Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of skills using a virtual reality temporal bone surgery simulator

SUMMARY Surgery on the temporal bone is technically challenging due to its complex anatomy. Precise anatomical dissection of the human temporal bone is essential and is fundamental for middle ear surgery. We assessed the possible application of a virtual reality temporal bone surgery simulator to the education of ear surgeons. Seventeen ENT physicians with different levels of surgical training and 20 medical students performed an antrotomy with a computer-based virtual temporal bone surgery simulator. The ease, accuracy and timing of the simulated temporal bone surgery were assessed using the automatic assessment software provided by the simulator device and additionally with a modified Final Product Analysis Scale. Trained ENT surgeons, physicians without temporal bone surgical training and medical students were all able to perform the antrotomy. However, the highly trained ENT surgeons were able to complete the surgery in approximately half the time, with better handling and accuracy as assessed by the significant reduction in injury to important middle ear structures. Trained ENT surgeons achieved significantly higher scores using both dissection analysis methods. Surprisingly, there were no significant differences in the results between medical students and physicians without experience in ear surgery. The virtual temporal bone training system can stratify users of known levels of experience. This system can be used not only to improve the surgical skills of trained ENT surgeons for more successful and injury-free surgeries, but also to train inexperienced physicians/medical students in developing their surgical skills for the ear.
Comprehending Chinese Relative Clauses in Context : Thematic Patterns and Grammatical Functions

Processing asymmetries between subjectand object-extracted relative clauses (RCs) have been reported in various languages. This paper examines whether locality or one’s experience of canonical thematic patterns better predicts the processing of head-final RCs by manipulating thematic patterns in the contexts. Two self-paced reading experiments of relative clauses preceded by contexts were conducted. In Experiment 1, two factors were manipulated: the context prior to the RCs consisted of either canonical (Agent-Verb-Patent) or scrambled thematic patterns with BA (Agent-BA-Patient-Verb), and the RCs involved subject or object extractions. It was found that only when preceded by the canonical Agent-Verb-Patent patterns was an ORC advantage obtained. In Experiment 2, we further used passives in the context, forming thematic patterns of Patient-BEI-Agent-Verb. The processing advantage for ORCs was altogether eliminated. We conclude that the processing advantage for Chinese ORCs previously reported was due to thematic priming, not locality. This paper thus shows that in comprehending Chinese relative clauses, the thematic experience in the preceding context is important in determining how easily the relative clause can be comprehended.
Comprehending Comprehensive Income

type="main"> Comprehensive income (CI) contains a mixture of realised, unrealised, temporary, persistent and recyclable elements. How, when and where these elements should be reported in income and equity have been issues intensively debated (and changed) by international regulators over the last 20 years. This article traces the major threads of the debate and places changes within the context of empirical academic research. Our contention is that the recent IAS 1 (AASB 101) Presentation of Financial Statements , effective 1 July 2012, has benefited from past academic research that focused on the value relevance from disaggregation and presentation of unrealised other comprehensive income (OCI). We conclude by outlining the equity posting and recycling to profit or loss (P&L) issues and assert that, because of the inconsistent nature and complexity of OCI, it would benefit from further research.
Enhancement of parametric pumping due to Andreev reflection

We report properties of parametric electron pumping in the presence of a superconducting lead. Due to a constructive interference between the direct reflection and the multiple Andreev reflection, the pumped current is greatly enhanced. For both quantum point contacts and double barrier structures at resonance, we obtain exact solutions in the weak pumping regime showing that IpNS=4IpN, which should be compared with the result of conductance GNS=2GN. Numerical results are also provided for the strong pumping regime showing interesting Andreev assisted pumping behavior.
Application of risk analysis and assessment in tunnel design

A new risk analysis system for estimating the risk factors in tunneling is suggested in consideration of the complex effect in tunnel construction. It is verified that various risk factors can be expressed by stability and environment index using numerical and statistical analysis. Stability index includes the factors of safety of ground condition, the amount of ground settlement, condition of inflow and earthquake as a variable, and environment index includes vibration and noise by blasting under construction and train operation. The risk analysis of geotechnical stability factors were performed by classifying the factor of safety calculated SSR method, the damage of neighboring structure due to settlement, the groundwater inflow rate into the tunnel and the potential damage by the certain earthquake. Also, the environmental factors can be grouped into two aspects such as the construction stage and the operation stage; vibration, noise and the drawdown of the groundwater level caused by tunnel construction. Each risk factor was evaluated as a classified term to be the fixed quantity based on various probabilistic and statistic technique, then it was analyzed the distribution characteristic of risk along tunnel line. Then, the impact was evaluated that how much each risk factor influences on the construction cost with a tunnel construction period by analyzing social charge, so it is possible to perform reasonable tunnel design which was capable of minimizing the risk in the construction stage as well as the design stage. Finally, the applicability of quantitative risk assessment method using stability and environment index are evaluated and utilization method in designing tunnels in Korea is reviewed.
Considering resistance in systematic reviews of antibiotic treatment.

