Miracle-dz/UniFAR-FTUs huggingface dataset:
A fully actuated quadrotor UAV with a propeller tilting mechanism: Modeling and control

Equipped with four actuators, quadrotor Unmanned Aerial Vehicles belong to the family of underactuated systems. The lateral motion of such platforms is strongly coupled with their orientation and consequently it is not possible to track an arbitrary 6D trajectory in space. In this paper, we propose a novel quadrotor design in which the tilt angles of the propellers with respect to the quadrotor body are being simultaneously controlled with two additional actuators by employing the parallelogram principle. Since the velocity of the controlled tilt angles of the propellers does not appear directly in the derived dynamic model, the system cannot be static feedback linearized. Nevertheless, the system is linearizable at a higher differential order, leading to a dynamic feedback linearization controller. Simulations confirm the theoretical findings, highlighting the improved motion capabilities with respect to standard quadrotors.
Gene silencing by siRNAs and antisense oligonucleotides in the laboratory and the clinic

Synthetic nucleic acids are commonly used laboratory tools for modulating gene expression and have the potential to be widely used in the clinic. Progress towards nucleic acid drugs, however, has been slow and many challenges remain to be overcome before their full impact on patient care can be understood. Antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs) are the two most widely used strategies for silencing gene expression. We first describe these two approaches and contrast their relative strengths and weaknesses for laboratory applications. We then review the choices faced during development of clinical candidates and the current state of clinical trials. Attitudes towards clinical development of nucleic acid silencing strategies have repeatedly swung from optimism to depression during the past twenty years. Our goal is to provide the information needed to design robust studies with oligonucleotides, making use of the strengths of each oligonucleotide technology.
Area implications of memory partitioning for high-level synthesis on FPGAs

FPGAs normally have numerous independent memory banks that can be accessed simultaneously, potentially offering a very large memory bandwidth. Adopting a suitable application-based memory partitioning strategy is thus vital to take full advantage of the memory architecture. In addition to improving the potential memory bandwidth, partitioning also affects the area complexity of the generated system because the required steering logic depends on the partitioning scheme. This work describes the area implications of a lattice-based memory partitioning technique in the context of high-level synthesis for FPGAs. Experimental results with a commercial HLS tool show that the proposed partitioning technique improves area efficiency compared to alternative approaches.
Information state and dialogue management in the TRINDI dialogue move engine toolkit

We introduce an architecture and toolkit for building dialogue managers currently being developed in the TRINDI project, based on the notions of information state and dialogue move engine. The aim is to provide a framework for experimenting with implementations of different theories of information state, information state update and dialogue control. A number of dialogue managers are currently being built using the toolkit, and we present overviews of two of them. We believe that this framework will make implementation of dialogue processing theories easier, also facilitating comparison of different types of dialogue systems, thus helping to achieve a prerequisite for arriving at a best practice for the development of the dialogue management component of a spoken dialogue system.
Fuzzy Clustering Based Hierarchical Metamodeling For Space Reduction and Design Optimization

For computation-intensive design problems, metamodeling techniques are commonly used to reduce the computational expense during optimization; however, they often have difficulty or even fail to model an unknown system in a large design space, especially when the number of available samples is limited. This paper proposes an intuitive method to systematically reduce the design space to a relatively small region. This method entails three main elements: 1) constructing surrogate approximations using either response surface or kriging models to capture unknown systems in the original large space; 2) calculating many inexpensive points from the obtained surrogate model, clustering these points using the Fuzzy c-means clustering method, and choosing an attractive cluster and its corresponding reduced design space; 3) progressively generating sample points to construct kriging models and identify the design optimum within the reduced design space. The proposed method is illustrated using the well-known six-hump camel back problem. The method is then applied to a constrained, highly nonlinear optimization problem and a real design problem. After comparing with other methods, it is found that the proposed method can intuitively capture promising design regions and can efficiently identify the global or near-global design optimum with the presence of highly nonlinear constraints. The effect of using either response surface or kriging models in the original design space is also compared and discussed. Limitations of the proposed method are illustrated.
SceneCtrl: Mixed Reality Enhancement via Efficient Scene Editing

