nils-herrmann/clean_scirepeval huggingface dataset:
Output-Capacitor-Free LDO Design Methodologies for High EMI Immunity

This paper presents circuit design methodologies to enhance the electromagnetic immunity of an output-capacitor-free low-dropout (LDO) regulator. To evaluate the noise performance of an LDO regulator in the small-signal domain, power-supply rejection (PSR) is used. We optimize a bandgap reference circuit for optimum dc PSR, and propose a capacitor cancelation technique circuit for bandwidth compensation, and a low-noise biasing circuit for immunity enhancement in the bias circuit. For large-signal, transient performance enhancement, we suggest using a unity-gain amplifier to minimize the voltage difference of the differential inputs of the error amplifier, and an auxiliary N-channel metal oxide semiconductor (NMOS) pass transistor was used to maintain a stable gate voltage in the pass transistor. The effectiveness of the design methodologies proposed in this paper is verified using circuit simulations using an LDO regulator designed by 0.18-$\mu$m CMOS process. When sine and pulse signals are applied to the input, the worst dc offset variations were enhanced from 36% to 16% and from 31.7% to 9.7%, respectively, as compared with those of the conventional LDO. We evaluated the noise performance versus the conducted electromagnetic interference generated by the dc–dc converter; the noise reduction level was significantly improved.
The Camelidae (Mammalia, Artiodactyla) from the Quaternary of South America: Cladistic and Biogeographic Hypotheses

Presented here is a cladistic analysis of the South American and some North American Camelidae. This analysis shows that Camelini and Lamini are monophyletic groups, as are the genera Palaeolama and Vicugna, while Hemiauchenia and Lama are paraphyletic. Some aspects of the migration and distribution of South American camelids are also discussed, confirming in part the propositions of other authors. According to the cladistic analysis and previous propositions, it is possible to infer that two Camelidae migration events occurred in America. In the first one, Hemiauchenia arrived in South America and, this was related to the speciation processes that originated Lama and Vicugna. In the second event, Palaeolama migrated from North America to the northern portion of South America. It is evident that there is a need for larger studies about fossil Camelidae, mainly regarding older ages and from the South American austral region. This is important to better undertand the geographic and temporal distribution of Camelidae and, thus, the biogeographic aspects after the Great American Biotic Interchange.
Graham-Little syndrome.

Graham-Little syndrome, also know as Graham-Little-Piccardi-Lassueur syndrome, is an unusual form of lichen planopilaris, characterized by the presence of cicatricial alopecia on the scalp, keratosis pilaris of the trunk and extremities, and non-cicatricial hair loss of the pubis and axillae. We present the case of a 47-year-old woman whose condition was unusual in that there was a prominence of scalp findings. Her treatment included a topical steroid plus systemic prednisone beginning at 30 mg every morning, which rendered her skin smooth, but did not alter her scalp lopecia.
Spectrum-efficient coherent optical zero padding OFDM for future high-speed transport networks

By fully exploiting the optical channel properties, we propose in this paper the coherent optical zero padding orthogonal frequency division multiplexing (CO-ZP-OFDM) for future high-speed optical transport networks to increase the spectral efficiency and improve the system reliability. Unlike the periodically inserted training symbols in conventional optical OFDM systems, we design the polarization-time-frequency (PTF) coded pilots scattered within the time-frequency grid of the ZP-OFDM payload symbols to realize low-complexity multiple-input multiple-output (MIMO) channel estimation with high accuracy. Compared with conventional optical OFDM systems, CO-ZP-OFDM improves the spectral efficiency by about 6.62%. Simulation results indicate that the low-density parity-check (LDPC) coded bit error rate of the proposed scheme only suffers from no more than 0.3 dB optical signal-to-noise ratio (OSNR) loss compared with the ideal back-to-back case even when the optical channel impairments like chromatic dispersion (CD) and polarization mode dispersion (PMD) are severe.
Drivingstyles: a mobile platform for driving styles and fuel consumption characterization

