Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Defect Cluster Content in Singly and Doubly Doped Ceria through In Situ High-Pressure X-ray Diffraction

Defect aggregates in doped ceria play a crucial role in blocking the movement of oxygen vacancies and hence in reducing ionic conductivity. Nevertheless, evaluation of their amount and the correlation between domain size and transport properties is still an open issue. Data derived from a high-pressure X-ray diffraction investigation performed on the Ce1–x(Nd0.74Tm0.26)xO2–x/2 system are employed to develop a novel approach aimed at evaluating the defect aggregate content; the results are critically discussed in comparison to the ones previously obtained from Sm- and Lu-doped ceria. Defect clusters are present even at the lowest considered x value, and their content increases with increasing x and decreasing rare earth ion (RE3+) size; their amount, distribution, and spatial correlation can be interpreted as a complex interplay between the defects’ binding energy, nucleation rate, and growth rate. The synoptic analysis of data derived from all of the considered systems also suggests that the detection limit of the defects by X-ray diffraction is correlated to the defect size rather than to their amount, and that the vacancies’ flow through the lattice is hindered by defects irrespective of their size and association degree.
Effects of Montessori Education on the Academic, Cognitive, and Social Development of Disadvantaged Preschoolers: A Randomized Controlled Study in the French Public‐School System

Previous research on Montessori preschool education is inconsistent and prone to analytic flexibility. In this preregistered study, disadvantaged preschoolers in a French public school were randomly assigned to either conventional or Montessori classrooms, with the latter being adapted to French public education. Adaptations included fewer materials, shorter work periods, and relatively limited Montessori teacher training. Cross‐sectional analyses in kindergarten (N = 176; M age = 5–6) and longitudinal analyses over the 3 years of preschool (N = 70; M age = 3–6) showed that the adapted Montessori curriculum was associated with outcomes comparable to the conventional curriculum on math, executive functions, and social skills. However, disadvantaged kindergarteners from Montessori classrooms outperformed their peers on reading (d = 0.68). This performance was comparable to that of advantaged children from an accredited Montessori preschool.
Singularity avoidance for manipulators with spherical wrists using the approximate damped reciprocal algorithm

Due to the loss of freedom, the stability and tracking ability of the manipulator around the singularity become worse. This article aims at improving the accuracy of the manipulator and ensuring the stability of the system with the damped reciprocal method. Firstly, the singularities are separated into forearm and wrist singularities to obtain the singular factors of the manipulator respectively. Secondly, a new mathematical function of the approximate damped reciprocal of the singular factor is proposed. Thirdly, the singularities are avoided by modifying the Jacobian matrixes of the manipulator with the approximate damped reciprocal algorithm. Finally, the effectiveness and the stability of the system are proved by the simulations on a manipulator with the spherical wrist. The simulation results prove that this method can largely improve the accuracy of the end-effector and can ensure the stability of the system around the singular region.
Improved simultaneous localization and mapping algorithm combined with semantic segmentation model

In the past decades, emerging technologies such as unmanned driving and indoor navigation have developed rapidly, and simultaneous localization and mapping has played unparalleled roles as core technologies. However, dynamic objects in complex environments will affect the positioning accuracy. In order to reduce the influence of dynamic objects, this article proposes an improved simultaneous localization and mapping algorithm combined with semantic segmentation model. First, in the pre-processing stage, in order to reduce the influence of dynamic features, fully convolutional network model is used to find the dynamic object, and then the output image is masked and fused to obtain the final image without dynamic object features. Second, in the feature-processing stage, three parts are improved to reduce the computing complexity, which are extracting, matching, and eliminating mismatching feature points. Experiments show that the absolute trajectory accuracy in high dynamic scene is improved by 48.58% on average. Meanwhile, the average processing time is also reduced by 21.84%.
Trajectory optimization of an unmanned aerial–aquatic rotorcraft navigating between air and water

