nils-herrmann/clean_scirepeval huggingface dataset:
Dual-polarity floating battery for class AB output stages with accurate quiescent current control

A new dual-polarity floating battery with accurate quiescent current control for Class AB output stages is presented. The proposed circuit has the capability to operate at very low voltages, close to the threshold voltage of a transistor. It can also operate at very high voltages with accurate quiescent current control and minimum power dissipation. Simulation results of this structure verifying the described operation are provided.
Emergent Behaviors in Mixed-Autonomy Traffic

Traffic dynamics are often modeled by complex dynamical systems for which classical analysis tools can struggle to provide tractable policies used by transportation agencies and planners. In light of the introduction of automated vehicles into transportation systems, there is a new need for understanding the impacts of automation on transportation networks. The present article formulates and approaches the mixed-autonomy traffic control problem (where both automated and human-driven vehicles are present) using the powerful framework of deep reinforcement learning (RL). The resulting policies and emergent behaviors in mixed-autonomy traffic settings provide insight for the potential for automation of traffic through mixed fleets of automated and manned vehicles. Modelfree learning methods are shown to naturally select policies and behaviors previously designed by model-driven approaches, such as stabilization and platooning, known to improve ring road efficiency and to even exceed a theoretical velocity limit. Remarkably, RL succeeds at maximizing velocity by effectively leveraging the structure of the human driving behavior to form an efficient vehicle spacing for an intersection network. We describe our results in the context of existing control theoretic results for stability analysis and mixed-autonomy analysis. This article additionally introduces state equivalence classes to improve the sample complexity for the learning methods.
Solving Mastermind Using Genetic Algorithms

The MasterMind game involves decoding a secret code. The classic game is a code of six possible colors in four slots. The game has been analyzed and optimal strategies have been posed by computer scientists and mathematicians. In this paper we will survey previous work done on solving MasterMind, including several approaches using Genetic Algorithms. We will also analyze the solution sets and compare our results using a novel scoring system inside a GA against previous work using Genetic and Heuristic algorithms. Our GA is performing closer to optimal then previously published work. The GA we present is a Steady State GA using Fitness Proportional Reproduction (FPR), where the fitness function incorporates a simple heuristic algorithm. We also present a scoring method that is simpler then those used by other researchers. In larger games such as 10 colors and 8 slots our GA clearly outperform the heuristic algorithm. In fact if one wishes to tradeoff a higher average number of guesses to a faster running time, extremely large games such as 12 x10 can be solved in a reasonable time (i.e. minutes) of run time.
A 0–55-GHz Coplanar Waveguide to Coplanar Strip Transition

A broadband coplanar waveguide (CPW) to coplanar strip (CPS) transmission line transition directly integrated with an RF microelectromechanical systems reconfigurable multiband antenna is presented in this paper. This transition design exhibits very good performance up to 55 GHz, and uses a minimum number of dissimilar transmission line sections and wire bonds, achieving a low-loss and low-cost balancing solution to feed planar antenna designs. The transition design methodology that was followed is described and measurement results are presented.
Power Integrity Analysis of a 28 nm Dual-Core ARM Cortex-A57 Cluster Using an All-Digital Power Delivery Monitor

This paper presents a power delivery monitor (PDM) peripheral integrated in a flip-chip packaged 28 nm system-on-chip (SoC) for mobile computing. The PDM is composed entirely of digital standard cells and consists of: 1) a fully integrated VCO-based digital sampling oscilloscope; 2) a synthetic current load; and 3) an event engine for triggering, analysis, and debug. Incorporated inside an SoC, it enables rapid, automated analysis of supply impedance, as well as monitoring supply voltage droop of multi-core CPUs running full software workloads and during scan-test operations. To demonstrate these capabilities, we describe a power integrity case study of a dual-core ARM Cortex-A57 cluster in a commercial 28 nm mobile SoC. Measurements are presented of power delivery network (PDN) electrical parameters, along with waveforms of the CPU cluster running test cases and benchmarks on bare metal and Linux OS. The effect of aggressive power management techniques, such as power gating on the dominant resonant frequency and peak impedance, is highlighted. Finally, we present measurements of supply voltage noise during various scan-test operations, an often-neglected aspect of SoC power integrity.
Argumentation mining

