Miracle-dz/UniFAR-FTUs huggingface dataset:
Concordance of c‐kit Mutational Status in Matched Primary and Metastatic Cutaneous Canine Mast Cell Tumors at Baseline

Background Mutation analysis of proto‐oncogene c‐kit (c‐kit) is advisable before starting treatment with tyrosine kinase inhibitors in dogs with mast cell tumor (MCT), including those with metastatic disease. Testing is usually performed on primary tumors, assuming that c‐kit mutation status does not change in metastasis. Hypothesis/Objectives To give an insight into the mutational processes and to make a recommendation on the use of c‐kit mutational analysis in the clinical setting. Animals Twenty‐one client‐owned dogs with metastatic MCT. Methods Dogs undergoing resection or biopsy for both primary and matched metastatic MCT were prospectively enrolled. Total RNA or DNA was extracted from primary MCT and corresponding metastases. Exons 8, 9, and 11 were amplified by PCR and sequenced. Genetic features between primary MCT and metastases were compared. Their correlation with clinicopathologic features was investigated. Results Concordance (mutated or wild‐type) of mutational status, evaluable in 21 primary and matched metastatic (20 nodal and 1 splenic) MCTs, was 100%. Three new c‐kit mutations were identified. No significant correlation was detected between c‐kit mutation and clinicopathologic features. Conclusions and Clinical Importance Proto‐oncogene c‐kit mutational status is conserved between any primary and its matched secondary tumor, suggesting that both can be used for c‐kit mutational testing. Targeted therapies might be also used to treat metastatic disease.
Monaural Speech Enhancement Using Joint Dictionary Learning with Cross-Coherence Penalties

In the real world, the interferers are often nonstationary and potentially similar to the speech where the conventional speech enhancement (SE) approaches are often incompetent. In the recently proposed sparsity-based approaches, the clean speech is often recovered from the degraded speech by sparse coding of the mixture over the composite dictionary consisting of the speech and interferer dictionaries. However, parts of the speech component are explained by interferer dictionary atoms and vice-versa, which cause source confusion. The existing approaches learn the speech and interferer dictionaries separately and the source confusion is relatively large. In this paper, we introduce a new joint dictionary learning (JDL) method for SE which learns the speech and interferer dictionaries jointly. In the proposed method, the information of speech, interferer and their mixture and the cross-coherence of dictionaries are taken into account. These two parts constitute the new cost function and an algorithm is presented to solve this JDL optimization problem. The experimental results show that our proposed approach can obtain better performances than other tested approaches, and the advantages are more obvious when the input signal-to-interferer ratios are low.
“Squeezed oranges?”: Xhosa secondary school female teachers in township schools remember their learning about sexuality to reimagine their teaching sexuality education

Several concurrent and complex issues seem to influence the teaching of sexuality education in South African schools. Studies have shown that teachers believe they can teach the subject as they have the content knowledge of sexuality education, but experience discomfort when they actually begin the task. We were therefore interested in understanding their perspectives on their own learning about sexuality within their Xhosa culture. Working with 9 purposively selected female Xhosa teachers from 4 secondary schools in townships in Port Elizabeth, we used participatory visual methodology, located within a critical paradigm, generating data with them through drawing. The data was analysed using thematic analysis. The findings show that the women teachers largely learnt about sexuality through piecing together the ‘puzzle’ of limited information from various quarters; through strict rules and fear; through own mistakes and through shame. This remembering facilitated ideas to rethink and reimagine sexuality education, drawing the value-laden Xhosa cultural teachings about sexuality into contemporary sexuality education. The participatory visual research process enabled a deep and open engagement, and in more than one way the claiming back of power, demonstrating a way to engage today’s Xhosa adolescents on matters of sexualit
Hombres y Políticas de Igualdad de Género: Una Agenda en Construcción

E libro Hombres y políticas de igualdad de género: una agenda en construcción está destinado a ser una obra imprescindible en el diseño de políticas de género en México que busquen incorporar en ellas a los hombres de manera activa y decidida. Consta de once apartados escritos con precisión y claridad, donde se exponen análisis, se afinan acciones ya en marcha y se proponen otras por realizar, además de que se identifican temas específicos para dar un impulso definitivo a una política
Rotation model based quasi-dense matching propagation for uncalibrated fisheye images

