Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Kit Formulation for Preparation of 99 mTc-HYNIC-TOC : Results of Preliminary Clinical Evaluation in Imaging Patients with Neuroendocrine Tumors

Tc-HYNIC-TOC is a cost-effective and logistically viable agent for scintigraphy of neuroendocrine tumors overexpressing somatostatin receptors as compared with [In-DTPA-D-Phe] Octreotide (Octreoscan ). Several studies have been reported, wherein the efficacy of this agent is demonstrated. In the present article, the authors report the preparation of a single-vial HYNIC-TOC kit suitable for the preparation of 4–5 patient doses (15 mCi/patient) of Tc-HYNIC-TOC. The kits were tested for sterility and bacterial endotoxins to assure safety of the product. A significant modification in this kit is the inclusion of buffer in the kit itself, unlike in commercially available kits where the buffer solution has to be added during preparation. Tc-HYNIC-TOC was prepared by adding 20–80 mCi (740–2960 MBq) of freshly eluted NaTcO4 in 1–3 mL of sterile saline directly into the kit vial and heating the vial in a water bath at 100 C for 20 minutes. The labeling yield and radiochemical purity of Tc-HYNIC-TOC, prepared using the lyophilized cold kit, were consistently > 90%. The kits were evaluated over a period of 9 months and found to be stable when stored at 20 C. Limited clinical studies performed with the Tc-HYNIC-TOC, formulated using the kit, showed adequate sensitivity and specificity for the detection of gasteroenteropancreatic neuroendocrine tumors.
Accurate and Efficient Dynamics for Variable-Length Continuum Arms: A Center of Gravity Approach

Abstract To achieve their full potential, soft and compliant continuum robots must move faster and more accurately than they can today. To facilitate this, accurate and computationally efficient dynamic models are essential. While the integral Lagrangian approach can produce accurate models, it is complex and computationally intensive. In this article we propose a new dynamic model based on numerically stable modal kinematics that is both accurate and computationally efficient. The proposed model is a lumped parameter model, but one that is more accurate than prior lumped parameter models because mass locations and quantities are derived from a detailed description of the total energy in a continuum arm with continuously distributed mass. We experimentally validated the model using a pneumatic muscle-actuated continuum arm, and the proposed model successfully simulates the transient and steady-state dynamics of the prototype arm. Further, the model is also compared to the integral Lagrangian and a lumped .
Maximum Likelihood Estimation of Monocular Optical Flow Field for Mobile Robot Ego-Motion

This paper presents an optimized scheme of monocular ego-motion estimation to provide location and pose information for mobile robots with one fixed camera. First, a multi-scale hyper-complex wavelet phase-derived optical flow is applied to estimate micro motion of image blocks. Optical flow computation overcomes the difficulties of unreliable feature selection and feature matching of outdoor scenes; at the same time, the multi-scale strategy overcomes the problem of road surface self-similarity and local occlusions. Secondly, a support probability of flow vector is defined to evaluate the validity of the candidate image motions, and a Maximum Likelihood Estimation (MLE) optical flow model is constructed based not only on image motion residuals but also their distribution of inliers and outliers, together with their support probabilities, to evaluate a given transform. This yields an optimized estimation of inlier parts of optical flow. Thirdly, a sampling and consensus strategy is designed to estimate the ego-motion parameters. Our model and algorithms are tested on real datasets collected from an intelligent vehicle. The experimental results demonstrate the estimated ego-motion parameters closely follow the GPS/INS ground truth in complex outdoor road scenarios.
Optimizations to Earley Deduction for DATALOG Programs 1

The optimizations described below are designed to improve performance of the algorithm when there are large numbers of clauses with identical schemata. While it may often be the case that a DATALOG program has large numbers of unit clauses with the same schema, the real saving arises because many clauses with the same schema are derived during a typical deduction. The first optimization is a data structure that saves space when this condition is met. We then look at ways to do the subsumption checking and the reduction and instantiation steps quickly using this data representation.
Mast cell curve-response in partial Achilles tendon rupture after 830 nm phototherapy.

