Miracle-dz/UniFAR-FTUs huggingface dataset:
Head Pose Estimation Based on 3-D Facial Landmarks Localization and Regression

In this paper we present a system that is able to estimate head pose using only depth information from consumer RGB-D cameras such as Kinect 2. In contrast to most approaches addressing this problem, we do not rely on tracking and produce pose estimation in terms of pitch, yaw and roll angles using single depth frames as input. Our system combines three different methods for pose estimation: two of them are based on state-ofthe- art landmark detection and the third one is a dictionarybased approach that is able to work in especially challenging scans where landmarks or mesh correspondences are too difficult to obtain. We evaluated our system on the SASE database, which consists of 30K frames from 50 subjects. We obtained average pose estimation errors between 5 and 8 degrees per angle, achieving the best performance in the FG2017 Head Pose Estimation Challenge. Full code of the developed system is available on-line.
Gold investment as an inflationary hedge: cointegration evidence with allowance for endogenous structural breaks

This note tests for the presence of a stable long-run relationship between the price of gold and inflation in the United States from 1945 to 2006 and from 1973 to 2006. Since both the gold market and the inflationary regime have been subjected to structural change over time, a novel unit root testing procedure is employed which allows for the timing of significant breaks to be estimated, rather than assumed exogenous. After taking these breaks into account, a modified cointegration approach provides strong evidence of a cointegrating relationship between gold and inflation in the post-war period and since the early 1970s. The results lend support to the widely held view that direct and indirect gold investment can serve as an effective inflationary hedge.
Closing the Gap Between Specification and Programming: VDM++ and Scala

We argue that a modern programming language such as Scala offers a level of succinctness, which makes it suitable for program and systems specification as well as for high-level programming. We illustrate this by comparing the language with the Vdm++ specification language. The comparison also identifies areas where Scala perhaps could be improved, inspired by Vdm++. We furthermore illustrate Scala's potential as a specification language by augmenting it with a combination of parameterized state machines and temporal logic, defined as a library, thereby forming an expressive but simple runtime verification framework.
A study of suicides in Ballarat, Victoria, Australia.

OBJECTIVE To study suicides occurring in Ballarat with regard to incidence, demographic variables, possible causal factors, and association with psychiatric disorders over a period of 5 years. METHOD A detailed review of the coroner's record of every suicide occurring during 1992-1996 was undertaken. Information was obtained on socio-demographic variables, method and circumstances of suicide, and associated psychiatric disorders in each case and subjected to psychological autopsy. RESULTS 75 suicides were recorded. The male to female ratio was 4:1 and average age was 43 years. 60% had associated psychiatric illnesses, mainly affective disorders. Carbon monoxide self-poisoning accounted for 40%, firearms for 30%, and hanging, overdose, asphyxia and other methods for the remaining 30%. It was statistically significant that the younger age group preferred firearms to other methods, and that their suicides were precipitated by interpersonal conflicts. Social and personal difficulties were associated in 33%, and triggering factors were present in 40%. Previous suicide attempts were present in 28%, while 32% had manifest behavior changes preceding suicides or verbalized their intent to suicide. CONCLUSIONS Suicide rates in Ballarat were higher than the average overall Victorian and Australian rates. After a consistent decline over 4 years an increase occurred in 1996. The preferred method of suicide was carbon monoxide, although the young preferred firearms. Demographic and other psychosocial factors were similar to the rest of Australia. Unemployment was not a significant factor. Psychiatric conditions, personal and social problems figured prominently as factors of etiological significance in suicide subjects.
Discrete invariants of varieties in positive characteristic

