Miracle-dz/UniFAR-FTUs huggingface dataset:
Thin-Slice Reconstructions of Nonenhanced CT Images Allow for Detection of Thrombus in Acute Stroke

Background and Purpose— The purpose of this study was to investigate whether thin-slice image reconstructions of cranial nonenhanced CT scans could be used to significantly increase sensitivity for detecting intraluminal thrombus in patients with acute ischemic stroke due to proximal occlusion of the middle cerebral artery. Methods— In a prospective case series, the raw data of nonenhanced CT scans from 54 patients presenting with acute ischemic stroke and proven vascular obliteration of the middle cerebral artery were collected along with the same data from patients not having a stroke but the same sex and age. All raw data were reconstructed with a slice thickness of 5 mm and as thin slices with a thickness of 0.625 mm. Three observers independently evaluated the 5-mm nonenhanced CT reconstructions and 5-mm maximum intensity projections of the thin slices and rated the likelihood of a clot obliterating the middle cerebral artery trunk or first-order branches using a 5-point scale. The results were evaluated in comparison with base data using receiver operating curve analysis. Interobserver agreement was measured using Cohen &kgr; for every pair of observers. Results— The area under the curve for the receiver operating curve analysis for the thick slices ranged from 0.63 to 0.67, whereas for the maximum intensity projection images of the thin slice reconstructions, receiver operating curve analysis revealed areas under the curve between 0.94 and 0.97. Interobserver agreement was higher for thin-slice (&kgr;, 0.69–0.83) versus thick-slice nonenhanced CT reconstructions (&kgr;, 0.38–0.45). Conclusions— Thin-slice reconstructions of standard cranial nonenhanced CT raw data allow for more sensitive and reliable detection of clots occluding the proximal middle cerebral artery.
Feature Quantization and Pooling for Videos

Abstract : Building video representations typically involves four steps: feature extraction quantization, encoding, and pooling. While there have been large advances in feature extraction and encoding, the questions of how to quantize video features and what kinds of regions to pool them over have been relatively unexplored. To tackle the challenges present in video data, it is necessary to develop robust quantization and pooling methods. The first contribution of this thesis, Source Constrained Clustering, quantizes features into a codebook that generalizes better across actions. The main insight is to incorporate readily available labels of the sources generating the data. Sources can be the people who performed each cooking recipe, the directors who made each movie, or the YouTube users who shared their videos. In the pooling step, it is common to pool feature vectors over local regions. The regions of choice include the entire video, coarse spatio-temporal pyramids or cuboids of pre-determined fixed size. A consequence of using indiscriminately chosen cuboids is that widely dissimilar features may be pooled together if they are in nearby locations. It is natural to consider pooling video features over supervoxels for example, obtained from a video segmentation. However, since videos can have a different number of supervoxels, this produces a video representation of variable size. The second contribution of this thesis is a new, fixed size video representation Motion Words, where we pool features over video segments. The ultimate goal of video segmentation is to recover object boundaries, often grouping pixels from regions of very different motion. However, in the context of Motion Words, it is important that regions preserve motion boundaries. The third contribution of this thesis is a supervoxel segmentation, Globally Consistent Supervoxels which respects motion boundaries and provides better spatio-temporal support for Motion Words.
Personal recognition system using hand modality based on local features

Human hand is a physiological biometric trait employed in order to characterize and identify an individual. It is considered as one of the most popular biometric technologies especially in forensic applications, due to its high users acceptance compared to other biometric technologies. In this paper, we propose a new hand biometric system for personal identity verification, combining two local features at matching score level. Indeed, these features are represented by SIFT (Scale Invariant Feature Transform) descriptors and geometrical measurements of the hand. Our experiments are evaluated using Bogazici University Hand database containing 1926 left hand images acquired from 642 subjects and showed promising results which are comparable with other approaches.
Nanoparticle Delivery of Natural Products in the Prevention and Treatment of Cancers: Current Status and Future Prospects

The advent of nanotechnology has had a revolutionary impact on many aspects of 21st century life. Nanotechnology has provided an opportunity to explore new avenues that conventional technologies have been unable to make an impact on for diagnosis, prevention, and therapy of different diseases, and of cancer in particular. Entities in nanometer sizes are excellent platforms to incorporate various drugs or active materials that can be delivered effectively to the desired action site without compromising the activity of the incorporated drug or material. In particular, nanotechnology entities can be used to deliver conventional natural products that have poor solubility or a short half life. Conventional natural products used with entities in nanometer sizes enable us to solve many of the inherent problems (stability, solubility, toxicity) associated with natural products, and also provide a platform for targeted delivery to tumor sites. We recently introduced the novel concept of using nanotechnology for enhancing the outcome of chemoprevention, which we called ‘nanochemoprevention’. This idea was subsequently exploited by several laboratories worldwide and has now become an advancing field in chemoprevention research. This review examines some of the applications of nanotechnology for cancer prevention and therapy using natural products.
2,8,9-Tris(2-methylpropyl)-2,5,8,9-tetraaza-1λ5-phosphatricyclo[3.3.3.01,5]undecan-5-ium chloride dihydrate

