nils-herrmann/clean_scirepeval huggingface dataset:
Cell-Adhesive Bioinspired and Catechol-Based Multilayer Freestanding Membranes for Bone Tissue Engineering

Mussels are marine organisms that have been mimicked due to their exceptional adhesive properties to all kind of surfaces, including rocks, under wet conditions. The proteins present on the mussel's foot contain 3,4-dihydroxy-l-alanine (DOPA), an amino acid from the catechol family that has been reported by their adhesive character. Therefore, we synthesized a mussel-inspired conjugated polymer, modifying the backbone of hyaluronic acid with dopamine by carbodiimide chemistry. Ultraviolet-visible (UV-vis) spectroscopy and nuclear magnetic resonance (NMR) techniques confirmed the success of this modification. Different techniques have been reported to produce two-dimensional (2D) or three-dimensional (3D) systems capable to support cells and tissue regeneration; among others, multilayer systems allow the construction of hierarchical structures from nano- to macroscales. In this study, the layer-by-layer (LbL) technique was used to produce freestanding multilayer membranes made uniquely of chitosan and dopamine-modified hyaluronic acid (HA-DN). The electrostatic interactions were found to be the main forces involved in the film construction. The surface morphology, chemistry, and mechanical properties of the freestanding membranes were characterized, confirming the enhancement of the adhesive properties in the presence of HA-DN. The MC3T3-E1 cell line was cultured on the surface of the membranes, demonstrating the potential of these freestanding multilayer systems to be used for bone tissue engineering.
SnabbSwitch user space virtual switch benchmark and performance optimization for NFV

New paradigms in networking industry, such as Software Defined Networking (SDN) and Network Functions Virtualization (NFV), require the hypervisors to enable the execution of Virtual Network Functions in virtual machines (VMs). In this context, the virtual switch function is critical to achieve carrier grade performance, hardware independence, advanced features and programmability. SnabbSwitch is a virtual switch designed to run in user space with carrier grade performance targets, based on an efficient architecture which has driven the development of vhost-user (now also adopted by OVS-DPDK, the user space implementation of OVS based on Intel DPDK), easy to deploy and to program through its Lua scripting layer. This paper presents the SnabbSwitch virtual switch implementation along with its novelties (the vhost-user implementation and the usage of a trace compiler) and code optimizations, which have been merged in the mainline project repository. Extensive benchmarking activities, whose results are included in this paper, have been carried on to compare SnabbSwitch with other virtual switching solutions (i.e., OVS, OVS-DPDK, Linux Bridge, VFIO and SR-IOV). These results show that SnabbSwitch performs as well as hardware based solutions, such as SR-IOV and VFIO, while allowing for additional functional and flexible operation; they show also that SnabbSwitch is faster than the vhost-user based version (user space) of OVS-DPDK.
On cluster validity for the fuzzy c-means model

Many functionals have been proposed for validation of partitions of object data produced by the fuzzy c-means (FCM) clustering algorithm. We examine the role a subtle but important parameter-the weighting exponent m of the FCM model-plays in determining the validity of FCM partitions. The functionals considered are the partition coefficient and entropy indexes of Bezdek, the Xie-Beni, and extended Xie-Beni indexes, and the FukuyamaSugeno index. Limit analysis indicates, and numerical experiments confirm, that the FukuyamaSugeno index is sensitive to both high and low values of m and may be unreliable because of this. Of the indexes tested, the Xie-Beni index provided the best response over a wide range of choices for the number of clusters, (%lo), and for m from 1.01-7. Finally, our calculations suggest that the best choice for m is probably in the interval [U, 2.51, whose mean and midpoint, m = 2, have often been the preferred choice for many users of FCM.
Grade prediction with models specific to students and courses

The accurate estimation of students’ grades in future courses is important as it can inform the selection of next term’s courses and create personalized degree pathways to facilitate successful and timely graduation. This paper presents future course grade predictions methods based on sparse linear and low-rank matrix factorization models that are specific to each course or student–course tuple. These methods identify the predictive subsets of prior courses on a course-by-course basis and better address problems associated with the not-missing-at-random nature of the student–course historical grade data. The methods were evaluated on a dataset obtained from the University of Minnesota, for two different departments with different characteristics. This evaluation showed that focusing on course-specific data improves the accuracy of grade prediction.
Triple band notch UWB antenna array with EBG structure

