Miracle-dz/UniFAR-FTUs huggingface dataset:
Conceptualising humiliation

ABSTRACT Humiliation lacks an empirically derived definition, sometimes simply being equated with shame. We approached the conceptualisation of humiliation from a prototype perspective, identifying 61 features of humiliation, some of which are more central to humiliation (e.g. losing self-esteem) than others (e.g. shyness). Prototypical humiliation involved feeling powerless, small, and inferior in a situation in which one was brought down and in which an audience was present, leading the person to appraise the situation as unfair and resulting in a mix of emotions, most notably disappointment, anger, and shame. Some of the features overlapped with those of shame (e.g. looking like a fool, losing self-esteem, presence of an audience) whereas other features overlapped with those of anger (e.g. being brought down, unfairness). Which specific features are present may determine whether the humiliation experience becomes more shame- or anger-like (or a combination thereof).
Task-switching deficits and repetitive behaviour in genetic neurodevelopmental disorders: Data from children with Prader–Willi syndrome chromosome 15 q11–q13 deletion and boys with Fragile X syndrome

Prader–Willi syndrome (PWS) and Fragile X syndrome (FraX) are associated with distinctive cognitive and behavioural profiles. We examined whether repetitive behaviours in the two syndromes were associated with deficits in specific executive functions. PWS, FraX, and typically developing (TD) children were assessed for executive functioning using the Test of Everyday Attention for Children and an adapted Simon spatial interference task. Relative to the TD children, children with PWS and FraX showed greater costs of attention switching on the Simon task, but after controlling for intellectual ability, these switching deficits were only significant in the PWS group. Children with PWS and FraX also showed significantly increased preference for routine and differing profiles of other specific types of repetitive behaviours. A measure of switch cost from the Simon task was positively correlated to scores on preference for routine questionnaire items and was strongly associated with scores on other items relating to a preference for predictability. It is proposed that a deficit in attention switching is a component of the endophenotypes of both PWS and FraX and is associated with specific behaviours. This proposal is discussed in the context of neurocognitive pathways between genes and behaviour.
Depressive mood, bonding failure, and abusive parenting among mothers with three-month-old babies in a Japanese community

Objective: To investigate the relationships between depressive mood, bonding failure, and abusive parenting. Method: We distributed questionnaires to 1198 mothers attending a three-month postnatal health check-up in rural areas in Japan. The questionnaires assessed these three variables along with demographics. We evaluated the causal relationships by comparing different structural equation models to the data. Results: Although all the models fit the data well, the best Akaike Information Criterion was obtained from a model where both depressive mood and bonding failure predict abusive parenting, but depressive mood and bonding failure do not predict each other directly. The determinant coefficient of child abuse in the final model was 0.13. Discussion: We found depressive mood and bonding failure during postpartum period impacted negatively on mother’s parenting behaviour. Because only 13% of the variance of abusive parenting was explainable by this model, further study should be needed to identify other risk factors of child abuse. Similarly, midwives and public health nurse in community should pay attention to not only depression but also bonding failure to prevent child abuse.
Hues of a dragon's belly: morphological correlates of ventral coloration in water dragons

Sexual dichromatism is common in lizards, and may play an important role in sex recognition and mating systems. Nonetheless, relatively few published papers provide quantitative analyses of colour, deal with Australian taxa or are based on large-bodied species. Water dragons Physignathus lesueurii (Agamidae) from eastern Australia are very large (upto 1 m total length) and sexually dichromatic, with conspicuous red ventral coloration in adult males. We quantified coloration in three ventral regions (throat, chest and abdomen) of males and females using a spectroradiometer and looked for associations of colour with sex and with morphological traits predicted to correlate with fitness (body size, body condition, relative head size and asymmetry of femoral pores). Among adult males, larger individuals showed less red on the abdomen than did smaller animals, and males with relatively large heads had darker, less red abdomens than did males with smaller heads. Among adult females, larger animals had darker chests, and less red on the abdomen and chest, than did smaller females. The similarity in these trends between the sexes, and the location of the sexually dichromatic and size-sensitive colours in an area (under the abdomen) where they presumably are not visible to other lizards cast doubt on their utility as sexual or dominance signals. Hence, although we documented significant sex and body-size effects on ventral coloration, our results suggest that ventral colours in water dragons do not function in sex-specific displays.
Short‐term synaptic plasticity, simulation of nerve terminal dynamics, and the effects of protein kinase C activation in rat hippocampus