If S is a scheme of characteristic p, we define an F-zip over S to be a vector bundle with two filtrations plus a collection of semilinear isomorphisms between the graded pieces of the filtrations. For every smooth proper morphism X → S satisfying certain conditions, the de Rham bundles HdRn(X/S) have a natural structure of an F-zip. We givea complete classification of F-zips over an algebraically closed field by studying a semilinear variant of a variety that appears in recent work of Lusztig. For every F-zip over S, our methods give a scheme-theoretic stratification of S. If the F-zip is associated to an abelian scheme over S, the underlying topological stratification is the Ekedahl-Oort stratification. We conclude the paper with a discussion of several examples, such as good reductions of Shimura varieties of PEL type and K3 surfaces.
Skeletal bone age assessment from epiphysis/metaphysis of phalanges using Hausdorff distance

The work explains an efficient method for skeletal bone age assessment (BAA) from the epiphysis/metaphysis of phalanges using Hausdorff distance as the measure for classification. The method was based on the Tanner and Whitehouse (TW2) method of BAA. The system guaranteed accurate BAA for the age range 0-10 years for both male and female. The input image was initially preprocessed and 8 EMROI joints were identified and cropped, which were segmented using difference of the Gaussian (DoG) method. 14 features were extracted from each EMROI and stored as feature vector. In addition, three distance parameters were extracted to compute the closeness of the epiphysis and metaphysis of the fifth finger middle phalanx as a measure of fusion. Finally, classification of the image into one of the ten bone age classes was done by measuring the Hausdorff distance between the trained feature vector and the feature set of the test image. The assigned age class (Class A – J), was then mapped onto the final bone age. The performance of the system was evaluated with the help of diagnosis done by two skilled radiologists. The system was very robust, achieving an accuracy rate of 98%, specificity rate 99%, precision rate 88%, and recall rate 90% when partitioning the dataset into 120 train images and 100 test images. When partitioned into 160 train images and 60 test images, the system scored 99% for accuracy, 99% for specificity, 95% for precision and 94% for recall. For the partition with 180 train images and 40 test images, the proposed method showed 100% results in all the four performance metrics. Key words: Skeletal bone age assessment (BAA), TW2, radiograph, EMROI, epiphysis, metaphysis, Hausdorff distance, classification.
D-branes on some one- and two-parameter Calabi-Yau hypersurfaces

D-branes on one-parameter Calabi-Yau spaces and two-parameter K3-fibered Calabi-Yau manifolds are analyzed from both the Gepner model point of view and the geometric perspective. We compute part of the spectrum of the boundary states and comment on the appearance of the D0-brane as well as on nonsupersymmetric large volume configurations becoming supersymmetric at the Gepner point.
Efficient Mining of Data Streams Using Associative Classification Approach

Data stream associative classification poses many challenges to the data mining community. In this paper, we address four major challenges posed, namely, infinite length, extraction of knowledge with single scan, processing time, and accuracy. Since data streams are infinite in length, it is impractical to store and use all the historical data for training. Mining such streaming data for knowledge acquisition is a unique opportunity and even a tough task. A streaming algorithm must scan data once and extract knowledge. While mining data streams, processing time, and accuracy have become two important aspects. In this paper, we propose PSTMiner which considers the nature of data streams and provides an efficient classifier for predicting the class label of real data streams. It has greater potential when compared with many existing classification techniques. Additionally, we propose a compact novel tree structure called PSTree (Prefix Streaming Tree) for storing data. Extensive experiments conducted on 24 real datasets from UCI repository and synthetic datasets from MOA (Massive Online Analysis) show that PSTMiner is consistent. Empirical results show that performance of PSTMiner is highly competitive in terms of accuracy and performance time when compared with other approaches under windowed streaming model.
MRI and Computed Tomography of Cardiac and Pulmonary Complications of Tetralogy of Fallot in Adults

