Miracle-dz/UniFAR-FTUs huggingface dataset:
Accessible Dyslexia Detection with Real-Time Reading Feedback through Robust Interpretable Eye-Tracking Features

Developing reliable, quantifiable, and accessible metrics for dyslexia diagnosis and tracking represents an important goal, considering the widespread nature of dyslexia and its negative impact on education and quality of life. In this study, we observe eye-tracking data from 15 dyslexic and 15 neurotypical Serbian school-age children who read text segments presented on different color configurations. Two new eye-tracking features were introduced that quantify the amount of spatial complexity of the subject’s gaze through time and inherently provide information regarding the locations in the text in which the subject struggled the most. The features were extracted from the raw eye-tracking data (x, y coordinates), from the original data gathered at 60 Hz, and from the downsampled data at 30 Hz, examining the compatibility of features with low-cost or custom-made eye-trackers. The features were used as inputs to machine learning algorithms, and the best-obtained accuracy was 88.9% for 60 Hz and 87.8% for 30 Hz. The features were also used to analyze the influence of background/overlay color on the quality of reading, and it was shown that the introduced features separate the dyslexic and control groups regardless of the background/overlay color. The colors can, however, influence each subject differently, which implies that an individualistic approach would be necessary to obtain the best therapeutic results. The performed study shows promise in dyslexia detection and evaluation, as the proposed features can be implemented in real time as feedback during reading and show effectiveness at detecting dyslexia with data obtained using a lower sampling rate.
Peculiar surface deformation of sapphire: Numerical simulation of nanoindentation

This report addresses the origin of peculiar anisotropic deformation of sapphire. The three-dimensional finite element simulation of the contact between spherical indenter and elastically anisotropic solid allowed us to analyze stress under the tip that penetrates in the (1010) and (0001) planes, and consequently, to localize those regions in which particular deformation mechanisms are likely to be activated. This approach contrasts the available models of “hardness anisotropy,” which routinely apply a modified uniaxial-stress approach to this essentially three-dimensional, nonisotropic contact problem. The calculated results are in agreement with the microscopic inspection of impressions; that is, the surface features reflect the distribution of stress. The computations made it also possible to evaluate the actual radius of the tip (nominally 5 μm ball).
Three-dimensional motion-compensated subband coding

Three-dimensional (3-D) frequency coding is an alternative approach to hybrid coding concepts used in nowaday standards. However, the lack of Motion Compensation (MC) techniques is a drawback in 3-D coders when compared to hybrid MC coding. This paper presents a 3-D Subband Coding (SBC) scheme with MC, which is based on a separable structure. Motion-compensated 2-tap Quadrature Mirror Filters (QMFs) are employed for subband decomposition along the temporal axis, and a parallel Time Domain Aliasing Cancellation (TDAC) filter bank is used for decomposition in the spatial domain. The temporal axis analysis and synthesis operations are performed in a cascade structure. A special substitution technique, which occasionally places unfiltered values into the temporal lowpass band at any stage of cascade, guarantees perfect reconstruction synthesis in the case of a non- uniform Motion Vector Field (MVF) with full-pel MC accuracy. With sub-pel accuracy, though coding efficiency is higher, perfect reconstruction is no longer guaranteed. Lattice Vector Quantization (LVQ) has been employed to encode the subband samples. In contrast to hybrid coders, it is straightforward to perform quantization with spatio-temporal perceptual weighting. Coding results are presented, which show that standard hybrid coding concepts are outperformed by up to 4 dB with the 3-D MC-SBC/VQ coder.
Prescribing Patterns and Outcomes of Edoxaban in Atrial Fibrillation: One-Year Data from the Global ETNA-AF Program