OBJECTIVE The aim of this study was to quantify mast cells at different time intervals after partial Achilles tendon rupture in rats treated with low-level laser therapy (LLLT). BACKGROUND DATA There is a high incidence of lesions and ruptures in the Achilles tendon that can take weeks and even months to heal completely. As the mast cells help in the healing repair phase, and LLLT has favorable effects on this tissue repair process, study of this modality on the quantity of mastocytes in the ruptured tendon is relevant. METHODS Sixty Wistar rats were subjected to partial Achilles' tendon rupture by direct trauma, randomized into 10 groups, and then divided into the group treated with 80 mW aluminum gallium arsenide infrared laser diode, continuous wave, 2.8 W/cm(2) power density, 40 J/cm(2) energy density, and 1.12 J total energy, and the simulation group. Both the groups were subdivided according to the histological assessment period of the sample, either 6 h, 12 h, 24 h, 2 days, or 3 days after the rupture, to quantify the mastocytes in the Achilles' tendon. RESULTS The group subjected to LLLT presented a greater quantity of mastocytes in the periods of 6 h, 12 h, 24 h, 2 days, and 3 days after rupture, compared with the simulation groups, but differences were detected between the sample assessment periods only in the simulation group. CONCLUSIONS LLLT was shown to increase the quantity of mastocytes in the assessment periods compared with the simulation groups.
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Dalhousie University, Halifax, Nova Scotia Correspondence: Mr Joshua Gillis, c/o Dr Jason Williams, Dalhousie University, Division of Plastic Surgery, Suite 4447, Halifax Infirmary, 1796 Summer Street Halifax, Nova Scotia B3H 3A7.Telephone 902-473-6315, fax 902-473-6296, e-mail jgillis@dal.ca The thumb carpometacarpal (CMC) joint, a biconcave-convex saddle joint, consists of the articulation between the first metacarpal of the thumb and the trapezium carpal bone. Other significant articulations of the trapezial bone are the scaphoid and trapezoid carpal bones and the second metacarpal bone. Because the CMC joint lacks bony confimement, there are various ligaments that play a role in stabilizing it; however, the most important is the anterior oblique (also known as ‘beak’), ligament. One of the main contributors to osteoarthritis (OA) of the CMC joint is laxity of this ligament, which leads to increased stress loads on the CMC joint, causing cartilage loss, bony impingement and pain. The treatment of CMC OA is aimed at relieving this pain and restoring joint stability (1,2). The arthritic CMC joint cartilage loses glycosaminoglycan from the extracellular matrix, which causes progression of the disease (1). The structure of the CMC joint enables three different planes of motion: adductionabduction, flexion-extension and axial rotation. This property of the joint has contributed to the fact that CMC OA is the second most common degenerative joint disease of the hand. It typically affects postmenopausal women in their fifth to sixth decade of life, where it has been estimated that between 17% and 33% of these women have evidence of CMC OA, compared with 5% to 11% of men of similar age (1,3). This is possibly due to a hormonal predisposition for OA in women (4).
DLLs for Beginners

Introduction The objective of this article is to introduce the concepts of the Dynamic Link Library (DLL) and the mechanism of writing a DLL for Microsoft® Windows® applications. This discussion is limited to 32-bit applications using Microsoft Visual C++® version 4.0 or later and versions 2.x. Appendix A contains information about 16-bit DLL implementation and porting to 32-bit DLLs. Most references used in this article are available in the Microsoft Developer Network Library (MSDN Library). The articles cited in the text that are followed by a "Q" number can be found either in the MSDN Library or in the Knowledge Base at http://www.microsoft. com/kb/default.asp.
Accuracy of emergency severity index of triage in Imam Hossein hospital - Tehran, Iran (2011)