Tetralogy of Fallot (TOF) represents the most common form of cyanotic congenital heart disease, accounting for 6.8% of all congenital heart disease. As surgical techniques and medical management of patients with TOF have improved, most affected patients are reaching adulthood. Though surgical outcomes are favorable (<2% early mortality rate), adults with TOF may experience complications from the long-term sequelae of congenital heart disease and complications related to treatment. We describe common and uncommon findings in adults with TOF, including pulmonary insufficiency, central and peripheral pulmonary artery stenosis and aneurysms, in addition to graft and shunt-related complications. Pulmonary function abnormalities and lung parenchymal imaging findings will be detailed. The diagnostic value of computed tomography and magnetic resonance imaging in adults with complications of TOF will be illustrated.
Modifying the Gestalt Factor of Proximity: Theories Compared

A theoretical controversy between adaptation-level (AL) theory and response-frequency-equalization (RFE) theory was examined. The stimulus presented for judgment was a matrix of dots which varied in appearance as the relative horizontal and vertical separation between the dots was altered. The matrix appeared to be columns of dots (larger horizontal separation), rows of dots (larger vertical separation), or neither row-like nor column-like (when the two separations were equal). A stimulus with an extreme row organization was presented on alternate trials and resulted in more vertical judgments. Both AL theory and RFE theory are shown to be inadequate on two counts. They both predict that the response latencies to the vertical stimuli should be affected, whereas these were unaffected. They both predict that in terms of the categorical decision, ‘horizontal’ or ‘vertical’, the responses to both horizontal and vertical stimuli should be affected. It is shown that the context effect is almost entirely on the horizontal stimuli. These results are consistent with a spatial-adaptation model.
A high-temperature superconducting filter for future mobile telecommunication systems

This paper presents a narrow-band high-temperature superconducting bandpass filter on a sapphire substrate applicable to future mobile communications systems. The design and simulation of a ten-pole quasi-elliptic function filter implemented using a cascaded quadruplet trisection coupling topology is discussed. The filter is designed to have a 10-MHz passband in the Universal Mobile Telecommunications System base-station receive band. The filter substrate was a sapphire wafer measuring 47 mm /spl times/17 mm /spl times/43 mm, which had a double-sided thin-film coating of Yba/sub 2/Cu/sub 3/O/sub 7/. The filter displayed a minimum insertion loss of 0.2 dB in the passband and a return loss better than (-12dB preliminary) over the passband. A high performance out-of-band rejection associated with a quasi-elliptic filter function was also recorded.
Double-well potential: The Refined Spectral Method

We demonstrate an application of the Refined Spectral Method as an extremely accurate technique for finding the eigenstates and eigenvalues of an arbitrary symmetric double-well potential. Our numerical calculations does not make any use of perturbation techniques and show that the proposed method can give extremely accurate results for this problem. For example here we present results with an accuracy of at least 80 significant digits for the energy splittings, whereas the highest reported accuracy sofar has been 10−15. Moreover, higher precisions are also easily obtainable with this method. Mathematics Subject Classifications (2000). : 34L40, 76M22, 41A99.
Genomics of Hepatitis B and C Infections: Diagnostic and Therapeutic Applications of Microarray Profiling

Microarray profiling offers many potential advances in diagnostic and therapeutic intervention in human disease because of its unparalleled ability to conduct high-throughput analysis of gene expression. However, limitations of this technique relate in part to issues regarding the various methodologies and experimental designs as well as difficulties in the interpretation of results. Despite this, microarray profiling has led to a better understanding of the molecular pathogenesis of hepatitis B virus (HBV) and hepatitis C virus (HCV) infection. Key events in clearance and the development of chronicity of HCV have been identified that may prove to have a role in the development of future treatments. In addition, pharmacogenomic studies of interferon-based treatment for chronic HCV and HBV have provided mechanistic insights into the therapeutic action of interferons. These advances have implications with respect to the development of improved therapeutic agents. New biomarkers for cancer screening and gene profiles with prognostic value for survival have also been developed for hepatocellular carcinoma, which frequently complicates chronic viral hepatitis. Thus, microarray profiling offers enormous potential for improvements in antiviral therapy and our understanding of blood-borne viral hepatitis.
Sunflower genetic, genomic and ecological resources

