Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydroxyl-functionalized Graphene from Spent Batteries as Efficient Adsorbent for Amoxicillin

A chemically exfoliated graphene, functionalized with hydroxide, was prepared and used as an adsorbent for the removal of amoxicillin from aqueous solutions. This nanocomposite was recovered from chemically exfoliated graphite rods present in spent zinc-carbon batteries. The graphene-OH was determined to have a sheet-like morphology with high surface area (As,BET = 181 m2 g-1) . Its adsorption characteristics were observed at different adsorption time, initial amoxicillin concentrations, and adsorbent dosage to establish the kinetics, isotherm, and optimal adsorption conditions. Pseudo-first-order and pseudo-second-order models were used to study the kinetics, while Freundlich and Langmuir models were used to study the adsorption isotherms. Results showed that amoxicillin adsorption fitted with Langmuir isotherm with higher correlation than the Freundlich isotherm and followed the pseudo-second-order rate model. The removal efficiency increased as the adsorbent dosage was also increased. Similarly, increasing the adsorbent dosage from 1 g/L to 20 g/L, the adsorption capacity decreased from 36 mg/g to 4 mg/g. For recyclability, the adsorptivity of graphene – OH was shown to be slightly decreasing over the 5-cycles (99.75 % to 95.37 %). Based on the results, hydroxyl-functionalized graphene demonstrated high industrial potential for amoxicillin wastewater treatment.
Learning 3D Medical Image Patch Descriptors with the Triplet Loss

Computational anatomy focuses on the analysis of the human anatomical variability. Typical applications are the discovery of differences across healthy and sick subjects and the classification of anomalies. A fundamental tool in computational anatomy, which forms the central focus of this paper, is the computation of point correspondences across volumes (3D images) such as Computed Tomography (CT) volumes, for multiple subjects. More specifically, we consider automatically detected keypoints and their local descriptors, computed from the image or volume patch surrounding each keypoint. Theses descriptors are essential because they must be discriminant and repeatable [5,10]. Learned descriptors based on Convolutional Neural Networks (CNN) have recently shown great success for 2D images [4]. However, while classical 2D image descriptors were extended to volumes [8], recent CNN based approaches were not. We propose a methodology to construct these learned volume keypoint descriptors. The main difficulty is to define a sound training approach, combining a training dataset and a loss function. In short, we propose to generate semi-synthetic data by transforming real volumes and to use a triplet loss inspired by 2D descriptor learning. Our experimental results show that our learned descriptor outperforms the hand-crafted descriptor 3D-SURF [1], a 3D extension of SURF, with similar runtime.
2 7 M ay 2 02 1 Symplectic quantization II : dynamics of space-time quantum fluctuations and the cosmological constant

The symplectic quantization scheme proposed for matter scalar fields in the companion paper [1] is generalized here to the case of space-time quantum fluctuations. That is, we present a new formalism to frame the quantum gravity problem. Inspired by the stochastic quantization approach to gravity, symplectic quantization considers an explicit dependence of the metric tensor gμν on an additional time variable, named intrinsic time at variance with the coordinate time of relativity, from which it is different. The physical meaning of intrinsic time, which is truly a parameter and not a coordinate, is to label the sequence of gμν quantum fluctuations at a given point of the four-dimensional space-time continuum. For this reason symplectic quantization necessarily incorporates a new degree of freedom, the derivative ġμν of the metric field with respect to intrinsic time, corresponding to the conjugated momentum πμν . Our proposal is to describe the quantum fluctuations of gravity by means of a symplectic dynamics generated by a generalized action functional A[gμν , πμν ] = K[gμν , πμν ]−S[gμν ], playing formally the role of a Hamilton function, where S[gμν ] is the standard Einstein-Hilbert action while K[gμν , πμν ] is a new term including the kinetic degrees of freedom of the field. Such an action allows us to define an ensemble for the quantum fluctuations of gμν analogous to the microcanonical one in statistical mechanics, with the only difference that in the present case one has conservation of the generalized action A[gμν , πμν ] and not of energy. Since the Einstein-Hilbert action S[gμν ] plays the role of a potential term in the new pseudo-Hamiltonian formalism, it can fluctuate along the symplectic action-preserving dynamics. These fluctuations are the quantum fluctuations of gμν . Finally, we show how the standard path-integral approach to gravity can be obtained as an approximation of the symplectic quantization approach. By doing so we explain how the integration over the conjugated momentum field πμν gives rise to a cosmological constant term in the path-integral approach.
Generalized Reflection Method for the Stokes Equation in Confined Geometries: Applications To Microfluidics and Particle Transport

