nils-herrmann/clean_scirepeval huggingface dataset:
An Ultra-Wideband Resistive-Feedback Low-Noise Amplifier with Noise Cancellation in 0.18μm Digital CMOS

We present a wideband resistive feedback CMOS low-noise amplifier (LNA) with noise cancellation technique for ultra-wideband applications. The LNA achieves a 3-dB bandwidth of 0.7-6.5 GHz, power gain of 12.5 dB, and noise figure of 3.5-4.2 dB within the 3-dB bandwidth. The input matching is better than -11 dB from 0.7 to 12 GHz. The IIP3 is measured -5 dBm at 5 GHz. It is implemented in a 0.18 mum standard digital CMOS technology, occupies an area of 0.78 mmtimes0.68 mm, and consumes 11.1 mW from a 1.8 V supply.
Valuating privacy

In several experimental auctions, participants put a dollar value on private information before revealing it to a group. An analysis of results show that a trait's desirability in relation to the group played a key role in the amount people demanded to publicize private information. Because people can easily obtain, aggregate, and disperse personal data electronically, privacy is a central concern in the information age. This concern is clear in relation to financial data and genetic information, both of which can lead to identity abuse and discrimination. However, other relatively harmless information can also be abused, including a person's gender, salary, age, marital status, or shopping preferences. What's unclear is whether it's the fear of such abuse that actually causes people's stated hesitance to reveal their data. Our hypothesis - and the motivation for our study - is that people reveal information when they feel that they're somewhat typical or positively atypical compared to the target group. To test this hypothesis, we conducted experiments that elicit the value people place on their private data. We found, with great significance (more than 95 percent statistical confidence) that a linear relationship exists between an individual's belief about a trait and the value he or she places on it. That is, the less desirable the trait, the greater the price a person demands for releasing the information. Furthermore, we found that small deviations in a socially positive direction are associated with a lower asking price.
Efficient navigation using slow feature gradients

A model of hierarchical Slow Feature Analysis (SFA) enables a mobile robot to learn a spatial representation of its environment directly from images captured during a random walk. After the unsupervised learning phase a subset of the resulting representations are orientation invariant and code for the position of the robot. Hence, they change monotonically over space even though the variation of the sensory signals received from the environment might change drastically e.g. during rotation on the spot. Furthermore, the property of spatial smoothness allows us to infer a navigation direction by taking the difference between the measurement at the current location and a measurement at a target location. In our work we investigated the use of slow feature representations, learned for a specific environment, for the purpose of navigation. We present a straightforward method for navigation using gradient descent on the difference between two points specified in slow feature space. Due to its slowness objective, the resulting slow feature representations implicitly encode information about static obstacles, allowing a mobile robot to efficiently circumnavigate them by simply following the steepest gradient in slow feature space.
Continuous word representation using neural networks for proper name retrieval from diachronic documents

Developing high-quality transcription systems for very large vocabulary corpora is a challenging task. Proper names are usually key to understanding the information contained in a document. One approach for increasing the vocabulary coverage of a speech transcription system is to automatically retrieve new proper names from contemporary diachronic text documents. In recent years, neural networks have been successfully applied to a variety of speech recognition tasks. In this paper, we investigate whether neural networks can enhance word representation in vector space for the vocabulary extension of a speech recognition system. This is achieved by using high-quality word vector representation of words from large amounts of unstructured text data proposed by Mikolov. This model allows to take into account lexical and semantic word relationships. Proposed methodology is evaluated in the context of broadcast news transcription. Obtained recall and ASR proper name error rate is compared to that obtained using cosine-based vector space methodology. Experimental results show a good ability of the proposed model to capture semantic and lexical information.
Malaysian E-government : Issues and Challenges in Public Administration

E-government has become part and parcel of every government’s agenda. Many governments have embraced its significant impacts and influences on governmental operations. As the technology mantra has become more ubiquitous, so government have decided to inaugurate e-government policy in its agencies and departments in order to enhance the quality of services, better transparency and greater accountability. As for Malaysia, the government is inspired by the wave of the e-government, as its establishment can improve the quality of public service delivery, and also its internal operations. This qualitative study will explore the status implementation of e-government initiatives as a case study, and will also provide a comparative evaluation of these findings, using the South Korean government as a benchmark study, given its outstanding performance in e-government. The findings of this study will highlight potential areas for improvement in relation to the public administration perspective and from this comparative approach too, Malaysia can learn some lessons from South Korea’s practices to ensure the success of e-government projects.
Neuroprotection by freezing ischemic penumbra evolution without cerebral blood flow augmentation with a postsynaptic density-95 protein inhibitor.

