nils-herrmann/clean_scirepeval huggingface dataset:
Algebraic and Geometric Reasoning Using Dixon Resultants

Dixon's method for computing multivariate resultants by simultaneously eliminating many variables is reviewed. The method is found to be quite restrictive because often the Dixon matrix is singular, and the Dixon resultant vanished identically yielding no information about solutions for many algebraic and geometry problems. We extend Dixon's method for the case when the Dixon matrix is singular, but satisfies a condition. An efficient algorithm is developed based on the proposed extension for extracting conditions for the existence of affine solutions of a finite set of polynomials. Using this algorithm, numerous geometric and algebraic identities are derived for examples which appear intractable with other techniques of triangulation such as the successive resultant method, the Gro¨bner basis method, Macaulay resultants and Characteristic set method. Experimental results suggest that the resultant of a set of polynomials which are symmetric in the variables is relatively easier to compute using the extended Dixon's method.
Reliability and validity of a quantitative color scale to evaluate masticatory performance using color-changeable chewing gum.

In the present study, we developed a novel color scale for visual assessment, conforming to theoretical color changes of a gum, to evaluate masticatoryperformance; moreover, we investigated the reliability and validity of this evaluation method using the color scale. Ten participants (aged 26.30 years) with natural dentition chewed the gum at several chewing strokes. Changes in color were measured using a colorimeter, and then, linearregression expressions that represented changes in gum color were derived. The color scale was developed using these regression expressions. Thirty-two chewed gums were evaluated using colorimeter and were assessed three times using the color scale by six dentists aged 25.27 (mean, 25.8) years, six preclinical dental students aged 21.23 (mean, 22.2) years, and six elderly individuals aged 68.84 (mean, 74.0) years. The intrarater and interrater reliability of evaluations was assessed using intraclass correlation coefficients. Validity of the method compared with a colorimeter was assessed using Spearman's rank correlation coefficient. All intraclass correlation coefficients were > 0.90, and Spearman's rank-correlation coefficients were > 0.95 in all groups. These results indicated that the evaluation method of the color-changeable chewing gum using the newly developed color scale is reliable and valid.
Prototype CNC machine design

The Computer Numeric Control (CNC) is a technology which aims to generate, parse and execute sequential actions that describes the behavior of the end effector. This article reports the development small sized prototype CNC machine, based on a modular system with the capability of communication through USB. It is also reported the development of the basic electronic devices to run a CNC machine and proposes, as well, a software developed in LabVIEW to establish the communication between the machine and the computer. The main objective of this work is the development of a machine which allows future researches on the process performance, on educational purposes, the demonstration the parts involved on the CNC machine.
A Practical Visual Servo Control for an Unmanned Aerial Vehicle

An image-based visual servo control is presented for an unmanned aerial vehicle (UAV) capable of stationary or quasi-stationary flight with the camera mounted onboard the vehicle. The target considered consists of a finite set of stationary and disjoint points lying in a plane. Control of the position and orientation dynamics is decoupled using a visual error based on spherical centroid data, along with estimations of the linear velocity and the gravitational inertial direction extracted from image features and an embedded inertial measurement unit. The visual error used compensates for poor conditioning of the image Jacobian matrix by introducing a nonhomogeneous gain term adapted to the visual sensitivity of the error measurements. A nonlinear controller, that ensures exponential convergence of the system considered, is derived for the full dynamics of the system using control Lyapunov function design techniques. Experimental results on a quadrotor UAV, developed by the French Atomic Energy Commission, demonstrate the robustness and performance of the proposed control strategy.
Scabies incognito presenting as urticaria pigmentosa in an infant.

Misdiagnosis is frequent in scabies of infants and children because of a low index of suspicion, secondary eczematous changes, and inappropriate therapy. Topical or systemic corticosteroids may modify the clinical presentation of scabies and that situation is referred to as scabies incognito. We describe a 10-month-old infant with scabies incognito mimicking urticaria pigmentosa.
A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.

Deep learning methods for radiomics/computer-aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for extensive image preprocessing.



We aim to develop a breast CADx methodology that addresses the aforementioned issues by exploiting the efficiency of pre-trained convolutional neural networks (CNNs) and using pre-existing handcrafted CADx features.



We present a methodology that extracts and pools low- to mid-level features using a pretrained CNN and fuses them with handcrafted radiomic features computed using conventional CADx methods. Our methodology is tested on three different clinical imaging modalities (dynamic contrast enhanced-MRI [690 cases], full-field digital mammography [245 cases], and ultrasound [1125 cases]).



