Miracle-dz/UniFAR-FTUs huggingface dataset:
Domains of type X collagen: alteration of cartilage matrix by fibril association and proteoglycan accumulation

During endochondral bone formation, hypertrophic cartilage is replaced by bone or by a marrow cavity. The matrix of hypertrophic cartilage contains at least one tissue-specific component, type X collagen. Structurally type X collagen contains both a collagenous domain and a COOH-terminal non-collagenous one. However, the function(s) of this molecule have remained largely speculative. To examine the behavior and functions of type X collagen within hypertrophic cartilage, we (Chen, Q., E. Gibney, J. M. Fitch, C. Linsenmayer, T. M. Schmid, and T. F. Linsenmayer. 1990. Proc. Natl. Acad. Sci. USA. 87:8046-8050) recently devised an in vitro system in which exogenous type X collagen rapidly (15 min to several hours) moves into non-hypertrophic cartilage. There the molecule becomes associated with preexisting cartilage collagen fibrils. In the present investigation, we find that the isolated collagenous domain of type X collagen is sufficient for its association with fibrils. Furthermore, when non-hypertrophic cartilage is incubated for a longer time (overnight) with "intact" type X collagen, the molecule is found both in the matrix and inside of the chondrocytes. The properties of the matrix of such type X collagen-infiltrated cartilage become altered. Such changes include: (a) antigenic masking of type X collagen by proteoglycans; (b) loss of the permissiveness for further infiltration by type X collagen; and (c) enhanced accumulation of proteoglycans. Some of these changes are dependent on the presence of the COOH-terminal non-collagenous domain of the molecule. In fact, the isolated collagenous domain of type X collagen appears to exert an opposite effect on proteoglycan accumulation, producing a net decrease in their accumulation, particularly of the light form(s) of proteoglycans. Certain of these matrix alterations are similar to ones that have been observed to occur in vivo. This suggests that within hypertrophic cartilage type X collagen has regulatory as well as structural functions, and that these functions are achieved specifically by its two different domains.
CUBPT: Lock-free bulk insertions to B+ tree on GPU architecture

B+-tree is one of the most widely-used index structures. To improve insertion process, several batch algorithms are proposed, which all use one thread to complete one node insertion and cannot make full use of GPU’s parallel throughput. So, a batch building and insertion method on GPU named CUBPT is proposed in this paper. During the process of bulk building and insertion, CUBPT use one thread to insert one key, which can maximize the performance by GPU. The experimental results show that when build a 10M tree, the overall performance of CUBPT improved 25.03 times compare with four threads PBI. When insert 10M uniform keys into a 10M tree, the overall performance of CUBPT improved 13.38 times compare with four threads PALM; when insert 10M highly skewed keys into tree with same size, the overall performance of CUBPT improved 15.23 times compare with four threads PALM.
The Comparison of the Text Classification Methods to be Used for the Analysis of Motion Data in DLP Architect

Text classification is used for the purpose of preventing the leakage of the data which is highly important within the institution through unallowed ways. The results obtained from the text classification process should be integrated into the DLP architecture immediately. The data flowing through the net requires instant control and the flow of the sensitive data should be prevented. The use of the machinery learning methods is required to perform the text classification which will be integrated into the DLP architecture. The experimental results of the comparison of text classification methods to be used in the interface written on the ICAP protocol have been prepared in the networked architecture developed for the DLP system. Also, the choice of the text classification method to be used in the instant control of the sensitive data has been carried out. The DLP text classification architecture developed helps decide the classification method through the examination of the data in motion. The method to be chosen for the text classification is applied to the ICAP protocol, and the analysis of the sensitive data and confidentiality are provided.
A cluster randomized controlled trial testing the effectiveness of a school-based dental health education program for adolescents.

OBJECTIVES This trial investigated the value of a school-based dental health education program in terms of changes in knowledge, reported behavior, and plaque scores. METHODS A total of 2,678 pupils with a mean age of 12.1 years attending 28 schools participated in a school-based dental health education program. The study used a cluster randomized controlled study design. The health service administrators stipulated that all participants receive the intervention; to meet this requirement, a rolling program of two six-month periods was utilized. During the first six months, half the adolescents received the intervention program, the other half acting as controls. Throughout a further six-month period, all participants received the intervention program. This research design allowed comparisons between participants receiving the program for six and 12 months. At baseline, six, and 12 months, a random subsample of 40 children in each participating school had their plaque scores recorded and a questionnaire was used to record their knowledge of dental health and reported dental behavior. RESULTS The analysis used the subjects clustered within the schools, which were the units of randomization. The intervention program produced statistically significant improvements (P < .001) in knowledge about periodontal disease and the frequency of sugar intake and dental caries in both assessment time periods. The reported frequency of brushing did not change, but the group who had received 12 months of the intervention were more likely (P < .05) to brush for over a minute. At six months the early intervention group had a statistically significant, 13 percent reduction in the mean proportion of sites with plaque compared with the late intervention group (P = .043). This difference was sustained at 12 months (P = .037). CONCLUSION This cluster randomized control trial demonstrated that the intervention program resulted in an improvement in knowledge of dental disease and an increase in the reported duration of brushing. These improvements were accompanied by a significant improvement in oral hygiene and a reported reduction in gingival bleeding.
Surgical and interventional robotics: part III [Tutorial]

