Miracle-dz/UniFAR-FTUs huggingface dataset:
MicroRNA Alterations Induced in Human Skin by Diesel Fumes, Ozone, and UV Radiation

Epigenetic alterations are a driving force of the carcinogenesis process. MicroRNAs play a role in silencing mutated oncogenes, thus defending the cell against the adverse consequences of genotoxic damages induced by environmental pollutants. These processes have been well investigated in lungs; however, although skin is directly exposed to a great variety of environmental pollutants, more research is needed to better understand the effect on cutaneous tissue. Therefore, we investigated microRNA alteration in human skin biopsies exposed to diesel fumes, ozone, and UV light for over 24 h of exposure. UV and ozone-induced microRNA alteration right after exposure, while the peak of their deregulations induced by diesel fumes was reached only at the end of the 24 h. Diesel fumes mainly altered microRNAs involved in the carcinogenesis process, ozone in apoptosis, and UV in DNA repair. Accordingly, each tested pollutant induced a specific pattern of microRNA alteration in skin related to the intrinsic mechanisms activated by the specific pollutant. These alterations, over a short time basis, reflect adaptive events aimed at defending the tissue against damages. Conversely, whenever environmental exposure lasts for a long time, the irreversible alteration of the microRNA machinery results in epigenetic damage contributing to the pathogenesis of inflammation, dysplasia, and cancer induced by environmental pollutants.
Design and Development of a New Piezoelectric-Actuated Biaxial Compliant Microgripper With Long Strokes

In this paper, a new piezoelectric-actuated biaxial compliant microgripper with long strokes is proposed for automatically gripping and rolling tiny rigid objects. In order to improve the working stroke and maintain a compact footprint, a counter-side distributed two-stage lever amplifier with parallelogram mechanism is introduced. Based on the pseudo-rigid body model, analytical models of the displacement amplification ratio, input stiffness, and natural frequency of the left- and right-sided gripper mechanism are established. Structural optimization and performance simulation of the proposed microgripper mechanism are carried out with finite element analysis simulation. A prototype microgripper has been fabricated for open-loop and closed-loop tests to verify its working capabilities. The clamping and rubbing experiments show that the designed microgripper can grasp and rub an optical fiber with the diameter of 200 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> for rolling over 45°. The developed microgripper has a promising application in precision micromanipulation fields such as optical fiber alignment. Note to Practitioners—This work is motivated by the requirement of designing a biaxial microgripper with both a large working stroke and compact structure for complex operation in optical fiber alignment. Through a series of open-loop and closed-loop experiments on the developed prototype, it is demonstrated that the proposed dual-axis microgripper has superior working performance. The clamping stroke and rubbing stroke of the gripper are <inline-formula> <tex-math notation="LaTeX">$251.2~\mu \text{m}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$225.0~\mu \text{m}$ </tex-math></inline-formula>, respectively. The first two natural frequencies of the gripper are 350.63 Hz and 603.37 Hz, which correspond to the working modes of the right-side and left-side gripper mechanisms, respectively. The closed-loop experimental results show that the resolution of output displacement of the gripper is close to <inline-formula> <tex-math notation="LaTeX">$1.2~\mu \text{m}$ </tex-math></inline-formula> and the resolution of the clamping force is 3 mN. As compared with the reported microgrippers in previous work, the designed mechanism exhibits both a large working stroke and high resonant frequency for ensuring the reliability and rapidity of micromanipulation task.
Design, Metallurgical Features, and Mechanical Behaviour of NiTi Endodontic Instruments from Five Different Heat-Treated Rotary Systems

