Miracle-dz/UniFAR-FTUs huggingface dataset:
Can Positive Mood Replenish Resource Depletion Resulting in Less Compliance through a Heuristic ?

This study examines the effect of replenishment of self-regulatory resources after a depleting task, on compliance through a heuristic. The following three hypotheses were tested. Can positive mood replenish previously depleted self-regulatory resources? Do people comply more with a request when they are exposed to a compliance-promoting heuristic? Can replenishment through positive mood counteract the effect of regulatory resource depletion through less reliance on a heuristic? Results showed that none of the predicted effects occurred, but some other significant, partly reversed outcomes have been found. A short rest break did replenish depleted self-regulatory resources more than positive mood, and positive mood in itself had an effect on compliance. Together these results did not support the hypotheses, possibly due to the fact that mood induction and the heuristic activation did not work the way predicted and mood itself had an effect on the compliance measurement. Can positive mood replenish depleted self-regulatory resources resulting in less compliance through a heuristic? 1
REAL TIME FACE DETECTION AND TRACKING USING HAAR CLASSIFIER ON SOC

-In this paper we intend to Implement a real time Face detection and tracking the head poses position’s from high definition video using Haar Classifier through Raspberry Pi BCM2835 CPU processor which is an combination of SoC with GPU based Architecture. OVA5647 CMOS Image sensor with 5-megapixel used for obtaining high definition video H.264 video data via GPU’s hardware video decoder to improve playback of H.264 Video data supporting from 1080p at 30fps with complete user control over formatting and output data transfer also supporting with 720p/60HD video in full field of View(FOV). SimpleCV and OpenCV libraries are used for face detection and tracking the head poses position. The experimental result computed by using computer vision SimpleCV and OpenCV framework libraries along with above mentioned hardware results in a sustained throughput of 30 fps under 1080p resolutions for with higher accuracy and speediness for face detection and tracking the head poses position.
What are Treebank Grammars

State-of-the-art syntactic disambiguators for natural language employ ”Treebank Grammars”: probabilistic grammars directly projected from annotated corpora (treebanks). Treebank Grammars mark a paradigm shift from the manually constructed, a priori fixed linguistic grammars. In this paper we show that for describing these systems in the framework of Statistical Estimation Theory one must assume an unbounded number of parameters. The unboundedness assumption of Treebank Grammars expresses persistent uncertainty over the formal grammar of natural language. We argue that embracing the unboundedness assumption also brings the justification of smoothing techniques within the scope of Estimation Theory.
An information theoretic approach to source enumeration in array signal processing

In this paper, a new information theoretic algorithm is proposed for signal enumeration in array processing. The approach is based on predictive description length (PDL) that is defined as the length of a predictive code for the set of observations. We assume that several models, with each model representing a certain number of sources, will compete. The PDL criterion is computed for the candidate models and is minimized over all models to select the best model and to determine the number of signals. In the proposed method, the correlation matrix is decomposed into two orthogonal components in the signal and noise subspaces. The maximum likelihood (ML) estimates of the angles-of-arrival are used to find the projection of the sample correlation matrix onto the signal and noise subspaces. The summation of the ML estimates of these matrices is the ML estimate of the correlation matrix. This method can detect both coherent and noncoherent signals. The proposed method can be used online and can be applied to time-varying systems and target tracking.
Superstrings on AdS4 × ℂℙ3 as a coset sigma-model

According to the recent proposal by Aharony, Bergman, Jafferis and Maldacena the = 6 supersymmetric Chern-Simons theory in three dimensions has a 't Hooft limit whose holographic dual is described by type IIA superstings on AdS4 × 3 background. We argue that the Green-Schwarz action for type IIA string theory on AdS4 × 3 with κ-symmetry partially fixed can be understood as a coset sigma-model on the same space supplied with a proper Wess-Zumino term. We construct the corresponding sigma-model Lagrangian and show that it is invariant under a local fermionic symmetry which for generic bosonic string configurations allows one to remove 8 out of 24 fermionic degrees of freedom. The remaining 16 fermions together with their bosonic partners should describe the physical content of AdS4 × 3 superstring. As further evidence, we demonstrate that in the plane-wave limit the quadratic action arising from our model reproduces the one emerging from the type IIA superstring. The coset sigma-model is classically integrable which opens up the possibility to investigate its dynamics in a way very similar to the case of AdS5 × S5 superstrings.
Comparative study of multiple-output series resonant inverters for IH applications

