Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost-effectiveness Analysis of the Diagnosis of Meniscus Tears

Background: Diagnostic imaging represents the fastest growing segment of costs in the US health system. This study investigated the cost-effectiveness of alternative diagnostic approaches to meniscus tears of the knee, a highly prevalent disease that traditionally relies on MRI as part of the diagnostic strategy. Purpose: To identify the most efficient strategy for the diagnosis of meniscus tears. Study Design: Economic and decision analysis; Level of evidence, 1. Methods: A simple-decision model run as a cost-utility analysis was constructed to assess the value added by MRI in various combinations with patient history and physical examination (H&P). The model examined traumatic and degenerative tears in 2 distinct settings: primary care and orthopaedic sports medicine clinic. Strategies were compared using the incremental cost-effectiveness ratio (ICER). Results: In both practice settings, H&P alone was widely preferred for degenerative meniscus tears. Performing MRI to confirm a positive H&P was preferred for traumatic tears in both practice settings, with a willingness to pay of less than US$50,000 per quality-adjusted life-year. Performing an MRI for all patients was not preferred in any reasonable clinical scenario. The prevalence of a meniscus tear in a clinician’s patient population was influential. For traumatic tears, MRI to confirm a positive H&P was preferred when prevalence was less than 46.7%, with H&P preferred above that. For degenerative tears, H&P was preferred until the prevalence reaches 74.2%, and then MRI to confirm a negative was the preferred strategy. In both settings, MRI to confirm positive physical examination led to more than a 10-fold lower rate of unnecessary surgeries than did any other strategy, while MRI to confirm negative physical examination led to a 2.08 and 2.26 higher rate than H&P alone in primary care and orthopaedic clinics, respectively. Conclusion: For all practitioners, H&P is the preferred strategy for the suspected degenerative meniscus tear. An MRI to confirm a positive H&P is preferred for traumatic tears for all practitioners. Consideration should be given to implementing alternative diagnostic strategies as well as enhancing provider education in physical examination skills to improve the reliability of H&P as a diagnostic test. Clinical Relevance: Alternative diagnostic strategies that do not include the use of MRI may result in decreased health care costs without harm to the patient and could possibly reduce unnecessary procedures.
A practical clock tree synthesis for semi-synchronous circuits

In this paper, we propose a new clock tree synthesis method for semi-synchronous circuits. A clock tree obtained by the proposed method is a multi-level multi-way clock tree such that a clockinput timing of each register is a multiple of a predefined unit delay and the length of interconnection from a parent node to its child is upper bounded. The clock trees are constructed for several practical circuits. The size of each clock tree is comparable to a zero skew clock tree. In order to assure the practical quality, they are examined under the five delay conditions, which cover various environmental and manufacturing conditions. As a result, they are proved stable under each condition and improve the clock speed up to 17.3 % against the zero skew clock trees.
Diversity-Multiplexing Tradeoff in Multiple Antenna Systems with Quantized Feedback

In this paper, we derive lower bounds on optimal diversity-multiplexing tradeoff in multiple antenna channels when the transmitter has finite bits of channel state information. We show that for each multiplexing gain, the diversity order is higher than the case without feedback. Furthermore, as the number of feedback bits increases, the diversity-multiplexing tradeoff grows unboundedly to approach the case of perfect channel state information at the transmitter. The major reason for diversity order gain is the opportunistic use of channel degrees of freedom, in the form of “location-dependent” temporal power control, which adapts the power control strategy based on the average signal to noise ratio of the channel. Index Terms Finite rate, quantized, feedback, diversity, multiplexing, MIMO
Using Decision Trees for Knowledge-Assisted Topologically Structured Data Analysis

Supervised learning of an ensemble of randomized trees is considered to recognize classes of events in topologically structured data (e.g. images or time series). We are primarily interested in classification problems that are characterized by severe scarcity of the training samples. The main idea of our paper consists in favoring the selection of attributes that are known to efficiently discriminate the minority class in those nodes of the tree that are close to the leaves and where classes are represented by a small number of training examples. In practice, the knowledge about the ability of an attribute to discriminate the classes represented in a particular node is either provided by an expert or inferred based on a pre-analysis of the entire initial training set. The experimental validation of our approach considers sign language and human behavior recognition. It reveals that the proposed knowledge- assisted tree induction mechanism efficiently compensates for the shortage of the training samples, and significantly improves the tree classifier accuracy in such scenarios.
Neurotoxins and Their Binding Areas on Voltage-Gated Sodium Channels

