Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of PICO as a Knowledge Representation for Clinical Questions

The paradigm of evidence-based medicine (EBM) recommends that physicians formulate clinical questions in terms of the problem/population, intervention, comparison, and outcome. Together, these elements comprise a PICO frame. Although this framework was developed to facilitate the formulation of clinical queries, the ability of PICO structures to represent physicians' information needs has not been empirically investigated. This paper evaluates the adequacy and suitability of PICO frames as a knowledge representation by analyzing 59 real-world primary-care clinical questions. We discovered that only two questions in our corpus contain all four PICO elements, and that 37% of questions contain both intervention and outcome. Our study reveals prevalent structural patterns for the four types of clinical questions: therapy, diagnosis, prognosis, and etiology. We found that the PICO framework is primarily centered on therapy questions, and is less suitable for representing other types of clinical information needs. Challenges in mapping natural language questions into PICO structures are also discussed. Although we point out limitations of the PICO framework, our work as a whole reaffirms its value as a tool to assist physicians practicing EBM.
Qualitative research & evaluation methods

This book explains clearly conceptual issues and themes on qualitative research and evaluaton methods including: qualitative data, triangulated inquiry, qualitative inquiry, constructivism, constructionism, Complexity (chaos) theory, qualitative designs and data collection, fieldwork strategies, interviewing, tape-recording, ethical issues, analysis, interpretation and reporting, observations vs. perceived impacts and utilisation-focused evaluation reporting.
Dynamic formations in real-time strategy games

Current approaches to organising units in strategic video games are typically implemented via static formations. Static formations are not capable of adapting effectively to opponent tactics. In this paper we discuss an approach to organising units by learning the effectiveness of a formation in actual play, and directly applying learned formations according to the classification of the opponent player. This approach to establish so-called dynamic formations, is tested in the ORTS game environment. From our results, we may conclude that the approach to established dynamic formations can be successfully applied in actual video-game environments.
Multi-Hop Synchronization at the Application Layer of Wireless and Satellite Networks

Time synchronization is a key issue in wireless and satellite networks; time-stamping collected data, tasks scheduling or efficient communications are just some applications. From all the existing techniques to achieve synchronization, those that work at the MAC layer and can precisely timestamp sync messages are the most accurate. However, working with standard protocols, usually prevents the user from accessing lower layers and consequently reduces accuracy. Receiver-receiver schema improves time-stamping performance because it eliminates the biggest non-deterministic error at the sender side; the medium access time. Nevertheless, utilization of these methods in multi- hop networks usually requires an extra amount of traffic. In this paper we present a method which allows accurate synchronization of large multi-hop networks such as satellite networks working at the application layer while keeping the message exchange to the minimum. Through an exhaustive experimentation, we show the protocol's performance and analyze the factors that influence synchronization accuracy the most.
BCI competition 2003-data set III: probabilistic modeling of sensorimotor /spl mu/ rhythms for classification of imaginary hand movements

Brain-computer interfaces require effective online processing of electroencephalogram (EEG) measurements, e.g., as a part of feedback systems. We present an algorithm for single-trial online classification of imaginary left and right hand movements, based on time-frequency information derived from filtering EEG wideband raw data with causal Morlet wavelets, which are adapted to individual EEG spectra. Since imaginary hand movements lead to perturbations of the ongoing pericentral /spl mu/ rhythm, we estimate probabilistic models for amplitude modulation in lower (10 Hz) and upper (20 Hz) frequency bands over the sensorimotor hand cortices both contra- and ipsilaterally to the imagined movements (i.e., at EEG channels C3 and C4). We use an integrative approach to accumulate over time evidence for the subject's unknown motor intention. Disclosure of test data labels after the competition showed this approach to succeed with an error rate as low as 10.7%.
Termination of atrial fibrillation by catheter ablation can be successfully predicted from baseline ECG

Several organization indices have been used to predict the outcome of stepwise catheter ablation (step-CA) in long-standing persistent atrial fibrillation (LS-pAF), however with limited success. Our study aims at developing innovative indices from baseline (BL) ECG (i.e before ablation) in order to predict the procedure outcome and the site of AF termination (AF-term) by step-CA. We report an adaptive method for tracking AF-term based on indices characterizing the relationship between harmonic components of atrial activity from the ECG. Our preliminary results suggest that adaptive measures of AF organization computed at BL perform better than classical indices for identifying patients whose AF will terminate during ablation within the left atrium only. These findings are indicative of a higher baseline organization in these patients.
Performance of Dynamic Replication Schemes for an Internet Hosting Service