CONTEXT Microorganisms resistant to antibiotic drugs are a threat to the health and chances of survival of patients. Systematic reviews on antibiotic drugs that ignore the topic of resistance present readers with a skewed view, emphasizing short-term efficacy or effectiveness while ignoring long-term consequences. OBJECTIVES To examine whether systematic reviews of antibiotic treatment consider resistance; if not, to find out whether data on resistance were reported in the original trials; and based on that, to offer a framework for taking resistance into account in systematic reviews. DATA SOURCES The Cochrane Database of Systematic Reviews (the Cochrane Library, 2001, issue 2); and MEDLINE, 1996-2000. STUDY SELECTION (i) Systematic reviews or meta-analyses of antimicrobial therapy, published during 1996-2000. (ii) Randomized, controlled trials abstracted in systematic reviews that addressed a topic highly relevant to antibiotic resistance. DATA EXTRACTION We examined each systematic review, and each article, to see whether the implications of resistance were discussed; and whether data on resistance were collected. RESULTS Out of 111 systematic reviews, only 44 (40%) discussed resistance. Ten reviews (9%) planned or performed collection of data on the response of patients with susceptible or resistant isolates. In 22 systematic reviews (20%), collection of data on induction of resistance was planned or performed. The topic of 41 reviews was judged highly relevant to resistance, and these reviews extracted data from 337 articles, out of which we retrieved 279 articles (83%). In 201 (72%) articles, resistance was discussed or data pertaining to it were collected. Ninety-seven articles (35%) gave actual data on resistance of pathogens to the study drugs, 71 articles (25%) data on efficacy of antibiotic drugs in patients with susceptible and resistant pathogens, and 55 articles (20%) provided data on infection or colonization with resistant strains during treatment. CONCLUSIONS Most systematic reviews on antibiotic treatment ignored the issue of resistance, although many of the original articles referred to it and some reported relevant data. Reviewers should collect data on resistance and discuss the implications in their discussion and sections concerned with policy implications.
Topic-related Sentiment Analysis for Discovering Contradicting Opinions in Weblogs

This work addresses the problem of analyzing the evolution of community opinions across time. First, a two-step approach is introduced to determine a continuous sentiment value for each topic discussed in a text based on SentiWordNet as lexical resource. Sentences are clustered according to their topic using Latent Dirichlet Allocation. Both steps are extensively evaluated and tested. The output is then exploited for studying contradictions among weblog posts and comments. We introduce a novel measure for contradictions based on a mean value and the variance of opinions among different posts. In addition, a method is proposed, which identifies posts with contradicting opinions on certain topics on a basis of such a measure. It can be used to analyze and track opinion evolution over time and to identify interesting trends and patterns. The developed algorithm is applied to a dataset of medical blogs and comments on political news with promising performance and accuracy.
Towards Applying Text Mining Techniques on Software Quality Standards and Models

Many of quality approaches are described in hundreds of textual pages. Manual processing of information consumes plenty of resources. In this report we present a text mining approach applied on CMMI, one well known and widely known quality approach. The text mining analysis can provide a quick overview on the scope of a quality approaches. The result of the analysis could accelerate the understanding and the selection of quality approaches.
Performance improvements of video WSN surveillance in case of traffic congestions

The work presented in this paper considers traffic surveillance realized using video camera sensors. These sensors are wireless networked and scattered along the road. They monitor the area of interest and send the most important data to a sink. In case of intense traffic situations the sensors' field of view (FoV) are obstructed by vehicles. The algorithm proposed here maintains coverage by a dynamic sensor management, based on the concept of redundancy. When the algorithm detects traffic congestion, the sensors' obstruction gets worse. Therefore the algorithm adjusts the redundancy value in order to increase the number of active sensors. The performance of the proposed algorithm in this situation is analyzed in this paper. The dependability of the method is proved using Monte Carlo simulation.
Clock Synchronisation in Industry-standard Computer Hardware

Accurate timing is an essential component for various areas of experimental research. Although expensive capture cards provide accurate time stamps for packets seen in networks, those do not help in synchronising applications or in-kemel processes. We present a moderate-cost approach to provide sub-microsecond accuracy on common PC hardware using custom-built clock card. The synchronisation accuracy is improved several orders of magnitude compared with synchronisation over network and an order of magnitude compared with pulse-per-second signal on a serial port. Clock accuracy does not significantly suffer from a high I/O load on the computer.
Metadata-Assisted Global Motion Estimation for Medium-Altitude Unmanned Aerial Vehicle Video Applications

