Miracle-dz/UniFAR-FTUs huggingface dataset:
Next‐Generation Genotoxicology: Using Modern Sequencing Technologies to Assess Somatic Mutagenesis and Cancer Risk

Mutations have a profound effect on human health, particularly through an increased risk of carcinogenesis and genetic disease. The strong correlation between mutagenesis and carcinogenesis has been a driving force behind genotoxicity research for more than 50 years. The stochastic and infrequent nature of mutagenesis makes it challenging to observe and to study. Indeed, decades have been spent developing increasingly sophisticated assays and methods to study these low‐frequency genetic errors, in hopes of better predicting which chemicals may be carcinogens, understanding their mode of action, and informing guidelines to prevent undue human exposure. While effective, widely used genetic selection‐based technologies have a number of limitations that have hampered major advancements in the field of genotoxicity. Emerging new tools, in the form of enhanced next‐generation sequencing platforms and methods, are changing this paradigm. In this review, we discuss rapidly evolving sequencing tools and technologies, such as error‐corrected sequencing and single cell analysis, which we anticipate will fundamentally reshape the field. In addition, we consider a variety emerging applications for these new technologies, including the detection of DNA adducts, inference of mutational processes based on genomic site and local sequence contexts, and evaluation of genome engineering fidelity, as well as other cutting‐edge challenges for the next 50 years of environmental and molecular mutagenesis research. Environ. Mol. Mutagen. 61:135–151, 2020. © 2019 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society.
Two Hand Gesture Based 3D Navigation in Virtual Environments

Natural interaction is gaining popularity due to its simple, attractive, and realistic nature, which realizes direct Human Computer Interaction (HCI). In this paper, we presented a novel two hand gesture based interaction technique for 3 dimensional (3D) navigation in Virtual Environments (VEs). The system used computer vision techniques for the detection of hand gestures (colored thumbs) from real scene and performed different navigation (forward, backward, up, down, left, and right) tasks in the VE. The proposed technique also allow users to efficiently control speed during navigation. The proposed technique is implemented via a VE for experimental purposes. Forty (40) participants performed the experimental study. Experiments revealed that the proposed technique is feasible, easy to learn and use, having less cognitive load on users. Finally gesture recognition engines were used to assess the accuracy and performance of the proposed gestures. kNN achieved high accuracy rates (95.7%) as compared to SVM (95.3%). kNN also has high performance rates in terms of training time (3.16 secs) and prediction speed (6600 obs/sec) as compared to SVM with 6.40 secs and 2900 obs/sec.
Chromosomal Mapping of Rex Retrotransposons in Tambaqui (Colossoma macropomum Cuvier, 1818) Exposed to Three Climate Change Scenarios

Greenhouse gas emissions are known to influence the planet's temperature, mainly due to human activities. To allow hypothesis testing, as well as to seek viable alternatives for mitigation, the Intergovernmental Panel on Climate Change (IPCC) suggested 3 main scenarios for changes projected for the year 2100. In this paper, we subjected Colossoma macropomum Cuvier, 1818 (tambaqui) individuals in a microcosm to IPCC scenarios B1 (mild), A1B (intermediate), and A2 (extreme) to test possible impacts on their genome. We found chromosome heterochromatinization in specimens exposed to the A2 scenario, where terminal blocks and interstitial bands were detected on several chromosome pairs. The behavior of Rex1 and Rex3 sequences differed between the test scenarios. Hybridization of Rex1 resulted in diffuse signals which showed a gradual increase in the tested scenarios. For Rex3, an increase was observed in the A2 scenario with blocks on several chromosomes, some of which coincided with heterochromatin. Heterochromatinization is an epigenetic process, which may have occurred as a mechanism for regulating Rex3 activity. The signal pattern of Rex6 did not change, suggesting that other mechanisms are acting to regulate its activity.
MicroRNAs: Small molecules with a large impact on pre‐eclampsia

As critical mediators in biological processes, microRNAs (miRNAs) which are small and endogenous noncoding RNAs have been associated with disease progression, cell proliferation, and development. Pre‐eclampsia (PE), a pregnancy‐related disorder with no early markers or symptoms is recognized as the main reason for fetal and maternal mortality and morbidity in the initial steps or even during pregnancy, worldwide. Clinical symptoms usually appear in the third trimester of the pregnancy. Although numerous research have unraveled several aspects of placenta development abnormalities associated with abnormal trophoblastic invasion and angiogenesis modification, many questions about the PE pathogenesis remains unanswered. A large number of studies have shown the important role of miRNAs as potential biomarkers in the PE prognosis and diagnosis. Here, the latest investigations about the PE and placental miRNAs expression, as well as, the crucial role of miRNA molecules including miR‐210 and miR‐155 which are deregulated in patients with PE, will be argued.
English Proverbs into Arabic through Machine Translation