Due to the development of 3D sensing and modeling techniques, the state-of-the-art mixed reality devices such as Microsoft Hololens have the ability of digitalizing the physical world. This unique feature bridges the gap between virtuality and reality and largely elevates the user experience. Unfortunately, the current solution only performs well if the virtual contents complement the real scene. It can easily cause visual artifacts when the reality needs to be modified due to the virtuality (e.g., remove real objects to offer more space for virtual objects), a common scenario in mixed reality applications such as room redecoration and environment design. We present a novel system, called emph{SceneCtrl}, that allows the user to interactively edit the real scene sensed by Hololens, such that the reality can be adapted to suit virtuality. Our proof-of-concept prototype employs scene reconstruction and understanding to enable efficient editing such as deleting, moving, and copying real objects in the scene. We also demonstrate emph{SceneCtrl} on a number of example scenarios in mixed reality, verifying the enhanced experience by resolving conflicts between virtuality and reality.
Manual removal of the placenta and postcesarean endometritis.

OBJECTIVE To determine if manual vs. spontaneous delivery of the placenta at cesarean section affects the rate of postoperative endometritis and amount of blood loss. STUDY DESIGN A prospective, randomized study was carried out on patients who had cesarean delivery assigned either to spontaneous delivery of the placenta (group 1) or manual removal (group 2). We excluded patients undergoing emergency cesareans and those with possible placenta accreta or evidence of preexisting infection. Outcome measures (frequency of endometritis and quantitative decrease in hemoglobin) were compared for the two groups. RESULTS Study criteria were met for 375 subjects: 177 in group 1 and 198 in group 2. Endometritis was diagnosed in 1.7% of the former and 2.5% of the latter. The change in hemoglobin, reflecting operative blood loss, was similar in both groups (-1.81 and -1.72 g/dL, respectively). CONCLUSION We found no significant difference in either postoperative endometritis or blood loss regardless of the means used to effect delivery of the placenta. The frequency of febrile morbidity in our study cases was considerably lower than heretofore reported.
Big-data: Acid versus base for database transactions

Database developers all know the ACID acronym. It says that database transactions should be: Atomic, Consistent, Isolated, and Durable. These qualities seem indispensable, and yet they are incompatible with availability and performance in very large systems. For example, suppose you run an online book store and you proudly display how many of each book you have in your inventory. Every time someone is in the process of buying a book, you lock part of the database until they finish so that all visitors around the world will see accurate inventory numbers. That works well if you run The Shop around the Corner but not if you run Amazon.com. Amazon might instead use cached data. Users would not see not the inventory count at this second, but what it was say an hour ago when the last snapshot was taken. Also, Amazon might violate the “I” in ACID by tolerating a small probability that simultaneous transactions could interfere with each other. For example, two customers might both believe that they just purchased the last copy of a certain book. The company might risk having to apologize to one of the two customers (and maybe compensate them with a gift card) rather than slowing down their site and irritating myriad other customers. There is a computer science theorem that quantifies the inevitable trade-offs. Eric Brewer's CAP theorem says that if you want consistency, availability, and partition tolerance, you have to settle for two out of three. (For a distributed system, partition tolerance means the system will continue to work unless there is a total network failure. A few nodes can fail and the system keeps going.) An alternative to ACID is BASE: Basic Availability, Soft-state, Eventual consistency.
Hindi Character Recognition Using Neural Network and Various Optimizing Techniques : A Survey