Intelligent transportation systems (ITS) rely on connected vehicle applications to address real-world problems. Research is currently being conducted to support safety, mobility and environmental applications. This paper presents the DrivingStyles architecture, which adopts data mining techniques and neural networks to analyze and generate a classification of driving styles and fuel consumption based on driver characterization. In particular, we have implemented an algorithm that is able to characterize the degree of aggressiveness of each driver. We have also developed a methodology to calculate, in real-time, the consumption and environmental impact of spark ignition and diesel vehicles from a set of variables obtained from the vehicle’s electronic control unit (ECU). In this paper, we demonstrate the impact of the driving style on fuel consumption, as well as its correlation with the greenhouse gas emissions generated by each vehicle. Overall, our platform is able to assist drivers in correcting their bad driving habits, while offering helpful tips to improve fuel economy and driving safety.
Vision-based real-time position control of a semi-automated system for robot-assisted joint fracture surgery

Joint fracture surgery quality can be improved by robotic system with high-accuracy and high-repeatability fracture fragment manipulation. A new real-time vision-based system for fragment manipulation during robot-assisted fracture surgery was developed and tested. The control strategy was accomplished by merging fast open-loop control with vision-based control. This two-phase process is designed to eliminate the open-loop positioning errors by closing the control loop using visual feedback provided by an optical tracking system. Evaluation of the control system accuracy was performed using robot positioning trials, and fracture reduction accuracy was tested in trials on ex vivo porcine model. The system resulted in high fracture reduction reliability with a reduction accuracy of 0.09 mm (translations) and of $$0.15^{\circ }$$ 0 . 15 ∘ (rotations), maximum observed errors in the order of 0.12 mm (translations) and of $$0.18^{\circ }$$ 0 . 18 ∘ (rotations), and a reduction repeatability of 0.02 mm and $$0.03^{\circ }$$ 0 . 03 ∘ . The proposed vision-based system was shown to be effective and suitable for real joint fracture surgical procedures, contributing a potential improvement of their quality.
TensOrMachine: Probabilistic Boolean Tensor Decomposition

Boolean tensor decomposition approximates data of multi-way binary relationships as product of interpretable low-rank binary factors, following the rules of Boolean algebra. Here, we present its first probabilistic treatment. We facilitate scalable sampling-based posterior inference by exploitation of the combinatorial structure of the factor conditionals. Maximum a posteriori decompositions feature higher accuracies than existing techniques throughout a wide range of simulated conditions. Moreover, the probabilistic approach facilitates the treatment of missing data and enables model selection with much greater accuracy. We investigate three real-world data-sets. First, temporal interaction networks in a hospital ward and behavioural data of university students demonstrate the inference of instructive latent patterns. Next, we decompose a tensor with more than 10 billion data points, indicating relations of gene expression in cancer patients. Not only does this demonstrate scalability, it also provides an entirely novel perspective on relational properties of continuous data and, in the present example, on the molecular heterogeneity of cancer. Our implementation is available on GitHub2.
A framework for inverse tone mapping

In recent years many tone mapping operators (TMOs) have been presented in order to display high dynamic range images (HDRI) on typical display devices. TMOs compress the luminance range while trying to maintain contrast. The inverse of tone mapping, inverse tone mapping, expands a low dynamic range image (LDRI) into an HDRI. HDRIs contain a broader range of physical values that can be perceived by the human visual system. We propose a new framework that approximates a solution to this problem. Our framework uses importance sampling of light sources to find the areas considered to be of high luminance and subsequently applies density estimation to generate an expand map in order to extend the range in the high luminance areas using an inverse tone mapping operator. The majority of today’s media is stored in the low dynamic range. Inverse tone mapping operators (iTMOs) could thus potentially revive all of this content for use in high dynamic range display and image based lighting (IBL). Moreover, we show another application that benefits quick capture of HDRIs for use in IBL.
Gate signal jitter elimination and noise shaping modulation for high-SNR Class-D power amplifiers