Non-recommended dosing occurs in ~25–50% of non-vitamin K antagonist oral anticoagulant prescriptions, with limited data for edoxaban. We analyzed edoxaban dosing patterns in atrial fibrillation patients from the Global ETNA-AF program, relating patterns to baseline characteristics and 1-year clinical outcomes. The following dosing groups were compared: non-recommended 60 mg (“overdosed”) vs. recommended 30 mg; non-recommended 30 mg (“underdosed”) vs. recommended 60 mg. Most (22,166/26,823; 82.6%) patients received recommended doses. Non-recommended dosing was more frequent near label-specified dose-reduction thresholds. Ischemic stroke (IS; HR 0.85, 95% CI 0.50–1.47; p = 0.6) and major bleeding (MB; HR 1.47, 95% CI 0.97–2.71; p = 0.07) did not differ between recommended 60 mg and “underdosed” groups, whereas all-cause (HR 1.61, 95% CI 1.23–2.08; p = 0.0003) and cardiovascular deaths (HR 1.61, 95% CI 1.11–2.38; p = 0.01) were higher in the “underdosed” group. Compared with recommended 30 mg, the “overdosed” group had lower IS (HR 0.51, 95% CI 0.28–0.98; p = 0.04) and all-cause death (HR 0.74, 95% CI 0.55–0.98; p = 0.03) without higher MB (HR 0.74, 95% CI 0.46–1.22; p = 0.2). In conclusion: non-recommended dosing was infrequent, but more common near dose-reduction thresholds. “Underdosing” was not associated with better clinical outcomes. The “overdosed” group had lower IS and all-cause death without higher MB.
Distinct Effects of Chemical Toxicity and Radioactivity on Metabolic Heat of Cultured Cells Revealed by “Isotope-Editing”

Studying the toxicity of chemical compounds using isothermal microcalorimetry (IMC), which monitors the metabolic heat from living microorganisms, is a rapidly expanding field. The unprecedented sensitivity of IMC is particularly attractive for studies at low levels of stressors, where lethality-based data are inadequate. We have revealed via IMC the effect of low dose rates from radioactive β−-decay on bacterial metabolism. The low dose rate regime (<400 µGyh−1) is typical of radioactively contaminated environmental sites, where chemical toxicity and radioactivity-mediated effects coexist without a predominance or specific characteristic of either of them. We found that IMC allows distinguishing the two sources of metabolic interference on the basis of “isotope-editing” and advanced thermogram analyses. The stable and radioactive europium isotopes 153Eu and 152Eu, respectively, were employed in monitoring Lactococcus lactis cultures via IMC. β−-emission (electrons) was found to increase initial culture growth by increased nutrient uptake efficiency, which compensates for a reduced maximal cell division rate. Direct adsorption of the radionuclide to the biomass, revealed by mass spectrometry, is critical for both the initial stress response and the “dilution” of radioactivity-mediated damage at later culture stages, which are dominated by the chemical toxicity of Eu.
Quality of Service Generalization using Parallel Turing Integration Paradigm to Support Machine Learning

The Quality-of-Service (QoS) provision in machine learning is affected by lesser accuracy, noise, random error, and weak generalization (ML). The Parallel Turing Integration Paradigm (PTIP) is introduced as a solution to lower accuracy and weak generalization. A logical table (LT) is part of the PTIP and is used to store datasets. The PTIP has elements that enhance classifier learning, enhance 3-D cube logic for security provision, and balance the engineering process of paradigms. The probability weightage function for adding and removing algorithms during the training phase is included in the PTIP. Additionally, it uses local and global error functions to limit overconfidence and underconfidence in learning processes. By utilizing the local gain (LG) and global gain (GG), the optimization of the model’s constituent parts is validated. By blending the sub-algorithms with a new dataset in a foretelling and realistic setting, the PTIP validation is further ensured. A mathematical modeling technique is used to ascertain the efficacy of the proposed PTIP. The results of the testing show that the proposed PTIP obtains lower relative accuracy of 38.76% with error bounds reflection. The lower relative accuracy with low GG is considered good. The PTIP also obtains 70.5% relative accuracy with high GG, which is considered an acceptable accuracy. Moreover, the PTIP gets better accuracy of 99.91% with a 100% fitness factor. Finally, the proposed PTIP is compared with cutting-edge, well-established models and algorithms based on different state-of-the-art parameters (e.g., relative accuracy, accuracy with fitness factor, fitness process, error reduction, and generalization measurement). The results confirm that the proposed PTIP demonstrates better results as compared to contending models and algorithms.
Time-reversal RAP-MUSIC imaging

