nils-herrmann/clean_scirepeval huggingface dataset:
mOS : An open middlebox platform with programmable network stacks

Though the growing popularity of software-based middleboxes raises new requirements for network stack functionality, existing network stack have fundamental challenges in supporting the development of high-performance middlebox applications in a fast and flexible manner. In this work, we design and implement an enriched, programmable, and extensible network stack and its API to support the various requirements of middlebox applications. mOS supports proxy and monitoring function as well as traditional end TCP stack function. Further, we allow applications extend TCP functionality by hooking in middle of TCP processing and define user-level events on TCP state. Meanwhile, Epoll-like API allows applications manipulate read/write from/to byte stream buffers in an efficient way. To support an efficient consolidation of multiple middlebox applications in a single machine, mOS will allow multiple middlebox applications share the same TCP processing context without duplicated IP/TCP processing. We show that mOS can support various middlebox applications in an easy and efficient way without building TCP functionality from scratch.
Effectiveness of Occupational Therapy Interventions for Adults With Fibromyalgia: A Systematic Review.

This systematic review addresses the effectiveness of occupational therapy-related interventions for adults with fibromyalgia.



We examined the literature published between January 2000 and June 2014. A total of 322 abstracts from five databases were reviewed. Forty-two Level I studies met the inclusion criteria. Studies were evaluated primarily with regard to the following outcomes: daily activities, pain, depressive symptoms, fatigue, and sleep.



Strong evidence was found for interventions categorized for this review as cognitive-behavioral interventions; relaxation and stress management; emotional disclosure; physical activity; and multidisciplinary interventions for improving daily living, pain, depressive symptoms, and fatigue. There was limited to no evidence for self-management, and few interventions resulted in better sleep.



Although the evidence supports interventions within the scope of occupational therapy practice for people with fibromyalgia, few interventions were occupation based.
Enabling Lightweight Transactions with Precision Time

Distributed transactional storage is an important service in today's data centers. Achieving high performance without high complexity is often a challenge for these systems due to sophisticated consistency protocols and multiple layers of abstraction. In this paper we show how to combine two emerging technologies---Software-Defined Flash (SDF) and precise synchronized clocks---to improve performance and reduce complexity for transactional storage within the data center.
 We present a distributed transactional system (called MILANA) as a layer above a durable multi-version key-value store (called SEMEL) for read-heavy workloads within a data center. SEMEL exploits write behavior of SSDs to maintain a time-ordered sequence of versions for each key efficiently and durably. MILANA adds a variant of optimistic concurrency control above SEMEL's API to service read requests from a consistent snapshot and to enable clients to make fast local commit or abort decisions for read-only transactions.
 Experiments with the prototype reveal up to 43% lower transaction abort rates using IEEE Precision Time Protocol (PTP) vs. the standard Network Time Protocol (NTP). Under the Retwis benchmark, client-local validation of read-only transactions yields a 35% reduction in latency and 55% increase in transaction throughput.
A triangle histogram for object classification by tactile sensing

We present a new descriptor for tactile 3D object classification. It is invariant to object movement and simple to construct, using only the relative geometry of points on the object surface. We demonstrate successful classification of 185 objects in 10 categories, at sparse to dense surface sampling rate in point cloud simulation, with an accuracy of 77.5% at the sparsest and 90.1% at the densest. In a physics-based simulation, we show that contact clouds resembling the object shape can be obtained by a series of gripper closures using a robotic hand equipped with sparse tactile arrays. Despite sparser sampling of the object's surface, classification still performs well, at 74.7%. On a real robot, we show the ability of the descriptor to discriminate among different object instances, using data collected by a tactile hand.
Models of vertical cytomegalovirus (CMV) transmission and pathogenesis

Despite the considerable clinical impact of congenital human cytomegalovirus (HCMV) infection, the mechanisms of maternal–fetal transmission and the resultant placental and fetal damage are largely unknown. Here, we discuss animal models for the evaluation of CMV vaccines and virus-induced pathology and particularly explore surrogate human models for HCMV transmission and pathogenesis in the maternal–fetal interface. Studies in floating and anchoring placental villi and more recently, ex vivo modeling of HCMV infection in integral human decidual tissues, provide unique insights into patterns of viral tropism, spread, and injury, defining the outcome of congenital infection, and the effect of potential antiviral interventions.
Branch and Bound Methods

Branch and bound algorithms are methods for global optimization in nonconvex problems [LW66, Moo91]. They are nonheuristic, in the sense that they maintain a provable upper and lower bound on the (globally) optimal objective value; they terminate with a certificate proving that the suboptimal point found is 2-suboptimal. Branch and bound algorithms can be (and often are) slow, however. In the worst case they require effort that grows exponentially with problem size, but in some cases we are lucky, and the methods converge with much less effort. In these brief notes we describe two typical and simple examples of branch and bound methods.
Logical Structure Recovery in Scholarly Articles with Rich Document Features