The purpose of this study was to determine whether neuroprotection is feasible without cerebral blood flow augmentation in experimental permanent middle cerebral artery occlusion.



Rats were subjected to permanent middle cerebral artery occlusion by the suture occlusion method and were treated 1 hour thereafter with a single 5-minute intravenous infusion of the postsynaptic density-95 protein inhibitor Tat-NR2B9c (7.5 mg/kg) or saline (n=8/group). Arterial spin-labeled perfusion-weighted MRI and diffusion weighted MRI were obtained with a 4.7-T Bruker system at 30, 45, 70, 90, 120, 150, and 180 minutes postmiddle cerebral artery occlusion to determine cerebral blood flow and apparent diffusion coefficient maps, respectively. At 24 hours, animals were neurologically scored (0 to 5), euthanized, and the brains stained with 2-3-5-triphenyl tetrazolium chloride to ascertain infarct volumes corrected for edema. Additionally, the effects of Tat-NR2B9c on adenosine 5'-triphosphate levels were measured in vitro in neurons subjected to oxygen-glucose deprivation.



Final infarct volume was decreased by 30.3% in the Tat-NR2B9c-treated animals compared with controls (P=0.028). There was a significant improvement in 24 hours neurological scores in the Tat-NR2B9c group compared with controls, 1.8±0.5 and 2.8±1.0, respectively (P=0.021). Relative to controls, Tat-NR2B9c significantly attenuated diffusion-weighted imaging lesion growth and preserved the diffusion-weighted imaging/perfusion-weighted imaging mismatch (ischemic penumbra) without affecting cerebral blood flow in the ischemic core or penumbra. Tat-NR2B9c treatment of primary neuronal cultures resulted in 26% increase in cell viability and 34% greater adenosine 5'-triphosphate levels after oxygen-glucose deprivation.



Preservation of adenosine 5'-triphosphate levels in vitro and neuroprotection in permanent middle cerebral artery occlusion in rats is achievable without cerebral blood flow augmentation using a postsynaptic density-95 protein inhibitor.
A noise-immune stylus analog front-end using adjustable frequency modulation and linear-interpolating data reconstruction for both electrically coupled resonance and active styluses

As the demand for intuitive and interactive displays is increasing in mobile devices such as smartphones and tablets, a pressure-sensitive stylus pen solution is needed for advanced user experiences [1-5].  10.4.1 compares electromagnetic resonance (EMR), active, and electrically coupled resonance (ECR) stylus systems, and shows cross-sectional views of sensor panels. EMR stylus systems have been successfully commercialized for high-end devices due to their battery-less, light, and pressure-sensing features [1-2]. However, EMR stylus systems require an extra sensing panel for electro-magnetic coupling. The active stylus system does not require the additional sensing panel but needs a battery located inside the stylus. On the other hand, ECR stylus systems are cost-effective without needing either the additional sensing panel or a built-in battery. Furthermore, ECR stylus systems measure pen pressure by sensing a stylus' resonant frequency change upon pressure without additional circuitry . Due to the external noise injection to the stylus system being more than ten times larger than the pen signal as shown in Fig. 10.4.1, noise immunity is a key performance factor for commercialization. This paper proposes an analog front-end (AFE) for both ECR and active stylus systems with high noise immunity that results in improved signal-to-noise ratio (SNR) by applying a fully differential architecture, adjustable frequency modulation (AFM), and linear-interpolating data reconstruction (LIDR).
Concept analysis: resilience.

This paper will systematically analyze the concept of resilience using an integrated review of literature. The historical perspective, attributes, antecedents, and consequences of resilience will be reviewed. A theoretical and operational definition will be provided. The Walker and Avant method will be used to describe the cases. Finally, the use of concept map will capture the relationships among the attributes, antecedents, consequences, and empirical indicators through clustering and chaining.
Online 3D acquisition and model integration

This paper presents a system which yields complete 3D models in a fast and inexpensive way. The major building blocks are a high-speed structured light range scanner and a registration module. The former generates ’raw’ range data whereas the latter performs a fast registration (ICP) and renders the partially integrated model as a preview of the final result. As the scanner uses only a single image to make a reconstruction, it is possible to scan while the object is moved. The use of an adaptive projection pattern gives a more robust behaviour. This allows the system to deal more easily with complicated geometry and texture than most other systems. During the scanning process the model is built up incrementally and rendered on the screen. This real-time visual feedback allows the user to check the current state of the 3D model. Holes or other flaws can be detected during the acquisition process itself. This speeds up the model building process, and solves indirectly the problem of view planning. The whole real-time pipeline comprising acquisition, merging and visualization only uses off-the-shel f hardware. A regular desktop PC connected to a camera and LCD projector is turned into a high-speed scanner and modeler. The current implementation has a throughput of approx. 5 fps.
Torque-Maximizing Design of Double-Stator, Axial-Flux, PM Machines Using Simple Non-Linear Magnetic Analysis

