Miracle-dz/UniFAR-FTUs huggingface dataset:
Seguimiento citogenético y molecular en pacientes con leucemia mieloide crónica y trasplante alogénico de médula ósea

The genetic hallmark of chronic myelogenous leukemia (CML) is the t(9;22)(q34;q11), this gene fusion leads to the expression of chimeric BCR/ABL messenger RNA (mRNA), this marker is an attractive target for monitoring minimal residual disease (MDR) after bone marrow transplantation (BMT). The RT-PCR assays has become widely used for monitoring MDR after BMT for CML. We reported the cytogenetic and molecular findings in follow-up samples from 15 CML patients undergoing BMT. All 15 patients investigated before BMT by cytogenetic and RT-PCR were positive for Ph1 chromosome and BCR/ABL transcripts. Ten patients in complete remission presented for >12 month BCR/ABL transcript negative and karyotype normal. In five patients the RT-PCR nested for BCR/ABL were positive, three developed disease recurrence, one died by relapse, the other case with BCR/ABL+ for >12 months received donor lymphocyte infusion (DLI), then he has complete remission. We concluded that cytogenetic analysis is limited and insufficient in the monitoring of BMT and the RT-PCR provide reliable information on residual tumor burden in CML patients with BMT. The prognostic significance of a qualitative BCR/ABL can be refined by quantitative assays and this may target patients who would benefit from early intervention therapeutic.
A Single-Channel Consumer-Grade EEG Device for Brain–Computer Interface: Enhancing Detection of SSVEP and Its Amplitude Modulation

Brain-Computer interfaces (BCIs) play a significant role in easing neuromuscular patients on controlling computers and prosthetics. Due to their high signal-to-noise ratio, steady-state visually evoked potentials (SSVEPs) has been widely used to build BCIs. However, currently developed algorithms do not predict the modulation of SSVEP amplitude, which is known to change as a function of stimulus luminance contrast. In this study, we aim to develop an integrated approach to simultaneously estimate the frequency and contrast-related amplitude modulations of the SSVEP signal. To achieve that, we developed a behavioral task in which human participants focused on a visual flicking target which the luminance contrast can change through time in several ways. SSVEP signals from 16 subjects were then recorded from electrodes placed at the central occipital site using a low-cost, consumer-grade EEG. Our results demonstrate that the filter bank canonical correlation analysis (FBCCA) performed well in SSVEP frequency recognition, while the support vector regression (SVR) outperformed the other supervised machine learning algorithms in predicting the contrast-dependent amplitude modulations of the SSVEPs. These findings indicate the applicability and strong performance of our integrated method at simultaneously predicting both frequency and amplitude of visually evoked signals, and have proven to be useful for advancing SSVEP-based applications.
The D/H Ratio in Interstellar Gas toward G191-B2B

Recent analysis of Goddard High-Resolution Spectrograph (GHRS) echelle spectra suggests ~30% variations in the D/H abundance ratio along the line of sight to the nearby (69 pc) hot white dwarf (WD) G191-B2B (Vidal-Madjar et al.). Variations in the D/H ratio on such short length scales imply nonuniform production/destruction of deuterium and an inefficient mixing of gas in the local interstellar medium (LISM). We reinvestigate the question of the spatial variation of the local D/H abundance using both archival GHRS spectra and new echelle spectra of G191-B2B obtained with the Space Telescope Imaging Spectrograph (STIS) aboard the Hubble Space Telescope. The STIS spectra were obtained in the high-resolution (E140H) mode and cover the wavelength region ranging from 1140 to 1700 Å. Our analysis uses stratified line-blanketed non-LTE model atmosphere calculations to determine the shape of the intrinsic WD Lyα profile and to estimate the WD photospheric contamination of the interstellar lines. Although three velocity components were reported previously toward G191-B2B, we deduce only two velocity components. The first component is at vhel ~ 8.6 km s-1, and the second is at vhel ~ 19.3 km s-1, which we identify with the local interstellar cloud (LIC). From the STIS data, we derive D/H = 1.60 × 10-5 for the LIC component and D/H > 1.26 × 10-5 for the 8.6 km s-1 component (uncertainties denote 2 σ or 95% confidence limits). The derived D/H values in both components are consistent with (D/H)LIC = (1.5 ± 0.1) × 10-5, which was determined by Linsky in 1998. The STIS data provide no evidence for local or component-to-component variation in the D/H ratio. Our reanalysis of the GHRS data gives essentially the same results as Vidal-Madjar et al., despite using two velocity components for the profile fitting (vs. three by Vidal-Madjar et al.) and a more physically realistic WD Lyα profile for G191-B2B. The GHRS data indicate a component-to-component variation as well as a variation of the D/H ratio in the LISM, neither of which are supported by the newer STIS data. The D I absorption in the GHRS spectrum is shallower than in the STIS spectrum. The most probable cause for this difference in the two data sets is the characterization of the background due to scattered light in the GHRS and STIS spectrographs. The D/H ratios derived are sensitive to the background-subtraction procedures employed. The two-dimensional MAMA detectors of STIS measure both the spatial and wavelength dependences of scattered light, allowing more accurate scattered-light corrections than was possible with GHRS.
Implementation of voyage data recording device using a digital forensics-based hash algorithm