Results: The calculated λ for the degree of agreement of triage between nurse and clinician was 81% (95% CI: 0.79-0.83). The sensivity of triage for step I, II, III, IV and V were 100%, 53.2%, 90.7%, 67.1% and 98% respectively. The specificity of triage for step I, II, III, IV and V were 99.8%, 97.5%, 93.7%, 98.3% and 94% respectively. There was a significant overlapping between the triage step and the patient clinical outcome. Conclusion: This study showed that five steps triage contain a high accuracy and estimation of patient outcomes.
Predicting protein-protein interactions as a one-class classification problem

Protein-protein interactions represent a key step in understanding proteins functions. This is due to the fact that proteins usually work in context of other proteins and rarely function alone. Machine learning techniques have been used to predict protein-protein interactions. However, most of these techniques address this problem as a binary classification problem. While it is easy to get a dataset of interacting protein as positive example, there is no experimentally confirmed non-interacting protein to be considered as a negative set. Therefore, in this paper we solve this problem as a one-class classification problem using One-Class SVM (OCSVM). Using only positive examples (interacting protein pairs) for training, the OCSVM achieves accuracy of 80%. These results imply that protein-protein interaction can be predicted using one-class classifier with reliable accuracy.
Identifying "E-mmediacy" Strategies for Web-Based Instruction: A Delphi Study

• Patricia J. Slagter van Tryon, Educational Technology, College of Education Lehigh University, 17 Martindell Drive,Wrightstown, PA 18940. Telephone: (215) 598-9301. E-mail: pas2@lehigh.eduThe Quarterly Review of Distance Education, Volume 7(1), 2006, pp. 49–62 ISSN 1528-3518Copyright © 2006 Information Age Publishing, Inc. All rights of reproduction in any form reserved.
AN INEXPENSIVE APPARATUS FOR PRESENTING AVERSIVE STIMULATION TO RODENTS IN A SOCIAL SITUATION

Sz~mmary. -An apparatus and procedure are described for presenting subcutaneous shock sirnultancously to cwo tats for the purpose of eliciting social behavior. Preliminary observations suggest that a full range of agonistic postures are elicited by this arrang-ment and that they are quite similar to behaviors elicited by grid shock. A major problem with using electric shock in free-operant situations is its application through a grid :o the animal's feet. Since S is free-moving, changes in foot placement or posture often alter the effects of the shock. The use of constant current stimulators and various kinds of grid scramblers for alternating the respective grids which ate hot, have been only partial solutions to chis problem, as other investigators have noted (Azrin & Holz, 1966; Dinsmoor, 1961). These problems are particularly acute in experiments in which elicited behaviors ate studied (e.g., shock-elicited aggression, SEA). During the course of an experiment S may instrumencally acquire a partial escape response of some kind which later interferes with the natural occurrence of the respondent behav~or being studied. Where a single animal is studied, subdermal electrodes sutured to the hide and exiting via microminiature connectors through a slip-ring assembly or mercury commutator have sufficed (e.g., see Campbell 8: Moorcroft, 1970). Where the animal is partially restrained such electrodes may be merely attached to the surface of the skin (Weiss, 1967; Azrin, Rubin, & Hutchinson, 1968; Rubin & Aztin, 1967). However, with the exception of the latter study involving the sexual behavior of rabbits, none of chese solutions have been used to study social behaviors, as in experiments on shock-elicited aggression, for example. We report here the use of a technique which is suitable for studying two animals simultaneously in which subdermal electric shock is separately presented to each animal. Such a procedure may likewise be used for making various kinds of psychophysiological recordings or for studying the effects of CNS stimulation upon social behaviors. However, it originated from attempts to gain greater control over the eliciting stimulus in studies of shock elicited aggression.
A Smart Phone Based PDR Solution for Indoor Navigation

