Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Semantic Multimodal Emotion Recognition for Enhancing Assistive Services in Ubiquitous Robotics

In this paper, the problem of endowing ubiquitous robots with cognitive capabilities for recognizing emotions, sentiments, affects and moods of humans, in their context, is studied. A hybrid approach based on multilayer perceptron (MLP) neural network and n-ary ontologies for emotion-aware robotic systems is proposed. In particular, an algorithm based on the hybrid-level fusion, an expressive emotional knowledge representation and reasoning model are introduced to recognize complex and non-observable emotional context of the user. Empirical experiments on real-world dataset corroborate its effectiveness.
Understanding the Role of Visual Mental Imagery in Intelligence: The Retinotopic Reasoning (R2) Cognitive Architecture

This paper presents a new Retinotopic Reasoning (R2) cog- nitive architecture that is inspired by studies of visual mental imagery in people. R2 is a hybrid symbolic-connectionist architecture, with certain components of the system represented in propositional, symbolic form, but with a primary working memory store that contains visual “mental” images that can be created and manipulated by the system. R2 is not intended to serve as a full-ﬂedged, stand-alone cognitive architecture, but rather is a specialized system focusing on how visual mental imagery can be represented, learned, and used in support of intelligent behavior. Examples illustrate how R2 can be used to model human visuospatial cognition on several different standardized cognitive tests, including the Raven’s Progressive Matrices test, the Block Design test, the Embedded Figures test, and the Paper Folding test.
Perceived risk, safety climate and safety behavior on Moroccan construction sites

In Morocco, the construction sector is very dynamic economically, but suffers from weak safety performance. The few available statistics about the rates of occupational injuries and fatalities point to an alarming situation. However, root causes are yet to be identified. To fill this gap in knowledge, we conducted this study using an exploratory approach. Literature review, onsite observations and a survey were conducted to gather information about safety and risk aspects on construction sites. We conducted a series of correlation tests and a regression analysis using IBM SPSS version 20. The results showed that: (a) there is a relatively strong risk perception bias among workers, with an underestimation of risk severity and occurrence probability; (b) risk perception was not found to predict safety behavior; (c) a positive safety climate seems to neutralize the negative impact that high risk tolerance had on safety behavior.
Optimization Task in Equivalent to Word2vec Matrix Factorization

Omer Levy and Yoav Goldberg have shown in their paper at NIPS 2014 that word2vec is equivalent to the factorization of shifted PMI matrix. The question which was not discussed in this work and later papers is the right choice of the norm for an approximation of the matrix. Authors also presented the results of the experiments with SVD approximating the matrix with respect to Frobenius norm. In this work we show that weighted Frobenius norm could be the reasonable choice, but weights shouldn’t be equal to one as in Levy and Goldberg experiments. We conjecture that the right choice of weights could help to improve matrix factorization results on analogy questions, where skipgram with negative sampling (SGNS) remains superior to SVD.
Extensive Macular Atrophy with Pseudodrusen Imaged with OCT Angiography

This report describes the first case of extensive macular atrophy with pseudodrusen (EMAP) imaged with optical coherence tomography angiography (OCTA). A 58-year-old Caucasian man presented with decreased central vision in both eyes. Fundus examination showed large areas of macular atrophy centered on the fovea surrounded by diffuse reticular pseudodrusen. Spectral domain OCT (SDOCT) revealed outer retinal and choriocapillaris atrophy. OCTA demonstrated marked absence of choriocapillaris flow. Extensive macular atrophy with pseudodrusen is a rare clinical entity and a new extreme phenotype of macular degenerations that could shed more light on the role of pseudodrusen and choriocapillaris compromise in the pathogenesis of AMD.
Child Gender Determination with Convolutional Neural Networks on Hand Radio-Graphs