The asymmetric unit of the title hydrated salt, C18H40N4P+·Cl−·2H2O, consists of two ionic molecules and four water molecules. The molecular geometry around the pentacoordinate P atom is trigonal–bipyramidal, with a H atom and an apical N atom in axial positions and three N atoms with isobutyl substituents in equatorial positions. The Cl− ions and water molecules are connected via O—H⋯Cl hydrogen bonds, forming chains along [100]. The ethylene bridging groups are disordered with refined site-occupancy ratios of 0.578 (9):0.422 (9).
Integration of a Time-of-Flight Camera into a Mixed Reality System for Handling Dynamic Scenes, Moving Viewpoints and Occlusions in Real-Time

We present a novel approach to mixed reality applications. The key characteristics of the presented system are the use of a automatically generated static environment model and a time-of-flight camera device. The combination of both allows the correct handling of mutual occlusion between real and virtual content on the fly, which is not possible with the currently applied approaches. Typically expensive studio setups with complex camera tracking installations and multi-camera approaches in combination with chroma-keying facilities are used. Our system is rather inexpensive, compact, mobile, flexible and provides convenient calibration procedures. The use of a background model not only eliminates the need for chroma-keying in mixed reality production, it moreover supports planing and alignment of virtual content. Based on depth information the system is generating appropriate depth maps in realtime, making the approach suitable for 3D-TV productions. The presented paper discusses all key elements of mixedreality applications based on our approach. This includes camera pose tracking, correct real-time handling between interacting virtual and real content and the fast environment model building.
Screening for breast cancer in Ireland: the Eccles Breast Screening Programme

The Eccles Breast Screening Programme is a population-based screening programme for breast cancer, based at the Mater Misericordiae Hospital, Dublin. It began in 1989 simultaneously with similar programmes in Belgium, France, Greece, Portugal and Spain. The objectives of the Eccles Programme are: (i) to evaluate the impact of mammographic screening on morbidity and mortality from breast cancer in Irish women; and (ii) to address the feasibility and potential value of a national breast cancer screening programme. The specific group targeted for screening is women born in 1925 to 1940 inclusive, in a defined geographical area comprising north Dublin City and County, and Counties Cavan and Monaghan. The areas combined comprise 16% of the country's population; just over 29,000 women were invited for screening. An analysis of the demographic and socioeconomic features of the target population reveals that it represents the total population remarkably well. Participants were invited from a population register to attend one of two screening units. Follow-up treatment for those with abnormalities takes place predominantly at the Mater Hospital where the facilities of the Departments of Pathology, Surgery and Oncology have been made available to the programme. Almost 18,000 women had a mammogram in the first round of screening, an overall response rate of 62%. A total of 129 cancers were detected, a prevalence of breast cancer of 7.2 per 1,000. Of those, 15 (11.6%) were entirely intraduct, and an additional 7 (5.4%) had minimal invasion. This is considerably higher than the proportion of intraduct cancers seen in referral practice populations.
On a Rapid Lithium Enrichment and Depletion of K Giant Stars

A model scenario has recently been introduced by de la Reza and colleagues to explain the presence of very strong Li lines in the spectra of some low-mass K giant stars. In this scenario all ordinary, Li-poor, K giants become Li rich during a short time (~105 yr) when compared to the red giant phase of 5 × 107 yr. In this “Li period,” a large number of the stars are associated with an expanding thin circumstellar shell supposedly triggered by an abrupt internal mixing mechanism resulting in a surface new 7Li enrichment. This Letter presents nearly 40 Li-rich K giants known up to now. The distribution of these Li-rich giants, along with 41 other observed K giants that have shells but are not Li rich, in a color-color IRAS diagram confirms this scenario, which indicates, also as a new result, that a rapid Li depletion takes place on a timescale of between ~103 and 105 yr. This model explains the problem of the presence of K giants with far-infrared excesses presented by Zuckerman and colleagues. Other present and future tests of this scenario are briefly discussed.
A framework for distributed key management schemes in heterogeneous wireless sensor networks

Key management is a major challenge in the design and deployment of secure wireless sensor networks. A common assumption in most distributed key management schemes is that all sensor nodes have the same capability. However, recent research work has shown that the connectivity and lifetime of the sensor network can be substantially improved if a small number of sensor nodes have more energy capacity and transmission capability. Therefore, how to utilize these heterogeneity features to design a good distributed key management scheme has become an important issue and needs to be explored. In this paper, we propose a framework for key management schemes in distributed wireless sensor networks with heterogeneous sensor nodes. We show by simulations analysis that, with a small number of heterogeneous nodes, the wireless sensor network can achieve higher key connectivity and higher resilience
In-situ Neutron Diffraction Studies of Various Metals on Engin-X at ISIS

