227 research outputs found

    THE IMPACT OF DIFFERENT PROOF STRATEGIES ON LEARNING GEOMETRY THEOREM PROVING

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    Two problem solving strategies, forward chaining and backward chaining, were compared to see how they affect students' learning of geometry theorem proving with construction. It has been claimed that backward chaining is inappropriate for novice students due to its complexity. On the other hand, forward chaining may not be appropriate either for this particular task because it can explode combinatorially. In order to determine which strategy accelerates learning the most, an intelligent tutoring system was developed. It is unique in two ways: (1) It has a fine grained cognitive model of proof-writing, which captured both observable and unobservable inference steps. This allows the tutor to provide elaborate scaffolding. (2) Depending on the student's competence, the tutor provides a variety of scaffolding from showing precise steps to just prompting students for a next step. In other words, the students could learn proof-writing through both worked-out examples (by observing a model of proof-writing generated by the tutor) and problem solving (by writing proofs by themselves). 52 students were randomly assigned to one of the tutoring systems. They solved 11 geometry proof problems with and without construction with the aid from the intelligent tutor. The results show that (1) the students who learned forward chaining showed better performance on proof-writing than those who learned backward chaining, (2) both forward and backward chaining conditions wrote wrong proofs equally frequently, (3) both forward and backward chaining conditions seldom wrote redundant or wrong statements when they wrote correct proofs, (4) the major reason for the difficulty in applying backward chaining lay in the assertion of premises as unjustified propositions (i.e., subgoaling). These results provide theoretical implications for the design of tutoring systems for problem solving

    A preliminary report on noble gases in the Kobe (CK) meteorite: A carbonaceous chondrite fell in Kobe City, Japan

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    We have investigated elemental and isotopic compositions of noble gases in the newly-fallen CK chondrite, Kobe. The relatively low concentrations of primordial heavy noble gases (Kr and Xe) and the relatively high ^Xe/^Xe ratio (6.51±0.02) are similar to those found in previous studies of CK chondrites. The calculated cosmic-ray exposure age based on cosmogenic ^Ne is 41Ma, and the K-Ar age is 2.1Ga. Based on calculated exposure ages and gas retention ages of Kobe and some other CK chondrites, it is likely that they have partially lost both radiogenic and cosmogenic He by solar heating during the time of exposure. Based on the ^Ar retention age, we interpret that Kobe may also have experienced thermal events, possibly related to impacts about 2 billion years age

    Pharmacological Characteristics and Clinical Applications of K201

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    K201 is a 1,4-benzothiazepine derivative that is a promising new drug with a strong cardioprotective effect. We initially discovered K201 as an effective suppressant of sudden cardiac cell death due to calcium overload. K201 is a nonspecific blocker of sodium, potassium and calcium channels, and its cardioprotective effect is more marked than those of nicorandil, prazosine, propranolol, verapamil and diltiazem. Recently, K201 has also been shown to have activities indicated for treatment of atrial fibrillation, ventricular fibrillation, heart failure and ischemic heart disease, including action as a multiple-channel blocker, inhibition of diastolic Ca2+ release from the sarcoplasmic reticulum, suppression of spontaneous Ca2+ sparks and Ca2+ waves, blockage of annexin V and provision of myocardial protection, and improvement of norepinephrine-induced diastolic dysfunction. Here, we describe the pharmacological characteristics and clinical applications of K201

    How quickly can wheel spinning be detected?

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    ABSTRACT We have developed a wheel spinning detector for cognitive tutors that uses a simplified method compared to existing wheel spinning detectors. The detector reads a sequence of the correctness of applying particular skill performed by a student using the cognitive tutor. The response sequence is first fed to Bayesian knowledge tracing to compute a sequence of probability of mastery at each time a skill was applied. The detector uses a neural-network model to make a binary classification for a response sequence into wheelspinning and none-wheel spinning. To test the accuracy of the detector, we validated the detector using learning interaction data taken from a school study where students used a Geometry cognitive tutor. Human coders manually tagged the data to identify wheel spinning. The results show that the neural-network based detector has high recall (0.79) but relatively low precision (0.25) when combined with Bayesian knowledge tracing that detects mastery cases. The result suggests that the neural-network based detector is practical and has a potential for scalable use such as adaptive online course where cognitive tutors are embedded into online courseware

    Involvement of S-adenosylmethionine-dependent halide/thiol methyltransferase (HTMT) in methyl halide emissions from agricultural plants: isolation and characterization of an HTMT-coding gene from Raphanus sativus (daikon radish)