One main difference for various quasi-dense matching approaches is the different assumptions about local transformations between corresponding patches of two images. The translation is assumed as local transformation for small baseline based approaches, which can not truly reflect the distortion between fisheye patches, and the affine transformation model is usually used for highly distortion images, e.g., wide baseline images, which found to be not as stable and reliable as expected. In this paper we propose a quasi-dense matching algorithm in which a novel local distortion model named rotation transformation is assumed for fisheye images. Initial local rotation transformation for seed match is obtained by phase correlation technique while the estimate of the local transformation for new candidate matches is conducted based on the current seed match. Experiment results show that our algorithm can provide satisfactory results with characteristics of simplicity, stability and reliability.
Strategic Decision-Making and Social Skills: Integrating Behavioral Economics and Social Cognition Research

Strategic decisions are affected by beliefs about the expectations of others and their possible decisions. Thus, strategic decisions are influenced by the social context and by beliefs about other actors’ levels of sophistication. The present study investigated whether strategic decision-making, as measured by the beauty contest game, is associated with social skills, as measured by the Autism Quotient (AQ). In line with our hypothesis, we found that social skills were positively related to successful strategic decision-making. Furthermore, results showed a curvilinear relationship between steps of reasoning in the beauty contest game and social skills, indicating that very high as well as very low scoring individuals on the social skills subscale of the AQ engaged in high-levels of strategic thinking.
Stabilizing effect of a double-harmonic RF system in the CERN PS

Motivated by the discussions on scenarios for LHC upgrades, beam studies on the stability of flat bunches in a double-harmonic RF system have been conducted in the CERN Proton Synchrotron (PS). Injecting nearly nominal LHC beam intensity per cycle, 18 bunches are accelerated on harmonic h = 21 to 26GeV with the 10MHz RF system. On the flat-top, all bunches are then transformed to flat bunches by adiabatically adding RF voltage at h = 42 from a 20 MHz cavity in anti-phase to the h = 21 system. The voltage ratio V (h42)/V (h21) of about 0.5 was set according to simulations. For the next 140 ms, longitudinal profiles show stable bunches in the double-harmonic RF bucket until extraction. Without the second harmonic component, coupled-bunch oscillations are observed. The flatness of the bunches along the batch is analyzed as a measure of the relative phase error between the RF systems due to beam loading. The results of beam dynamics simulations and their comparison with the measured data are presented.
Dimensional structure of DSM-5 posttraumatic stress symptoms in Spanish trauma victims

Background Confirmatory factor analytic studies have shown that posttraumatic stress disorder (PTSD) symptoms included in the fifth edition of the Diagnostic and Statistical Manual Disorders (DSM-5) may be better explained by two 6-factor models (the Externalizing Behaviours model and the Anhedonia model) and a 7-factor Hybrid model. The latter model comprises the symptom clusters of intrusion, avoidance, negative affect, anhedonia, externalizing behaviours, and anxious and dysphoric arousal. This model has received empirical support mainly in American samples. Of note, there have been a limited number of studies conducted on samples from other countries. Objective This study aimed to examine the underlying dimensionality of DSM-5 PTSD symptoms in a Spanish clinical sample exposed to a range of traumatic events. Method Participants included 165 adults (78.8% females) seeking treatment in trauma services in the Madrid area (Spain). PTSD was assessed using the Global Assessment of Posttraumatic Stress Scale 5, a Spanish self-report instrument assessing posttraumatic symptoms according to the DSM-5 criteria. Confirmatory factor analyses were conducted in Mplus. Results Both the 7-factor Hybrid model and the 6-factor Anhedonia model demonstrated good and equivalent fit to the data. Conclusions The findings of this study replicate and extend previous research by providing support for both the 7-factor Hybrid model and the 6-factor Anhedonia model in a clinical sample of Spanish trauma survivors. Given equivalent fit for these two models and the fewer number of latent factors in the Anhedonia model, it was selected as optimal in a traumatized Spanish sample. Implications and future research directions are discussed. Highlights of the article The 7-factor Hybrid model (which comprises the intrusion, avoidance, negative affect, anhedonia, externalizing behaviours, and anxious and dysphoric arousal symptoms clusters) and the 6-factor Anhedonia model (in which the externalizing behaviour symptoms are part of the dysphoric arousal symptom cluster) provided equivalent fit to the data. The Anhedonia model is the most parsimonious and thus the optimal-fitting model in the current sample. The findings support the distinctiveness between dysphoric arousal, anxious arousal, negative affect, and anhedonia factors. The separation of the externalizing behaviour symptoms from the dysphoric arousal symptoms does not improve the model fit in the current sample.
Joint Coupling and Actuation Design of Underactuated Hands for Unstructured Environments

