Miracle-dz/UniFAR-FTUs huggingface dataset:
Disabled People’s Experiences of the Coronavirus Pandemic: A Call to Action for Social Change

The Coronavirus pandemic has caused significant disruption and change in most aspects of society, and there are concerns that disabled people may be particularly disadvantaged. This article, written by disabled activists and non‐disabled allies, shares data extrapolated from focus groups regarding the lived experiences of twelve disabled people and disability allies during the Covid‐19 pandemic, eleven of whom were based in the UK, and one based in Iraq. We describe the key issues and learning points from this data, arguing that the measures taken by the government and organisations to protect the public during the pandemic have instead brought to the fore long‐standing ableist narratives regarding which bodies are valuable in society. This ableist agenda has acted to control and silence the voices of disabled people by objectifying disability and defining “pre‐existing health conditions” as being more expendable, and therefore less worthy of attention during the pandemic. In presenting our position for change and call to action, we will argue that it is only when disabled people’s experiences and voices are heard in decision‐making that policymakers can begin to learn from the inequalities that have been demonstrated through the pandemic. Here, we will introduce our Wellcome Trust‐funded “We Are the People” Disability Research Collective programme (2021–2026). This programme develops a new disability activist‐led research network, whereby disabled people can conduct research into topics that are important to them.
The Expansion of Consciousness during Mystical Experiences: The Example of Moses

What happens in the brain during meditation? Neuroscientists such as Andrew Newberg, who studies religious experiences on the neural level, may provide an answer. He calls the devolution, which is similar to all mystical experiences in different faiths, self-transcendent experience (STE); in a further instance, he also calls it the feeling of Absolute Unitary Being (AUB). A more detailed consideration of related issues is done by examining the human expansion of consciousness in Islamic mysticism based on an event depicted in the Qurʾān, namely Mosesʾ desire to talk to or see God, his subsequent unconsciousness due to the awe of God, and his subsequent attainment of a new consciousness. The following paper will have a brief look at the case of Moses and aims to investigate the states of consciousness during such experiences. Here, an attempt will be made to trace and prove a connection between neuroscience and the mystical state of the feeling of union with God. In doing so, particular attention will be paid to the state of the encounter between Moses and God. From a neuropsychological point of view, the question will be investigated whether the special spiritual experiences such as those of Moses can be measured, and within this framework, different consciousness models will be presented. Can Newberg’s STE or AUB theory be regarded equally with the fanāʾ state? Finally, which kind of psychological experience is applicable to Moses will be examined.
Effect of replacement of fishmeal by soybean products with attractants supplementation on the growth performance, feed utilization, body composition, plasma physiological responses and hepatic antioxidant abilities of juvenile golden pompano Trachinotus ovatus

A feeding experiment was carried out to develop a practical diet with low fishmeal for juvenile golden pompano (Trachinotus ovatus) by substituting fishmeal protein with soybean products mixture. Six isocaloric (17.6 KJ g−1) diets were designed by replacing 0 (FM100), 5 (FM95), 10 (FM90), 15 (FM85), 20 (FM80), and 25% (FM75) of the fishmeal with soybean products mixture (SPM) (soybean meal and soybean protein concentrate). The experiment diets were supplemented with 1.5%, 3%, 4.5%, 6% and 7.5% squid paste as attractants or palatability enhancer. The experimental fish (6.9 g) were cultured in sea cages (1.0 m × 1.0 m × 1.5 m) with 25 fish in each cage. Fish were fed the corresponding experimental diets to satiation twice daily for 8 weeks. At the end of the feeding experiment, no differences were found in the final weight and weight gain (WG) of fish fed FM100, FM85, FM80, and FM75 diets (P > 0.05). The WG was significantly (P < 0.05) better in the fish-fed FM95 diet compared to FM100 and FM75 diets. FCR in diet FM95 and FM90 was significantly (P < 0.05) than that of FM80 and FM75, but these values were not significantly different from those in other treatments. Although the condition factor value in diets FM90, FM85, and FM80 was significantly (P < 0.05) higher than that of FM100, these values were not significantly different from the rest of the other groups. There was no statistical difference in SGR, FR, VSI, and survival rates among different dietary treatments. The plasma AST activity was significantly lower in fish fed FM90 diet compared to fish fed with control, FM85, FM80, and FM75 (P < 0.05). There was no significant difference in plasma AST among all dietary treatments except FM95 and FM90. In contrast, the plasma AKP activity showed the opposite trend. Compared with the control, the fish-fed FM80 and FM75 diets had significantly decreased plasma cholesterol, triglyceride total protein, albumin, and globulin level (P < 0.05) while significantly increasing plasma COR levels (P < 0.05). There was no significant difference in ALT, Urea and glucose values among all treatments. No statistical difference was observed among the FM100, FM80, and FM75 treatments for those of plasma LYZ activity, C3, and C4 levels. The hepatic T-AOC and SOD activities were significantly increased in fish fed the FM90 diet (P < 0.05) compared to those in fish fed with FM100 diet. According to the current experiment, it can be concluded that SPM supplemented with SP could partially substitute fishmeal (25%) for juvenile golden pompano without any adverse symptoms.
Genomic Transcriptome Benefits and Potential Harms of COVID-19 Vaccines Indicated from Optimized Genomic Biomarkers

