Miracle-dz/UniFAR-FTUs huggingface dataset:
Dna Mutation/Methylation Screening Method for Colon Cancer Screening

Cancer is a result of unregulated cell growth. For all types of cancer currently studied, the transition from a healthy cell to a malignant tumor cell is a step-by-step process which requires mutation in at least several oncogenes and tumor suppressor genes together. Another cancer early event is DNA methylation. Cancer-related DNA methylation focuses on promoter hypermethylation of the certain genes. The DNA mutation and methylation profile can serve as biomarkers for diagnosing early stage of cancer. Colorectal cancer is the third most common cancer type in the United States and has been well studied. The essential mechanism of cancer development is becomeing clear, so there are more approaches to diagnose early stage cancer and improve cancer treatment, which benefits colorectal cancer screening in recent years. The current mutation/methylation detection techniques generally have two major categories which rely on the 1) physical property of double strand DNA or 2) enzyme
Learning Probabilistic Models of the Web

In the World Wide Web, myriads of hyperlinks connect documents and pages to create an unprecedented, highly complex graph structure - the Web graph. This paper presents a novel approach to learning probabilistic models of the Web, which can be used to make reliable predictions about connectivity and information content of Web documents. The proposed method is a probabilistic dimension reduction technique which recasts and unites Latent Semantic Analysis and Kleinberg's Hubs-and-Authori ties algorithm in a statistical setting. This is meant to be a first step towards the development of a statistical foundation for Web-related information technologies. Although this paper does not focus on a particular application, a variety of algorithms operating in the Web/Internet environment can take advantage of the presented techniques, including search engines, Web crawlers, and information agent systems.
Epigrams on Programming.

The phenomena surrounding computers are diverse and yield a surprisingly rich base for launching metaphors at individual and group activities. Conversely, classical human endeavors provide an inexhaustible source of metaphor for those of us who are in labor within computation. Such relationships between society and device are not new, but the incredible growth of the computer's influence (both real and implied) lends this symbiotic dependency a vitality like a gangly youth growing out of his clothes within an endless puberty.
Variation across speech and writing: Methodology

Part I. Background Concepts and Issues: 1. Introduction: textual dimensions and relations 2. Situations and functions 3. Previous linguistic research on speech and writing Part II. Methodology: 4. Methodological overview of the study 5. Statistical analysis Part III. Dimensions and Relations in English: 6. Textual dimensions in speech and writing 7. Textual relations in speech and writing 8. Extending the description: variations within genres 9. Afterword: applying the model Appendices.
Aggregating Multiple Instances in Relational Database Using Semi-Supervised Genetic Algorithm-based Clustering Technique

In solving the classification problem in relational data mining, traditional methods, for example, the C4.5 and its variants, usually require data transformations from datasets stored in multiple tables into a single table. Unfortunately, we may loss some information when we join tables with a high degree of one-to-many association. Therefore, data transformation becomes a tedious trial-and-error work and the classification result is often not very promising especially when the number of tables and the degree of one-to -many association are large. In this paper, we propose a genetic semi-supervised clustering technique as a means of aggregating data in multiple tables for the classification problem in relational database. This algorithm is suitable for classification of datasets with a high degree of one-to-many associations. It can be used in two ways. One is user-controlled clustering, where the user may control the result of clustering by varying the compactness of the spherical cluster. The other is automatic clustering, where a non-overlap clustering strategy is applied. In this paper, we use the latter method to dynamically cluster multiple instances, as a means of aggregating them, and illustrate the effectiveness of this method using the semi-supervised genetic algorithm-based clustering technique.
SZTAKI @ ImageCLEF 2010

Our approach to the ImageCLEF 2010 tasks is based on Histogram of Oriented Gradients descriptors (HOG) and Okapi BM25 based text retrieval. We extracted feature vectors to describe the visual content of an image region or the entire image. We trained a Gaussian Mixture Model (GMM) to cluster the feature vectors extracted from the image regions. To represent each image with only one vector we computed a Bag-of-Words (BOW) model from GMM probabilities of HOG descriptors. We trained linear regression classificators for the Photo Annotation task. To improve our textual ranking in the Wikipedia MM task we successfully expanded the textual query based on the visual ranking.
Personal computing: from P-books to E-books