A generalized reflection method is proposed for determining the hydrodynamic resistance matrix of a rigid particle translating in a confined Stokesian fluid, by reducing its estimate to the solution of two simpler problems: (i) the singular expansion of the hydrodynamic variables due to the particle motion in the free space, represented by the Faxén operator associated with the particle geometry, and (ii) the determination of the Green function associated with the specific channel geometry. This approach extends the Stokeslet approximation to a Faxén approximation that is reliable to ratios of the particles characteristic length to the characteristic distance from the walls higher than the existing literature approximations, the error of which is order of O /d . Given the solution of the two above mentioned subproblems, the proposed method applies to any particle and channel geometry. The application to prolate spheroidal particles translating parallel to a plane is discussed and compared against numerical simulations.
O ct 2 00 9 NSF-KITP-09-110 Holography from Conformal Field Theory

The locality of bulk physics at distances below the AdS length scale is one of the remarkable aspects of AdS/CFT duality, and one of the least tested. It requires that the AdS radius be large compared to the Planck length and the string length. In the CFT this implies a large-N expansion and a gap in the spectum of anomalous dimensions. We conjecture that the implication also runs in the other direction, so that any CFT with a large-N expansion and a large gap has a local bulk dual. For an abstract CFT we formulate the consistency conditions, most notably crossing symmetry, and show that the conjecture is true in a broad range of CFT’s, to first nontrivial order in 1/N2: in any CFT with a gap and a large-N expansion, the four-point correlator is generated via the AdS/CFT dictionary from a local bulk interaction. We establish this result by a counting argument on each side, and also investigate various properties of some explicit solutions.
Application of acute stroke imaging Selecting patients for revascularization therapy

Due to the dynamic and versatile characteristics of ischemic penumbra, selecting the right acute ischemic stroke (AIS) patients for revascularization therapy (RT) based on initial available imaging can be challenging. The main patient selection criterion for RT is the size of the mismatch between the potentially salvageable tissue (penumbra) and the irreversibly damaged tissue (core). The goal of revascularization RT is to “freeze” the core and prevent it from extending to the penumbral tissue. Penumbral imaging selection of AIS patients for RT, using magnetic resonance or CTbased studies, may provide more clinical benefit to the appropriate patients, although direct evidence is pending. Not all penumbra-core mismatches beyond 3 hours are equal and need treatment, and defining which mismatches to target for RT is the current goal of ongoing clinical trials. In addition to “penumbral”-based imaging, large vessel occlusion and clot length estimation based on CT angiography and noncontrasted ultrathin CT scan has been used to identify patients who are refractory to systemic thrombolysis and may be eligible for endovascular therapy. The application of various imaging modalities in selecting and triaging AIS patients for RT is discussed in this review. Larger prospective randomized trials are needed to better understand the role of various imaging modalities in selecting AIS patients for RT and to understand its influence on clinical outcome. Neurology 2012;79 (Suppl 1):S86–S94
Where Can I Fi Nd out More?