Two important aspects of switched-mode (Class-D) amplifiers providing a high signal to noise ratio (SNR) for mechatronic applications are investigated. Signal jitter is common in digital systems and introduces noise, leading to a deterioration of the SNR. Hence, a jitter elimination technique for the transistor gate signals in power electronic converters is presented and verified. Jitter is reduced tenfold as compared to traditional approaches to values of 25 ps at the output of the power stage. Additionally, digital modulators used for the generation of the switch control signals can only achieve a limited resolution (and hence, limited SNR) due to timing constraints in digital circuits. Consequently, a specialized modulator structure based on noise shaping is presented and optimized which enables the creation of high-resolution switch control signals. This, together with the jitter reduction circuit, enables half-bridge output voltage SNR values of more than 100dB in an open-loop system.
Laboratorio Virtual para el Aprendizaje de Motores Asíncronos en Grados de Ingeniería

— Studies within the EHEA framework include the acquisition of skills such as the ability to learn autonomously, which requires students to devote much of their time to individual and group work to reinforce and further complement the knowledge acquired in the classroom. In order to consolidate the results obtained from classroom activities, lecturers must develop tools to encourage learning and facilitate the process of independent learning. The aim of this work is to present the use of virtual laboratories based on Easy Java Simulations to assist in the understanding and testing of electrical machines. con los usuarios integrándose fácilmente en plataformas de e-aprendizaje. Para nuestra aplicación hemos escogido el Java Ejs (Easy Java Simulations), ya que es una herramienta de software gratuita, diseñada para el desarrollo de laboratorios virtuales interactivos, dispone de elementos visuales parametrizables
Investigation of the Bioequivalence of Rosuvastatin 20 mg Tablets after a Single Oral Administration in Mediterranean Arabs Using a Validated LC-MS/MS Method

There is a wide inter-individual response to statin therapy including rosuvastatin calcium (RC), and it has been hypothesized that genetic differences may contribute to these variations. In fact, several studies have shown that pharmacokinetic (PK) parameters for RC are affected by race. The aim of this study is to demonstrate the interchangeability between two generic RC 20 mg film-coated tablets under fasting conditions among Mediterranean Arabs and to compare the pharmacokinetic results with Asian and Caucasian subjects from other studies. A single oral RC 20 mg dose, randomized, open-label, two-way crossover design study was conducted in 30 healthy Mediterranean Arab volunteers. Blood samples were collected prior to dosing and over a 72-h period. Concentrations in plasma were quantified using a validated liquid chromatography tandem mass spectrometry method. Twenty-six volunteers completed the study. Statistical comparison of the main PK parameters showed no significant difference between the generic and branded products. The point estimates (ratios of geometric mean %) were 107.73 (96.57-120.17), 103.61 (94.03-114.16), and 104.23 (94.84-114.54) for peak plasma concentration (Cmax), Area Under the Curve (AUC)0→last, and AUC0→∞, respectively. The 90% confidence intervals were within the pre-defined limits of 80%-125% as specified by the Food and Drug Administration and European Medicines Agency for bioequivalence studies. Both formulations were well-tolerated and no serious adverse events were reported. The PK results (AUC0→last and Cmax) were close to those of the Caucasian subjects. This study showed that the test and reference products met the regulatory criteria for bioequivalence following a 20 mg oral dose of RC under fasting conditions. Both formulations also showed comparable safety results. The PK results of the test and reference in the study subjects fall within the acceptable interval of 80%-125% and they were very close to the results among Caucasians. These PK results may be useful in order to determine the suitable RC dose among Arab Mediterranean patients.
Time-Location-Relationship Combined Service Recommendation Based on Taxi Trajectory Data