Global motion estimation (GME) is a key technology in unmanned aerial vehicle remote sensing (UAVRS). However, when a UAV’s motion and behavior change significantly or the image information is not rich, traditional image-based methods for GME often perform poorly. Introducing bottom metadata can improve precision in a large-scale motion condition and reduce the dependence on unreliable image information. GME is divided into coarse and residual GME through coordinate transformation and based on the study hypotheses. In coarse GME, an auxiliary image is built to convert image matching from a wide baseline condition to a narrow baseline one. In residual GME, a novel information and contrast feature detection algorithm is proposed for big-block matching to maximize the use of reliable image information and ensure that the contents of interest are well estimated. Additionally, an image motion monitor is designed to select the appropriate processing strategy by monitoring the motion scales of translation, rotation, and zoom. A medium-altitude UAV is employed to collect three types of large-scale motion datasets. Peak signal to noise ratio (PSNR) and motion scale are computed. This study’s result is encouraging and applicable to other medium- or high-altitude UAVs with a similar system structure.
A novel human truncated IL12rβ1-Fc fusion protein ameliorates experimental autoimmune encephalomyelitis via specific binding of p40 to inhibit Th1 and Th17 cell differentiation

Interleukin (IL)-12 and IL-23 respectively driving polarization of T helper (Th) 1 and Th17 cells has been strongly implicated in the pathogenesis of both multiple sclerosis (MS) and experimental autoimmune encephalomyelitis (EAE). In this study, we first constructed, expressed and purified a novel human truncated IL12rβ1-Fc fusion protein (tIL12rβ1/Fc) binding multiple forms of the p40 subunit of human IL-12 and IL-23. tIL12rβ1/Fc was found to effectively ameliorate MOG35–55-induced EAE through reducing the production of Th1- and Th17-polarized pro-inflammatory cytokines and suppressing inflammation and demyelination in the focused parts. Moreover, tIL12rβ1/Fc suppressed Th1 (IFN-γ+ alone) and IFN-γ+ IL-17+ as well as the population of classic Th17 (IL-17+ alone) cells in vivo. Furthermore, tIL12rβ1/Fc ameliorated EAE at the peak of disease via the inhibition of STAT pathway, thereby causing a prominent reduction of RORγt (Th17) and T-bet (Th1) expression. Notably, tIL12rβ1/Fc could increase the relative number of CD4+ Foxp3+ regulatory T cells. These findings indicates that tIL12rβ1/Fc is a novel fusion protein for specific binding multiple forms of p40 subunit to exert potent anti-inflammatory effects and provides a valuable approach for the treatment of MS and other autoimmune diseases.
Performance and accuracy trade-off analysis of techniques for anomaly detection in IoT sensors

IoT environments are typically composed of hundreds of geographically distributed sensors. Usually, these sensors are not physically protected from unauthorized access, which makes them vulnerable to exploitation where they can be manipulated to send incorrect data. The identification of such compromised sensors can be helpful in the process of exclusion or verification by administrators. To perform the detection of anomalous sensors, several algorithms can be used. However, based on the algorithm used, this evaluation may be delayed or can be inaccurate. Therefore, to detect sensors with different behavior compared to others, we evaluated the trade-off between performance and accuracy of different anomalies detection algorithms. The results showed that Mahalanobis Distance could improve the trade-off between detecting multiple anomalous sensors at execution time and accuracy to avoid false-positives.
The Universal Biometric System

The Universal Biometric System is a biometric enabled third-party authentication system. It tries to address most of the major issues faced by current biometric industry. Mainly issues relating to integration of biometrics in an enterprise level network. This paper describes a system that hides all the complexity of biometrics and provides biometric technology, vendor and platform independent authentication. It also introduces two novel ideas: many-to-many mapping to reduce the Total Cost of Ownership (TCO) while Device-Hierarchy enforces in-depth security. It achieves biometric vendor, technology and platform independence through the BioAPI specification (the Defacto standard for Biometrics). However the system sets its sights far beyond the BioAPI. It is designed to provide a simple development environment that does not require complex data structures, pointers and memory management inherent to the BioAPI. This is a Proof of Concept effort.
Numerical Simulations of High-Redshift Star Formation in Dwarf Galaxies

