehicles and is a challenging problem since the payload constraints only permit monocular cameras and obstacles cannot be directly observed. Depth can however be inferred based on various cues in the image. Prior work has examined optical flow, and perspective cues, however these methods cannot handle frontal obstacles well. In this paper we examine the problem of detecting obstacles right in front of the vehicle. We developed a method to detect relative size changes of image patches that is able to detect size changes in the absence of optical flow. The method uses SURF feature matches in combination with template matching to compare relative obstacle sizes with different image spacing. We present results from our algorithm in autonomous flight tests on a small quadrotor. We are able to detect obstacles with a frame-to-frame enlargement of 120% with a high confidence and confirmed our algorithm in 20 successful flight experiments. In future work, we will improve the control algorithms to avoid more complicated obstacle configurations.
IBM Memory Expansion Technology (MXT)

Several technologies are leveraged to establish an architecture for a low-cost, high-performance memory controller and memory system that more than double the effective size of the installed main memory without significant added cost. This architecture is the first of its kind to employ real-time main-memory content compression at a performance competitive with the best the market has to offer. A large low-latency shared cache exists between the processor bus and a content-compressed main memory. Highspeed, low-latency hardware performs realtime compression and decompression of data traffic between the shared cache and the main memory. Sophisticated memory management hardware dynamically allocates main-memory storage in small sectors to accommodate storing the variable-sized compressed data without the need for "garbage" collection or significant wasted space due to fragmentation. Though the main-memory compression ratio is limited to the range 1:1-64:1, typical ratios range between 2:1 and 6:1, as measured in "real-world" system applications.
An Adaptive Algorithm for ModifyingHyperellipsoidal Decision

The LVQ algorithm is a common method which allows a set of reference vectors for a distance classiier to adapt to a given training set. We have developed a similar learning algorithm, LVQ-MM, which manipulates hyperellipsoidal cluster boundaries as opposed to reference vectors. Regions of the input feature space are rst enclosed by ellipsoidal decision boundaries, and then these boundaries are iteratively modiied to reduce classiication error. Results obtained by classifying the Iris data set are provided.
Investigation of domain switching of PZT and KNN - based ceramics

As known, ferroelectric ceramics generate strain and stress against an external clamping at high electric fields, which is used in actuator applications. To understand this response quantitatively bulk samples of commercial PZT and in-house produced KNN ceramics were investigated in model experiments. On bulk samples, the typical non-linear polarization hysteresis is found in a wide temperature range TN…TC. Below the characteristic temperature TN polarization reversal is suppressed, which is explained by domain wall pinning. The applied energy by the external electric field is too low to overcome the critical pinning energy barrier U/kT. Experimental results of measured threshold electric field and energy for domain switching are given for Sonox P 53 and KNN based ceramics.
Abstract Generation Based on Rhetorical Structure Extraction

We have developed an automatic abstract generation system for Japanese expository writings based on rhetorical structure extraction. The system first extracts the rhetorical structure, the compound of the rhetorical relations between sentences, and then cuts out less important parts in the extracted structure to generate an abstract of the desired length.Evaluation of the generated abstract showed that it contains at maximum 74% of the most important sentences of the original text. The system is now utilized as a text browser for a prototypical interactive document retrieval system.
Using neural networks with automatic relevance determination to identify regions of the thalamus implicated in schizophrenia

Abnormalities of the thalamus may contribute to the pathophysiology of schizophrenia. Several studies have found the thalamus to be altered in schizophrenia, and the thalamus has connections with other brain structures implicated in the disorder. This work examined thalamic levels of the metabolite N-acetylaspartate (NAA), taken from schizophrenics and controls using in-vivo proton magnetic resonance spectroscopic imaging. Neural networks were trained on this data, and automatic relevance determination (ARD) identified NAA group differences in the pulvinar and mediodorsal nucleus, underscoring the importance of examining thalamic subregions in schizophrenia.
On the well posedness of singularly perturbed fault detection filters

In this paper, we study the well posedness of observer-based fault detection filters using the theory of singular perturbation. By proper scaling of the fault maps, it is shown that the ill-conditioning of the residual fault projector can be alleviated. This allows the construction of an approximate projector in terms of the projectors for the slow and fast subsystems.
Top Quark Seesaw Theory of Electroweak Symmetry Breaking

We study electroweak symmetry breaking involving the seesaw mechanism of quark condensation. These models produce a composite Higgs boson involving the left-handed top quark, yet the top mass arises naturally at the observed scale. We describe a schematic model which illustrates the general dynamical ideas. We also consider a generic low-energy effective theory which includes several composite scalars, and we use the effective potential formalism to compute their spectrum. We develop a more detailed model in which certain features of the schematic model are replaced by additional dynamics.