Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical Control of Superlattices States Formed Due to Electronic Phase Separation in Multiferroic Eu0.8Ce0.2Mn2O5

The effect of optical pumping and magnetic field on properties of the electronic phase separation regions, which are the multiferroic semiconductor heterostructures in the form of superlattices, have been studied in Eu0.8Ce0. 2Mn2O5. These superlattices are formed due to self-organization in a dielectric crystal matrix as a result of the competing internal interactions balance and occupy a small crystal volume. The dynamical equilibrium states of superlattices are initially formed during cycling of as-grown samples in a magnetic field. The superlattices in such states are ferromagnetic and electrically neutral. Sets of ferromagnetic resonances were observed from individual layers of superlattices. Their features give rise information on properties of these layers and of a superlattice as a whole. The differences in the parameters of these resonances were due to different distributions of Mn3+ and Mn4+ ions in individual superlattices layers. It has been found that optical pumping having different powers allows us to control of multiferroic properties of superlattices layers by changing their magnetic and electric properties. It is shown that, under certain conditions, it is possible to significantly increase the temperatures at which multiferroic heterostructures exist.
CLEP_A_288046 273..285

1Biostatistics and Bioinformatics (DIM), University Hospital, Dijon, France; 2Bourgogne Franche-Comté University, Dijon, France; 3Inserm, CIC 1432, Dijon, France; 4Clinical Investigation Center, Clinical Epidemiology/Clinical Trials Unit, Dijon University Hospital, Dijon, France; 5Department of Gynecology and Obstetrics, Hospital Felix Guyon, CHU La Reunion, France; 6EA 7285, Versailles Saint Quentin University, Versailles, France; 7The Department of Obstetrics and Gynecology, Poissy-Saint Germain Hospital, Poissy, France; 8High-Dimensional Biostatistics for Drug Safety and Genomics, CESP, Inserm, Université Paris-Saclay, UVSQ, Univ. ParisSud, Villejuif, France Purpose: To analyze the socio-residential factors associated with extremely and very preterm deliveries occurring in non-level 3 maternity units in France. Materials and Methods: This is a population-based observational retrospective study using national hospital data from 2012 to 2014. A generalized estimating equations regression model was used to study the characteristics of women who delivered very preterm and the socio-residential risk factors for not delivering in a level 3 maternity unit at 24–31+6d weeks of gestation. Results: Among deliveries resulting in live births and without contraindication to in-utero transfer, we identified 9198 extremely or very preterm deliveries; 2122 (23.1%) of these were managed in a non-level 3 unit. Our study showed that young maternal age (women under 20 years at delivery) was associated with the risk of giving birth prematurely in a non-level 3 maternity, and particularly in a level 1 maternity unit (adjusted relative risk, 1.53; 95% CI 1.09–2.16). Living more than 30 minutes away from the closest level 3 unit increased the risk of delivering very preterm in a level 1 or 2 unit. Living in an urban area or urban periphery increased the risk of giving birth in a level 2 maternity unit (adjusted relative risk, 1.53; 95% CI 1.28–1.83 and 1.42; 95% CI 1.17–1.71, respectively). Conclusion: This study shows that young pregnant women living more than 30 minutes from a level 3 hospital have an increased risk of delivering in a maternity unit that is not equipped to deal with premature births. The risk also increases with an urban place of residence when the delivery occurs in a level 2 unit. A clearer understanding of the population at risk of delivering prematurely in a non-level 3 maternity could lead to improvements in structuring healthcare to encourage earlier management and better support.
Smartphone-Based Inertial Odometry for Blind Walkers

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.
Unpacking Underperformance: Learning Mindsets and the Challenge of Academic Achievement Among Filipino Students

The 2018 PISA report revealed that 71.8 percent of participating students from the Philippines have failed to reach minimum basic learning thresholds, raising doubts about the state of education in the country. While most East Asian economies lead the world in terms of their significant share of high-performing students, Filipino students are critically left behind by their peers. Before the PISA, the discourse on policies surrounding educational improvement processes lacked a strong evidence base, mainly due to the absence of a robust learner-centered evaluation mechanism. In addition, despite prior discussions on how the Philippines suffers from systemic issues of access and equity, learners’ characteristics and backgrounds were rarely considered. <br><br>To contribute to the policy discussions, we unpack the primary sources of inequalities in science, mathematics, and reading achievement using the PISA data. We also explored how performance is construed by factors such as learners’ backgrounds, learning mindsets (such as the implicit beliefs about intelligence, i.e., growth vs. fixed mindset beliefs), reading difficulties, and other self-reported characteristics. Our results indicate that (1) inequalities are highly persistent among regions, between public and private schools; (2) significant gains in academic achievement are contingent on the interaction between students’ socioeconomic backgrounds and the possession of a growth mindset. However, the associated positive effect of growth mindset on test scores interacts only among higher-SES students and not among students with lower-SES. Further, (3) reading difficulties are prevalent among Filipino students, which are comorbid with science and mathematics achievement. Lastly, (4) students with a history of repetition are severely disadvantaged, particularly males from public schools. <br><br>The paper contributes to the literature on the determinants of academic achievement through a large-scale assessment framework. Several actionable policy insights related to learning mindsets are also presented in the paper, particularly improving the curriculum and intensifying teacher training. Thus, the education sector needs to strategically commit to long-term education quality goals to prevent the otherwise late detection of learning comorbidities among Filipino students.
Flexible SAW Microfluidic Devices as Wearable pH Sensors Based on ZnO Nanoparticles