Recently, urban traffic management has encountered a paradoxical situation which is the empty carrying phenomenon for taxi drivers and the difficulty of taking a taxi for passengers. In this paper, through analyzing the quantitative relationship between passengers’ getting on and off taxis, we propose a time-location-relationship (TLR) combined taxi service recommendation model to improve taxi drivers’ profits, uncover the knowledge of human mobility patterns, and enhance passengers’ travel experience. Moreover, the TLR model uses Gaussian process regression and statistical approaches to acquire passenger volume, mean trip distance, and average trip time in functional regions during every period on weekdays and weekends, and allows drivers to pick up more passengers within a short time frame. Finally, we compare our proposed model with the autoregressive integrated moving average model, the back-propagation neural network model, the support vector machine model, and the gradient boost decision tree model by using the real taxi GPS data in Beijing. The experimental results show that our optimizing taxi service recommendation can predict more accurately than others by considering the 3-D properties.
litewi: A combined term extraction and entity linking method for eliciting educational ontologies from textbooks

Major efforts have been conducted on ontology learning, that is, semiautomatic processes for the construction of domain ontologies from diverse sources of information. In the past few years, a research trend has focused on the construction of educational ontologies, that is, ontologies to be used for educational purposes. The identification of the terminology is crucial to build ontologies. Term extraction techniques allow the identification of the domain-related terms from electronic resources. This paper presents LiTeWi, a novel method that combines current unsupervised term extraction approaches for creating educational ontologies for technology supported learning systems from electronic textbooks. LiTeWi uses Wikipedia as an additional information source. Wikipedia contains more than 30 million articles covering the terminology of nearly every domain in 288 languages, which makes it an appropriate generic corpus for term extraction. Furthermore, given that its content is available in several languages, it promotes both domain and language independence. LiTeWi is aimed at being used by teachers, who usually develop their didactic material from textbooks. To evaluate its performance, LiTeWi was tuned up using a textbook on object oriented programming and then tested with two textbooks of different domains—astronomy and molecular biology.
The application visualization system: a computational environment for scientific visualization

A software system for developing interactive scientific visualization applications quickly, with a minimum of programming effort, is described. This application visualization system (AVS) is an application framework targeted at scientists and engineers. The goal of the system is to make applications that combine interactive graphics and high computational requirements easier to develop for both programmers and nonprogrammers. AVS is designed around the concept of software building blocks, or modules, which can be interconnected to form visualization applications. AVS allows flow networks of existing modules to be constructed using a direct-manipulation user interface, and it automatically generates a simple user interface to each module.<<ETX>>
Energy-efficient signal acquisition in wireless sensor networks: a compressive sensing framework

The sampling rate of the sensors in wireless sensor networks (WSNs) determines the rate of its energy consumption since most of the energy is used in sampling and transmission. To save the energy in WSNs and thus prolong the network lifetime, we present a novel approach based on the compressive sensing (CS) framework to monitor 1-D environmental information in WSNs. The proposed technique is based on CS theory to minimize the number of samples taken by sensor nodes. An innovative feature of our approach is a new random sampling scheme that considers the causality of sampling, hardware limitations and the trade-off between the randomization scheme and computational complexity. In addition, a sampling rate indicator (SRI) feedback scheme is proposed to enable the sensor to adjust its sampling rate to maintain an acceptable reconstruction performance while minimizing the number of samples. A significant reduction in the number of samples required to achieve acceptable reconstruction error is demonstrated using real data gathered by a WSN located in the Hessle Anchorage of the Humber Bridge.
Psoriatic arthritis: correlation between imaging and pathology.

Psoriatic arthritis (PsA) is an archetypal type of spondyloarthritis, but may have some features of rheumatoid arthritis, namely a small joint polyarthritis pattern. Most of these features are well demonstrated on imaging, and as a result, imaging has helped us to better understand the pathophysiology of PsA. Although the unique changes of PsA such as the "pencil-in-cup" deformities and periostitis are commonly shown on conventional radiography, PsA affects all areas of joints, with enthesitis being the predominant pathology. Imaging, especially magnetic resonance imaging (MRI) and ultrasonography, has allowed us to explain the relationships between enthesitis, synovitis (or the synovio-entheseal complex) and osteitis or bone oedema in PsA. Histological studies have complemented the imaging findings, and have corroborated the MRI changes seen in the skin and nails in PsA. The advancement in imaging technology such as high-resolution "microscopy" MRI and whole-body MRI, and improved protocols such as ultrashort echo time, will further enhance our understanding of the disease mechanisms. The ability to demonstrate very early pre-clinical changes as shown by ultrasonography and bone scintigraphy may eventually provide a basis for screening for disease and will further improve the understanding of the link between skin and joint disease.
Use of the Pediatric Symptom Checklist in a low-income, Mexican American population.