Scholarly digital libraries increasingly provide analytics to information within documents themselves. This includes information about the logical document structure of use to downstream components, such as search, navigation, and summarization. In this paper, the authors describe SectLabel, a module that further develops existing software to detect the logical structure of a document from existing PDF files, using the formalism of conditional random fields. While previous work has assumed access only to the raw text representation of the document, a key aspect of this work is to integrate the use of a richer representation of the document that includes features from optical character recognition (OCR), such as font size and text position. Experiments reveal that using such rich features improves logical structure detection by a significant 9 F1 points, over a suitable baseline, motivating the use of richer document representations in other digital library applications.  10.4018/978-1-4666-0900-6.ch014
Ultrasound guided low thoracic erector spinae plane block for management of acute herpes zoster.

Interfascial plane blocks have becomevery popular in recent years. A novel interfascial plane block, erector spinae plane (ESP) block can target the dorsal and ventral rami of the thoracic spinal nerves but its effect in neuropathic pain is unclear . If acute pain management for herpes zoster is not done aggressively, it can turn into chronic pain. However; ESP block is first described as inject local anesthetics around the erector spinae muscle at the level of T5 spinous process for thoracic region, if the block is performed at lower levels it could be effective for abdominal and lumbar region . There have been no reports on the efficacy of ESP block over the herpes zoster pain. Here it we report the successful management of acute herpes zoster pain using low thoracic ESP block. Awritten consent formwasobtained from thepatient for this report. The patient was an 72-year-oldmanwho presentedwith severe painful vesicles (9/10 VAS intensity) over posterior lumbar and lateral abdominal region . The patient received amitriptyline 10 mg, non-
A Novel Active Interphase Transformer Scheme to Achieve Three-Phase Line Current Balance for 24-Pulse Converter

A new active interphase transformer (IPT) scheme to achieve three-phase line current balance for a 24-pulse converter is proposed in this paper. The proposed active IPT scheme consists of three IPT and a current-controlled inverter with required rating only 1.16% of system power rating. A current injection method for an active IPT is also proposed in this paper. The balance of three-phase current and high power quality can be achieved by injecting compensation current into the secondary winding of the active IPT. Moreover, the proposed scheme can operate in flexible load configurations, by which separated loads can be connected to the separated outputs of the converter independently. The operation criteria for flexible load arrangements are analyzed to obtain better performance. System simulation is conducted and a 6-kW laboratory prototype is built both for evaluation and test. Both simulation and experimental results demonstrate the validity of the proposed scheme.
Characterization of genomic deletion efficiency mediated by clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 nuclease system in mammalian cells.

The clustered regularly interspaced short [corrected] palindromic repeats (CRISPR)/CRISPR-associated (Cas) 9 nuclease system has provided a powerful tool for genome engineering. Double strand breaks may trigger nonhomologous end joining repair, leading to frameshift mutations, or homology-directed repair using an extrachromosomal template. Alternatively, genomic deletions may be produced by a pair of double strand breaks. The efficiency of CRISPR/Cas9-mediated genomic deletions has not been systematically explored. Here, we present a methodology for the production of deletions in mammalian cells, ranging from 1.3 kb to greater than 1 Mb. We observed a high frequency of intended genomic deletions. Nondeleted alleles are nonetheless often edited with inversions or small insertion/deletions produced at CRISPR recognition sites. Deleted alleles also typically include small insertion/deletions at predicted deletion junctions. We retrieved cells with biallelic deletion at a frequency exceeding that of probabilistic expectation. We demonstrate an inverse relationship between deletion frequency and deletion size. This work suggests that CRISPR/Cas9 is a robust system to produce a spectrum of genomic deletions to allow investigation of genes and genetic elements.
Intellectual structure of knowledge in iMetrics: A co-word analysis

As an iMetrics technique, co-word analysis is used to describe the status of various subject areas, however, iMetrics itself is not examined by a co-word analysis. For the purpose of using co-word analysis, this study tries to investigate the intellectual structure of iMetrics during the period of 1978 to 2014. The research data are retrieved from two core journals on iMetrics research ( Scientometrics , and Journal of Informetrics ) and relevant articles in six journals publishing iMetrics studies. Application of hierarchical clustering led to the formation of 11 clusters representing the intellectual structure of iMetrics, including “Scientometric Databases and Indicators,” “Citation Analysis,” “Sociology of Science,” “Issues Related to Rankings of Universities, Journals, etc.,” “Information Visualization and Retrieval,” “Mapping Intellectual Structure of Science,” “Webometrics,” “Industry–University– Government Relations,” “Technometrics (Innovation and Patents), “Scientific Collaboration in Universities”, and “Basics of Network Analysis.” Furthermore, a two-dimensional map and a strategic diagram are drawn to clarify the structure, maturity, and cohesion of clusters.
A Self-Powered Insole for Human Motion Recognition

