Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost Implications of Comorbidity for Autologous Stem Cell Transplantation in Elderly Patients with Multiple Myeloma Using SEER-Medicare

Comorbidity is more common in older patients and can increase the cost of care by increasing toxicity. Using the SEER-Medicare database from 2000 to 2007, we examined the costs and life-year benefit of Auto-HSCT for MM patients over the age of 65 by evaluating the difference over time relative to comorbidity burden. One hundred ten patients had an Auto-HSCT in the early time period (2000–2003) and 160 in the late time period (2004–2007). Patients were divided by a Charlson Comorbidity Index (CCI) of 0 or greater than 1 (CCI1+). Median overall survival was 53.5 months for the late time period patients compared to 40.3 months for the early time period patients (p = 0.031). Median costs for CCI0 versus CCI1+ in the early period were, respectively, $70,900 versus $72,000 (100 d); $86,100 versus $98,300 (1 yr); and $139,200 versus $195,300 (3 yrs). Median costs for late period were, respectively, $58,400 versus $60,400 (100 d); $86,300 versus $77,700 (1 yr); and $124,400 versus $110,900 (3 yrs). Comorbidity had a significant impact on survival and cost among early time period patients but not among late time period patients. Therefore, older patients with some comorbidities can be considered for Auto-HSCT depending on clinical circumstances.
Mesure de couplage statistique entre signaux EEG : application à l'évaluation quantitative des relations fonctionnelles entre structures cérébrales en épilepsie

La connectivite fonctionnelle cerebrale peut etre caracterisee par l'evolution temporelle de la correlation entre les signaux enregistres dans des regions spatialement distribuees. Ici, nous proposons une comparaison exhaustive et quantitative pour juger des performances de differentes classes de methodes pour l'estimation de cette connectivite. Bases sur plusieurs modeles de simulation, les resultats montrent que les performances sont fortement dependantes des caracteristiques des signaux, aucune methode ne surpassant les autres dans toutes les situations. La nature non stationnaire et oscillatoire des activites des populations neuronales, nous a amene a proposer un estimateur Temps-Frequence de relation. La comparaison objective de ce nouvel estimateur avec un estimateur plus classique, base sur la fonction de coherence, montre qu'il peut conduire a de meilleures performances. Sur des donnees reelles, les resultats indiquent que cet estimateur peut augmenter la lisibilite de la representation TF de la relation et peut ainsi ameliorer l'interpretation des relations entre signaux EEG.
An adaptive texture and shape based defect classification

In this paper classification of surface defects is considered. The classification system consists of several classifiers whose outputs are combined in order to produce the final classification. The self-organizing maps (SOMs) are used as classifiers. Each SOM is taught unsupervised with examples of defects. Classification is based on the internal structure and the shape characteristics of defects. Texture features from the co-occurrence matrix and the gray level histogram are used to describe the internal structure. The set of simple shape descriptors is used for shape characterization The results of experiments with base paper defects are encouraging.
Design and realization of 3D character animation engine

Character animation which is used to show human figure has been extensively applied in VR (Visual Reality) field. Because too much initial work is being repeated, it usually costs more than needed to make character animation, and the technical difficulty is also at a high level. Large game corporations incline to keep the core technologies of character animation as commercial secrets, thus block its development. In this paper, the main framework of a “3D character animation engine” is designed. Great emphasis is put on the principle of different types of character animation and their realization methods. The 3D character animation engine provides consistent APIs for key-frame animation, mixed animation and morph animation. It enable users make character animation through programming in a fast and easy way.
Results of the 4th edition of BioASQ Challenge

The goal of this task is to push the research frontier towards hybrid information systems. We aim to promote systems and approaches that are able to deal with the whole diversity of the Web, especially for, but not restricted to, the context of biomedicine. This goal is pursued by the organization of challenges. The fourth challenge, as the previous challenges, consisted of two tasks: semantic indexing and question answering. 16 systems participated by 7 different participating teams for the semantic indexing task. The question answering task was tackled by 37 different systems, developed by 11 different teams. 25 of the systems participated in the phase A of the task, while 12 participated in phase B. 3 of the teams participated in both phases of the question answering task. Overall, as in previous years, the best systems were able to outperform the strong baselines. This suggests that advances over the state of the art were achieved through the BIOASQ challenge but also that the benchmark in itself is very challenging. In this paper, we present the data used during the challenge as well as the technologies which were at the core of the participants’ frameworks.
Five-year outcomes of severe acute kidney injury requiring renal replacement therapy.

