Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal management of ankle syndesmosis injuries

Syndesmosis injuries occur when there is a disruption of the distal attachment of the tibia and fibula. These injuries occur commonly (up to 18% of ankle sprains), and the incidence increases in the setting of athletic activity. Recognition of these injuries is key to preventing long-term morbidity. Diagnosis and treatment of these injuries requires a thorough understanding of the normal anatomy and the role it plays in the stability of the ankle. A complete history and physical examination is of paramount importance. Patients usually experience an external rotation mechanism of injury. Key physical exam features include detailed documentation about areas of focal tenderness (syndesmosis and deltoid) and provocative maneuvers such as the external rotation stress test. Imaging workup in all cases should consist of radiographs with the physiologic stress of weight bearing. If these images are inconclusive, then further imaging with external rotation stress testing or magnetic resonance imaging are warranted. Nonoperative treatment is appropriate for stable injuries. Unstable injuries should be treated operatively. This consists of stabilizing the syndesmosis with either trans-syndesmotic screw or tightrope fixation. In the setting of a concomitant Weber B or C fracture, the fibula is anatomically reduced and stabilized with a standard plate and screw construct. Proximal fibular fractures, as seen in the Maisonneuve fracture pattern, are not repaired operatively. Recent interest is moving toward repair of the deltoid ligament, which may provide increased stability, especially in rehabilitation protocols that involve early weight bearing. Rehabilitation is focused on allowing patients to return to their pre-injury activities as quickly and safely as possible. Protocols initially focus on controlling swelling and recovery from surgery. The protocols then progress to restoration of motion, early protected weight bearing, restoration of strength, and eventually a functional progression back to desired activities.
ENERGY EFFICIENT ROUTING IN COGNITIVE RADIO NETWORKS: CHALLENGES AND EXISTING SOLUTIONS

Dynamic Spectrum Allocation using Cognitive Radio (CR) is a promising solution to the spectrum availability problem in wireless networks. Cognitive Radio, however, opens up certain new issues, mainly at the physical, medium access control and routing layer levels. Several solutions have been proposed to tackle these issues and use dynamic spectrum allocation to improve the performance of wireless networks. The focus of most of these has been to improve the throughput and other Quality of Service (QoS) metrics. However, energy spent by a node is also an important matter of concern in most wireless networks e.g. wireless sensor networks. In this paper, we focus on the challenges posed by CR in routing data in an energy efficient manner. We then study some existing solutions to route data energy efficiently in CR networks and suggest some directions for future
Whitening SOA Testing via Event Exposure

Whitening the testing of service-oriented applications can provide service consumers confidence on how well an application has been tested. However, to protect business interests of service providers and to prevent information leakage, the implementation details of services are usually invisible to service consumers. This makes it challenging to determine the test coverage of a service composition as a whole and design test cases effectively. To address this problem, we propose an approach to whiten the testing of service compositions based on events exposed by services. By deriving event interfaces to explore only necessary test coverage information from service implementations, our approach allows service consumers to determine test coverage based on selected events exposed by services at runtime without releasing the service implementation details. We also develop an approach to design test cases effectively based on event interfaces concerning both effectiveness and information leakage. The experimental results show that our approach outperforms existing testing approaches for service compositions with up to 49 percent more test coverage and an up to 24 percent higher fault-detection rate. Moreover, our solution can trade off effectiveness, efficiency, and information leakage for test case generation.
Knowledge and Data Fusion in Probabilistic Networks

Probability theory provides the theoretical basis for a logically coherent process of combining prior knowledge with empirical data to draw plausible inferences and to refine theories as observations accrue. Increases in the expressive power of languages for expressing probabilistic theories have been accompanied by refinements and adaptations of Bayesian learning methods to handle the more expressive constructs. These innovations have established Bayesian learning as a unifying theoretical framework for learning in intelligent systems, and have given rise to practical techniques that are receiving wide application. This paper describes theory and methods for exact and approximate learning of probabilistic theories from a combination of background knowledge and observations. The concepts and methods can be adapted to any knowledge representation framework that can express probability distributions over interpretations of a first-order logic. We focus specifically on methods to learn theories that can be expressed in the Multi-Entity Bayesian Network (MEBN) probabilistic logic. MEBN logic is sufficiently general to represent a probability distribution over interpretations of any set of statements that can be expressed in firstorder predicate calculus. Bayesian inference provides both a proof theory for combining prior knowledge with observational evidence to derive plausible conclusions and a learning theory for refining a representation as observational evidence accrues. A formal specification is provided for the MEBN logic. A semantics is based on random variables provides a logically coherent foundation for open world reasoning. The paper describes modifications of standard Bayesian learning methods to handle the repeated structures that occur in MEBN theories. Methods are given for specifying domain knowledge as MEBN fragments with structure and parameter prior distributions.
A Genetic Algorithm for Source Election in Cooperative Clusters Implementing Network Coding

