Miracle-dz/UniFAR-FTUs huggingface dataset:
A Systematic and Generalizable Approach to the Heuristic Evaluation of User Interfaces

ABSTRACT Heuristic evaluation is one of the most actively used techniques for analyzing usability, as it is quick and inexpensive. This technique is based on following a given set of heuristics, which are typically defined as broad rules of thumb. In this paper, we propose a systematic and generalizable approach to this type of evaluation based on using comprehensive taxonomies as a source for the heuristics. This approach contrasts with other typical approaches, such as following (or adapting) Jakob Nielsen’s heuristics or creating ad hoc heuristics (formally or informally). The usefulness of our approach is investigated in two ways. Firstly, we carry out an actual heuristic evaluation of a mobile app in this manner, which we describe in detail. Secondly, we compare our approach and Nielsen’s. Additionally, we identify some limitations in Nielsen’s heuristics and some inconsistencies between them and established usability models, including Nielsen’s own.
Measuring Perceived Usability: The CSUQ, SUS, and UMUX

ABSTRACT The primary purpose of this research was to investigate the relationship between two widely used questionnaires designed to measure perceived usability: the Computer System Usability Questionnaire (CSUQ) and the System Usability Scale (SUS). The correlation between concurrently collected CSUQ and SUS scores was 0.76 (over 50% shared variance). After converting CSUQ scores to a 0–100-point scale (to match the range of the SUS scores), there was a small but statistically significant difference between CSUQ and SUS means. Although this difference (just under 2 scale points out of a possible 100) was statistically significant, it did not appear to be practically significant. Although usability practitioners should be cautious pending additional independent replication, it appears that CSUQ scores, after conversion to a 0–100-point scale, can be interpreted with the Sauro–Lewis curved grading scale. As a secondary research goal, investigation of variations of the Usability Metric for User Experience (UMUX) replicated previous findings that the regression-adjusted version of the UMUX-LITE (UMUX-LITEr) had the closest correspondence with concurrently collected SUS scores. Thus, even though these three standardized questionnaires were independently developed and have different item content and formats, they largely appear to be measuring the same thing, presumably, perceived usability.
Robust impedance control of robot manipulators using differential equations as universal approximator

ABSTRACT This paper presents a robust impedance controller for robot manipulators using function approximation techniques (FATs). Recently, some FAT-based robust impedance control approaches have been presented using Fourier series expansion or Legendre polynomials for uncertainty estimation. However, the dimensions of regressor matrices in these approaches are relatively large. This problem becomes hypersensitive especially for higher degree of freedom robot manipulators. In this paper, a simpler and less computational FAT-based robust controller is presented without considering discontinuous nonlinearities. It is assumed that the lumped uncertainty can be modelled by a linear differential equation with unknown coefficients. Then, using the Stone–Weierstrass theorem, it is verified that these differential equations are universal approximators. The advantage of the proposed controller in comparison with previous related works is reducing the dimensions of regressor matrices. Simulation results on a Puma560 robot manipulator indicate the efficiency of the proposed method.
Engineering Kluyveromyces marxianus as a Robust Synthetic Biology Platform Host

