Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical application of transanal ileal tube placement using X-ray monitoring

Colorectal cancer, which includes colon and rectal cancer, is a common digestive tract tumor. Although surgery is the primary form of treatment, there are a number of drawbacks, including patients experiencing considerable pain and high cost. The present study was undertaken to examine the clinical value of transanal ileal tube placement under X-ray monitoring. Thirty-six cases of left colon obstruction presenting to our hospital between July 2011 and February 2014, underwent transanal ileal tube placement using a single-curve catheter guided by a guidewire under X-ray monitoring. An ileal tube was successfully inserted into 32 patients. Clinical symptoms were alleviated effectively within 48 h. Indwelling catheter decompression time was 4–9 days with an average of 5.61 days. In two cases, the colon guidewire perforated into the abdominal cavity. Repeated exploration resistance of the guidewire and catheter indicated stenosis at this position owing to obstruction. In conclusion, transanal placement of the ileal tube through X-ray monitoring is capable of effectively alleviating the symptoms of ileus. Thus, this constitutes a safe, effective, and economical method that is acceptable to patients.
A System for the Semantic Interpretation of Unrestricted Domains using WordNet

In this demonstration, we show an algorithm for the semantic interpretation of unrestricted texts. The algorithm presents a solution for the following interpretation problems: determination of the meaning of the verb, identification of thematic roles and adjuncts, and attachments of prepositional phrases (PPs). An interesting aspect of the algorithm is that the solution of all these problems is interdependent. The interpretation algorithm uses WordNet (Miller et al. 1993) as its lexical knowledge-base. Predicates, or verbal concepts, have been defined for WordNet verb classes (Fellbaum 1993), which have been reorganized considerably following the criteria imposed by the interpretation algorithm. The WordNet ontology for nouns has also undergone some reorganization and redefinition to conform with the entries in the thematic roles of the predicates. We have taken a top-down approach that defines generic
Design and Evaluation of Interactive Proofreading Tools for Connectomics

Proofreading refers to the manual correction of automatic segmentations of image data. In connectomics, electron microscopy data is acquired at nanometer-scale resolution and results in very large image volumes of brain tissue that require fully automatic segmentation algorithms to identify cell boundaries. However, these algorithms require hundreds of corrections per cubic micron of tissue. Even though this task is time consuming, it is fairly easy for humans to perform corrections through splitting, merging, and adjusting segments during proofreading. In this paper we present the design and implementation of Mojo, a fully-featured single-user desktop application for proofreading, and Dojo, a multi-user web-based application for collaborative proofreading. We evaluate the accuracy and speed of Mojo, Dojo, and Raveler, a proofreading tool from Janelia Farm, through a quantitative user study. We designed a between-subjects experiment and asked non-experts to proofread neurons in a publicly available connectomics dataset. Our results show a significant improvement of corrections using web-based Dojo, when given the same amount of time. In addition, all participants using Dojo reported better usability. We discuss our findings and provide an analysis of requirements for designing visual proofreading software.
On Fokker-Planck approximations of on-line learning processes

There are several ways to describe on-line learning in neural networks. The two major ones are a continuous-time master equation and a discrete-time random-walk equation. The random-walk equation is obtained in the case of fixed time intervals between subsequent learning steps, the master equation results when the time intervals are drawn from a Poisson distribution. Following Van Kampen (1992), we give a rigorous expansion of both the master and the random-walk equation in the limit of small learning parameters. The results explain the difference between the Fokker-Planck approaches proposed by Radons et al (1990) and Hansen et al. (1993). Furthermore, we find that the mathematical validity of these approaches is restricted to local properties of the learning process. Yet Fokker-Planck approaches are often suggested as models to study global properties, such as mean first passage times and stationary solutions. To check their accuracy and usefulness in these situations we compare simulations of two learning procedures with exactly the same drift vector and diffusion matrix, the only moments that are considered in Fokker-Planck approximation. The simulations show that the mean first passage times for these two learning procedures diverge rather than converge for small learning parameters. We reach the conclusion that Fokker-Planck approaches are not accurate enough to compute global properties of on-line learning processes.
Coassociative K3 fibrations of compact G_2-manifolds

A class of examples of Riemannian metrics with holonomy G_2 on compact 7-manifolds was constructed by the author in arXiv:math.DG/0012189 and later in a joint work with N. -H. Lee in arXiv:0810.0957, using a certain `generalized connected sum' of two asymptotically cylindrical manifolds with holonomy SU(3). We consider, on each of the two initial SU(3)-manifolds, a fibration arising from a Lefschetz pencil of K3 surfaces. The gluing of the two K3 fibrations yields a coassociative fibration of the connected sum G_2-manifold over a 3-dimensional sphere. The singular fibres of this fibration are diffeomorphic to K3 orbifolds with ordinary double points and are parameterized by a Hopf-type link. We believe that these are the first examples of fibrations of compact manifolds of holonomy G_2 by coassociative minimal submanifolds.
Medication Timing Errors for Parkinson's Disease: Perspectives Held by Caregivers and People with Parkinson's in New Zealand