Voltage-gated sodium channels (VGSCs) are large transmembrane proteins that conduct sodium ions across the membrane and by doing so they generate signals of communication between many kinds of tissues. They are responsible for the generation and propagation of action potentials in excitable cells, in close collaboration with other channels like potassium channels. Therefore, genetic defects in sodium channel genes can cause a wide variety of diseases, generally called “channelopathies. ” The first insights into the mechanism of action potentials and the involvement of sodium channels originated from Hodgkin and Huxley for which they were awarded the Nobel Prize in 1963. These concepts still form the basis for understanding the function of VGSCs. When VGSCs sense a sufficient change in membrane potential, they are activated and consequently generate a massive influx of sodium ions. Immediately after, channels will start to inactivate and currents decrease. In the inactivated state, channels stay refractory for new stimuli and they must return to the closed state before being susceptible to a new depolarization. On the other hand, studies with neurotoxins like tetrodotoxin (TTX) and saxitoxin (STX) also contributed largely to our today’s understanding of the structure and function of ion channels and of VGSCs specifically. Moreover, neurotoxins acting on ion channels turned out to be valuable lead compounds in the development of new drugs for the enormous range of diseases in which ion channels are involved. A recent example of a synthetic neurotoxin that made it to the market is ziconotide (Prialt®, Elan). The original peptide, ω-MVIIA, is derived from the cone snail Conus magus and now FDA/EMA-approved for the management of severe chronic pain by blocking the N-type voltage-gated calcium channels in pain fibers. This review focuses on the current status of research on neurotoxins acting on VGSC, their contribution to further unravel the structure and function of VGSC and their potential as novel lead compounds in drug development.
Feature extraction and clustering-based retrieval for mathematical formulas

Mathematical formulas or expressions are essential for presenting scientific knowledge in many research documents in academic areas such as physics and mathematics. Searching for related mathematical formulas is an important but challenging problem as formulas contain both structural and semantic information. Such information is hidden inside the mathematical expressions of the formulas. To support effective formula search, it is necessary to extract the structural and semantic features from the mathematical presentation of the formulas faithfully. In this paper, we propose an effective approach for formula feature extraction. To evaluate the proposed approach, the extracted features are tested with three popular clustering algorithms, namely K-means, Self Organizing Map (SOM), and Agglomerative Hierarchical Clustering (AHC), for formula retrieval. The performance of the clustering-based retrieval is measured based on a dataset of 881 formulas and promising results have been achieved.
Body image in Brazil: recent advances in the state of knowledge and methodological issues

OBJECTIVE To analyze Brazilian literature on body image and the theoretical and methodological advances that have been made. METHODS A detailed review was undertaken of the Brazilian literature on body image, selecting published articles, dissertations and theses from the SciELO, SCOPUS, LILACS and PubMed databases and the CAPES thesis database. Google Scholar was also used. There was no start date for the search, which used the following search terms: “body image” AND “Brazil” AND “scale(s)”; “body image” AND “Brazil” AND “questionnaire(s)”; “body image” AND “Brazil” AND “instrument(s)”; “body image” limited to Brazil and “body image”. RESULTS The majority of measures available were intended to be used in college students, with half of them evaluating satisfaction/dissatisfaction with the body. Females and adolescents of both sexes were the most studied population. There has been a significant increase in the number of available instruments. Nevertheless, numerous published studies have used non-validated instruments, with much confusion in the use of the appropriate terms (e.g., perception, dissatisfaction, distortion). CONCLUSIONS Much more is needed to understand body image within the Brazilian population, especially in terms of evaluating different age groups and diversifying the components/dimensions assessed. However, interest in this theme is increasing, and important steps have been taken in a short space of time.
imulating activities : Relating motives , deliberation , and attentive coordination Action

Activities are located behaviors, taking time, conceived as socially meaningful, and usually involving interaction with tools and the environment. In modeling human cognition as a form of problem solving (goal-directed search and operator sequencing), cognitive science researchers have not adequately studied ‘off-task’ activities (e.g. waiting), non-intellectual motives (e.g. hunger), sustaining a goal state (e.g. playful interaction), and coupled perceptual–motor dynamics (e.g. following someone). These aspects of human behavior have been considered in bits and pieces in past research, identified as scripts, human factors, behavior settings, ensemble, flow experience, and situated action. More broadly,activity theory provides a comprehensive framework relating motives, goals, and operations. This paper ties these ideas together, using examples from work life in a Canadian High Arctic research station. The emphasis is on simulating human behavior as it naturally occurs, such that ‘working’ is understood as an aspect of living. The result is a synthesis of previously unrelated analytic perspectives and a broader appreciation of the nature of human cognition. Simulating activities in this comprehensive way is useful for understanding work practice, promoting learning, and designing better tools, including human–robot systems.  2002 Elsevier Science B.V. All rights reserved.
Arbitrage Networks

