nils-herrmann/clean_scirepeval huggingface dataset:
Neuronavigation in minimally invasive spine surgery.

OBJECT
Parallel advancements in image guidance technology and minimal access techniques continue to push the frontiers of minimally invasive spine surgery (MISS). While traditional intraoperative imaging remains widely used, newer platforms, such as 3D-fluoroscopy, cone-beam CT, and intraoperative CT/MRI, have enabled safer, more accurate instrumentation placement with less radiation exposure to the surgeon. The goal of this work is to provide a review of the current uses of advanced image guidance in MISS.



The authors searched PubMed for relevant articles concerning MISS, with particular attention to the use of image-guidance platforms. Pertinent studies published in English were further compiled and characterized into relevant analyses of MISS of the cervical, thoracic, and lumbosacral regions.



Fifty-two studies were included for review. These describe the use of the iso-C system for 3D navigation during C1-2 transarticular screw placement, the use of endoscopic techniques in the cervical spine, and the role of navigation guidance at the occipital-cervical junction. The authors discuss the evolving literature concerning neuronavigation during pedicle screw placement in the thoracic and lumbar spine in the setting of infection, trauma, and deformity surgery and review the use of image guidance in transsacral approaches.



Refinements in image-guidance technologies and minimal access techniques have converged on spinal pathology, affording patients the ability to undergo safe, accurate operations without the associated morbidities of conventional approaches. While percutaneous transpedicular screw placement is among the most common procedures to benefit from navigation, other areas of spine surgery can benefit from advances in neuronavigation and further growth in the field of image-guided MISS is anticipated.
Highly articulated robotic probe for minimally invasive surgery

We have developed a novel highly articulated robotic probe (HARP) that can thread through tightly packed volumes without disturbing the surrounding tissues and organs. We use cardiac surgery as the focal application of this work. As such, we have designed the HARP to enter the pericardial cavity through a subxiphoid port. The surgeon can effectively reach remote intrapericardial locations on the epicardium and deliver therapeutic interventions under direct control. Reducing the overall cross-sectional diameter of the mechanism was the main challenge in the design of this device. Our device differs from others in that we use conventional actuation and still have good maneuverability. We have performed simple proof-of-concept clinical experiments to give preliminary validation of the ideas presented here
RefineNet: Refining Object Detectors for Autonomous Driving

Highly accurate, camera-based object detection is an essential component of autonomous navigation and assistive technologies. In particular, for on-road applications, localization quality of objects in the image plane is important for accurate distance estimation, safe trajectory prediction, and motion planning. In this paper, we mathematically formulate and study a strategy for improving object localization with a deep convolutional neural network. An iterative region-of-interest pooling framework is proposed for predicting increasingly tight object boxes and addressing limitations in current state-of-the-art deep detection models. The method is shown to significantly improve the performance on a variety of datasets, scene settings, and camera perspectives, producing high-quality object boxes at a minor additional computational expense. Specifically, the architecture achieves impressive gains in performance (up to 6% improvement in detection accuracy) at fast run-time speed (0.22 s per frame on  $1242 \times 375$ sized images). The iterative refinement is shown to impact subsequent vision tasks, such as object tracking in the image plane and in ground plane.
Predestination: Inferring Destinations from Partial Trajectories

We describe a method called Predestination that uses a history of a driver’s destinations, along with data about driving behaviors, to predict where a driver is going as a trip progresses. Driving behaviors include types of destinations, driving efficiency, and trip times. Beyond considering previously visited destinations, Predestination leverages an open-world modeling methodology that considers the likelihood of users visiting previously unobserved locations based on trends in the data and on the background properties of locations. This allows our algorithm to smoothly transition between “out of the box” with no training data to more fully trained with increasing numbers of observations. Multiple components of the analysis are fused via Bayesian inference to produce a probabilistic map of destinations. Our algorithm was trained and tested on hold-out data drawn from a database of GPS driving data gathered from 169 different subjects who drove 7,335 different trips.
AeroRP performance in highly-dynamic airborne networks using 3D Gauss-Markov mobility model

Emerging airborne networks require domainspecific routing protocols to cope with the challenges faced by the highly-dynamic aeronautical environment. We present an ns-3 based performance comparison of the AeroRP protocol with conventional MANET routing protocols. To simulate a highly-dynamic airborne network, accurate mobility models are needed for the physical movement of nodes. The fundamental problem with many synthetic mobility models is their random, memoryless behavior. Airborne ad hoc networks require a flexible memory-based 3-dimensional mobility model. Therefore, we have implemented a 3-dimensional Gauss-Markov mobility model in ns-3 that appears to be more realistic than memoryless models such as random waypoint and random walk. Using this model, we are able to simulate the airborne networking environment with greater realism than was previously possible and show that AeroRP has several advantages over other MANET routing protocols.
Board test coverage: the value of prediction and how to compare numbers

