Miracle-dz/UniFAR-FTUs huggingface dataset:
Carnal Knowledge: The Epistemology of Sexual Trauma in Witches' Sabbaths, Satanic Ritual Abuse, and Alien Abduction Narratives

There are strong similarities between the confessions taken from accused witches in early modern Europe, the testimony of Satanic ritual abuse taken by modern therapists, and accounts of alien abduction given under hypnosis. In each of these narratives, a subject describes horrible sexual transgressions performed on them at the hand of a mysterious other: the thorny penis of the Devil, the bizarre anal insertions of Satanists, and the mysterious probing of aliens. The motive behind these sexual acts is never revealed and the existence of the perpetrators is usually in doubt. This article suggests that sexual trauma serves an epistemological function. For such apparent victims, a belief in demons, Satanists, or aliens provides a meaningful worldview, and narratives of sexual transgressions maintain and even compound these beliefs. "Carnal knowledge"—knowledge through sexual encounters—is privileged above visual or auditory encounters, and is therefore more useful for constructing meaningful cosmologies in which human beings may interact with the divine. Carnal knowledge was a privileged form of epistemology in pre-Christian cultures. Since the days of the early Christian Church and the equation of sexuality with sin, carnal knowledge has survived in the form of masochistic and traumatic sexual encounters.
Connected Speech Recognition with an Isolated Word Recognizer

and it explains how a speaker independent isolated word recognizer could be incorporated in a connected word recognition system. The recognizer used here is an Artificial Neural Network (ANN), which is presented as an alternative to the traditional statistical approaches to speech recognition. Here, more weight is given to describe word boundary detection and splitting the input speech signal into separate words. Another area that is being explained here is the concept of language modeling. These two are the areas which make the connected word recognition distinct from isolated word recognition. The main contribution of this paper is the attempt to extend a simple isolated word recognizer into a connected speech recognizer, by introducing sophisticated signal pre-processing and fine-tuning the recognizer output using a language model. Here, the language model was implemented in a very unique way, extending the concept of Hidden Markov Model (HMM), which is a completely new idea introduced.
Online Selection of Tracking Features using AdaBoost

This paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between features into consideration. Pixels of object/background regions are first treated as training samples. The feature selection problem is then modeled as finding a good subset of features and constructing a compound likelihood image with better discriminability for the tracking process. By adopting the AdaBoost algorithm, we iteratively select one best feature which compensate the previous selected features and linearly combine the set of corresponding likelihood images to obtain the compound likelihood image. We include the proposed algorithm into the mean shift based tracking system. Experimental results demonstrate that the proposed algorithm achieve very promising results.
Evaluating and Improving the Quality of Teacher Collaboration

Teacher collaboration is an essential element of substantive school change for which principals have responsibility for cultivating. As such, it is becoming increasingly important for school leaders to employ models of supervision that focus on the performance and improvement of collective teacher behavior. In this article, the authors present a field-tested, action-research leadership framework for evaluating the quality and improving the performance of teacher collaboration at the secondary school level.
Who wrote What Where: Analyzing the content of human and automatic summaries

Abstractive summarization has been a longstanding and long-term goal in automatic summarization, because systems that can generate abstracts demonstrate a deeper understanding of language and the meaning of documents than systems that merely extract sentences from those documents. Genest (2009) showed that summaries from the top automatic summarizers are judged as comparable to manual extractive summaries, and both are judged to be far less responsive than manual abstracts, As the state of the art approaches the limits of extractive summarization, it becomes even more pressing to advance abstractive summarization. However, abstractive summarization has been sidetracked by questions of what qualifies as important information, and how do we find it? The Guided Summarization task introduced at the Text Analysis Conference 2010 attempts to neutralize both of these problems by introducing topic categories and lists of aspects that a responsive summary should address. This design results in more similar human models, giving the automatic summarizers a more focused target to pursue, and also provides detailed diagnostics of summary content, which can can help build better meaning-oriented summarization systems.
When Disfluency Signals Competence: The Effect of Processing Difficulty on Perceptions of Service Agents

This research examines the effect of processing fluency on judgments of agent competence. In the context of service relationships, four studies reveal that the experience of processing difficulty, or disfluency, enhances expectations of agent-exerted effort and competence, which in turn increase expected service value. When reading information about a target service, consumers interpret the difficulty of processing information as a signal of the level of skill required to execute the task, which highlights the agent's expected utility. The authors explore several moderators of this positive effect of disfluency, showing that it is attenuated under conditions that decrease the relevance of consumers’ subjective experiences and it may be reversed on measures of experienced (vs. expected) service value.
Ultratrace Detection of Histamine Using a Molecularly-Imprinted Polymer-Based Voltammetric Sensor