Most smart phones are embedded with low-cost navigation sensors such as GPS receiver, accelerometer, digital compass, and gyros. In addition to these low cost sensors, RF signals from WLAN (Wireless Local Area Network), Bluetooth, RFID (Radio Frequency Identification) and cellular networks are also available in smart phones. With the embedded navigation sensors, especially the GPS receiver, it is not a challenging task to locate the smart phone whenever an open sky is visible. However, it is still a challenging task to locate smart phones in GNSS signal challenging environments such as indoors. Therefore, indoor positioning problem has become attractive to the scientific community. This paper introduces a PDR (Pedestrian Dead Reckoning) positioning solution for indoors, especially for corridor environments. The solution is based on a low cost accelerometer and a digital compass embedded in a smart phone (Nokia 6710) plus the low energy Bluetooth RF chip that has a potential to become a standard component in smart phones in the very near future. It is an instant solution that requires any training phases for e.g. establishing the step-length model and the heading error model. The positioning process is initiated automatically when the mobile user passing a Bluetooth access point, for example the one installed at the front door of a building.
Noise robust open vocabulary information retrieval in large spoken document collection (Geräuschrobuste vokabular-unabhängige Methoden für das Informations-Retrieval in der großen Sammlung von gesprochenen Dokumenten)

The amount of available spoken information is growing very fast. Consequently, there is an increasing need for effective and efficient approaches for the indexing and retrieval of spoken information. Classical spoken document retrieval systems are often based on the word transcription provided by an automatic speech recognition system. A large vocabulary word recognizer will be used to transcribe spoken documents. If there are only few errors contained in the recognition transcription of spoken documents, this kind of spoken document retrieval approaches could achieve comparable performance to text-based information retrieval. However, the mismatch between training and application conditions will lead to a high rate of recognition errors. At the same time, the size of the vocabulary will grow with the size of data collection. The growing number of unforeseeable words that are not appearing in the recognizable vocabulary (out-of-vocabulary words) have become the main problem that word-based spoken document retrieval system has to deal with. This thesis focuses on the exploration of spoken document retrieval approaches dealing with misrecognition and the problems caused by out-ofvocabulary words. We have collected our test data from the Wall Street Journal Corpus. It includes records made under variation in acoustic environment (background music or talking radio), records made from different channels, and records from different speakers. A 20k word recognizer has been built for transcribing speech into representations. This recognizer can achieve a word-error rate of 25% on our text collection. In this work, we will only consider the case of single-word queries. About 13% of queries are out-ofvocabulary words. Traditional word-based spoken document retrieval system is built as baseline system. It reaches a mean average value of 61% and a maximal recall rate of 78% on our test collection. We first explore different word-based spoken document retrieval approaches dealing with misrecognition errors. Experiments with in-vocabulary queries show that enriching
Learning Scientific Reasoning Skills May Be Key to Retention in Science, Technology, Engineering, and Mathematics

The United States produces too few Science, Technology, Engineering, and Mathematics (STEM) graduates to meet demand. We investigated scientific reasoning ability as a possible factor in STEM retention. To do this, we classified students in introductory biology courses at a large private university as either declared STEM or non-STEM majors and assessed their reasoning ability using the Lawson Classroom Test of Scientific Reasoning. We then obtained their declared majors 1 to 4 years later. We found that reasoning ability correlates with high-level performance and final course grades. In addition, results indicate that STEM majors have higher reasoning skills than non-STEM majors but not until after the freshman year. However, we show that reasoning ability does not predict retention or declaration of a STEM degree and suggests instead that increased reasoning skills are a product of learning. We suggest educational interventions that may plug the leaky pipeline in STEM education.
Testing Students’ Understanding of Vector Concepts