Background. Common but seldom published are Parkinson's disease (PD) medication errors involving late, extra, or missed doses. These errors can reduce medication effectiveness and the quality of life of people with PD and their caregivers. Objective. To explore lay perspectives of factors contributing to medication timing errors for PD in hospital and community settings. Design and Methods. This qualitative research purposively sampled individuals with PD, or a proxy of their choice, throughout New Zealand during 2008-2009. Data collection involved 20 semistructured, personal interviews by telephone. A general inductive analysis of the data identified core insights consistent with the study objective. Results. Five themes help to account for possible timing adherence errors by people with PD, their caregivers or professionals. The themes are the abrupt withdrawal of PD medication; wrong, vague or misread instructions; devaluation of the lay role in managing PD medications; deficits in professional knowledge and in caring behavior around PD in formal health care settings; and lay forgetfulness. Conclusions. The results add to the limited published research on medication errors in PD and help to confirm anecdotal experience internationally. They indicate opportunities for professionals and lay people to work together to reduce errors in the timing of medication for PD in hospital and community settings.
Segmentation of Facial Features based on Human Face configuration for Facial Expression System

Mouth and eye plays very virtual role in the analysis of human mood. The proposed method focus on segmentation of these potential features. In this paper, an approach to the problem of facial feature detection based on human face configuration is presented . To recognize facial features from given image. Applying appropriate threshold value to find Facial feature such as eye, and mouth are extracted using statistical features, such as right array division and right array multiplications operations. Experiments are carried out on JAFFE facial expression database [12] and obtained better performance of the proposed approach in terms of accuracy.
New approach for imbalanced biological dataset classification

This paper presents a new ensemble classifier for class imbalance problem with the emphasis on two -class (binary) classification. This novel method is a combination of SMOTE (Synthetic Minority Over-sampling Technique), Rotation Forest, and AdaBoostM1 algorithms. SMOTE was employed for the over-sampling of the minority samples at 100%, 200%, 300%, 400%, and 500% of the initial sample size, with attribute selection being conducted in order to prevent the classification from being over-fitted. The ensemble classifier method was presented to solve the problem of imbalanced biological datasets classification by obtaining a low prediction error and raising the prediction performance. The Rotation Forest algorithm was used to produce an ensemble classifier with a lower prediction error, while the AdaBoostM1 algorithm was used to enhance the performance of the classifier. All the tests were carried out using the java-based WEKA (Waikato Environment for Knowledge Analysis) and Orange canvas data mining systems for training datasets. The performances of three types of classifiers on imbalanced biomedical datasets were assessed. This paper explores the efficiency of this new method in producing an accurate overall classifier and in lowering the error rate in the overall performance of the classifier. Tests were carried out on three actual imbalanced biomedical datasets, which were obtained from the KEEL dataset repository. These imbalanced datasets were divided into ten categories according to their imbalance ratios (IR) which ranged from 1.86 to 41.40. The results indicated that the proposed method, which used a combination of three methods and various evaluation metrics in its assessments, was effective. In practical terms, the use of the SMOTERotBoost for the classification of biological datasets results in a low mean absolute error rate as well as high accuracy and precision. The values of the Kappa Coefficient were close to 1, thus indicating that all the rates in every classification were the same even though the false negative rates, which were close to 0, showed the reliability of the measurements. The SMOTE-RotBoost has useful AUC-ROC outputs that characterise the wider area under the curve compared to other classifiers and is a vital method for the assessment of diagnostic tests.
A Graduate Course on E-commerce Information Systems Engineering

Interest in developing and deploying e-commerce systems has grown greatly over the past few years, leading to a major shortage of qualified developers able to deliver such applications. This paper describes the development of a graduate course in e-commerce education that has been implemented as part of an Honours degree programme and a first year Masters offering for a traditional Information Systems programme. The aim of this course is to give graduate students a broad grounding and holistic set of skills to enable them to begin successful e-commerce systems development. This paper provides a background and context for this course, an overview and discussion of the course content, delivery methods and practical focus, and discusses experience in running and evolving the course over the past two years. We hope that our experiences and approaches will be useful for others who are planning similar courses focusing on e-commerce systems engineering.
A Historical-Information-Based Algorithm in Dynamic Spectrum Allocation