COVID-19 vaccines can be the tugboats for preventing SARS-CoV-2 infections when they are practical and, more importantly, without adverse effects. However, the reality is that they may result in short-term or long-term impacts on COVID-19-related diseases and even trigger the formation of new variants of SARS-CoV-2. Using published data, we use a set of optimized-performance COVID-19 genomic biomarkers (MND1, CDC6, ZNF282) to study the benefits and adverse effects of the BNT162b2 vaccine. We found that the vaccine lowered the expression values of genes MND1 and CDC6 while heightening the expression values of ZNF282 in individuals who are SARS-CoV-2 naïve, which is expected and satisfies the biological equivalence between the COVID-19 disease and the genomic signature patterns established in the literature. However, we also found that COVID-19-convalescent octogenarians responded reversely. The vaccine heightened the expression values of MND1 and CDC6. In addition, it lowered the expression values of ZNF282. Such adverse effects raise outstanding concerns about whether or not COVID-19-convalescent individuals should take the current vaccine or when they can take it. These findings are new at the genomic level and can provide insights into developing next-generation vaccines, antiviral drugs, and pandemic management guidance.
AX J1910.7+0917: the slowest X-ray pulsar

Pulsations from the high-mass X-ray binary AX J1910.7+0917 were discovered during Chandra observations performed in 2011. We report here more details on this discovery and discuss the source nature. The period of the X-ray signal is P = 36200 ± 110 s, with a pulsed fraction, PF, of 63 ± 4 per cent. Given the association with a massive B-type companion star, we ascribe this long periodicity to the rotation of the neutron star (NS), making AX J1910.7+0917 the slowest known X-ray pulsar. We also report on the spectroscopy of XMM-Newton observations that serendipitously covered the source field, resulting in a highly absorbed (column density almost reaching 1023 cm-2), power-law X-ray spectrum. The X-ray flux is variable on a time-scale of years, spanning a dynamic range ≳ 60. The very long NS spin period can be explained within a quasi-spherical settling accretion model that applies to low luminosity, wind-fed, X-ray pulsars.
[Solution] Mir-BFT: Scalable and Robust BFT for Decentralized Networks

The paper presents Mir-BTF a Byzantine fault-tolerant total order broadcast system that uses multiple leaders to increase the total throughput. The key contribution of Mir-BTF is the novel hash-based bucketing of requests coupled with leader rotation such that neither request are duplicated nor requests are consistently censored. This allows Mir-BTF to achieves up to 60.000 transactions per second throughput in a deployment of 100 replicas. The reviewers appreciated the simplicity of building Mir-BTF atop PBFT making the protocol easier to be adopted. Mir-BTF is currently under adoption from a major cryptocurrency.
Detection and Risk Analysis with Lane-Changing Decision Algorithms for Autonomous Vehicles