After four years of research we designed a 20-item multiple choice vector concept test (Test of Understanding of Vectors, TUV). In this article we analyze: 1) the reliability and discriminatory power of the test, and 2) students’ understanding of the vector concepts evaluated in the test. The final version of the test was administered in English to 423 students who were finishing an Electricity and Magnetism course at a large private Mexican university. In the first part of the article, we show results indicating that the TUV is a reliable assessment tool. In the second part, we examine students’ overall performance on the test and analyze the results of the five most difficult items for students: geometric interpretation of dot product, calculation of dot product of two vectors written in unit-vector notation, graphic representation of a unit vector, calculation of the direction of a vector written in unit-vector notation, and graphical subtraction of vector in 2D.
Parallel Networks that Learn to Pronounce

This paper describes NETtalk, a class of massively-parallel network systems that learn to convert English text to speech. The memory representations for pronunciations are learned by practice and are shared among many processing units. The performance of NETtalk has some similarities with observed human performance. (i) The learning follows a power law. (;i) The more words the network learns, the better it is at generalizing and correctly pronouncing new words, (iii) The performance of the network degrades very slowly as connections in the network are damaged: no single link or processing unit is essential. (iv) Relearning after damage is much faster than learning during the original training. (v) Distributed or spaced prac- tice is more effective for long-term retention than massed practice. Network models can be constructed that have the same perfor- mance and learning characteristics on a particular task, but differ completely at the levels of synaptic strengths and single-unit responses. However, hierarchical clustering techniques applied to NETtalk re- veal that these different networks have similar internal representations of letter-to-sound correspondences within groups of processing units. This suggests that invariant internal representations may be found in assemblies of neurons intermediate in size between highly localized and completely distributed representations.
Application of BCFD unstructured grid solver to simulation of micro-ramp control of shock/boundary layer interactions

An unstructured grid solver implemented in the BCFD code has been applied to simulate the eect of a micro-ramp on oblique shock wave/boundary layer interactions. Specifically, the micro-ramp’s ability to prevent inlet unstart was examined. The 3D Reynolds-averaged Navier-Stokes equations were solved by an implicit time-marching method. Starting from a steady-state solution at a freestream Mach number of 2.0, the upstream boundary condition was perturbed to simulate a disturbance upstream of the oblique shock wave/boundary layer interaction. The reaction of the flow field to this disturbance was examined for cases with and without a micro-ramp. The results are in agreement with the previous findings of Anderson et al.
IMPLEMENTATION OF DBRAIN SEARCH ALGORITHM ON PAGE CLUSTERING

This paper implements an DBRAIN of a clustering algorithm based on gravitational forces to the problem of Web Page Clustering in a dynamic environment. Web pages are attributed with weights in a mathematical space. Computing the gravity between the pages in the mathematical space is expensive, since the definition of mathematical space is very expensive (time, space). Clustering without using the notion of the space is used in this paper Experiments with data representing real URL's and sessions are performed, and a comparison with the incremental connected components algorithm, which has been previously used to solve this problem, is done.
Mining Social Distance from Mobile Phone Communication Networks

Nowadays, smartphones have been widely deployed. Scientists can obtain position and proximity data as well as call and SMS log data easily. Rich information are hidden behind these mobile data. For example, social interaction patterns of smartphone users. The discovery of those patterns can benefit many important applications such as (1) Relationship inference; (2) Community detection in counter terrorism. However, mobile data owns many unique characteristics, such as (1) The amount of data is massive; (2) Timeliness is very important; (3) Different types of data are highly coupled. Traditional statistical methods have been used to analyze mobile data, which can not be applied to huge amount of mobile data streams in real-world situations. In this paper, we take mobile data as an example, to analyze the social distance and fulfill popular tasks such as (1) Relationship inference; (2) Community detection. We propose a time-constrained homogeneous graph model, which takes a mobile call log as input and models the social distance problem by a time-based sliding window scheme. We further design an efficient modified EdgeRank algorithm to compute the social distances among users. We propose an algorithm for community detection. Experimental results on real data sets show that the proposed approach can infer social distance efficiently and achieves an accuracy of 80-85% automatically. We apply the results of social distance relationships to community detection and an improvement of accuracy of 5% can be achieved.