BACKGROUND Current research priorities in critical care medicine are focusing on long-term outcomes of survivors of critical illness. Severe acute kidney injury (AKI) is a common occurrence in intensive care. However, few studies have followed up these patients beyond 12 months after hospital discharge. METHODS Of a cohort of 425 patients, 226 survivors with severe AKI necessitating renal replacement therapy (RRT) were followed up for 60 months after hospital discharge. None of these patients had pre-existing kidney disease. Vital status and renal function were documented annually for 5 years. RESULTS None of the discharged or transferred patients was dependent on RRT; 57% had complete recovery and 43% had partial recovery of renal function. During the first year after hospital discharge, 18% of survivors died, during the second year 4% and during the third to fifth year 2% per year. At 5 years, 25% of the cohort were still alive. Further improvement in renal function (eGFR) was noted in 26 patients within the first year only. Deterioration of renal function occurred in eight patients. At 5 years, renal function was normal in 86% of the remaining survivors, it was impaired in 9% and 5% of the patients alive needed dialysis again. The proportional Cox regression analysis model showed that pre-existing extrarenal comorbidity, surgery and partial recovery of renal function were independent determinants of long-term survival. CONCLUSIONS This prospective observational study indicates that severe AKI is not only a determinant of excess in-hospital case fatalities of critically ill patients, but it also carries significant implications for long-term mortality.
Deep Learning Based Oil Palm Tree Detection and Counting for High-Resolution Remote Sensing Images

Oil palm trees are important economic crops in Malaysia and other tropical areas. The number of oil palm trees in a plantation area is important information for predicting the yield of palm oil, monitoring the growing situation of palm trees and maximizing their productivity, etc. In this paper, we propose a deep learning based framework for oil palm tree detection and counting using high-resolution remote sensing images for Malaysia. Unlike previous palm tree detection studies, the trees in our study area are more crowded and their crowns often overlap. We use a number of manually interpreted samples to train and optimize the convolutional neural network (CNN), and predict labels for all the samples in an image dataset collected through the sliding window technique. Then, we merge the predicted palm coordinates corresponding to the same palm tree into one palm coordinate and obtain the final palm tree detection results. Based on our proposed method, more than 96% of the oil palm trees in our study area can be detected correctly when compared with the manually interpreted ground truth, and this is higher than the accuracies of the other three tree detection methods used in this study.
A Linked Data Model for E-books

This paper proposes and develops a conceptual model for the rigorous representation, design, and utilization of e-books using RDF (Resource Description Framework) as the modeling language. The conceptual model views an e-book as a new type of information object with a complex structure in which its content is broken down into atomic units called "content nodes" and semantically linked together to form a hypermedia database. Content nodes can be of different media types such as images, video clips, text, etc. and the content could come from different sources including the LOD (Linked Open Data) cloud. As a result, an e-book could serve as a distributed semantic hypermedia database. This new way of viewing ebooks will increase the potential and benefits of e-books. A reader could read them as a well-structured book or query their distributed but connected content as a semantic hypermedia database. The conceptual model has been verified to satisfy all major requirements for e-books and support all their necessary operations.
The Surgical Overcorrection of Lenke Type 1 Deformities with Selective Fusion Segments: What Happens to the Coronal Balance?

Purpose The aim of our study is to determine the alterations on coronal balance after overcorrection of Lenke type 1 curve, retrospectively. Methods Datas of 34 patients (29 female, 5 male patients; mean age, 16.3±3.3 years; range, 13-24 years) surgically treated for scoliosis between 2004 and 2010 were reviewed, retrospectively. The adolescent idiopathic scoliosis patients with Lenke type 1 curve treated with only posterior pedicle screw and postoperative thoracic curves less than 10° by Cobb method on frontal plane were enrolled in this study. Mean follow-up period was 52.5±29.7 months. Results The mean amount of the preoperative thoracic curves was measured as 41.2°±6.1° (range, 30°-56°). The mean amount of the early postoperative thoracic curves was measured as 6.5°±1.8° (range, 3°-9°). The mean amount of the thoracic curves was measured as 8.5°±4.6° (range, 3°-22°) during the last follow-up (p=0.01). The mean preoperative coronal balance was measured as 8.5mm(range, 1-30mm). The mean early postoperative coronal balance was measured as 3.5mm(range, 0-36 mm). The mean coronal balance was measured as 5.5mm(range, 0-38mm) during the last follow-up (p>0.05). Conclusion We suggest that Lenke type 1B and 1C should be carefully evaluated and the fusion levels should be accurately selected in order to maintain the correction of coronal balance. We suggest that selective fusion with overcorrection in Lenke type 1A are applied to curves that can be corrected lumbar curve at the preoperative bending radiograph and curves that not have coronal decompensation and >10° distal junctional kyphosis, preoperatively.
Monopolistic nonlinear pricing with consumer entry