The yeast Kluyveromyces marxianus grows at high temperatures and on a wide range of carbon sources, making it a promising host for industrial biotechnology to produce renewable chemicals from plant biomass feedstocks. However, major genetic engineering limitations have kept this yeast from replacing the commonly used yeast Saccharomyces cerevisiae in industrial applications. Here, we describe genetic tools for genome editing and breeding K. marxianus strains, which we use to create a new thermotolerant strain with promising fatty acid production. These results open the door to using K. marxianus as a versatile synthetic biology platform organism for industrial applications. ABSTRACT Throughout history, the yeast Saccharomyces cerevisiae has played a central role in human society due to its use in food production and more recently as a major industrial and model microorganism, because of the many genetic and genomic tools available to probe its biology. However, S. cerevisiae has proven difficult to engineer to expand the carbon sources it can utilize, the products it can make, and the harsh conditions it can tolerate in industrial applications. Other yeasts that could solve many of these problems remain difficult to manipulate genetically. Here, we engineered the thermotolerant yeast Kluyveromyces marxianus to create a new synthetic biology platform. Using CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats with Cas9)-mediated genome editing, we show that wild isolates of K. marxianus can be made heterothallic for sexual crossing. By breeding two of these mating-type engineered K. marxianus strains, we combined three complex traits—thermotolerance, lipid production, and facile transformation with exogenous DNA—into a single host. The ability to cross K. marxianus strains with relative ease, together with CRISPR-Cas9 genome editing, should enable engineering of K. marxianus isolates with promising lipid production at temperatures far exceeding those of other fungi under development for industrial applications. These results establish K. marxianus as a synthetic biology platform comparable to S. cerevisiae, with naturally more robust traits that hold potential for the industrial production of renewable chemicals. IMPORTANCE The yeast Kluyveromyces marxianus grows at high temperatures and on a wide range of carbon sources, making it a promising host for industrial biotechnology to produce renewable chemicals from plant biomass feedstocks. However, major genetic engineering limitations have kept this yeast from replacing the commonly used yeast Saccharomyces cerevisiae in industrial applications. Here, we describe genetic tools for genome editing and breeding K. marxianus strains, which we use to create a new thermotolerant strain with promising fatty acid production. These results open the door to using K. marxianus as a versatile synthetic biology platform organism for industrial applications.
Does the age at adiposity rebound reflect a critical period?

M. F. Rolland-Cachera and T. J. Cole Paris 13 University, Nutritional Epidemiology Research Team, French National Institute of Health and Medical Research (Inserm) U1153, French National Institute for Agricultural Research (Inra) U1125, French National Conservatory of Arts and Crafts (CNAM), Sorbonne Paris Cité University, Bobigny, France; UCL Great Ormond Street Institute of Child Health, London, UK
A New Approach for Loading Anticancer Drugs Into Mesenchymal Stem Cell-Derived Exosome Mimetics for Cancer Therapy

Exosomes derived from mesenchymal stem cells (MSCs) have been evaluated for their potential to be used as drug delivery vehicles. Synthetically personalized exosome mimetics (EMs) could be the alternative vesicles for drug delivery. In this study, we aimed to isolate EMs from human MSCs. Cells were mixed with paclitaxel (PTX) and PTX-loaded EMs (PTX-MSC-EMs) were isolated and evaluated for their anticancer effects against breast cancer. EMs were isolated from human bone marrow-derived MSCs. MSCs (4 × 106 cells/mL) were mixed with or without PTX at different concentrations in phosphate-buffered saline (PBS) and serially extruded through 10-, 5-, and 1-μm polycarbonate membrane filters using a mini-extruder. MSCs were centrifuged to remove debris and the supernatant was filtered through a 0.22-μm filter, followed by ultracentrifugation to isolate EMs and drug-loaded EMs. EMs without encapsulated drug (MSC-EMs) and those with encapsulated PTX (PTX-MSC-EMs) were characterized by western blotting, nanoparticle tracking analysis (NTA), and transmission electron microscopy (TEM). The anticancer effects of MSC-EMs and PTX-MSC-EMs were assessed with breast cancer (MDA-MB-231) cells both in vitro and in vivo using optical imaging. EMs were isolated by the extrusion method and ultracentrifugation. The isolated vesicles were positive for membrane markers (ALIX and CD63) and negative for golgi (GM130) and endoplasmic (calnexin) marker proteins. NTA revealed the size of MSC-EM to be around 149 nm, while TEM confirmed its morphology. PTX-MSC-EMs significantly (p < 0.05) decreased the viability of MDA-MB-231 cells in vitro at increasing concentrations of EM. The in vivo tumor growth was significantly inhibited by PTX-MSC-EMs as compared to control and/or MSC-EMs. Thus, MSC-EMs were successfully isolated using simple procedures and drug-loaded MSC-EMs were shown to be therapeutically efficient for the treatment of breast cancer both in vitro and in vivo. MSC-EMs may be used as drug delivery vehicles for breast cancers.
Contrasting dynamics and trait controls in first-order root compared with leaf litter decomposition