This paper examines joint coupling in underactuated robotic grippers for unstructured environments where object properties and location may not be well known. A simplified grasper consisting of a pair of two-link planar fingers with compliant revolute joints was simulated as it was actuated after contact with a target object. The joint coupling configuration of the gripper was varied in order to maximize successful grasp range and minimize contact forces for a wide range of target object size and position. The number of actuators was also varied in order to test the performance of the gripper for varying degrees of underactuation. A normal distribution of object position was assumed in order to model sensing uncertainty and weight the results accordingly. There are three main results: distal/proximal joint torque ratios of around 1.0 produced the best results both for cases in which sensory information available for the task was poor as well as when sensing was good; a single actuator for both gripper fingers performs no better than one actuator per finger; and that for good sensing, the gripper should be positioned off-center from the object, resulting in an increased lever arm and lower unbalanced contact forces on the object. A concise survey of underactuated, adaptive robot hands is also presented.
Sequential and Incremental Precoder Design for Joint Transmission Network MIMO Systems With Imperfect Backhaul

In this paper, we propose a sequential and incremental precoder design for downlink joint transmission (JT) network multiple-input-multiple-output (MIMO) systems with imperfect backhaul links. The objective of our design is to minimize the maximum of the substream mean square errors, which dominates the average bit error rate (BER) performance of the system. In the proposed scheme, we first optimize the precoder at the serving base station (BS) and then sequentially optimize the precoders of nonserving BSs in the JT set according to the descending order of their probabilities of participating in the JT. The BS-wise sequential optimization process can improve system performance when some BSs have to temporarily quit the JT operations because of poor instant backhaul conditions. In addition, the precoder of an additional BS is derived in an incremental way, i.e., the sequentially optimized precoders of the previous BSs are fixed, and thus, the additional precoder plays an incremental part in multi-BS JT operations. An iterative algorithm is designed to jointly optimize the substream precoder and substream power allocation for each additional BS in the proposed sequential and incremental optimization scheme. Simulations show that, under the practical backhaul link conditions, our scheme significantly outperforms the autonomous global precoding scheme in terms of BER performance.
Cooperation in Decentralised Networks

This paper describes a new model of cooperation between autonomous participants in decentralised networks. Our approach is based on reciprocation between immediate neighbours, which does not require any centralised infrastructure for accounting or identity management. We describe the conditions that are necessary for reciprocation to occur, and show how reciprocation between immediate neighbours can support multi-hop interactions such as packet forwarding.
Synthesis of Stylized Walking Controllers for Planar Bipeds

We present a new method for generating controllers for physics-based simulations of planar bipedal walking, targeted towards producing autonomous character behaviors for computer animation. A common criticism of physics-based character animation is the lack of personality and style in the final motion. We develop controllers that mimic a desired style as much as possible, while still subject to the laws of physics and to the realities of maintaining balance. The resulting simulated character can interact with and respond to its environment, unlike the original kinematically-specified desired motion. Walking is a very challenging control task because of its dynamically unstable nature. Continuous balance control is required to prevent the character from falling over or reaching poses from which it cannot recover. The complexity of a walking controller is compounded by high dimensional continuous.state and action spaces. Our controller implements a nearest-neighbor control policy with respect to a set of nodes embedded in the state space, and is parameterized by the locations of these nodes and their associated actions. We use greedy search to find an optimized controller given an intuitive objective function. Importantly, several shaping techniques are used to ensure that local minima in the optimization space define good, meaningful solutions. We demonstrate the ability to generate stable walks of various styles, walks for bipeds of varying dimensions, and walks that are robust to unobserved terrain variations.
Chemical Bonding and Schottky Barrier for Metal-Carbon Nanotube Contacts

We investigate both end-contact and side-contact structures between Al, Pd, Sc and carbon nanotube (CNT) in this paper. The different structures show the different chemical bonds and charge transfer at the metal-CNT contact interfaces. A novel method based on dipole effect is proposed to calculate the Schottky barrier height (SBH). Different SBHs for the contacts are due to different electro-negativity of metal atoms as well as the chemical bonds.
Joint Rate and Power Control for Elastic and Inelastic Traffic in Multihop Wireless Networks

The current optimal joint rate and power control algorithms for wireless networks are mainly for elastic traffic which has strictly concave utility functions. In the multiclass service networks such that elastic and inelastic, the inelastic traffic is usually associated with the sigmoidal utilities which are nonconcave functions. Therefore, the corresponding Network Utility Maximization (NUM) problem is nonconvex in both objective and constraints. The current approaches cannot be applied and the problem is difficult to solve for the global optimal solution even with the centralized method. This paper proposes the joint rate and power control algorithm which can be distributively implemented. We approximate the nonconvex NUM to the convex problem which is easily solved by dual decomposition method. After a series of approximations, the algorithm converges the local optimal solution.
Investigating the feasibility of extracting tool demonstrations from in-situ video content

