Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrieval feedback in MEDLINE.

OBJECTIVE To investigate a new approach for query expansion based on retrieval feedback. The first objective in this study was to examine alternative query-expansion methods within the same retrieval-feedback framework. The three alternatives proposed are: expansion on the MeSH query field alone, expansion on the free-text field alone, and expansion on both the MeSH and the free-text fields. The second objective was to gain further understanding of retrieval feedback by examining possible dependencies on relevant documents during the feedback cycle. DESIGN Comparative study of retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a MEDLINE test collection of 75 queries and 2,334 MEDLINE citations. MEASUREMENTS Retrieval effectivenesses of the original unexpanded and the alternative expanded queries were compared using 11-point-average precision scores (11-AvgP). These are averages of precision scores obtained at 11 standard recall points. RESULTS All three expansion strategies significantly improved the original queries in terms of retrieval effectiveness. Expansion on MeSH alone was equivalent to expansion on both MeSH and the free-text fields. Expansion on the free-text field alone improved the queries significantly less than did the other two strategies. The second part of the study indicated that retrieval-feedback-based expansion yields significant performance improvements independent of the availability of relevant documents for feedback information. CONCLUSIONS Retrieval feedback offers a robust procedure for query expansion that is most effective for MEDLINE when applied to the MeSH field.
Ontology Description using OWL to Support Semantic Web Applications

The World Wide Web (WWW) serves the human with vast amount of data and information.The usage pattern or user base has multiplied many folds since its origin. Despite the increasing importance gained by the WWW, to serve the human, it lacks the feature to serve meaningful information to machine this means that limited support for utilization of data and information is achieved. Thus the web needs to be made Semantic wherein different applications, agents, Web services and the web sites can exchange information to their full potential. This calls for representing the knowledge residing on WWW in a uniform manner understandable by both man and machine. Thus some taxonomy is needed to make representations of the web contents which can be machine readable and usable . This paper proposes to relate the need for Ontology and relate it to Web ontology language (OWL) and identify its position in making the Semantic Web. It is also felt that ontological support is needed for the semantic web in order to make the information ready for machine consumption. The ontological structure using the Web Ontology Language (OWL) which is used for modeling ontologies of context and for supporting Context reasoning is explored in this paper.The Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content
Identifying a Medical Department based on Unstructured Data - A Big Data Application in Healthcare

Health is an individual’s most precious asset and healthcare is one of the vehicles for preserving it. The Indian government’s spend on healthcare system is relatively low (1.2% of GDP). Consequently, Secondary and Tertiary government healthcare centers in India (that are presumed to be of above average ratings) are always crowded. In Tertiary healthcare centers, like AIIMS, patients are often unable to articulate correctly their problems to the healthcare center’s Reception staff for these patients to be directed to the correct healthcare department. In this paper, we propose a system based on Big Data and Machine Learning to direct the patient to the most relevant department . We have implemented and tested parts of this system wherein a patient enters his symptoms and/or provisional diagnosis; the system suggests a department based on this user input. Our system suggests the correct department 68.05% of the time. Our system presently makes its suggestions using gradient boosting algorithm that has been trained using two information repositoriessymptoms and disease data, functional description of each medical department. It is our informed assumption that, once we have incorporated medicine information and diagnostics imaging data to train the system and the complete medical history of the patient, performance of the system will improve significantly.
Generalized feedback detection for spatial multiplexing multi-antenna systems

We present a unified detection framework for spatial multiplexing multiple-input multiple-output (MIMO) systems by generalizing Heller's classical feedback decoding algorithm for convolutional codes. The resulting generalized feedback detector (GFD) is characterized by three parameters: window size, step size and branch factor. Many existing MIMO detectors are turned out to be special cases of the GFD. Moreover, different parameter choices can provide various performance-complexity tradeoffs. The connection between MIMO detectors and tree search algorithms is also established. To reduce redundant computations in the GFD, a shared computation technique is proposed by using a tree data structure. Using a union bound based analysis of the symbol error rates, the diversity order and signal-to-noise ratio (SNR) gain are derived analytically as functions of the three parameters; for example, the diversity order of the GFD varies between 1 and N. The complexity of the GFD varies between those of the maximum-likelihood (ML) detector and the zero-forcing decision feedback detector (ZF-DFD). Extensive computer simulation results are also provided.
Hubble Space Telescope imaging of the progenitor sites of six nearby core‐collapse supernovae