Phorbol esters are hypothesised to produce a protein kinase C (PKC)‐dependent increase in the probability of transmitter release via two mechanisms: facilitation of vesicle fusion or increases in synaptic vesicle number and replenishment. We used a combination of electrophysiology and computer simulation to distinguish these possibilities. We constructed a stochastic model of the presynaptic contacts between a pair of hippocampal pyramidal cells that used biologically realistic processes and was constrained by electrophysiological data. The model reproduced faithfully several forms of short‐term synaptic plasticity, including short‐term synaptic depression (STD), and allowed us to manipulate several experimentally inaccessible processes. Simulation of an increase in the size of the readily releasable vesicle pool and the time of vesicle replenishment decreased STD, whereas simulation of a facilitation of vesicle fusion downstream of Ca2+ influx enhanced STD. Because activation of protein kinase C with phorbol ester enhanced STD of EPSCs in rat hippocampal slice cultures, we conclude that an increase in the sensitivity of the release process for Ca2+ underlies the potentiation of neurotransmitter release by PKC.
Cocultivation of Mesenchymal Stem Cells and Endothelial Progenitor Cells Reveals Antiapoptotic and Proangiogenic Effects

Integrating bioartificial tissues into the host vasculature is a prerequisite for tissue engineering applications. Endothelial progenitor cells (EPCs) display a high angiogenic potential and a low donor-site morbidity, making them ideal for tissue engineering applications. In our study we used a murine EPC cell line (T17b) and rat mesenchymal stem cells (MSCs) for cocultivation experiments. MSCs were cocultured with increasing T17b EPC amounts. Furthermore, MSCs in monoculture were treated with conditioned medium (CM) from T17b EPCs and T17b EPCs were treated with CM from MSCs. Proliferation and apoptosis were quantified with a bromodeoxyuridine ELISA and a DNA fragmentation ELISA, respectively. Osteogenic differentiation was detected with an alkaline phosphatase assay and bone morphogenetic protein-2 ELISA. The production of proangiogenic molecules was measured with a matrix metalloproteinase-3 and vascular endothelial growth factor ELISA as well as nitric oxide assay. We could show that T17b EPCs stimulated MSC proliferation but not vice versa. On the other hand, MSCs promoted the cell survival of EPCs. The growth-inducing and antiapoptotic effects were dependent on heterotypic cell contacts and paracrine mediators. Moreover, proangiogenic growth factors were found in the coculture. Collectively, our results indicate that the coapplication of MSCs and T17b EPCs provides new perspectives for tissue engineering applications.
Improving Entity Linking by Modeling Latent Relations between Mentions

Entity linking involves aligning textual mentions of named entities to their corresponding entries in a knowledge base. Entity linking systems often exploit relations between textual mentions in a document (e.g., coreference) to decide if the linking decisions are compatible. Unlike previous approaches, which relied on supervised systems or heuristics to predict these relations, we treat relations as latent variables in our neural entity-linking model. We induce the relations without any supervision while optimizing the entity-linking system in an end-to-end fashion. Our multi-relational model achieves the best reported scores on the standard benchmark (AIDA-CoNLL) and substantially outperforms its relation-agnostic version. Its training also converges much faster, suggesting that the injected structural bias helps to explain regularities in the training data.
Protective role of ceftriaxone plus sulbactam with VRP1034 on oxidative stress, hematological and enzymatic parameters in cadmium toxicity induced rat model