Time-reversal imaging with the MUltiple SIgnal Classification (MUSIC) method for the location of point targets was first proposed by Devaney et al. In this paper, a recursive time-reversal MUSIC algorithm is proposed. The considered approach is based on the Recursively Applied and Projected (RAP) MUSIC which was first introduced for magnetoencephalographic (MEG) data processing. The main goal of this contribution is to test and study a time-reversal RAP-MUSIC approach for target location and imaging.
Bootstrap study of parameter estimates for nonlinear Richards growth model through genetic algorithm

Richards nonlinear growth model, which is a generalization of the well-known logistic and Gompertz models, generally provides a realistic description of many phenomena. However, this model is very rarely used as it is extremely difficult to fit it by employing nonlinear estimation procedures. To this end, utility of using a very powerful optimization technique of genetic algorithm is advocated. Parametric bootstrap methodology is then used to obtain standard errors of the estimates. Subsequently, bootstrap confidence-intervals are constructed by two methods, viz. the Percentile method, and Bias-corrected and accelerated method. The methodology is illustrated by applying it to India's total annual foodgrain production time-series data.
Crossover from Nearest-Neighbor Hopping Conduction to Efros–Shklovskii Variable-Range Hopping Conduction in Hydrogenated Amorphous Silicon Films

We presented the results of optical and electrical studies of the properties of hydrogenated amorphous silicon (a-Si:H) film which was prepared by hot wire method. Using transmittance measurements, the dielectric constant of the a-Si:H was determined. The temperature-dependent conductivity was measured using the two-point probe method in the temperature range 115–326 K. It was shown that the temperature-dependent conductivity can be well explained by the nearest-neighbor hopping conduction and the Efros–Shklovskii variable-range hopping conduction models. A clear transition from the nearest-neighbor hopping conduction mechanism to the Efros–Shklovskii variable-range hopping conduction mechanism was also observed. The transition between two conduction regimes and characteristic hopping temperatures, as well as the complete set of parameters describing the properties of the localized electrons (the localization length, the hopping energy, the hopping distance, the width of the Coulomb gap, and the value of the density of states at the Fermi level) were determined.
Temperature-induced modulation of stress-tolerant PGP genes bioprospected from Bacillus sp. IHBT-705 associated with saffron (Crocus sativus) rhizosphere: A natural -treasure trove of microbial biostimulants

There is a renewed interest in sustainable agriculture wherein novel plant growth-promoting rhizobacteria (PGPR) are being explored for developing efficient biostimulants. The key requirement of a microbe to qualify as a good candidate for developing a biostimulant is its intrinsic plant growth-promoting (PGP) characteristics. Though numerous studies have been conducted to assess the beneficial effects of PGPRs on plant growth under normal and stressed conditions but not much information is available on the characterization of intrinsic traits of PGPR under stress. Here, we focused on understanding how temperature stress impacts the functionality of key stress tolerant and PGP genes of Bacillus sp. IHBT-705 isolated from the rhizosphere of saffron (Crocus sativus). To undertake the study, Bacillus sp. IHBT-705 was grown under varied temperature regimes, their PGP traits were assessed from very low to very high-temperature range and the expression trend of targeted stress tolerant and PGP genes were analyzed. The results illustrated that Bacillus sp. IHBT-705 is a stress-tolerant PGPR as it survived and multiplied in temperatures ranging from 4°C-50°C, tolerated a wide pH range (5-11), withstood high salinity (8%) and osmolarity (10% PEG). The PGP traits varied under different temperature regimes indicating that temperature influences the functionality of PGP genes. This was further ascertained through whole genome sequencing followed by gene expression analyses wherein certain genes like cspB, cspD, hslO, grpE, rimM, trpA, trpC, trpE, fhuC, fhuD, acrB5 were found to be temperature sensitive while, cold tolerant (nhaX and cspC), heat tolerant (htpX) phosphate solubilization (pstB1), siderophore production (fhuB and fhuG), and root colonization (xerC1 and xerC2) were found to be highly versatile as they could express well both under low and high temperatures. Further, the biostimulant potential was checked through a pot study on rice (Oryza sativa), wherein the application of Bacillus sp. IHBT-705 improved the length of shoots, roots, and number of roots over control. Based on the genetic makeup, stress tolerance potential, retention of PGP traits under stress, and growth-promoting potential, Bacillus sp. IHBT-705 could be considered a good candidate for developing biostimulants.
The lift force on a spherical body in a rotational flow