Argumentation mining aims to automatically detect, classify and structure argumentation in text. Therefore, argumentation mining is an important part of a complete argumentation analyisis, i.e. understanding the content of serial arguments, their linguistic structure, the relationship between the preceding and following arguments, recognizing the underlying conceptual beliefs, and understanding within the comprehensive coherence of the specific topic. We present different methods to aid argumentation mining, starting with plain argumentation detection and moving forward to a more structural analysis of the detected argumentation. Different state-of-the-art techniques on machine learning and context free grammars are applied to solve the challenges of argumentation mining. We also highlight fundamental questions found during our research and analyse different issues for future research on argumentation mining.
Men’s Partner-Directed Insults and Sexual Coercion in Intimate Relationships

Women who have been sexually coerced by an intimate partner experience many negative health consequences. Recent research has focused on predicting this sexual coercion. In two studies, we investigated the relationship between men’s use of partner-directed insults and sexually coercive behaviors in the context of intimate relationships. Study 1 secured self-reports from 247 men on the Partner-Directed Insults Scale and the Sexual Coercion in Intimate Relationships Scale. Study 2 obtained partner-reports from 378 women on the same measures. Across both studies, results indicate that men’s use of sexually coercive behaviors can be statistically predicted by the frequency and content of the insults that men direct at their intimate partner. Insults derogating a partner’s value as a person and accusing a partner of sexual infidelity were most useful in predicting sexual coercion. The discussion notes limitations of the current research and highlights directions for future research.
A Lower Bound for the Optimization of Finite Sums

This paper presents a lower bound for optimizing a finite sum of n functions, where each function is L-smooth and the sum is μ-strongly convex. We show that no algorithm can reach an error ε in minimizing all functions from this class in fewer than Ω(n+ √ n(κ−1) log(1/ε)) iterations, where κ = L/μ is a surrogate condition number. We then compare this lower bound to upper bounds for recently developed methods specializing to this setting. When the functions involved in this sum are not arbitrary, but based on i.i.d. random data, then we further contrast these complexity results with those for optimal first-order methods to directly optimize the sum. The conclusion we draw is that a lot of caution is necessary for an accurate comparison, and identify machine learning scenarios where the new methods help computationally.
CAR-Net: Clairvoyant Attentive Recurrent Network

We present an interpretable framework for path prediction that leverages dependencies between agents’ behaviors and their spatial navigation environment. We exploit two sources of information: the past motion trajectory of the agent of interest and a wide top-view image of the navigation scene. We propose a Clairvoyant Attentive Recurrent Network (CAR-Net) that learns where to look in a large image of the scene when solving the path prediction task. Our method can attend to any area, or combination of areas, within the raw image (e.g., road intersections) when predicting the trajectory of the agent. This allows us to visualize fine-grained semantic elements of navigation scenes that influence the prediction of trajectories. To study the impact of space on agents’ trajectories, we build a new dataset made of top-view images of hundreds of scenes  One racing tracks) where agents’ behaviors are heavily influenced by known areas in the images (e.g., upcoming turns). CAR-Net successfully attends to these salient regions. Additionally, CAR-Net reaches state-of-the-art accuracy on the standard trajectory forecasting benchmark, Stanford Drone Dataset (SDD). Finally, we show CAR-Net’s ability to generalize to unseen scenes.
Preventing Reading Difficulties in Young Children