The current study aimed to compare the F1 endodontic instruments from five different heat-treated rotary systems regarding their design, metallurgical properties, and mechanical performance. Five F1 root canal shaping instruments (ProTaper Gold [PTG], Premium Taper Gold, Go-Taper Flex, EdgeTaper Platinum, and Super Files Blue)—plus, a conventional ProTaper Universal (PTU)—which were evaluated regarding their design, nickel/titanium ratio, phase transformation temperatures, microhardness, cyclic fatigue, and torsional and bending strengths. Mood's median test was used for the statistical comparison with a significance set at 5%. The instruments were similar regarding the nickel/titanium ratio and overall design. Go-Taper Flex had the closest transformation temperatures to PTG. PTU and Go-Taper Flex had the highest microhardness (408.3 and 410.5 HVN). The time to fracture of Super Files Blue was three and seven times higher than PTG and PTU, respectively. No difference was observed in the maximum torque to fracture among PTG (1.30 N·cm) and the other systems, except for the Premium Taper Gold (1.05 N·cm) and Go-Taper Flex (1.10 N·cm). Significantly lower bending loads than PTG (269.2 gf) were observed for the EdgeTaper Platinum (158.3 gf) and Premium Taper Gold (103.5 gf) instruments. Super Files Blue outperformed PTG in the cyclic fatigue test, while EdgeTaper Platinum and Premium Taper Gold were more flexible. Premium Taper Gold and Go-Taper Flex showed lower torsional strength.
Textile Slotted Waveguide Antennas for Body-Centric Applications

One of the major challenges in the development of wearable antennas is to design an antenna that can at the same time satisfy technical requirements, be aesthetically acceptable, and be suitable for wearable applications. In this paper, a novel wearable antenna is proposed—textile realization of a slotted waveguide antenna. The antenna is realized using conductive fabric to manufacture the walls of a rectangular waveguide in which the slots were cut out. All connections and cuts are sewn with conductive thread taking over advantages of the traditional process of manufacturing textile objects. The developed slotted waveguide array prototype, containing three slots and designed for operation in the 5.8-GHz ISM band, is experimentally characterized and compared to an equivalent metallic antenna. The achieved operating bandwidth is larger than 300 MHz in both cases. The measured gain of a textile slotted waveguide array is around 9 dBi with a radiation efficiency larger than 50% in the whole operating bandwidth, i.e., the textile array showed a 2 dB lower gain in comparison to the metallic counterpart. The gain is stable in the whole bandwidth and the radiation patterns do not differ. The results demonstrated that such textile antennas are suitable for body-centric communication and sensor systems and can be integrated into clothing, e.g., into a smart safety vest or into a uniform. Further analysis of various realizations of slotted waveguide antennas is presented showing that different versions of the proposed antenna can be used in all three off-body, on-body, and in-body communication scenarios.
Cross-Lingual Few-Shot Hate Speech and Offensive Language Detection using Meta Learning

Automatic detection of abusive online content such as hate speech, offensive language, threats, etc. has become prevalent in social media, with multiple efforts dedicated to detecting this phenomenon in English. However, detecting hatred and abuse in low-resource languages is a non-trivial challenge. The lack of sufficient labeled data in low-resource languages and inconsistent generalization ability of transformer-based multilingual pre-trained language models for typologically diverse languages make these models inefficient in some cases. We propose a meta learning-based approach to study the problem of few-shot hate speech and offensive language detection in low-resource languages that will allow hateful or offensive content to be predicted by only observing a few labeled data items in a specific target language. We investigate the feasibility of applying a meta-learning approach in cross-lingual few-shot hate speech detection by leveraging two meta-learning models based on optimization-based and metric-based (MAML and Proto-MAML) methods. To the best of our knowledge, this is the first effort of this kind. To evaluate the performance of our approach, we consider hate speech and offensive language detection as two separate tasks and make two diverse collections of different publicly available datasets comprising 15 datasets across 8 languages for hate speech and 6 datasets across 6 languages for offensive language. Our experiments show that meta learning-based models outperform transfer learning-based models in a majority of cases, and that Proto-MAML is the best performing model, as it can quickly generalize and adapt to new languages with only a few labeled data points (generally, 16 samples per class yields an effective performance) to identify hateful or offensive content.
tlrmvnmvt: Computing High-Dimensional Multivariate Normal and Student- t Probabilities with Low-Rank Methods in R

