nils-herrmann/clean_scirepeval huggingface dataset:
Reliable Communication in the Presence of Failures

The design and correctness of a communication facility for a distributed computer system are reported on. The facility provides support for fault-tolerant process groups in the form of a family of reliable multicast protocols that can be used in both local- and wide-area networks. These protocols attain high levels of concurrency, while respecting application-specific delivery ordering constraints, and have varying cost and performance that depend on the degree of ordering desired. In particular, a protocol that enforces causal delivery orderings is introduced and shown to be a valuable alternative to conventional asynchronous communication protocols. The facility also ensures that the processes belonging to a fault-tolerant process group will observe consistent orderings of events affecting the group as a whole, including process failures, recoveries, migration, and dynamic changes to group properties like member rankings. A review of several uses for the protocols in the ISIS system, which supports fault-tolerant resilient objects and bulletin boards, illustrates the significant simplification of higher level algorithms made possible by our approach.
Combining structural and timing errors in overclocked inexact speculative adders

Worst-case design is used in IoT devices and high performance data centers to ensure reliability, leading to a power efficiency loss. Recently, approximate computing has been proposed to trade off accuracy for efficiency. In this paper, we use Inexact Speculative Adders, which redesign the adder architecture to shorten its critical path and improve performance, but introduces controlled structural errors. On the other hand, overclocking is used to reduce conservative timing guardbands but could normally introduce catastrophic timing errors, we thus apply a supervised learning model to overclock speculative adders and predict their timing errors. We build a methodology to combine both structural and timing errors and analyze how they interplay with each other to limit the overal errors.
GeoSocialBound: an efficient framework for estimating social POI boundaries using spatio-textual information

In this paper, we present a novel framework for estimating social point-of-interest (POI) boundaries, also termed GeoSocialBound, utilizing spatio--textual information based on geo-tagged tweets. We first start by defining a social POI boundary as one small-scale cluster containing its POI center, geographically formed with a convex polygon. Motivated by an insightful observation with regard to estimation accuracy, we formulate a constrained optimization problem, in which we are interested in finding the radius of a circle such that a newly defined objective function is maximized. To solve this problem, we introduce an efficient optimal estimation algorithm whose runtime complexity is linear in the number of geo-tags in a dataset. In addition, we empirically evaluate the estimation performance of our GeoSocialBound algorithm for various environments and validate the complexity analysis. As a result, vital information on how to obtain real-world GeoSocialBounds with a high degree of accuracy is provided.
Classification of ventilator modes: update and proposal for implementation.

Ventilator manufacturers and the respiratory care academic community have not yet adopted a standardized system for classifying and describing ventilation modes. As a result, there is enough confusion that potential sales, education, and patient care are all put at risk. This proposal summarizes a ventilator-mode classification scheme and complete lexicon that has been extensively published over the last 15 years. Specifically, the classification system has 3 components: (1) a description of the breathing pattern and control variables within breaths, (2) a description of control type used within and between breaths, (3) a detailed description of adjunctive operational algorithms. This 3-level specification provides scalability of detail to make the mode description appropriate for the particular need. At the bedside we need only refer to a mode briefly using the first component. To distinguish between similar modes and brand names we would need to use at least the first and second components. For a complete and unique mode specification (as in an operator's manual) we would use all 3 components. The classification system proposed in this article uses the equation of motion for the respiratory system as the underlying theoretical framework. All terms relevant to describing ventilation modes are defined in an extensive glossary.
The interaction of cigarette smoking and antioxidants. Part I: diet and carotenoids.

It is logical that the requirement for antioxidant nutrients depends on a person's exposure to endogenous and exogenous reactive oxygen species. Since cigarette smoking results in an increased cumulative exposure to reactive oxygen species from both sources, it would seem cigarette smokers would have an increased requirement for antioxidant nutrients. Logic dictates that a diet high in antioxidant-rich foods such as fruits, vegetables, and spices would be both protective and a prudent preventive strategy for smokers. This review examines available evidence of fruit and vegetable intake, and supplementation of antioxidant compounds by smokers in an attempt to make more appropriate nutritional recommendations to this population.
Effective Multi-step Temporal-Difference Learning for Non-Linear Function Approximation

Multi-step temporal-difference (TD) learning, where the update targets contain information from multiple time steps ahead, is one of the most popular forms of TD learning for linear function approximation. The reason is that multi-step methods often yield substantially better performance than their single-step counter-parts, due to a lower bias of the update targets. For non-linear function approximation, however, single-step methods appear to be the norm. Part of the reason could be that on many domains the popular multi-step methods TD(λ) and Sarsa(λ) do not perform well when combined with non-linear function approximation. In particular, they are very susceptible to divergence of value estimates. In this paper, we identify the reason behind this. Furthermore, based on our analysis, we propose a new multi-step TD method for non-linear function approximation that addresses this issue. We confirm the effectiveness of our method using two benchmark tasks with neural networks as function approximation.
Comparison of stability of two kinds of sacro-iliac screws in the fixation of bilateral sacral fractures in a finite element model.