To evaluate the usefulness of the Pediatric Symptom Checklist (PSC) in identifying behavioral problems in low-income, Mexican American children.



A cross-sectional study design was used to examine the PSC as a screening test, with the Child Behavior Checklist (CBCL) as the criterion standard.



The study was conducted at a health center in a diverse low-income community. Patients Eligible patients were children and adolescents, 4 to 16 years of age, who were seen for nonemergent, well-child care. Of 253 eligible children during a 9-month study period, 210 agreed to participate in the study. There was a 100% completion rate of the questionnaires. The average age of the children was 7.5 years, and 45% were female. Ninety-five percent of patients were of Hispanic descent (Mexican American); 86% of families spoke only Spanish. Socioeconomic status was low (more than three fourths of families earned <$20 000 annually).



The CBCL Total scale determined that 27 (13%) of the children had clinical levels of behavioral problems. With a cutoff score of 24, the PSC screened 2 (1%) of the 210 children as positive for behavioral problems. Using the CBCL as the criterion standard, the PSC sensitivity was 7.4%, and the specificity was 100%. Receiver operator characteristic analysis determined that a PSC cutoff score of 12 most correctly classified children with and without behavioral problems (sensitivity, 0.74; specificity, 0.94).



When using the PSC, a new cutoff score of 12 for clinical significance should be considered if screening low-income, Mexican American children for behavioral problems. Additional study is indicated to determine the causes of the PSC's apparently lower sensitivity in Mexican American populations.
A Classification for Business Model Types in E-commerce

Internet business models have been widely discussed in literature and applied within the last decade. Nevertheless, a clear understanding of some e-commerce concepts does not exist yet. The classification of business models in e-commerce is one of these areas. The current research tries to fill this gap through a conceptual and qualitative study. Nine main e-commerce business model types are selected from literature and analyzed to define the criteria and their sub-criteria (characteristics). As a result three different classifications for business models are determined. This study can be used to improve the understanding of essential functions, relations and mechanisms of existing e-commerce business models.
Title of Document : CONCUSSION : EXAMINING THE EFFECT OF NEURONAL OXIDATIVE STRESS ON THE PATHOPHYSIOLOGY OF BRAIN AND BLOOD BRAIN BARRIER CELLS

Neuronal stretching during concussion alters glucose transport and reduces neuronal viability, also affecting other cells in the brain and the Blood Brain Barrier (BBB). Our hypothesis is that oxidative stress (OS) generated in neurons during concussions contributes to this outcome. To validate this, we investigated: (1) whether OS independently causes alterations in brain and BBB cells, namely human neuron-like, neuroblastoma cells (NCs), astrocyte cells (ACs) and brain microvascular endothelial cells (ECs), and (2) whether OS originated in NCs (as in concussion) is responsible for causing the subsequent alterations observed in ACs and ECs. We used H2O2 treatment to mimic OS, validated by examining the resulting reactive oxygen species, and evaluated alterations in cell morphology, expression and localization of the glucose transporter GLUT1, and the overall cell viability. Our results showed that OS, either directly affecting each cell type or originally affecting NCs, caused changes in several morphological parameters (surface area, Feret diameter, circularity, inter-cellular distance), slightly varied GLUT1 expression and lowered the overall cell viability of all NCs, ACs, and ECs. Therefore, we can conclude that oxidative stress, which is known to be generated during concussion, caused alterations in NCs, ACs, and ECs whether independently originated in each cell or when originated in the NCs and could further propagate the ACs and ECs.  EXAMINING THE EFFECT OF NEURONAL OXIDATIVE STRESS ON THE PATHOPHYSIOLOGY OF BRAIN AND BLOOD BRAIN BARRIER CELLS