This paper introduces the usage and performance of the R package tlrmvnmvt, aimed at computing high-dimensional multivariate normal and Student-t probabilities. The package implements the tile-low-rank methods with block reordering and the separationof-variable methods with univariate reordering. The performance is compared with two other state-of-the-art R packages, namely the mvtnorm and the TruncatedNormal packages. Our package has the best scalability and is likely to be the only option in thousands of dimensions. However, for applications with high accuracy requirements, the TruncatedNormal package is more suitable. As an application example, we show that the excursion sets of a latent Gaussian random field can be computed with the tlrmvnmvt package without any model approximation and hence, the accuracy of the produced excursion sets is improved.
MIOTA-Based Filters for Noise and Motion Artifact Reductions in Biosignal Acquisition

This paper presents a new low-voltage CMOS structure for operational transconductance amplifier (OTA) exploiting the bulk-driven, the self-cascode and the multiple-input transistor techniques (MI). The multiple-input OTA (MIOTA) circuit operates in subthreshold region using 0.5V supply voltage and offers enhanced linearity. The MIOTA is developed for biopotential signal as well as electrocardiogram (ECG) signal processing circuit and it is exploited to design a 5th-order Chebyshev low-pass and 3rd-order band-pass filters with a dynamic range (DR) of 57.6 dB and 60.4 dB, and nanopower consumption of 50 nW and 60 nW, respectively. Due to the electronic tuning of cut-off frequency, the low-pass and band-pass filters are suitable for random noise and motion artifact noise reductions in biopotential signals. The circuits were designed in Cadence environment using the standard N-well $0.18~\mu \text{m}$ TSMC CMOS technology. Intensive post-layout simulation results along with the process, voltage, temperature analysis (PVT) and Monte Carlo (MC) prove the robustness of the design. The chip area of the proposed MIOTA is 0.00725 mm2 ( $118~\mu \text{m}\,\,\times 61.5\,\,\mu \text{m}$ ). Compared with standard OTA the MIOTA offers simplification of filter topology and reduced number of active elements. In order to demonstrate these advantages, the MIOTA-based filter was also build using commercially available OTA LT1228. The experimental results of OTA LT1228 confirm both the filter functionality and the advantages of the proposed MIOTA.
A KNN Classification Advisory System For Higher Institution Students’ Performance

This study focuses on enhancing students' performance through data mining techniques to reduce the challenges of low grades associated with some students in higher institutions in Nigeria. Presently, the amount of data stored in most higher institutions' databases are increasing rapidly. Nevertheless, some higher institutions still rely on paper files to store students’ results. Even those institutions with databases do not know what to do with their data after graduating the students. Thus, this study proposes a method that will use data mining techniques such as the k-nearest neighbor's algorithm to extract the hidden knowledge available in the higher institution databases. The proposed method of classifying students' performance is useful in identifying the poor students by providing the framework that will guide them to acquire better grades or change to other departments where they may be better suited. Keywords: Advisory, classification, data mining, KNN, performance.
Ekstraksi Perubahan Tutupan Vegetasi Di Kabupaten Gorontalo Menggunakan Google Earth Engine

Monitoring changes in vegetation cover is important for the restoration of ecosystems in the Gorontalo Regency area. The utilization of remote sensing technology makes it possible to detect the dynamics of changes in vegetation cover spatially and temporally. The Terra MODIS satellite image collection in the study area is available in large numbers and sizes. Therefore, cloud computing-based spatial technology support is needed. Google Earth Engine (GEE) as a geospatial computing device is an alternative to cover this shortfall. The aim of this study is to explore the condition of vegetation cover spatially and temporally using the GEE platform. A total of 43 MODIS images in the study area, recording periods 2000 and 2020, were used to quickly and effectively generate vegetation cover maps. The process of downloading, processing, and analyzing data was automated through the GEE interface. The results of the mapping in 2000 and 2020 are shown by maps of vegetation cover in two classes, namely; vegetation and non-vegetation. The accuracy of the vegetation cover map shows good results, namely an overall accuracy of 0.81 for 2000 and 0.85 for 2020. The area of the non-vegetation class increased by 2815.29 ha, and the vegetation class decreased by 2767.31 ha. The map of spatial changes in vegetation cover in the study area is classified into three classes, namely revegetation, devegetation, and unchanged. Based on these results, the extraction of vegetation cover changes in the study area using the GEE platform can be carried out well.
Lingering Male Breadwinner Norms as Predictors of Family Satisfaction and Marital Instability