lines and the cost of culture maintenance is lower than that for fl owering plants and most animal models. In addition, the easily controllable transition from vegetative to sexual reproduction enables forward genetic studies. Marchantia is amenable to mutagenesis, and there is ample genetic diversity for genetic mapping. In contrast to most fl owering plant species, Marchantia is amenable to homologous recombination with high effi ciency. Specifi c fl uorescent proteins and selectable markers have been engineered. Transgenic haploid lines can be produced in four to six weeks, and genome editing has been implemented with CRISPR/Cas9. These features, along with its small, non-duplicated genome and predominantly haploid lifestyle , make Marchantia a tremendously effi cient model for functional studies. Several aspects of Marchantia make this species suitable for cell biology studies, including some transparent cell types and the availability of fl uorescent markers. As some cells acquire distinct polarity or motility, Marchantia is a good model for the study of cytoskeleton-related processes. The chromosome number is moderate (n = 8 + X or Y), and the availability of haploid and diploid cells without the complexity of endoreduplication make Marchantia ideal for studies of cell cycle and meiosis. Why is Marchantia useful for investigating land plant evolution? Earth remained devoid of land plants until about 470 mya. The fi rst traces of land plant evolution are spores resembling those produced by extant liverworts. From a common ancestor, the paraphyletic bryophytes evolved in a grade comprising liverworts, mosses, and hornworts. Molecular phylogenies combined with the fossil record support the idea that liverworts were the fi rst land plants. The order Marchantiopsida is one of the most ancient among liverworts, and Marchantia retains most characteristics of fossils from the Jurassic (200 mya). The specifi c evolutionary position of liverworts makes this group suitable for studying the origins of land plant traits. Marchantia also provides a key link between other plant basal species with a sequenced genome, the fi lamentous charophycean alga Klebsormidium fl accidum, the moss Physcomitrella patens, and the hornwort Anthoceros agrestis. The complexity of the Marchantia genome is much reduced compared with fl owering plants, thus simplifying the process to study the function of transcription and signaling factors. It is expected that Marchantia will provide knowledge of prototypic transcriptional networks that enabled the acquisition of new developmental and physiological traits that led to the colonization of land. Auxin produced by the …
Towards the Superdictionary: Layers, Tools and Unidirectional Meaning Relations

We report on the ongoing project of developing the Ekilex dictionary writing system and joining existing dictionaries into the EKI Combined Dictionary. To facilitate the joining, several tools have been developed to solve data quality issues and turn textual data into structured entities. The resulting superdictionary thus contains various sets of information, which we call layers, either transformed from existing dictionaries or authored already in Ekilex. Our current focus is on the layers for synonyms and equivalents, which we describe in terms of their data model, lexicographic processes and lexicographer feedback from the first six months of Ekilex in production. As it turns out, the layer system may need expanding to accommodate an ever-growing list of requirements. The unidirectional data model for synonyms fully conforms to its design specification and received favourable first impressions, but extended use has started to cast doubt on the optimality of the model. We describe the pros and cons of this model and possible alternatives.
Psychological Impact of the COVID-19 Pandemic on Palestinian Nursing Students: A Cross-Sectional Study

Introduction: The COVID-19 pandemic became a global pandemic in early 2020. The pandemic has many impacts on people’s live posing a threat to their physical and mental health. Therefore, this study aimed to assess the psychological impact of COVID-19 pandemic on Palestinian nursing students residing in the Gaza Strip, Palestine. Materials and Methods: A convenience sample of 345 nursing students from the Islamic University of Gaza completed on line questionnaire packet that included demographic data and the 7-item Generalized Anxiety Disorder Scale (GAD-7). Results: Results from this study revealed that most of our participants were females (79.1%), single (82.3%), not working (90.4%) and having no chronic disease (94.8%). Variant levels of anxiety were reported by participants with 34.5% of them having mild, 31% moderate and 19.1% severe levels of anxiety. Levels of anxiety reported in this study were not impact by any study variables such as age, sex, study year, etc. Conclusions and Implications for Practice: The results of this study revealed high levels of anxiety among nursing students. The closure of the universities, the new experience of e-learning along with the multi-stressors already prevailing in the Gaza Strip have contributed to this high level of anxiety. Universities and the health care system in the Gaza Strip should pay attention to reduce anxiety levels among students. This could be approached by providing online training courses or setting channels of one-to-one online or phone counseling for students to alleviate negative psychological effects and to enhance mental health of students.
Scrutinizing Taxpayer Perceptions on the Service Quality of Income Tax Services: An Application of SERVPREF Model