In this work, a new flexible and biocompatible microfluidic pH sensor based on surface acoustic waves (SAWs) is presented. The device consists of polyethylene naphthalate (PEN) as a flexible substrate on which aluminum nitride (AlN) has been deposited as a piezoelectric material. The fabrication of suitable interdigitated transducers (IDTs) generates Lamb waves (L-SAW) with a center frequency ≈500 MHz traveling in the active region. A SU-8 microfluidics employing ZnO nanoparticles (NPs) functionalization as a pH-sensitive layer is fabricated between the IDTs, causing a shift in the L-SAW resonance frequency as a function of the change in pH values. The obtained sensitivity of ≈30 kHz/pH from pH 7 to pH 2 demonstrates the high potential of flexible SAW devices to be used in the measurement of pH in fluids and biosensing.
Antibody Response to Pertussis Vaccination in Pregnant and Non-Pregnant Women—The Role of Sex Hormones

Pertussis containing vaccine is recommended for pregnant women to protect neonates prior to being fully immunized against the disease. The immune response during pregnancy may be impacted by changes in the hormonal status. The aim of this study was to evaluate the immune response to pertussis immunization in pregnancy and to assess the role of sex hormones. In a cross-sectional study, blood samples were drawn from 174 pregnant and 74 non-pregnant women 45–60 days following immunization. Anti-pertussis toxin (Anti-PT) IgG antibody levels, estrogen, and progestogen concentrations were compared between the two groups. Multiple logistic regression analysis was used to examine the association between serum antibody and sex hormone concentrations in each group, controlling for age, body mass index (BMI), and smoking status. The geometric mean concentration (GMC) of anti-PT IgG antibody was significantly higher in non-pregnant women compared with pregnant women (median of 2.09 and 1.86, interquartile range = 2.36–1.8 and 2.11–1.16 respectively, p < 0.0001). Among pregnant women, the anti-PT IgG antibody GMC was negatively associated with both progesterone (odds ratio = 0.300, 95% CI = 0.116, 0.772, p = 0.013) and estrogen (odds ratio = 0.071, 95% CI = 0.017, 0.292, p < 0.0001), after controlling for age, BMI, and smoking. Pregnancy was associated with lower anti-PT IgG antibody levels (odds ratio = 0.413, 95% CI = −0.190, 0.899, p = 0.026). This appears to be at least partially explained by the higher levels of hormones during pregnancy. These findings demonstrate the important role of sex hormones in the response to pertussis vaccine during pregnancy and can help to evaluate the optimum vaccination schedule.
Development of an Age-Appropriate Mini Orally Disintegrating Carvedilol Tablet with Paediatric Biopharmaceutical Considerations

Owing to considerable differences observed in anatomy and physiology between paediatric subsets, it has been well established that children respond to drugs differently compared to adults. Furthermore, from a formulation perspective, there is a distinct challenge to develop a dosage form that is capable of safely, accurately, and reliably delivering the dose across the whole paediatric population. Orally disintegrating mini-tablets (ODMT) have widely been considered as an age-appropriate formulation option that possess the ability for adequate dose flexibility, avoids swallowing difficulties, and exhibits superior stability due to its solid state. Within this study, two strengths (0.5 mg and 2 mg) of carvedilol ODMT formulations were developed using an excipient composition and load that is appropriate for paediatric use. The formulations demonstrated adequate mechanical strength (>20 N) and fast disintegration times (<30 s). Dissolution profiles observed were robust and comparable to the marketed conventional tablet formulation across various parts of the gastrointestinal (GI) tract in both the fed and fasted state, signifying appropriate efficacy, quality, and performance. As such, the formulations developed in this study show potential to address the need of an ‘age-appropriate’ formulation of carvedilol, as highlighted by the European Medicines Agency (EMA) Inventory of the Needs for Paediatric Medicine.
Comparative Metabolic Profiling of Grape Pulp during the Growth Process Reveals Systematic Influences under Root Restriction