Scholars have assumed that as gender revolutions are completed and societies achieve advanced levels of gender egalitarianism, married persons become happier, and marriages become stable. This study investigates how the norms about gender roles are associated with marital instability. The analysis is based on two propositions: (1) marital dissolution is an outcome of two rather distinct processes, deterioration of marital quality and formation of a decision to leave a marriage, and (2) the antithesis of advanced gender egalitarianism is a set of lingering male breadwinner norms, not gender inequality often manifested by working women performing second shifts. The data are from 68 national surveys conducted in 2002 and 2012 through ISSP coordination, and the sample of person-level analysis is restricted to ages 30–49, supposedly in the life cycle stages of family formation and expansion. The norms of gender roles are classified into four types: traditional norm, prescribing gendered division of labor; lingering male breadwinner norm, emphasizing men as the primary breadwinners while allowing flexibility of women’s roles; super woman norm, prescribing women to perform double roles; and egalitarian norm, emphasizing equal sharing of roles. At the country level, aggregate variables were constructed by calculating the percentage of adults who held each type of norm. The results strongly support the prediction that the male breadwinner norm at the societal level is detrimental to marital quality, while persons holding the egalitarian norm are most satisfied with their family lives.
Seasonal Tidewater Glacier Terminus Oscillations Bias Multi‐Decadal Projections of Ice Mass Change

Numerical, process‐based simulations of tidewater glacier evolution are necessary to project future sea‐level change under various climate scenarios. Previous work has shown that nonlinearities in tidewater glacier and ice stream dynamics can lead to biases in simulated ice mass change in the presence of noisy forcings. Ice sheet modeling projections that are used in the IPCC Assessment Report 6 (AR6) utilize atmospheric and oceanic forcings at annual temporal resolution, omitting any higher frequency forcings. Here, we quantify the effect of seasonal (<1 year) tidewater glacier terminus oscillations on decadal‐scale (30 years) mass change. We use an idealized geometry to mimic realistic tidewater glacier geometries and investigate the impact of the magnitude of seasonal oscillations, bed slope at the glacier terminus, and basal friction law. We find that omitting seasonal terminus motion results in biased mass change projections, with up to an 39% underestimate or 25% overestimate of mass loss when seasonality is neglected, depending on bed slope and magnitude of oscillations. The bias is most sensitive to the magnitude of the seasonal terminus oscillations and exhibits very little sensitivity to choice of friction law. Although omitting seasonal terminus motion may bias mass change projections of individual glaciers, further work is needed to investigate the impact on ice sheet mass change projections. In order to achieve this, seasonality in atmospheric and oceanic forcings must be adequately represented and observations of seasonal terminus positions and tidewater glacier thickness changes must be acquired to evaluate numerical models.
Perception of runway image shape and approach angle magnitude by pilots in simulated night landing approaches

One cue for visual judgments of glidepath angle has been referred to as form ratio. Form ratio is defined as the ratio of vertical height of the runway to width of the far end in the runway retinal image. The ability of pilots to judge form ratios was compared with the ability to judge approach angles in the nighttime "black hole" situation in two experiments. Responses in both static and dynamic simulated approach conditions indicated a general tendency to overestimate form ratios and approach angles less than 3 degrees. Intersubject and intrasubject variability of form ratio and approach angle responses were comparable. These findings (i) do not support the utility of form ratio judgments as an aid in selecting approach angle, (ii) add to the empirical evidence of visual illusions and the danger of reliance on visual information for judgment of approach angle in the nighttime "black hole" situation where only runway light are visible, and (iii) point to variability in perception of approach angle as an important part of the problem. Language: en
Recent Advances in the Rheumatic Fever and Rheumatic Heart Disease Continuum