Proverbs are sentences used by people to convey wisdom, truth or morals that have been handed down for generations. Translating them from one language into another through machine translation has been a matter of interest because of their importance in keeping the religious, cultural and historical aspects. The accuracy of machine translation systems has become one of the most important issues nowadays as the demand for online translation is increasing. Therefore, the current study aimed at investigating the linguistic obstacles that machine translation might face in carrying out the same translation from English proverbs into Arabic. It also attempted to confirm the importance of human intervention in solving the issue of accuracy. To achieve these objectives, a group of English proverbs were randomly selected, translated into Arabic by ‘Google translate’ and analysed qualitatively by the researchers. On the one hand, the findings revealed that ‘Google translate’ faced some linguistic obstacles in carrying out the same meaning of English proverbs into Arabic. Lexically, words that have multiple meanings present countless challenges and difficulties to online translation. On the other hand, the different linguistic structures between English and Arabic make the process of translation sometimes a bit challenging as both languages belong to unrelated families. Simply put, machine translation is expected to encounter various problems in providing meaningful logical translation. A detailed discussion is provided and recommendations for further research are given based on the analysis.
TOR Signaling in Caenorhabditis elegans Development, Metabolism, and Aging

The Target of Rapamycin (TOR or mTOR) is a serine/threonine kinase that regulates growth, development, and behaviors by modulating protein synthesis, autophagy, and multiple other cellular processes in response to changes in nutrients and other cues. Over recent years, TOR has been studied intensively in mammalian cell culture and genetic systems because of its importance in growth, metabolism, cancer, and aging. Through its advantages for unbiased, and high-throughput, genetic and in vivo studies, Caenorhabditis elegans has made major contributions to our understanding of TOR biology. Genetic analyses in the worm have revealed unexpected aspects of TOR functions and regulation, and have the potential to further expand our understanding of how growth and metabolic regulation influence development. In the aging field, C. elegans has played a leading role in revealing the promise of TOR inhibition as a strategy for extending life span, and identifying mechanisms that function upstream and downstream of TOR to influence aging. Here, we review the state of the TOR field in C. elegans, and focus on what we have learned about its functions in development, metabolism, and aging. We discuss knowledge gaps, including the potential pitfalls in translating findings back and forth across organisms, but also describe how TOR is important for C. elegans biology, and how C. elegans work has developed paradigms of great importance for the broader TOR field.
Translation, adaptation and validation of the Nurse-Work Instability Scale to Brazilian Portuguese*

Objective to translate, adapt and test the psychometric properties of the Brazilian Nurse-Work Instability Scale. Method this was a methodological study following the translation steps: synthesis, back-translation, specialist´s committee, semantics analysis, pretest, and psychometric tests. The committee was composed of 5 specialists. For the semantics analysis, 18 nursing workers evaluated the instrument and 30 pretested it. For the psychometric tests, the sample size was 214 nursing workers. The internal construct validity was analyzed by the Rasch model. Reliability was assessed using internal consistency, and concurrent validity with Pearson’s correlation between the Nurse-Work Instability Scale, and the Work Ability Index, Job Stress Scale. Results a Nurse-Work Instability Scale in Brazilian Portuguese with 20 items showed an adequate reliability (0.831), stability (p <0.0001), and an expected correlation with Work Ability Index (r = -0.526; P<0.0001) and Job Stress Scale (r = 0.352; p <0.0001). Conclusion the instrument is appropriated to detect work instability in Brazilian nursing workers with musculoskeletal disorders. Its application is fundamental to avoid long-term withdrawal from work by early identification of the work instability. Furthermore, the scale can assist the development of actions and strategies to prevent the abandonment of the profession of nursing workers affected by musculoskeletal disorders.
Early classroom reading gains moderate shared environmental influences on reading comprehension in adolescence.