The paper explores schemes for dynamic replication and migrationof web objects in the context of an Internet hosting service. It describes a replica placement algorithm for deciding the location and number of replicas of an object as well as request distribution schemes for choosing among currently available replicas. We compare two classes of request distribution algorithms – namely feedback and non-feedback based. Further, we compare dynamic replication to a static replication scheme. We have simulated the algorithms using synthetic workloads as well as a real trace from a hosting service. Measurement and analysis show that dynamic replication significantly reduces bandwidth consumption and latency, removes hot spots from the network and smooths out bursts in bandwidth demand while imposing only a low network traffic overhead. For example, on the trace, our algorithm reduces bandwidth consumption by as much as 52%while imposing a traffic overhead of only about 5%. Results of the simulation also demonstrate that at high loads, the ability to predict the effect of a migration or replication is important for any system that takes dynamic replica placement decisions.
From Terms to Concepts: A Revisited Approach to Local Context Analysis

Pseudo-Relevance Feedback (PRF) is a widely used technique which aims to improve the query representation assuming as relevant the top ranked documents. This should results in better performance as, after the expansion and re-weigh of the original query, the resultant vector should contain all those worth features able to express utterly the user’s information need. This paper presents the application of a pseudo-relevance feedback technique, called Local Context Analysis (LCA), to SENSE (SEmantic N-levels Search Engine). SENSE is an IR system that tries to overcome the limitations of the ranked keyword approach by introducing semantic levels which integrate (and not simply replace) the lexical level represented by keywords. The evaluation shows that this PRF technique is able to work worthily on both the lexical level represented by keywords and the semantic level represented by WordNet synsets.
Sketch Based Picture-Collage Generation Using Evolutionary Computation

This paper describes a sketch based image synthesis method. In this work, image synthesis is treated as a layout generation problem. This method allows users to easily obtain a favorite layout with a simple user operation, sketch drawing. Our method realizes an evolutionary layout generation based on genetic algorithm. First, the target image is given as user strokes. Then, a layout image is generated by pasting sub images that are automatically selected from pre-registered image set. In our approach, the layout image is composed of a base image and the appendant sub images. A base image is probabilistically selected based on roulette wheel selection. The selected base image and the sub images are automatically arranged by the evolutionary generation. We have demonstrated a picture collage application.
Planning for PDDL3 - An OCSP Based Approach

Recent research in AI Planning is focused on improving the quality of the generated plans. PDDL3 incorporates hard and soft constraints on goals and the plan trajectory. Plan trajectory constraints are conditions that need to be satisfied at various stages of the plan. Soft goals are goals, which need not necessarily be achieved but are desirable. An extension of Constraint Satisfaction Problem, called Optimal Constraint Satisfaction Problem (OCSP) has allowance for defining soft constraints and objective functions. Each soft constraint is associated with a penalty, which will be levied if the constraint is violated. The OCSP solver arrives at a solution that minimizes the total penalty (Objective function) and satisfies all hard constraints. In this paper, an OCSP encoding for the classical planning problems with plan trajectory constraints, soft and hard goals is proposed. Modal operators associated with hard goals and hard plan trajectory constraints are handled by preprocessing and imposing new constraints over the existing GP-CSP encoding. A new encoding for each of the modal operators associated with the soft goals and soft plan trajectory constraints is proposed. Also, a way of encoding conditional goal preference constraints into OCSP is discussed. Based on this research, we intend to submit a planner for the coming planning competition-IPC2006.
Simple Printed Multiband Antenna With Novel Parasitic-Element Design for Multistandard Mobile Phone Applications

A simple printed multiband antenna with parasitic-element design for multi-standard handheld terminals in mobile communications is presented. The proposed antenna performs three resonance modes covering six bands of wireless standards, including GSM, GPS, DCS, PCS, UMTS, and LTE 2300/2500. In geometry, the antenna simply consists of two metal stubs. One is an L-shaped driven stub working as a feeder and an embedded transmission line. The other is a U-shaped parasitic stub working as a radiator. With fully printed and simple configuration, the proposed antenna design is cost effective in manufacturing and easy to optimize for different frequency bands. Parametric studies and the design rule are included. The antenna occupies an area of 18 × 37 mm2 on top of a system board. This communication covers the details of the antenna design, working principle, and the performances of simulation and measurement.
Knowledge Discovery from Area‐Class Resource Maps: Data Preprocessing for Noise Reduction