To compare the stability of lengthened sacro-iliac screw and sacro-iliac screw for the treatment of bilateral vertical sacral fractures to provide reference for clinical application.



A finite element model of Tile C pelvic ring injury (bilateral type Denis II fracture of sacrum) was produced. (Tile and Denis are surgeons, who put forward the classifications of pelvic ring injury and sacral fracture respectively.) The bilateral sacral fractures were fixed with a lengthened sacro-iliac screw and a sacro-iliac screw in seven types of models, respectively. The translation and angular displacement of the superior surface of the sacrum in the case of standing on both feet were measured and compared.



The stability of one lengthened sacro-iliac screw fixation in the S1 or S2 segment is superior to that of two bidirectional sacro-iliac screws in the same sacral segment; the stability of one lengthened sacro-iliac screw fixation in S1 and S2 segments, respectively, is superior to that of two bidirectional sacro-iliac screw fixation in S1 and S2 segments, respectively; the stability of one lengthened sacro-iliac screw fixation in S1 and S2 segments, respectively, is superior to that of one lengthened sacro-iliac screw fixation in the S1 or S2 segment; the stability of two bidirectional sacro-iliac screw fixation in S1 and S2 segments, respectively, is markedly superior to that of two bidirectional sacro-iliac screw fixation in the S1 or S2 segment and is also markedly superior to that of one sacro-iliac screw fixation in the S1 segment and one sacro-iliac screw fixation in the S2 segment; the vertical stability of the lengthened sacro-iliac screw or the sacro-iliac screw fixation in S2 is superior to that of S1. The rotational stability of the lengthened sacro-iliac screw or sacro-iliac screw fixation in S1 is superior to that of S2.



S1 and S2 lengthened sacro-iliac screws should be used for the fixation in bilateral sacral fractures of Tile C pelvic ring injury as far as possible and the most stable fixation is the combination of the lengthened sacro-iliac screws of S1 and S2 segments. Even if lengthened sacro-iliac screws cannot be used due to limited conditions, two bidirectional sacro-iliac screw fixation in S1 and S2 segments, respectively, is recommended. No matter which kind of sacro-iliac screw is applied, the fixation combination of S1 and S2 segments is strongly recommended to maximise the stability of the pelvic posterior ring.
Annotating evidence-based argumentation in biomedical text

A new challenge in natural language processing, argumentation mining is the automatic identification of an argument's premises, conclusion, and argumentation scheme, and relationships between arguments. Argumentation mining could provide critical context for information extraction and question answering and support new forms of summarization and citation indexing. However, argumentation mining, in this sense, has not yet been addressed in BioNLP. This theoretical paper contributes towards annotation of argumentation in biomedical/biological corpora. We show that argumentative zone models and models of discourse coherence do not represent the same aspects of discourse as a model of evidence-based argumentation. We explore the challenges of annotation of argumentation in full-text biomedical articles and describe the steps we have taken towards annotating a biomedical corpus for argumentation mining research.
Parameter Estimation for Single Diode Models of Photovoltaic Modules

Many popular models for photovoltaic system performance employ a single diode model to compute the I-V curve for a module or string of modules at given irradiance and temperature conditions. A single diode model requires a number of parameters to be estimated from measured I-V curves. Many available parameter estimation methods use only short circuit, open circuit and maximum power points for a single I-V curve at standard test conditions together with temperature coefficients determined separately for individual cells. In contrast, module testing frequently records I-V curves over a wide range of irradiance and temperature conditions which, when available, should also be used to parameterize the performance model. We present a parameter estimation method that makes use of a full range of available I-V curves. We verify the accuracy of the method by recovering known parameter values from simulated I-V curves. We validate the method by estimating model parameters for a module using outdoor test data and predicting the outdoor performance of the module.
Centralized Coded Caching with Heterogeneous Cache Sizes