From ROC analysis, our fusion-based method demonstrates, on all three imaging modalities, statistically significant improvements in terms of AUC as compared to previous breast cancer CADx methods in the task of distinguishing between malignant and benign lesions. (DCE-MRI [AUC = 0.89 (se = 0.01)], FFDM [AUC = 0.86 (se = 0.01)], and ultrasound [AUC = 0.90 (se = 0.01)]).



We proposed a novel breast CADx methodology that can be used to more effectively characterize breast lesions in comparison to existing methods. Furthermore, our proposed methodology is computationally efficient and circumvents the need for image preprocessing.
Miscarriage, peripheral thromboses and aortic aneurysm in antiphospholipid-antibody-negative Sneddon's syndrome

A 46-year-old woman was referred to our hospital because of suspected cerebral ischemia. Two days earlier the patient had recognized a left-sided weakness and clumsiness. On neurological examination we found a mild left-sided hemiparesis and hemiataxia. There was a generalized shrinking violaceous netlike pattering of the skin especially on both legs and arms but also on the trunk and buttocks . The patient reported the skin changing to be more prominent on cold exposure. The patient’s family remembered this skin finding to be evident since the age of five years. A diagnosis of livedo racemosa had been made 5 years ago. The neuropsychological assessment of this highly educated civil servant revealed a slight cognitive decline. MRI showed a right-sided cerebral ischemia in the middle cerebral artery (MCA) territory. Her medical history was significant for migraine-like headache for many years, a miscarriage 18 years before and a deep vein thrombosis of the left leg six years ago. She had no history of smoking or other cerebrovascular risk factors including no estrogen-containing oral contraceptives. The patient underwent intensive examinations including duplex sonography of extraand intracranial arteries, transesophageal echocardiography, 24-h ECG, 24-h blood pressure monitoring, multimodal evoked potentials, electroencephalography, lumbar puncture and sonography of abdomen. All these tests were negative. Extensive laboratory examinations revealed a heterozygote prothrombin 20210 mutation, which is associated with a slightly increased risk for thrombosis. Antiphospholipid antibodies (aplAB) and other laboratory examinations to exclude vasculitis, toxic metabolic disturbances and other causes for livedo racemosa were negative. Skin biopsy showed vasculopathy with intimal proliferation and an occluding thrombus. The patient was diagnosed as having antiphospholipid-antibodynegative Sneddon’s syndrome (SS) based on cerebral ischemia combined with wide-spread livedo racemosa associated with a history of miscarriage, deep vein thrombosis, migraine like headaches and mild cognitive decline. We started long-term prophylactic pharmacological therapy with captopril as a myocyte proliferation agent and with aspirin as an antiplatelet therapy. Furthermore we recommended thrombosis prophylaxis in case of immobilization. One month later the patient experienced vein thrombosis of her right forearm and suffered from dyspnea. Antiphospholipid antibody testing again was negative. EBT and CT of thorax showed an aneurysmatic dilatation of aorta ascendens up to 4.5 cm. After careful consideration of the possible disadvantages we nevertheless decided to start long-term anticoagulation instead of antiplatelet therapy because of the second thrombotic event. The elucidating and interesting issue of this case is the association of miscarriage and two vein thromboses in aplAB-negative SS. Little is known about this phenomenon and there are only a few reports about these symptoms in aplABLETTER TO THE EDITORS
Extending the recognition-primed decision model to support human-agent collaboration

There has been much research investigating team cognition, naturalistic decision making, and collaborative technology as it relates to real world, complex domains of practice. However, there has been limited work in incorporating naturalistic decision making models for supporting distributed team decision making. The aim of this research is to support human decision making teams using cognitive agents empowered by a collaborative Recognition-Primed Decision model. In this paper, we first describe an RPD-enabled agent architecture (R-CAST), in which we have implemented an internal mechanism of decision-making adaptation based on collaborative expectancy monitoring, and an information exchange mechanism driven by relevant cue analysis. We have evaluated R-CAST agents in a real-time simulation environment, feeding teams with frequent decision-making tasks under different tempo situations. While the result conforms to psychological findings that human team members are extremely sensitive to their workload in high-tempo situations, it clearly indicates that human teams, when supported by R-CAST agents, can perform better in the sense that they can maintain team performance at acceptable levels in high time pressure situations.
Analysis and Design of Voltage-Controlled Oscillator Based Analog-to-Digital Converter

A voltage-controlled oscillator (VCO) based analog-to-digital converter (ADC) is a time-based architecture with a first-order noise-shaping property, which can be implemented using a VCO and digital circuits. This paper analyzes the performance of VCO-based ADCs in the presence of nonidealities such as jitter, nonlinearity, mismatch, and the metastability of D flip-flops. Based on this analysis, design criteria for determining parameters for VCO-based ADCs are described. In addition, a digital calibration technique to enhance the spurious-free dynamic range degraded by the nonlinearity is also introduced. To verify the theoretical analysis, a prototype chip is implemented in a 0.13-¿m CMOS process. With a 500-MHz sampling frequency, the prototype achieves a signal-to-noise ratio ranging from 71.8 to 21.3 dB for an input bandwidth of 100 kHz-247 MHz, while dissipating 12.6 mW and occupying an area of 0.078 mm2.
Evolutionary Algorithms for Solving Multi-Objective Problems