Suggesting that empirical work in the field of reading has advanced sufficiently to allow substantial agreed-upon results and conclusions, this literature review cuts through the detail of partially convergent, sometimes discrepant research findings to provide an integrated picture of how reading develops and how reading instruction should proceed. The focus of the review is prevention. Sketched is a picture of the conditions under which reading is most likely to develop easily--conditions that include stimulating preschool environments, excellent reading instruction, and the absence of any of a wide array of risk factors. It also provides recommendations for practice as well as recommendations for further research. After a preface and executive summary, chapters are (1) Introduction; (2) The Process of Learning to Read; (3) Who Has Reading Difficulties; (4) Predic:ors of Success and Failure in Reading; (5) Preventing Reading Difficulties before Kindergarten; (6) Instructional Strategies for Kindergarten and the Primary Grades; (7) Organizational Strategies for Kindergarten and the Primary Grades; (8) Helping Children with Reading Difficulties in Grades 1 to 3; (9) The Agents of Change; and (10) Recommendations for Practice and Research. Contains biographical sketches of the committee members and an index. Contains approximately 800 references.
Lidocaine gel as an anesthetic protocol for nasogastric tube insertion in the ED.

The aim of the study was to evaluate the efficacy of topical 2% lidocaine gel in reducing pain and discomfort associated with nasogastric tube insertion (NGTI) and compare lidocaine to ordinary lubricant gel in the ease in carrying out the procedure.



This prospective, randomized, double-blind, placebo-controlled, convenience sample trial was conducted in the emergency department of our tertiary care university-affiliated hospital. Five milliliters of 2% lidocaine gel or placebo lubricant gel were administered nasally to alert hemodynamically stable adult patients 5 minutes before undergoing a required NGTI. The main outcome measures were overall pain, nasal pain, discomfort (eg, choking, gagging, nausea, vomiting), and difficulty in performing the procedure. Standard comparative statistical analyses were used.



The study cohort included 62 patients (65% males). Thirty-one patients were randomized to either lidocaine or placebo groups. Patients who received lidocaine reported significantly less intense overall pain associated with NGTI compared to those who received placebo (37 ± 28 mm vs 51 ± 26 mm on 100-mm visual analog scale; P < .05). The patients receiving lidocaine also had significantly reduced nasal pain (33 ± 29 mm vs 48 ± 27 mm; P < .05) and significantly reduced sensation of gagging (25 ± 30 mm vs 39 ± 24 mm; P < .05). However, conducting the procedure was significantly more difficult in the lidocaine group (2.1 ± 0.9 vs 1.4 ± 0.7 on 5-point Likert scale; P < .05).



Lidocaine gel administered nasally 5 minutes before NGTI significantly reduces pain and gagging sensations associated with the procedure but is associated with more difficult tube insertion compared to the use of lubricant gel.
Learning DTW-Shapelets for Time-Series Classification

Shapelets are discriminative patterns in time series, that best predict the target variable when their distances to the respective time series are used as features for a classifier. Since the shapelet is simply any time series of some length less than or equal to the length of the shortest time series in our data set, there is an enormous amount of possible shapelets present in the data. Initially, shapelets were found by extracting numerous candidates and evaluating them for their prediction quality. Then, Grabocka et al.  proposed a novel approach of learning time series shapelets called LTS. A new mathematical formalization of the task via a classification objective function was proposed and a tailored stochastic gradient learning was applied. It enabled learning near-to-optimal shapelets without the overhead of trying out lots of candidates. The Euclidean distance measure was used as distance metric in the proposed approach. As a limitation, it is not able to learn a single shapelet, that can be representative of different subsequences of time series, which are just warped along time axis. To consider these cases, we propose to use Dynamic Time Warping (DTW) as a distance measure in the framework of LTS. The proposed approach was evaluated on 11 real world data sets from the UCR repository and a synthetic data set created by ourselves. The experimental results show that the proposed approach outperforms the existing methods on these data sets.
A smoke detection algorithm based on K-means segmentation

