Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure Types Design and Genetic Algorithm Dimension Synthesis of a CPM Machine for Injured Fingers

In order to provide a CPM (continuous passive motion) machine for the rehabilitation of injured fingers and a means of quantitative detection and evaluation, we design the structure types of the CPM machine for injured fingers, and analyze the realization principles of the linkages of single degree of freedom and two degrees of freedom. A method of genetic algorithm dimension synthesis of the linkages based on the mechanical properties and motion properties is brought forward. Through the optimization calculation, we can know that the influence of the bars' dimensions to mechanical properties is slim but the motion properties are sensitive to them. The results show that by selecting proper bars' dimensions perfect mechanical properties and motion properties can be got
F-measure optimisation in multi-label classifiers

When a multi-label classifier outputs a real-valued score for each class, a well known design strategy consists of tuning the corresponding decision thresholds by optimising the performance measure of interest on validation data. In this paper we focus on the F-measure, which is widely used in multi-label problems. We derive two properties of the micro-averaged F measure, viewed as a function of the threshold values, which allow its global maximum to be found by an optimisation strategy with an upper bound on computational complexity of O(n2N2), where N and n are respectively the number of classes and of validation samples. So far, only a suboptimal threshold selection rule and a greedy algorithm without any optimality guarantee were known for this task. We then devise a possible optimisation algorithm based on our strategy, and evaluate it on three benchmark, multi-label data sets.
MafA transcription factor identifies the early ret‐expressing sensory neurons

Dorsal root ganglia proceed from the coalescence of cell bodies of sensory neurons, which have migrated dorsoventrally from the delaminating neural crest. They are composed of different neuronal subtypes with specific sensory functions, including nociception, thermal sensation, proprioception, and mechanosensation. In contrast to proprioceptors and thermonociceptors, little is known about the molecular mechanisms governing the early commitment and later differentiation into mechanosensitive neurons. This is mainly due to the absence of specific molecular markers for this particular cell type. Using knockout mice, we identified the bZIP transcription factor MafA as the first specific marker of a subpopulation of “early c‐ret” positive neurons characterized by medium‐to‐large diameters. This marker will allow further functional characterization of these neurons. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 70:485–497, 2010
Normalization of Relative and Incomplete Temporal Expressions in Clinical Narratives

OBJECTIVE To improve the normalization of relative and incomplete temporal expressions (RI-TIMEXes) in clinical narratives. METHODS We analyzed the RI-TIMEXes in temporally annotated corpora and propose two hypotheses regarding the normalization of RI-TIMEXes in the clinical narrative domain: the anchor point hypothesis and the anchor relation hypothesis. We annotated the RI-TIMEXes in three corpora to study the characteristics of RI-TMEXes in different domains. This informed the design of our RI-TIMEX normalization system for the clinical domain, which consists of an anchor point classifier, an anchor relation classifier, and a rule-based RI-TIMEX text span parser. We experimented with different feature sets and performed an error analysis for each system component. RESULTS The annotation confirmed the hypotheses that we can simplify the RI-TIMEXes normalization task using two multi-label classifiers. Our system achieves anchor point classification, anchor relation classification, and rule-based parsing accuracy of 74.68%, 87.71%, and 57.2% (82.09% under relaxed matching criteria), respectively, on the held-out test set of the 2012 i2b2 temporal relation challenge. DISCUSSION Experiments with feature sets reveal some interesting findings, such as: the verbal tense feature does not inform the anchor relation classification in clinical narratives as much as the tokens near the RI-TIMEX. Error analysis showed that underrepresented anchor point and anchor relation classes are difficult to detect. CONCLUSIONS We formulate the RI-TIMEX normalization problem as a pair of multi-label classification problems. Considering only RI-TIMEX extraction and normalization, the system achieves statistically significant improvement over the RI-TIMEX results of the best systems in the 2012 i2b2 challenge.
Structural SVM for visual localization and continuous state estimation

We present an integrated model for visual object localization and continuous state estimation in a discriminative structured prediction framework. While existing discriminative ‘prediction through time’ methods have showed remarkable versatility for visual reconstruction and tracking problems, they tend to assume that the input is known (or the object is segmented) a condition that can rarely be accommodated in images of real scenes. Our structural Support Vector Machine (structSVM) framework offers an end-to-end training and inference framework that overcomes these limitations by consistently searching both in the space of possible inputs (effectively an efficient form of object localization) and in the space of possible structured outputs, given those inputs. We demonstrate the potential of this methodology for 3d human pose reconstruction in monocular images both in the HumanEva benchmark, where 3d ground truth is available, and qualitatively, in un-instrumented images of real scenes.1
Altérations hydrothermales associées aux zones de fractures à l'interface de la couverture sédimentaire et du socle cristallin dans le Fossé rhénan supérieur : application aux forages géothermiques de Rittershoffen (Alsace, France)