Cognitive radio is viewed as a novel approach for improving the utilization of radio frequency spectrum greatly by intelligently search and utilize free spectrum not used by licensed user. Dynamic spectrum allocation technology is one of the key technologies in realization of cognitive radio. In this paper we propose a new algorithm for spectrum sharing which considering historical allocation information of secondary user. Simulation results indicate this Historical-information-based algorithm can achieve greater performance in sum bandwidth and fairness compared to the original algorithm.
Assistive Technology Needs and Measurement of the Psychosocial Impact of Assistive Technologies for Independent Living of Older Hispanics: Lessons Learned

(1) Knowledge about the assistive technology (AT) needs and psychosocial impact of AT in different populations is needed because the adoption, retention, or abandonment of AT may be influenced by the psychosocial impact that AT has on its users. The aims of this study were to: (a) identify the AT needs of a sample of Hispanic older adults with functional limitations, (b) describe the psychosocial impact of these technologies on the sample’s quality of life, and (c) describe the methodological challenges in using the Puerto Rican version of the Psychosocial Impact of Assistive Device Scale (PR-PIADS) with a Hispanic sample. (2) Methods: This study used a cross-sectional design conducted with a sample of 60 participants. Data was collected using the Assistive Technology Card Assessment Questionnaire (ATCAQ) and the PR-PIADS. Data analyses included descriptive statistics and bivariate analysis. (3) Results: The sample’s most frequently reported needs for AT devices were in the areas of cooking, home tasks, and home safety activities. The sample reported a positive impact of AT use in their quality of life. Several methodological challenges of the PIADS were identified. (4) Conclusions: The sample has unmet needs for using AT devices to overcome difficulties in daily living activities.
UTILIZING TYPE Ia SUPERNOVAE IN A LARGE, FAST, IMAGING SURVEY TO CONSTRAIN DARK ENERGY

We study the utility of a large sample of Type Ia supernovae (SNe Ia) that might be observed in an imaging survey that rapidly scans a large fraction of the sky for constraining dark energy. We consider both the information contained in the traditional luminosity distance test as well as the spread in Ia SN fluxes at fixed redshift induced by gravitational lensing. As would be required from an imaging survey, we include a treatment of photometric redshift uncertainties in our analysis. Our primary result is that the information contained in the mean distance moduli of SNe Ia and the dispersion of SN Ia distance moduli complement each other, breaking a degeneracy between the present dark energy equation of state and its time variation without the need for a high-redshift (z ≳ 0.8) SN sample. Including lensing information also allows for some internal calibration of photometric redshifts. To address photometric redshift uncertainties, we present dark energy constraints as a function of the size of an external set of spectroscopically observed SNe that may be used for redshift calibration, Nspec. Depending upon the details of potentially available, external SN data sets, we find that an imaging survey can constrain the dark energy equation of state at the epoch where it is best constrained wp, with a 1σ error of σ(wp) ≈ 0.03–0.09. In addition, the marginal improvement in the error σ(wp) from an increase in the spectroscopic calibration sample drops once Nspec ∼ a few × 103. This result is important because it is of the order of the size of calibration samples likely to be compiled in the coming decade and because, for samples of this size, the spectroscopic and imaging surveys individually place comparable constraints on the dark energy equation of state. In all cases, it is best to calibrate photometric redshifts with a set of spectroscopically observed SNe with relatively more objects at high redshift (z ≳ 0.5) than the parent sample of imaging SNe.
The N-DRC forms a conserved biochemical complex that maintains outer doublet alignment and limits microtubule sliding in motile axonemes

The nexin–dynein regulatory complex (N-DRC) is implicated in the control of dynein activity as a structural component of the nexin link. This study identifies several new subunits of the N-DRC and demonstrates for the first time that it forms a discrete biochemical complex that maintains outer doublet integrity and regulates microtubule sliding.
Multi-level fault modeling for transaction-level specifications

Fault modeling is a fundamental element for several activities, ranging from off- and on-line testing, to fault tolerance and dependability-aware design. These activities are carried out during various design phases, dealing with specifications at different abstraction levels. Therefore, modeling faults across abstraction levels is of paramount importance to introduce dependability-related issues from the early phases of design. This paper analyzes how faults can be modeled at the different levels of abstraction with respect to Transaction Level Models, and how these models are related across levels. The work focuses on soft errors and aims at providing support to dependability analysis. A case study of a Transaction Level specification of a Network-on-Chip switch is used to evaluate the methodology and its applicability.
Homelessness: Critical reflections and observations from an occupational perspective