Part I of this tutorial described two broad paradigms of interventional assistance: surgical computer-aided design (CAD)/computer-aided manufacturing (CAM) and surgical assistance. Part II focused on the underlying concepts of surgical CAD/CAM, with a particular emphasis on percutaneous procedures. This final installment of our three-part tutorial series discusses surgical assistance. In this section, we introduce the basic concepts of a surgical workstation and briefly review several core robotic technologies used in surgical workstations.
Isolated Squamous Cell Carcinoma of the Orbital Apex

A 43-year-old woman (Case 1), 63-year-old man (Case 2), and a 67-year-old man (Case 3) presented with diplopia (Cases 1, 2, and 3) and upper-eyelid ptosis (Cases 1 and 3). The cases had preceding cranial nerve V1 disturbances ranging from 3 months to 8 years. Each demonstrated complete internal ophthalmoplegia and external ophthalmoplegia. No case had a cutaneous squamous cell carcinoma (SCC) on presentation or by history. Imaging revealed isolated orbital apex masses. Tumor biopsies revealed SCCs of various differentiations. Systemic workup revealed no extraorbital malignancy. All received radiation therapy, and 2 patients underwent adjuvant chemotherapy. One patient is alive since diagnosis (49 months). In Case 2, SCC developed in the contralateral orbit, and the patient died 19 months after diagnosis; and Case 3 died 12 months after diagnosis. These isolated cases of orbital SCC may have arisen from orbital choristomatous squamous epithelium, may represent de novo or metastatic tumors, or may be manifestations of occult perineural spread.
Computer vision methods for large-scale online clustering and quantitative dermatology

OF THE DISSERTATION Computer Vision Methods for Large-scale Online Clustering and Quantitative Dermatology by Siddharth K. Madan Dissertation Director: Dr. Kristin J. Dana In modern computer vision applications where datasets are large and updates with new data may be ongoing, methods of online clustering are extremely important. Online clustering algorithms incrementally cluster the data points, use a fraction of the dataset memory, and update the clustering decisions when new data comes in. In this thesis we adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) to incrementally cluster large datasets of features commonly used in computer vision, e.g., 840K color SIFT descriptors, 1.09 million color patches, 60K outlier corrupted grayscale patches, and 700K grayscale SIFT descriptors. We use the algorithm to cluster datasets consisting of non-convex clusters, e.g., Hopkins 155 3-D motion segmentation dataset. We call the adapted version modified-BIRCH (m-BIRCH). BIRCH was originally developed by the database management community. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in the data summarization. Our implementation of the algorithm provides a useful clustering tool and is made publicly available.
GPU-based real-time beamforming for large arrays of optical wireless acoustic sensors

: Recent optical wireless acoustic sensors have demonstrated the possibility to simultaneously sense massive numbers of audio channels in real time. Although this technology has enabled the deployment of large-scale applications, it raises new challenges from the computational perspective. In this regard, Graphics Processing Units provide signiﬁcant parallel computational power. However, not all the existent algorithms are GPU-implementable in a straightforward way. This paper discusses signal processing schemes and implementation strategies to achieve real-time broadband beamforming using a single GPU card. The experiments introduced here, show our prototype implementation handling over 120 audio channels in real time. The experimental results further highlight the particular advantages of using a video camera-based approach to improve the beamforming performance.
Sensing for Scalable Semantic Localization

Even though location sensors have improved in accuracy and map services o er more and more detailed information including even 3D buildings, it is di cult to infer the semantic location, such as being in a co ee shop, furniture store or clothes shop, from the coordinates. Our thesis addresses this problem and proposes a scalable approach to distinguish between up to 18 di erent store categories. It uses only the camera and the mobile phone's coarse position. Both can be captured in short time on demand, so there is no need to track the user with lots of sensors all the time. For the training we use images that we collect from the Internet. This can be done in relatively short time with the help of appropriate tools. The prediction is a combination of three modules: scene classi cation, object detection and Internet database exploration for the coarse position. With a sophisticated combination technique, it is possible to deduce the best information from all these modules. Our approach can not only capture the semantics of a user's environment with a precision of 88% in case of 5 categories, 72% in case of 10 categories and still over 50% for 18 categories, it is also extremely scalable because it needs neither on-site training, nor additional infrastructure or hardware. An additional important contribution is that we have collected a large set of test cases for our data set called "SnapStore". The test cases come from real locations and are used to evaluate the precision of our approach.
Oprelvekin: a review of its pharmacology and therapeutic potential in chemotherapy-induced thrombocytopenia.