ABSTRACT We investigated the protective role of ceftriaxone plus sulbactam with VRP1034 (Elores) on hematological, lipid peroxidation, antioxidant enzymatic activities and Cd levels in the blood and tissues of cadmium exposed rats. Twenty-four male rats were divided into three groups of eight rats each. The control group received distilled water whereas group II received CdCl2 (1.5 mg/4 ml/body weight) through gastric gavage for 21 days. Group III received CdCl2 and was treated with ceftriaxone plus sulbactam with VRP1034 for 21 days. The hematological, biochemical, lipid per-oxidation levels and enzymatic parameters were measured in plasma and tissues (brain, liver and kidney) of all groups. The Cd, Zn and Fe levels were measured in blood and tissues of all groups. Our findings showed significantly decreased cadmium (p<0.001), malonaldialdehyde (p<0.001) and myloperoxidase (MPO) levels along with significantly increased hemoglobin (p<0.01), RBC (p<0.05), hematocrit (p<0.05) levels and all antioxidant enzymatic activities (SOD, CAT, GR, GPx) in plasma and tissues of ceftriaxone plus sulbactam with VRP1034 treated group as compared to cadmium exposed group. Delta aminolevulinate dehydratase (δ-ALAD) activity was significantly (p<0.001) increased in the blood of ceftriaxone plus sulbactam with VRP1034 treated group as compared with cadmium exposed group. The levels of hepatic and renal parameters were significantly (p<0.001) decreased in ceftriaxone plus sulbactam with VRP1034 treated group as compared to cadmium exposed group. These findings indicate that ceftriaxone plus sulbactam with VRP1034 acts as a potent free radical scavenger and exhibits metal chelating properties that reduce free radical mediated tissue injury and prevent dysfunction of hepatic and renal organs during metal intoxication.
Securing Distributed Machine Learning in High Dimensions

We consider securing a distributed machine learning system wherein the data is kept confidential by its providers who are recruited as workers to help the learner to train a $d$--dimensional model. In each communication round, up to $q$ out of the $m$ workers suffer Byzantine faults; faulty workers are assumed to have complete knowledge of the system and can collude to behave arbitrarily adversarially against the learner. We assume that each worker keeps a local sample of size $n$. (Thus, the total number of data points is $N=nm$.) Of particular interest is the high-dimensional regime $d \gg n$. We propose a secured variant of the classical gradient descent method which can tolerate up to a constant fraction of Byzantine workers. We show that the estimation error of the iterates converges to an estimation error $O(\sqrt{q/N} + \sqrt{d/N})$ in $O(\log N)$ rounds. The core of our method is a robust gradient aggregator based on the iterative filtering algorithm proposed by Steinhardt et al. \cite{Steinhardt18} for robust mean estimation. We establish a uniform concentration of the sample covariance matrix of gradients, and show that the aggregated gradient, as a function of model parameter, converges uniformly to the true gradient function. As a by-product, we develop a new concentration inequality for sample covariance matrices of sub-exponential distributions, which might be of independent interest.
Roughness-dependent tribology effects on discontinuous shear thickening

Significance Shear thickening is a ubiquitous rheological phenomenon whereby dense suspensions of particles in a fluid exhibit a viscosity increase at high shear, which can turn into a viscosity divergence [discontinuous shear thickening (DST)]. Although macroscopically well characterized, the microscopic origin of DST is still debated, especially in connection to particle surface properties, e.g., roughness and friction. We elucidate here the mechanisms underpinning DST by carrying out nanotribological measurements of the interparticle contacts of model rough colloids. We demonstrate that rough particles exhibit DST over a broader range of shear rates and for volume fractions much lower than for smooth colloids, due to interlocking of surface asperities, showing that taking an engineering-tribology approach is a powerful way to tune DST. Surface roughness affects many properties of colloids, from depletion and capillary interactions to their dispersibility and use as emulsion stabilizers. It also impacts particle–particle frictional contacts, which have recently emerged as being responsible for the discontinuous shear thickening (DST) of dense suspensions. Tribological properties of these contacts have been rarely experimentally accessed, especially for nonspherical particles. Here, we systematically tackle the effect of nanoscale surface roughness by producing a library of all-silica, raspberry-like colloids and linking their rheology to their tribology. Rougher surfaces lead to a significant anticipation of DST onset, in terms of both shear rate and solid loading. Strikingly, they also eliminate continuous thickening. DST is here due to the interlocking of asperities, which we have identified as “stick–slip” frictional contacts by measuring the sliding of the same particles via lateral force microscopy (LFM). Direct measurements of particle–particle friction therefore highlight the value of an engineering-tribology approach to tuning the thickening of suspensions.
Selective inhibition of BCL-2 is a promising target in patients with high-risk myelodysplastic syndromes and adverse mutational profile