La connaissance des reseaux de fractures est essentielle pour comprendre la circulation des fluides dans un reservoir. Cette these s’appuie sur la reconnaissance du reseau de fractures naturelles qui chenalisent les circulations a l’echelle des deux forages profonds GRT-1 et GRT-2 de Rittershoffen (Alsace, France) qui ont recoupe les sediments greseux triasiques et le socle granitique altere dans le cadre d’un projet industriel de geothermie. L’etude structurale de ce reseau de fractures a ete realisee a partir d’imageries de paroi acoustiques correlees a des diagraphies geophysiques standard tandis que l’etude petro-mineralogique se base sur les echantillons de cuttings. Les zones de fractures permeables des puits de Rittershoffen montrent une organisation asymetrique de la permeabilite. Des fractures ouvertes a l’echelle du puits semblent agir comme des drains permeables entoures de halos d’alteration hydrothermale. Ces zones de fractures sont associees a des perturbations locales du profil de temperature dans le puits. La presence de mineraux illitiques heterogenes pourrait etre un indicateur pour prospecter les zones de circulations actuelles et passees a l’echelle des puits. Cette etude geologique permet d’evoluer vers un modele de forage hydrothermal possedant des connexions favorables avec le reservoir sans avoir recours a des operations de stimulation.
Large Asymmetric Hypertrophy of Rectus Abdominis Muscle in Professional Tennis Players

Purpose To determine the volume and degree of asymmetry of the musculus rectus abdominis (RA) in professional tennis players. Methods The volume of the RA was determined using magnetic resonance imaging (MRI) in 8 professional male tennis players and 6 non-active male control subjects. Results Tennis players had 58% greater RA volume than controls (P = 0.01), due to hypertrophy of both the dominant (34% greater volume, P = 0.02) and non-dominant (82% greater volume, P = 0.01) sides, after accounting for age, the length of the RA muscle and body mass index (BMI) as covariates. In tennis players, there was a marked asymmetry in the development of the RA, which volume was 35% greater in the non-dominant compared to the dominant side (P<0.001). In contrast, no side-to-side difference in RA volume was observed in the controls (P = 0.75). The degree of side-to-side asymmetry increased linearly from the first lumbar disc to the pubic symphysis (r = 0.97, P<0.001). Conclusions Professional tennis is associated with marked hypertrophy of the musculus rectus abdominis, which achieves a volume that is 58% greater than in non-active controls. Rectus abdominis hypertrophy is more marked in the non-dominant than in the dominant side, particularly in the more distal regions. Our study supports the concept that humans can differentially recruit both rectus abdominis but also the upper and lower regions of each muscle. It remains to be determined if this disequilibrium raises the risk of injury.
A Systematic Framework for Sentiment Identification by Modeling User Social Effects

Social media is becoming a major and popular technological platform that allows users to express personal opinions toward the subjects with shared interests. Identifying the sentiments of these social media data can help users make informed decisions. Existing research mainly focus on developing algorithms by mining textual information in social media. However, none of them collectively consider the relationships among heterogeneous social entities. Since users interact with social brands in social platforms, their opinions on specific topics are inevitably dependent on many social effects such as user preference on topics, peer influence, user profile information, etc. In this paper, we present a systematic framework to identify sentiments by incorporating user social effects besides textual information. We apply distributed item-based collaborative filtering technique to estimate user preference. Our experiments, conducted on large datasets from current major social platforms, such as Facebook, Twitter, Amazon.com, and Flyertalk.com, demonstrate that incorporating those user social effects can significantly improve sentiment identification accuracy.
The Role of Lexicalization and Pruning for Base Noun Phrase Grammars

This paper explores the role of lexicalization and pruning of grammars for base noun phrase identification. We modify our original framework (Cardie & Pierce 1998) to extract lexicalized treebank grammars that assign a score to each potential noun phrase based upon both the part-of-speech tag sequence and the word sequence of the phrase. We evaluate the modified framework on the "simple" and "complex" base NP corpora of the original study. As expected, we find that lexicalization dramatically improves the performance of the unpruned treebank grammars; however, for the simple base noun phrase data set, the lexicalized grammar performs below the corresponding unlexicalized but pruned grammar, suggesting that lexicalization is not critical for recognizing very simple, relatively unambiguous constituents. Somewhat surprisingly, we also find that error-driven pruning improves the performance of the probabilistic, lexicalized base noun phrase grammars by up to 1.0% recall and 0.4% precision, and does so even using the original pruning strategy that fails to distinguish the effects of lexicalization. This result may have implications for many probabilistic grammar-based approaches to problems in natural language processing: error-driven pruning is a remarkably robust method for improving the performance of probabilistic and non-probabilistic grammars alike.
SAFDIS: A Framework to Bring Self-Adaptability to Service-Based Distributed Applications