This paper concerns the flow about a sphere placed in a weak shear flow of an inviscid fluid. The secondary velocity resulting from advection of vorticity by the irrotational component of the flow is computed on the sphere surface, and on the upstream axis. The resulting lift force on the sphere is evaluated, and the result is confirmed by an analytical far-field calculation. The displacement of the stagnation streamline, far upstream of the sphere, is calculated more accurately than in previous papers.
Investigation of Cu Adsorption and Migration with Spectral Induced Polarization in Activated Carbon

In this paper, the adsorption process of copper ions on activated carbon (AC) was simulated in a column test. It was deduced that it is consistent with the pseudo-second-order model. Cation exchange was observed to be the major mechanism of Cu–AC interactions through scanning electron microscopy–energy dispersive X-ray spectroscopy (SEM–EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) measurements. Adsorption isotherms were fitted well using the Freundlich model. Adsorption thermodynamics at 298, 308, 318 K demonstrated that the adsorption process is spontaneous and endothermic. Spectral induced polarization (SIP) technique was used to monitor the adsorption process, and the double Cole–Cole model was used to analyze the SIP results. The normalized chargeability was proportional to the adsorbed copper content. Two measured relaxation times from the SIP testing were converted into the average pore sizes of 2, 0.8, 0.6, 100–110, 80–90, and 53–60 µm by the Schwartz equation, which are consistent with the measured pore sizes from both mercury intrusion porosimetry and scanning electron microscopy (SEM). The reduction in the pore sizes by SIP during the flow-through tests suggested that the adsorbed Cu2+ gradually migrated into small pores as with continued permeation of the influent. These results showcased the feasibility of using SIP technique in engineering practice involving the monitoring of copper contamination in land near a mine waste dump or in adjacent permeable reactive barriers.
The Influence of Metabolic Factors and Diet on Fertility

Infertility is a disease globally affecting 20–30% of the reproductive age female population. However, in up to 50% on recorded cases, problems with infertility are ascribed to men; therefore, it is important to popularize healthy eating also in this group. During the last decade, it has been observed that society’s lifestyle changed drastically: reduced energy expenditure in physical activity per day, increased consumption of hypercaloric and high-glycemic-index foods with high content of trans fats, and reduced consumption of dietary fiber, which negatively affects fertility. Increasing evidence points to a link between diet and fertility. It is becoming clear that well-planned nutrition can also contribute to the effectiveness of ART. The low-GI plant-based diet appears to have a positive effect, especially when it is based on Mediterranean dietary patterns: rich in antioxidants, vegetable protein, fiber, MUFA fatty acids, omega-3, vitamins, and minerals. Importantly, this diet has been shown to protect against chronic diseases associated with oxidative stress, which also translates into pregnancy success. As lifestyle and nutrition seem to be important factors affecting fertility, it is worth expanding knowledge in this regard among couples trying to conceive a child.
Explore the interrelationship of cognition, emotion and interaction when learners engage in online discussion