Long a major focus of genetic research and breeding, sunflowers (Helianthus) are emerging as an increasingly important experimental system for ecological and evolutionary studies. Here, we review the various attributes of wild and domesticated sunflowers that make them valuable for ecological experimentation and describe the numerous publicly available resources that have enabled rapid advances in ecological and evolutionary genetics. Resources include seed collections available from germplasm centres at the USDA and INRA, genomic and EST sequences, mapping populations, genetic markers, genetic and physical maps and other forward‐ and reverse‐genetic tools. We also discuss some of the key evolutionary, genetic and ecological questions being addressed in sunflowers, as well as gaps in our knowledge and promising areas for future research.
Localization of Reversion-Induced LIM Protein (RIL) in the Rat Central Nervous System

Reversion-induced LIM protein (RIL) is a member of the ALP (actinin-associated LIM protein) subfamily of the PDZ/LIM protein family. RIL serves as an adaptor protein and seems to regulate cytoskeletons. Immunoblotting suggested that RIL is concentrated in the astrocytes in the central nervous system. We then examined the expression and localization of RIL in the rat central nervous system and compared it with that of water channel aquaporin 4 (AQP4). RIL was concentrated in the cells of ependyma lining the ventricles in the brain and the central canal in the spinal cord. In most parts of the central nervous system, RIL was expressed in the astrocytes that expressed AQP4. Double-labeling studies showed that RIL was concentrated in the cytoplasm of astrocytes where glial fibrillary acidic protein was enriched as well as in the AQP4-enriched regions such as the endfeet or glia limitans. RIL was also present in some neurons such as Purkinje cells in the cerebellum and some neurons in the brain stem. Differential expression of RIL suggests that it may be involved in the regulation of the central nervous system.
Hybrid Self-Adaptive Evolution Strategies Guided by Neighborhood Structures for Combinatorial Optimization Problems

This article presents an Evolution Strategy (ES)--based algorithm, designed to self-adapt its mutation operators, guiding the search into the solution space using a Self-Adaptive Reduced Variable Neighborhood Search procedure. In view of the specific local search operators for each individual, the proposed population-based approach also fits into the context of the Memetic Algorithms. The proposed variant uses the Greedy Randomized Adaptive Search Procedure with different greedy parameters for generating its initial population, providing an interesting exploration–exploitation balance. To validate the proposal, this framework is applied to solve three different -Hard combinatorial optimization problems: an Open-Pit-Mining Operational Planning Problem with dynamic allocation of trucks, an Unrelated Parallel Machine Scheduling Problem with Setup Times, and the calibration of a hybrid fuzzy model for Short-Term Load Forecasting. Computational results point out the convergence of the proposed model and highlight its ability in combining the application of move operations from distinct neighborhood structures along the optimization. The results gathered and reported in this article represent a collective evidence of the performance of the method in challenging combinatorial optimization problems from different application domains. The proposed evolution strategy demonstrates an ability of adapting the strength of the mutation disturbance during the generations of its evolution process. The effectiveness of the proposal motivates the application of this novel evolutionary framework for solving other combinatorial optimization problems.
k‐t group sparse: A method for accelerating dynamic MRI

Compressed sensing (CS) is a data‐reduction technique that has been applied to speed up the acquisition in MRI. However, the use of this technique in dynamic MR applications has been limited in terms of the maximum achievable reduction factor. In general, noise‐like artefacts and bad temporal fidelity are visible in standard CS MRI reconstructions when high reduction factors are used. To increase the maximum achievable reduction factor, additional or prior information can be incorporated in the CS reconstruction. Here, a novel CS reconstruction method is proposed that exploits the structure within the sparse representation of a signal by enforcing the support components to be in the form of groups. These groups act like a constraint in the reconstruction. The information about the support region can be easily obtained from training data in dynamic MRI acquisitions. The proposed approach was tested in two‐dimensional cardiac cine MRI with both downsampled and undersampled data. Results show that higher acceleration factors (up to 9‐fold), with improved spatial and temporal quality, can be obtained with the proposed approach in comparison to the standard CS reconstructions. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.
Correlation between Thromboplastin Sensitivity and In Vitro F1 + 2 Generation Rate