TE R R Y M IU R A The dream of electronic books has been with us at least since Vannevar Bush published his famous article, “As We May Think,” in which he speculated on a desk-sized machine that would hold one’s personal writing and library [1]. Alan Kay named his prototype of the modern PC the Dynabook, and related research has been done at prestigious centers including Xerox PARC, MIT, Bell Labs, and Brown University. I have speculated about e-books and portable devices earlier (see [6, 7]), but am still reading paper books (p-books) because content is abundant and user interaction is simple and subconscious. The idea of an e-book is appealing— a single device with an entire library of interlinked documents, dictionary lookup, unlimited, sharable annotation, search capability, and so forth. But the technology to date has not been good enough to displace the p-book. Is it now? For a first pass at answering that question, I looked at two new e-book devices, the Rocket Ebook (REB) from NuvoMedia (www.nuvomedia.com) and the Softbook (SB) from Softbook Press (www.softbook.com). Both are PC pads with flash RAM storage and backlit, touch-sensitive monochrome screens. The REB is 5” x 7.5” and weighs 22 ounces; the SB is 8.75” x 8.5” and weighs 2.9 pounds. Both are designed solely for reading and annotating documents and have simple user interfaces. The REB has three buttons: on/off, page forward and page backward, and the SB has four buttons: a neat rocker switch for next/previous page plus menu, top-of-document, and devicecontents buttons. If I were an early gadget adopter or traveled a lot, I would own one of these devices. I prefer them to a standard laptop PC for reading. They balance well, have reasonable battery life, are small and light, turn pages fairly thoughtlessly, boot quickly and never display the Windows “blue
MITK-DI: A new diffusion imaging component for MITK

Diffusion-MRI provides a unique window on brain anatomy and insights into aspects of brain structure in living humans that could not be studied previously. There is a major effort in this rapidly evolving field of research to develop algorithms that provide detailed information on the white matter fibre architecture and disorders in the brain. High angular resolution diffusion imaging (HARDI) provides an extraordinarily high level of detail, including entire manifolds of information at each voxel. The lack of standardized software tools for data I/O, model reconstruction, interactive visualization, feature extraction and statistics impedes development and sustainable evaluation in HARDI research. In this paper, a new toolkit component of the Medical Imaging and Interaction Toolkit (MITK, www.mitk.org), MITK-DI, is presented and its features are summarized at each stage of the pipeline from raw data processing to comprehensive statistics. MITK-DI aims at integrating novel diffusion imaging techniques into the MITK toolkit to provide a comprehensive software framework for performant data processing, analysis and interactive visualization. An examplary application of the framework is shown using phantom and in-vivo datasets from a clinical MR scanner. Visualizations are presented that reveal details for which there would be no direct way to appreciate using conventional display of scalaror RGB-images.
Robust f H Filter Design for Networked Control System with Random Time Delays

Networked control system (NCS) is a completely distributed and networked real-time feedback control system. In NCS, the network-induced delay is inevitable, which is the major cause of the deterioration of system dynamic performance and potential system stability. In this paper, a new robust f H filter is designed for the networked control systems with random time-delays based on linear matrix inequality (LMI). The paper’s principal results show that designing the robust filter can be posed as the f H performance analysis for the augmented model. Both the sufficient condition and corresponding design method are also analyzed for the proposed robust f H filter. The simulation results also demonstrate that the proposed method is effective.
Equi-depth multidimensional histograms

1. Introduction Multi-dimensional queries commonly occur in databases dealing with geographical, image, and VLSI databases. A typical two dimensional query in a geographical database might involve finding all cities within certain latitudinal and longitudinal bounds. Several multi-dimensional index struc­ tures for point data have been proposed in the literature. KDB trees [Robinson81] and and Grid files [Nievergelt84] are among the more popular ones. However, there has been no work in designing multi-dimensional histograms to aid in the optimization process using these multi-dimensional index structures. In order for an optimizer to select an appropriate access path for a multi-dimensional query, fairly accurate selectivity estimates must be available to it. Selectivity esti­ mates are also useful in determining appropriate join methods that follow the selections. In this paper we present an algorithm for generating equi-depth, multi-dimensional histograms. One might expect that the cost of building a D-dimensional histogram would be at least D times the cost of sorting the relation on a single attribute. We show, in our algorithm, that the sorting cost of building a D-dimensional histogram is significantly less than the cost of sorting the relation D times. We present a main memory data structure for storing the histograms and discuss two schemes for estimating the number of tuples that will be "etrieved by a given query. Experimental results are presented that show the efficacy of our histograms. The usefulness of a sampling technique in generating histograms at a very low cost is also explored. 2. Related Work The System R optimizer [Selinger79] used simple statis­ tics, such as the minimum and maximum values in a given column, to estimate selectivity factors. Using such simple statistics will produce good selectivity estimates only if the attribute values are uniformly distributed. Since attribute values can have other distributions, it has become
Developing a Screening Measure for Early Detection of Depressive Symptoms: The Depressive Cognition Scale