In this paper, we propose a CPW fed triple band notch UWB antenna array with EBG structure. The major consideration in the antenna array design is the mutual coupling effect that exists within the elements. The use of Electromagnetic Band Gap structures in the antenna arrays can limit the coupling by suppresssing the surface waves. The triple band notch antenna consists of three slots which act as notch resonators for a specific band of frequencies, the C shape slot at the main radiator (WiMax-3.5GHz), a pair of CSRR structures at the ground plane(WLAN-5.8GHz) and an inverted U shaped slot in the center of the patch (Satellite Service bands-8.2GHz). The main objective is to reduce mutual coupling which in turn improves the peak realized gain, directivity.
Gordie Howe’s Stem Cell ‘Miracle’: A Qualitative Analysis of News Coverage and Readers’ Comments in Newspapers and Sports Websites

Stem cells continue to garner attention by the news media and play a role in public and policy discussions of emerging technologies. As new media platforms develop, it is important to understand how different news media represents emerging stem cell technologies and the role these play in public discussions. We conducted a comparative analysis of newspaper and sports websites coverage of one recent high profile case: Gordie Howe’s stem cell treatment in Mexico. Using qualitative coding methods, we analyzed news articles and readers’ comments from Canadian and US newspapers and sports websites. Results indicate that the efficacy of stem cell treatments is often assumed in news coverage and readers’ comments indicate a public with a wide array of beliefs and perspectives on stem cells and their clinical efficacy. Media coverage that presents uncritical perspectives on unproven stem cell therapies may create patient expectations, may have an affect on policy discussions, and help to feed the marketing of unproven therapies. However, news coverage that provides more balanced or critical coverage of unproven stem cell treatments may also inspire more critical discussion, as reflected in readers’ comments.
Ketamine: teaching an old drug new tricks.

K etamine has a special position among anesthetic drugs. It was introduced into clinical practice >30 yr ago with the hope that it would function as a “monoanesthetic” drug: inducing analgesia, amnesia, loss of consciousness, and immobility. This dream was not fulfilled because significant side effects were soon reported. With the introduction of other IV anesthetic drugs, ketamine’s role diminished rapidly. However, it is still used clinically for indications such as induction of anesthesia in patients in hemodynamic shock; induction of anesthesia in patients with active asthmatic disease; IM sedation of uncooperative patients, particularly children; supplementation of incomplete regional or local anesthesia; sedation in the intensive care setting; and short, painful procedures, such as dressing changes in burn patients. However, recent insights into ketamine’s anesthetic mechanism of action and its neuronal effects, as well as a reevaluation of its profound analgesic properties, offer the potential of expanding this range of indications. In addition, studies with the S(+) ketamine isomer suggest that its use may be associated with fewer side effects than the racemic mixture. In this article, we review the mechanism of action of ketamine anesthesia, the pharmacologic properties of its stereoisomers, and the potential uses of ketamine for preemptive analgesia and neuroprotection. Several aspects discussed herein have been reviewed previously (l-4).
A temperature monitoring system incorporating an array of precision wireless thermometers

This paper addresses the design and implementation of a real-time temperature monitoring system with applications in telemedicine. The system consists of a number of precision wireless thermometers which are conceived and realized to measure the patients' body temperature in hospitals and the intensive care units (ICUs). Each wireless thermometer incorporates an accurate semiconductor temperature sensor, a transceiver operating at 2.4 GHz and a microcontroller that controls the thermometer functionalities. An array of two thermometers are implemented and successfully evaluated in different scenarios, including free-space and in vivo tests. Also, an in-house developed computer software is used in order to visualize the measurements in addition to detecting rapid increase and alerting high body temperature. The agreement between the experimental data and reference temperature values is significant.
Foot strike patterns of recreational and sub-elite runners in a long-distance road race.

Although the biomechanical properties of the various types of running foot strike (rearfoot, midfoot, and forefoot) have been studied extensively in the laboratory, only a few studies have attempted to quantify the frequency of running foot strike variants among runners in competitive road races. We classified the left and right foot strike patterns of 936 distance runners, most of whom would be considered of recreational or sub-elite ability, at the 10 km point of a half-marathon/marathon road race. We classified 88.9% of runners at the 10 km point as rearfoot strikers, 3.4% as midfoot strikers, 1.8% as forefoot strikers, and 5.9% of runners exhibited discrete foot strike asymmetry. Rearfoot striking was more common among our sample of mostly recreational distance runners than has been previously reported for samples of faster runners. We also compared foot strike patterns of 286 individual marathon runners between the 10 km and 32 km race locations and observed increased frequency of rearfoot striking at 32 km. A large percentage of runners switched from midfoot and forefoot foot strikes at 10 km to rearfoot strikes at 32 km. The frequency of discrete foot strike asymmetry declined from the 10 km to the 32 km location. Among marathon runners, we found no significant relationship between foot strike patterns and race times.
Magnesium as a Biodegradable and Bioabsorbable Material for Medical Implants