Pulsed neutron beams available at the ISIS spallation source offer diverse possibilities for materials characterization. ENGIN-X [1] is the dedicated materials engineering neutron beamline at ISIS. The Engin-X diffractometer operates in time-of-flight (TOF) diffraction mode, using neutron pulses with a range of energies which travel a distance of 50 meters towards the sample before being elastically scattered, so that the TOF of a given neutron is proportional to its wavelength. The primary function of the beamline is the determination of residual stresses within the interior of bulk engineering components and test samples, in particular for the development of modern engineering processes (e.g. welding, peening) and variety of structural integrity investigations. A second important function of the beamline is for studies of fundamental material behaviour, such as composite and rock mechanics, the basic deformation mechanisms of metals, and phase transformations in shape memory alloys and ferroelectrics. In-situ straining neutron diffraction experiments can provide a way to verify assumptions regarding the relative activity of the different deformation systems which can provide valuable information for various polycrystalline deformation models. These models require inputs of the relative activity of the different damage mechanisms operating during deformation. To address this need, a range of sample environment equipment such as hydraulic dynamic mechanical testing rigs, cryogenic [2] and radiant furnaces [3] are available for these investigations on Engin-X as it shown in Table 1.
Inflammation as an Animal Development Phenomenon

Inflammation is a term that has been used throughout history in different contexts; it may represent a simple collection of clinical symptoms for which drugs are developed, a disease mechanism, or even a defense mechanism against microbes validating Pasteur's studies on bacteriology and Darwin's proposed struggle for survival. Thus, an explanation of this term must also consider the scientific questions addressed. In this study, I propose that several of the inflammatory events typically described in immunological, pathological, and pharmacological contexts can also be perceived as mechanisms of animal development. Thus, by recognizing that the generation of an animal form, its conservation, and its regeneration after tissue damage are phenomena of the same nature, inflammation can be addressed through the approach of developmental biology, thereby acquiring a much neglected physiological counterpart.
Cellulose Saccharification after Ultrasonic- Assisted Ionic Liquid [Amim][ HCOO] Pretreatment

In this study we used 1-allyl-3-methyl imidazole formate ([Amim][HCOO]) as ionic liquid to pre-treat the cellulose and determined the rate of polymerization and enzymatic hydrolysis. The results showed that pretreatment with ([Amim][HCOO]) significantly decreased the cellulose polymerization. As the pretreatment temperature went up, the enzymatic hydrolysis rate was first increased and then decreased. The maximal enzymatic hydrolysis rate was achieved when the pretreatment temperature was 90°C. Under the ultrasonic condition, the initial rate of enzymatic hydrolysis for the ionic liquid-treated cellulose was up to 11.10 gL-1h-1, which was 33% increase compared to the untreated cellulose. Scanning Electronic Microscopy (SEM) and Fourier Transform Infrared-Raman Spectroscop (FT-IR) analysis showed that ionic liquid- treated cellulose started to depolymerize. In addition, the crystallinity of the cellulose was significantly decreased after pretreatment with ionic liquid.
M-band packet wavelet Farsi handwriting word recognition Farsi script segmentation based on new wavelet function

Farsi Handwriting Word Recognition (FHWR), especially those with different orientation and scale changes as well as different handwriting style, is a challenging and important problem in document image analysis. This paper proposes a holistic FHWR scheme using local features of M-Band packet wavelet. The rotation and scale invariant local feature extraction for a given word image involves applying a polar transform to eliminate the rotation and scale effects, but at same time produce a row shifted polar image, which is then passed to an M-Band wavelet transform with row shift invariant to eliminate the row shift effects. So, the output M-Band wavelet coefficients are rotation and scale invariant. A local feature vector extracted from each subband of M-Band wavelet coefficients is constructed for rotation and scale invariant FHWR. In the experiments, we employed a Mahalanobis classifier to recognition a set of 224 distinct Farsi words selected from different persons with different style of writing. The experimental results, based on different handwriting style testing data sets for images with different orientations and scales, show that the proposed classification scheme using M-Band wavelet signatures outperforms other holistic handwriting word recognition methods, its overall accuracy rate for joint rotation and scale invariance being 95.8 percent, demonstrating that the extracted local energy features are effective rotation and scale invariant features.
Visual user interface to supporting information seeking behavior in context searching