Test coverage prediction for board assemblies has an important function in, among others, test engineering, test cost modeling, test strategy definition and product quality estimation. Introducing a method that defines how this coverage is calculated can increase the value of such prediction across the electronics industry. There are three aspects to test coverage calculation: fault modeling, coverage-per-fault and total coverage. An abstraction level for fault categories is introduced, called MPS (material, placement, soldering) that enables us to compare coverage results using different fault models. Additionally, the rule-based fault coverage estimation and the weighted coverage calculation are discussed.  As such, the full text of the paper was not available in time for inclusion in the general volume of the 2003  The full text is available in 2003 ITC Proceedings— Board and System Test Track. ITC INTERNATIONAL TEST CONFERENCE Proceedings of the International Test Conference 2003 (ITC’03) 1089-3539/03 $ 17.00
Conventional physical therapy with lumbar traction; clinical evaluation and magnetic resonance imaging for lumbar disc herniation.

This study measures and compares the outcome of conservative physical therapy with traction, by using magnetic resonance imaging and clinical parameters in patients presenting with low back pain caused by lumbar disc herniation.



A total of 26 patients with LDH (14F, 12M with mean aged 37 +/- 11) were enrolled in this study and 15 sessions (per day on 3 weeks) of physical therapy were applied. That included hot pack, ultrasound, electrotherapy and lumbar traction. Physical examination of the lumbar spine, severity of pain, sleeping order, patient and physician global assessment with visual analogue scale, functional disability by HAQ, Roland Disability Questionnaire, and Modified Oswestry Disability Questionnaire were assessed at baseline and at 4-6 weeks after treatment. Magnetic resonance imaging examinations were carried out before and 4-6 weeks after the treatment



All patients completed the therapy session. There were significant reductions in pain, sleeping disturbances, patient and physician global assessment and disability scores, and significant increases in lumbar movements between baseline and follow-up periods. There were significant reductions of size of the herniated mass in five patients, and significant increase in 3 patients on magnetic resonance imaging after treatment, but no differences in other patients.



This study showed that conventional physical therapies with lumbar traction were effective in the treatment of patient with subacute LDH. These results suggest that clinical improvement is not correlated with the finding of MRI. Patients with LDH should be monitored clinically .
Blockchain-based publicly verifiable data deletion scheme for cloud storage

With the rapid development of cloud storage, more and more data owners store their data on the remote cloud, that can reduce data owners’ overhead because the cloud server maintaining the data for them, e.g., storing, updating and deletion. However, that leads to data deletion becomes a security challenge because the cloud server may not delete the data honestly for financial incentives. Recently, plenty of research works have been done on secure data deletion. However, most of the existing methods can be summarized with the same protocol essentially, which called “one-bit-return” protocol: the storage server deletes the data and returns a one-bit result. The data owner has to believe the returned result because he cannot verify it. In this paper, we propose a novel blockchain-based data deletion scheme, which can make the deletion operation more transparent. In our scheme, the data owner can verify the deletion result no matter how malevolently the cloud server behaves. Besides, with the application of blockchain, the proposed scheme can achieve public verification without any trusted third party.
Usability inspection of digital libraries: a case study

This paper reports a case study about lessons learned and usability issues encountered in a usability inspection of a digital library system called the Networked Computer Science Technical Reference Library (NCSTRL). Using a co-discovery technique with a team of three expert usability inspectors (the authors), we performed a usability inspection driven by a broad set of anticipated user tasks. We found many good design features in NCSTRL, but the primary result of a usability inspection is a list of usability problems as candidates for fixing. The resulting problems are organized by usability problem type and by system functionality, with emphasis on the details of problems specific to digital library functions. The resulting usability problem list was used to illustrate a cost/importance analysis technique that trades off importance to fix against cost to fix. The problems are sorted by the ratio of importance to cost, producing a priority ranking for resolution.
Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]

This article provides an overview of the mainstream deep learning approaches and research directions proposed over the past decade. It is important to emphasize that each approach has strengths and "weaknesses, depending on the application and context in "which it is being used. Thus, this article presents a summary on the current state of the deep machine learning field and some perspective into how it may evolve. Convolutional Neural Networks (CNNs) and Deep Belief Networks (DBNs) (and their respective variations) are focused on primarily because they are well established in the deep learning field and show great promise for future work.
Effects of slow-release urea fertilizers on urease activity, microbial biomass, and nematode communities in an aquic brown soil