Nearly 10% of American adults experience depressive symptoms each year. Negative thought patterns associated with risk for depression can be identified using a psychometrically sound measure, such as the Depressive Cognition Scale (DCS). However, no meaningful cutoff score has been established for the DCS. This study used a receiver operating characteristic (ROC) curve to establish a DCS cutoff score for risk for depression, using the Center for Epidemiological Studies–Depression Scale (CES-D) as the gold standard measure. In a national nondepressed sample of 629 adults, the ROC showed that the DCS accurately discriminated between participants with and without serious depressive thinking in 80% of cases and established an optimum balance of sensitivity (73.9-76.6%) and specificity (69.075.3%) at a score of 7. Although findings indicate that the DCS may overidentify risk for clinical depression, the instrument is useful for screening and assessment, with possible initiation of psychological treatment to prevent clinical depression.
Facial Nerve Neuroma in the Mastoid Segment of the Temporal Bone: A Case Report

Introduction: Facial nerve neuroma is a rare disease that comprises less than 1% of all intrapetrous mass lesions. Diagnosis of the lesions of the tumor is difficult, as these tumors have relationships with other structures of the lateral skull base, such as nerves. In addition, surgical treatment is difficult because the risk of injury after the intervention is high. In this case report, we describe the clinical findings, diagnosis, and treatment of a 55-year-old man with facial nerve neuroma in the mastoid portion, a rare type of neuroma who underwent surgical operation at Khalili Hospital, Shiraz, Iran. Case Presentation: In this report, we describe a rare facial nerve neuroma in the mastoid portion in a 55-year-old man with a history of hypertension (HTN) and diabetes mellitus (DM). The patient also had otalgia related to the periauricular area, otorrhea, and tympanic membrane retraction on the left side. In addition, the patient had facial palsy (Brackmann grade V) and often suffered from headaches. Magnetic resonance imaging (MRI) with contrast, biopsy from the external ear canal region, and tympanometry were carried out. Then, the patient underwent surgical treatment, and the mass was successfully totally removed. The result of the patient’s pathology test was margin free. At a recent follow-up, the patient was still symptom-free (otalgia and headache). Conclusions: In surgery for facial nerve neuroma in the mastoid segment, it is better not to rely on imaging alone; all facial nerves from the geniculate ganglion to the styloid foramen become exposed for tumor removal.
Prolidase activity in serum and pleural fluids in patients with tuberculous pleural effusion

Objectives In this study we aimed to evaluate pleural fluid and serum prolidase(PLD) activities in patients with tuberculous(TB) pleurisy and compared with those in non-tuberculous(non-TB) pleural effusions.Methods PLD activity in pleural fluid-and serum sample collected from 26 patients with tuberculous(TB) pleurisy and 28 patients with non-tuberculous(non-TB) pleural were measured using ELISA method.ResultsProlidase enzyme activities in serum and pleural fluids of TB groupwere significantly higher than those values in non-TB group.Prolidase activities in pleural fluid were significantly higher than those in serum in both groups.There was a significant positive correlation between pleural and serum prolidase activities in TB group and in non-TB group.ConclusionIn conclusion,there is an elevated pleural fluid and serum prolidase enzyme activity in patients with TB pleurisy compared with non-TB pleurisy group.The higher enzyme activities in TB group might reflect increased collagen turnover in those patients.
N-Isopropyl-a-glucoheptonamide

The structure of N-iso­propyl-d-glycero-d-gulo-hepton­amide, C10H21NO7, shows a bent C chain conformation in the glucoheptonic acid moiety. The crystal packing comprises a two-dimensional arrangement of intermolecular hydrogen bonds involving all O atoms. A feature of the crystal packing is a hydrogen-bonded (OH)4 ring, which might be responsible for the observed conformation.
Adhesive capsulitis: current concepts in diagnosis and treatment

Adhesive capsulitis is a condition of the shoulder highlighted by shoulder discomfort with limited shoulder range of motion. This condition generally is seen in women between the ages of 40-60 years. It has an insidious onset of symptoms over several months. This condition has been commonly associated with diabetes mellitus, thyroid disorders, and other autoimmune diseases. Patients describe pain about the deltoid insertion with a mechanical resistance to passive glenohumeral joint motion, particularly with glenohumeral external rotation with the arm at the side against the body. When describing adhesive capsulitis, three stages (the freezing phase, the frozen phase, and the thawing phase) are used to describe disease progression and determine treatment options. Management of adhesive capsulitis begins with nonoperative care consisting of antiinflammatory medications, corticosteroids, and physical therapy with stretching. Patients who fail to improve or worsen after 4 months of conservative care likely will need more invasive intervention. Manipulation under anesthesia may be considered a next option; however, this has fallen out of favor given its associated complications. Finally, operative intervention, consisting of arthroscopic capsular release and lysis of adhesions has become a common operative option with good pain relief and range-of-motion results that can last as long as 7.5 years after the procedure.
What is Programming?