UNLABELLED Oprelvekin is a recombinant human interleukin-11. Its predominant haemopoietic activity is stimulation of megakaryocytopoiesis. Oprelvekin is indicated for the prevention of severe thrombocytopenia and the reduction of platelet transfusion requirements following myelosuppressive chemotherapy in patients with nonmyeloid malignancies at high risk of severe thrombocytopenia. It is the first available pharmacological alternative to platelet transfusions for these patients. Oprelvekin stimulates platelet progenitor cells (megakaryoblasts and colony-forming unit megakaryocytes). The drug also increases megakaryocyte size and ploidy. The recommended adult dosage of subcutaneous oprelvekin is 50 microg/kg once daily, administered until the platelet count is >or=50 000/microl after the expected nadir, but for not more than 21 days per chemotherapy cycle. Three placebo-controlled trials involving patients with cancer (mostly breast cancer) undergoing dose-intensive cancer chemotherapy, with or without autologous bone marrow transplantation (n = 75 to 82), have been conducted. Compared with placebo, oprelvekin 50 microg/kg/day was associated with significantly fewer patients requiring platelet transfusions and a trend towards a lower median number of platelet transfusions. There was also at least a trend towards reduced time to platelet recovery in oprelvekin recipients. The efficacy of oprelvekin is unaffected by previous platelet transfusion requirements and/or chemotherapy. To date the drug has not been shown to ameliorate chemotherapy-induced leucopenia or neutropenia or to have effects on time to neutrophil engraftment or red blood cell transfusion requirements in clinical trials. The most common adverse events with this agent (oedema and dyspnoea) are considered attributable to drug-induced fluid retention and increased plasma volume; these events are usually mild to moderate, reversible on drug discontinuation and dose related. Cardiovascular events including atrial arrhythmias are also considered attributable to increased plasma volume. CONCLUSIONS Evidence suggests that oprelvekin reduces severe thrombocytopenia, accelerates platelet recovery and reduces the need for platelet transfusions in patients with nonmyeloid malignancies receiving chemotherapy regimens associated with severe thrombocytopenia. If further studies confirm these findings, oprelvekin is likely to be a valuable means of allowing patients to receive their full planned chemotherapy course.
Concreteness and Corpora: A Theoretical and Practical Study

An increasing body of empirical evidence suggests that concreteness is a fundamental dimension of semantic representation. By implementing both a vector space model and a Latent Dirichlet Allocation (LDA) Model, we explore the extent to which concreteness is reflected in the distributional patterns in corpora. In one experiment, we show that that vector space models can be tailored to better model semantic domains of particular degrees of concreteness. In a second experiment, we show that the quality of the representations of
A framework for comparing Spatial Data Infrastructures on the basis of web services and metadata management: an Australian-Swiss case study

This article from Research and Theory in Advancing Spatial Data Infrastructure Concepts (ed. Harlan Onsrud; Redlands, CA: ESRI Press, 2007) is made available under a Creative Commons License, Attribution 2.5 (http://creativecommons.org/licenses/by/2.5/legalcode).
Ontology Based Question Answering System

Data and Information requirement is increasing with the Increase in the volumes of data in the repositories such as www etc, now question arises that out of this enormous data how to find the information which is required by the user and should be specific in nature. Information retrieval techniques solves the problem to an extent but they cannot help in a situation where only specific information pertaining to a question is required. Information retrieval engines will retrieve documents containing phrases and paragraphs which may have an answer to user query. This problem is addressed in this research paper which proposes a question answering system to satisfy users specific information need.
Optimal electrode shape and size of a few singly rotated quartz and langasite resonators

Based on Mindlin's early work, we calculate and plot optimal electrode shape and size of Y-cut quartz, At-cut quartz, and Y-cut langasite plate thickness-shear resonators. The electrodes obtained are optimal in that they satisfy Bechmann's number in every direction. The results are useful in the design optimization of these resonators.
Lack of reliability of CA125 response criteria with anti‐VEGF molecularly targeted therapy

CA125 is an accepted indicator of epithelial ovarian cancer (EOC) response and is used to monitor patients treated with cytotoxic chemotherapy. It is uncertain how CA125 is affected by molecularly targeted drugs. In this pilot study, the authors analyzed the utility of CA125 to predict disease behavior in patients who were receiving sorafenib, a Raf‐kinase/VEGFR2 inhibitor, and bevacizumab, an anti‐VEGF monoclonal antibody.
Realization of a Multichannel Chemical and Biological Sensor Using 6x6 Multimode Interference Structures