ABSTRACT This comment is the result of our critical reflections, observations and discussions in relation to occupation and homelessness, inspired by our participation in the fourth conference of Occupational Science Europe and informed by our research and experiences in the field. Whilst we acknowledge the growing contribution of occupational science and therapy to homelessness, our practices have led us to identify a number of complex factors that impact this work. In this paper, we discuss issues that influence the participation of homeless persons in everyday life and make suggestions to support occupational participation. At the macro level, we recognise the importance of definitions and categories of homelessness, how legislation can frame the responsibility of homelessness on individuals, and poverty as a causal factor. At the meso level, we explore how charity and power differentials within homelessness services influence participation and propose an occupationally informed approach to homelessness services to enhance meaningful participation. Finally, at the micro level, we focus on interactions with individuals, examining the notion of occupational choice for homeless persons and critiquing traditional rehabilitative approaches. This comment reflects our own critical awakening as occupational therapists situated within a neoliberal society and the value of collaboration between occupational science and occupational therapy. It reinforces the essential role that critical occupational science plays in knowledge generation by attending to the complex structural, cultural and social factors that influence the choices and occupations of homeless persons, which in turn enhances occupation-focused practice.
The Case for Anisotropic Afterglow Efficiency within Gamma-Ray Burst Jets

Early X-ray afterglows recently detected by Swift frequently show a phase of very shallow flux decay lasting from ~102.5 up to ~104 s, followed by a steeper, more familiar decay. We suggest that the flat early part of the light curve may be a combination of (1) the decaying tail of the prompt emission and (2) the delayed onset of the afterglow emission observed from viewing angles slightly outside the edge of that part of the jet that generates prominent afterglow emission, as predicted previously. This would imply that a significant fraction of viewers get very little external shock energy along their line of sight and, therefore, see a very high γ-ray-to-kinetic energy ratio at early times. The early flat phase in the afterglow light curve implies, for standard afterglow theory, a very large γ-ray efficiency, typically ≳90%, which is very difficult to extract from baryons by internal shocks.
AN INVESTIGATION INTO THE IDENTIFICATION OF CONCURRENTLY PRESENTED EARCONS

In this paper we describe an experiment investigating the ability of participants to identify multiple, concurrently playing structured sounds, called earcons. Several different sets of earcons were compared, one “state of the art” set based on the guidelines of Brewster [1], and other sets of earcons modified to take account of auditory scene analysis principles. The effect of the number of concurrently playing earcons on identification was also investigated, with instances of 1, 2, 3 and 4 concurrently playing earcons tested. Overall, performance was low, with less than two earcons being successfully identified in any condition. However it was found that both staggering the onset times of each earcon, as well as presenting each earcon with a unique timbre, had a significantly positive effect on identification.
Appendix Identifying Response Styles : A Latent-Class Bilinear Multinomial Logit Model

Several parameter restrictions are necessary for identification of the model parameters. Here, we describe the restrictions that we impose. First, we consider location restrictions, that is, restrictions that are necessary because adding a constant to a set of parameters would not change the estimated probabilities in the model. Location restrictions are needed for aj|r, F, Gk, and Hs. We impose sum-to-zero constraints for all these parameters per set, that is, we require that
Long-term working memory and interrupting messages in human – computer interaction

The extent to which memory for information content is reliable, trustworthy, and accurate is crucial in the information age. Being forced to divert attention to interrupting messages is common, however, and can cause memory loss. The memory effects of interrupting messages were investigated in three experiments. In Experiment 1, attending to an interrupting message decreased memory accuracy. Experiment 2, where four interrupting messages were used, replicated this result. In Experiment 3, an interrupting message was shown to be most disturbing when it was semantically very close to the main message. Drawing from a theory of long-term working memory it is argued that interrupting messages can both disrupt the active semantic elaboration of content during encoding and cause semantic interference upon retrieval. Properties of the interrupting message affect the extent and type of errors in remembering. Design implications are discussed.
The RhoGEF Cysts couples apical polarity proteins to Rho and myosin activity at adherens junctions

The spatio-temporal regulation of small Rho GTPases is crucial for the dynamic stability of epithelial tissues. However, how RhoGTPase activity is controlled during development remains largely unknown. To explore the regulation of Rho GTPases in vivo we analyzed the Rho GTPase guanine nucleotide exchange factor (RhoGEF) Cysts, the Drosophila orthologue of mammalian p114RhoGEF, GEF-H1, p190RhoGEF, and AKAP-13. Loss of Cysts causes a phenotype that closely resemble the mutant phenotype of the apical polarity regulator Crumbs. This phenotype can be suppressed by the loss of basolateral polarity proteins suggesting that Cysts in an integral component of the apical polarity protein network. Cysts activates Rho at adherens junctions to promote junctional enrichment of myosin II, which requires the RhoGEF domain and the coiled-coil domain containing C-terminal region of Cysts. Cysts recruitment to the apico-lateral cortex depends on Crumbs and Bazooka/Par3 and requires multiple domains within Cysts including the C-terminal region. Together, our findings indicate that Cysts links apical polarity proteins to Rho1 and myosin activation at adherens junctions to support junctional and epithelial integrity in the Drosophila ectoderm.