Biomechanical energy harvesting is a feasible solution for powering wearable sensors by directly driving electronics or acting as wearable self-powered sensors. A wearable insole that not only can harvest energy from foot pressure during walking but also can serve as a self-powered human motion recognition sensor is reported. The insole is designed as a sandwich structure consisting of two wavy silica gel film separated by a flexible piezoelectric foil stave, which has higher performance compared with conventional piezoelectric harvesters with cantilever structure. The energy harvesting insole is capable of driving some common electronics by scavenging energy from human walking. Moreover, it can be used to recognize human motion as the waveforms it generates change when people are in different locomotion modes. It is demonstrated that different types of human motion such as walking and running are clearly classified by the insole without any external power source. This work not only expands the applications of piezoelectric energy harvesters for wearable power supplies and self-powered sensors, but also provides possible approaches for wearable self-powered human motion monitoring that is of great importance in many fields such as rehabilitation and sports science.
Turning characteristic study of multi-axle compound steering vehicle

The larger and longer body of multi-axle vehicle makes it difficult to steer as flexibly as usual. For this reason, a novel steering mode which combines traditional Ackerman steering and Skid steering method is proposed and the resulted turning characteristics is studied in this research. First, the research methods are identified by means of building and analysing a vehicle dynamical model. Then, the influence of rear-wheels' assisted steering on vehicle yaw rate, turning radius and wheel side-slip angle is analysed by solving a linear simplified model. An executive strategy of an additional yaw moment produced by rear-wheels during the vehicle steering at a relative lower speed is put forward. And a torque distribution method of rear-wheels is given. Finally, a comparison with all-wheel steering vehicles is made. It turned out that this steering mode can effectively decrease the turning radius or increase mobility and have an advantage over all-wheel steering.
Stabilization of a Quadrotor With Uncertain Suspended Load Using Sliding Mode Control

The stability and trajectory control of a quadrotor carrying a suspended load with a fixed known mass has been extensively studied in recent years. However, the load mass is not always known beforehand in practical applications. This mass uncertainty brings uncertain disturbances to the quadrotor system, causing existing controllers to have a worse performance or to be collapsed. To improve the quadrotor’s stability in this situation, we investigate the impacts of the uncertain load mass on the quadrotor. By comparing the simulation results of two controllers -the proportional-derivative (PD) controller and the sliding mode controller (SMC) driven by a sliding mode disturbance of observer (SMDO), the quadrotor’s performance is verified to be worse as the uncertainty increases. The simulation results also show a controller with stronger robustness against disturbances is better for practical applications.
An On-Demand Rate-Adaptation Mechanism For IEEE 802.11 Networks

The current IEEE 802.11 standard mandates multiple transmission rates at the physical layer by employing different modulation and coding schemes. However, it does not specify any rate adaptation mechanism. It is left up to the researchers and vendors to implement adaptation algorithms that utilize the multi-rate capability. Rate adaptation algorithm is a critical component to the wireless system performance. The design of such algorithm is, however, not trivial due to the time-varying characteristics of the wireless channel (attenuation, collisions, interferences etc.). This has attracted the attention of researchers during the last few years. Previous work tends to select bit rates based on either frame loss statistics or physical layer (PHY) metrics, e.g., signal-to-noise ratio. While decisions in frame-based approaches are based on narrow information that limit their adaptability, the decisions in PHYbased approaches are more precise. However, the latter come with the overhead cost of transferring the channel information from the receiver to the transmitter. In this thesis we try to compromise between the channel adaptability and the cost of transferring channel information by signaling a minimized amount of information with respect to channel variations. This thesis presents a novel On-demand Feedback Rate Adaptation (OFRA) algorithm. The novelty of OFRA is that it allows receiver based adaptation through signaling channel information on a rate close to the channel coherence time. Hence, it eliminates the unnecessary overhead of transferring channel information at a fixed rate oblivious to the channel speed. In OFRA, the receiving node assesses the channel conditions by tracking the signal-to-noise ratio. Once it detects variations in the channel, it selects a new bit-rate and signals it back to the sending node. OFRA is to the best of our knowledge the first rate adaptation algorithm that can work in the absence of acknowledgments. This makes OFRA specially beneficial to nonacknowledged traffic that so far had to operate with a fixed bit-rate scheme. The throughput gains using OFRA stem from its ability to react fast in rapidly fluctuating channels and keeping the overhead low. Evaluation results obtained using NS-3 simulator show that OFRA consistently performs well in static as well as in mobile environments and outperforms ARF, Minstrel and Onoe.
Subdimensional Expansion: A Framework for Computationally Tractable Multirobot Path Planning

