Miracle-dz/UniFAR-FTUs huggingface dataset:
Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study

Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34–74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention.
Application of a Validated RP-HPLC Method in Solubility and Dissolution Testing for Simultaneous Estimation of Diacerein and Its Active Metabolite Rhein in Presence of Coformers in the Eutectic Tablet Formulation.

The present study aimed to develop and validate a novel reversed-phase high-performance liquid chromatography method for simultaneous estimation of Diacerein (DIA) and Rhein (Rh, alkaline degradation product and active metabolite) in the presence of various coformers used to prepare eutectic oral formulation. Chromatographic separations were achieved on a Phenomenex Gemini C18 column (250 mm × 4.6 mm, 5 μm) placed in the thermostated column oven at 40°C. The mobile phase, comprising of acetonitrile and 10 mM ammonium acetate (pH 3.0), was eluted through the gradient system with 0.8 mL/min flow rate at 254 nm detection and analytical run time of 14 min. Additionally, the method was validated for specificity, linearity, precision, accuracy, selectivity, limit of quantitation, limit of detection and robustness as per International Conference on Harmonization guideline. The developed method was applied for the comparison of drug release profiles of pure DIA and from prepared eutectic formulations for the quantitation of DIA and Rh in the multicomponent adducts. The achieved method advocated their applicability in routine quality control analysis of DIA formulations without interference of degraded product and excipients.
In Vitro Tests of FDM 3D-Printed Diclofenac Sodium-Containing Implants

One of the most promising emerging innovations in personalized medication is based on 3D printing technology. For use as authorized medications, 3D-printed products require different in vitro tests, including dissolution and biocompatibility investigations. Our objective was to manufacture implantable drug delivery systems using fused deposition modeling, and in vitro tests were performed for the assessment of these products. Polylactic acid, antibacterial polylactic acid, polyethylene terephthalate glycol, and poly(methyl methacrylate) filaments were selected, and samples with 16, 19, or 22 mm diameters and 0%, 5%, 10%, or 15% infill percentages were produced. The dissolution test was performed by a USP dissolution apparatus 1. A 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide dye (MTT)-based prolonged cytotoxicity test was performed on Caco-2 cells to certify the cytocompatibility properties. The implantable drug delivery systems were characterized by thermogravimetric and heatflow assay, contact angle measurement, scanning electron microscopy, microcomputed tomography, and Raman spectroscopy. Based on our results, it can be stated that the samples are considered nontoxic. The dissolution profiles are influenced by the material properties of the polymers, the diameter, and the infill percentage. Our results confirm the potential of fused deposition modeling (FDM) 3D printing for the manufacturing of different implantable drug delivery systems in personalized medicine and may be applied during surgical interventions.
Diffusion hindrance vs. wood-induced catalytic activation of MUF adhesive polycondensation

The reaction of hardening of melamine–urea–formaldehyde (MUF) adhesive resins in the presence of wood and cellulose was confirmed to have a lower energy of activation than the MUF adhesive alone, both in the presence or absence of ammonium chloride hardener, thus both in mildly acid and mildly alkaline environments. DSC exotherms showed that during hardening of melamine to melamine, melamine to urea, and urea to urea crosslinks through methylene bridges occur. Only the earliest reaction, mainly melamine to melamine crosslinking, presents a decrease in energy of activation which can be assigned to catalytic activation by the cellulosic substrate. The other types of crosslinking reactions (i) appear not to occur due to the more favorable and rapid melamine to melamine reaction which precedes them at lower temperature or (ii) do not present catalytic activation by the substrate but rather hindrance by it or (iii) variation of their energy of activation appears to be due to increased diffusion hindrance by the substrate caused by the increasing molecular weight of the resin while hardening. This because the Kissinger equation plots of the resin alone are in the main linear, for all the exotherms, indicating that in hardening of the resin alone diffusion problems appear to be limited. © 1995 John Wiley & Sons, Inc.
Efficacy of Daptomycin-Containing Regimen for Treatment of Staphylococcal or Enterococcal Vertebral Osteomyelitis: A Prospective Clinical Experience