Identifying the causes of marine accidents is difficult because of problems in scene preservation, reenactment, and procuring of witnesses. Thanks to new regulations, larger vessels are now required to carry voyage data recorders (VDRs) and automatic identification systems (AISs). However, the content of these devices, which is created, stored, and managed digitally, has security vulnerabilities such as the potential for data modification. Therefore, when managing digital records it is important to guarantee reliability. To this end, we suggest a digital forensics-based digital records migration method using a hash algorithm to guarantee the integrity and authenticity of digital records.
Product recommendation system based user purchase criteria and product reviews

In this paper, we propose a system that provides customized product recommendation information after crawling product review data of internet shopping mall with unstructured data, morphological analysis using Python. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product. And extracts and analyzes only the review including the purchase criterion selected by the user among the product reviews left by other users. The positive and negative evaluations contained in the extracted product review data are quantified and using the average value, we extract the top 10 products with good product evaluation, sort and recommend to users. And provides user-customized information that reflects the user's preference by arranging and providing a center around the criteria that the user occupies the largest portion of the product purchase. This allows users to reduce the time it takes to purchase a product and make more efficient purchasing decisions.
On Addressing Efficiency Concerns in Privacy Preserving Data Mining

Data mining services require accurate input data for their results to be meaningful, but privacy concerns may influence users to provide spurious information. To encourage users to provide correct inputs, we recently proposed a data distortion scheme for association rule mining that simultaneously provides both privacy to the user and accuracy in the mining results. However, mining the distorted database can be orders of magnitude more time-consuming as compared to mining the original database. In this paper, we address this issue and demonstrate that by (a) generalizing the distortion process to perform symbol-specific distortion, (b) appropriately choosing the distortion parameters, and (c) applying a variety of optimizations in the reconstruction process, runtime efficiencies that are well within an order of magnitude of undistorted mining can be achieved.
Detection of abused drugs in urine by GC-MS

This paper reviews gas chromatography-mass spectrometry (GC-MS) methods for the analysis of amphetamines, ketamines, opioids, cocaine, and other abused drugs in urine that were developed by authors in Taiwanese institutions, and published during the 2000 to early 2008 period. Information on sample preparation, derivatization, internal standard, GC column, detection mode, and validation data for the reported methods are summarized in table format to facilitate readers' reference and adaptation.
PARTICULATE MATTER DETERMINATION FROM TRANSPORTATION AND CONSTRUCTION AREA