The fire accident usually causes economical and ecological damage as well as cause danger to people's lives. Therefore, its early detection is must for controlling this damage. Also smoke is considered as main constituent of fire, thus an efficient smoke detection algorithm on sequences of frame obtained from static camera is proposed. It is based on computer vision based technology. This algorithm uses color feature of smoke & is comprised of following steps: reading the image, preprocessing, classify color pixels using k-means segmentation. This paper discusses mainly the segmentation problem. It adopts L*a*b* color space and k-means clustering algorithm to isolate the smoke from video sequences. Finally the K-means algorithm used is compared with the fuzzy c-means algorithm used previously.
Recent Research on Febrile Seizures: A Review

Febrile seizures are common and mostly benign. They are the most common cause of seizures in children less than five years of age. There are two categories of febrile seizures, simple and complex. Both the International League against Epilepsy and the National Institute of Health has published definitions on the classification of febrile seizures. Simple febrile seizures are mostly benign, but a prolonged (complex) febrile seizure can have long term consequences. Most children who have a febrile seizure have normal health and development after the event, but there is recent evidence that suggests a small subset of children that present with seizures and fever may have recurrent seizure or develop epilepsy. This review will give an overview of the definition of febrile seizures, epidemiology, evaluation, treatment, outcomes and recent research.
Applying The CHAID Algorithm to Analyze How Achievement is Influenced by University Students' Demographics, Study Habits, and Technology

The purpose of this study is to analyze three separate constructs (demographics, study habits, and technology familiarity) that can be used to identify university students’ characteristics and the relationship between each of these constructs with student achievement. A survey method was used for the current study, and the participants included 2,949 university students from 11 faculties of a public university in Turkey. A survey was used to collect data, and the data were analyzed using the chi-squared automatic interaction detection (CHAID) algorithm. The results of the study revealed that female students are significantly more successful than male students. In addition, the more introverted students, whether male or female, have higher grade point averages (GPAs) than those students who are more extroverted. Furthermore, male students who use the Internet more than 22 hours per week and use the Internet for up to six different aims have the lowest GPAs among all students, while female students who use the Internet for up to 21 hours per week have the highest GPAs among all students. The implications of these findings are also discussed herein.
Estimating the prevalence of limb loss in the United States: 2005 to 2050.

To estimate the current prevalence of limb loss in the United States and project the future prevalence to the year 2050.



Estimates were constructed using age-, sex-, and race-specific incidence rates for amputation combined with age-, sex-, and race-specific assumptions about mortality. Incidence rates were derived from the 1988 to 1999 Nationwide Inpatient Sample of the Healthcare Cost and Utilization Project, corrected for the likelihood of reamputation among those undergoing amputation for vascular disease. Incidence rates were assumed to remain constant over time and applied to historic mortality and population data along with the best available estimates of relative risk, future mortality, and future population projections. To investigate the sensitivity of our projections to increasing or decreasing incidence, we developed alternative sets of estimates of limb loss related to dysvascular conditions based on assumptions of a 10% or 25% increase or decrease in incidence of amputations for these conditions.



Community, nonfederal, short-term hospitals in the United States.



Persons who were discharged from a hospital with a procedure code for upper-limb or lower-limb amputation or diagnosis code of traumatic amputation.



Not applicable.



Prevalence of limb loss by age, sex, race, etiology, and level in 2005 and projections to the year 2050.



In the year 2005, 1.6 million persons were living with the loss of a limb. Of these subjects, 42% were nonwhite and 38% had an amputation secondary to dysvascular disease with a comorbid diagnosis of diabetes mellitus. It is projected that the number of people living with the loss of a limb will more than double by the year 2050 to 3.6 million. If incidence rates secondary to dysvascular disease can be reduced by 10%, this number would be lowered by 225,000.



One in 190 Americans is currently living with the loss of a limb. Unchecked, this number may double by the year 2050.
Bioelectrical impedance analysis-part II: utilization in clinical practice.