Significance Decomposition of plant roots and associated fungal mutualists is a dominant process in ecosystem carbon cycles, yet is woefully understudied compared with decomposition of leaf litter, particularly for the finest order roots that have the highest turnover. In a field experiment, we compared decomposition of the finest, most distal roots and leaf litter among 35 cooccurring temperate forest species over 6 years. We found that decomposition rates of root tips were considerably lower than those of leaf litter and were controlled by nonlignin carbon compounds in contrast to lignin:nitrogen ratio control over leaf litter decomposition. Our study suggests that models of terrestrial carbon cycling based on aboveground patterns are inadequate to describe decomposition of the finest plant roots. Decomposition is a key component of the global carbon (C) cycle, yet current ecosystem C models do not adequately represent the contributions of plant roots and their mycorrhizae to this process. The understanding of decomposition dynamics and their control by traits is particularly limited for the most distal first-order roots. Here we followed decomposition of first-order roots and leaf litter from 35 woody plant species differing in mycorrhizal type over 6 years in a Chinese temperate forest. First-order roots decomposed more slowly (k = 0.11 ± 0.01 years−1) than did leaf litter (0.35 ± 0.02 years−1), losing only 35% of initial mass on average after 6 years of exposure in the field. In contrast to leaf litter, nonlignin root C chemistry (nonstructural carbohydrates, polyphenols) accounted for 82% of the large interspecific variation in first-order root decomposition. Leaf litter from ectomycorrhizal (EM) species decomposed more slowly than that from arbuscular mycorrhizal (AM) species, whereas first-order roots of EM species switched, after 2 years, from having slower to faster decomposition compared with those from AM species. The fundamentally different dynamics and control mechanisms of first-order root decomposition compared with those of leaf litter challenge current ecosystem C models, the recently suggested dichotomy between EM and AM plants, and the idea that common traits can predict decomposition across roots and leaves. Aspects of C chemistry unrelated to lignin or nitrogen, and not presently considered in decomposition models, controlled first-order root decomposition; thus, current paradigms of ecosystem C dynamics and model parameterization require revision.
A Profile of eHealth Behaviors in China: Results From a National Survey Show a Low of Usage and Significant Digital Divide

Background: The widely accessible Internet has boosted an enthusiasm for eHealth in China, but we know little about eHealth behaviors in the general population. Objective: To assess the prevalence of eHealth behaviors in general Chinese population and identify the predictors of digital divide. Methods: A nationally representative survey was administered in 2016–2017 with a sample size of 4,043. Five eHealth behaviors were assessed: search health information, communicate with healthcare providers, connect with patients of similar health conditions, buy medicine, and make doctor's appointment online. Multivariate logistic regression was employed to assess the independent relationship between eHealth behaviors and key demographic variables. Results: About 33% of participants have ever searched health information online, and the prevalence of other eHealth behaviors was less than 10%. The adoption of eHealth behaviors was significantly associated with younger age, more education, higher income, and urban residence. By contrast, gender, employment status, health insurance, and health status were not associated with eHealth behavior. Conclusion: The adoption of eHealth behaviors in the general Chinese population was low, and a significant digital divide exists. We caution against the speedy development of Internet hospitals and call for more resources allocated to bridge digital health divide.
Clozapine Pharmacogenetic Studies in Schizophrenia: Efficacy and Agranulocytosis

Clozapine is an efficacious atypical antipsychotic for treatment-refractory schizophrenia. Clinical response and appearance of adverse events vary among individual patients receiving clozapine, with genetic and non-genetic factors potentially contributing to individual variabilities. Pharmacogenetic studies investigate associations between genetic variants and drug efficacy and toxicity. To date, most pharmacogenetic studies of clozapine have been conducted through candidate gene approaches. A recent advance in technology made it possible to perform comprehensive genetic mapping underlying clinical phenotypes and outcomes, which allow novel findings beyond biological hypotheses based on current knowledge. In this paper, we will summarize the studies on clozapine pharmacogenetics that have extensively examined clinical response and agranulocytosis. While there is still limited evidence on clozapine efficacy, recent genome-wide studies provide further evidence of the involvement of the human leukocyte antigen (HLA) region in clozapine-induced agranulocytosis.
Vitamin D and the Immune System