Service Based Applications (SBA) running in distributed and heterogeneous environments are subject to varying constraints that can lead to fluctuations in the quality of the application. We propose a solution in the form of a distributed framework for adaptation to improve in a autonomous way the quality delivered by those applications and to maintain it above a minimum level. This framework, named SAFDIS for Self-Adaptation For DIstributed Services, enables the dynamic evolution of service-based architectures by providing all the functionalities of the MAPE model. Among these functionalities, particular emphasis is put on the analysis phase which permits to use several reasoners able to take decisions with multiple temporal scopes, at short term as well as at long term. Specific attention is also paid to the planning phase, which enables to schedule parallel actions while taking into account different constraints.
A Robust Object Detecting and Tracking Method

No feature-based vision system can work unless good features can be identified and tracked from frame to frame. This paper addresses robust feature tracking. We extend the well-known Shi-Tomasi-Kanade tracker by introducing a simple scheme for rejecting spurious features. Interest points extracted with the Harris-SIFT detector can be adapted to affine transformations and give repeatable results. In this paper, an efficient method of object tracking with motion prediction and object recognizing is presented. Then object recognizing are implemented by matching local invariant features which are learned online. The experimental results illustrate that the proposed method is capable of tracking objects under partial or severe occlusions.
Snowmelt‐Driven Trade‐Offs Between Early and Late Season Productivity Negatively Impact Forest Carbon Uptake During Drought

Future projections of declining snowpack and increasing potential evaporation are predicted to advance the timing of snowmelt in mountain ecosystems globally with unknown implications for snowmelt‐driven forest productivity. Accordingly, this study combined satellite‐ and tower‐based observations to investigate the forest productivity response to snowpack and potential evaporation variability between 1989 and 2012 throughout the Southern Rocky Mountain ecoregion, United States. Our results show that early and late season productivity were significantly and inversely related and that future shifts toward earlier and/or reduced snowmelt could decrease snowmelt water use efficiency and thus restrict productivity despite a longer growing season. This was explained by increasing snow aridity, which incorporated evaporative demand and snow water supply, and was modified by summer precipitation to determine total annual productivity. The combination of low snow accumulation and record high potential evaporation in 2012 resulted in the 34 year minimum ecosystem productivity that could be indicative of future conditions.
Block BFGS Methods

We introduce a quasi-Newton method with block updates called Block BFGS. We show that this method, performed with inexact Armijo-Wolfe line searches, converges globally and superlinearly under the same convexity assumptions as BFGS. We also show that Block BFGS is globally convergent to a stationary point when applied to non-convex functions with bounded Hessian, and discuss other modifications for non-convex minimization. Numerical experiments comparing Block BFGS, BFGS and gradient descent are presented.
WattTime: Novel System Power Model and Completion Time Model for DVFS-Enabled Servers

Power consumption costs takes up to half of the operational expenses of data centers, making power management a critical concern. Advances in processor technology provide fine-grained control over operating frequency of processors and this control can be used to trade off power for performance. We show that existing power models incorrectly assume quadratic relationship between power and frequency, leading to higher inaccuracy in prediction. Moreover, existing performance models have significant error margins while predicting performance of memory or file-intensive tasks and HPC applications due to negligence of the combined effects of frequency and CPU variations on the task execution time. In this paper, we empirically derive power and completion time models using linear regression with CPU utilization and operating frequency as parameters. We validate our power model on several Intel and AMD processors by predicting within 2-7% of measured power. We validate our completion time model using five kernels of NASA Parallel Benchmark suite and five CPU, memory and file-intensive benchmarks on four heterogeneous systems and predicting within 1-6% of observed performance.
The Study of the Tropical Cyclone Tracks Over the Western Indian Ocean up to the Mokran Region and Oman Sea.