This paper studies the general equilibrium implications of arbitrage trades in segmented financial markets. Arbitrageurs choose a category of trades to specialize in. This results in an equilibrium network in which the various market segments are linked by arbitrageurs. Arbitrageurs exert externalities on each other depending on their position in the network. Due to these externalities, the complete network architecture, in which all links are feasible, is in general suboptimal for arbitrageurs; it is dominated by a hub-spoke architecture. The hub acts as a repository of liquidity, facilitating trades with minimal price impact. For an arbitrary architecture, as the mass of arbitrageurs grows, equilibrium prices converge to those of the frictionless economy with no segmentation. On the other hand, even if the architecture is complete, equilibrium networks may not be complete or even connected, regardless of the mass of arbitrageurs.
ClickRemoval: interactive pinpoint image object removal

In this paper, we explore the problem of deleting objects in still pictures. We present an interactive system based on an intuitive user-friendly interface for removing undesirable objects in digital pictures. To erase an object in an image, a user indicates which object is to be removed by simply pinpointing it with the mouse cursor. As the mouse cursor rolls over the image, the current implicit selected object's border is highlighted, providing a visual feedback. In case where the computer-segmented area does not match the users' perception of the object, users can further provide a few inside/outside object cues by clicking on a small number of object or nonobject pixels. A small number of such cues is generally enough to reach a correct matching, even for complex textured images. Afterwards, the user removes the object by clicking the left mouse button, and a hole-filling technique is initiated to generate a seamless background portion. Our image manipulation system consists of two components: (i) fully automatic or partially user-steered image segmentation based on an improved fast statistical region-growing segmentation, and (ii) texture synthesis or image inpainting of irregular shaped hole regions. Experiments on a variety of photographs display the ability of the system to handle complex scenes with highly textured objects.
An initial approach towards measuring and characterising software evolution

Proposes a number of metrics to assess the maintainability of code. Dominance relations are used to express the complexity of call relations and an assumption is made that, when more complex relations are present within a source code module, it is harder for an application to be maintained. The paper describes a case study whereby the changes in dominance relations are investigated over versions of the software. Based on the changes to the relations, assumptions are made regarding the maintainability of the software. These assumptions are later verified by investigating change documentation and interviewing the maintainers. The results of this study seem to indicate that the dominance relations do reflect some principles of code maintainability.
Efficient Top-k Monitoring of Abnormality in Sensor Networks

There exist challenges in Continuous monitoring application, mainly due to the limited battery power of sensor nodes all the time. Power efficiency is the key. A power efficient top-k monitoring framework called PECTMA is proposed which is a three level architecture including four novel algorithms, CRVMR, ESR, Top-k-sort and BRCR. The basic idea is to install two level filters. One is at each sample sensor node, called CRVMR, to save power battery by suppressing unnecessary data transmittance with a regression function. Another is at each cluster, called ESR, to further reduce the communication cost by eliminating the spatial redundancy. The performance of PECTMA is evaluated using synthetic data sets which is get by referencing the real data sets. Experiment results show that PECTMA is substantially outperforms the existing filter-based TA and the TAG-based approaches for continuous top-k abnormal monitoring when the sample reading are inherently fluctuates, especially with constant periodicity
Exploring Food Purchase Behavior of Low-Income Households: How Do They Economize?

This report compares food purchases by U.S. households of different income levels and finds that low-income shoppers spend less on food purchases despite some evidence that they face generally higher purchase prices. Households can economize on food spending by purchasing more discounted products, favoring private-label (generic) products over brand, pursuing volume discounts, or settling for a less expensive product (for example, less lean beef within a product class. A 1998 sample of food store purchase data shows that low-income households adhere to these practices when possible, but that the typically smaller size of food stores in urban and rural locations may sometimes preclude them from doing so.
QoS Management in Cloud@Home Infrastructures

Cloud is strongly emerging as the new deal of distributed computing. One of the reason behind the Cloud success is its business/commercial-oriented nature, proof of its effectiveness and applicability to real problems. There are actually a lot of open-private Cloud infrastructures aiming at providing dynamic-on demand resource provisioning according to the IAAS paradigm. To this purpose they usually apply a best effort policy, without taking into account service level agreements (SLA) and related quality of service (QoS) requirements. In such a context, the main goal of Cloud@Home is to implement a volunteer-Cloud paradigm which allows to aggregate Cloud infrastructure providers. In this work we specifically focus on SLA-QoS aspects, describing how to provide SLA based QoS guarantees through Cloud@Home on top of non-QoS oriented Cloud Providers. Aim of the paper is to demonstrate how Cloud@Home can fulfil such goal, providing and specifying the architecture, the algorithms and the components that implement SLA-QoS management features.
Evaluation of the Accuracy of Anthropometric Clinical Indicators of Visceral Fat in Adults and Elderly