It is now clear that vitamin D has important roles in addition to its classic effects on calcium and bone homeostasis. As the vitamin D receptor is expressed on immune cells (B cells, T cells, and antigen-presenting cells), and these immunologic cells are all capable of synthesizing the active vitamin D metabolite, vitamin D has the capability of acting in an autocrine manner in a local immunologic milieu. Vitamin D can modulate the innate and adaptive immune responses. Deficiency in vitamin D is associated with increased autoimmunity and an increased susceptibility to infection. As immune cells in autoimmune diseases are responsive to the ameliorative effects of vitamin D, the beneficial effects of supplementing vitamin D-deficient individuals with autoimmune disease may extend beyond the effects on bone and calcium homeostasis.
COGNITIVE DEPTH OF TEACHING AND LEARNING PROCESS IN BIOLOGY FROM 7TH TILL 9TH GRADE

From OECD PISA Science test results presented in 2016 shows that in Latvia only 3,4 % of students performance is in accordance to the 5th and 6th performance level (higher order cognitive skills (HOCS) measured), which is below OECD average. In Latvia from 2016 started Curriculum Development and Implementation project, which one of the priorities is student’s ability to apply HOCS (higher order cognitive skills) to improve these results. The development of deeper thinking (cognitive activity) is one of the most advanced skills in all subjects, including biology. In order to reduce the risks, it is necessary to analyze introducing new reforms the opportunities for students to develop HOCS through biology lessons and textbooks in current teaching and learning process. In previous researches it was found out that all items with context of 9th grade biology in the Latvia’s National level Science test (period 2015-2017) were measuring only low and average depth and no one was in high cognitive level as opposed to the PISA framework. It is required to study reasons of that more deeply. The research goal is to analyze cognitive depth of given tasks that students have the opportunity to do in the lessons of biology, biology textbooks from 7th till 9th grade and with 9th grade biology tasks in Latvia’s National level Science tests from years 2015 till 2017 and to compare these three cognitive depth results to the PISA 2015 Science framework. To find out cognitive depth of given tasks, there were analysed 31 samples of biology lessons and 6 biology textbooks for grades 7th till 9th.
Pattern Matching in Link Streams: Timed-Automata with Finite Memory

Link streams model the dynamics of interactions in complex distributed systems as sequences of links (interactions) occurring at a given time. Detecting patterns in such sequences is crucial for many applications but it raises several challenges. In particular, there is no generic approach for the speciﬁcation and detection of link stream patterns in a way similar to regular expressions and automata for text patterns. To address this, we propose a novel automata framework integrating both timed constraints and ﬁnite memory together with a recognition algorithm. The algorithm uses structures similar to tokens in high-level Petri nets and includes non-determinism and concurrency. We illustrate the use of our framework in real-world cases and evaluate its practical performances.
Direct screening of plasma circulating microRNAs

ABSTRACT Circulating microRNAs (miRNAs) are considered as reliable candidates for biomarker discovery. RNA-Sequencing has become the most suitable technique to accurately quantify the miRNAome. However, RNA-Sequencing relies on several technical passages before reaching the final-end. HTG EdgeSeq technology, thanks to the abrogation of RNA extraction step, allows productivity enhancement by reducing the number of hands-on steps, the time for sample preparation and, therefore, the costs. We found a strong correlation between qPCR and dPCR with HTG (Pearson’s coefficient of 0.93 and 0.94, respectively). In conclusion, we showed that HTG EdgeSeq, performed on human plasma specimens without RNA extraction, is reliable, allows the simultaneous screening of more than 2,000 miRNAs, and thus, it could be applied to biomarker discovery in large cohorts.
LC3‐Associated Phagocytosis and Antigen Presentation