For many years, stainless steel, cobalt-chromium, and titanium alloys have been the primary biomaterials used for load-bearing applications. However, as the need for structural materials in temporary implant applications has grown, materials that provide short-term structural support and can be reabsorbed into the body after healing are being sought. Since traditional metallic biomaterials are biocompatible but not biodegradable, the potential for magnesium-based alloys, which are biodegradable and bioabsorbable, in biomedical applications has gained more interest. Biodegradable and bioabsorbable magnesium-based alloys provide a number of benefits over traditional permanent implants. This paper summarizes the history and current status of magnesium as a bioabsorbable implant material. Also discussed is the development of a magnesium-zinc-calcium alloy that demonstrates promising degradation behavior relative to a commercially available Mg and magnesium-aluminum-zinc alloy.
Generative agents for player decision modeling in games

This paper presents a method for modeling player decision making through the use of agents as AI-driven personas. The paper argues that artificial agents, as generative player models, have properties that allow them to be used as psychometrically valid, abstract simulations of a human player’s internal decision making processes. Such agents can then be used to interpret human decision making, as personas and playtesting tools in the game design process, as baselines for adapting agents to mimic classes of human players, or as believable, human-like opponents. This argument is explored in a crowdsourced decision making experiment, in which the decisions of human players are recorded in a small-scale dungeon themed puzzle game. Human decisions are compared to the decisions of a number of a priori defined“archetypical” agent-personas, and the humans are characterized by their likeness to or divergence from these. Essentially, at each step the action of the human is compared to what actions a number of reinforcement-learned agents would have taken in the same situation, where each agent is trained using a different reward scheme. Finally, extensions are outlined for adapting the agents to represent sub-classes found in the human decision making traces.
Robustness of conditional GANs to noisy labels

We study the problem of learning conditional generators from noisy labeled samples, where the labels are corrupted by random noise. A standard training of conditional GANs will not only produce samples with wrong labels, but also generate poor quality samples. We consider two scenarios, depending on whether the noise model is known or not. When the distribution of the noise is known, we introduce a novel architecture which we call Robust Conditional GAN (RCGAN). The main idea is to corrupt the label of the generated sample before feeding to the adversarial discriminator, forcing the generator to produce samples with clean labels. This approach of passing through a matching noisy channel is justified by accompanying multiplicative approximation bounds between the loss of the RCGAN and the distance between the clean real distribution and the generator distribution. This shows that the proposed approach is robust, when used with a carefully chosen discriminator architecture, known as projection discriminator. When the distribution of the noise is not known, we provide an extension of our architecture, which we call RCGAN-U, that learns the noise model simultaneously while training the generator. We show experimentally on MNIST and CIFAR-10 datasets that both the approaches consistently improve upon baseline approaches, and RCGAN-U closely matches the performance of RCGAN.
Human-Machine-Learner Interaction : The Best of Both Worlds

Paste the appropriate copyright statement here. ACM now supports three different copyright statements:  ACM holds the copyright on the work. This is the historical approach.  The author(s) retain copyright, but ACM receives an exclusive publication license.  The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is single spaced in a sans-serif 7 point font. Every submission will be assigned their own unique DOI string to be included here.  This position statement presents a notional framework for more tightly integrating interactive visual systems with machine learning. We posit that increasingly, powerful systems will be built for data analysis and consumer use that leverage the best of both human insight and raw computing power by effectively integrating machine learning and human interaction. We note some existing contributions to this space and provide a framework that organizes existing efforts and illuminates future endeavors by suggesting the categories of machine learning algorithm and interaction type that are most germane to this integration.
A Higher-Order CRF Model for Road Network Extraction

The aim of this work is to extract the road network from aerial images. What makes the problem challenging is the complex structure of the prior: roads form a connected network of smooth, thin segments which meet at junctions and crossings. This type of a-priori knowledge is more difficult to turn into a tractable model than standard smoothness or co-occurrence assumptions. We develop a novel CRF formulation for road labeling, in which the prior is represented by higher-order cliques that connect sets of super pixels along straight line segments. These long-range cliques have asymmetric PN-potentials, which express a preference to assign all rather than just some of their constituent super pixels to the road class. Thus, the road likelihood is amplified for thin chains of super pixels, while the CRF is still amenable to optimization with graph cuts. Since the number of such cliques of arbitrary length is huge, we furthermore propose a sampling scheme which concentrates on those cliques which are most relevant for the optimization. In experiments on two different databases the model significantly improves both the per-pixel accuracy and the topological correctness of the extracted roads, and outperforms both a simple smoothness prior and heuristic rule-based road completion.
Evaluating the use of side-scan sonar for detecting freshwater mussel beds in turbid river environments