Spatial data mining techniques have been investigated to extract valuable knowledge from natural resource maps. One challenge in applying general‐purpose data mining algorithms to knowledge discovery from these maps is that the unavoidable existence of errors in traditional area‐class resource maps introduces noise to the process and impacts the accuracy of the extracted knowledge. This paper examines the effect of data preprocessing in knowledge discovery from area‐class resource maps. Presented here is a sampling method designed to obtain samples that exclude noise and are representative of the central concepts of the mapped classes. The method is based on selecting only the pixels that fall in modes of environmental histograms for each individual class. A case study in extracting knowledge from soil maps shows that data preprocessing plays an important role in the knowledge discovery process, and that the sampling method based on environmental histograms significantly improves the knowledge discovery performance.
The Gender Gap in Radical Right Voting: Explaining differences in the Netherlands

Men and women differ in their level of radical right votes in most European countries. This research, a cross sectional survey study amoung 1125 Dutch respondents, examines both structural and attitudinal explanations for a difference between male and female voting patterns in the Netherlands. The differences in structural backgrounds, being self-employed, and the importance one attaches to its religion all appear to be factors that close the gender gap in radical right voting. Attitudinal explanations seemed to explain a large part of the variance in voting behavior for both sexes. Comparative analyses showed that the effect of both structural and attitudinal explanations had a higher explanatory power for males than they have for females.
Phenomenology and Its Implications for Gifted Studies Research: Investigating the Lebenswelt of Academically Gifted Students Attending an Elementary Magnet School

A phenomenological investigation of the lebenswelt (life world) of academically gifted students attending an elementary magnet school was conducted. The magnet school is housed in an elementary school that maintains 2 classes per grades 1–6, 1 gifted and 1 heterogeneous. Fifteen gifted students (2 per grades 1–3 and 3 per grades 4–6) participated in phenomenological interviews. The interviews, averaging 50 minutes in length, were recorded and transcribed. Data were analyzed via a 6-step thematic analysis process. The social milieu of the school was described by the students as the backdrop for the meaning of the experience of attending the magnet school for gifted students. Four themes emerged across the magnet school experience: Others, Role, Personal Development, and Time. Nuances and characteristics of the themes are reported.
Max-Sum Diversification, Monotone Submodular Functions and Semi-metric Spaces

In many applications such as web-based search, document summarization, facility location and other applications, the results are preferable to be both representative and diversified subsets of documents. The goal of this study is to select a good "quality", bounded-size subset of a given set of items, while maintaining their diversity relative to a semi-metric distance function. This problem was first studied by Borodin et al\cite{borodin}, but a crucial property used throughout their proof is the triangle inequality. In this modified proof, we want to relax the triangle inequality and relate the approximation ratio of max-sum diversification problem to the parameter of the relaxed triangle inequality in the normal form of the problem (i.e., a uniform matroid) and also in an arbitrary matroid.
Profiling-Based Task Scheduling for Factory-Worker Applications in Infrastructure-as-a-Service Clouds

With the recent advances of cloud computing, effective resource usage (e.g., CPU, memory or network) becomes an important question as application developers have to continuously pay for rented resources, even if they are not used effectively. In order to maintain required performance levels, it is currently common to reserve resources for peak resource usage or possible resource usage overlaps, if more than one task is executed on a host. While this is a reasonable approach for long-running applications or web servers, for some applications with disperse resource usage over time, this strategy causes significant over-provisioning and thus resource wastage and financial loss. In this paper we present a profiling-based task scheduling approach for factory-worker applications that schedules tasks within the defined resource limitations (e.g., Existing machine memory size or network quota) and distributes the tasks in the cloud environment in order to use resources effectively. The evaluation of our approach approved the efficiency of the proposed algorithm and minimal performance overhead. In case of the evaluated application, the presented scheduling process leads up to 33% resource savings with only 1% of performance loss.
Decoupling facial expressions and head motions in complex emotions

Perception of emotion through facial expressions and head motion is of interest to both psychology and affective computing researchers. However, very little is known about the importance of each modality individually, as they are often treated together rather than separately. We present a study which isolates the effect of head motion from facial expression in the perception of complex emotions in videos. We demonstrate that head motions carry emotional information that is complementary rather than redundant to the emotion content in facial expressions. Finally, we show that emotional expressivity in head motion is not limited to nods and shakes and that additional gestures (such as head tilts, raises and general amount of motion) could be beneficial to automated recognition systems.
Table information extraction and structure recognition using query patterns