Unmanned aerial–aquatic vehicles are a new type of aircraft that can navigate in air and underwater. An unmanned aerial–aquatic rotorcraft (UAAR) is introduced to complete the task of navigating between air and underwater, and the trajectory optimization problem for this task is focused on in this study. The dynamics of a four-axle rotorcraft with eight rotors operating in air and underwater is described. On this basis, the trajectory optimization model is established, wherein the constraints on control variables and states in different media are included. The optimization index is denoted as the weighted sum of the terminal states. In view of the weakness of the teaching- and learning-based optimization (TLBO) algorithm, the formula for updating the individual grade in the teaching process is modified. Thus, this ensures that the algorithm avoids converging at the local optimum and improves the solution quality. Finally, an improved TLBO (ITLBO)-based trajectory optimization method for UAAR navigating between air and water is developed. The control variables are discretized with respect to height at a set of Chebyshev collocation points to reduce the terminal error of states, and the values of control variables at other heights are obtained via interpolation. In the simulation studies, the ITLBO-based method exhibits better performance in terms of optimizing the index when compared to the other two algorithms. Furthermore, the effects of the distribution and number of collocation points on the results are analyzed.
The photodegradation of milled-wood lignin. II: The effect of inhibitors

L'irradiation de la lignine de bois broyee, separee d'une PTM blanchie au peroxyde en presence d'azote, engendre la formation de produits photolytiques de masse moleculaire elevee. Par ailleurs, en presence d'oxygene, la masse moleculaire decroit de 30% par rapport a sa valeur originale, et l'on n'observe aucune evidence de produits de condensation. L'addition du desactivateur d'oxygene par singulet, le diazabicyclooctane (DABCO), dans la solution de lignine de bois broyee et blanchie a reduit l'importance de la decomposition photooxydative. La masse moleculaire se chiffrait a 72% de sa valeur originale en comparaison des 30% observes quand il n'y avait pas eu d'addition de DABCO. Les thiols, connus pour retarder le jaunissement induit par la lumiere dans les papiers contenant de la lignine, ont favorise et non empeche la photodecomposition de la lignine. On etudie ici ces resultats en relation avec les processus de reaction conduisant a la desintegration de la structure macromoleculaire de la lignine.
Implementation of Quantum Key Distribution Protocols

As a wide spectrum of the human activity rapidly transitions to a digital environment, the need for secure and efficient communication intensifies. The currently used public key distribution cryptosystems, such as the Rivest-Shamir-Adleman (RSA) protocol, source their security from the computational difficulty of certain mathematical problems. While widely successful, the security these cryptosystems offer remains heuristic and the development of Quantum computers may render them obsolete. The security that Quantum Key Distribution (QKD) guarantees, stems not from the mathematical complexity of the encryption algorithms but from the laws of Quantum Physics. Implementations of QKD protocols, however, rely on imperfect instruments and devices for information encoding, transmission and detection. Device imperfections limit the rate of information exchange and introduce vulnerabilities which can be exploited by a potential eavesdropper. This work explores practical aspects of QKD as it matures beyond proof-of-principle experiments, focusing on the Measurement Device Independent QKD, a novel Quantum Communication protocol that offers an exceptional balance between security and efficiency. At the heart of the MDI-QKD lies the Hong-Ou-Mandel (HOM) interference which characterizes the indistinguishability of the photon states that the communicating parties independently send. This study examines the HOM interference in a realistic lab environment and concludes that exceptional interference visibility can be achieved using typical commercially available optical devices and detectors, further demonstrating the applicability of the MDI-QKD protocol. An important limiting factor for every Quantum Communication protocol is the transmission medium. Fiber based optical networks suffer significant losses that prohibit Quantum Communication beyond metropolitan scales. While Free Space communication is an attractive alternative for long distance communication, is susceptible to losses due to the atmospheric Turbulence of the channel. As a means to improve the key generation efficiency, this work examines and experimentally demonstrates the Prefixed-Threshold Real Time Selection (P-RTS) scheme, which improves the free-space communication efficiency by rejecting detections that occur while the channel transmittance drops below a predetermined threshold.
Attosecond imaging of molecular dynamics