The search for the progenitors of six core-collapse supernovae (CCSNe) in archival Hubble Space Telescope (HST) WFPC2 pre-explosion imaging is presented. These SNe are 1999an, 1999br, 1999ev, 2000ds, 2000ew and 2001B. Post-explosion imaging of the SNe, with the HST ACS/WFC, has been utilized with the technique of differential astrometry to identify the progenitor locations on the pre-explosion imaging. SNe 1999br, 1999ev, 2000ew and 2001B are recovered in late-time imaging, and estimates of the progenitor locations on the pre-explosion imaging, with subpixel accuracy, have been made. Only the progenitor of the Type II-P SN 1999ev has been recovered, on pre-explosion F555W imaging, at a 4. 8σ significance level. Assuming a red supergiant progenitor, the pre-explosion observation is consistent with M ZAMS = 15-18 M ○. The progenitors of the other five SNe were below the 3σ detection threshold of the pre-explosion observations. The detection thresholds were translated to mass limits for the progenitors by comparison with stellar evolution models. Pre-explosion observations of the peculiarly faint SN 1999br limit the mass of a red supergiant progenitor to M ZAMS < 12 M ○. Analysis has been extended, from previous studies, to include possible detections of high-T eff , high-mass stars by conducting synthetic photometry of model Wolf-Rayet star spectra. The mass limits for the Type II-P SNe 1999an and 1999br are consistent with previously determined mass limits for this type of SN. The detection limits for the progenitors of the Type Ibc SNe (2000ds, 2000ew and 2001B) do not permit differentiation between high-mass Wolf-Rayet progenitors or low-mass progenitors in binaries.
Communication-Efficient Tracking of Distributed Cumulative Triggers

In recent work, we proposed D-Trigger, a framework for tracking a global condition over a large network that allows us to detect anomalies while only collecting a very limited amount of data from distributed monitors. In this paper, we expand our previous work by designing a new class of queries (conditions) that can be tracked for anomaly violations. We show how security violations can be detected over a time window of any size. This is important because security operators do not know in advance the window of time in which measurements should be made to detect anomalies. We also present an algorithm that determines how each machine should filter its time series measurements before back-hauling them to a central operations center. Our filters are computed analytically such that upper bounds on false positive and missed detection rates are guaranteed. In our evaluation, we show that botnet detection can be carried out successfully over a distributed set of machines, while simultaneously filtering out 80 to 90% of the measurement data.
Separating objects and clutter in indoor scenes

Objects' spatial layout estimation and clutter identification are two important tasks to understand indoor scenes. We propose to solve both of these problems in a joint framework using RGBD images of indoor scenes. In contrast to recent approaches which focus on either one of these two problems, we perform `fine grained structure categorization' by predicting all the major objects and simultaneously labeling the cluttered regions. A conditional random field model is proposed to incorporate a rich set of local appearance, geometric features and interactions between the scene elements. We take a structural learning approach with a loss of 3D localisation to estimate the model parameters from a large annotated RGBD dataset, and a mixed integer linear programming formulation for inference. We demonstrate that our approach is able to detect cuboids and estimate cluttered regions across many different object and scene categories in the presence of occlusion, illumination and appearance variations.
Immunogenicity Assessment of Lipegfilgrastim in Patients with Breast Cancer Receiving Chemotherapy

Lipegfilgrastim is a long-acting, once-per-cycle, glycopegylated recombinant granulocyte colony-stimulating factor (G-CSF) used to prevent neutropenia in patients receiving myelosuppressive chemotherapy. This integrated analysis examined the immunogenicity of lipegfilgrastim and its potential clinical impact in two double-blind randomized studies (phases II and III) of patients with breast cancer receiving chemotherapy. Serum samples were analyzed using sequential assays for screening, confirmation, antibody titer, and characterization of antidrug antibodies (ADA). Neutropenia-related efficacy measures were reviewed for each ADA-positive patient. Among 255 patients receiving lipegfilgrastim (154 in phase II, 101 in phase III) and 155 patients receiving pegfilgrastim (54 in phase II, 101 in phase III), the incidence of treatment-emergent ADA was low and similar between the lipegfilgrastim (phase II: 1.3%; phase III: 1.0%) and pegfilgrastim (phase II: 1.9%; phase III: 1.0%) arms. None of the treatment-emergent ADA-positive samples exhibited neutralizing activity against lipegfilgrastim, pegfilgrastim, or glycosylated G-CSF in a cell-based neutralizing antibody assay. No changes were observed in neutropenia-related efficacy measures among ADA-positive patients, and no treatment-related hypersensitivity or anaphylaxis occurred. These results indicate that there is no apparent impact of ADA on lipegfilgrastim efficacy and safety.
Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors

BACKGROUND: Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. OBJECTIVE: In this study, we developed a finger language recognition algorithm based on an ensemble artificial neural network (E-ANN) using an armband system with 8-channel electromyography (EMG) sensors. METHODS: The developed algorithm was composed of signal acquisition, filtering, segmentation, feature extraction and an E-ANN based classifier that was evaluated with the Korean finger language (14 consonants, 17 vowels and 7 numbers) in 17 subjects. E-ANN was categorized according to the number of classifiers (1 to 10) and size of training data (50 to 1500). The accuracy of the E-ANN-based classifier was obtained by 5-fold cross validation and compared with an artificial neural network (ANN)-based classifier. RESULTS AND CONCLUSIONS: As the number of classifiers (1 to 8) and size of training data (50 to 300) increased, the average accuracy of the E-ANN-based classifier increased and the standard deviation decreased. The optimal E-ANN was composed with eight classifiers and 300 size of training data, and the accuracy of the E-ANN was significantly higher than that of the general ANN.
Acceleration of Visual System Development by Environmental Enrichment

Thus far, the developmental plasticity of the visual system has been studied by altering or reducing visual experience. Here, we investigated whether a complex sensory-motor stimulation, provided by rearing animals in an enriched environment, affects visual system development. We found that raising mice in this condition causes an earlier eye opening, a precocious development of visual acuity, and an accelerated decline of white matter-induced long-term potentiation. These effects are accompanied by a precocious cAMP response element-mediated gene expression and a significant increase of BDNF protein and GAD65/67 expression in enriched pups. In addition, we showed that enriched pups experienced higher levels of licking behavior provided by adult females. Thus, rearing mice from birth in an enriched environment leads to a conspicuous acceleration of visual system development as ascertained at behavioral, electrophysiological, and molecular level.
The impact of nutritional status and appetite on the hospital length of stay and postoperative complications in elderly patients with severe aortic stenosis before aortic valve replacement

Introduction Severe aortic stenosis (AS) is associated with the reduction of physical activity and muscle mass and may be associated with decreased appetite. Aim To assess the nutritional status and the impact of nutritional status and appetite on the hospital length of stay and postoperative complications in elderly patients with severe AS before aortic valve replacement. Material and methods Ninety-nine patients (55 male, 44 female; 74.3 ±5.2 years old) with severe AS and an indication for aortic valve replacement (AVR) were included. The nutritional status was assessed by different questionnaires (7-point Subjective Global Assessment Score – 7-SGA, full-Mini Nutritional Assessment – full-MNA) and anthropometric measurements (body mass index (BMI) kg/m2). Body composition was estimated using multi-frequency bioelectrical impedance analysis. Appetite was assessed by the Simplified Nutrition Assessment Questionnaire (SNAQ). Results The average BMI of patients was 28.8 ±5.8 kg/m2. Results of the 7-SGA and f-MNA questionnaires revealed that 39 patients (39.4%) were at risk of malnutrition. The mean SNAQ score was 15.8 ±1.8. The average length of hospital stay was 10 ±5.8 days. There was a positive correlation of LOS with age (r = 0.26, p = 0.03) and a negative correlation with fat mass (kg) (r = –0.28, p = 0.04) and BMI (r = –0.22, p = 0.03). Postoperative complications were observed in 37 patients (37.4%). Patients who developed complications were older and had poorer nutritional status according to the results of the 7-SGA. Conclusions Despite many patients undergoing AVR being overweight and obese, a considerable proportion displayed clinical signs of malnutrition. The results suggest that an assessment of nutritional status and appetite in this group of patients should be conducted regularly and that the 7-SGA scale could represent a reliable tool to assess malnutrition.
Design of User Interface for Shot Boundary Detection using Classical Methods

: Video summarization refers to creating a summary of a digital video. With the advent of digital multimedia, a lot of digital content such as movies, news, television shows and sports is widely available. Also, due to the advances in digital content distribution (DTH satellite reception) and digital video recorders, this digital content can be easily recorded. However, the user may not have sufficient time to watch the entire video (Ex. User may want to watch just the highlights of a game) or the whole of video content may not be of interest to the user(Ex. Golf game video). In such cases, the user may just want to view the summary of the video instead of watching the whole video. Thus, the summary should be such that it should convey as much information about the occurrence of various incidents in the video. Also, the method should be very general so that it can work with the videos of a variety of genre. Current research topics on video includes video abstraction or summarization, video classification, video annotation, content based video retrieval. In nearly all these application one needs to identify shots in video which will correctly and briefly indicate the contents of video. This paper compares some of the popular shot boundary detection techniques; discuses the merits and demerits of each of the techniques and some experiments.
Register organization for enhanced on-chip parallelism