Vertebral osteomyelitis (VO) is a compelling clinical entity for clinicians, because of its insidious and indolent course that makes diagnosis difficult. A concern is reported about the choice of antibiotic regimens, duration of therapy, and criteria to switch to oral therapy. We conducted a prospective observational study. All consecutive hospitalized patients with a confirmed diagnosis of VO caused by staphylococcal or enterococcal strains were analyzed. The primary endpoint was the analysis of clinical cure at the end of therapy. A propensity score for receiving therapy with daptomycin was added to the model. During the study period, 60 episodes of confirmed VO were observed. The main etiology of infection was methicillin-resistant Staphylococcus aureus (29%). Overall, clinical failure at end of therapy was reported in 11 (18.3%) patients. Logistic regression analysis, after propensity score, showed that >2 vertebrae involved (OR 2.4, CI95% 1.12–5.24, p = 0.002) and inadequate drainage of infection (OR 4.8, CI95% 2.45–8.51, p < 0.001) were independently associated with failure of therapy, while the use of a daptomycin-containing-regimen (OR 0.15, CI 95% 0.04–0.46, p < 0.001) with clinical cure. VO caused by staphylococcal or enterococcal strains is associated with an important rate of clinical failure. Daptomycin-containing regimen was strongly associated with clinical cure. Considering that over 70% of VO etiology is caused by Gram-positive strains but the etiology of infection is obtained in about 75% of cases, these data may help physicians to choose the appropriate antibiotic regimen.
Time Course and Magnitude of Tolerance to the Ergogenic Effect of Caffeine on the Second Ventilatory Threshold

Pre-exercise caffeine ingestion has been shown to increase the workload at ventilatory threshold, suggesting an ergogenic effect of this stimulant on submaximal aerobic exercise. However, the time course of tolerance to the effect of caffeine on ventilatory threshold is unknown. This study aimed to determine the evolution of tolerance to the ergogenic effect of caffeine on the ventilatory threshold. Methods: Eleven participants (age 32.3 ± 4.9 yrs, height 171 ± 8 cm, body mass 66.6 ± 13.6 kg, VO2max = 48.0 ± 3.8 mL/kg/min) took part in a longitudinal, double-blind, placebo-controlled, randomized, crossover experimental design. Each participant took part in two identical treatments: in one treatment, participants ingested a capsule containing 3 mg of caffeine per kg of body mass per day (mg/kg/day) for twenty consecutive days; in the other treatment, participants ingested a capsule filled with a placebo for the same duration and frequency. During these treatments, participants performed a maximal ramp test on a cycle ergometer three times per week and the second ventilatory threshold (VT2) was assessed by using the ventilatory equivalents for oxygen and carbon dioxide. Results: A two-way ANOVA with repeated measures (substance × time) revealed statistically significant main effects of caffeine (p < 0.01) and time (p = 0.04) on the wattage obtained at VT2, although there was no interaction (p = 0.09). In comparison to the placebo, caffeine increased the workload at VT2 on days 1, 4, 6 and 15 of ingestion (p < 0.05). The size of the ergogenic effect of caffeine over the placebo on the workload at VT2 was progressively reduced with the duration of the treatment. In addition, there were main effects of caffeine (p = 0.03) and time (p = 0.16) on VO2 obtained at VT2, with no interaction (p = 0.49). Specifically, caffeine increased oxygen uptake at VT2 on days 1 and 4 (p < 0.05), with no other caffeine–placebo differences afterwards. For heart rate obtained at VT2, there was a main effect of substance (p < 0.01), while the overall effect of time (p = 0.13) and the interaction (p = 0.22) did not reach statistical significance. Heart rate at VT2 was higher with caffeine than with the placebo on days 1 and 4 (p < 0.05). The size of the effect of caffeine on VO2 and heart at VT2 tended to decline over time. Conclusion: Pre-exercise intake of 3 mg/kg/day of caffeine for twenty days enhanced the wattage obtained at VT2 during cycling ramp tests for ~15 days of ingestion, while there was a progressive attenuation of the size of the ergogenic effect of caffeine on this performance variable. Therefore, habituation to caffeine through daily ingestion may reduce the ergogenic effect of this stimulant on aerobic exercise of submaximal intensity.
Sharp Error Estimates on a Stochastic Structure-Preserving Scheme in Computing Effective Diffusivity of 3D Chaotic Flows

In this paper, we study the problem of computing the effective diffusivity for particles moving in chaotic flows. Instead of solving a convection-diffusion type cell problem in the Eulerian formulation (arising from homogenization theory for parabolic equations), we compute the motion of particles in the Lagrangian formulation, which is modeled by stochastic differential equations (SDEs). A robust numerical integrator based on a splitting method was proposed to solve the SDEs and a rigorous error analysis for the numerical integrator was provided using the backward error analysis (BEA) technique [35]. However, the upper bound in the error estimate is not sharp. To improve our result, we propose a new and uniform in time error analysis for the numerical integrator that allows us to get rid of the exponential growth factor in our previous error estimate. Our new error analysis is based on a probabilistic approach, which interprets the solution process generated by our numerical integrator as a Markov process. By exploring the ergodicity of the solution process, we prove the convergence analysis of our method in computing effective diffusivity over infinite time. We present numerical results to verify the accuracy and efficiency of the proposed method in computing effective diffusivity for several chaotic flows, especially the Arnold-Beltrami-Childress (ABC) flow and Kolmogorov flow in three-dimensional space.
Computational Identification of Essential Enzymes as Potential Drug Targets in Shigella flexneri Pathogenesis Using Metabolic Pathway Analysis and Epitope Mapping