In this paper, we present a query-based approach to selectively extract tabular information and recognize the table structure from scanned documents. Unlike conventional table processing paradigms, we adopt a client-driven approach where clients provide a query pattern by specifying a set of key-fields in the document image. The query pattern is first transformed into an attributed relational graph where each node is described with features and the edges with spatial relationships between the nodes. A fast graph matching technique is then used to retrieve other similar graphs from the document image. Further, the extracted graphs are collectively analyzed to deduce the overall tabular structure. Experiments on a dataset of 101 commercial transaction documents demonstrate the effectiveness of the proposed method.
Distributed under Creative Commons Cc-by 4.0 the Sensitivity of Biological Finite Element Models to the Resolution of Surface Geometry: a Case Study of Crocodilian Crania

The reliability of finite element analysis (FEA) in biomechanical investigations depends upon understanding the influence of model assumptions. In producing finite element models, surface mesh resolution is influenced by the resolution of input geometry, and influences the resolution of the ensuing solid mesh used for numerical analysis. Despite a large number of studies incorporating sensitivity studies of the effects of solid mesh resolution there has not yet been any investigation into the effect of surface mesh resolution upon results in a comparative context. Here we use a dataset of crocodile crania to examine the effects of surface resolution on FEA results in a comparative context. Seven high-resolution surface meshes were each down-sampled to varying degrees while keeping the resulting number of solid elements constant. These models were then subjected to bite and shake load cases using finite element analysis. The results show that incremental decreases in surface resolution can result in fluctuations in strain magnitudes, but that it is possible to obtain stable results using lower resolution surface in a comparative FEA study. As surface mesh resolution links input geometry with the resulting solid mesh, the implication of these results is that low resolution input geometry and solid meshes may provide valid results in a comparative context.
Assessment of Tracer 99mTc(V)-DMSA Uptake as a Measure of Tumor Cell Proliferation In Vitro

Purpose To examine whether 99mTc(V)-DMSA could be used as a non-invasive measure of cancer cell proliferation. Methods Human breast cancer MCF-7, MDA-MB-231 and pII, and prostate cancer PC-3 cell lines were grown to 30, 50 and 100% confluency and pulsed with 99mTc(V)-DMSA in media for 60 min at 37°C. DNA synthesis was analysed by quantification of the S phase using flow cytometry, [methyl-3H]thymidine incorporation and expression of proliferation markers PCNA and Ki-67 using realtime PCR. One way ANOVA was used to compare groups. Results In all cell lines rates of 99mTc(V)-DMSA uptake were inversely related to cell density. This was paralleled by similar trends in S phase proportions, [methyl-3H]thymidine incorporation and expression of PCNA and Ki-67. Conclusion Rates of 99mTc(V)-DMSA uptake into different types of tumour cells correlate well with cell density that is useful as a non-invasive measure of tumour cellular proliferation in vivo.
Instance- and bag-level manifold regularization for aggregate outputs classification

Aggregate outputs learning differs from the classical supervised learning setting in that, training samples are packed into bags with only the aggregate outputs (labels for classification or real values for regression) known. This setting of the problem is associated with several kinds of application background. We focus on the aggregate outputs classification problem in this paper, and set up a manifold regularization framework to deal with it. The framework can be of both instance level and bag level for different testing goals. We propose four concrete algorithms based on our framework, each of which can cope with both binary and multi-class scenarios. The experimental results on several datasets suggest that our algorithms outperform the state-of-art technique.
Enhancing the properties of a lead-free solder with the addition of Ni-coated carbon nanotubes

In this study, 0.05wt. % of Ni-coated multi-walled carbon nanotubes (Ni-CNTs) were successfully introduced into the 95.8Sn-3.5Ag-0.7Cu solder using the powder metallurgy technique, to synthesize a new lead-free composite solder system. The samples were characterized in terms of their microstructural and mechanical properties. Microstructural analysis of the polished samples revealed uniformly distributed intermetallic phases throughout the solder matrix and EDS analysis identified the phases as Ag3Sn and Cu6Sn5. Furthermore, with the addition of Ni-CNTs, the tensile results showed an improvement in 0.2% yield strength (~13%) and ultimate tensile strength (~15%), when compared with that of unreinforced SnAgCu solder. Nanoindentation tests were also conducted to assess the creep performance of the samples. The results showed that addition of Ni-CNTs improved the creep resistance of the composite solder. The results in this study convincingly established that nanotechnology coupled with composite technology in electronics solders can lead to the enhancement of mechanical properties. Thus, these advanced interconnect materials will benefit the microelectronics assembly and packaging industry. An attempt is made in this study to interrelate the mechanical properties of the resultant composite solder with the presence of Ni-CNTs.