Rapid and cost-effective analysis of histamine, in food, environmental, and diagnostics research has been of interest recently. However, for certain applications, the already-existing biological receptor-based sensing methods have usage limits in terms of stability and costs. As a result, robust and cost-effective imprinted polymeric receptors can be the best alternative. In the present work, molecularly-imprinted polymers (MIPs) for histamine were synthesized using methacrylic acid in chloroform and acetonitrile as two different porogens. The binding affinity of the MIPs with histamine was evaluated in aqueous media. MIPs synthesized in chloroform displayed better imprinting properties for histamine. We demonstrate here histamine MIPs incorporated into a carbon paste (CP) electrode as a MIP-CP electrode sensor platforms for detection of histamine. This simple sensor format allows accurate determination of histamine in the sub-nanomolar range using an electrochemical method. The sensor exhibited two distinct linear response ranges of 1 × 10−10–7 × 10−9 M and 7 × 10−9–4 × 10−7 M. The detection limit of the sensor was calculated equal to 7.4 × 10−11 M. The specificity of the proposed electrode for histamine is demonstrated by using the analogous molecules and other neurotransmitters such as serotonin, dopamine, etc. The MIP sensor was investigated with success on spiked serum samples. The easy preparation, simple procedure, and low production cost make the MIP sensor attractive for selective and sensitive detection of analytes, even in less-equipped laboratories with minimal training.
Heterogeneity between men and women in the influence of the HLA-DRB1 shared epitope on the clinical expression of rheumatoid arthritis.

OBJECTIVE To test the hypothesis that the influence of the HLA-DRB1 shared epitope (SE) on the clinical manifestations of rheumatoid arthritis (RA) differs between men and women. METHODS We assessed 777 consecutive RA patients for age at disease onset, articular manifestations, subcutaneous nodules, laboratory and radiographic findings, and treatment received. We typed HLA-DRB1 alleles by polymerase chain reaction-sequence-specific primer amplification and categorized the number of SE-containing alleles. We used regression models to adjust comparisons between the sexes for age and clustering by recruitment center, and included SE x sex interaction terms to look for heterogeneity between men and women in the effect of the SE. RESULTS Among the 777 RA patients, 548 (71%) were women. Men and women differed significantly in the adjusted frequency of SE positivity (women 71.4% versus men 78.4%; P < or = 0.001). The SE was associated with a younger age at symptom onset and RA diagnosis among men, but not among women. The SE likewise had a significant adverse effect on joint tenderness, swelling, and deformity among men only. The SE was associated with a higher erythrocyte sedimentation rate in women and more frequent positivity for rheumatoid factor among both men and women. CONCLUSION There is heterogeneity between men and women in the effect of the SE on RA susceptibility and clinical expression. Further research is needed to understand the mechanism of this heterogeneity.
The Effect of Out-Group Competition on Individual Behavior and Out-Group Perception in the Intergroup Prisoner’s Dilemma (IPD) Game

Hebrew University of Jerusalem students participated in two experiments of repeated play of the Intergroup Prisoners’ Dilemma (IPD) game, which involves conflict of interests between two groups and, simultaneously, within each group. The experiments manipulated the level of competition exhibited by the out-group members (i.e. their level of contribution to their group’s effort in the conflict). Consistent with the hypothesis that participants use strategies of reciprocal cooperation between groups, higher levels of out-group competition caused participants to increase their contribution and lower levels caused them to decrease it. In addition, participants had accurate recall of the contribution levels of out-group members, and they attributed motivations to out-group members in a manner that reflected their level of contribution. The nature of reciprocation with the out-group is discussed in light of both behavioral and cognitive data.
Electrophysiology of the Normal‐to‐Hypoxic Transition Zone

The “normal-to-hypoxic” transition zone was modeled after the chamber technique for perpendicular and parallel orientation with respect to the direction of fiber axis. The evidence obtained from the recording of the transmembrane action potentials suggests the presence of a preservation phenomenon in the hypoxic area, based on the utilization of energy stores of the normoxic area. The preservation phenomenon is enhanced with improvement of the intercellular communication. Better intercellular coupling in longitudinal than in transverse fiber direction results in the anisotropic properties of the preservation phenomenon. The preservation phenomenon provides a basis for the existence of critical size of the viable hypoxic area compared to the size of the transitional zone. The crucial role of electrotonic coupling was demonstrated, as well as the possible contribution to the preservation phenomenon mechanism of the cell-to-cell diffusion of metabolites.
A new condition for convergence in continuous-time consensus seeking systems