Air quality sampling was conducted to determine particulate matter (PM10) at the traffic intersections of University Malaysia Sabah (UMS) entrance and at the construction site located at Kota Kinabalu Industrial Park (KKIP). Both represent the determination particulate matter due to transportation and construction air pollution case study started from 10 February 2012 until 19 February 2012. Air was sampled using Minivol Portable Air Sampler operating in particulatesampling mode with two types of membrane filter media namely glass fiber and nano-fiber membrane. Daily samples were gravimetrically determined and comparisons made between the results obtained. Daily PM10 concentrations at construction area of KKIP recorded the range of 129-163μm for Polymer Nano Fiber membrane filter and 82-130 μmfor Glass Fiber membrane filter whereas at the entrance of UMS recorded 80-161μm and 40.16-161. 29μm respectively. More than 60% of the data sets were exceeded the Malaysian Ambient Air Quality Standard value of 150μm. So it can be summarize that the air quality in the sampling areas were in the unhealthy status. Comparatively, data obtained from this study clarify that PM10 were determined using Polymer Nano Fiber membrane filter trapped slightly higher concentration compared to Glass Fiber membrane filter.
"First mover advantage" or "second mover advantage": corporate profit margin and Outward Foreign Direct Investment——Test based on micro data of Chinese listed companies

With the gradual deepening of reform and opening up, more Chinese enterprises "go out" of foreign direct investment, corporate profit rate has increased steadily, but few people focuses on the causal relationship between the two in-depth discussion. Based on the micro data of OFDI of listed companies, this paper matches the profit rate of enterprises, and tests the interaction between OFDI and profit rate of enterprises through dynamic simultaneous equations model. The results show that the profit rate of listed companies significantly affects the OFDI of enterprises. One of the influence mechanisms is tax effect. At the same time, the current OFDI of enterprises has a significant negative impact on the profit rate, lagging one has a positive correlation between OFDI and profit rate, and its influencing mechanism changes from "experience acquisition stage" to "profit acquisition stage". Further subdivision test shows that both the OFDI mode adopted by enterprises in mergers and acquisitions and private enterprises will affect the choice of profit rate acting on OFDI behavior, while whether the host country is a developed country has no significant effect on the effect of profit rate on OFDI behavior.
Running Title A new prognostic model for ischemic stroke

Background: Efficient assessment of patients after ischemic stroke has important reference value for doctors to choose appropriate treatment and rehabilitation method for patients. Our study aimed to develop a new prognostic model for predicting outcomes three months after ischemic stroke among Chinese Population. Methods: A prospective observational cohort study among ischemic stroke patients presenting to Emergency Department in the Second Affiliated Hospital of Guangzhou Medical University was conducted from May 2012 to June 2013. Demographic data of ischemic stroke patients, assessment of NIHSS and laboratory results were collected. Based on three-month modified Rankin Scale (mRS) ischemic stroke patients were divided into either favorable outcome (mRS: 0-2) or unfavorable outcome groups (mRS: 3-6). The variables closely associated with prognosis of ischemic stroke were selected to develop the new prognostic model consisted of four parameters: NIHSS, age, atrial fibrillation (AF), prealbumin (PA). The prognostic value of the modified prognostic model (NAAP: NIHSS+Age+AF+PA) was then compared with NIHSS alone. Results: A total of 454 patients with suspected stroke were recruited. 186 patients with ischemic stroke were included in the final analysis. There were 105 (56.5%) cases of ischemic stroke with favorable outcome, and 81 (43.5%) cases of ischemic stroke with unfavorable outcome. A new prognostic model, NAAP was developed. The area under curve (AUC) of NAAP was 0.861 (95%CI: 0.803-0.907), whilst the AUC of NIHSS was 0.783 (95%CI: 0.717-0.840), (P=0.0048). Decision curve analysis (DCA) showed that NAAP had a higher net benefit for threshold probabilities of 65% for predictive risk of poor outcomes. Conclusion: The modified prognostic model, NAAP may be a better prognostic tool for predicting 3-month unfavorable outcomes for ischemic stroke than NIHSS alone.
Sensor array for the analysis of the lighting situation in an intelligent industrial hall