Large register file with multiple ports is a critical component of a high-performance processor. A large number of registers are necessary for processing a larger number of in-flight instructions to exploit higher instruction level parallelism (ILP). Multiple ports for a register file are necessary to support execution of multiple instructions each cycle. These necessities lead to a larger register access time. However, register access time has to be minimal to enable design of high frequency processors. Analysis of lifetime of a logical to physical register mapping reveals that there are long latencies between the times a physical register is allocated, consumed, and released. We propose a dual bank register file organization that exploits such long latencies, resulting in a large bandwidth with a reduced register access time. Implementation of one flavor of the proposed register file organization, as compared to a conventional monolithic register file, in an 8-wide out-of-order issue superscalar processor enhanced instructions per cycle (IPC) throughput up to 6% for Spec2000 applications while inducing register access time up to 22%. Another flavor of the register file organization, with a similar access time as the conventional monolithic register file, enhanced the IPC up to 15%. Thus a trade-off between register access time and ILP exploitation is shown.
A multimedia-driven ambient edutainment system for the young children

Recently, there has been a tremendous demand for developing tools to support education and entertainment in a seamless manner. Many existing works in this domain have focused on developing systems that either require too much interaction or are not suitable for young children who are at their very early stage of learning. It is also very challenging to develop an edutainment environment that does not require special technical skills, yet provides useful functionalities. In this paper, we address this issue and present the design and development of an ambient edutainment system for the very young children. Based on communication and multimedia technologies, "it" provides educative and entertaining capabilities for children between the age of 1 and 4. One of the important features it presents is the transformation of narrative activities into visual representations. Children, supervised or unsupervised, can have both the capability of improving their cognitive skills and learning about new objects and entities through the use of visual presentations provided by the proposed system.
Empowering Online Advertisements by Empowering Viewers with the Right to Choose

ABSTRACT In 2010, YouTube introduced TrueView in-stream advertising—online video advertisements that allowed the user to skip directly to the desired video content after five seconds of viewing. Google sought to compare these “skippable” in-stream advertisements to the conventional (non-skippable) in-stream video advertising formats, using a new advertising effectiveness metric based on the propensity to search for terms related to advertising content. Google's findings indicated that skippable video advertisements may be as effective on a per-impression basis as traditional video advertisements. In addition, data from randomized experiments showed a strong implied viewer preference for the skippable advertisements. Taken together, these results suggest that formats like TrueView in-stream advertisements can improve the viewing experience for users without sacrificing advertising value for advertisers or content owners.
Flavin-Dependent Redox Transfers by the Two-Component Diketocamphane Monooxygenases of Camphor-Grown Pseudomonas putida NCIMB 10007

The progressive titres of key monooxygenases and their requisite native donors of reducing power were used to assess the relative contribution of various camphor plasmid (CAM plasmid)- and chromosome-coded activities to biodegradation of (rac)-camphor at successive stages throughout growth of Pseudomonas putida NCIMB 10007 on the bicylic monoterpenoid. A number of different flavin reductases (FRs) have the potential to supply reduced flavin mononucleotide to both 2,5- and 3,6-diketocamphane monooxygenase, the key isoenzymic two-component monooxygenases that delineate respectively the (+)- and (−)-camphor branches of the convergent degradation pathway. Two different constitutive chromosome-coded ferric reductases able to act as FRs can serve such as role throughout all stages of camphor-dependent growth, whereas Fred, a chromosome-coded inducible FR can only play a potentially significant role in the relatively late stages. Putidaredoxin reductase, an inducible CAM plasmid-coded flavoprotein that serves an established role as a redox intermediate for plasmid-coded cytochrome P450 monooxygenase also has the potential to serve as an important FR for both diketocamphane monooxygenases (DKCMOs) throughout most stages of camphor-dependent growth.
Performance analysis of AODV and AOMDV over SMAC and IEEE 802.15.4 in Wireless Multimedia Sensor Network

Wireless Multimedia Sensor Networks (WMSNs) have recently gained a great attention of the research community as potential solutions for wide range of applications. However, they are subject to strict constraints due to their limited energy, limited processing capacities in contrast to the huge video data rate to be transmitted. To tackle with this challenge, we investigate in this paper, various protocols dedicated to the WMSNs in each layer aiming to reduce the amount of video data using powerful video encoder or/and reduce the energy consumption by increasing the life cycle of each node and consequently the life cycle of the whole network. Specifically, we consider the protocols of the application, network, and MAC layers. We have used the NS-2 framework, in which we have added the H264 encoder and decoder as application layer protocol. We have used the IEEE 802.15. 4 and the SMAC protocols for the MAC layer, and the AODV and the AOMDV for the network layer. The obtained results are evaluated by the dead nodes number, the energy consumption and the Peak Signal to Noise Ratio (PSNR) for the video decoding quality.