Today in this digitized world, Soft Computing techniques like Artificial Neural Network, genetic algorithm and other optimization techniques proved to be an effective way to solve the problem of getting optimum value for character recognition. It provides solution for high dimension problems along with multiple local optima. This paper highlights the implementation of neural network and other techniques like Hidden Markov Modeling (HMM), Differential Evolution (DE) Techniques and Genetic Algorithm on characters for different languages which results in better performance.
Supratentorial lesions contribute to trigeminal neuralgia in multiple sclerosis

Background It has been proposed that multiple sclerosis lesions afflicting the pontine trigeminal afferents contribute to trigeminal neuralgia in multiple sclerosis. So far, there are no imaging studies that have evaluated interactions between supratentorial lesions and trigeminal neuralgia in multiple sclerosis patients. Methods We conducted a retrospective study and sought multiple sclerosis patients with trigeminal neuralgia and controls in a local database. Multiple sclerosis lesions were manually outlined and transformed into stereotaxic space. We determined the lesion overlap and performed a voxel-wise subtraction analysis. Secondly, we conducted a voxel-wise non-parametric analysis using the Liebermeister test. Results From 12,210 multiple sclerosis patient records screened, we identified 41 patients with trigeminal neuralgia. The voxel-wise subtraction analysis yielded associations between trigeminal neuralgia and multiple sclerosis lesions in the pontine trigeminal afferents, as well as larger supratentorial lesion clusters in the contralateral insula and hippocampus. The non-parametric statistical analysis using the Liebermeister test yielded similar areas to be associated with multiple sclerosis-related trigeminal neuralgia. Conclusions Our study confirms previous data on associations between multiple sclerosis-related trigeminal neuralgia and pontine lesions, and showed for the first time an association with lesions in the insular region, a region involved in pain processing and endogenous pain modulation.
BaseNP Chunking using ILP

This paper reports on the application of Inductive Logic Programming (ILP) to the task of BaseNP chunking. After ILP and NP Chunking are discussed, the experimental setup for using ILP to construct a BaseNP tagger in Prolog is described. Finally, the results are analysed quantitatively as well as qualitatively.
Intrusion Monitoring in Process Control Systems

To protect process control networks from cyber intrusions, preventive security measures such as perimeter defenses (for example, network firewalls and demilitarized zones) and secure versions of process control network protocols have been increasingly adopted or proposed. Although system hardening and fixing known vulnerabilities of existing systems are crucial to secure process control systems, intrusion monitoring is essential to ensure that the preventive measures are not compromised or bypassed. Our approach involves a multilayer security architecture for monitoring process control systems to achieve accurate and effective situational awareness. Also, we leverage some of the characteristics of process control systems such as the regularity of network traffic patterns to perform intrusion detection, with the potential to detect unknown attacks. To facilitate human analysts to gain a better understanding of anomalous network traffic patterns, we present a visualization tool that supports multiple user-customizable views and animation for analyzing network packet traces.
Edge-preserving single image super-resolution

This paper proposes a novel approach to single image super-resolution. First, an image up-sampling scheme is proposed which takes the advantages of both bilateral filtering and mean shift image segmentation. Then we use a shock filter to enhance strong edges in the initial up-sampling result and obtain an intermediate high-resolution image. Finally, we enforce a reconstruction constraint on the high-resolution image so that fine details can be inferred by back projection. Since strong edges in the intermediate result are enhanced, ringing artifacts can be suppressed in the back projection step. We compare our algorithm with several state-of-the-art image super-resolution algorithms. Qualitative and quantitative experimental results demonstrate that our approach performs the best.
A prospective study of children with head injures: III. Psychiatric sequelae