Cyclones are considered one of the most dangerous meteorological phenomena of the tropical region. Behavior of tropical cyclone trajectories needs to be better understood in order to find predictable aspects of landfall potentially. This research aims to analyze the cyclone tracks statistically and then study of the associated meteorological effects of Gonu cyclone in June 2007 as an example. Using the cluster analysis (K-mean method) 5 principal clusters have been derived and spatial – temporal studies including the monthly variation of cyclone trajectories and their intensity and frequencies are performed. The 4 cluster indicated more spatial variability and expansion (4o-31oN and 48.5o-78oE). The second cluster showed the highest frequency with 349 events as well as the highest maximum intensity and standard deviation of 235.2km/h and 47.96km/h respectively. During 17 June 2007, the Gonu super cyclone traversed the Arabian Sea and reached the Iranian southern shores. In this 7-day period the daily composite maps of different atmospheric levels showed that by intensifying of Gonu cyclone the axis of subtropical high pressures in the lower levels moved to the east and in the 500hp level they moved to the northward over the study region.
Design and implementation of a pneumatically-actuated robot for breast biopsy under continuous MRI

Magnetic Resonance Imaging (MRI) is superior to other imaging modalities such as Ultrasound and Computed Tomography and is used for both diagnostic and therapeutic procedures. However, current breast biopsy procedures based on MR images obtained apriori, use a blind targeting approach, which can be long and painful. Current approaches, due to possible patient motion, can lead to tool tip positioning errors thereby affecting diagnostic accuracy and causing significant patient discomfort, if repeated procedures are required. Hence, it is desired to develop a MRI-compatible robot for breast biopsy procedures without removing the patient from the MRI bore. This approach could potentially avoid multiple biopsy needle insertions and minimize sampling errors. Due to the working principle of MRI, material, actuation, and sensing techniques are limited as the MR images must not be affected significantly during the procedure. In addition, the limited space of the MRI bore requires the robot to be compact. This paper presents a four degrees of freedom robot with a compact parallel mechanism of which three degrees of freedom are pneumatically actuated while the needle driver mechanism is actuated by a piezo motor. Fiber-optic force sensor is also designed, developed, and mounted on the top mobile platform of the parallel mechanism to sense the needle and tissue interaction forces. Position control of the pneumatic cylinders is implemented using PI control with a modified integration term to achieve a slow and smooth motion.
Plane couette flow as model for the nocturnal boundary layer

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Estimation of age-dependent survival rates of female tsetse flies (Diptera : Glossinidae) from ovarian age distributions

Existing attempts to estimate the survival rate of tsetse flies from ovarian age distributions generally assume that the population is stationary. The fact that the survival rate cannot be dissociated from the growth rate by these methods poses a problem. Under the assumption of a stable age distribution, we propose a maximum likelihood method to estimate the ‘apparent survival rate’ for three categories of females: nulliparous ( β 0 ), young parous ( β 1 ) and old parous flies ( β 2 ). The rate depends both on ‘real survival rates’ a 0 , a 1 and a 2 , and a growth rate λ : β 0 = a 0 / λ , β 1 = a 1 / λ , and β 2 = a 2 / λ . We used a matrix model, which can be parameterized if the pupal survival rate and the pupal period are known. Replacing a 0 , a 1 and a 2 by β 0 , λ , β 1 λ , and β 2 λ in the projection matrix, the problem amounts to calculating its dominant eigen-value λ , and hence a 0 , a 1 and a 2 . The application to a field population of Glossina palpalis gambiensis Vanderplank in Burkina Faso showed there was a marked difference in survival rate according to age category. The average survival rate increased with age with decreasing variability. The results suggested that sampling (by trapping) may have had an effect on the dynamics of this tsetse population by ageing it artificially. This method may be a useful tool for monitoring tsetse control.
Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification

This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and social networks. As an example of our current research efforts, we applied temporal data mining analysis techniques to a PSLC DataShop data set [17, 18, 19, 20]. First, we show that process mining techniques allow for discovery of learning processes from student behaviours. Second, sequential pattern mining is used to classify students according to skill. Our results show that considering sequences of activities as opposed to single events improved classification by up to 230%.
Conjugate Effects of Heat and Mass Transfer on MHD Free Convection Flow over an Inclined Plate Embedded in a Porous Medium

The aim of this study is to present an exact analysis of combined effects of radiation and chemical reaction on the magnetohydrodynamic (MHD) free convection flow of an electrically conducting incompressible viscous fluid over an inclined plate embedded in a porous medium. The impulsively started plate with variable temperature and mass diffusion is considered. The dimensionless momentum equation coupled with the energy and mass diffusion equations are analytically solved using the Laplace transform method. Expressions for velocity, temperature and concentration fields are obtained. They satisfy all imposed initial and boundary conditions and can be reduced, as special cases, to some known solutions from the literature. Expressions for skin friction, Nusselt number and Sherwood number are also obtained. Finally, the effects of pertinent parameters on velocity, temperature and concentration profiles are graphically displayed whereas the variations in skin friction, Nusselt number and Sherwood number are shown through tables.