Despite the great technological advances in ADAS, autonomous driving still faces many challenges. Among them is improving decision-making algorithms so that vehicles can make the right decision inspired by human driving. Not only must these decisions ensure the safety of the car occupants and the other road users, but they have to be understandable by them. This article focuses on decision-making algorithms for autonomous vehicles, specifically for lane changing on highways and sub-urban roads. The challenge to overcome is to develop a decision-making algorithm that combines fidelity to human behavior and that is based on machine learning, with a global structure that allows understanding the behavior of the algorithm and that is not opaque such as black box algorithms. To this end, a three-step decision-making method was developed: trajectory prediction of the surrounding vehicles, risk and gain computation associated with the maneuver and based on the predicted trajectories, and finally decision making. For the decision making, three algorithms: decision tree, random forest, and artificial neural network are proposed and compared based on a naturalistic driving database and a driving simulator.
Representing ethical decision-making graphically

Ethical Decision-Making Models (EDMMs) can formalize the course of action through which agents reach their decision-making processes, concerning morals and ethics. The interest in ethical decision-making both from academia and practitioners in Business Computing has increased recently due to the applied computing advances, specially regarding Artificial Intelligence. Research is mainly focused on theoretical models to explain ethical decision-making, factors that influence it or measuring tools to assess it. However, to the best of our knowledge there is an absence of a graphic resource to represent the elements of an EDMM that goes beyond the textual scope. This paper is a first proposal in thinking-making a graphical representation that includes elements of EDMM, enables a more complete information panorama as possible, documents ethical decision-making and facilitates the visualization of these knowledge assets.
The Role of Hidden Conformers in Determination of Conformational Preferences of Mefenamic Acid by NOESY Spectroscopy

Mefenamic acid has been used as a non-steroidal anti-inflammatory drug for a long time. However, its practical use is quite limited due to a number of side effects on the intestinal organs. Conformational polymorphism provides mefenamic acid with unique properties regarding possible modifications obtained during the micronization process, which can improve pharmacokinetics and minimize side effects. Micronization can be performed by decompression of supercritical fluids; methods such as rapid expansion of the supercritical solution have proven their efficiency. However, this group of methods is poorly applicable for compounds with low solubility, and the modification of the method using a pharmaceutically suitable co-solvent may be useful. In our case, addition of only 2 mol% dimethyl sulfoxide increased the solubility remarkably. Information on the conformational state may be critically important for carrying out micronization. In this work, structural analysis and estimate of conformational preferences of mefenamic acid in dimethyl sulfoxide-d6 (at 25 °C and 0.1 MPa) and in a mixed solvent supercritical carbon dioxide + dimethyl sulfoxide-d6 (45 °C, 9 MPa) were performed based on nuclear Overhauser effect spectroscopy. Results show changes in the conformation fractions depending on the medium used. The importance of allowing for hidden conformers in estimating the conformational state was demonstrated in the analysis. Obtained results may be useful for improving micronization parameters.
Gravastars in f(R,T) gravity

We propose a unique stellar model under the $f(R,\mathcal{T})$ gravity by using the conjecture of Mazur-Mottola [P. Mazur and E. Mottola, Report number: LA-UR-01-5067. , P. Mazur and E. Mottola, Proc. Natl. Acad. Sci. USA 101, 9545 (2004)] which is known as gravastar and a viable alternative to the black hole as available in literature. This gravastar is described by the three different regions, viz., (I) Interior core region, (II) Intermediate thin shell, and (III) Exterior spherical region. The pressure within the interior region is equal to the constant negative matter density which provides a repulsive force over the thin spherical shell. This thin shell is assumed to be formed by a fluid of ultra relativistic plasma and the pressure, which is directly proportional to the matter-energy density according to Zel'dovich's conjecture of stiff fluid [Y.B. Zel'dovich, Mon. Not. R. Astron. Soc. 160, 1 (1972)], does counter balance the repulsive force exerted by the interior core region. The exterior spherical region is completely vacuum and assumed to be de Sitter spacetime which can be described by the Schwarzschild solution. Under this specification we find out a set of exact and singularity-free solution of the collapsing star which presents several other physically valid features within the framework of alternative gravity.
Novel doping alternatives for single-layer transition metal dichalcogenides