Income tax revenue assortment management is more crucial to every economy as tax is the prime source of revenue for the government that necessitates quality service while collecting tax from tax payers. Income taxpayer perception on service quality has become a perilous element in measuring the quality of Income-tax services. The SERVPREF model of measurement for tax payers’ perception was used to test service quality of tax services in Bangladesh and to study taxpayer’s understanding on the level of quality service being offered and examining predictors of service quality in respect to items and dimensions such as tangibles, reliability, responsiveness, empathy, and assurance of SERVPREF model. A survey was conducted on a total of 120 income taxpayers to determine the perceived quality and the study revealed both positive and negative relationships among dimensions of the model. In particular, the most negative correlation was found between tangibles and significant correlation among responsiveness, awareness, and empathy of taxpayers’ satisfaction on service quality. Assessment and Measurement Model under SMART-PLS imply that almost all dimensions of SERVPREF are the significant predictor for high levels of overall service quality. The findings of the study indicate that awareness, responsiveness and empathy are significantly related to satisfaction of taxpayers but tangibility is insignificant to the satisfaction of taxpayers. The result of the study provides a momentous urge for further research in this field that may help National Board of Revenue (NBR) to make effective central policy, brings positive motivation for taxpayers to submit tax return, as well as might contribute high revenue earning for the economy.
Shape from Sky: Polarimetric Normal Recovery Under The Sky

The sky exhibits a unique spatial polarization pattern by scattering the unpolarized sun light. Just like insects use this unique angular pattern to navigate, we use it to map pixels to directions on the sky. That is, we show that the unique polarization pattern encoded in the polarimetric appearance of an object captured under the sky can be decoded to reveal the surface normal at each pixel. We derive a polarimetric reflection model of a diffuse plus mirror surface lit by the sun and a clear sky. This model is used to recover the per-pixel surface normal of an object from a single polarimetric image or from multiple polarimetric images captured under the sky at different times of the day. We experimentally evaluate the accuracy of our shape-from-sky method on a number of real objects of different surface compositions. The results clearly show that this passive approach to fine-geometry recovery that fully leverages the unique illumination made by nature is a viable option for 3D sensing. With the advent of quad-Bayer polarization chips, we believe the implications of our method span a wide range of domains.
Epidemiological Profile of Premature Newborns Monitored at the Kangaroo Unit at Sikasso Hospital

The objective of this study was to determine the epidemiological profile of preterm infants followed at the Kangaroo Unit. Patients and Methods: This was a descriptive cross-sectional study carried out in the Pediatrics Department of Sikasso hospital (Mali), a second-reference hospital from 1 January 2019 to 31 December 2019 on a comprehensive sample of all preterm infants followed at the unit during the study period. Results: We collected 94 files out of 194, a frequency of 48.4%. The average age of mothers was 28.5 years and 92, 5% were married, the out-of-school represented 51%. Housewives were the majority with 78.8% and living in urban communities in 70.2%. Primigest accounted for 37.2% of cases; 62.7% of women had completed at least four antenatal consultations. Malaria was found in 38.2% of pathologies during pregnancy. In 73.4% of the cases the newborns were born from a vaginal birth and 54.2% from birth in the born. The sex ratio is 1.5 and average gestational age is 31 SA. The average weight was 1325g. 40% of newborns were successfully followed up to 12 months of corrected age, sight loss was 21.2% and 40.4% were outstanding follow-up, we recorded 7 deaths or 7.4%. From 3 months to 12 months of corrected age all infants had an average weight located within WHO standard standards. Conclusion: The management of premature babies remains a major challenge for the pediatric services of our hospitals.
PREVALENCE AND INCIDENCE OF ANTIBODIES AGAINST SARS-COV-2 AMONG PRIMARY HEALTHCARE PROVIDERS IN BELGIUM DURING ONE YEAR OF THE COVID-19 EPIDEMIC: PROSPECTIVE COHORT STUDY PROTOCOL