Reference scenarios of the present research are clusters of cooperating wireless nodes, implementing random linear network coding to enhance the throughput performance of file downloading and information spreading services. In particular, a sub-set of cluster nodes will access, through their cellular link, parts of a file to be exchanged among all cluster members. The paper focus is on the "source election" issue. The novelty of the research lies in the main problem constraints, which make it far different from (and more exacting than) traditional cluster head election problems: the source number can cover the whole range of nodes and all the nodes must be considered data destinations. We propose a source election algorithm, only based on the knowledge of the number of nodes, which is fast in converging to either the optimal or, alternatively, a satisfactory sub-optimal solution. In so doing, we exploit a performing genetic algorithm. Its observed behaviour makes us confident that the followed approach can be the winning one in conditions of null/limited awareness of node position and type of relevant available cellular links.
Integration of reactive and telerobotic control in multi-agent robotic systems

Multi-agent schema-based reactive robotic systems are complemented with the addition of a new behavior controlled by a teleoperator. This enables the whole society to be a(cid:11)ected as a group rather than forcing the operator to con-trol each agent individually. The operator is viewed by the reactive control system as another behavior exerting his/her in(cid:13)uence on the society as a whole. Simulation results are presented for foraging, grazing, and herding tasks. Teleau-tonomous operation of multi-agent reactive systems was demonstrated to be signi(cid:12)cantly useful for some tasks, less so for others.
Holography and Applied String Theory

Until the middle of the 1990’s, string theory had a reputation for being a rather ambitious formalism that, while being the most promising candidate for unifying gravity with the Standard Model, had provided few concrete, testable predictions or applications. This changed following Maldacena’s proposal, the AdS/CFT correspondence or gauge/gravity duality [36, 2], in 1997; building on holographic notions reaching back to the work of ’t Hooft and Susskind, the conjecture posits that certain quantum field theories, in say d spacetime dimensions, are equivalent to quantum theories of gravity in d + 1 dimensions obtained from string theory. This allows one to use string theory to obtain results, such as correlation functions or response functions related to experimental probes, that may be otherwise difficult to compute directly in a field theoretic approach. In particular, the correspondence relates some strongly coupled quantum field theories to the classical limits of certain string theories, e.g. classical gravity, allowing access to quantities where there was previously no tractable approach. Though the most precise formulations of the correspondence often involve particular field theories with large amounts of supersymmetry and in the large N limit, the hope is that the results obtained via holography will shed light on the structure of more realistic theories. Since its inception, gauge/gravity duality has sparked enormous activity in the numerous areas of physics, both in using the classical gravity to learn about strongly coupled quantum field theories (QFT) as well as using QFTs to learn about the nature of quantum gravity. Early applications of the correspondence focused more on its uses in traditional particle physics systems, such as the behavior of QCD (quantum chromodynamics) in the strongly coupled regimes found in heavy ion collisions being explored at RHIC (Relativistic Heavy Ion Collider) and the LHC (Large Hadron Collider), but a widely growing field of late has been applying the duality to condensed matter systems, which has seen a plethora of strongly coupled systems emerge in the past few decades that challenge conventional understandings. In the other direction, the correspondence provides a precise formulation of quantum gravity and can provide useful insight and intuition into the structure of quantum gravity. As quantum gravity has proved to be a rather formidable subject, any insights are welcome and may prove invaluable to our understanding of gravity. In this report we briefly discuss some of the major areas of current holographic research and the results presented during the workshop. Due to the widespread applicability of holographic techniques and numerous open questions regarding the nature of the duality, the topics covered in the workshop ranged over a large
Separability of pose and expression in facial tracking and animation

We explore the application of facial tracking to automated re-animation. To this end, it is necessary to recover both head-pose and facial expression from the facial movement of a performer. However, both effects are coupled. This is a serious problem, which previous studies haven't fully considered. The solution to this interaction problem proposed here is to solve explicitly, at each timestep, for pose and expression variables. In principle this is a nonlinear inverse problem. However, appropriate parameterisation of pose in terms of affine transformations with parallax, and of expression in terms of key-frames, reduces the problem to a bilinear one. This can then be solved directly by Singular Value Decomposition. Thus actor-driven animation has ben implemented in real-time, at video field-rate, using two Indy desktop workstations.
Communication and coping as predictors of fertility problem stress: cohort study of 816 participants who did not achieve a delivery after 12 months of fertility treatment.

