Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase I Study of GTI-2040, an Antisense to Ribonucleotide Reductase, in Combination with High-Dose Cytarabine in Patients with Acute Myeloid Leukemia

Purpose: Inhibition of ribonucleotide reductase reduces the availability of the endogenous pool of deoxycytidine and may increase cytarabine (AraC) cytotoxicity. We performed a phase I dose escalation trial of AraC combined with GTI-2040, a 20-mer antisense oligonucleotide shown in preclinical studies to decrease levels of the R2 subunit of ribonucleotide reductase, to determine the maximum tolerated dose in adults with relapsed/refractory acute myeloid leukemia. Experimental Design: Twenty-three adults (ages 18-59 years) were enrolled in this dose escalation phase I trial, receiving high-dose AraC twice daily combined with infusional GTI-2040. An ELISA-based assay measured plasma and intracellular concentrations of GTI-2040. R2 protein changes were evaluated by immunoblotting in pretreatment and post-treatment bone marrow samples. Results: The maximum tolerated dose was 5 mg/kg/d GTI-2040 (days 1-6) and 3 g/m2/dose AraC every 12 hours for 8 doses. Neurotoxicity was dose limiting. Eight patients (35%) achieved complete remission. Mean bone marrow intracellular concentration of GTI-2040 were higher at 120 hours than at 24 hours from the start of GTI-2040 (P = 0.002), suggesting intracellular drug accumulation over time. Reductions in bone marrow levels of R2 protein (>50%) were observed at 24 and 120 hours. Higher baseline R2 protein expression (P = 0.03) and reductions after 24 hours of GTI-2040 (P = 0.04) were associated with complete remission. Conclusions: GTI-2040 and high-dose AraC were coadministered safely with successful reduction of the intended R2 target and encouraging clinical results. The clinical efficacy of this combination will be tested in an upcoming phase II study.
ASSESSMENT OF FOREST PARAMETERS BY MEANS OF LASER SCANNING

This paper deals with forest inventory methods based on laser scanning and satellite remote sensing. It will be demonstrated to what extent forest inventories can benefit from the synergistic use of both sensor types. The forest inventory parameters to be assessed are: tree height, timber volume, tree species, tree age, stand boundary, and basal area. The results presented are derived from the “HIGHSCAN” project (Assessing forest stand attributes by integrated use of high-resolution satellite imagery and laser scanner) which is coordinated by the Helsinki University of Technology and financed by the EU, DG XII. Developments have been carried out in close co-operation with forest management authorities, in particular with private forest owners. In this paper the results derived from the Austrian test sites will be presented.
A survey of image registration techniques

Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors, or from different viewpoints. Virtually all large systems which evaluate images require the registration of images, or a closely related operation, as an intermediate step. Specific examples of systems where image registration is a significant component include matching a target with a real-time image of a scene for target recognition, monitoring global land usage using satellite images, matching stereo images to recover shape for autonomous navigation, and aligning images from different medical modalities for diagnosis. Over the years, a broad range of techniques has been developed for various types of data and problems. These techniques have been independently studied for several different applications, resulting in a large body of research. This paper organizes this material by establishing the relationship between the variations in the images and the type of registration techniques which can most appropriately be applied. Three major types of variations are distinguished. The first type are the variations due to the differences in acquisition which cause the images to be misaligned. To register images, a spatial transformation is found which will remove these variations. The class of transformations which must be searched to find the optimal transformation is determined by knowledge about the variations of this type. The transformation class in turn influences the general technique that should be taken. The second type of variations are those which are also due to differences in acquisition, but cannot be modeled easily such as lighting and atmospheric conditions. This type usually effects intensity values, but they may also be spatial, such as perspective distortions. The third type of variations are differences in the images that are of interest such as object movements, growths, or other scene changes. Variations of the second and third type are not directly removed by registration, but they make registration more difficult since an exact match is no longer possible. In particular, it is critical that variations of the third type are not removed. Knowledge about the characteristics of each type of variation effect the choice of feature space, similarity measure, search space, and search strategy which will make up the final technique. All registration techniques can be viewed as different combinations of these choices. This framework is useful for understanding the merits and relationships between the wide variety of existing techniques and for assisting in the selection of the most suitable technique for a specific problem.
Networks on Chips: From research to products