In this paper, the possibility of using a multi-channel color sensor to identify artificial light and daylight for use in an intelligently illuminated industrial hall is investigated. First, an overview of intelligent lighting systems is given and the experimental setup is explained. Due to the large amount of data, the processing of large data sets is then highlighted. On the basis of the data collected, it will then be shown that it is possible to distinguish between daylight and artificial light using multi-channel colour sensors.
AN ABSTRACT OF THE THESIS OF Marc A. Kinsley for the degree of Master of Science in Veterinary Science presented on June 4, 2013 Title: Molecular Characterization of Wnt/β-catenin Signaling in Early Equine Osteochondrosis

approved: __________________________________________________________________ Stacy A. Semevolos Abstract: The objective of this study was to elucidate the expression of signaling molecules associated with the Wnt signaling pathway in cartilage of prepubescent foals The objective of this study was to elucidate the expression of signaling molecules associated with the Wnt signaling pathway in cartilage of prepubescent foals and determine their association with chondrocytes located at the osteochondral junction and cartilage canals. Our hypothesis was that increased expression of the components of the Wnt signaling pathway in chondrocytes of the osteochondral junction and cartilage canals would be found in early osteochondrosis (OC) lesions when compared to normal controls. Chondrocytes surrounding cartilage canals and the osteochondral junction were captured using laser capture microdissection from cartilage samples collected from 6 foals with early OC and 8 normal controls. Equine-specific β-catenin, Wnt-4, Wnt-5b, Wnt-11, Dkk-1, Lrp4, Lrp6, Axin1, WIF-1, Sfrp1, Sfrp3, Sfrp5, RARgamma, SC-PEP and 18S mRNA expression levels were evaluated by two-step real-time quantitative PCR. Spatial tissue protein expression of β-catenin, Wnt-11, Wnt 4, and Dkk1 was determined by immunohistochemistry. There was significantly decreased Wnt-11 and increased βcatenin, Wnt-5b, Dkk1, Lrp6, WIF-1, Axin1, and SC-PEP gene expression in early OC chondrocytes along the cartilage canals compared to controls. There was also significantly increased β-catenin and SC-PEP gene expression in early OC chondrocytes along the osteochondral junction compared to normal controls. Wnt 11 showed significantly decreased protein expression in the superficial cartilage layer and Dkk1 showed significantly decreased protein expression in the deep cartilage. Increased gene expression of β-catenin, Wnt 5b, WIF-1, SC-PEP, Axin1, Dkk1, and Lrp6 provides evidence that canonical Wnt signaling is altered in early osteochondrosis of horses and may be associated with disease pathogenesis. ©Copyright by Marc A. Kinsley June 4, 2013 All Rights Reserved Molecular Characterization of Wnt/β-catenin Signaling in Early Equine Osteochondrosis
Dilated LSTM with attention for Classification of Suicide Notes

In this paper we present a dilated LSTM with attention mechanism for document-level classification of suicide notes, last statements and depressed notes. We achieve an accuracy of 87.34% compared to competitive baselines of 80.35% (Logistic Model Tree) and 82.27% (Bi-directional LSTM with Attention). Furthermore, we provide an analysis of both the grammatical and thematic content of suicide notes, last statements and depressed notes. We find that the use of personal pronouns, cognitive processes and references to loved ones are most important. Finally, we show through visualisations of attention weights that the Dilated LSTM with attention is able to identify the same distinguishing features across documents as the linguistic analysis.
Artificial Neural Network Based Target Recognition for Marine Search

The key point of marine search and rescue is to find out and recognize the distress objects. At present, the visual search method is usually adopted to detect the ships in distress, and this method can only be used at good sea condition and visibility. In this paper, a new target detection and recognition system is proposed. The parameters of radar transmitter and echo graphics and the invariant moments of radar images are extracted as the system’s recognition features, and the system’s target classifier is based on Artificial Neural Networks (ANN). The developed recognition classifier has been tested using three kinds of target Images, the target’s features are used as the inputs of trained ANN and the outputs of networks are target classification. Sea experimental results show that the proposed method is well-clustering and with high classified accuracy.
Improving collective interpretation by extended potentiality assimilation for multi-layered neural networks