LC3‐associated phagocytosis (LAP) is an unconventional form of autophagy that relies on parts of the canonical autophagy machinery for its function. LAP is triggered upon receptor‐mediated phagocytosis and is characterized by the formation of a single‐membrane vesicle decorated with the autophagy protein LC3. In professional phagocytic cells, such as macrophages, the role of LAP in immune processes has been characterized, although how LAP functions at the molecular level remains poorly defined. It is important to point out that as for all autophagic pathways, the study of LAP is still challenging for the scientific community because it is a dynamic and complex process, requiring interactions among several proteins. Here, we describe the most common methods used to monitor and quantify the formation of LC3‐coated single‐membrane endosomes, or so‐called LAPosomes, and to validate the involvement of LAP in immunological processes of human macrophages. © 2018 by John Wiley & Sons, Inc.
Adenomatoid odontogenic tumor: An updated analysis of the cases reported in the literature

PURPOSE To review the clinical and radiographic features of the available data published on adenomatoid odontogenic tumor (AOT) with special emphasis on the comparison of its variants. METHODS An electronic search was undertaken in July 2018. Eligibility criteria included publications having enough clinical/radiological/histological information to confirm the diagnosis. RESULTS A total of 436 publications reporting 1558 cases were included, of which 739 follicular, 247 extrafollicular, and 30 peripheral AOTs. Impacted canine is associated with follicular AOTs in almost 70% of the cases. AOTs were more prevalent in females, in the second decade of life, in maxillae, in anterior region of the jaws, and most are asymptomatic, with a considerable number of lesions presenting cortical bone perforation. Most of the lesions were treated by enucleation. Some cases of recurrence were reported in the literature, but only one was well documented. No difference was found when comparing the clinical/radiological features of the follicular, extrafollicular, and peripheral variants. CONCLUSIONS Adenomatoid odontogenic tumor variants do not show distinctive clinical radiological features. Recurrence of AOT is very rare, which justify its conservative management.
Spatialized Vibrotactile Feedback Improves Goal-Directed Movements in Cluttered Virtual Environments

ABSTRACT Spatial awareness in virtual reality (VR) is a dominant research topic. It plays an essential role in the assessment of human operators’ behavior in simulated tasks, notably for the evaluation of the feasibility of manual maintenance tasks in cluttered industrial settings. In such contexts, it is decisive to evaluate the spatial and temporal correspondence between the operator’s movement kinematics and that of his/her virtual avatar in the virtual environment (VE). Often, in a cluttered VE, direct kinesthetic (force) feedback is limited or absent. We tested whether vibrotactile (cutaneous) feedback would increase visuo-proprioceptive consistency, spatial awareness, and thus the validity of VR studies, by augmenting the perception of the operator’s contact(s) with virtual objects. We present experimental results obtained using a head-mounted display (HMD) during a goal-directed task in a cluttered VE. Results suggest the contribution of spatialized vibrotactile feedback to visuo-proprioceptive consistency.
A MATLAB toolbox for multivariate analysis of brain networks

Complex brain networks formed via structural and functional interactions among brain regions are believed to underlie information processing and cognitive function. A growing number of studies indicate that altered brain network topology is associated with physiological, behavioral, and cognitive abnormalities. Graph theory is showing promise as a method for evaluating and explaining brain networks. However, multivariate frameworks that provide statistical inferences about how such networks relate to covariates of interest, such as disease phenotypes, in different study populations are yet to be developed. We have developed a freely available MATLAB toolbox with a graphical user interface that bridges this important gap between brain network analyses and statistical inference. The modeling framework implemented in this toolbox utilizes a mixed‐effects multivariate regression framework that allows assessing brain network differences between study populations as well as assessing the effects of covariates of interest such as age, disease phenotype, and risk factors on the density and strength of brain connections in global (i.e., whole‐brain) and local (i.e., subnetworks) brain networks. Confounding variables, such as sex, are controlled for through the implemented framework. A variety of neuroimaging data such as fMRI, EEG, and DTI can be analyzed with this toolbox, which makes it useful for a wide range of studies examining the structure and function of brain networks. The toolbox uses SAS, R, or Python (depending on software availability) to perform the statistical modeling. We also provide a clustering‐based data reduction method that helps with model convergence and substantially reduces modeling time for large data sets.