BACKGROUND Reading is important for children's success in school and beyond, yet many adolescents fail to reach expected levels of proficiency. This highlights the need to better understand the factors that influence reading effectiveness over time, including genes and environment. Greater expression of genetic influence on first- and second-grade reading fluency has been observed in higher quality classroom reading environments. To what degree this early environment continues to influence genetic and other environmental influences on later reading is unknown and was tested in this study. METHODS The quality of the early classroom reading environment was approximated by gains in oral reading fluency (ORF) across the school year among first- or second-grade classmates of 546 MZ and 1,016 DZ twin children (mean age = 7.13 years; SD = 0.45) who had reading comprehension scores from a state-wide mandatory test in school year 2013-2014 when most twin pairs were in seventh to tenth grade (mean age = 14.41; SD = 1.13) in a variable called Class ORF Gain. Biometrical models were fit to the data to assess whether Class ORF Gain moderated the genetic, shared environmental and/or nonshared environmental variance associated with adolescent reading comprehension. RESULTS Class ORF Gain moderated shared environmental influences on reading comprehension 6-9 years later. When early classroom reading gains were poor, variability in reading comprehension in adolescence was high and was associated largely with shared environmental influences. When early classroom reading gains were good, overall and shared environmentally influenced variability in adolescent reading comprehension was lower so that genetic influences were most relevant in explaining that variability. CONCLUSIONS Our findings suggested that classroom reading environment experienced when children were learning to read had a lasting influence on the factors underlying variability in later reading effectiveness.
A mobile game-based C programming language learning: results of university students' achievement and motivations

Teaching and learning process has been modified from lecture-based learning to be more interesting and motivating learning environment with the use of modern technologies and variety of technological tools. The educational computer game, which is one of the effective learning tools, has been used to support teaching and to motivate learning in various subjects. With less computer game in higher education, especially on C programming language course, this study developed a mobile game for simulating the compiler working with human daily life situations for the C programming language learning. The developed game was conducted on university students for evaluating the overview of students' C programming language motivation and learning achievement. Moreover, this study examined the differences of motivation and learning achievement between students who had experience and inexperience with educational computer games.
H2Al - The Human Health and Activity Laboratory

The Human Health and Activity Laboratory (H2Al) is a new research facility at Luleå University of Technology implemented during 2018 as a smart home environment in an educational training apartment for nurses and therapists at the Luleå campus. This paper presents the design and implementation of the lab together with a discussion on potential impact. The aim is to identify and overcome economical, technical and social barriers to achieve an envisioned good and equal health and welfare within and from home environments. The lab is equipped with multiple sensor and actuator systems in the environment, worn by persons and based on digital information. The systems will allow for advanced capture, filtering, analysis and visualization of research data such as A/V, EEG, ECG, EMG, GSR, respiration and location while being able to detect falls, sleep apnea and other critical health and wellbeing issues. The resulting studies will be aimed towards supporting and equipping future home environments and care facilities, spanning from temporary care to primary care at hospitals, with technologies for activity and critical health and wellness issue detection. The work will be conducted at an International level and within a European context, based on a collaboration with other smart labs, such that experiments can be replicated at multiple sites. This paper presents some initial lessons learnt including design, setup and configuration for comparison of sensor placements and configurations as well as analytical methods.
Evaluation of the shrinkage and creep of medium strength self compacting concrete

The difference between self compacting concrete (SCC) and conventional concrete (CC) is in fresh state, is the high fluidity at first and the need for vibration at second, but in hardened state, both concretes must comply with the resistance specified, in addition to securing the safety and functionality for which it was designed. This article describes the tests and results for shrinkage and creep at some medium strength Self Compacting Concrete with added sand (SCC-MSs) and two types of cement. The research was conducted at the Laboratorio de Tecnología de Estructuras (LTE) of the Universitat Politécnica de Catalunya (UPC), in dosages of 200 liters; with the idea of evaluating the effectiveness of implementation of these new concretes at elements designed with conventional concrete (CCs).
Correction for Beeby et al., Diverse high-torque bacterial flagellar motors assemble wider stator rings using a conserved protein scaffold

Although it is known that diverse bacterial flagellar motors produce different torques, the mechanism underlying torque variation is unknown. To understand this difference better, we combined genetic analyses with electron cryo-tomography subtomogram averaging to determine in situ structures of flagellar motors that produce dif- ferent torques, from Campylobacter and Vibrio species. For the first time, to our knowledge, our results unambiguously locate the torque- generating stator complexes and show that diverse high-torque motors use variants of an ancestrally related family of structures to scaffold incorporation of additional stator complexes at wider radii from the axial driveshaft than in the model enteric motor. We identify the protein components of these additional scaffold structures and elucidate their sequential assembly, demonstrating that they are required for stator-complex incorporation. These proteins are widespread, suggesting that different bacteria have tailored torques to specific environments by scaffolding alternative stator placement and number. Our results quantitatively account for dif- ferent motor torques, complete the assignment of the locations of the major flagellar components, and provide crucial constraints for understanding mechanisms of torque generation and the evolution of multiprotein complexes.
Visualizing Data to Support Judgement, Inference, and Decision Making in Learning Analytics: Insights from Cognitive Psychology and Visualization Science