Somatic mutations in genes such as ASXL1, RUNX1, TP53 or EZH2 adversely affect the outcome of patients with myelodysplastic syndromes (MDS). Since selective BCL-2 inhibition is a promising treatment strategy in hematologic malignancies, we tested the therapeutic impact of ABT-199 on MDS patient samples bearing an adverse mutational profile. By gene expression, we found that the level of pro-apoptotic BIM significantly decreased during MDS disease progression in line with an acquired resistance to cell death. Supporting the potential for ABT-199 treatment in MDS, high-risk MDS patient samples specifically underwent cell death in response to ABT-199 even when harbouring mutations in ASXL1, RUNX1, TP53 or EZH2. ABT-199 effectively targeted the stem- and progenitor compartment in advanced MDS harbouring mutations in ASXL1, RUNX1, TP53 or EZH2 and even proved effective in patients harbouring more than one of the defined high-risk mutations. Moreover, we utilized the protein abundance of BCL-2 family members in primary patient samples using flow cytometry as a biomarker to predict ABT-199 treatment response. Our data demonstrate that ABT-199 effectively induces apoptosis in progenitors of high-risk MDS/sAML despite the presence of adverse genetic mutations supporting the notion that pro-apoptotic intervention will hold broad therapeutic potential in high-risk MDS patients with poor prognosis.
Tiramisu: A Code Optimization Framework for High Performance Systems

This paper introduces Tiramisu, an optimization framework designed to generate efficient code for high-performance systems such as multicores, GPUs, FPGAs, distributed machines, or any combination of these. Tiramisu relies on a flexible representation based on the polyhedral model and introduces a novel four-level IR that allows full separation between algorithms, schedules, data-layouts and communication. This separation simplifies targeting multiple hardware architectures from the same algorithm. We evaluate Tiramisu by writing a set of linear algebra and DNN kernels and by integrating it as a pass in the Halide compiler. We show that Tiramisu extends Halide with many new capabilities, and that Tiramisu can generate efficient code for multicores, GPUs, FPGAs and distributed heterogeneous systems. The performance of code generated by the Tiramisu backends matches or exceeds hand-optimized reference implementations. For example, the multicore backend matches the highly optimized Intel MKL library on many kernels and shows speedups reaching 4x over the original Halide.
Therapeutic coma for status epilepticus

Objective: Our aim was to analyze and compare the use of therapeutic coma (TC) for refractory status epilepticus (SE) across different centers and its effect on outcome. Methods: Clinical data for all consecutive adults (>16 years) with SE of all etiologies (except postanoxic) admitted to 4 tertiary care centers belonging to Harvard Affiliated Hospitals (HAH) and the Centre Hospitalier Universitaire Vaudois (CHUV) were prospectively collected and analyzed for TC details, mortality, and duration of hospitalization. Results: Two hundred thirty-six SE episodes in the CHUV and 126 in the HAH were identified. Both groups were homogeneous in demographics, comorbidities, SE characteristics, and Status Epilepticus Severity Score (STESS); TC was used in 25.4% of cases in HAH vs 9.75% in CHUV. After adjustment, TC use was associated with younger age, lower Charlson Comorbidity Index, increasing SE severity, refractory SE, and center (odds ratio 11.3 for HAH vs CHUV, 95% confidence interval 2.47–51.7). Mortality was associated with increasing Charlson Comorbidity Index and STESS, etiology, and refractory SE. Length of stay correlated with STESS, etiology, refractory SE, and use of TC (incidence rate ratio 1.6, 95% confidence interval 1.22–2.11). Conclusions: Use of TC for SE treatment seems markedly different between centers from the United States and Europe, and did not affect mortality considering the whole cohort. However, TC may increase length of hospital stay and related costs. Classification of evidence: This study provides Class III evidence that for patients with SE, TC does not significantly affect mortality. The study lacked the precision to exclude an important effect of TC on mortality.
Analysis for locomotive wheels' degradation