Motivation: In forensic or medico-legal investigation as well as in anthropology the gender determination of the subject (hit by a disastrous or any kind of traumatic situation) is mostly the first step. In state-of-the-art techniques the gender is determined by examining dimensions of the bones of skull and the pelvis area. In worse situations when there is only a small portion of the human remains to be investigated and the subject is a child, we need alternative techniques to determine the gender of the subject. In this work we propose a technique called GDCNN (Gender Determination with Convolutional Neural Networks), where the left hand radio-graphs of the children between a wide range of ages in 1 month to 18 years are examined to determine the gender. To our knowledge this technique is first of its kind. Further to identify the area of the attention we used Class Activation Mapping (CAM). Results: The results suggest the accuracy of the model is as high as 98%, which is very convincing by taking into account the incompletely grown skeleton of the children. The attention observed with CAM discovers that the lower part of the hand around carpals (wrist) is more important for child gender determination.
A Recognition Model of Driving Risk Based on Belief Rule-Base Methodology

This paper aims to recognize driving risks in individual vehicles online based on a data-driven methodology. Existing advanced driver assistance systems (ADAS) have difficulties in effectively processing multi-source heterogeneous driving data. Furthermore, parameters adopted for evaluating the driving risk are limited in these systems. The approach of data-driven modeling is investigated in this study for utilizing the accumulation of on-road driving data. A recognition model of driving risk based on belief rule-base (BRB) methodology is built, predicting driving safety as a function of driver characteristics, vehicle state and road environment conditions. The BRB model was calibrated and validated using on-road data from 30 drivers. The test results show that the recognition accuracy of our proposed model can reach about 90% in all situations with three levels (none, medium, large) of driving risks. Furthermore, the proposed simplified model, which provides real-time operation, is implemented in a vehicle driving simulator as a reference for future ADAS and belongs to research on artificial intelligence (AI) in the automotive field.
Adaptive Kernel-Based Fuzzy C-Means Clustering with Spatial Constraints for Image Segmentation

In order to resolve the disadvantages of fuzzy C-means (FCM) clustering algorithm for image segmentation, an improved Kernel-based fuzzy C-means (KFCM) clustering algorithm is proposed. First, the reason why the kernel function is introduced is researched on the basis of the classical KFCM clustering. Then, using spatial neighborhood constraint property of image pixels, an adaptive weighted coefficient is introduced into KFCM to control the influence of the neighborhood pixels to the central pixel automatically. At last, a judging rule for partition fuzzy clustering numbers is proposed that can decide the best clustering partition numbers and provide an optimization foundation for clustering algorithm. An adaptive kernel-based fuzzy C-means clustering with spatial constraints (AKFCMS) model for image segmentation approach is proposed in order to improve the efficiency of image segmentation. Various experiment results show that the proposed approach can get the spatial information features of an image accurately and is robust to realize image segmentation.
Smart City Planning with Constrained Crowd Judgment Analysis

Collecting opinions from multiple crowd workers has been proved to be very effective to reach into a prompt and robust decision. There are many real-life applications (like smart city planning and urban development) where public (skilled or unskilled) opinions play a better role in comparison with single expert opinion. A spectrum of algorithms has already been proposed for obtaining robust consensus judgment from multiple crowd opinions. In most of the problems, for a particular question we receive a single opinion with multiple options. But in this article, we have proposed a new research problem termed as constrained judgment analysis problem that consists of the questions having multiple opinions. More-over, some constraints among the options are required to be satisﬁed while giving opinions. In this constrained judgment analysis, the traditional way of decision making, like majority voting, weighted voting or probablistic model, cannot be applied directly due to the purpose of constraint satisfaction. In this work, we have also proposed a probabilistic method for obtaining ﬁnal solution for constrained judgment analysis problem and demonstrated its efﬁcacy over a synthetic dataset, thereby proving its utility in resource allocation for smart city planning.
Defining the in vivo characteristics of acute myeloid leukemia cells behavior by intravital imaging