Since the first observation of high-order harmonic spectra in gases, high harmonic generation (HHG) has demonstrated its importance, opening a door to the field of attosecond sience. The bandwidth of the emitted spectrum reaches up to the XUV. The attosecond pulses reach a very high time resolution, allowing the study of electron dynamics in atoms or molecules. The generation mechanism of HHG is based on the emission of an attosecond electron wavepacket by the atoms/molecules. The electron wavepacket is accelerated by the laser field and finally recombines radiatively with its parent ion. Thus the structural information of the probed orbital is encoded in the high harmonic spectrum with a spatial resolution of one Angtrom and a temporal resolution of few femtoseconds. HHG can be used as a probe signal resolved for pump-probe spectroscopy. High harmonic spectroscopy allows the study of the orbital structure and ultra-fast molecular dynamics. In this thesis the fundamental mechanisms playing a role in atoms, molecules and condensed matter are probed using HHG. In order to understand how to extract dynamical and structural information of orbitals from a harmonic signal, we have first studied an easy and well known system: the argon atom. A new theoretical approach developped by Fabre and Pons allowed us to reproduce the experimental results in good agreement. We continued with a study of the molecular structure and dynamics of N2 and CO2. A supersonic Even-Lavie jet permitted to reach rotational temperatures lower than 10K with an excellent alignment distribution. Owing to the good alignment in such gas jet, we were able to resolve the orbital structure with a higher sensitivity and to identify the contribution of several orbitals. In the next step we used the sensitivity of HHG towards the structure of molecular orbitals in order to probe the complex dynamics of NO2 in the vicinity of a conical intersection. We applied HHG combined with transient grating spectroscopy which leads to a higher sensitivity of the excited molecules. We then continued with studying cluster. We were able to disentangle the contribution of large clusters to the harmonic signal due to a 2D spatio-spectral representation of a temperature dependent differential measurement. Our analysis suggests a new generation mechanism in clusters and allows an estimation of the electron correlation length in clusters. This thesis ends with the presentation of a XUV beamline. This technique uses the emitted fs-XUV radiation, provided by HHG, as a probe pulse for ionizing the photofragments by a one photon transition.
Electrification and Children’s Education: A Cross-Country Analysis

Access to electricity is undoubtedly an essential part of economic and social development in the developing world. For children, electrification can improve education as it enables studies after nightfall and it can help alleviate the burden of household chores. This study adds to the existing literature by using a cross-country approach as well as including test scores to examine the relationship between electrification and educational outcomes, in order to help clarify whether the results found in previous studies are local phenomenon or if they hold at a larger scale. Using OLS fixed-effects regressions based on panel data from the Young Lives survey between 2002 and 2013, focusing on Ethiopia and Peru, we find positive relationships between access to electricity and test scores, school enrollment and time spent in school, while we could not find any statistically significant differences between girls’ and boys’ outcomes. However, our results suggest that mere access to electricity is not enough to raise children’s educational attainment, but that electrification must be combined with other efforts that aim to increase the quality of the education the children receive in school. Supervisor: Heather Congdon Fors
Leveraging Alignment and Phonology for low-resource Indic to English Neural Machine Transliteration

In this paper we present a novel transliteration technique based on Orthographic Syl-lable (OS) segmentation for low-resource Indian languages (ILs) . Given that alignment has produced promising results in Statistical Machine Transliteration systems and phonology plays an important role in transliteration, we introduce a new model which uses alignment representation similar to that of IBM model 3 to pre-process the tokenized input sequence and then use pre-trained source and target OS-embeddings for training. We apply our model for transliteration from ILs to English and report our accuracy based on Top-1 Exact Match. We also compare our accuracy with a previously proposed Phrase-Based model and report improvements.
Mobility Patterns of the Portuguese Population During the First Year of the COVID-19 Pandemic: A Longitudinal Study

This study analyzes the relationship between the spread of the SARS-CoV-2 virus (COVID-19) and the mobility patterns of the Portuguese population. By reducing mobility, the idea is that contacts are reduced, countering the spread of the virus in the community. As an indicator of the spread of the virus, the reproduction number (Rt) was used. Data from Google's Community Mobility Reports was used to evaluate changes in mobility patterns. This report uses location data from Android mobile phone users. The locations are divided into retail and recreation, grocery and pharmacy, parks, transit stations, workplaces and residential. In this year of the COVID-19 crisis in Portugal, population mobility patterns have changed over the various phases of the pandemic. At first, all mobility was affected uniformly, with the population avoiding much of the activity outside the home. In a second phase, there was some adaptation, and the areas considered to be of lower risk had less impact, emphasizing the changes in the relationship between daily life and the workplace.
Adaptive Receiver Window Scaling: Minimizing MPI Communication Memory over InﬁniBand