Nearly a century after rheumatic fever (RF) and rheumatic heart disease (RHD) was eradicated from the developed world, the disease remains endemic in many low- and middle-income countries (LMICs), with grim health and socioeconomic impacts. The neglect of RHD which persisted for a semi-centennial was further driven by competing infectious diseases, particularly the human immunodeficiency virus (HIV) pandemic. However, over the last two-decades, slowly at first but with building momentum, there has been a resurgence of interest in RF/RHD. In this narrative review, we present the advances that have been made in the RF/RHD continuum over the past two decades since the re-awakening of interest, with a more concise focus on the last decade’s achievements. Such primary advances include understanding the genetic predisposition to RHD, group A Streptococcus (GAS) vaccine development, and improved diagnostic strategies for GAS pharyngitis. Echocardiographic screening for RHD has been a major advance which has unearthed the prevailing high burden of RHD and the recent demonstration of benefit of secondary antibiotic prophylaxis on halting progression of latent RHD is a major step forward. Multiple befitting advances in tertiary management of RHD have also been realized. Finally, we summarize the research gaps and provide illumination on profitable future directions towards global eradication of RHD.
Phenolic Content and Antioxidant Activity in Apples of the ‘Galaval’ Cultivar Grown on 17 Different Rootstocks

Apple cultivars are one of the main factors setting the composition of bioactive compounds in apples and the quality of the fruit. However, research has been providing increasing amounts of data on the influence of rootstocks on the variations in the composition of bioactive compounds in apples. The aim of the study was to determine the influence of rootstocks on the changes in the qualitative and quantitative composition of phenolic compounds and their antioxidant activity in vitro in apple flesh and peel. HPLC analyses of phenolic compounds in apple samples were performed. The rootstock–scion combination had a significant effect on the composition and antioxidant activity of phenolic compounds in apple samples. Depending on the rootstock, the total content of phenolic compounds in apple flesh of the ‘Galaval’ cultivar could vary by 2.9 times, and in the peel by up to 90%. The genotype of the rootstock resulted in the highest variation in total flavan-3-ol content in apple flesh—by as much as 4.3 times—while the total content of flavonols varied by 2.1 times. In apple peel, on the contrary, the greatest variation was recorded for the total flavonol content (by 4.4 times), and the total flavan-3-ol content varied the least (by 1.8 times). A proper match of a cultivar and a rootstock can program a fruit tree to grow larger amounts of higher-quality, antioxidant-rich, and high-nutrition-value fruit.
The Structural Basis of Mycobacterium tuberculosis RpoB Drug-Resistant Clinical Mutations on Rifampicin Drug Binding

Tuberculosis (TB), caused by the Mycobacterium tuberculosis infection, continues to be a leading cause of morbidity and mortality in developing countries. Resistance to the first-line anti-TB drugs, isoniazid (INH) and rifampicin (RIF), is a major drawback to effective TB treatment. Genetic mutations in the β-subunit of the DNA-directed RNA polymerase (rpoB) are reported to be a major reason of RIF resistance. However, the structural basis and mechanisms of these resistant mutations are insufficiently understood. In the present study, thirty drug-resistant mutants of rpoB were initially modeled and screened against RIF via a comparative molecular docking analysis with the wild-type (WT) model. These analyses prioritized six mutants (Asp441Val, Ser456Trp, Ser456Gln, Arg454Gln, His451Gly, and His451Pro) that showed adverse binding affinities, molecular interactions, and RIF binding hinderance properties, with respect to the WT. These mutant models were subsequently analyzed by molecular dynamics (MD) simulations. One-hundred nanosecond all-atom MD simulations, binding free energy calculations, and a dynamic residue network analysis (DRN) were employed to exhaustively assess the impact of mutations on RIF binding dynamics. Considering the global structural motions and protein–ligand binding affinities, the Asp441Val, Ser456Gln, and His454Pro mutations generally yielded detrimental effects on RIF binding. Locally, we found that the electrostatic contributions to binding, particularly by Arg454 and Glu487, might be adjusted to counteract resistance. The DRN analysis revealed that all mutations mostly distorted the communication values of the critical hubs and may, therefore, confer conformational changes in rpoB to perturb RIF binding. In principle, the approach combined fundamental molecular modeling tools for robust “global” and “local” level analyses of structural dynamics, making it well suited for investigating other similar drug resistance cases.