This paper proposes an interface to support information seeking behavior for context searching. Context searching is a search behavior based on trend-related queries (e.g., “What were the hot topics last year? ”). Our proposed system facilitates such search behavior using trend-related queries. In the current search engine, users encounter difficulty in inputting a trend-related query using natural language because their query needs to have specific terms (e.g., iPod MAX @period). The users also experience difficulty in understanding the search results that are usually presented in a tabular form. To solve these issues, we present a new user interface to facilitate exploratory behavior and understanding. Initially, this interface identifies seven questions that we assume the users will use to perform a context search. Then, the system starts the search according to the classified questions, and the results are displayed in a timeline format.
Evaluation of Decision Tree Pruning Algorithms for Complexity and Classification Accuracy

ABSTRACT Classification is an important problem in data mining. Given a database of records, each with a class label, a classifier generates a concise and meaningful description for each class that can be used to classify subsequent records. A number of popular classifiers construct decision trees to generate class models. These classifiers first build a decision tree and then prune subtrees from the decision tree in a subsequent pruning phase to improve accuracy and prevent “overfitting”. In this paper, the different pruning methodologies available & their various features are discussed. Also the effectiveness of pruning is evaluated in terms of complexity and classification accuracy by applying C4.5 decision tree classification algorithm on Credit Card Database with pruning and without pruning. Instead of classifying the transactions either fraud or non-fraud the transactions are classified in four risk levels which is an innovative concept.
Kurosawa-Desmedt Key Encapsulation Mechanism , Revisited and More ?

While the hybrid public key encryption scheme of Kurosawa and Desmedt (CRYPTO 2004) is provably secure against chosen ciphertext attacks (namely, IND-CCA-secure), its associated key encapsulation mechanism (KEM) is widely known as not IND-CCA-secure. In this paper, we present a direct proof of IND-CCA security thanks to a simple twist on the Kurosawa-Desmedt KEM. Our KEM beats the standardized version of Cramer-Shoup KEM in ISO/IEC 18033-2 by margins of • at least 20% in encapsulation speed, and • up to 60% in decapsulation speed, which are verified by both theoretical comparison and experimental results. The efficiency of decapsulation can be even • about 40% better than the decapsulation of the PSEC-KEM in ISO/IEC 18033-2 • only slightly worse than the decapsulation of the ECIES-KEM in ISO/IEC 18033-2 which is of independent interest since the security of both PSEC-KEM and ECIES-KEM are argued using the controversial random oracle heuristic in contrast to ours. We then generalize the technique into hash proof systems, proposing several KEM schemes with INDCCA security under decision linear and decisional composite residuosity assumptions respectively. All the KEMs are in the standard model, and use standard, computationally secure symmetric building blocks. We finally show that, with additional simple yet innovative twists, the KEMs can be proved resilient to certain amount of leakage on the secret key. Specifically with the DDH-based scheme, a fraction of 1/4− o(1) of the secret key can be leaked, and when conditioned on a fixed leakage rate, we obtain the most efficient leakage-resilient KEMs regarding computation and storage.
Automatic Identification for Singing Style based on Sung Melodic Contour Characterized in Phase Plane

A stochastic representation of singing styles is pro- posed. The dynamic property of melodic contour, i.e., fun- damental frequency (F0) sequence, is assumed to be the main cue for singing styles because it can characterize such typical ornamentations as vibrato . F0 signal trajectories in the phase plane are used as the basic representation. By fitting Gaussian mixture models to the observed F0 trajec- tories in the phase plane, a parametric representation is ob- tained by a set of GMM parameters. The effectiveness of our proposed method is confirmed through experimental evaluation where 94.1% accuracy for singer-class discrim- ination was obtained. these studies try to use the local dynamics of melodic con- tour as a cue for ornamentation, no systematic method has been proposed for characterizing singing styles. A lag system model for typical ornamentations was reported in (14,17-19); however, variation of singing styles was not discussed. In this paper, we propose a stochastic phase plane as a graphical representation of singing styles and show its effectiveness for singing style discrimination. One merit of this representation to characterize singing style is that since neither an explicit detection function for ornamen- tation like vibrato nor estimation of the target note is re- quired, it is robust to sung melodies. In a previous paper (20), we applied this graphical rep- resentation of the F0 contour in the phase plane to a query- by-hamming system and neutralized the local dynamics of the F0 sequence so that only musical information was uti- lized for the query. In contrast, in this study, we use the local dynamics of the F0 sequence for modeling singing styles and disregard the musical information because mu- sical information and singing style are in a dual relation. In this paper, we also evaluate the proposed represen- tation through a singer-class discrimination experiment in which we show that our proposed model can extract the dynamic properties of sung melodies shared by a group of singers. In the next section, we propose stochastic phase plane (SPP) as a stochastic representation of the melodic contour and show how singing ornamentations are modeled by the proposed SPP. In Section 3, we experimentally show the effectiveness of our proposed method through singer class discrimination experiments. Section 4 discusses the ob- tained results and concludes this paper.