We present first results from three-dimensional hydrodynamic simulations of the high-redshift formation of dwarf galaxies. The simulations use an Eulerian adaptive mesh refinement technique to follow the nonequilibrium chemistry of hydrogen and helium with cosmological initial conditions drawn from a popular Λ-dominated, cold dark matter (CDM) model. We include the effects of reionization using a uniform radiation field, a phenomenological description of the effect of star formation, and, in a separate simulation, the effects of stellar feedback. The results highlight the effects of stellar feedback and photoionization on the baryon content and star formation of galaxies with virial temperatures of approximately 104 K. Dwarf-sized dark matter halos that assemble prior to reionization are able to form stars. Most halos of similar mass that assemble after reionization do not form stars by redshift 3. Dwarf galaxies that form stars show large variations in their gas content because of stellar feedback and photoionization effects. Baryon-to-dark matter mass ratios are found to lie below the cosmic mean as a result of stellar feedback. The supposed substructure problem of CDM is critically assessed on the basis of these results. The star formation histories modulated by radiative and stellar feedbacks are discussed. In addition, metallicities of individual objects are shown to be naturally correlated with their mass-to-light ratios, as is also evident in the properties of local dwarf galaxies.
Airborne Chemical Sensing with Mobile Robots

Airborne chemical sensing with mobile robots has been an active research area since the beginning of the 1990s. This article presents a review of research work in this field, including gas distribution mapping, trail guidance, and the different subtasks of gas source localisation. Due to the difficulty of modelling gas distribution in a real world environment with currently available simulation techniques, we focus largely on experimental work and do not consider publications that are purely based on simulations.
Optimizing the IEEE 802.11b Performance using Slow Congestion Window Decrease

We investigate a new process for the decrease of the IEEE 802.11b Contention Window (CW) called CW decrease, introduced by Ni et al. We give some mathematical analysis of the model that explains the experimental results previously obtained. The analysis allows us to refine the MAC optimization and reach the optimal asymptotical saturation throughput when the number of stations increases. We also investigate other parameters such as the average waiting time, that lead us to introduce another variant of the CW decrease that we call additive as opposed to the multiplicative original scheme. We provide some experimental results based upon simulation to validate our analysis. Surprisingly our global goodput rate in the basic mode is kept from 7.4 Mbit/s with 5 stations to more than 7.3 Mbit/s with 100 stations, overperforming by 40% the original basic scheme and by 8% the scheme with the RTS/CTS enhancement.
THE ORIGIN OF THE BLUE TILT IN EXTRAGALACTIC GLOBULAR CLUSTER SYSTEMS

Some early-type galaxies show a correlation between color and integrated magnitude among the brighter metal-poor globular clusters (GCs). This phenomenon, known as the blue tilt, implies a mass–metallicity relationship among these clusters. In this paper, we show that self-enrichment in GCs can explain several aspects of the blue tilt and discuss predictions of this scenario.
Risk and IT factors that Contribute to Competitive Advantage and Corporate Performance

Existing research has established determinants of an IT-enabled strategy for competitive advantage which include IT Leadership, IT Skill, and IT Infrastructure (Sambamurthy 2000; Dehning and Stratopoulos 2003). Although research is emerging to demonstrate risk’s impact on competitive advantage, it still remains focused on mitigation and avoidance as its contribution (McGaughey et al. 1994). This study leverages and expands existing research in the area in three ways: first, it establishes higher-level constructs defined as Technical Leadership, Technical Skill, and Technical Infrastructure. Doing so affords us to have a more robust framework to accommodate additional technical capabilities and assets a firm possesses such as risk. Second, unique information to explain the individual impact of IT-centric and Risk-centric determinants on competitive advantage are uncovered. Third, the combined impact of risk determinants and IT determinants are analyzed and contrasted by creating interaction indices for both.
A layered defense mechanism for a social engineering aware perimeter

While many cyber security organizations urge the corporate world to use defence-in-depth to create vigilant network perimeters, the human factor is often overlooked. Security evaluation frameworks focus mostly on critical assets of an organization and technical aspects of prevailing risks. There is consequently no specific framework to identify, categorize, analyse and mitigate social engineering related risks. This paper identifies the requirement for such a framework through an in-depth investigation of an actual organization and extensive analysis of existing methodologies. On the basis of this a layered defence strategy SERA is developed, starting with the basic building blocks for social-engineering aware risk analysis. A chronological attack classification framework is presented as an enhancement of existing frameworks on social engineering.
Performance and Economic Analysis of Distributed Power Electronics in Photovoltaic Systems

Distributed electronics like micro-inverters and DC-DC converters can help recover mismatch and shading losses in photovoltaic (PV) systems. Under partially shaded conditions, the use of distributed electronics can recover between 15-40% of annual performance loss or more, depending on the system configuration and type of device used. Additional value-added features may also increase the benefit of using per-panel distributed electronics, including increased safety, reduced system design constraints and added monitoring and diagnostics. The economics of these devices will also become more favorable as production volume increases, and integration within the solar panel? s junction box reduces part count and installation time. Some potential liabilities of per-panel devices include increased PV system cost, additional points of failure, and an insertion loss that may or may not offset performance gains under particular mismatch conditions.