This paper presents the comparative study of multiple output inverter topologies in terms of their circuit operation, control techniques, output power, number of switches required and their efficiency. It includes the concept of multi-output inverter for IH applications. Two multi-output topologies are explained for high power and low power applications. These topologies allow higher efficiency, low cost and less switching losses as compared to other multiple output techniques such as paralleled power converters and load-multiplexation technique. The control strategy includes asymmetrical voltage cancellation (AVC), Variable frequency duty cycle (VFDC) and Pulse density modulation (PDM) control techniques. The performance of multiple-output inverter topologies is verified using MATLAB Simulink.
Automatically learning the units of speech by non-negative matrix factorisation

We present an unsupervised technique to discover the (wordsized) speech units in which a corpus of utterances can be decomposed. First, a fixed-length high-dimensional vector representation of the utterances is obtained. Then, the resulting matrix is decomposed in terms of additive units by applying the non-negative matrix factorisation algorithm. On a small vocabulary task, the obtained basis vectors each represent one of the uttered words. We also investigate the amount of speech data that is needed to obtain a correct set of basis vectors. By decreasing the number of occurrences of the words in the corpus, an indication of the learning rate of the system is obtained.
Leveraging Subjective Human Annotation for Clustering Historic Newspaper Articles

The New York Public Library is participating in the Chronicling America initiative to develop an online searchable database of historically significant newspaper articles. Microfilm copies of the newspapers are scanned and high resolution Optical Character Recognition (OCR) software is run on them. The text from the OCR provides a wealth of data and opinion for researchers and historians. However, categorization of articles provided by the OCR engine is rudimentary and a large number of the articles are labeled editorial without further grouping. Manually sorting articles into fine-grained categories is time consuming if not impossible given the size of the corpus. This paper studies techniques for automatic categorization of newspaper articles so as to enhance search and retrieval on the archive. We explore unsupervised (e.g. KMeans) and semi-supervised (e.g. constrained clustering) learning algorithms to develop article categorization schemes geared towards the needs of end-users. A pilot study was designed to understand whether there was unanimous agreement amongst patrons regarding how articles can be categorized. It was found that the task was very subjective and consequently automated algorithms that could deal with subjective labels were used. While the small scale pilot study was extremely helpful in designing machine learning algorithms, a much larger system needs to be developed to collect annotations from users of the archive. The "BODHI" system currently being developed is a step in that direction, allowing users to correct wrongly scanned OCR and providing keywords and tags for newspaper articles used frequently. On successful implementation of the beta version of this system, we hope that it can be integrated with existing software being developed for the Chronicling America project.
Nominal Expressions in Multilingual Corpora: Definites and Demonstratives

This paper presents the results of a multilingual corpus study on definite descriptions and demonstrative noun phrases. The analysis made on a parallel corpus (French and Portuguese) reinforces previous findings regarding the predominance of non-anaphoric uses of definite descriptions in English corpus. It is also shown that the use of demonstrative noun phrases, on the other hand, is more regularly based on discourse salient entities. The analysis involves syntactic issues and is oriented to the design of natural language processing tools.
Enhancing the Strength of an Optical Trap by Truncation

Optical traps (tweezers) are beginning to be used with increasing efficacy in diverse studies in the biological and biomedical sciences. We report here results of a systematic study aimed at enhancing the efficiency with which dielectric (transparent) materials can be optically trapped. Specifically, we investigate how truncation of the incident laser beam affects the strength of an optical trap in the presence of a circular aperture. Apertures of various sizes have been used by us to alter the beam radius, thereby changing the effective numerical aperture and intensity profile. We observe significant enhancement of the radial and axial trap stiffness when an aperture is used to truncate the beam compared to when no aperture was used, keeping incident laser power constant. Enhancement in trap stiffness persists even when the beam intensity profile is modulated. The possibility of applying truncation to multiple traps is explored; to this end a wire mesh is utilized to produce multiple trapping that also alters the effective numerical aperture. The use of a mesh leads to reduction in trap stiffness compared to the case when no wire mesh is used. Our findings lead to a simple-to-implement and inexpensive method of significantly enhancing optical trapping efficiency under a wide range of circumstances.
Asymmetric cooperative multiple access channels with delayed CSI

We consider a two-user multiaccess channel with degraded messages sets in which the channel state information (CSI) is revealed, strictly causally or with one-unit delay, to only the encoder that sends the common message. We study the capacity region of this model. We establish inner and outer bounds on the capacity region. We also identify some special cases in which the bounds meet, thereby characterizing the capacity region in these cases. The outer bound is non-trivial and has a relatively simple convenient expression (it incorporates only one auxiliary random variable). The coding scheme that we use for the inner bound utilizes rate-splitting to resolve a tension at the informed encoder among exploiting the knowledge of the (delayed) CSI (through a noisy network coding or quantize-map-and-forward state compression) and sending information cooperatively with the other encoder. Together with some previous results on closely related models, the results in this paper shed more light on the utility of delayed CSI for increasing the capacity region of multiaccess channels; and tie with some recent progress in this framework.
Robotic radical prostatectomy in high-risk prostate cancer: current perspectives