We consider consumer entry in the canonical monopolistic nonlinear pricing model (Mussa and Rosen, 1978) wherein consumers learn their preference "types" after incurring privately known entry costs. We show that by taking into account consumer entry, the nature of optimal nonlinear pricing contracts changes significantly: compared to the benchmark without costly entry, in our model both quality distortion and market exclusion are reduced, sorting is more likely, and whenever bunching occurs, the bunching interval is necessarily smaller. Additionally, under certain conditions the monopoly solution may even achieve the first best (i.e., production efficiency). We also demonstrate that the optimal monopoly solutions can be ranked according to inverse hazard rate functions of the entry cost, which suggests an interesting dynamic for monopolistic nonlinear pricing with consumer entry.
Roots and fields: excursions through place, space, and local in hyperlocal media

In 2012, UK charity Nesta announced Destination Local, a program focused on future developments in ‘hyperlocal media’ based on location-based technologies. The program’s first round funded an experimental portfolio of 10 small projects. In this article, I present vignettes drawn from walking interviews with four of the project leaders, putting these into dialogue with phenomenological and practice-centered media theory, as well as growing interests in the geographies of media. My argument is that practices of so-called hyperlocal media should be understood via a phenomenological duality. On one hand, as activities rooted in place: conducting media work though situated environments. Yet, on the other hand, as inhabitations of field spaces: geographically dispersed social and technical worlds. This analysis suggests we step back in order to consider the conceptualization of place, space, and the local itself in studies of ‘hyperlocal’ as an emergent form of media production.
Induction and effector phase of allergic lung inflammation is independent of CCL21/CCL19 and LT-beta

The chemokines CCL21 and CCL19, and cell bound TNF family ligand lymphotoxin beta (LTβ), have been associated with numerous chronic inflammatory diseases. A general role in chronic inflammatory diseases cannot be assumed however; in the case of allergic inflammatory disease, CCL21/CCL19 and LTβ have not been associated with the induction, recruitment, or effector function of Th2 cells nor dendritic cells to the lung. We have examined the induction of allergic inflammatory lung disease in mice deficient in CCL21/CCL19 or LTβ and found that both kinds of mice can develop allergic lung inflammation. To control for effects of priming differences in knockout mice, adoptive transfers of Th2 cells were also performed, and they showed that such effector cells had equivalent effects on airway hyper-responsiveness in both knockout background recipients. Moreover, class II positive antigen presenting cells (B cells and CD11c+ dendritic cells) showed normal recruitment to the peribronchial spaces along with CD4 T cells. Thus, the induction of allergic responses and recruitment of both effector Th2 cells and antigen presenting cells to lung peribronchial spaces can develop independently of CCL21/CCL19 and LTβ.
The auditory and the visual percept evoked by the same audiovisual vowels

In analyses and models of audiovisual speech perception, it has been common to consider three percepts: (1) the auditory percept evoked by acoustic stimuli, (2) the visual percept evoked by optic stimuli and (3) a common percept evoked by synchronous optic and acoustic stimuli. Here, it is shown that a vocal percept that is heard and influenced by vision has to be distinguished from a gestural percept that is seen and influenced by audition. In the two experiments reported, syllables distinguished solely by their vowels [i], [y] or [e] were presented to phonetically sophisticated subjects auditorily, visually and in incongruently cross-dubbed audiovisual form. In the first, the subjects rated roundedness, lip spreading, openness and backness of the vowels they heard in the second of those they saw. The results confirmed that roundedness is mainly heard by eye while openness is heard by ear. Heard backness (retraction) varied with the acoustic and optic presence of roundedness. Seen openness was substantially influenced by acoustic cues, while there was no such influence on seen roundedness. The results are discussed in the context of theories and models.
Ensemble learning for speech enhancement

Over the years, countless algorithms have been proposed to solve the problem of speech enhancement from a noisy mixture. Many have succeeded in improving at least parts of the signal, while often deteriorating others. Based on the assumption that different algorithms are likely to enjoy different qualities and suffer from different flaws, we investigate the possibility of combining the strengths of multiple speech enhancement algorithms, formulating the problem in an ensemble learning framework. As a first example of such a system, we consider the prediction of a time-frequency mask obtained from the clean speech, based on the outputs of various algorithms applied on the noisy mixture. We consider several approaches involving various notions of context and various machine learning algorithms for classification, in the case of binary masks, and regression, in the case of continuous masks. We show that combining several algorithms in this way can lead to an improvement in enhancement performance, while simple averaging or voting techniques fail to do so.
A Low Cost Packet Detector in OFDM-Based Ultra-Wideband Systems

Multiband orthogonal frequency-division multiplexing (MB-OFDM) systems employ frequency-hopping technology to achieve the capabilities of multiple access and frequency diversity. However, they also complicate packet detector (PD) in terms of the requirement for the high hardware complexity. In this paper, we propose several low-cost design schemes for the PD, such as Walsh-Hadamard decomposition, buffered summation, and sign-bit-remaining methods. The estimated gate count of the resulting implemented PD is less than half that of existing solutions
Data Gathering Phase of the Dynamic Reverse Engineering