Introduction National severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence data provides essential information about population exposure to the virus and helps predict the future course of the epidemic. Early cohort studies have suggested declines in levels of antibodies in individuals, associated with, for example, illness severity, age and co-morbidities. This protocol focuses on the seroprevalence among primary health care providers (PHCPs) in Belgium. They manage the vast majority of COVID-19 patients in addition to other patients and therefore play an essential role in the efficient organisation of health care. Currently, evidence is lacking on 1. how many PHCPs get infected with SARS-CoV-2 in Belgium, 2. the rate at which this happens, 3. their clinical spectrum, 4. their risk factors, 5. the effectiveness of the measures to prevent infection and 6. the accuracy of the serology-based point-of-care test in a primary care setting. Methods and analysis This study will be set up as a prospective cohort study. General practitioners (GPs) and other PHCPs (working in a GP practice) will be recruited via professional networks and professional media outlets to register online to participate. Registered GPs and other PHCPs will be asked at each testing point (n=9) to perform a capillary blood sample antibody point-of-care test (OrientGene) and complete an online questionnaire. The primary outcomes are the prevalence and incidence of antibodies against SARS-CoV-2 in PHCPs during a 12-month follow-up period. Secondary outcomes include the longevity of antibodies against SARS-CoV-2. Ethics and dissemination: Ethical approval has been granted by the Ethics Committee of the University Hospital Antwerp/University of Antwerp (Belgian registration number: 3002020000237). Alongside journal publications, dissemination activities include the publication of monthly reports to be shared with the participants and the general population through the publicly available website of the Belgian health authorities (Sciensano).
Simultaneous Removal of Soot and NOx over the (La1.7Rb0.3CuO4)x/nmCeO2 Nanocomposite Catalysts

Nanometric CeO2-supported perovskite-liked La1.7Rb0. 3CuO4 oxide catalysts with different loading amounts were obtained by the method of ultrasonic-assisted incipient-wetness impregnation. All of the catalysts were calcined at 700 °C for 6 h and characterized by means of BET, XRD, IR, and UV−vis−NIR. These materials were tested for the simultaneous removal of NOx and soot in the temperature range from 200 to 600 °C. As compared to nanometric CeO2 support particles (nmCeO2) or pure La1.7Rb0. 3CuO4 perovskite-liked catalyst, the catalytic activities of all of the supported catalysts were remarkably enhanced. The temperatures for soot combustion of Tm decreased and the productivities of N2 increased, and the activities of the catalysts increased with the perovskite-liked oxide loading amount. On the basis of in situ DRIFT characterization, NO oxidation, and O2-TPD results, a reaction mechanism for the simultaneous removal of NOx and soot over (La1.7Rb0.3CuO4)x/nmCeO2 was proposed.
An Energy-Efficient Stress Monitoring System Using Physiological Data

— Anxiety is your body's natural response to stress. People with anxiety disorders frequently have intense, excessive and persistent worry and fear about everyday situations. As we know stress is the main cause of long-term health disorder, Stress management is so necessary to maintain an individual's stress levels keep down and able to reduce health risks. In this article, we are finding out some measures and methods through which we employ low-cost wearable sensors collection of data and machine learning algorithms to predict an individual's stress level so as to manage his stress level. Researchers have found out that stress levels can also be detected using physiological tests such as pulse rate, heart rate amplitude and skin infections or skin diseases. This research paper' main aim is to offer a necessary analysis of various kinds of stress detection and to find out different methods to overcome it as well as a reliable checklist for more effective stress detection.