We consider continuous-time consensus seeking systems whose time-dependent interactions are cut-balanced, in the following sense: if a group of agents influences the remaining ones, the former group is also influenced by the remaining ones by at least a proportional amount. Models involving symmetric interconnections and models in which a weighted average of the agent values is conserved are special cases. We present a result guaranteeing the convergence of every cut-balanced system, and giving a sufficient condition on the evolving interaction topology for the limit values of two agents to be the same. This condition is also necessary up to a zero-measure subset of the initial conditions. Using the fact that our convergence requires no additional condition, we show that it also applies to systems where the agent connectivity and interactions are random, or endogenous, that is, determined by the agent values. We also derive corresponding results for discrete-time systems.
Detecting the correct graph structure in pose graph SLAM

While graph-based representations allow an efficient solution to the SLAM problem posing it as a non-linear least squares optimization, they require additional methods to detect and eliminate outliers. It is necessary to obtain the correct structure of the graph representing the SLAM problem which is topologically correct and will lead to a metric correct solution once optimized. In the graph-SLAM context, the edges represent constraints relating two poses whereas the vertices represent the robot poses. While all the edges between consecutive poses actually exist (odometry), the same may not be true for edges coming from a place recognition system. Place recognition algorithms always have some degree of failure in the presence of perceptual aliasing in real environments, creating edges between otherwise unrelated poses. We argue that rather than mitigating the effect of incorrect loop closures, these edges must be detected and removed as they represent non-existent topological connections in the graph. In this paper we describe a method that is able to detect and remove such false edges, leading to a solution of the SLAM problem based on the resulting topologically correct graph. Our method is robust both to outliers in place recognition as well as errors in odometry systems. We focus our experiments on real world and synthetic datasets and provide comparisons against other robust SLAM methods.
FixerCache: unsupervised caching active developers for diverse bug triage

Context: Bug triage aims to recommend appropriate developers for new bugs in order to reduce time and effort in bug resolution. Most previous approaches for bug triage are supervised. Before recommending developers, these approaches need to learn developers' bug-fix preferences via building and training models using text-information of developers' historical bug reports. Goal: In this paper, we empirically address three limitations of supervised bug triage approaches and propose FixerCache, an unsupervised approach for bug triage by caching developers based on their activeness in components of products. Method: In FixerCache, each component of a product has a dynamic developer cache which contains prioritized developers according to developers' activeness scores. Given a new bug report, FixerCache recommends fixers with high activeness in developer cache to participate in fixing the new bug. Results: Results of experiments on four products from Eclipse and Mozilla show that FixerCache outperforms supervised bug triage approaches in both prediction accuracy and diversity. And it can achieve prediction accuracy up to 96.32% and diversity up to 91.67%, with top-10 recommendation list. Conclusions: FixerCache recommends fixers for new bugs based on developers' activeness in components of products with high prediction accuracy and diversity. Moreover, since FixerCache does not need to learn developers' bug-fix preferences through complex and time consuming processes, it could reduce bug triage time from hours of supervised approaches to seconds.
Visual cues for manual control of headway

The ability to maintain appropriate gaps to objects in one's environment is important when navigating through a three-dimensional world. Previous research has shown that the visual angle subtended by a lead/approaching object and its rate of change are important variables for timing interceptions, collision avoidance, continuous regulation of braking, and manual control of headway. However, investigations of headway maintenance have required participants to maintain a fixed distance headway and have not investigated how information about own-speed is taken into account. In the following experiment, we asked participants to use a joystick to follow computer-simulated lead objects. The results showed that ground texture, following speed, and the size of the lead object had significant effects on both mean following distances and following distance variance. Furthermore, models of the participants' joystick responses provided better fits when it was assumed that the desired visual extent of the lead object would vary over time. Taken together, the results indicate that while information about own-speed is used by controllers to set the desired headway to a lead object, the continuous regulation of headway is influenced primarily by the visual angle of the lead object and its rate of change. The reliance on visual angle, its rate of change, and/or own-speed information also varied depending on the control dynamics of the system. Such findings are consistent with an optimal control criterion that reflects a differential weighting on different sources of information depending on the plant dynamics. As in other judgements of motion in depth, the information used for controlling headway to other objects in the environment varies depending on the constraints of the task and different strategies of control.
Challenging emotivity: the voice

We present a new tool and test procedure – based on the use of the finite state emotional model described by the Plutchick ‘flower’ – designed to measure the ability of the human to recognize the emotion carried by the voice when the italian language is used. Using the no-sense sentences contained in the corpus EMOVO we have been able to that in natural conditions the human ability to recognize the emotional states using only the vocal channel are quite poor (30% in average). The recognition rate depends on many factors, among them the sex and the peculiarities of the speaker, the specific emotion, the specific contest.
An exploration of kaupapa Maori research, its principles, processes and applications