This paper presents a torque-maximizing design of a double-stator, axial-flux PM machine using a simple non-linear magnetic analysis. The proposed analysis consists of a geometric- flux-tube-based equivalent-magnetic-circuit model. The model can take into account not only the magnetic saturation but also the three-dimensional(3D) flux distribution. The proposed analysis has realized a dramatic reduction in the computation time compared to 3D-FEA, keeping reasonable analytical accuracy. At first, the validity of the proposed analysis is examined for the various design parameters. After verifying the accuracy of the torque computation of the proposed analysis through the comparisons with 3D-FEA, an 8-pole axial-flux PM machine with double-stator-single-rotor is optimally designed. The performance of the optimized motor are finally verified by 3D-FEA.
Transcultural medicine: a multi-sited ethnography on the scientific-industrial networking of Korean medicine.

Through a multi-sited ethnography of three different types of organization--a traditional medical clinic, two laboratories, and a biotech company--this article examines how Korean medicine (KM) scientizes, globalizes, and industrializes its clinical knowledge. By tracing the complex networking process among multiple places, I aim to understand how KM reinvents its knowledge, identity, and boundaries in a global situation. In particular, I pay attention to how this process involves multiple dimensions of power relations, economic interests, and scientific authorities. This article concludes that heterogeneous and unequal encounters between KM, science, and industry lead to simultaneous productions of new culture and power without reducing them to a single logic or center in a global age.
The generic model query language GMQL - Conceptual specification, implementation, and runtime evaluation

The generic model query language GMQL is designed to query collections of conceptual models created in arbitrary graph-based modelling languages. Querying conceptual models means searching for particular model subgraphs that comply with a predefined pattern query. Such a query specifies the structural and semantic properties of the model language from the literature and formally specify the language’s syntax and semantics. We conduct an analysis of GMQL's theoretical and practical runtime performance concluding that it returns query results within satisfactory time. Given its generic nature, GMQL contributes to a broad range of different model analysis scenarios ranging from business process compliance management to model translation and business process weakness detection. As GMQL returns results with acceptable runtime performance, it can be used to query large collections of hundreds or thousands of conceptual models containing not only process models, but also data models or organizational charts. In this paper, we furthermore evaluate GMQL against the backdrop of existing query approaches thereby carving out its advantages and limitations as well as pointing toward future research.
Diabetes management in the primary care setting: a comparison of physicians' performance by gender.

A major shift in the gender of the medical-doctor workforce is now underway, and all over the world it is expected that an average 65% of the medical workforce will be women by 2030. In addition, an aging population means that chronic diseases, such as diabetes, are becoming more prevalent and the demand for care is rising. There is growing evidence of female physicians performing better than male physicians.AimOur study aimed to investigate whether any differences in diabetes process indicators are associated with gender, and/or the interaction between gender and different organizational models.Design and settingA population-based cross-sectional analysis was conducted on a large data set obtained by processing the public health administration databases of seven Italian local health units (LHUs). The seven LHUs, distributed all over the Italian peninsula in seven different regions, took part in a national project called MEDINA, with the focus on chronic disease management in primary care (PC).



A total score was calculated for the average performance in the previously listed five indicators, representing global adherence to a quality management of patients with diabetes. A multilevel analysis was applied to see how LHUs affected the outcome. A quantile regression model was also fitted.



Our study included 2287 Italian general practitioners (586 of them female) caring for a total of 2 646 059 patients. Analyzing the performance scores confirmed that female general practitioners obtained better results than males. The differences between males and females were stronger on the 25th and 75th percentiles of the score than on the median values. The interaction between gender and LHU was not significant.