Planning optimal paths for large numbers of robots is computationally expensive. In this thesis, we present a new framework for multirobot path planning called subdimensional expansion, which initially plans for each robot individually, and then coordinates motion among the robots as needed. More specifically, subdimensional expansion initially creates a one-dimensional search space embedded in the joint configuration space of the multirobot system. When the search space is found to be blocked during planning by a robot-robot collision, the dimensionality of the search space is locally increased to ensure that an alternative path can be found. As a result, robots are only coordinated when necessary, which reduces the computational cost of finding a path. Subdimensional expansion is a flexible framework that can be used with multiple planning algorithms. For discrete planning problems, subdimensional expansion can be combined with A* to produce the M* algorithm, a complete and optimal multirobot path planning problem. When the configuration space of individual robots is too large to be explored effectively with A*, subdimensional expansion can be combined with probabilistic planning algorithms to produce sRRT and sPRM. M* is then extended to solve variants of the multirobot path planning algorithm. We present the Constraint Manifold Subsearch (CMS) algorithm to solve problems where robots must dynamically form and dissolve teams with other robots to perform cooperative tasks. Uncertainty M* (UM*) is a variant of M* that handles systems with probabilistic dynamics. Finally, we apply M* to multirobot sequential composition. Results are validated with extensive simulations and experiments on multiple physical robots.
Synthetic aperture imaging algorithms : with application to wide bandwidth sonar

This thesis contains the complete end-to-end simulation, development, implementation, and calibration of the wide bandwidth, low-Q, Kiwi-SAS synthetic aperture sonar (SAS). Through the use of a very stable towfish, a new novel wide bandwidth transducer design, and autofocus procedures, high-resolution diffraction limited imagery is produced. As a complete system calibration was performed, this diffraction limited imagery is not only geometrically calibrated, it is also calibrated for target cross-section or target strength estimation. Is is important to note that the diffraction limited images are formed without access to any form of inertial measurement information. Previous investigations applying the synthetic aperture technique to sonar have developed processors based on exact, but inefficient, spatial-temporal domain time-delay and sum beamforming algorithms, or they have performed equivalent operations in the frequency domain using fast-correlation techniques (via the fast Fourier transform (FFT)). In this thesis, the algorithms used in the generation of synthetic aperture radar (SAR) images are derived in their wide bandwidth forms and it is shown that these more efficient algorithms can be used to form diffraction limited SAS images. Several new algorithms are developed; accelerated chirp scaling algorithm represents an efficient method for processing synthetic aperture data, while modified phase gradient autofocus and a low-Q autofocus routine based on prominent point processing are used to focus both simulated and real target data that has been corrupted by known and unknown motion or medium propagation errors.
Boosting to correct inductive bias in text classification

This paper studies the effects of boosting in the context of different classification methods for text categorization, including Decision Trees, Naive Bayes, Support Vector Machines (SVMs) and a Rocchio-style classifier. We identify the inductive biases of each classifier and explore how boosting, as an error-driven resampling mechanism, reacts to those biases. Our experiments on the Reuters-21578 benchmark show that boosting is not effective in improving the performance of the base classifiers on common categories. However, the effect of boosting for rare categories varies across classifiers: for SVMs and Decision Trees, we achieved a 13-17% performance improvement in macro-averaged F1 measure, but did not obtain substantial improvement for the other two classifiers. This interesting finding of boosting on rare categories has not been reported before.
Bitlist: New Full-text Index for Low Space Cost and Efficient Keyword Search

Nowadays Web search engines are experiencing significant performance challenges caused by a huge amount of Web pages and increasingly larger number of Web users. The key issue for addressing these challenges is to design a compact structure which can index Web documents with low space and meanwhile process keyword search very fast. Unfortunately, the current solutions typically separate the space optimization from the search improvement. As a result, such solutions either save space yet with search inefficiency, or allow fast keyword search but with huge space requirement. In this paper, to address the challenges, we propose a novel structure bitlist with both low space requirement and supporting fast keyword search. Specifically, based on a simple and yet very efficient encoding scheme, bitlist uses a single number to encode a set of integer document IDs for low space, and adopts fast bitwise operations for very efficient boolean-based keyword search. Our extensive experimental results on real and synthetic data sets verify that bitlist outperforms the recent proposed solution, inverted list compression [23, 22] by spending 36.71% less space and 61.91% faster processing time, and achieves comparable running time as  but with significantly lower space.