The compositions and contents of metabolites in the pulp tissue play critical roles in the fruit quality for table grape. In this study, the effects of root restriction (RR) on the primary and secondary metabolites of pulp tissue at five developmental stages were studied at the metabolomics level, using “Red Alexandria” grape berry (Vitis vinifera L.) as materials. The main results were as follows: 283 metabolites were annotated by using ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS); 28 and 16 primary metabolites contents were increased and decreased, and 11 and 19 secondary metabolites contents were increased and decreased, respectively, along the berry development; RR significantly decreased 12 metabolites (four amino acids and derivatives, three organic acids, four flavonoids and one other compound) contents, and improved 40 metabolites (22 amino acids and derivatives, six nucleotides, four carbohydrates, four cofactors, three cinnamic acids and one other compound) accumulation at the different developmental stages. Altogether, our study would be helpful to increase our understanding of grape berry’s responses to RR stress.
Temperature Effect of Water Coagulation Bath on Chitin Fiber Prepared through Wet-Spinning Process

Chitin was chemically extracted from crab shell waste and dissolved in N,N-dimethyl acetamine/5% lithium chloride (DMAc/5% LiCl) at room temperature to obtain 1% and 2% concentrations of chitin solution. Chitin fibers were prepared by phase inversion at different temperatures of water coagulation bath at 5, 20, and 60 °C. The deconvolution of FTIR spectra indicated that the area portion of the intermolecular hydrogen bonding NH…OC increased at 60 °C due to the higher density of the chitin segment in the fiber. As a result, scanning electron microscope (SEM) measurement suggests that a denser structure of the chitin fiber was observed when the temperature of the coagulation bath increased. In addition, the resultant chitin fibers generated better mechanical properties relative to the amount of chitin concentration and temperature. At 2% of chitin solution, the tensile strength significantly increased from 80 to 182 MPa for the fiber obtained at temperatures of 5 and 60 °C of the water coagulation bath, respectively. Meanwhile, the water content in the fiber significantly decreased from 1101% to 335%. This green synthesis route has high potential for the fabrication of the fiber as future material of interest for biomedical application.
Biological Effects of Bioresorbable Materials in Alveolar Ridge Augmentation: Comparison of Early and Slow Resorbing Osteosynthesis Materials

The purpose of this study was to investigate the bone healing properties and histological environment of a u-HA/PLLA/PGA (u-HA—uncalcined and unsintered hydroxyapatite, PLLA—Poly L-lactic acid, PGA—polyglycolic acid) composite device in humans, and to understand the histological dynamics of using this device for maxillofacial treatments. Twenty-one subjects underwent pre-implant maxillary alveolar ridge augmentation with mandibular cortical bone blocks using u-HA/PLLA or u-HA/PLLA/PGA screws for fixation. Six months later, specimens of these screws and their adjacent tissue were retrieved. A histological and immunohistochemical evaluation of these samples was performed using collagen 1a, ALP (alkaline phosphatase), and osteocalcin. We observed that alveolar bone augmentation was successful for all of the subjects. Upon histological evaluation, the u-HA/PLLA screws had merged with the bone components, and the bone was directly connected to the biomaterial. In contrast, direct bone connection was not observed for the u-HA/PLLA/PGA screw. Immunohistological findings showed that in the u-HA/PLLA group, collagen 1a was positive for fibers that penetrated vertically into the bone. Alkaline phosphatase was positive only in the u-HA/PLLA stroma, and the stroma was negative for osteocalcin. In this study, u-HA/PLLA showed a greater bioactive bone conductivity than u-HA/PLLA/PGA and a higher biocompatibility for direct bone attachment. Furthermore, u-HA/PLLA was shown to have the potential for bone formation in the stroma.
Effective Communication at Different Phases of COVID-19 Prevention: Roles, Enablers and Barriers

In an age of globalisation and hyperconnectivity, the COVID-19 pandemic has caused unprecedented and sustained impact worldwide. This article discusses issues related to (science) communication at different phases of the COVID-19 epidemic timeline. We consider the role of communication for prevention from the ecological perspective, taking into consideration that many emerging pathogens, including COVID-19, likely arise in part due to anthropogenic changes to natural environments. Communication forms part of the early response setting the scene for public buy-in of public health interventions at the start of an outbreak, as well as to maintain precautions over time. Finally, communication is a key element in increasing acceptance for new tools that require mass uptake to be effective, as seen with roll-out challenges for the COVID-19 vaccines, which faced heightened concerns of efficacy and safety while mired with rampant misinformation. Ultimately, strategies for prevention of viral epidemics such as COVID-19 must include communication strategies at the forefront to reduce the risk of the emergence of new diseases and enhance efforts to control their spread and burden. Despite key themes emerging, what constitutes effective communication strategies for different people and contexts needs to be investigated further.
PPGTempStitch: A MATLAB Toolbox for Augmenting Annotated Photoplethsmogram Signals