Commodity clusters are rapidly scaling up to tens-of-thousands of processors. With the increasing scale, providing scalable design and implementation of the Message Passing Interface (MPI) is a challenge. Current generation MPI implementations provide scalable modes of operation, but they lack adaptive mechanisms to dynamically adapt resource consumption as per application requirements. As a result, intimate knowledge of application characteristics is required to minimize resource consumption by the MPI layer. In this paper, we present a mechanism which dynamically adapts resource consumption according to application runtime characteristics enabling the MPI layer to consume only minimum amounts of resources. We evaluate this mechanism in the context of MVAPICH, a high-performance, open-source MPI implementation over InﬁniBand. Experimental evaluation of our proposed design with NAS Parallel Benchmarks and NAMD (apoa1 dataset) reveals that the adaptive mechanism can provide the best available performance while consuming around
Graphene and Graphene Oxide Modified by Deep Eutectic Solvents and Ionic Liquids Supported on Silica as Adsorbents for Solid-Phase Extraction

A novel deep eutectic solvent (DES) and ionic liquid (IL)-modified graphene (G) and graphene oxide (GO) were synthesized and used as effective adsorbents for the preconcentration of three chlorophenols (CPs), 4-chlorophenol (4-CP), 2,4-dichlorophenol (2,4-DCP), and 2,4,6-trichlorophenol (2,4,6-TCP), in environmental water samples prior to high-performance liquid chromatography (HPLC). The new materials were characterized by scanning electron microscopy (S-4200) and Fourier-transform infrared spectrometry. The prepared functionalized GO@silica shows remarkable adsorption capacity toward CPs. When used as solid-phase extraction (SPE) sorbents, a superior recovery (88.49–89.70%) could be obtained compared to commercial sorbents, such as silica and aminosilica. Based on this, a method for the analysis of CPs in water samples was established by coupling SPE with HPLC. These results highlight the potential new role of DES and IL-modified GO in the preparation of analytical samples.
HYPOLIPIDEMIC AND ANTI-OXIDATIVE ACTIVITIES OF TERMINALIA ARJUNA BARKS AGAINST INDUCED HYPERLIPIDEMIC ALBINO RATS

One of the preeminent factors of Coronary heart disease contemplated to be Hyperlipidemia. High cholesterol additives activates hyperlipidemia and Oxidative stress in rats eliciting biochemical and toxicological changes. Traditionally, Terminalia arjuna bark consumed as medicinal agents for various purposes, mainly as cardiac protectives. The present data experiments the influences of Terminalia arjuna ethanolic extract in chow(5% cholesterol+0.5% cholic acid) induced hyperlipidemia rats in compare with free plant additive control group rats. The hyperlipidemia aftermath assessed by evaluating the lipid profile and oxidative stress biomarkers. The test results showed that the Terminalia arjuna bark possessed significant cutback of the cholesterol level, Low density lipoprotein and elevated High density lipoprotein in Hyperlipidemia model rats. Free radicals cut off capabilities of T. arjuna has observed by significantly decreased levels of Malondialdehyde and Superoxide dismutase in induced hyperlipidemia rats. The blood inquiry of all tested groups revealed non-significant alteration by T. arjuna bark extract. The ethanolic extract of Terminalia arjuna bark (500 mg/kg body weight) possessed positive effect on the lipid profile and could serve as good antioxidant agent incorporating into Certain recipes as edible materials hyperlipidemia and high oxidative stress patients as they rely on chemical drugs drugs for too many periods.
Screening for Growth Inhibitory Effects of Medicinal Plants Used in Traditional Korean Medicine in NCI-H1229 Human Lung Cancer Cells