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    <p>Abstract</p> <p>Background</p> <p>Biogenic emissions of methyl halides (CH<sub>3</sub>Cl, CH<sub>3</sub>Br and CH<sub>3</sub>I) are the major source of these compounds in the atmosphere; however, there are few reports about the halide profiles and strengths of these emissions. Halide ion methyltransferase (HMT) and halide/thiol methyltransferase (HTMT) enzymes concerning these emissions have been purified and characterized from several organisms including marine algae, fungi, and higher plants; however, the correlation between emission profiles of methyl halides and the enzymatic properties of HMT/HTMT, and their role in vivo remains unclear.</p> <p>Results</p> <p>Thirty-five higher plant species were screened, and high CH<sub>3</sub>I emissions and HMT/HTMT activities were found in higher plants belonging to the Poaceae family, including wheat (<it>Triticum aestivum </it>L.) and paddy rice (<it>Oryza sativa </it>L.), as well as the Brassicaceae family, including daikon radish (<it>Raphanus sativus</it>). The in vivo emission of CH<sub>3</sub>I clearly correlated with HMT/HTMT activity. The emission of CH<sub>3</sub>I from the sprouting leaves of <it>R. sativus</it>, <it>T. aestivum </it>and <it>O. sativa </it>grown hydroponically increased with increasing concentrations of supplied iodide. A gene encoding an <it>S</it>-adenosylmethionine halide/thiol methyltransferase (HTMT) was cloned from <it>R. sativus </it>and expressed in <it>Escherichia coli </it>as a soluble protein. The recombinant <it>R. sativus </it>HTMT (RsHTMT) was revealed to possess high specificity for iodide (I<sup>-</sup>), bisulfide ([SH]<sup>-</sup>), and thiocyanate ([SCN]<sup>-</sup>) ions.</p> <p>Conclusion</p> <p>The present findings suggest that HMT/HTMT activity is present in several families of higher plants including Poaceae and Brassicaceae, and is involved in the formation of methyl halides. Moreover, it was found that the emission of methyl iodide from plants was affected by the iodide concentration in the cultures. The recombinant RsHTMT demonstrated enzymatic properties similar to those of <it>Brassica oleracea </it>HTMT, especially in terms of its high specificity for iodide, bisulfide, and thiocyanate ions. A survey of biogenic emissions of methyl halides strongly suggests that the HTM/HTMT reaction is the key to understanding the biogenesis of methyl halides and methylated sulfur compounds in nature.</p

    Laparoscopic Hepatectomy for the Patient with Hemophilia A with High Titer Factor VIII Inhibitor

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    We present the first case of laparoscopic left lateral segmentectomy for hepatocellular carcinoma (HCC) in a patient with hemophilia A, acquired hepatitis C, and high-titer factor VIII inhibitor, which was confirmed by preoperative diagnosis. He underwent laparoscopic left lateral segmentectomy with the administration of recombinant activated factor VII. Surgery could be performed with reduced intraoperative hemorrhage. He experienced postoperative intra-abdominal wall hemorrhage, which was successfully managed with red cell concentrates transfusion and administration of recombinant activated factor VII. Laparoscopic hepatectomy can be applied for hemophilia patients with high titer inhibitors

    Performance of in-hospital mortality prediction models for acute hospitalization: Hospital Standardized Mortality Ratio in Japan

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    <p>Abstract</p> <p>Objective</p> <p>In-hospital mortality is an important performance measure for quality improvement, although it requires proper risk adjustment. We set out to develop in-hospital mortality prediction models for acute hospitalization using a nation-wide electronic administrative record system in Japan.</p> <p>Methods</p> <p>Administrative records of 224,207 patients (patients discharged from 82 hospitals in Japan between July 1, 2002 and October 31, 2002) were randomly split into preliminary (179,156 records) and test (45,051 records) groups. Study variables included Major Diagnostic Category, age, gender, ambulance use, admission status, length of hospital stay, comorbidity, and in-hospital mortality. ICD-10 codes were converted to calculate comorbidity scores based on Quan's methodology. Multivariate logistic regression analysis was then performed using in-hospital mortality as a dependent variable. C-indexes were calculated across risk groups in order to evaluate model performances.</p> <p>Results</p> <p>In-hospital mortality rates were 2.68% and 2.76% for the preliminary and test datasets, respectively. C-index values were 0.869 for the model that excluded length of stay and 0.841 for the model that included length of stay.</p> <p>Conclusion</p> <p>Risk models developed in this study included a set of variables easily accessible from administrative data, and still successfully exhibited a high degree of prediction accuracy. These models can be used to estimate in-hospital mortality rates of various diagnoses and procedures.</p
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