An annotated photoplethysmogram (PPG) is required when evaluating PPG algorithms that have been developed to detect the onset and systolic peaks of PPG waveforms. However, few publicly accessible PPG datasets exist in which the onset and systolic peaks of the waveforms are annotated. Therefore, this study developed a MATLAB toolbox that stitches predetermined annotated PPGs in a random manner to generate a long, annotated PPG signal. With this toolbox, any combination of four annotated PPG templates that represent regular, irregular, fast rhythm, and noisy PPG waveforms can be stitched together to generate a long, annotated PPG. Furthermore, this toolbox can simulate real-life PPG signals by introducing different noise levels and PPG waveforms. The toolbox can implement two stitching methods: one based on the systolic peak and the other on the onset. Additionally, cubic spline interpolation is used to smooth the waveform around the stitching point, and a skewness index is used as a signal quality index to select the final signal output based on the stitching method used. The developed toolbox is free and open-source software, and a graphical user interface is provided. The method of synthesizing by stitching introduced in this paper is a data augmentation strategy that can help researchers significantly increase the size and diversity of annotated PPG signals available for training and testing different feature extraction algorithms.
A Single-Trial P300 Detector Based on Symbolized EEG and Autoencoded-(1D)CNN to Improve ITR Performance in BCIs

In this paper, we propose a breakthrough single-trial P300 detector that maximizes the information translate rate (ITR) of the brain–computer interface (BCI), keeping high recognition accuracy performance. The architecture, designed to improve the portability of the algorithm, demonstrated full implementability on a dedicated embedded platform. The proposed P300 detector is based on the combination of a novel pre-processing stage based on the EEG signals symbolization and an autoencoded convolutional neural network (CNN). The proposed system acquires data from only six EEG channels; thus, it treats them with a low-complexity preprocessing stage including baseline correction, windsorizing and symbolization. The symbolized EEG signals are then sent to an autoencoder model to emphasize those temporal features that can be meaningful for the following CNN stage. This latter consists of a seven-layer CNN, including a 1D convolutional layer and three dense ones. Two datasets have been analyzed to assess the algorithm performance: one from a P300 speller application in BCI competition III data and one from self-collected data during a fluid prototype car driving experiment. Experimental results on the P300 speller dataset showed that the proposed method achieves an average ITR (on two subjects) of 16.83 bits/min, outperforming by +5.75 bits/min the state-of-the-art for this parameter. Jointly with the speed increase, the recognition performance returned disruptive results in terms of the harmonic mean of precision and recall (F1-Score), which achieve 51.78 ± 6.24%. The same method used in the prototype car driving led to an ITR of ~33 bit/min with an F1-Score of 70.00% in a single-trial P300 detection context, allowing fluid usage of the BCI for driving purposes. The realized network has been validated on an STM32L4 microcontroller target, for complexity and implementation assessment. The implementation showed an overall resource occupation of 5.57% of the total available ROM, ~3% of the available RAM, requiring less than 3.5 ms to provide the classification outcome.
Sarcoma Metabolomics: Current Horizons and Future Perspectives

The vast array of metabolic adaptations that cancer cells are capable of assuming, not only support their biosynthetic activity, but also fulfill their bioenergetic demands and keep their intracellular reduction–oxidation (redox) balance. Spotlight has recently been placed on the energy metabolism reprogramming strategies employed by cancer cells to proliferate. Knowledge regarding soft tissue and bone sarcomas metabolome is relatively sparse. Further characterization of sarcoma metabolic landscape may pave the way for diagnostic refinement and new therapeutic target identification, with benefit to sarcoma patients. This review covers the state-of-the-art knowledge on cancer metabolomics and explores in detail the most recent evidence on soft tissue and bone sarcoma metabolomics.
Envelope Proteins of Hepatitis B Virus: Molecular Biology and Involvement in Carcinogenesis

The envelope of hepatitis B virus (HBV), which is required for the entry to hepatocytes, consists of a lipid bilayer derived from hepatocyte and HBV envelope proteins, large/middle/small hepatitis B surface antigen (L/M/SHBs). The mechanisms and host factors for the envelope formation in the hepatocytes are being revealed. HBV-infected hepatocytes release a large amount of subviral particles (SVPs) containing L/M/SHBs that facilitate escape from the immune system. Recently, novel drugs inhibiting the functions of the viral envelope and those inhibiting the release of SVPs have been reported. LHBs that accumulate in ER is considered to promote carcinogenesis and, especially, deletion mutants in the preS1/S2 domain have been reported to be associated with the development of hepatocellular carcinoma (HCC). In this review, we summarize recent reports on the findings regarding the biological characteristics of HBV envelope proteins, their involvement in HCC development and new agents targeting the envelope.