BACKGROUND We investigated coping strategies and communication strategies as predictors of fertility problem stress 12 months after start of fertility treatment. METHODS We used a prospective, longitudinal cohort design including 2250 people beginning fertility treatment with a 12-month follow-up. Data were based on self-administered questionnaires measuring communication with partner and with other people, coping strategies: active-avoidance coping, active-confronting coping, passive-avoidance coping, meaning-based coping, and fertility problem stress. The study population included those participants (n = 816, men and women) who had not achieved pregnancy by assisted reproduction or delivery at follow-up. RESULTS Among both men and women, difficulties in partner communication predicted high fertility problem stress (odds ratio for women, 3.47, 95% confidence interval 2.09-5.76; odds ratio for men, 3.69, 95% confidence interval 2.09-6.43). Active-avoidance coping (e.g. avoiding being with pregnant women or children, turning to work to take their mind off things) was a significant predictor of high fertility problem stress. Among men, high use of active-confronting coping (e.g. letting feelings out, asking other people for advice, seeking social support) predicted low fertility problem stress in the marital domain (odds ratio 0.53, 95% confidence interval 0.28-1.00). Among women, medium or high use of meaning-based coping significantly predicted low fertility problem stress in the personal and marital domain. CONCLUSION The study provides information about where to intervene with fertility patients in order to reduce their stress after medically unsuccessful treatment.
Laying the table for HCI: uncovering ecologies of domestic food consumption

Food contributes fundamentally to our well-being: physically, mentally, and socially. Unsurprisingly then, the importance of food to our lives has long been recognized in the social sciences, and more recently, in Human-Computer Interaction. Yet, despite ongoing trends towards the digital augmentation of domestic environments, little consideration has been given to the impact of the material aspects of food consumption in the home. This paper takes an ecological approach to uncovering the role spaces, tabletops, and artefacts play in the social organization of domestic eating practices. Based on our findings of interviews with seven households in England, we discuss implications for those seeking to digitally augment domestic dining.
Leaf Deformation Taking Into Account Fluid Flow

This paper proposes a method for animating leaf structural deformation considering the leaf water content and its change due to evaporation. To achieve this we embed a massspring system into a mesh representing the leaf, and couple the mass-spring parameters with a simulation representing the fluid flow and evaporation occurring in the leaf. This chain of events aims to simulate the natural process that connects the leaf structural deformation to the water amount in the cells through the turgor pressure. To the best of our knowledge no existing method considers this phenomenon in the simulation of leaf wilting in computer graphics.
Small deviations of weighted fractional processes and average non–linear approximation

We investigate the small deviation problem for weighted fractional Brownian motions in L q -norm, 1 < q ≤ ∞. Let B H be a fractional Brownian motion with Hurst index 0 < H < 1. If 1/r:= H + 1/q, then our main result asserts formula math. provided the weight function p satisfies a condition slightly stronger than the r-integrability. Thus we extend earlier results for Brownian motion, i.e. H = 1/2, to the fractional case. Our basic tools are entropy estimates for fractional integration operators, a non-linear approximation technique for Gaussian processes as well as sharp entropy estimates for l q -sums of linear operators defined on a Hilbert space.
VHDL-based Fault Injection with VERIFY1

This paper describes a new methodology to inject transient and permanent faults in digital systems. For this purpose, the simulation based fault injector VERIFY (VHDL-based Evaluation of Reliability by Injecting Faults efficientlY) has been developed, which allows fault injection at several abstraction levels of a digital system. The combined approach of injection and analysis of the results enables the system’s engineer to evaluate the reliability of the system as well as the coverage of fault tolerance mechanisms applied to the system. The approach is applied to the DP32-processor, where faults are injected at pin-level, by flipping bits in internal registers and gate-level. The results of this comparison shows, that the time to recover from a fault and the total number of faults which lead to a recovery differ significantly according to the type of fault injection. Whereas in the first 2 μs after fault injection using the bitflip fault model more than 79% of all faults injected were still present in the system, only 4.5% remained in the processor when using a stuck-at fault model at gate-level.
Research on library management system for CDs attached to books based on Cloud Computing

Nowadays, all of library management systems for CDs attached to books are running independently: independent devices, independent systems, and making CD images independently. That brings huge waste of investment and labor. In this paper, we redesign the management system for CDs attached to books based on Cloud Computing. By comparing and analyzing the two systems, we can see that the system based on Cloud Computing saves the cost of the library greatly. Then we discuss the workflow of database design for the system, management module, release module, and the computing way of the expense.
Witchcraft or Mental Illness