SYNOPSIS A 2¼-year prospective study of children suffering head injury is described. Three groups of children were studied: (a) 31 children with ‘severe’ head injuries resulting in a post-traumatic amnesia (PTA) of at least 7 days; (b) an individually matched control group of 28 children with hospital-treated orthopaedic injuries; and (c) 29 children with ‘mild’ head injuries resulting in a PTA exceeding 1 hour but less than 1 week. A retrospective assessment of the children's pre-accident behaviour was obtained by parental interview and teacher questionnaire immediately after the accident and before the behavioural sequelae of the injury could be known. Further psychiatric assessments were undertaken 4 months, 1 year and 21 years after the initial injury. The mild head injury group showed a raised level of behavioural disturbance before the accident but no increase thereafter. It was concluded that head injuries resulting in a PTA of less than I week did not appreciably increase the psychiatric risk. By contrast, there was a marked increase in psychiatric disorders following severe head injury. The high rate of new disorders in children with severe head injuries who were without disorder before the accident, together with the finding of a dose–response relationship with the severity of brain injury, indicated a causal relationship. However, the development of psychiatric disorders in children with severe head injuries was also influenced by the children's pre-accident behaviour, their intellectual level, and their psychosocial circumstances. With the exception of social disinhibition and a slight tendency for the disorders to show greater persistence over time, the disorders attributable to head injury showed no specific features.
Ratio of Dietary n-6/n-3 Polyunsaturated Fatty Acids Independently Related to Muscle Mass Decline in Hemodialysis Patients

Background n-3 polyunsaturated fatty acids (PUFAs) might be useful nutritional strategy for treating patients with sarcopenia. We evaluated the effect of the intake of dietary n-3 PUFAs on the skeletal muscle mass (SMM), appendicular skeletal muscle mass (ASM), and its determinants in patients receiving standard hemodialysis (HD) treatment for the management of end stage renal disease. Methods In this cross-sectional study, data of 111 HD patients were analyzed. Anthropometric and bioelectrical impedance measurements used to estimate the muscle mass were performed the day of dialysis immediately after the dialysis session. Routine laboratory and 3-day dietary data were also collected. The cutoff value of adequate intake (AI) for both n-3 PUFAs and alpha-linolenic acid (ALA) was 1.6 g/day and 1.1 g/day for men and women, respectively. Results The mean age, mean dietary n-3 PUFAs intake, ALA intake, ratio of n-6/n-3 PUFAs intake, SMM, and ASM of patients were 61.4 ± 10.4 years, 2.0 ± 1.3 g/day, 1.5 ± 1.0 g/day, 9.5 ± 6.7 g/day, 23.9 ± 5.5 kg, and 17.5 ± 4.5 kg, respectively. A higher SMM and ASM significantly observed in patients who achieved an AI of n-3 PUFAs. Similar trends appeared to be observed among those patients who achieved the AI of ALA, but the difference was not significantly, except for ASM (P = 0.047). No relevant differences in demographics, laboratory and nutritional parameters were observed, regardless of whether the patients achieved an AI of n-3 PUFAs. Multivariate analysis showed that the BMI and equilibrated Kt/V were independent determinants of the muscle mass. Moreover, the ratio of n-6/n-3 PUFAs was an independent risk determinant of reduced ASM in HD patients. Conclusion Patients with an AI of n-3 PUFAs had better total-body SMM and ASM. A higher dietary ratio of n-6/n-3 PUFAs seemed to be associated with a reduced muscle mass in HD patients.
ALGORITHMS FOR MATRIX EXTENSION AND ORTHOGONAL WAVELET FILTER BANKS OVER ALGEBRAIC NUMBER FIELDS

As a finite dimensional linear space over the rational number field Q, an algebraic number field is of particular importance and interest in mathematics and engineering. Algorithms using algebraic number fields can be efficiently implemented involving only integer arithmetics. We observe that all known finitely supported orthogonal wavelet low-pass filters in the literature have coefficients coming from an algebraic number field. Therefore, it is of theoretical and practical interest for us to consider orthogonal wavelet filter banks over algebraic number fields. In this paper, we formulate the matrix extension problem over any general subfield of C (including an algebraic number field as a special case), and we provide step-by-step algorithms to implement our main results. As an application, we obtain a satisfactory algorithm for constructing orthogonal wavelet filter banks over algebraic number fields. Several examples are provided to illustrate the algorithms proposed in this paper.
Unsupervised Ensemble Anomaly Detection through Time-Periodical Packet Sampling