Research into the cognitive aspects of programming originated in the study of professional programmers (either experts or those learning to program). As personal computers become widespread, and most new domestic appliances incorporate microprocessors, many more people are engaging in programming-like activities. Some of these are studied as “end-user” programmers, by analogy to professional programming, but many encounter tasks and contexts completely unlike conventional programming. This paper analyses the generic nature of these new kinds of programming, identifies the cognitive demands that characterize them, and presents one possibility for a cognitive model of programming whose development was driven by these concerns.
X-Rooms A PC-based immersive visualization environment

This paper describes X-Rooms, a PC-based immersive visualization environment with integrated spatial audio, video and graphics. The concept is similar to the original CAVE® [1], but it uses a novel web-based visualization system running on top of a PCcluster with Windows XP installed. Compared to other common installations based on expensive high-end unix graphics systems, costs are reduced by up to one magnitude (depending on the installation setup) using of the shelf PC and projector equipment. Using the developed external API X-Rooms systems can be deployed in the same application domain as conventional CAVE systems; in addition several new areas are open for less expensive systems. Processing VRML the X-Rooms system is a high end visualization platform for interaction with online 3D web content. Furthermore, the X-Rooms content can be driven by the web.
Building probabilistic networks: Where do the numbers come from? - a guide to the literature

Probabilistic networks are now fairly well established as practical representations of knowl-edge for reasoning under uncertainty, as demonstrated by an increasing number of success-ful applications in such domains as (medical) diagnosis and prognosis, planning, vision, information retrieval, and natural language processing. A probabilistic network (also referred to as a belief network. Bayesian network, or, somewhat imprecisely, causal network) Consists of a graphical structure, encoding a domain's variables and the qualitative rela-tionships between them, and a quantitative part, encoding probabilities over the variables [Pearl, 1988].
Acoustic and optical properties of a fast-spinning dielectric nanoparticle

Nanoparticles levitated in vacuum can be set to spin at ultimate frequencies, limited only by the tensile strength of the material. At such high frequencies, drastic changes to the dynamics of solid-state quantum excitations are to be expected. Here, we theoretically describe the interaction between acoustic phonons and the rotation of a nanoparticle around its own axis, and model how the acoustic and optical properties of the nanoparticle change when it rotates at a fixed frequency. As an example, we analytically predict the scaling of the shape, the acoustic eigenmode spectrum, the permittivity, and the polarizability of a spinning dielectric nanosphere. We find that the changes to these properties at frequencies of a few gigahertz achieved in current experiments should be measurable with presents technology. Our work aims at exploring solid-state quantum excitations in mesoscopic matter under extreme rotation, a regime that is now becoming accessible with the advent of precision control over highly isolated levitated nanoparticles.
Cost Volume Pyramid Based Depth Inference for Multi-View Stereo

We propose a cost volume-based neural network for depth inference from multi-view images. We demonstrate that building a cost volume pyramid in a coarse-to-fine manner instead of constructing a cost volume at a fixed resolution leads to a compact, lightweight network and allows us inferring high resolution depth maps to achieve better reconstruction results. To this end, we first build a cost volume based on uniform sampling of fronto-parallel planes across the entire depth range at the coarsest resolution of an image. Then, given current depth estimate, we construct new cost volumes iteratively on the pixelwise depth residual to perform depth map refinement. While sharing similar insight with Point-MVSNet as predicting and refining depth iteratively, we show that working on cost volume pyramid can lead to a more compact, yet efficient network structure compared with the Point-MVSNet on 3D points. We further provide detailed analyses of the relation between (residual) depth sampling and image resolution, which serves as a principle for building compact cost volume pyramid. Experimental results on benchmark datasets show that our model can perform 6x faster and has similar performance as state-of-the-art methods. Code is available at https://github.com/JiayuYANG/CVP-MVSNet
Stone Duality for Relations

We show how Stone duality can be extended from maps to relations. This is achieved by working order enriched and defining a relation from A to B as both an order-preserving function from the opposite of A times B to the 2-element chain and as a subobject of A times B. We show that dual adjunctions and equivalences between regular categories, taken in a suitably order enriched sense, extend to (framed bi)categories of relations.
Optomechanical detection of light with orbital angular momentum.

We present the design of an optomechanical device that allows sensitive transduction of the orbital angular momentum of light. An optically induced twist imparted on the device is detected using a photonic crystal cavity optomechanical system. This device allows the measurement of the orbital angular momentum of light when photons are absorbed by the mechanical element or the detection of the presence of photons when they are scattered into new orbital angular momentum states by a sub-wavelength grating patterned on the device. Such a system allows the detection of optical pulses with an l = 1 orbital angular momentum field that have an average photon number of 3.9 × 103 at a 5 MHz repetition rate, assuming that detector noise is not limiting measurement sensitivity. This scheme can be extended to higher order orbital angular momentum states.