The majority of acute myeloid leukemia (AML) patients have a poor response to conventional chemotherapy. The survival of chemoresistant cells is thought to depend on leukemia‐bone marrow (BM) microenvironment interactions, which are not well understood. The CXCL12/CXCR4 axis has been proposed to support AML growth but was not studied at the single AML cell level. We recently showed that T‐cell acute lymphoblastic leukemia (T‐ALL) cells are highly motile in the BM; however, the characteristics of AML cell migration within the BM remain undefined. Here, we characterize the in vivo migratory behavior of AML cells and their response to chemotherapy and CXCR4 antagonism, using high‐resolution 2‐photon and confocal intravital microscopy of mouse calvarium BM and the well‐established MLL‐AF9‐driven AML mouse model. We used the Notch1‐driven T‐ALL model as a benchmark comparison and AMD3100 for CXCR4 antagonism experiments. We show that AML cells are migratory, and in contrast with T‐ALL, chemoresistant AML cells become less motile. Moreover, and in contrast with T‐ALL, the in vivo exploratory behavior of expanding and chemoresistant AML cells is unaffected by AMD3100. These results expand our understanding of AML cells‐BM microenvironment interactions, highlighting unique traits of leukemia of different lineages.
Political parties and climate policy

This study presents an innovative approach to hand-coding parties’ policy preferences in the relatively new, cross-sectoral field of climate change mitigation policy. It applies this approach to party manifestos in six countries, comparing the preferences of parties in Denmark, France, Germany, Ireland, Italy and the United Kingdom over the past two decades. It probes the data for evidence of validity through content validation and convergent/discriminant validation and engages with the debate on position-taking in environmental policy by developing a positional measure that incorporates ‘pro’ and ‘anti’ climate policy preferences. The analysis provides evidence for the validity of the new measures, shows that they are distinct from comparable measures of environmental policy preferences and argues that they are more comprehensive than existing climate policy measures. The new measures strengthen the basis for answering questions that are central to climate politics and to party politics. The approach developed here has important implications for the study of new, complex or cross-cutting policy issues and issues that include both valence and positional aspects.
Multichannel Image Segmentation Algorithm for Agricultural Crop Detection

In this article we propose an algorithm for multichannel image segmentation within the predeﬁned region of interest. The algorithm allows to determine whether the region of interest is homogeneous or not and it also produces a partition of the region of interest into homogeneous subsets and reﬁnes objects borders. The proposed method has been applied to remote sensing images of agricultural ﬁelds as a prelim-inary step of crop detection mechanism. Segmentation quality has been estimated by means of a speciﬁc measure proposed in this article.
Contextual Knowledge for Language-Endowed Intelligent Agents

That context plays an important – possibly, crucial – role in language processing is a truism. But what counts as context is different for different people. Automatic language understanding and generation has not yet attained the levels of quality habitually demonstrated by people. It is therefore not surprising that the notion of context has been gradually extended to include previously untapped phenomena, knowledge and data in efforts to improve system perfor- mance. This paper briefly discusses textual, knowledge, situational and interpersonal facets of a comprehensive view of context when characterizing the processes of understand- ing and generating natural language texts by artificial intelligent agents.
Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence

Abstract Molecular phylogenetics is often used to estimate the time since the divergence of modern gene sequences. For highly diverged sequences, such phylogenetic techniques sometimes estimate surprisingly recent divergence times. In the case of viruses, independent evidence indicates that the estimates of deep divergence times from molecular phylogenetics are sometimes too recent. This discrepancy is caused in part by inadequate models of purifying selection leading to branch-length underestimation. Here we examine the effect on branch-length estimation of using models that incorporate experimental measurements of purifying selection. We find that models informed by experimentally measured site-specific amino-acid preferences estimate longer deep branches on phylogenies of influenza virus hemagglutinin. This lengthening of branches is due to more realistic stationary states of the models, and is mostly independent of the branch-length extension from modeling site-to-site variation in amino-acid substitution rate. The branch-length extension from experimentally informed site-specific models is similar to that achieved by other approaches that allow the stationary state to vary across sites. However, the improvements from all of these site-specific but time homogeneous and site independent models are limited by the fact that a protein’s amino-acid preferences gradually shift as it evolves. Overall, our work underscores the importance of modeling site-specific amino-acid preferences when estimating deep divergence times—but also shows the inherent limitations of approaches that fail to account for how these preferences shift over time.
The fallacy of the Pcrit – are there more useful alternatives?