Research on Networks on Chips (NoCs) has spanned over a decade and its results are now visible in some products. Thus the seminal idea of using networking technology to address the chip-level interconnect problem has been shown to be correct. Moreover, as technology scales down in geometry and chips scale up in complexity, NoCs become the essential element to achieve the desired levels of performance and quality of service while curbing power consumption levels. Design and timing closure can only be achieved by a sophisticated set of tools that address NoC synthesis, optimization and validation.
A Night Time Application for a Real-Time Vehicle Detection Algorithm Based on Computer Vision

Vehicle detection technology is the key technology of intelligent transportation systems, attracting the attention of many researchers. Although much literature has been published concerning daytime vehicle detection, little has been published concerning nighttime vehicle detection. In this study, a nighttime vehicle detection algorithm, consisting of headlight segmentation, headlight pairing and headlight tracking, is proposed. First, the pixels of the headlights are segmented in nighttime traffic images, through the use of the thresholding method. Then the pixels of the headlights are grouped and labeled, to analyze the characteristics of related components, such as area, location and size. Headlights are paired based on their location and size and then tracked via a tracking procedure designed to detect vehicles. Vehicles with only one headlight or those with three or four headlights are also detected. Experimental results show that the proposed algorithm is robust and effective in detecting vehicles in nighttime traffic.
VisUnit : Evaluating Interactive Graph Visualizations Using Crowdsourcing

The process of evaluating visualizations can be time-consuming. Here, we present a design aimed at automating the process of performing quantitative and qualitative evaluations of graph visualizations by leveraging crowdsourcing, and a set of predefined evaluation modules based on a graph task taxonomy. Specifically, we allow designers to quickly set up a user study with representative graph tasks, measurable metrics, and evaluation methods. Our system then uses a thin-client architecture to automatically generate a web accessible user study from our desktop visualization, places the study on Mechanical Turk, and uses a statistical package to automatically process incoming results. To evaluate our system, we performed three concrete evaluation studies, all of which were configured and deployed in less than an hour. We discuss how our system can be used for automatic evaluations of interactive graph visualizations, how it can facilitate evaluation of alternative designs during iterative design processes, and how it could be used to find good default configurations for graph visualizations.
Mass Casualties and Health Care Following the Release of Toxic Chemicals or Radioactive Material—Contribution of Modern Biotechnology

Catastrophic chemical or radiological events can cause thousands of casualties. Such disasters require triage procedures to identify the development of health consequences requiring medical intervention. Our objective is to analyze recent advancements in biotechnology for triage in mass emergency situations. In addition to identifying persons “at risk” of developing health problems, these technologies can aid in securing the unaffected or “worried well”. We also highlight the need for public/private partnerships to engage in some of the underpinning sciences, such as patho-physiological mechanisms of chemical and radiological hazards, and for the necessary investment in the development of rapid assessment tools through identification of biochemical, molecular, and genetic biomarkers to predict health effects. For chemical agents, biomarkers of neurotoxicity, lung damage, and clinical and epidemiological databases are needed to assess acute and chronic effects of exposures. For radiological exposures, development of rapid, sensitive biomarkers using advanced biotechnologies are needed to sort exposed persons at risk of life-threatening effects from persons with long-term risk or no risk. The final implementation of rapid and portable diagnostics tools suitable for emergency care providers to guide triage and medical countermeasures use will need public support, since commercial incentives are lacking.
Revisiting Credit Scoring Models in a Basel 2 Environment

This paper discusses two of the primary motivating influences on the recentdevelopment/revisions of credit scoring models, i.e., the important implications ofBasel 2 s proposed capital requirements on credit assets and the enormous amountsand rates of defaults and bankruptcies in the US in 2001-2002. Two of the more prominent credit scoring techniques, Z-Score and KMV s EDF models, are reviewed. Finally, both models are assessed with respect to default probabilities in general and in particular to the infamous Enron debacle. In order to be effective, these and other credit risk models should be utilized by firms with a sincere credit risk culture.
Explaining recurring maser flares in the ISM through large-scale entangled quantum mechanical states