Background Visceral obesity is associated with higher occurrence of cardiovascular events. There are few studies about the accuracy of anthropometric clinical indicators, using Computed Tomography (CT) as the gold standard. We aimed to determine the accuracy of anthropometric clinical indicators for discrimination of visceral obesity. Methods Cross-sectional study with 191 adults and elderly of both sexes. Variables: area of visceral adipose tissue (VAT) identified by CT, Waist-to-Height Ratio (WHtR), Conicity index (C index), Lipid Accumulation Product (LAP) and Visceral Adiposity Index (VAI). ROC analyzes. Results There were a strong correlation between adiposity indicators and VAT area. Higher accuracy of C index and WHtR (AUC≥0.81) than the LAP and the VAI was observed. The higher AUC of LAP and VAI were observed among elderly with areas of 0.88 (CI: 0.766–0.944) and 0.83 (CI: 0.705–0.955) in men and 0.80 (CI: 0.672–0.930) and 0.71 (CI: 0.566–0.856) in women, respectively. The cutoffs of C index were 1.30 in elderly, in both sexes, with sensitivity ≥92%, the LAP ranged from 26.4 to 37.4 in men and from 40.6 to 44.0 in women and the VAI was 1.24 to 1.45 (sens≥76.9%) in men and 1.46 to 1.84 in women. Conclusion Both the anthropometric indicators, C Index and WHtR, as well as LAP and VAI had high accuracy in visceral obesity discrimination. So, they are effective in cardiovascular risk assessment and in the follow-up for individual and collective clinical practice.
Radon transform inversion via Wiener filtering over the Euclidean motion group

In this paper we formulate the Radon transform as a convolution integral over the Euclidean motion group (SE(2)) and provide a minimum mean square error (MMSE) stochastic deconvolution method for the Radon transform inversion. Proposed approach provides a fundamentally new formulation that can model nonstationary signal and noise fields. Key components of our development are the Fourier transform over SE(2), stochastic processes indexed by groups and fast implementation of the SE(2) Fourier transform. Numerical studies presented here demonstrate that the method yields image quality that is comparable or better than the filtered backprojection algorithm. Apart from X-ray tomographic image reconstruction, the proposed deconvolution method is directly applicable to inverse radiotherapy, and broad range of science and engineering problems in computer vision, pattern recognition, robotics as well as protein science.
Predictors of Clinical Outcomes of Flexible Ureterorenoscopy with Holmium Laser for Renal Stone Greater than 2 cm

Objective. To evaluate the clinical outcome of flexible ureterorenoscopy (F-URS) with holmium laser in managing renal stone greater than 2 cm. Patients and Methods. Records of 120 patients (123 renal units) with renal stone greater than 2 cm who underwent F-URS with holmium laser iwere evaluated. The mean stone size was 26.3 mm. Patient and stone characteristics, perioperative outcomes and complications were evaluated. The outcome was determined at 4 weeks on plain radiograph (KUB) and Non-contrast CT scan (NCCT). Follow-up visit was up to 6 months to evaluate the clinical outcome and patients symptoms. Results. Stone burden was an independent predictor of FURS results. After first session of treatment, success rate was obtained in 72 renal units (58.5%). On the other hand, significant residual fragment was encountered in 51 renal units (41.5%). This was improved with “staged-therapy” to 87% and 96.7% after second and third session of treatment, respectively. Complications were recorded. They were managed in proper manner accordingly. Conclusion. This is an attractive, safe and effective technique. It is an ideal option for low volume complex stone with average burdens of 2 to 3 cm. Patient should be informed and consented about staged-therapy.
Nested evolution of an autonomous agent using descriptive encoding

In this paper, we investigate the use of nested evolution in which each step of one evolutionary process involves running a second evolutionary process. We apply this approach to build a neuroevolution system for reinforcement learning (RL) problems. Genetic programming based on a descriptive encoding is used to evolve the neural architecture, while a nested evolution strategy is used to evolve the needed connection weights. We test this hierarchical evolution on a non-Markovian RL problem involving an autonomous foraging agent, finding that the evolved networks significantly outperform a rule-based agent serving as a control.
A PAC-Bayesian Approach to Formulation of Clustering Objectives

Clustering is a widely used tool for exploratory data analysis. However, the theoretical understanding of clustering is very limited. We still do not have a well-founded answer to the seemingly simple question of “how many clusters are present in the data? ”, and furthermore a formal comparison of clusterings based on different optimization objectives is far beyond our abilities. The lack of good theoretical support gives rise to multiple heuristics that confuse the practitioners and stall development of the field. We suggest that the ill-posed nature of clustering problems is caused by the fact that clustering is often taken out of its subsequent application context. We argue that one does not cluster the data just for the sake of clustering it, but rather to facilitate the solution of some higher level task. By evaluation of the clustering’s contribution to the solution of the higher level task it is possible to compare different clusterings, even those obtained by different optimization objectives. In the preceding work it was shown that such an approach can be applied to evaluation and design of co-clustering solutions. Here we suggest that this approach can be extended to other settings, where clustering is applied.