Coded caching can improve fundamental limits of communication, utilizing storage memory at individual users. This paper considers a centralized coded caching system, introducing heterogeneous cache sizes at the users, i.e., the users' cache memories are of different size. The goal is to design cache placement and delivery policies that minimize the worst-case delivery load on the server. To that end, the paper proposes an optimization framework for cache placement and delivery schemes which explicitly accounts for the heterogeneity of the cache sizes. We also characterize explicitly the optimal caching scheme, for the case where the sum of the users' cache sizes is smaller than or equal to the library size.
Geometry of quantum states: an introduction to quantum entanglement by Ingemar Bengtsson and Karol Zyczkowski

A long journey to a distant destination can be tedious but, keeping the anticipated pleasure of arrival in mind, we stoically make our way forward. On the other hand, there are travels for which the journey itself is more rewarding than the destination. The subtitle of this book, ”An introduction to quantum entanglement”, is in fact the subject of the last of fifteen chapters. While this is a worthwhile destination, it is the preceding fourteen chapters that make this book a delight to read and to savour. In his recent book The Mathematician’s Brain (Princeton University Press, 2007), David Ruelle writes: “· · · some mathematicians (in particular beginners) like to write formulas rather than sentences because they think it is more ’rigorous’. But this practice rapidly produces and incomprehensible mess. Efficient transmission of mathematics to humans depends on lucky choices for what to express with formulas and what to express with words · · ·. Making these choices · · · is an art and some mathematicians are very much better at it than others” Bengtsson’s and Zyczkowski’s book is an artful presentation of the geometry that lies behind quantum theory. It begins with the notion of convexity, illustrated by way of colour theory. (Which, apparently, was Schroedinger’s field of expertise before it became quantum mechanics). This beginning provides the background for the concepts of statistical distance efficiently treated in chapter two. The book then continues, through a digression on the geometry of spheres, complex projective spaces before taking a first run at the formalism of quantum theory in chapter 5. The following nine chapters extract and develop the intertwining themes of convexity and statistical distance in the quantum context, covering along the way density matrices, purification, majorisation, and quantum operations before landing at the penultimate chapter on monotone metrics and measures. Along the way the authors collect, and artfully explain, many important results scattered throughout the literature on mathematical physics. The careful explication of statistical distinguishability metrics (Fubini-Study and Bures) is the best I have read. If you want a rapid introduction to quantum entanglement I suspect you should take a shorter journey than provided here, but your life will be the poorer for it. If however you are a mathematical traveller who delights in the unexpected experience, then I suggest you hang a gone fishin’ notice on your office door and board the leisurely and stimulating ride conducted by Bengtsson and Zyczkowski.
Evolution of the Kidney

The excretory system regulates the chemical composition of body fluids by removing metabolic wastes and retaining the proper amount of water, salts and nutrients. The invertebrate excretory structures are classified in according to their marked variations in the morphological structures into three types included contractile vacuoles in protozoa, nephridia (flame cell system) in most invertebrate animals and Malpighian tubules (arthropod kidney) in insects . There are three distinct excretory organs formed in succession during the development of the vertebrate kidney, they are called pronephros, mesonephros and metanephros. The pronephros is the most primitive one and exists as a functional kidney only in some of the lowest fishes and is called the archinephros. The mesonephros represents the functional excretory organs in anamniotes and called as opisthonephros. The metanephros is the most caudally located of the excretory organs and the last to appear, it represents the functional kidney in amniotes [2-4].
Immersive Recommendation: News and Event Recommendations Using Personal Digital Traces

We propose a new user-centric recommendation model, called Immersive Recommendation, that incorporates cross-platform and diverse personal digital traces into recommendations. Our contextaware topic modeling algorithm systematically profiles users’ interests based on their traces from different contexts, and our hybrid recommendation algorithm makes high-quality recommendations by fusing users’ personal profiles, item profiles, and existing ratings. Specifically, in this work we target personalized news and local event recommendations for their utility and societal importance. We evaluated the model with a large-scale offline evaluation leveraging users’ public Twitter traces. In addition, we conducted a direct evaluation of the model’s recommendations in a 33-participant study using Twitter, Facebook and email traces. In the both cases, the proposed model showed significant improvement over the stateof-the-art algorithms, suggesting the value of using this new usercentric recommendation model to improve recommendation quality, including in cold-start situations.
Relationship between body mass index, body image, and fear of negative evaluation: Moderating role of self-esteem