Short video demonstrations are effective resources for helping users to learn tools in feature-rich software. However manually creating demonstrations for the hundreds (or thousands) of individual features in these programs would be impractical. In this paper, we investigate the potential for identifying good tool demonstrations from within screen recordings of users performing real-world tasks. Using an instrumented image-editing application, we collected workflow video content and log data from actual end users. We then developed a heuristic for identifying demonstration clips, and had the quality of a sample set of clips evaluated by both domain experts and end users. This multi-step approach allowed us to characterize the quality of 'naturally occurring' tool demonstrations, and to derive a list of good and bad features of these videos. Finally, we conducted an initial investigation into using machine learning techniques to distinguish between good and bad demonstrations.
Quantifying Anuran Microhabitat Use to Infer the Potential for Parasite Transmission between Invasive Cane Toads and Two Species of Australian Native Frogs

Parasites that are carried by invasive species can infect native taxa, with devastating consequences. In Australia, invading cane toads (Rhinella marina) carry lungworm parasites (Rhabdias pseudosphaerocephala) that (based on previous laboratory studies) can infect native treefrogs (Litoria caerulea and L. splendida). To assess the potential of parasite transmission from the invader to the native species (and from one infected native frog to another), we used surveys and radiotelemetry to quantify anuran microhabitat use, and proximity to other anurans, in two sites in tropical Australia. Unsurprisingly, treefrogs spent much of their time off the ground (especially by day, and in undisturbed forests) but terrestrial activity was common at night (especially in anthropogenically modified habitats). Microhabitat overlap between cane toads and frogs was generally low, except at night in disturbed areas, whereas overlap between the two frog species was high. The situations of highest overlap, and hence with the greatest danger of parasite transmission, involve aggregations of frogs within crevices by day, and use of open ground by all three anuran species at night. Overall, microhabitat divergence between toads and frogs should reduce, but not eliminate, the transmission of lungworms from invasive toads to vulnerable native frogs.
Degenerate Wave and Capacitive Coupling Increase Human MSC Invasion and Proliferation While Reducing Cytotoxicity in an In Vitro Wound Healing Model

Non-unions pose complications in fracture management that can be treated using electrical stimulation (ES). Bone marrow mesenchymal stem cells (BMMSCs) are essential in fracture healing; however, the effect of different clinical ES waveforms on BMMSCs cellular activities remains unknown. We compared the effects of direct current (DC), capacitive coupling (CC), pulsed electromagnetic field (PEMF) and degenerate wave (DW) on cellular activities including cytotoxicity, proliferation, cell-kinetics and apoptosis by stimulating human-BMMSCs 3 hours a day, up to 5 days. In addition, migration and invasion were assessed using fluorescence microscopy and by quantifying gene and protein expression. We found that DW had the greatest proliferative and least apoptotic and cytotoxic effects compared to other waveforms. DC, DW and CC stimulations resulted in a higher number of cells in S phase and G2/M phase as shown by cell cycle analysis. CC and DW caused more cells to invade collagen and showed increased MMP-2 and MT1-MMP expression. DC increased cellular migration in a scratch-wound assay and all ES waveforms enhanced expression of migratory genes with DC having the greatest effect. All ES treated cells showed similar progenitor potential as determined by MSC differentiation assay. All above findings were shown to be statistically significant (p<0.05). We conclude that ES can influence BMMSCs activities, especially DW and CC, which show greater invasion and higher cell proliferation compared to other types of ES. Application of DW or CC to the fracture site may help in the recruitment of BMMSCs to the wound that may enhance rate of bone healing at the fracture site.
Statistical Language Processing Using Hidden Understanding Models

This paper introduces a class of statistical mechanisms, called hidden understanding models, for natural language processing. Much of the framework for hidden understanding models derives from statistical models used in speech recognition, especially the use of hidden Markov models. These techniques are applied to the central problem of determining meaning directly from a sequence of spoken or written words. We present an overall description of the hidden understanding methodology, and discuss some of the critical implementation issues. Finally, we report on experimental results, including results of the December 1993 ARPA evaluation.
Personality Measurement and Design in Human-Robot Interaction: A Systematic and Critical Review

This work aims to summarize research methods for measuring personality in human-robot interaction. A systematic review was performed, resulting in 35 studies that were categorized by whether they assessed human personality, robot personality, or both. It was found that the five-factor model (Big Five) of personality (extraversion, agreeableness, conscientiousness, openness, and neuroticism) was a common theme as it was used to assess personality in 31% of studies, and the extraversion dimension alone was used to assess personality in an additional 26% of studies. The strengths, limitations, and the human factors influences of user expectations of the Big Five as well as the recommendation for its use are discussed.