ABSTRACT Pcrit – generally defined as the PO2 below which the animal can no longer maintain a stable rate of O2 consumption (ṀO2), such that ṀO2 becomes dependent upon PO2 – provides a single number into which a vast amount of experimental effort has been invested. Here, with specific reference to water-breathers, I argue that this focus on the Pcrit is not useful for six reasons: (1) calculation of Pcrit usually involves selective data editing; (2) the value of Pcrit depends greatly on the way it is determined; (3) there is no good theoretical justification for the concept; (4) Pcrit is not the transition point from aerobic to anaerobic metabolism, and it disguises what is really going on; (5) Pcrit is not a reliable index of hypoxia tolerance; and (6) Pcrit carries minimal information content. Preferable alternatives are loss of equilibrium (LOE) tests for hypoxia tolerance, and experimental description of full ṀO2 versus PO2 profiles accompanied by measurements of ventilation, lactate appearance and metabolic rate by calorimetry. If the goal is to assess the ability of the animal to regulate ṀO2 from this profile in a mathematical fashion, promising, more informative alternatives to Pcrit are the regulation index and Michaelis–Menten or sigmoidal allosteric analyses. Summary: This Commentary argues that the concept of the critical oxygen tension in water-breathers is fundamentally flawed for many reasons, and it presents the case for more useful alternatives.
Comparing the inculcation of the value of rationalism from the Australia and Malaysia mathematics textbooks

This research seeks to compare the inculcation of the value of rationalism through the form four mathematics textbooks from Victoria (Australia) and Malaysia. One textbook is analyzed from each of the countries. Two chapters were chosen from both of the textbooks, namely Linear Equations and Trigonometry. Contents analysis was used to analyse evidence of the value of rationalism. Five characteristics of the value of rationalism are identified namely reason, explanation, abstraction, logical thinking and theorem. We found inculcation of the value of rationalism was moderate. However, the value of rationalism with characteristics of hypothetical reasoning was missing from both of the textbooks. Both textbooks inculcate the value of rationalism with characteristics of reasons fairly moderately. The inculcation of the value of rationalism with the characteristic of explanation appeared significantly in both textbooks. In contrast, the inculcation of the value of rationalism with characteristics of abstraction and theorem appeared only in the Mathematics Form 4 of the Malaysian textbook. This study highlights the need to inculcate the value of rationalism more thoroughly, especially the value of rationalism with characteristics of reason, hypothetical reasoning and logical thinking. The inclusion of the value of rationalism in the mathematics textbooks will enable students to understand mathematical concepts more deeply and meaningfully.
Highlighting the Potency of Biosurfactants Produced by Pseudomonas Strains as Anti-Legionella Agents

Legionella pneumophila, the causative agent of Legionnaires' disease, is a waterborne bacterium mainly found in man-made water systems in close association with free-living amoebae and multispecies biofilms. Pseudomonas strains, originating from various environments including freshwater systems or isolated from hospitalized patients, were tested for their antagonistic activity towards L. pneumophila. A high amount of tested strains was thus found to be active. This antibacterial activity was correlated to the presence of tensioactive agents in culture supernatants. As Pseudomonas strains were known to produce biosurfactants, these compounds were specifically extracted and purified from active strains and further characterized using reverse-phase HPLC and mass spectrometry methods. Finally, all biosurfactants tested (lipopeptides and rhamnolipids) were found active and this activity was shown to be higher towards Legionella strains compared to various other bacteria. Therefore, described biosurfactants are potent anti-Legionella agents that could be used in the water treatment industry although tests are needed to evaluate how effective they would be under field conditions.
Comparison of Comorbid Conditions Between Cancer Survivors and Age-Matched Patients Without Cancer