ABSTRACT The present paper aims to extend the potential learning method to overcome the problem of collective interpretation, which aims to interpret multi-layered neural networks by compressing them into the simplest ones. In the process of compression, positive, negative, and complicated weights have had unfavourable effects for interpretation. To deal with the problems of collective interpretation, the potential learning is extended only to use positive weights. In addition, to obtain more appropriate weights for interpretation, the number of candidate weights for higher potentialities is first increased as much as possible. Then, from among many candidates, more appropriate weights are selected as more important ones. This extended potentiality learning is expected to produce more stable and more simple representations for easy interpretation. The extended method was applied to three datasets, namely, an artificial dataset, a real eye-tracking dataset, and a student evaluation dataset. In all cases, it was observed that the selectivity of connection weights could be increased. Correspondingly, the majority of connection weights became positive, and the collective weights were quite similar to the regression coefficients of the logistic regression analysis. Finally, for the third dataset (student evaluations), the extended method could extract more explicit input-output relations, compared with the logistic regression analysis, while improving generalisation performance.
Zigbee-based Local Army Strategy Network Configurations for Multimedia Military Service

With the rapid evolution of communication technology, it became possible to overcome the spatial and temporal limitations faced by humans to some extent. Furthermore, the quality of personal life was revolutionized with the emergence of the personal communication device commonly known as the smart phone. In terms of defense networks, however, due to restrictions from the military and security perspectives, the use of smart phones has been prohibited and controlled in the army; thus, they are not being used for any defense strategy purposes as yet. Despite the current consideration of smart phones for military communication, due to the difficulties of network configuration and the high cost of the necessary communication devices, the main tools of communication between soldiers are limited to the use of flag, voice or hand signals, which are all very primitive. Although these primitive tools can be very effective in certain cases, they cannot overcome temporal and spatial limitations. Likewise, depending on the level of the communication skills of each individual, communication efficiency can vary significantly. As the term of military service continues to be shortened, however, types of communication of varying efficiency depending on the levels of skills of each individual newly added to the military is not desirable at all. To address this problem, it is essential to prepare an intuitive network configuration that facilitates use by soldiers in a short period of time by easily configuring the strategy network at a low cost while maintaining its security. Therefore, in this article, the author proposes a Zigbee-based local strategic network by using Opnet and performs a simulation accordingly.
Integrating COMPSs and OmpSs Programming Models to support distributed heterogeneous computing environments

Hoy en dia la gran variedad de recursos de computo (GPUs, ASICs, FPGAs) puede llegar a ser abrumador y aun mas las distintas maneras de programarlos. Los programadores que trabajan en entornos heterogeneos tienen que lidiar con mas de un modelo y herramientas para conseguir utilizar todos los recursos. En este proyecto queremos facilitar el uso de entornos distribuidos heterogeneos llevando a cabo la integracion de los modelos de programacion COMPSs y OmpSs. COMP Superscalar (COMPSs) es un modelo de programacion para entornos distribuidos basado en la generacion de tareas y Omp Superscalar (OmpSs) intenta explotar el paralelismo de las aplicaciones dentro de un nodo haciendo uso de todos los recursos presentes. En el proyecto se realiza la integracion COMPSs+OmpSs-2 que permite programar entornos distribuidos heterogeneos de una manera sencilla y se evalua su rendimiento.
Assessment of the Health of the Younger Generation of the Population of the Aral Sea Region

Data were obtained on the somatic health of schoolchildren in Kyzylorda (100 people) and rural schools Syrdariya district (71 people) and Zhalagash district (114 people) located in the central part of the Aral Sea region. The weight, height, lung capacity, blood pressure, and heart rate were determined according to the health scale method. It is shown that only a third of high school students (18% of urban school students and 29% of rural schoolchildren) in the Aral Sea region have a high and above average level of health. More than 46% of urban schoolchildren and 36% of rural students showed an average level of health, the indicators of the remaining 35-36% of high school students corresponded to a low level of health. This state of health shows a high likelihood of developing chronic health disorders associated with functional insufficiency of the cardiovascular system (low levels of Robinson and Rufe indexes), lack of lung capacity (Quality of Life Index), underdevelopment of the muscular system and an increasing tendency to increase body fat components.