We propose an anomaly detection method that trains a baseline model describing the normal behavior of network traffic without using manually labeled traffic data. The trained baseline distribution is used as the basis for comparison with the audit network traffic. The proposed method can be carried out in an unsupervised manner through the use of time-periodical packet sampling for a different purpose from which it was intended. That is, we take advantage of the lossy nature of packet sampling for the purpose of extracting normal packets from the unlabeled original traffic data. By using real traffic traces, we show that the proposed method is comparable in terms of false positive and false negative rates on detecting anomalies regarding TCP SYN packets to the conventional method that requires manually labeled traffic data to train the baseline model. In addition, in order to mitigate the possible performance variation due to probabilistic nature of sampled traffic data, we devised an ensemble anomaly detection method that exploits multiple baseline models in parallel. Experimental results show that the proposed ensemble anomaly detection performs well and is not affected by the variability of time-periodical packet sampling.
Combined Linear and Δ-Modulated Switched-Mode PA Supply Modulator for Polar Transmitters

A combined linear and Δ-modulated switched-mode PA supply modulator for polar transmitters is designed in a 0. 25μm CMOS process. The modulator follows the input envelope and achieves 20dB output DR, a maximum efficiency of 75.5%, and 75dB SNDR for envelope signals up to 4MHz occupied RF BW. For a 1625kb/s 8PSK RF input at 900MHz, polar modulation of a GSM-900 PA provides 10dB ACPR improvement.
Measuring Demand Responses to Wholesale Electricity Prices Using Market Power Indices

We investigate wholesale demand response to hourly price movements in the Ontario wholesale electricity market using detailed generator and market level data. We calculate hourly market power measures such as the Lerner Index and the Residual Supplier Index, which are utilized in a Cournot competition model to structurally estimate price elasticity of demand during peak hours of days, seasons and years. We find that price elasticities are small and statistically significant, and they exhibit large variations over the times of days/seasons and show differences over the years. For instance, while the elasticity estimates fall into the range [−0.021, −0.133] in 2007, they are in the interval of [−0.013, −0.053] in 2008. We also extend the study period to include 2006 (during which extreme weather conditions occurred) and 2009 (when the economic crisis hit and natural gas prices plummeted) to measure the demand responses to irregular price movements and find that price elasticities during the economic crisis were higher than a year earlier. Comparing high demand winter hours to high demand summer hours indicates that consumers' price responsiveness is lower in summer than in winter during 2006–2009. Moreover, we employ these indices along with the estimated price elasticities to project the likely impact of interconnection capacity expansions on market prices. Our calibrations show that even a small amount of transmission investment (and hence trade activity) can result in substantial market price reductions. In addition, we discuss how our approach could be used to estimate price elasticities for other goods such as crude oil and gasoline.
Adaptive Task Assignment in Online Learning Environments

With the increasing popularity of online learning, intelligent tutoring systems are regaining increased attention. In this paper, we introduce adaptive algorithms for personalized assignment of learning tasks to student so that to improve his performance in online learning environments. As main contribution of this paper, we propose a a novel Skill-Based Task Selector (SBTS) algorithm which is able to approximate a student's skill level based on his performance and consequently suggest adequate assignments. The SBTS is inspired by the class of multi-armed bandit algorithms. However, in contrast to standard multi-armed bandit approaches, the SBTS aims at acquiring two criteria related to student learning, namely: which topics should the student work on, and what level of difficulty should the task be. The SBTS centers on innovative reward and punishment schemes in a task and skill matrix based on the student behaviour. To verify the algorithm, the complex student behaviour is modelled using a neighbour node selection approach based on empirical estimations of a students learning curve. The algorithm is evaluated with a practical scenario from a basic java programming course. The SBTS is able to quickly and accurately adapt to the composite student competency --- even with a multitude of student models.