I don’t believe in witches or ghosts or things that go bump in the night. I’ve always thought that the Salem witch trials were a result of mass hysteria (on the part of the persecutors) rather than a phenomenon of dark forces at work. And seeing Arthur Miller’s The Crucible a few years ago, only confirmed my suspicions. So I was gratified to see Dr Quintanilla’s poster at this year’s meeting of the American Psychiatric Association. As a physician and researcher, she factually explains the fallacy of witchcraft. Looking at historical documents dating back to the 15th century, Dr Quintanilla was able to match the symptoms of people condemned as witches with associated neurological and psychiatric disorders, such as epilepsy and hysteria. [Editor’s Note: Natalie Timoshin]
Focus on State Policies Limiting Excess Undergraduate Credit Hours.

State funding for colleges and universities continues to subsidize the cost of educating state residents, as the in-state tuition rate paid by students only covers a portion of the actual expense of providing a college education. However, spiraling expenditures on health care, transportation and other high-priority areas are straining the ability of states to maximize their higher education investments in the face of growing demand.
Modeling OFDM Error Floor in a Small-Time- Dispersion Channel

In this paper, a novel error floor prediction model is proposed for estimating the peak performance of the OFDM transmission in a small- time-dispersion environment – typically indoor. The obtained analytical formula involves both the accordingly modified common channel time- dispersion parameters such as the rms delay spread, but distinct for the advanced multipath echoes and the delayed ones (with respect to the chosen sampling instant), as well as the OFDM signal-specific parameters. The validity of the model was confirmed by the results of the corresponding Monte-Carlo simulations.
Formal Abstraction of Semantics for Detecting Malicious Code

Semantics-based malware detection is a considerable technique to find out the semantically equivalent malicious codes with different layout. This paper presents an abstraction of instructions from lower-level program form to an intermediate representation which describes the program semantics. This abstraction is depended on decompilation technology. We detect malicious code based on patterns, which are obtained by previous experience of malware analysis, and build on top of the abstraction above. At last, we evaluate our method informally, and the result shows that our method is more resilient to detect obfuscated malicious code transformed by several obfuscation policies.
Prolongations of Lie algebras and applications

We study the skew-symmetric prolongation of a Lie subalgebra $\g \subseteq \mathfrak{so}(n)$, in other words the intersection $\Lambda^3 \cap (\Lambda^1 \otimes \g)$. We compute this space in full generality. Applications include uniqueness results for connections with skew-symmetric torsion and also the proof of the Euclidean version of a conjecture posed in \cite{ofarill} concerning a class of Pl\"ucker-type embeddings. We also derive a classification of the metric k-Lie algebras (or Filipov algebras), in positive signature and finite dimension. Prolongations of Lie algebras can also be used to finish the classification, started in \cite{datri}, of manifolds admitting Killing frames, or equivalently flat connections with 3-form torsion. Next we study specific properties of invariant 4-forms of a given metric representation and apply these considerations to classify the holonomy representation of metric connections with vectorial torsion, that is with torsion contained in $\Lambda^1 \subseteq \Lambda^1 \otimes \Lambda^2$.
Improving Text Independent Speaker Identification by Using Genetic Algorithm for Feature Selection

Nowadays, there exist many ways for speaker identification using different classifiers. But the problem is that all these methods use numerous and sometimes repetitive and unsuitable features that increase the modeling costs and decreases the accuracy of speaker identification. So, we seek a way which has the ability to select the best subset of the extracted features and to increase the accuracy of the classifier for speaker identification. In this paper, we have proposed a method based on synergy Genetic evolutionary algorithm with Gaussian Mixture Model classifier considering the selected suitable features of speech to improve the efficiency of text independent speaker identification systems. The algorithm was examined using a sample consisting of 40 people ranging from 30 to 50 years of age who had been selected randomly from Fars Data base. Experimental results showed that the proposed algorithm compared with the GMM classifier, increased the mean accuracy of speaker identification to 11.37% and decreased the mean number of selected features to 53.84%.
Tell Me Who Are Your Friends, and I'll Tell You Who You Are

Mentions of politicians in news articles can reflect politician interactions on their daily activities. In this work, we present a mathematical model to represent such interactions as a graph, and we use it to predict the political affiliation for a list of deputies of the Republic of Ireland. Our results show that there is a relation between political affiliations and mentions in news reports.