Side-scan sonar is a valuable tool for mapping habitat features in many aquatic systems suggesting it may also be useful for locating sedentary biota. The objective of this study was to determine if side-scan sonar could be used to identify freshwater mussel (unionid) beds and the required environmental conditions. We used side-scan sonar to develop a series of mussel-bed reference images by placing mussel shells within homogenous areas of fine and coarse substrates. We then used side-scan sonar to map a 32-km river reach during spring and summer. Using our mussel-bed reference images, several river locations were identified where mussel beds appeared to exist in the scanned images and we chose a subset of sites (n = 17) for field validation. The validation confirmed that ~60% of the sites had mussel beds and ~80% had some mussels or shells present. Water depth was significantly related to our ability to predict mussel-bed locations: predictive ability was greatest at depths of 1–2 m, but decreased in water >2-m deep. We determined side-scan sonar is an effective tool for preliminary assessments of mussel presence during times when they are located at or above the substrate surface and in relatively fine substrates excluding fine silt.
Integrating Both Visual and Audio Cues for Enhanced Video Caption

Video caption refers to generating a descriptive sentence for a specific short video clip automatically, which has achieved remarkable success recently. However, most of the existing methods focus more on visual information while ignoring the synchronized audio cues. We propose three multimodal deep fusion strategies to maximize the benefits of visual-audio resonance information. The first one explores the impact on cross-modalities feature fusion from low to high order. The second establishes the visual-audio short-term dependency by sharing weights of corresponding front-end networks. The third extends the temporal dependency to long-term through sharing multimodal memory across visual and audio modalities. Extensive experiments have validated the effectiveness of our three cross-modalities fusion strategies on two benchmark datasets, including Microsoft Research Video to Text (MSRVTT) and Microsoft Video Description (MSVD). It is worth mentioning that sharing weight can coordinate visualaudio feature fusion effectively and achieve the state-of-art performance on both BELU and METEOR metrics. Furthermore, we first propose a dynamic multimodal feature fusion framework to deal with the part modalities missing case. Experimental results demonstrate that even in the audio absence mode, we can still obtain comparable results with the aid of the additional audio modality inference module.
NMR Chemical Shifts of Common Laboratory Solvents as Trace Impurities.

In the course of the routine use of NMR as an aid for organic chemistry, a day-to-day problem is the identification of signals deriving from common contaminants (water, solvents, stabilizers, oils) in less-than-analytically-pure samples. This data may be available in the literature, but the time involved in searching for it may be considerable. Another issue is the concentration dependence of chemical shifts (especially 1H); results obtained two or three decades ago usually refer to much more concentrated samples, and run at lower magnetic fields, than today’s practice. We therefore decided to collect 1H and 13C chemical shifts of what are, in our experience, the most popular “extra peaks” in a variety of commonly used NMR solvents, in the hope that this will be of assistance to the practicing chemist.
Choosing knowledge management strategies by using a combined ANP and DEMATEL approach

Numerous companies are expecting their knowledge management (KM) to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. The KM strategy selection is a kind of multiple criteria decision-making (MCDM) problem, which requires considering a large number of complex factors as multiple evaluation criteria. A robust MCDM method should consider the interactions among criteria. The analytic network process (ANP) is a relatively new MCDM method which can deal with all kinds of interactions systematically. Moreover, the Decision Making Trial and Evaluation Laboratory (DEMATEL) not only can convert the relations between cause and effect of criteria into a visual structural model, but also can be used as a way to handle the inner dependences within a set of criteria. Hence, this paper proposes an effective solution based on a combined ANP and DEMATEL approach to help companies that need to evaluate and select KM strategies. Additionally, an empirical study is presented to illustrate the application of the proposed method.
Understanding the Impressions, Motivations, and Barriers of One Time Code Contributors to FLOSS Projects: A Survey

Successful Free/Libre Open Source Software (FLOSS) projects must attract and retain high-quality talent. Researchers have invested considerable effort in the study of core and peripheral FLOSS developers. To this point, one critical subset of developers that have not been studied are One-Time code Contributors (OTC) – those that have had exactly one patch accepted. To understand why OTCs have not contributed another patch and provide guidance to FLOSS projects on retaining OTCs, this study seeks to understand the impressions, motivations, and barriers experienced by OTCs. We conducted an online survey of OTCs from 23 popular FLOSS projects. Based on the 184 responses received, we observed that OTCs generally have positive impressions of their FLOSS project and are driven by a variety of motivations. Most OTCs primarily made contributions to fix bugs that impeded their work and did not plan on becoming long term contributors. Furthermore, OTCs encounter a number of barriers that prevent them from continuing to contribute to the project. Based on our findings, there are some concrete actions FLOSS projects can take to increase the chances of converting OTCs into long-term contributors.