Prothrombin times (PT) are strongly influenced by the sensitivity of the various thromboplastin preparations (i.e. by the International Sensi­ tivity Index, ISI); the introduction of the International Normalised Ra­ tio (INR) has led to a definite improvement in PT standardisation (1). The 35 kdalton peptide denominated Fragment F I+2 (F I+2), cleaved from the human prothrombin molecule during activation by Factor Xa (2), is considered a reliable measure of prothrombin activation (3). We
Human Glioblastoma Stem‐Like Cells are More Sensitive to Allogeneic NK and T Cell‐Mediated Killing Compared with Serum‐Cultured Glioblastoma Cells

Glioblastoma multiforme (GBM) is the most dramatic primary brain cancer with a very poor prognosis because of inevitable disease recurrence. The median overall survival is less than 1 year after diagnosis. Cancer stem cells have recently been disclosed in GBM. GBM stem‐like cells (GSCs) exhibit resistance to radio/chemotherapeutic treatments and are therefore considered to play an important role in disease recurrence. GSCs are thus appealing targets for new treatments for GBM patients. In this study, we show that GBM cells with stem cell characteristics are resistant to lysis mediated by resting natural killer (NK) cells because of the expression of MHC class I molecules. However, GSCs are killed by lectin‐activated NK cells. Furthermore, in experiments using the therapeutic antibody CetuximAb, we show that GSCs are sensitive to antibody‐mediated cytotoxicity. We confirm the sensitivity of GSC to cytotoxicity carried out by IL2‐activated NK cells and tumor‐specific T cells. More importantly, we show that GSCs are more sensitive to NK and T cell‐mediated lysis relatively to their corresponding serum‐cultured GBM cells obtained from the same initial tumor specimen. Altogether, these results demonstrate the sensitivity of GSC to immune cell cytotoxicity and, therefore, strongly suggest that GSCs are suitable target cells for immunotherapy of GBM patients.
Native Tongues, Lost and Found: Resources and Empirical Evaluations in Native Language Identification

In this paper we present work on the task of Native Language Identification (NLI). We present an alternative corpus to the ICLE which has been used in most work up until now. We believe that our corpus, TOEFL11, is more suitable for the task of NLI and will allow researchers to better compare systems and results. We show that many of the features that have been commonly used in this task generalize to new and larger corpora. In addition, we examine possible ways of increasing current system performance (e.g., additional features and feature combination methods), and achieve overall state-of-the-art results (accuracy of 90.1%) on the ICLE corpus using an ensemble classifier that includes previously examined features and a novel feature (n-gram language models). We also show that training on a large corpus and testing on a smaller one works well, but not vice versa. Finally, we show that system performance varies across proficiency scores.
Context-aware Services Composition based on AI Planning

AI planning technologies has proven to be useful for services composition. By treating service as an action, planners do various sorts of reasoning about how to combine services into a plan. However, planners typically support only limited reasoning capabilities which cannot handle the enormous size of the data involved in the planning process over Web. In parallel, the field of context-aware computing has been focusing on providing information that can be used to characterize the situation of an entity, and thereby using context can filter the inappropriate candidate services and adapt to user’s preference. The major technical contributions of this paper are: (1) We propose an OWL-SC model for the context-aware composition of Web services. (2) We propose contextaware plan architecture and thus is more scalability and flexibility for the planning process, and thereby improving the efficiency and precision. (3) We propose a hybrid approach to build a plan corresponding to a context-aware service composition, based on global planning and local optimization, considering both the usability and adoption. solution.