Simultaneously recurring maser flares from different molecular species in the ISM can be explained with superradiance. We apply Dicke’s theory of superradiance (introduced in 1954) to the 6.7-GHz methanol and 22-GHz water spectral lines, often detected in molecular clouds as signposts for the early stages of the star formation process. We suggest that superradiance, characterized by burst-like features taking place over a wide range of time scales, may provide a natural explanation for the recent observations of periodic and seemingly alternating methanol and water maser flares in G107.298+5.639. Although these observations would be very difficult to explain within the context of maser theory, we show that these flares may result from simultaneously initiated 6.7-GHz methanol and 22-GHz water superradiant bursts operating on different time scales, thus providing a natural mechanism for their observed durations and time ordering. The evidence of superradiance in this source further suggests the existence of entangled quantum mechanical states, involving a very large number of molecules, over distances of up to a few kilometers in the interstellar medium.
T313M polymorphism of the PINK1 gene in Parkinson’s disease

The present study aimed to investigate the association between T313M polymorphism at exon 4 of the PTEN-induced putative kinase 1 (PINK1) gene and Parkinson’s disease (PD) in the Uygur and Han populations of Xinjiang, China. Genetic DNA was extracted from 364 patients with PD from the Uygur and Han populations, as well as 346 normal control patients. Four exons of the PINK1 gene were amplified using quantitative polymerase chain reaction. The exons were then digested for restriction fragment length polymorphism analysis. Gene types and allele frequencies were identified using agarose gel electrophoresis followed by DNA sequencing to analyze the T313M polymorphisms. In the Han population, T313M polymorphism allele frequency was observed to be significantly different between the PD group and the control group (χ2=6.247; P<0.05). Significant differences were observed in in the T313M allele and genotype frequencies between the Uygur and Han populations (χ2=5.475 and χ2=10.950, respectively; P<0.05). Polymorphisms in the PINK1 T313M mutation may be associated with genetic susceptibility to PD.
IALM: an Interaction-enable Application Layer Multicast Protocol for Live Teaching

In this paper, an interaction-enable application layer multicast protocol is introduced for a scalable live teaching system. With a simple and effective interaction-enable algorithm, the proposed protocol abates the additional application layer relay time to enable the video and audio interactive behavior, which takes an important part in a collaborative learning scenario. Besides, the peculiar join request distribution of the learner in live teaching is also considered, and a new client admission algorithm is adopted in the protocol to enhance the judgment efficiency. Based on the above approaches, a real live teaching system is realized.
Retrospective perceptions of the death of a parent during adolescence

This qualitative autobiography explored the educational experiences of three adults who were bereaved in adolescence by the deaths of their fathers. Part of the purpose of this study is to make meaning of the school experiences of the participants after their fathers died. Three stories of bereavement are told to illuminate the needs of the participants at school. These needs are to communicate about their bereavement, to receive acknowledgement of their father's deaths and to feel affirmation from their peers. Data reveal that teachers and school personnel rarely addressed participants' needs. More could have been done to help the participants work through their bereavement while at school. For example, media such as art, literature, and music are explored in this study as means to work creatively with bereavement. These media are called sign systems, and are presented in this study as resources teachers can draw from to raise awareness of the human experience of bereavement. Suggestions for incorporating sign systems in the classroom setting are offered to integrate discussion about bereavement and grief with school curriculum. A Representation of Data Interpretation web is presented to illustrate the stories of the participants, and how three bereaved people work through bereavement together. The findings of this study suggest that bereavement is not a maladie to be euphemized and covered up, rather, open
A Log-quadratic relation between the nuclear black-hole masses and velocity dispersions of galaxies