Around 20%-30% of patients diagnosed with prostate cancer (PCa) still have high-risk PCa disease (HRPC) that requires aggressive treatment. Treatment of HRPC is controversial, and multimodality therapy combining surgery, radiation therapy, and androgen deprivation therapy have been suggested. There has been a trend toward performing radical prostatectomy (RP) in HRPC and currently, robot-assisted laparoscopic RP (RARP) has become the most common approach. Number of publications related to robotic surgery in HRPC is limited in the literature. Tissue and Tumor characteristics might be different in HRPC patients compared to low-risk group and increased surgical experience for RARP is needed. Due to the current literature, RARP seems to have similar oncologic outcomes including surgical margin positivity, biochemical recurrence and recurrence-free survival rates, additional cancer therapy needs and lymph node (LN) yields with similar complication rates compared to open surgery in HRPC. In addition, decreased blood loss, lower rates of blood transfusion and shorter duration of hospital stay seem to be the advantages of robotic surgery in this particular patient group. RARP in HRPC patients seems to be safe and technically feasible with good intermediate-term oncologic results, acceptable morbidities, excellent short-term surgical and pathological outcomes and satisfactory functional results.
Workshop on the Evaluation of Natural Language Processing Systems

In the past few years, the computational linguistics research community has begun to wrestle with the problem of how to evaluate its progress in developing natural language processing systems. With the exception of natural language interfaces there are few working systems in existence, and they tend to focus on very di(cid:11)erent tasks using equally di(cid:11)erent techniques. There has been little agreement in the (cid:12)eld about training sets and test sets, or about clearly de(cid:12)ned subsets of problems that constitute standards for di(cid:11)erent levels of performance. Even those groups that have attempted a measure of self-evaluation have often been reduced to discussing a system's performance in isolation - comparing its current performance to its previous performance rather than to another system. As this technology begins to move slowly into the marketplace, the lack of useful evaluation techniques is becoming more and more painfully obvious.
Molecular and Cellular Pathobiology MYB Is Essential for Mammary Tumorigenesis

MYB oncogene upregulation is associated with estrogen receptor (ER)-positive breast cancer, but disease requirements for MYB function in vivo have not been explored. In this study, we provide evidence of a critical requirement forMYB functions inmodels of human andmurine breast cancer. In human breast cancer, we found thatMYB expression was critical for tumor cell growth both in vitro and in vivo in xenograft settings. In transgenic knockout mice, tissue-specific deletion of the murine MYB gene caused a transient defect in mammary gland development that was reflected in delayed ductal branching and defective apical bud formation. In mouse mammary tumor virus (MMTV)-NEUmice where tumors are initiated by activation of HER2, MYB deletion was sufficient to abolish tumor formation. In the more aggressive MMTV-PyMTmodel system,MYB deletion delayed tumorigenesis significantly. Together, the findings in these transgenic knockout models implied that MYB was critical during an early window inmammary development when it was essential for tumor initiation, even though MYB loss did not exert a lasting impact upon normal mammary function. Two important MYB-target genes that promote cell survival, BCL2 and GRP78/BIP, were each elevated compared with nontransformed mammary epithelial cells, thereby promoting survival as confirmed in colony formation assays in vitro. Taken together, our findings establish a role for MYB at the hub of ERand HER2-dependent pathways in mammary carcinogenesis. Cancer Res; 71(22); 7029–37. 2011 AACR.
Characteristic Number: Theory and Its Application to Shape Analysis

Geometric invariants are important for shape recognition and matching. Existing invariants in projective geometry are typically defined on the limited number (e.g., five for the classical cross-ratio) of collinear planar points and also lack the ability to characterize the curve or surface underlying the given points. In this paper, we present a projective invariant named after the characteristic number of planar algebraic curves. The characteristic number in this work reveals an intrinsic property of an algebraic hypersurface or curve, which relies no more on the existence of the surface or curve as its planar version. The new definition also generalizes the cross-ratio by relaxing the collinearity and number of points for the cross-ratio. We employ the characteristic number to construct more informative shape descriptors that improve the performance of shape recognition, especially when severe affine and perspective deformations occur. In addition to the application to shape recognition, we incorporate the geometric constraints on facial feature points derived from the characteristic number into facial feature matching. The experiments show the improvements on accuracy and robustness to pose and view changes over the method with the collinearity and cross-ratio constraints.
Molecular Mechanics of Chitin-Protein Interface: Terminus and Side Chain