Our study evidenced that female physicians perform better than males in providing PC for diabetes independently by the different organizational models. Further research to understand the reasons for these gender differences is needed.
Nonlinear Dynamics of Spring Softening and Hardening in Folded-MEMS Comb Drive Resonators

This paper studies analytically and numerically the spring softening and hardening phenomena that occur in electrostatically actuated microelectromechanical systems comb drive resonators utilizing folded suspension beams. An analytical expression for the electrostatic force generated between the combs of the rotor and the stator is derived and takes into account both the transverse and longitudinal capacitances present. After formulating the problem, the resulting stiff differential equations are solved analytically using the method of multiple scales, and a closed-form solution is obtained. Furthermore, the nonlinear boundary value problem that describes the dynamics of inextensional spring beams is solved using straightforward perturbation to obtain the linear and nonlinear spring constants of the beam. The analytical solution is verified numerically using a Matlab/Simulink environment, and the results from both analyses exhibit excellent agreement. Stability analysis based on phase plane trajectory is also presented and fully explains previously reported empirical results that lacked sufficient theoretical description. Finally, the proposed solutions are, once again, verified with previously published measurement results. The closed-form solutions provided are easy to apply and enable predicting the actual behavior of resonators and gyroscopes with similar structures.
Detecting Interesting Event Sequences for Sports Reporting

This technique works for rolls, and could be used as a baseline and a starting point for a stochastic reranking approach, taking, say, the top 30%, and reranking them based on additional local score context. However, the results are not as promising for struggles; this is probably because struggles tend to be in games with a generally flat curve. One possible alternative is to use a different score-related measure, e.g., a matrix of lead changes per time period. A second is to compare intervals with other intervals of the same duration in all games, rather than in the same game.
Modified dual band gysel power divider with isolation bandwidth improvement

This paper presents a new design of a dual band power divider with high power handling capability and isolation bandwidth improvement, which contains six branch line sections, two grounded resistors, one resistor between output ports, an extension line at the input, and a single stub line at the end. Exact closed-form equations are derived for the proposed structure using even-mode and odd-mode analysis. In this design, flexibility in choosing two grounded resistors enables us to determine the frequency ratio range, bandwidth of the circuit, and the level of power handling capability. In addition, line admittance analysis shows that the proposed structure can support the acceptable frequency ratio range. For verification, the proposed structure is simulated, fabricated and measured using microstrip lines. Simulation and measurement results show wide isolation bandwidth, while maintaining high power handling capability over the Wilkinson power divider.
Using MPTCP subflow association control for heterogeneous wireless network optimization

Multipath TCP (MPTCP) was designed to increase the throughput and reliability of TCP, with specific motivation coming from scenarios including data center and cloud computing. The use of MPTCP has been recently explored to support heterogeneous wireless networks (HetNets) involving hosts that have multiple network interfaces. However, current solutions generally involve many simplifying assumptions. In this paper, we propose a new framework to collect scheduling information from various scheduling network entities and conduct optimization from a global view. The framework uses the existing or readily accessible MPTCP parameters. Under this framework, we introduce a centralized optimization algorithm to realize general proportional fairness of user throughput. Based on results from NS3 simulations, we provide evidence that the approach provides a low cost solution for improved performance from the perspectives of both applications and network operators.
Discovery is never by chance: designing for (un)serendipity

Serendipity has a long tradition in the history of science as having played a key role in many significant discoveries. Computer scientists, valuing the role of serendipity in discovery, have attempted to design systems that encourage serendipity. However, that research has focused primarily on only one aspect of serendipity: that of chance encounters. In reality, for serendipity to be valuable chance encounters must be synthesized into insight. In this paper we show, through a formal consideration of serendipity and analysis of how various systems have seized on attributes of interpreting serendipity, that there is a richer space for design to support serendipitous creativity, innovation and discovery than has been tapped to date. We discuss how ideas might be encoded to be shared or discovered by 'association-hunting' agents. We propose considering not only the inventor's role in perceiving serendipity, but also how that inventor's perception may be enhanced to increase the opportunity for serendipity. We explore the role of environment and how we can better enable serendipitous discoveries to find a home more readily and immediately.
Simple real-time QRS detector with the MaMeMi filter

Detection of QRS complexes in ECG signals is required to determine heart rate, and it is an important step in the study of cardiac disorders. ECG signals are usually affected by noise of low and high frequency. To improve the accuracy of QRS detectors several methods have been proposed to filter out the noise and detect the characteristic pattern of QRS complex. Most of the existing methods are at a disadvantage from relatively high computational complexity or high resource needs making them less optimized for its eywords: onlinear filters iomedical signal processing RS detection eal-time systems mbedded software implementation on portable embedded systems, wearable devices or ultra-low power chips. We present a new method to detect the QRS signal in a simple way with minimal computational cost and resource needs using a novel non-linear filter.