Understanding human judgement and decision making during visual inspection of data is of both practical and theoretical interest. While visualizing data is a commonly employed mechanism to support complex cognitive processes such as inference, judgement, and decision making, the process of supporting and scaffolding cognition through effective design is less well understood. Applying insights from cognitive psychology and visualization science, this paper critically discusses the role of human factors — visual attention, perception, judgement, and decision making — toward informing methodological choices when visualizing data. The value of visualizing data is discussed in two key domains: 1) visualizing data as a means of communication; and 2) visualizing data as research methodology. The first applies cognitive science principles and research evidence to inform data visualization design for communication. The second applies data- and cognitive-science to deepen our understanding of data, of its uncertainty, and of analysis when making inferences. The evidence for human capacity limitations — attention and cognition — are discussed in the context of data visualizations to support inference-making in both domains, and are followed by recommendations. Finally, how learning analytics can further research on understanding the role data visualizations can play in supporting complex cognition is proposed.
Methodology and architectures for system-on-chip real-time control

Control systems are being embedded in an ever-increasing number of applications, many of them unfeasible prior to the joined advances in control, solid state technology and microelectronics design. In the era of information, communication and technology, society continuously absorbs new technologies and quickly demands new tools, services and commodities that require challenging control techniques operated at high sample rates. However, the implementation of modern control systems is by no means straightforward and requires multidisciplinary knowledge in fields of control, hardware and software design. Complex control laws with demanding real-time constraints are usually implemented using high-end devices combined with some custom logic in project-dependent, hence non-reusable solutions. Such high-end devices are intended to be flexible enough to cover a wide range of applications and therefore their architectural complexity often leads to inefficient control solutions in terms of power consumption, area and even performance. Furthermore, in order to fulfil the real-time requirements, complex device-dependent arithmetic routines have to be usually hand crafted in assembly language as most modern compilers are unable to make use of the narrow data vector instructions that are especially tailored for signal processing applications, and sometimes, the required performance can only be reached by a number of these devices running in parallel. This thesis presents a comprehensive study of embedded real-time control implementations, bringing together hardware/software co-design, development tools and controller formulation aspects under a common framework that leads to a novel design methodology. [Continues. ]
Design Optimization of RML Glove for Improved Grasp Performance

This paper describes the design optimization of the RML Glove in order to improve its grasp performance. The existing design is limited to grasping objects of large diameter (> 110mm) due to its inability in attaining high bending angles. For an exoskeleton glove to be effective in its use as an assistive and rehabilitation device for Activities of Daily Living (ADL), it should be able to interact with objects over a wide range of sizes. Motivated by these limitations, the kinematics of the existing linkage mechanism was analyzed in detail and the design variables were identified. Two different cost functions were formulated and compared in their ability to yield optimal values for the design variables. The optimal set of design variables was chosen based on the grasp angles achieved and the resulting mechanism was simulated in CAD for feasibility testing. An exoskeleton mechanism corresponding to the index finger was manufactured with the chosen design variables and detailed experimental validation was performed to illustrate the improvement in grasp performance over the existing design. The paper ends with a summary of the experimental results and directions for future research.
License Plate Recognition using Convolutional Neural Networks Trained on Synthetic Images

In this thesis, we propose a license plate recognition system and study the feasibility of using synthetic training samples to train convolutional neural networks for a practical application. First we develop a modular framework for synthetic license plate generation; to generate different license plate types (or other objects) only the first module needs to be adapted. The other modules apply variations to the training samples such as background, occlusions, camera perspective projection, object noise and camera acquisition noise, with the aim to achieve enough variation of the object that the trained networks will also recognize real objects of the same class. Then we design two convolutional neural networks of low-complexity for license plate detection and character recognition. Both are designed for simultaneous classification and localization by branching the networks into a classification and a regression branch and are trained end-to-end simultaneously over both branches, on only our synthetic training samples. To recognize real license plates, we design a pipeline for scale invariant license plate detection with a scale pyramid and a fully convolutional application of the license plate detection network in order to detect any number of license plates and of any scale in an image. Before character classification is applied, potential plate regions are un-skewed based on the detected plate location in order to achieve an as optimal representation of the characters as possible. The character classification is also performed with a fully convolutional sweep to simultaneously find all characters at once. Both the plate and the character stages apply a refinement classification where initial classifications are first centered and rescaled. We show that this simple, yet effective trick greatly improves the accuracy of our classifications, and at a small increase of complexity. To our knowledge, this trick has not been exploited before.