A field experiment was carried out at the Shenyang Experimental Station of Ecology (CAS) in order to study the effects of slow-release urea fertilizers high polymer-coated urea (SRU1), SRU1 mixed with dicyandiamide DCD (SRU2), and SRU1 mixed with calcium carbide CaC2 (SRU3) on urease activity, microbial biomass C and N, and nematode communities in an aquic brown soil during the maize growth period. The results demonstrated that the application of slow-release urea fertilizers inhibits soil urease activity and increases the soil NH4 +-N content. Soil available N increment could promote its immobilization by microorganisms. Determination of soil microbial biomass N indicated that a combined application of coated urea and nitrification inhibitors increased the soil active N pool. The population of predators/omnivores indicated that treatment with SRU2 could provide enough soil NH4 +-N to promote maize growth and increased the food resource for the soil fauna compared with the other treatments.
The neurophysiology of brain injury

This article reviews the mechanisms and pathophysiology of traumatic brain injury (TBI).



Research on the pathophysiology of diffuse and focal TBI is reviewed with an emphasis on damage that occurs at the cellular level. The mechanisms of injury are discussed in detail including the factors and time course associated with mild to severe diffuse injury as well as the pathophysiology of focal injuries. Examples of electrophysiologic procedures consistent with recent theory and research evidence are presented.



Acceleration/deceleration (A/D) forces rarely cause shearing of nervous tissue, but instead, initiate a pathophysiologic process with a well defined temporal progression. The injury foci are considered to be diffuse trauma to white matter with damage occurring at the superficial layers of the brain, and extending inward as A/D forces increase. Focal injuries result in primary injuries to neurons and the surrounding cerebrovasculature, with secondary damage occurring due to ischemia and a cytotoxic cascade. A subset of electrophysiologic procedures consistent with current TBI research is briefly reviewed.



The pathophysiology of TBI occurs over time, in a pattern consistent with the physics of injury. The development of electrophysiologic procedures designed to detect specific patterns of change related to TBI may be of most use to the neurophysiologist.



This article provides an up-to-date review of the mechanisms and pathophysiology of TBI and attempts to address misconceptions in the existing literature.
A Systematic Literature Review of Mobile Cloud Computing

Mobile cloud computing (MCC) is a relatively new concept that leverages the combination of cloud technology, mobile computing, and wireless networking to enrich the usability experiences of mobile users. Many field of application such as mobile health, mobile learning, mobile commerce and mobile entertainment are now taking advantage of MCC technologies. Since MCC is new, there is need to advance research in MCC in order to deepen practice. Currently, what exist are mostly descriptive literature reviews in the area of MCC. In this paper, a systematic literature review (SLR), which offers a structured, methodical, and rigorous approach to the understanding of the trend of research in MCC, and the least and most researched issue is presented. The objective of the study is to provide a credible intellectual guide for upcoming researchers in MCC to help them identify areas in MCC research where they can make the most impact. The SLR was limited to peer-reviewed conference papers and journal articles published from 2002 to 2014. The study reveals that privacy, security and trust in MCC are the least researched, whereas issues of architecture, context awareness and data management have been averagely researched, while issues on operations, end users, service and applications have received a lot of attention in the literature.
Milestones in Software Engineering and Knowledge Engineering History: A Comparative Review

We present a review of the historical evolution of software engineering, intertwining it with the history of knowledge engineering because "those who cannot remember the past are condemned to repeat it." This retrospective represents a further step forward to understanding the current state of both types of engineerings; history has also positive experiences; some of them we would like to remember and to repeat. Two types of engineerings had parallel and divergent evolutions but following a similar pattern. We also define a set of milestones that represent a convergence or divergence of the software development methodologies. These milestones do not appear at the same time in software engineering and knowledge engineering, so lessons learned in one discipline can help in the evolution of the other one.
Chemical Constituents and Biological Activities of Promising Aromatic Plant Nagarmotha (Cyperus scariosus R.Br.): A Review

Cyperus scariosus R.Br. (Nagarmotha) is pestiferous perennial, delicate slender sedge found wildly in various parts of the country, especially in damp or marshy areas and collected wildly for extraction of its essential oil using steam distillation. The rhizomes of C. scariosus possess pleasant aromatic odour, the essential oil is used as anti-inflammatory, anti-microbial and anti-fungal agent and it is also used as one of the ingredients in several formulations for the Ayurvedic systems of medicine. Phytochemical studies have shown that the major chemical components of this herb are polyphenol, flavonol, glycoside, alkaloid, saponins, sesquiterpenoids and essential oil. Rhizome of the plant is used in fever, arthritis, diuretic, nervine tonic, treatment of diarrhea and dysentery, leprosy, bronchitis, amenorrhea and blood disorders. The fruits of the plant are used as carminative, diuretic tonic and have stomachic. The details of plant and its essential oil, chemical constituents and biological activities have been described in this review.
Accelerated healing of complex open pilonidal wounds using MatriStem extracellular matrix xenograft: nine cases