Shigella flexneri is a facultative intracellular pathogen that causes bacillary dysentery in humans. Infection with S. flexneri can result in more than a million deaths yearly and most of the victims are children in developing countries. Therefore, identifying novel and unique drug targets against this pathogen is instrumental to overcome the problem of drug resistance to the antibiotics given to patients as the current therapy. In this study, a comparative analysis of the metabolic pathways of the host and pathogen was performed to identify this pathogen’s essential enzymes for the survival and propose potential drug targets. First, we extracted the metabolic pathways of the host, Homo sapiens, and pathogen, S. flexneri, from the KEGG database. Next, we manually compared the pathways to categorize those that were exclusive to the pathogen. Further, all enzymes for the 26 unique pathways were extracted and submitted to the Geptop tool to identify essential enzymes for further screening in determining the feasibility of the therapeutic targets that were predicted and analyzed using PPI network analysis, subcellular localization, druggability testing, gene ontology and epitope mapping. Using these various criteria, we narrowed it down to prioritize 5 novel drug targets against S. flexneri and one vaccine drug targets against all strains of Shigella. Hence, we suggest the identified enzymes as the best putative drug targets for the effective treatment of S. flexneri.
The Vibrio cholerae MARTX toxin simultaneously induces actin collapse while silencing the inflammatory response to cytoskeletal damage

Multifunctional autoprocessing repeats-in-toxin (MARTX) toxins are pore-forming toxins that translocate multiple functionally independent effector domains into a target eukaryotic cell. Vibrio cholerae colonizes intestinal epithelial cells (IECs) and utilizes a MARTX toxin with three effector domains — an actin cross-linking domain (ACD), a Rho inactivation domain (RID), and an α/β hydrolase domain (ABH) — to suppress innate immunity and enhance colonization. We investigated whether these multiple catalytic enzymes delivered from a single toxin function in a coordinated manner to regulate intestinal innate immunity. Using cultured IECs, we demonstrate that ACD-induced cytoskeletal collapse activated ERK, p38, and JNK mitogen-activated protein kinase (MAPK) signaling to elicit a robust proinflammatory response characterized by production of interleukin-8 (IL-8) and expression of CXCL8, TNF, and other proinflammatory genes. However, RID and ABH, which are naturally delivered along with ACD, blocked MAPK activation via Rac1 and thus prevented the ACD-induced inflammation. RID also abolished IL-8 secretion induced by heat-killed bacteria, tumor necrosis factor, and latrunculin A. Thus, MARTX toxins utilize enzymatic multifunctionality to silence the host response to bacterial factors and to the damage it causes. Further, these data show how V. cholerae MARTX toxin suppresses intestinal inflammation and contributes to cholera being classically defined as non-inflammatory diarrheal disease.
A comparison of density functional theory and coupled cluster methods for the calculation of electric dipole polarizability gradients of methane

We have compared the performance of density functional theory (DFT) using five different exchange-correlation functionals with four coupled cluster theory based wave function methods in the calculation of geometrical derivatives of the polarizability tensor of methane. The polarizability gradients of hydrocarbons are important ingredients in the simulation of their electron energy loss spectra and reliable but cost-effective methods for obtaining the gradients need to be found. In the present work we present results of a systematic investigation on methane as a prototype molecule with special focus on DFT methods. The KT3, B3LYP, CAM-B3LYP, B97-2 and PBE0 DFT exchange-correlation functionals and the highly correlated wave function methods SOPPA(CCSD), CCSD-LR, CCSD and CCSD(T) were employed in combination with a series of eleven basis sets. Comparison of the DFT results with CCSD(T)/daug-cc-pVQZ reference values reveals that none of the investigated DFT approaches reaches the accuracy of correlated wave f.
Addressing big data analytics for classification intrusion detection system

Currently, with the rapid developments communication technologies, large number of trustworthy online systems and facilities has been introduced. The cybersecurity is quiet on the rise threat from unauthorized; such security threats can be detected by an intrusion detection system. Thus, enhancing the intrusion detection system is main object of numbers of research and developers for monitoring the network security. Addressing challenges of big data in intrusion detection is one issue faced the researchers and developers due to dimensionality reduction in network data. In this paper, hybrid model is proposed to handle the dimensionality reduction in intrusion detection system. The genetic algorithm was applied as preprocessing steps for selecting most significant features from entire big network dataset. The genetic algorithm was applied to generate subset of relevant features from network data set for handling dimensionality reduction. The Support Vector Machine (SVM) algorithm was processed the relevant features for detecting intrusion. The NSL-KDD standard data was considered to test the performance of the hybrid model. Standard evaluation metrics were employed to presents the results of hybrid model. It is concluded that the empirical results of hybrid outperformed the performance of existing systems.
Calorimetry for Inferential Conversion Monitoring in Emulsion Copolymerization Reactors