Chitin and protein are two main building blocks for many natural biomaterials such as crustacean cuticles, sponge skeletons and squid beaks. These biological materials gain growing interests with respect to biomimetic material design, since they possess great mechanical properties due to their evolutionarily refined structures at different hierarchy levels. The interaction between chitin and protein critically determines the properties of the composite biological materials. Moreover, living organisms usually encounter a complex environment, and ambient conditions like water, pH and ions are critical factors towards the structural integrity of biomaterials such as the chitin-protein composites. It is therefore essential to study the chitin-protein interface under different environmental conditions. Here, an atomistic model consisting of a chitin substrate and a protein filament is constructed, which is regarded as a representative of the chitin-protein interface existing in many chitin-based biomaterials. Based on this model, the mechanical properties of chitin-protein interface under different moisture and pH values are investigated through molecular dynamics simulations. The results reveal that there is a weakening effect of water towards the chitin-protein interface, as well as the influence of acidity, i.e. the protonated protein in acidic environment forms a stronger adhesion to chitin than that in the alkaline environment. In addition, the effect from side-chain of protein is studied and it is found that certain kinds of amino acid can form hydrophobic connections to chitin surface, which means that these peptides partly dodge the weakening effect of water. Our observation indicates that terminuses and side-chains in protein are of crucial importance in forming interfacial hydrogen bonds, which connect protein to chitin and contribute to the adhesion. From our full atomistic models, we can observe some molecular mechanisms about how protein interacts with chitin in different conditions, which may spotlight the engineering on biomaterials with similar interfaces. Key Reference: Jin K, Feng X, Xu Z (2013) Mechanical Properties of Chitin-Protein Interfaces: A Molecular Dynamics Study. BioNanoScience: 1—9
A Queueing Model for Wireless Tandem Network Coding

In this paper, we propose a new analytical model in order to evaluate the throughput of a wireless tandem network coding. Our analytical model is based on a multi-class open queueing network. In this model, we include two basic processes of network coding, i.e., packets combination and packets multicasting, in a suitable way considering the constraints of the queueing networks. To this end, we consider the coded packets as new classes of customers. In our model we consider the arrival and departure rates in and from the wireless nodes in steady state. By solving the related traffic equations and applying the stability condition, we compute the maximum stable throughput, i.e., the maximum packet generation rate at which the packets reach their destinations with finite delays. We apply our approach on a simple and yet fundamental model of wireless tandem networks with multicast flows and two different MAC schemes, i.e., scheduled access and slotted random access and then compute the maximum stable throughputs for the cases of simple routing and network coding, distinctly. Finally, we confirm our analytical results by simulation.
Exploiting Stylistic Idiosyncrasies for Authorship Attribution

Introduction Early researchers in authorship attribution used a variety of statistical methods to identify stylistic discriminators – characteristics which remain approximately invariant within the works of a given author but which tend to vary from author to author (Holmes 1998, McEnery & Oakes 2000). In recent years machine learning methods have been applied to authorship attribution. A few examples include (Matthews & Merriam 1993, Holmes & Forsyth 1995, Stamatatos et al 2001, de Vel et al 2001).
Cerebrovascular egmentation based on region growing and level set algorithm

This paper proposed a cerebrovascular segmentation model based on region growing and level set. Firstly, a statistics and region growing model is used to detect the vessel region. During the process, a Maximum Intensity Projection (MIP) image from volume data is segmented by Otsu algorithm to get the seeds, and then to get the contour of vessel by an improved region growing algorithm. Moreover, an improved local-adaptive level set method is developed to implement the accurate segmentation. It can be seen from the results that this hybrid segmentation algorithm is more accurate than the general level set algorithm, especially segmented the vessels with small radius.
Using Coverage Maps to Represent the Environment of Mobile Robots

Generating maps belongs to the fundamental tasks of mobile robots. In the past, many approaches have used occupancy grid maps to represent the environment during mapping and exploration. Occupancy grids, however, are based on the assumption that each cell is either occupied or free. In this paper we introduce coverage maps as an alternative way of representing the environment of a robot. Coverage maps store for each cell of a given grid a posterior about the amount the corresponding cell is covered by an obstacle. We also present a model that allows us to update coverage maps upon input obtained from proximity sensors. We furthermore describe how to use coverage maps for a decision theoretic approach to exploration. Finally we present experimental results illustrating that coverage maps can be used to efficiently learn highly accurate models even if noisy sensors such as ultrasounds are used.