Educational Goals of Course(s): i. Explore and evaluate Multi-Objective Evolutionary algorithm (MOEA) space, Multi-Objective Problem (MOP) space, and parameter space along with MOEA performance comparisons ii. Motivate the student to investigate new areas of MOEA design, implementation, and performance metrics iii. Developed an ability to utilize and improve MOEA performance across a wide variety of application problem domains.
Distributed Rational Decision Making

Automated negotiation systems with self interested agents are becoming increas ingly important One reason for this is the technology push of a growing standardized communication infrastructure Internet WWW NII EDI KQML FIPA Concor dia Voyager Odyssey Telescript Java etc over which separately designed agents belonging to di erent organizations can interact in an open environment in real time and safely carry out transactions The second reason is strong application pull for computer support for negotiation at the operative decision making level For example we are witnessing the advent of small transaction electronic commerce on the Internet for purchasing goods information and communication bandwidth There is also an industrial trend toward virtual enterprises dynamic alliances of small agile enterprises which together can take advantage of economies of scale when available e g respond to more diverse orders than individual agents can but do not su er from diseconomies of scale Multiagent technology facilitates such negotiation at the operative decision mak ing level This automation can save labor time of human negotiators but in addi tion other savings are possible because computational agents can be more e ective at nding bene cial short term contracts than humans are in strategically and com binatorially complex settings This chapter discusses multiagent negotiation in situations where agents may have di erent goals and each agent is trying to maximize its own good without concern for the global good Such self interest naturally prevails in negotiations among independent businesses or individuals In building computer support for negotiation in such settings the issue of self interest has to be dealt with In cooperative distributed problem solving the system designer imposes an interaction protocol and a strategy a mapping from state history to action a
Control under communication constraints

There is an increasing interest in studying control systems employing multiple sensors and actuators that are geographically distributed. Communication is an important component of these distributed and networked control systems. Hence, there is a need to understand the interactions between the control components and the communication components of the distributed system. In this paper, we formulate a control problem with a communication channel connecting the sensor to the controller. Our task involves designing the channel encoder and channel decoder along with the controller to achieve different control objectives. We provide upper and lower bounds on the channel rate required to achieve these different control objectives. In many cases, these bounds are tight. In doing so, we characterize the "information complexity" of different control objectives.
Will People Like Your Image?

The wide distribution of digital devices as well as cheap storage allow us to take series of photos making sure not to miss any specific beautiful moment. Thereby, the huge and constantly growing image assembly makes it quite timeconsuming to manually pick the best shots afterwards. Even more challenging, finding the most aesthetically pleasing images that might also be worth sharing is a largely subjective task in which general rules rarely apply. Nowadays, online platforms allow users to “like” or favor certain content with a single click. As we aim to predict the aesthetic quality of images, we now make use of such multi-user agreements. More precisely, we assemble a large data set of 380K images with associated meta information and derive a score to rate how visually pleasing a given photo is. Further, to predict the aesthetic quality of any arbitrary image or video, we transfer the obtained model into a deep learning problem. Our proposed model of aesthetics is validated in a user study. We demonstrate our results on applications for resorting photo collections, capturing the best shot on mobile devices and aesthetic key-frame extraction from videos.
Tocilizumab in patients with active rheumatoid arthritis and inadequate response to disease-modifying antirheumatic drugs or tumor necrosis factor inhibitors: subanalysis of Spanish results of an open-label study close to clinical practice.

To analyze the Spanish experience in an international study which evaluated tocilizumab in patients with rheumatoid arthritis (RA) and an inadequate response to conventional disease-modifying antirheumatic drugs (DMARDs) or tumor necrosis factor inhibitors (TNFis) in a clinical practice setting.



Subanalysis of 170 patients with RA from Spain who participated in a phase IIIb, open-label, international clinical trial. Patients presented inadequate response to DMARDs or TNFis. They received 8mg/kg of tocilizumab every 4 weeks in combination with a DMARD or as monotherapy during 20 weeks. Safety and efficacy of tocilizumab were analyzed. Special emphasis was placed on differences between failure to a DMARD or to a TNFi and the need to switch to tocilizumab with or without a washout period in patients who had previously received TNFi.