Complex open pilonidal wounds represent a challenging wound healing problem. Nine cases of complex open pilonidal wounds are described. Each of them was treated at the time of primary wide excision with placement of xenograft extracellular matrix material derived from urinary bladder (MatriStem, ACell Corporation). The patients left the xenograft material and dressings intact and returned to our clinic at weekly intervals for inspection of the wounds. All of the cases of complex open pilonidal wounds healed without infection and without requiring re-operation. The average time to healing in this series was 7 weeks. Treatment of complex open pilonidal wounds with MatriStem extracellular matrix derived from urinary bladder in this fashion results in favorable wound healing of complex open pilonidal wounds.
Anti-aliasing filter improvement in continuous-time feedback sigma-delta modulators

This paper describes a fundamental limitation of the implicit anti-aliasing filter in continuous-time feedback compensated sigma-delta modulators and a method to overcome it. This anti-aliasing filter can be used to relax an additionally required pre filtering stage. If a strong alias rejection is required, commonly used continuous-time feedback compensated sigma-delta modulators would need some pre-filtering or a large oversampling ratio. The described technique generates a notch at the sampling frequency to improve the performance of the antialiasing filter. This method is possible without additional active components or large oversampling ratios. It is also very robust against component mismatch.
A Widely Tunable Compact Patch Antenna

In this letter, we propose a tunable patch antenna made of a slotted rectangular patch loaded by a number of posts close to the patch edge. The posts are short circuited to the ground plane via a set of PIN diode switches. Simulations and measurements verify the possibility of tuning the antenna in subbands from 620 to 1150 MHz. Good matching has been achieved over most of the bands. Other performed designs show that more than one octave can be achieved using the proposed structure.
The Economics of Digital Business Models : A Framework for Analyzing the Economics of Platforms

The paper proposes an analytical framework for comparing different business models for producing information goods and digital services. It is based on three dimensions that also refer to contrasted literature: the economics of matching, the economics of assembling and the economics of knowledge management. Our framework attempts to identify the principal trade-offs at the core of choices among alternative digital business models, and to compare them in terms of competitiveness and efficiency. It also highlights the role played by users in the production of information goods and competition with pure suppliers.
Reconstruction-Based Disentanglement for Pose-Invariant Face Recognition

Deep neural networks (DNNs) trained on large-scale datasets have recently achieved impressive improvements in face recognition. But a persistent challenge remains to develop methods capable of handling large pose variations that are relatively under-represented in training data. This paper presents a method for learning a feature representation that is invariant to pose, without requiring extensive pose coverage in training data. We first propose to generate non-frontal views from a single frontal face, in order to increase the diversity of training data while preserving accurate facial details that are critical for identity discrimination. Our next contribution is to seek a rich embedding that encodes identity features, as well as non-identity ones such as pose and landmark locations. Finally, we propose a new feature reconstruction metric learning to explicitly disentangle identity and pose, by demanding alignment between the feature reconstructions through various combinations of identity and pose features, which is obtained from two images of the same subject. Experiments on both controlled and in-the-wild face datasets, such as MultiPIE, 300WLP and the profile view database CFP, show that our method consistently outperforms the state-of-the-art, especially on images with large head pose variations.
Relationships between pathology and crystal structure in breast calcifications: an in situ X-ray diffraction study in histological sections

Calcifications are not only one of the most important early diagnostic markers of breast cancer, but are also increasingly believed to aggravate the proliferation of cancer cells and invasion of surrounding tissue. Moreover, this influence appears to vary with calcification composition. Despite this, remarkably little is known about the composition and crystal structure of the most common type of breast calcifications, and how this differs between benign and malignant lesions. We sought to determine how the phase composition and crystallographic parameters within calcifications varies with pathology, using synchrotron X-ray diffraction. This is the first time crystallite size and lattice parameters have been measured in breast calcifications, and we found that these both parallel closely the changes in these parameters with age observed in fetal bone. We also discovered that these calcifications contain a small proportion of magnesium whitlockite, and that this proportion increases from benign to in situ to invasive cancer. When combined with other recent evidence on the effect of magnesium on hydroxyapatite precipitation, this suggests a mechanism explaining observations that carbonate levels within breast calcifications are lower in malignant specimens.