This paper undertakes a reliability study using both classical and Bayesian semi-parametric frameworks to explore the impact of a locomotive wheel's position on its service lifetime and to predict its other reliability characteristics. The goal is to illustrate how degradation data can be modeled and analyzed by using classical and Bayesian approaches. The adopted data in the case study have been collected from the Swedish company. The results show that: 1) an exponential degradation path is a better choice for the studied locomotive wheels; 2) both classical and Bayesian semi-parametric approaches are useful tools to analysis degradation data; 3) under given operation conditions, the position of the locomotive wheel could influence its reliability.
Crossbar-Net: A Novel Convolutional Neural Network for Kidney Tumor Segmentation in CT Images

Due to the unpredictable location, fuzzy texture, and diverse shape, accurate segmentation of the kidney tumor in CT images is an important yet challenging task. To this end, we, in this paper, present a cascaded trainable segmentation model termed as Crossbar-Net. Our method combines two novel schemes: 1) we originally proposed the crossbar patches, which consists of two orthogonal non-squared patches (i.e., the vertical patch and horizontal patch). The crossbar patches are able to capture both the global and local appearance information of the kidney tumors from both the vertical and horizontal directions simultaneously. 2) With the obtained crossbar patches, we iteratively train two sub-models (i.e., horizontal sub-model and vertical sub-model) in a cascaded training manner. During the training, the trained sub-models are encouraged to become more focused on the difficult parts of the tumor automatically (i.e., mis-segmented regions). Specifically, the vertical (horizontal) sub-model is required to help segment the mis-segmented regions for the horizontal (vertical) sub-model. Thus, the two sub-models could complement each other to achieve the self-improvement until convergence. In the experiment, we evaluate our method on a real CT kidney tumor dataset which is collected from 94 different patients including 3500 CT slices. Compared with state-of-the-art segmentation methods, the results demonstrate the superior performance of our method on the Dice similarity coefficient, true positive fraction, centroid distance, and Hausdorff distance. Moreover, to exploit the generalization to other segmentation tasks, we also extend our Crossbar-Net to two related segmentation tasks: 1) cardiac segmentation in MR images and 2) breast mass segmentation in X-ray images, showing the promising results for these two tasks. Our implementation is released at https://github.com/Qianyu1226/Crossbar-Net.
Decoupling Dynamics and Reward for Transfer Learning

Current reinforcement learning (RL) methods can successfully learn single tasks but often generalize poorly to modest perturbations in task domain or training procedure. In this work, we present a decoupled learning strategy for RL that creates a shared representation space where knowledge can be robustly transferred. We separate learning the task representation, the forward dynamics, the inverse dynamics and the reward function of the domain, and show that this decoupling improves performance within the task, transfers well to changes in dynamics and reward, and can be effectively used for online planning. Empirical results show good performance in both continuous and discrete RL domains.
A novel taxonomy for gestural interaction techniques: considerations for automotive environments

A large variety of gestural interaction techniques is now available. In this article, we use a new taxonomic space [18] as a comparative structure to analyze the applicability of these techniques on automotive environment. The taxonomy plots a gestural interaction technique as a point in a space where the vertical axis denotes the semantic coverage of the technique, and the horizontal axis expresses the physical actions users are engaged in. In addition, syntactic modifiers are used to express the interpretation process of input tokens into semantics, as well as pragmatic modifiers to make explicit the level of indirections between users actions and system responses. In the taxonomy, the complexity of the gestural interaction lexicon, and the syntactic/pragmatic modifiers it is decorated with, are indexes of the cognitive load users are engaged in during the interaction. The integration of modern mobile devices, complex user interfaces and gestural interaction techniques into automotive environment rise the necessity to analyze gestural interaction technique from their cognitive load point of view.