A dynamic model was developed describing emulsion copolymerization of styrene and MMA within a batch/semibatch stirred tank reactor. This model includes the initiation, propagation, transfer and termination steps of the monomers styrene and MMA. It also includes the mass and energy balance equations for the polymeric radicals. Energy balance equations incorporate the heat of reaction, internal and external heat transfer effects, as well as heat losses. The resulting sets of (differential/algebraic) equations were solved for both species concentrations and temperature profiles as functions of time. Experiments were conducted in a laboratory reactor, instrumented with platinum resistance thermal transducers and gravimetric conversion measurement devices. Thermal measurements in conjunction with the energy equations helped estimate monomer conversions as a function of time. The kinetic model predictions of conversion compared well with inferential calorimetric measurements, which were validated using gravimetric data. The experiments were run at variable operational conditions in terms of feed rate, temperature and monomers feed ratio. The calorimetric model was used as a soft sensor for the prediction of the rate of reaction, conversion and molar mass.
Organo-metal halide perovskite-based solar cells with CuSCN as inorganic hole selective contact

Please note that technical editing may introduce minor changes to the text and/or graphics, which may alter content. The journal’s standard Terms & Conditions and the Ethical guidelines still apply. In no event shall the Royal Society of Chemistry be held responsible for any errors or omissions in this Accepted Manuscript or any consequences arising from the use of any information it contains. Accepted Manuscript Journal of Materials Chemistry A
The Sliding Frank-Wolfe Algorithm for the BLASSO

This paper showcases the theoretical and numerical performance of the Sliding Frank-Wolfe, which is a novel optimization algorithm to solve the BLASSO sparse spikes super-resolution problem. The BLASSO is a continuous (i.e. off-the-grid or grid-less) counterpart to the well-known 1 sparse regularisation method (also known as LASSO or Basis Pursuit). Our algorithm is a variation on the classical Frank-Wolfe (also known as conditional gradient) which follows a recent trend of interleaving convex optimization updates (corresponding to adding new spikes) with non-convex optimization steps (corresponding to moving the spikes). Our main theoretical result is that this algorithm terminates in a finite number of steps under a mild non-degeneracy hypothesis. We then target applications of this method to several instances of single molecule fluorescence imaging modalities, among which certain approaches rely heavily on the inversion of a Laplace transform. Our second theoretical contribution is the proof of the exact support recovery property of the BLASSO to invert the 1-D Laplace transform in the case of positive spikes. On the numerical side, we conclude this paper with an extensive study of the practical performance of the Sliding Frank-Wolfe on different instantiations of single molecule fluorescence imaging, including convolutive and non-convolutive (Laplace-like) operators. This shows the versatility and superiority of this method with respect to alternative sparse recovery technics.
Excessive Turbidity Removal from Textile Effluents Using Electrocoagulation Technique

The work was conducted for improving textile effluent quality via turbidity removal by electrocoagulation (EC) using aluminum sacrificial electrode. Effluents were treated at 30 minutes and 30 volts (30min-30V) and 60 minutes and 40 volts (60min-40V) condition in a 1000 ml reactor cell with anode distance of 4 cm. Prior to EC experiment, physico-chemical parameters of effluent were measured and turbidity level was found eight times higher than the Department of Environment (DoE) standard. Turbidity removal ranged from 53 to 96.2% and 58 to 97.5% for condition one and two, respectively. Dissolved oxygen (DO) increased satisfactorily for both conditions. Total operational cost ranged from 62.50 to 70.41 taka/m 3 at 30min-30V and 159.57 to 187.7 taka/m 3 at 60min-40V. Moreover, sludge formation ranged from 6.73×10 -4 to 8.41×10 -4 kg in first condition and 1.21×10 -3 to 1.5431×10 -3 kg in second one. So, EC treatment was very effective and capable of elevating quality of the textile wastewater effluent in terms of turbidity to discharge into inland surface water. During EC operation it was also possible to lessen the total cost in maximum removal by changing the operating condition and 30min-30V was enough to get environmental friendly solution. Results will encourage the industry-owner to treat polluted effluents by EC. Keywords: Textile industry; ETP; Electrocoagulation; Sacrificial Electrode; Turbidity; Operational cost. © 2011 JSR Publications. ISSN: 2070-0237 (Print); 2070-0245 (Online). All rights reserved. doi:10.3329/jsr.v3i3. 7533 J. Sci. Res. 3 (3), 567-578 (2011)