This study examined the correlation between body mass index as independent variable, and body image and fear of negative evaluation as dependent variables, as well as the moderating role of self-esteem in these correlations. A total of 318 Malaysian young adults were conveniently recruited to do the self-administered survey on the demographic characteristics body image, fear of negative evaluation, and self-esteem. Partial least squares structural equation modeling was used to test the research hypotheses. The results revealed that body mass index was negatively associated with body image, while no such correlation was found with fear of negative evaluation. Meanwhile, the negative correlation of body mass index with body image was stronger among those with lower self-esteem, while a positive association of body mass index with fear of negative evaluation was significant only among individuals with low self-esteem.
Simulating public health emergency response: A case study of the 2004 North Carolina State Fair E. Coli Outbreak

Despite the investment of billions of dollars in federal funding towards emergency preparedness and response initiatives, broadly accepted performance measures for determining the efficacy of these systems have yet to be established. The inability to accurately capture this information creates knowledge gaps which hinder the ability to measure the true degree of preparedness. As a key communications component of North Carolina's public health system, the North Carolina Public Health Information Network (NC PHIN) serves as a promising means to measure emergency preparedness and response. We seek to determine how NC PHIN has increased emergency preparedness and response capacity by presenting a simulation of the 2004 State Fair E.coli Outbreak. We find that although the capacity exists within NC PHIN to increase emergency preparedness and response, other factors limit NC PHIN's effectiveness. Our findings suggest that proper resource allocation will be necessary in order to realize the true efficacy of NC PHIN.
Solution-processed graphene quantum dot deep-UV photodetectors.

Fast-response and high-sensitivity deep-ultraviolet (DUV) photodetectors with detection wavelength shorter than 320 nm are in high demand due to their potential applications in diverse fields. However, the fabrication processes of DUV detectors based on traditional semiconductor thin films are complicated and costly. Here we report a high-performance DUV photodetector based on graphene quantum dots (GQDs) fabricated via a facile solution process. The devices are capable of detecting DUV light with wavelength as short as 254 nm. With the aid of an asymmetric electrode structure, the device performance could be significantly improved. An on/off ratio of ∼6000 under 254 nm illumination at a relatively weak light intensity of 42 μW cm(-2) is achieved. The devices also exhibit excellent stability and reproducibility with a fast response speed. Given the solution-processing capability of the devices and extraordinary properties of GQDs, the use of GQDs will open up unique opportunities for future high-performance, low-cost DUV photodetectors.
Fuzzy-Model-Based Piecewise ${\mathscr H}_{\infty }$ Static-Output-Feedback Controller Design for Networked Nonlinear Systems

This paper investigates the problem of robust H∞ output-feedback control for a class of nonlinear systems under unreliable communication links. The nonlinear plant is represented by a Takagi-Sugeno (T-S) uncertain fuzzy model, and the communication links between the plant and controller are assumed to be imperfect, i.e., data-packet dropouts occur intermittently, which is often the case in a network environment. Stochastic variables that satisfy the Bernoulli random-binary distribution are adopted to characterize the data-missing phenomenon, and the attention is focused on the design of a piecewise static-output-feedback (SOF) controller such that the closed-loop system is stochastically stable with a guaranteed H∞ performance. Based on a piecewise Lyapunov function combined with some novel convexifying techniques, the solutions to the problem are formulated in the form of linear matrix inequalities (LMIs). Finally, simulation examples are also provided to illustrate the effectiveness of the proposed approaches.
Steroid concentrations in antepartum and postpartum saliva: normative values in women and correlations with serum

Saliva has been advocated as an alternative to serum or plasma for steroid monitoring. Little normative information is available concerning expected concentrations of the major reproductive steroids in saliva during pregnancy and the extended postpartum. Matched serum and saliva specimens controlled for time of day and collected less than 30 minutes apart were obtained in 28 women with normal singleton pregnancies between 32 and 38 weeks of gestation and in 43 women during the first six months postpartum. Concentrations of six steroids (estriol, estradiol, progesterone, testosterone, cortisol, dehydroepiandrosterone) were quantified in saliva by enzyme immunoassay. For most of the steroids examined, concentrations in antepartum saliva showed linear increases near end of gestation, suggesting an increase in the bioavailable hormone component. Observed concentrations were in agreement with the limited data available from previous reports. Modal concentrations of the ovarian steroids were undetectable in postpartum saliva and, when detectable in individual women, approximated early follicular phase values. Only low to moderate correlations between the serum and salivary concentrations were found, suggesting that during the peripartum period saliva provides information that is not redundant to serum. Low correlations in the late antepartum may be due to differential rates of change in the total and bioavailable fractions of the circulating steroid in the final weeks of the third trimester as a consequence of dynamic changes in carrier proteins such as corticosteroid binding globulin.