BIA is easy, non-invasive, relatively inexpensive and can be performed in almost any subject because it is portable. Part II of these ESPEN guidelines reports results for fat-free mass (FFM), body fat (BF), body cell mass (BCM), total body water (TBW), extracellular water (ECW) and intracellular water (ICW) from various studies in healthy and ill subjects. The data suggests that BIA works well in healthy subjects and in patients with stable water and electrolytes balance with a validated BIA equation that is appropriate with regard to age, sex and race. Clinical use of BIA in subjects at extremes of BMI ranges or with abnormal hydration cannot be recommended for routine assessment of patients until further validation has proven for BIA algorithm to be accurate in such conditions. Multi-frequency- and segmental-BIA may have advantages over single-frequency BIA in these conditions, but further validation is necessary. Longitudinal follow-up of body composition by BIA is possible in subjects with BMI 16-34 kg/m(2) without abnormal hydration, but must be interpreted with caution. Further validation of BIA is necessary to understand the mechanisms for the changes observed in acute illness, altered fat/lean mass ratios, extreme heights and body shape abnormalities.
A Fluxgate Current Sensor With an Amphitheater Busbar

Large dc and ac electric currents are often measured by open-loop sensors without a magnetic yoke. A widely used configuration uses a differential magnetic sensor inserted into a hole in a flat busbar. The use of a differential sensor offers the advantage of partial suppression of fields coming from external currents. Hall sensors and AMR sensors are currently used in this application. In this paper, we present a current sensor of this type that uses novel integrated fluxgate sensors, which offer a greater range than magnetoresistors and better stability than Hall sensors. The frequency response of this type of current sensor is limited due to the eddy currents in the solid busbar. We present a novel amphitheater geometry of the hole in the busbar of the sensor, which reduces the frequency dependence from 15% error at 1 kHz to 9%.
Tactile sensing in intelligent robotic manipulation - a review

A tactile sense is key to advanced robotic grasping and manipulation. By touching an object it is possible to measure contact properties such as contact forces, torques, and contact position. From these, we can estimate object properties such as geometry, stiffness, and surface condition. This information can then be used to control grasping or manipulation, to detect slip, and also to create or improve object models. This paper presents an overview of tactile sensing in intelligent robotic manipulation. The history, the common issues, and applications are reviewed. Sensor performance is briefly discussed and compared to the human tactile sense. Advantages and disadvantages of the most common sensor approaches are discussed. Some examples are given of sensors widely available today. Eventually the state of the art in applying tactile sensing experimentally is presented.
Cadaveric simulation of a pes cavus foot.

The pes cavus deformity has been well described in the literature; relative bony positions have been determined and specific muscle imbalances have been summarized. However, we are unaware of a cadaveric model that has been used to generate this foot pathology. The purpose of this study was to create such a model for future work on surgical and conservative treatment simulation.



We used a custom designed, pneumatically actuated loading frame to apply forces to otherwise normal cadaveric feet while measuring bony motion as well as force beneath the foot. The dorsal tarsometatarsal and the dorsal intercuneiform ligaments were attenuated and three muscle imbalances, each similar to imbalances believed to cause the pes cavus deformity, were applied while bony motion and plantar forces were measured.



Only one of the muscle imbalances (overpull of the Achilles tendon, tibialis anterior, tibialis posterior, flexor hallucis longus and flexor digitorum longus) was successful at consistently generating the changes seen in pes cavus feet. This imbalance led to statistically significant changes including hindfoot inversion, talar dorsiflexion, medial midfoot plantar flexion and inversion, forefoot plantar flexion and adduction and an increase in force on the lateral mid- and forefoot.



We have created a cadaveric model that approximates the general changes of the pes cavus deformity compared to normal feet. These changes mirror the general patterns of deformity produced by several disease mechanisms.



Future work will entail increasing the severity of the model and exploring various pes cavus treatment strategies.