Background: Lung cancer, the most common malignant disease worldwide, is the predominant cause of cancer deaths, particularly amongst men. Therefore, various researchers have focused on the growth inhibitory effects of medicinal plants used in traditional Korean medicine. This study aimed to investigate the growth inhibitory effects of ethanol extracts of Rubiae radix, Inulae flos, Nelumbinis receptaculum, Astilbe radix, and Lagerstroemia flos on NCI-H1229 cells. Method and Results: The viability of NCI-H1229 cells was evaluated in vitro using an MTS assay. Treatment with the ethanol extracts of the selected medicinal plants at 500 μg/ml reduced NCI-H1229 cell viability and increased apoptotic cell death and caspase-3 activation. In addition, treatment with ethanol extracts of Inulae flos and Astilbe radix increases DNA fragmentation, as measured by the TUNEL assay. Conclusions: These results indicated that ethanol extracts of Rubiae radix, Inulae flos, Nelumbinis receptaculum, Astilbe radix, and Lagerstroemia flos exhibited growth inhibitory effects, inducing apoptotic cell death, DNA fragmentation and caspase-3 activation in NCI-H1229 cells. Therefore, these medicinal plant extracts may be used in the development of natural medicines to inhibit the growth of lung cancers. However, further study is needed to determine the active ingredients of the ethanol extracts from medicinal plants that are reposible for the inhibitory effect on lung cancer cell grwoth.
Letter to the Editor Correspondence re: C. F. M. Sieret al., Enhanced Urinary Gelatinase Activities (Matrix Metalloproteinases 2 and 9) Are Associated with Early-Stage Bladder Carcinoma: A Comparison with Clinically Used Tumor

In looking for new urinary markers for bladder cancer (1, 2), an article on MMP-2 and -9 2 published in this journal is of great interest. Using recently introduced commercially available MMP-2 and MMP-9 specific activity assays, Siert al. (3) studied urine MMP-2 and MMP-9 excretion of superficial bladder carcinoma patients compared with patients with high-invasive tumors and healthy controls. The authors found increased concentrations of MMP-2 and MMP-9 in urine of bladder cancer patients. According to their results, urinary MMP-9 was elevated even in the early-stage bladder carcinoma. Because we have carried out similar measurements, we would like to add some comments on their findings to complement the data and conclusions of Sier et al. (3). In our investigation, we used similar activity assays for MMP-2 and MMP-9 (Amersham Pharmacia Biotech, Little Chalfont, United Kingdom; cat. no. RPN 2630 and RPN 2631). In contrast to Sier et al. (3), we measured only the total MMP-2 and MMP-9 and did not distinguish between active and latent forms of both enzymes. The study population included a group of 71 bladder cancer patients, 42 healthy controls, and a group of 14 cystitis patients. MMP values were corrected for urine creatinine concentration. Fig. 1 summarizes the results. The upper reference limits were determined as nonparametric 95% percentiles. The corresponding limits were 3.0 mg/g creatinine for MMP-2 and 9.2mg/g creatinine for MMP-9. In accordance to Sieret al. (3), urinary MMP-2 and MMP-9 were increased in bladder cancer patients compared with controls (Fig. 1). However, our data give additional information that in part differ from the results of Sier t al. (3): (a) in comparison with the controls, MMP-9 excretion was significantly increased in urine of cystitis patients (P , 0.05), whereas MMP-2 was not elevated in these patients (Fig. 1). Sier et al. (3) preferred MMP-9 instead of MMP-2, but, as our data have shown, inflammation should be considered as determinant of increased MMP-9 excretion. ( b) MMP-2 and MMP-9 excretions were mainly elevated in bladder cancer patients with muscle-invasive tumors (stages T2–T4) but not with noninvasive tumors (stages Ta and T1). With regard to the tumor grade, only 1 of 11 patients with tumor grade G1, but 8 of 28 with tumor grade G2, and 16 of 32 with tumor grade G3 showed MMP-2 excretions values above the cutoff. For MMP-9, 3 of 11 patients with G1 tumors, 10 of 28 patients with G2 tumors, and 20 of 32 with G3 tumors had increased excretion rates. In conclusion, we draw the clinician’s attention to these two aspects for utilizing urinary MMPs in bladder cancer diagnosis in order avoid false hopes in these new markers.