—Currently available systems for dynamic reverse engineering do not have the satisfying quality. Therefore it is necessary to set the assumptions needed to bring a new methodology that would cover all of the existing solutions. Entire analysis presented in this paper was based on a study of graphic mode initialization of the GeForce GPU. Utilization of 2D acceleration functions, and also all relevant details related to 3D acceleration functions were included.
Design Breakdowns: Designer-Developer Gaps in Representing and Interpreting Interactive Systems

Professional interaction designers and software developers have different trainings and skills, yet they need to closely collaborate to create interactive systems. We conducted three studies to understand the mismatches between their processes, tools and representations. Based on 16 interviews, we found that current practices induce unnecessary rework and cause discrepancies between the original design and the implementation. We identified three key design breakdowns where designers omitted critical details, ignored the presence of edge cases or disregarded technical limitations. We next observed two face-to-face meetings between designers and developers. We found that early involvement of the developer helped to mitigate potential design breakdowns but new ones emerged as the project unfolded. Finally, we ran a participatory design session with two designer/developer pairs. Both pairs had difficulty representing and communicating pre-existing interactions. Creating complete interaction descriptions required iterating from individual examples to rule-based representations. We conclude with implications for designing collaborative tools that facilitate the designer's ability to express and the developer's ability to implement complex interactive systems.
Reversible Pathologic and Cognitive Phenotypes in an Inducible Model of Alzheimer-Amyloidosis

Transgenic mice that express mutant amyloid precursor protein (APPsi) using tet-Off vector systems provide an alternative model for assessing short- and long-term effects of Aβ-targeting therapies on phenotypes related to the deposition of Alzheimer-type amyloid. Here we use such a model, termed APPsi:tTA, to determine what phenotypes persist in mice with high amyloid burden after new production of APP/Aβ has been suppressed. We find that 12- to 13-month-old APPsi:tTA mice are impaired in cognitive tasks that assess short- and long-term memories. Acutely suppressing new APPsi/Aβ production produced highly significant improvements in performing short-term spatial memory tasks, which upon continued suppression translated to superior performance in more demanding tasks that assess long-term spatial memory and working memory. Deficits in episodic-like memory and cognitive flexibility, however, were more persistent. Arresting mutant APPsi production caused a rapid decline in the brain levels of soluble APP ectodomains, full-length APP, and APP C-terminal fragments. As expected, amyloid deposits persisted after new APP/Aβ production was inhibited, whereas, unexpectedly, we detected persistent pools of solubilizable, relatively mobile, Aβ42. Additionally, we observed persistent levels of Aβ-immunoreactive entities that were of a size consistent with SDS-resistant oligomeric assemblies. Thus, in this model with significant amyloid pathology, a rapid amelioration of cognitive deficits was observed despite persistent levels of oligomeric Aβ assemblies and low, but detectable solubilizable Aβ42 peptides. These findings implicate complex relationships between accumulating Aβ and activities of APP, soluble APP ectodomains, and/or APP C-terminal fragments in mediating cognitive deficits in this model of amyloidosis.
Optimization of Task Allocation Time in Mesh using MBF Algorithm and Artificial Neural Network

In the paper, the problem of optimizing task allocation time is considered. A good allocation algorithm should find, for a given task, a free sub-mesh such that to minimize the allocation time, and to keep the fragmentation on the lowest possible level. The proposed here Modified Best Fit algorithm has very good fragmentation level performance, however, the algorithm is very slow. To minimize its allocation time, an Artificial Neural Network is applied. The properties of such an approach are discussed on the basis of the simulations made with experimentation system implemented in Matlab environment.
Progress in blind separation of magnetoencephalographic data

The match between the physics of MEG and the assumptions of the most well developed blind source separation (BSS) algorithms (unknown instantaneous linear mixing process, many sensors compared to expected recoverable sources, large data limit) have tempted researchers to apply these algorithms to MEG data. We review some of these efforts, with particular emphasis on our own work.
Visualizing flow data using assorted glyphs

This project visualizes a scientific dataset containing two-dimensional flow data from a simulated supernova collapse provided by astrophysics researchers. We started our project by designing visualizations using multiple hand drawings representing the flow data without taking into consideration the implementation constraints of our designs. We implemented a few of our hand drawn designs. We used an assortment of simple geometric graphical objects, called glyphs, such as, dots, lines, arrows, and triangles to represent the flow at each sample point. We also incorporated transparency in our visualizations. We identified two important goals for our project: (1) design different types of graphical glyphs to support flexibility in their placement and in their ability to represent multidimensional data elements, and (2) build an effective visualization technique that uses glyphs to represent the two-dimensional flow field.