We demonstrate, we have coloured green the names that we have assumed are surnames. If any of these are wrong, please let us know so we can amend the tagging. that a log-linear relation does not provide an adequate description of the correlation between the masses of super massive black holes (SMBHs, M bh ) and the velocity dispersions of their host spheroid (a). An unknown relation between log M bh and log σ may be expanded to second order to obtain a log-quadratic relation of the form log (M bh ) = a + β log (σ/200km s -1 ) + β 2 [log (σ /200km s -1 )]2. We perform a Bayesian analysis using the local sample described in Tremaine et al., and solve for β, β 2 and a, in addition to the intrinsic scatter (δ). We find unbiased parameter estimates of β = 4.2 ± 0.37, β 2 = 1.6 ± 1.3 and δ = 0.275 ± 0.05. At the 90 per cent level the M bh -σ relation does not follow a uniform power law. Indeed, over the velocity range 70? σ? 380 km s -1 the logarithmic slope d log M bh / d log a of the best-fitting relation varies between 2.7 and 5.1, which should be compared with a power-law estimate of 4.02 ± 0.33. The addition of the 14 galaxies with reverberation SMBH masses and measured velocity dispersions to the local SMBH sample leads to a log-quadratic relation with the same best fit as the local sample. However, the addition of the reverberation masses increases the significance of the log-quadratic contribution, yielding a value of β 2 that is non-zero at the 5σ level. Furthermore, assuming no systematic offset, single epoch virial SMBH masses estimated for active galactic nuclei (AGNs) follow the same log-quadratic M bh -a relation as the local sample, but extend it downward in mass by an order of magnitude. The log-quadratic term in the M bh -σ relation has a significant effect on estimates of the local SMBH mass function at M bh ? 10 9 M ⊙ , leading to densities of SMBHs with M bh ? 10 10 M ⊙ that are several orders of magnitude larger than inferred from a log-linear M bh -σ relation. We also estimate unbiased parameters for the SMBH-bulge mass relation using the sample assembled by Haring and Rix. With a parametrization log(M bh ) = α bulge + β bulge log(M bulge /10 11 M ⊙ ) + β 2,bulge [log(M bulge /10 11 M ⊙ )] 2 , we find β bulge = 1.15 ± 0.18 and β 2,bulge = 0.12 ± 0.14. We determined an intrinsic scatter δ bulge = 0.41 ± 0.07 which is ∼50 per cent larger than the scatter in the M bh-σ relation.
A novel feature selection based on Tibetan grammar for Tibetan text classification

Feature selection is a strategy that aims at making text classifiers more efficient and accurate. In this paper, we proposed a novel feature selection method based on Tibetan grammar for Tibetan classification. Tibetan language express grammatical meaning through the function words and word order, and the function word has large proportions. By analyzing the Tibetan grammar and distribution of part of speech, we proposed feature selection method based on Tibetan notional words. The method analyzed the part of speech of Tibetan text, and then used notional words as text features combined with IG method to realize feature selection. The experimental result shows that this method has improved significantly on classification efficiency and accuracy which compared with the traditional feature selection methods.
Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain

A distance constrained secondary structural model of the ≈10 kb RNA genome of the HIV-1 has been predicted but higher-order structures, involving long distance interactions, are currently unknown. We present the first global RNA secondary structure model for the HIV-1 genome, which integrates both comparative structure analysis and information from experimental data in a full-length prediction without distance constraints. Besides recovering known structural elements, we predict several novel structural elements that are conserved in HIV-1 evolution. Our results also indicate that the structure of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping protein-coding regions the COS is supported by a particular high frequency of compensatory base changes, suggesting functional importance for this element. This new structural element potentially organizes the whole genome into three major domains protruding from a conserved core structure with potential roles in replication and evolution for the virus.
Cell selection and trigger point decision for next generation heterogeneous wireless networking environment: Algorithm & evaluation

It is expected that many heterogeneous wireless networking systems such as 3GPP Long-term Evolution (LTE) system, WiMAX/WiBro system and WLAN system will exist in the next generation wireless communication environment. Under such environment, various communication services will be introduced by integrating heterogeneous wireless networking technologies, especially at radio access networks. In order to provide such integrated communication services, integrated radio resource management and seamless vertical handover across such heterogeneous access networks should be supported. In this paper, to tackle these problems, we propose a Generic Link Layer (GLL) based Common Radio Resource Management (CRRM) architecture and three vertical handover decision algorithms. We propose a vertical handover decision (VHD) algorithm that is a combination of a policy and a multi-criteria decision making (MCDM) approaches designed for achieving effective and seamless handover between heterogeneous radio access networks, especially between the LTE and the WLAN systems. We also propose the Data Mining(C4.5) based VHO decision making algorithm not only to consider various VHO decision factors but also to decide the handover trigger point adaptively to the network traffic situation. In order to verify effectiveness of the proposed CRRM architecture and the three proposed VHO decision making algorithms, extensive simulation studies are performed under various traffic situations. Simulation study shows that the proposed two VHO algorithms outperform the conventional received signal strength (RSS) based VHO algorithm in terms of the data throughput, the handover success rate, and the system service cost.