Kaupapa Maori research developed as part of a broader movement by Maori to question westernized notions of knowledge, culture, and research. Kaupapa Maori research has been used as both a form of resistance and a methodological strategy, wherein research is conceived, developed, and carried out by Maori, and the end outcome is to benefit Maori. This piece reviews the development and main principles of kaupapa Maori research, and it also describes and critiques the main processes of kaupapa Maori research. Three exemplars of research carried out by Maori researchers are provided to illustrate these principles and processes. We conclude that kaupapa Maori research is a relevant approach for research involving Maori and that it can enhance the self‐determination of Maori people. Kaupapa Maori research also has implications for research with indigenous people more generally.
Miz1 Is a Critical Repressor of cdkn1a during Skin Tumorigenesis

The transcription factor Miz1 forms repressive DNA-binding complexes with the Myc, Gfi-1 and Bcl-6 oncoproteins. Known target genes of these complexes encode the cyclin-dependent kinase inhibitors (CKIs) cdkn2b (p15Ink4), cdkn1a (p21Cip1), and cdkn1c (p57Kip2). Whether Miz1-mediated repression is important for control of cell proliferation in vivo and for tumor formation is unknown. Here we show that deletion of the Miz1 POZ domain, which is critical for Miz1 function, restrains the development of skin tumors in a model of chemically-induced, Ras-dependent tumorigenesis. While the stem cell compartment appears unaffected, interfollicular keratinocytes lacking functional Miz1 exhibit a reduced proliferation and an accelerated differentiation of the epidermis in response to the tumor promoter 12-O-tetradecanoylphorbol-13-acetate (TPA). Tumorigenesis, proliferation and normal differentiation are restored in animals lacking cdkn1a, but not in those lacking cdkn2b. Our data demonstrate that Miz1-mediated attenuation of cell cycle arrest pathways via repression of cdkn1a has a critical role during tumorigenesis in the skin.
A novel flag-language remote control design for a laparoscopic camera holder using image processing

Minimally invasive surgeries(MIS) possess obvious advantages for patients but require more specially trained personnel than common, open procedure. With modern advances in robotics, it becomes possible to ease these requirements by introducing robotized assistants into operation. However, for robot-assisted solo MIS, it is crucial to have appropriate methods for robot control. This work presents a design of flag language as a novel human-to-robot communication method based on image processing of the endoscope video during real-time intervention. The proposed system comprises autonomous positioning of endoscope holder combined with recognition of surgeon intention by analyzing surgical instrument postures. The proposed algorithm has been evaluated using experimental setup as well as video clips from laparoscopic operation. Experimental results show that the flag posture can be detected satisfactorily with speed of 12 frames per second, as well as system robustness under moderate lighting and noise conditions.
Development of the Deep Cerebellar Nuclei: Transcription Factors and Cell Migration from the Rhombic Lip

The deep cerebellar nuclei (DCN) are the main output centers of the cerebellum, but little is known about their development. Using transcription factors as cell type-specific markers, we found that DCN neurons in mice are produced in the rhombic lip and migrate rostrally in a subpial stream to the nuclear transitory zone (NTZ). The rhombic lip-derived cells express transcription factors Pax6, Tbr2, and Tbr1 sequentially as they enter the NTZ. A subset of rhombic lip-derived cells also express reelin, a key regulator of Purkinje cell migrations. In organotypic slice cultures, the rhombic lip was necessary and sufficient to produce cells that migrate in the subpial stream, enter the NTZ, and express Pax6, Tbr2, Tbr1, and reelin. In later stages of development, the subpial stream is replaced by the external granular layer, and the NTZ organizes into distinct DCN nuclei. Tbr1 expression persists to adulthood in a subset of medial DCN projection neurons. In reeler mutant mice, which have a severe cerebellar malformation, rhombic lip-derived cells migrated to the NTZ, despite reelin deficiency. Studies in Tbr1 mutant mice suggested that Tbr1 plays a role in DCN morphogenesis but is not required for reelin expression, glutamatergic differentiation, or the initial formation of efferent axon pathways. Our findings reveal underlying similarities in the transcriptional programs for glutamatergic neuron production in the DCN and the cerebral cortex, and they support a model of cerebellar neurogenesis in which glutamatergic and GABAergic neurons are produced from separate progenitor compartments.
Data abstraction mechanisms in SINA/ST

This paper describes a new data abstraction mechanism in an object-oriented model of computing. The data abstraction mechanism described here has been devised in the context of the design of Sina/st language. In Sina/st no language constructs have been adopted for specifying inheritance or delegation, but rather, we introduce simpler mechanisms that can support a wide range of code sharing strategies without selecting one among them as a language feature. Sina/st also provides a stronger data encapsulation than most of the existing object-oriented languages. This language has been implemented on the SUN 3 workstation using Smalltalk.