Background Cancer survivors suffer from many comorbid conditions even after the cure of their cancers beyond 5 years. We explored the differences in the association of comorbid conditions between the cancer survivors and patients without cancer. Methods Electronic medical records of 280 adult cancer survivors and 280 age-matched patients without cancer in our suburban internal medicine office were reviewed. Results Mean age of the cancer survivors was 72.5 ± 13.1 years, and the age of the patients without cancer was 72.5 ± 12.8 years. The number of male cancer survivors was significantly higher than the female cancer survivors (52.5% vs. 47.5%, P < 0.001). There were significantly more Caucasians and other races (majority Asians) in the cancer survivor group compared to the patients without cancer group (81.8% vs. 79.3% and 4.6% vs. 0.4%, respectively, P < 0.05); while there were significantly less African Americans and Hispanics in the cancer survivor group compared to the patients without cancer group (10.0% vs. 12.8% and 3.6% vs. 7.5%, respectively, P < 0.05). Hypertension (64.3%), hyperlipidemia (56.1%), osteoarthritis (34.3%), hypothyroidism (21.8%), diabetes mellitus (21.8%) and coronary artery disease (21.8%) were the most common comorbid conditions observed in the cancer survivors. Osteoarthritis was the only comorbid condition that was significantly less frequently associated with the cancer survivors compared to the patients without cancer (42.9%, P < 0.05). The frequencies of all other comorbid conditions were not significantly different between the two groups. The majority of our group of cancer survivors had one or more types of the top six cancers which include prostate cancer (30.7%), melanoma (13.9%), thyroid cancer (11.4%), colon cancer (11.1%), uterine cancer (11.1%) and urinary bladder cancer (11.1%); while only a few had cancer of the cervix (6.1%) or breast cancer (0.3%). Use of aspirin, statin, vitamin D, multivitamins, metformin and fish oil supplement in the cancer survivors was similar to the patients without cancer. Conclusions Hypertension, hyperlipidemia, osteoarthritis, hypothyroidism, diabetes mellitus and coronary artery disease are the most common associated comorbid conditions in the cancer survivors. Osteoarthritis is less frequently seen in the cancer survivors compared to the patients without cancer. The frequencies of other comorbid conditions are not significantly different between the two groups.
PanJoin: A Partition-based Adaptive Stream Join

In stream processing, stream join is one of the critical sources of performance bottlenecks. The sliding-window-based stream join provides a precise result but consumes considerable computational resources. The current solutions lack support for the join predicates on large windows. These algorithms and their hardware accelerators are either limited to equi-join or use a nested loop join to process all the requests. In this paper, we present a new algorithm called PanJoin which has high throughput on large windows and supports both equi-join and non-equi-join. PanJoin implements three new data structures to reduce computations during the probing phase of stream join. We also implement the most hardware-friendly data structure, called BI-Sort, on FPGA. Our evaluation shows that PanJoin outperforms several recently proposed stream join methods by more than 1000x, and it also adapts well to highly skewed data.
Effects of Network Latency on Games with Human and Distributed Agent Players

We are interested in mixed human and agent systems in the context of networked computer games. These games require a fully distributed computer system. State changes must be transmitted by network messages subject to possibly significant latency. The system then is composed of agents' mutually inconsistent views of the world state that cannot be rec-onciled because no single agent’s state is naturally more correct than another’s. The paper discusses the implications of this inconsistency for distributed AI systems. While our example is computer games, we argue the implications affect a much larger class of human/AI problems.