A new mirroring resonators (MRR) based on 6x6 multimode interference (MMI) couplers for multichannel and highly sensitive chemical and biological sensors is proposed in this paper. The proposed sensor structure has advantages of compactness, high sensitivity compared with the reported sensing structures. By using the transfer matrix method (TMM) and numerical simulations, the designs of the sensor based on silicon nanowires are optimized and demonstrated in detail. Current approaches to the real time analysis of chemical and biological sensing applications utilize systematic approaches such as mass spectrometry for detection. Such systems are expensive, heavy and cannot monolithically integrated in one single chip (1). Electronic sensors use metallic probes which produces electro magnetic noise, which can disturb the electro magnetic field being measured. This can be avoided in the case of using optical sensors. Optical sensors are very attractive due to their advantages of high sensitivity and ultra-wide bandwidth. A large class of optical sensors based on optical fibre and waveguides uses evanescent wave to monitor the presence of the analyte in the environment. Detection can be made by the optical absorption of the analytes, optic spectroscopy or the refractive index change (1). The two former methods can be directly obtained by measuring optical intensity. The third method is to monitor various chemical and biological systems via sensing of the change in refractive index (2). Optical waveguide devices can perform as refractive index sensors particularly when the analyte becomes a physical part of the device, such as waveguide cladding. In this case, the evanescent portion of the guided mode within the cladding will overlap and interact with the analyte. The measurement of the refractive index change of the guided mode of the optical waveguides requires a special structure to convert the refractive index change into detectable signals. A number of refractive index sensors based on optical waveguide structures have been reported, including Bragg grating sensors, directional coupler sensors, Mach- Zehnder interferometer (MZI) sensors, microring resonator sensors and surface plasmon resonance sensors (1-5).
BDI for Intelligent Agents in Computer Games

With the emergence of complex computer games and advanced gaming hardware, possibilities for overcoming some of the deficiencies in traditional game AI are becoming feasible. These deficiencies include repetitive, predictable, and inhuman behaviour are caused by the reliance on simple reactive AI techniques. By using more sophisticated AI and agent techniques, we intend to overcome some of these problem areas. The aim of our research is to create new forms of intelligent characters (agents) that will exhibit human-like intelligence and provide more challenging and entertaining virtual opponents and team mates for computer games. We present here our prototype application that implements a BDI agent system within the 3D computer game Unreal Tournament via GameBots and JavaBots technology.
Actinomycetes for Marine Drug Discovery Isolated from Mangrove Soils and Plants in China

The mangrove ecosystem is a largely unexplored source for actinomycetes with the potential to produce biologically active secondary metabolites. Consequently, we set out to isolate, characterize and screen actinomycetes from soil and plant material collected from eight mangrove sites in China. Over 2,000 actinomycetes were isolated and of these approximately 20%, 5%, and 10% inhibited the growth of Human Colon Tumor 116 cells, Candida albicans and Staphylococcus aureus, respectively, while 3% inhibited protein tyrosine phosphatase 1B (PTP1B), a protein related to diabetes. In addition, nine isolates inhibited aurora kinase A, an anti-cancer related protein, and three inhibited caspase 3, a protein related to neurodegenerative diseases. Representative bioactive isolates were characterized using genotypic and phenotypic procedures and classified to thirteen genera, notably to the genera Micromonospora and Streptomyces. Actinomycetes showing cytotoxic activity were assigned to seven genera whereas only Micromonospora and Streptomyces strains showed anti-PTP1B activity. We conclude that actinomycetes isolated from mangrove habitats are a potentially rich source for the discovery of anti-infection and anti-tumor compounds, and of agents for treating neurodegenerative diseases and diabetes.
THE COMBINED APPROACH FOR ANOMALY DETECTION USING NEUR AL NETWORKS AND CLUSTERING TECHNIQUE S

Nowadays detection of new threats has become a necessity for secured communication to provide absolute data confidentiality, integrity and availability. Designand development of such an intrusion detection system in the communication world, should not only be new, accurate and fast but also effective in a n environment encompassing the surrounding network. In this paper, anew approach is proposed for network anomaly detection by combining neural network and clustering algorithms. We propose modified Self Organizing Map algorithms which initially starts with null network and grows with the original data space as initial weight vector, updating neighbourhood rules and learning rate dynamically in order to overcome the fixed architecture and random weight vector assignmentof simple SOM. New nodes are created using distance threshold parameter and their neighbourhood is identified using connection strength and its learning rule and the weight vector updation iscarried out for neighbourhood nodes. The k-means clustering algorithm is employed for groupingsimilar nodes of Modified SOM into k clusters using similarity measures. Performance of the new approach is evaluated with standard bench mark dataset. The new approach is evaluatedusing performance metrics such asdetection rate and false alarm rate. The result is compared with other individual neural network methods, which shows considerable increase in the detection rate and 2% false alarm rate.