Online learning community provides abundant semantic text information for investigating learning behaviors. Despite the increasing of learning behavior in higher education, few previous researches have studied online learning from multidimensional behavior. This study mainly explores the interrelationship of cognition, emotion and interaction when learners engage in online discussion. The research object is online discussion textual from a certain course. First, lag sequence analysis is adopted to analyze the dynamic of cognition from the micro perspective, and the relationship between cognition and emotion combined with emotion analysis is investigated. Furthermore, this study proposes the standards of quantifying cognition and emotion from the macro perspective, and the cognition, emotion and interaction are analyzed in a unified framework by using social network analysis. Our findings suggest that: (1) Cognitive level is stable during the learning process, and can be improved by continuous thinking and analysis. (2) Positive emotion plays a significant role in developing higher-level cognition, and its value increases gradually with the improvement of cognition level. (3) Network structure has important influence on individual cognition, who with higher cognitive levels are usually in the center of the network and have larger interaction quality. (4) The learning community with more intensive interactions show higher positive emotion, indicating that emotion transmission is realized by means of network structure. This study might give theoretical and technical supports for helping learners improve the learning quality and efficiency in the online learning.
Ultraviolet interstellar extinction toward 1367 stars observed by ANS

Five-band UV photometry is used to investigate the character of interstellar extinction toward 1367 stars of spectral type B3 and earlier, with observations producing a galactic average of 5.11, 4.78, 6.52, 4.10 and 1.95 at 1550, 1800, 2200, 2500, and 3300 A, respectively. Differences in the strengths of the UV extinction features of these stars appear to be independent, since objects with either strong or weak 2200 A extinction can have strong, normal or weak far-UV extinction. Further investigation reveals that some of the deviant stars are embedded in localized regions whose average extinction curves diverge dramatically from the galactic mean. The anomalous extinction of these regions attests to localized inhomogeneities in the UV characteristics of interstellar dust. Because the evaluation of UV extinction toward a particular star would be more accurate if based on the average curve of the region immediately surrounding that star rather than that of the entire Galaxy, it is recommended that the galactic average presented be used with caution to correct astronomical data of individual objects.
Bench-to-Bedside Studies of Arginine Deprivation in Cancer

Arginine is a semi-essential amino acid which becomes wholly essential in many cancers commonly due to the functional loss of Argininosuccinate Synthetase 1 (ASS1). As arginine is vital for a plethora of cellular processes, its deprivation provides a rationale strategy for combatting arginine-dependent cancers. Here we have focused on pegylated arginine deiminase (ADI-PEG20, pegargiminase)–mediated arginine deprivation therapy from preclinical through to clinical investigation, from monotherapy to combinations with other anticancer therapeutics. The translation of ADI-PEG20 from the first in vitro studies to the first positive phase 3 trial of arginine depletion in cancer is highlighted. Finally, this review discusses how the identification of biomarkers that may denote enhanced sensitivity to ADI-PEG20 beyond ASS1 may be realized in future clinical practice, thus personalising arginine deprivation therapy for patients with cancer.
TLS Protocol Analysis Using IoTST—An IoT Benchmark Based on Scheduler Traces

The Internet of Things (IoT) envisions billions of everyday objects sharing information. As new devices, applications and communication protocols are proposed for the IoT context, their evaluation, comparison, tuning and optimization become crucial and raise the need for a proper benchmark. While edge computing aims to provide network efficiency by distributed computing, this article moves towards sensor nodes in order to explore efficiency in the local processing performed by IoT devices. We present IoTST, a benchmark based on per-processor synchronized stack traces with the isolation and precise determination of the introduced overhead. It produces comparable detailed results and assists in determining the configuration that has the best processing operating point so that energy efficiency can also be considered. On benchmarking applications which involve network communication, the results can be influenced by the constant changes that occur in the state of the network. In order to circumvent such problems, different considerations or assumptions were used in the generalization experiments and the comparison to similar studies. To present IoTST usage on a real problem, we implemented it on a commercial off the-shelf (COTS) device and benchmarked a communication protocol, producing comparable results that are unaffected by the current network state. We evaluated different Transport-Layer Security (TLS) 1.3 handshake cipher suites at different frequencies and with various numbers of cores. Among other results, we could determine that the selection of a specific suite (Curve25519 and RSA) can improve the computation latency by up to four times over the worst suite candidate (P-256 and ECDSA), while both providing the same security level (128 bits).