The most common adverse events were infections (25%), increased total cholesterol (38%) and transaminases (15%). Five patients discontinued the study due to an adverse event. After six months of tocilizumab treatment, 71/50/30% of patients had ACR 20/50/70 responses, respectively. A higher proportion of TNFi-naive patients presented an ACR20 response: 76% compared to 64% in the TNFi group with previous washout and 66% in the TNFi group without previous washout.



Safety results were consistent with previous results in patients with RA and an inadequate response to DMARDs or TNFis. Tocilizumab is more effective in patients who did not respond to conventional DMARDs than in patients who did not respond to TNFis.
Novel amidases of two Aminobacter sp. strains: Biotransformation experiments and elucidation of gene sequences

The amidase activities of two Aminobacter sp. strains (DSM24754 and DSM24755) towards the aryl-substituted substrates phenylhydantoin, indolylmethyl hydantoin, D,L-6-phenyl-5,6-dihydrouracil (PheDU) and para-chloro-D,L-6-phenyl-5,6-dihydrouracil were compared. Both strains showed hydantoinase and dihydropyrimidinase activity by hydrolyzing all substrates to the corresponding N-carbamoyl-α- or N-carbamoyl-β-amino acids. However, carbamoylase activity and thus a further degradation of these products to α- and β-amino acids was not detected. Additionally, the genes coding for a dihydropyrimidinase and a carbamoylase of Aminobacter sp. DSM24754 were elucidated. For Aminobacter sp. DSM24755 a dihydropyrimidinase gene flanked by two genes coding for putative ABC transporter proteins was detected. The deduced amino acid sequences of both dihydropyrimidinases are highly similar to the well-studied dihydropyrimidinase of Sinorhizobium meliloti CECT4114. The latter enzyme is reported to accept substituted hydantoins and dihydropyrimidines as substrates. The deduced amino acid sequence of the carbamoylase gene shows a high similarity to the very thermostable enzyme of Pseudomonas sp. KNK003A.
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach

Markov chain Monte Carlo (MCMC) methods are often deemed far too computationally intensive to be of any practical use for large datasets. This paper describes a methodology that aims to scale up the Metropolis-Hastings (MH) algorithm in this context. We propose an approximate implementation of the accept/reject step of MH that only requires evaluating the likelihood of a random subset of the data, yet is guaranteed to coincide with the accept/reject step based on the full dataset with a probability superior to a user-specified tolerance level. This adaptive subsampling technique is an alternative to the recent approach developed in (Korattikara et al., 2014), and it allows us to establish rigorously that the resulting approximate MH algorithm samples from a perturbed version of the target distribution of interest, whose total variation distance to this very target is controlled explicitly. We explore the benefits and limitations of this scheme on several examples.
Opioid rotation in patients with cancer pain. A retrospective comparison of dose ratios between methadone, hydromorphone, and morphine.

When a change of opioid is considered, equianalgesic dose tables are used. These tables generally propose a dose ratio of 5:1 between morphine and hydromorphone. In the case of a change from subcutaneous hydromorphone to methadone, dose ratios ranging from 1:6 to 1:10 are proposed. The purpose of this study was to review the analgesic dose ratios for methadone compared with hydromorphone.



In a retrospective study, 48 cases of medication changes from morphine to hydromorphone, and 65 changes between hydromorphone and methadone were identified. the reason for the change, the analgesic dose, and pain intensity were obtained.



The dose ratios between morphine and hydromorphone and vice versa were found to be 5.33 and 0.28, respectively (similar to expected results). However, the hydromorphone/methadone ratio was found to be 1.14:1 (5 to 10 times higher than expected). Although the dose ratios of hydromorphone/morphine and vice versa did not change according to a previous opioid dose, the hydromorphone/methadone ratio correlated with total opioid dose (correlation coefficient = 0.41 P < 0.001) and was 1.6 (range, 0.3-14.4) in patients receiving more than 330 mg of hydromorphone per day prior to the change, versus 0.95 (range, 0.2-12.3) in patients receiving ae330 mg of hydromorphone per day (P = 0.023).



These results suggest that only partial tolerance develops between methadone and hydromorphone. Methadone is much more potent than previously described and any change should start at a lower equivalent dose.
Food and mood: relationship between food, serotonin and affective disorders.

The relationship of food and eating with affective and other clinical disorders is complex and intriguing. Serotoninergic dysfunction in seasonal affective disorder, atypical depression, premenstrual syndrome, anorexia and bulimia nervosa, and binge eating disorder is reviewed. Patients exhibiting a relationship between food and behaviour are found in various diagnostic categories. This points to a need to shift from nosological to functional thinking in psychiatry. It also means application of psychopharmacological treatments across diagnostic boundaries. The use of phototherapy and psychotropic drugs (MAO inhibitors and selective serotonin reuptake inhibitors like fluoxetine) in these disorders is discussed.