Successful doping of single-layer transition metal dichalcogenides (TMDs) remains a formidable barrier to their incorporation into a range of technologies. We use density functional theory to study doping of molybdenum and tungsten dichalcogenides with a large fraction of the periodic table. An automated analysis of the energetics, atomic and electronic structure of thousands of calculations results in insightful trends across the periodic table and points out promising dopants to be pursued experimentally. Beyond previously studied cases, our predictions suggest promising substitutional dopants that result in p-type transport and reveal interesting physics behind the substitution of the metal site. Doping with early transition metals (TMs) leads to tensile strain and a significant reduction in the bandgap. The bandgap increases and strain is reduced as the d-states are filled into the mid TMs; these trends reverse as we move into the late TMs. Additionally, the Fermi energy increases monotonously as the .
Computing return times or return periods with rare event algorithms

The average time between two occurrences of the same event, referred to as its return time (or return period), is a useful statistical concept for practical applications. For instance insurances or public agencies may be interested by the return time of a 10 m flood of the Seine river in Paris. However, due to their scarcity, reliably estimating return times for rare events is very difficult using either observational data or direct numerical simulations. For rare events, an estimator for return times can be built from the extrema of the observable on trajectory blocks. Here, we show that this estimator can be improved to remain accurate for return times of the order of the block size. More importantly, we show that this approach can be generalised to estimate return times from numerical algorithms specifically designed to sample rare events. So far those algorithms often compute probabilities, rather than return times. The approach we propose provides a computationally extremely efficient way to estimate numerically the return times of rare events for a dynamical system, gaining several orders of magnitude of computational costs. We illustrate the method on two kinds of observables, instantaneous and time-averaged, using two different rare event algorithms, for a simple stochastic process, the Ornstein–Uhlenbeck process. As an example of realistic applications to complex systems, we finally discuss extreme values of the drag on an object in a turbulent flow.
Clinical Efficacies of FLT3 Inhibitors in Patients with Acute Myeloid Leukemia

FLT3 mutations are the most common genomic alteration detected in acute myeloid leukemia (AML) with a worse clinical prognosis. The highly frequent FLT3 mutations, together with the side effects associated with clinical prognosis, make FLT3 promising treatment targets and have provoked the advancement of FLT3 inhibitors. Recently, numerous FLT3 inhibitors were actively developed, and thus the outcomes of this aggressive subtype of AML were significantly improved. Recently, midostaurin and gilteritinib were approved as frontline treatment of AML and as therapeutic agents in the recurred disease by the United States Food and Drug Administration. Recently, numerous promising clinical trials attempted to seek appropriate management in frontline settings, in relapsed/refractory disease, or after stem cell transplantation in AML. This review follows numerous clinical trials about the usefulness of FLT3 inhibitors as frontline therapy, as relapsed/refractory conditioning, and as maintenance therapy of stem cell transplantation. The cumulative data of FLT3 inhibitors would be important clinical evidence for further management with FLT3 inhibitors in AML patients with FLT3 mutations.
An Improved Online Self-Calibration Method Utilizing Angular Velocity Observation for Ultra High Accuracy PIGA-Based IMU

In the field of ultra high accuracy inertial measurement unit (IMU), pendulous integrating gyroscopic accelerometer (PIGA) has become a research hot spot due to its high-end performance. However, PIGA is sensitive to angular velocity, and the calibration process of PIGA-based IMU will be very complicated, which makes online self-calibration difficult to implement. To solve the above problems, we proposed an online self-calibration method utilizing angular velocity observation. The main contributions of this study are twofold: (1) An error analysis of PIGA is conducted in this paper, and the error model has also been simplified to suit the self-calibration model. (2) An improved online self-calibration method utilizing angular observation based on a simplified PIGA error model is proposed in this study. Experimental results show that the self-calibration method proposed in this study can improve the PIGA online calibration accuracy effectively (with the accuracy within 0.02 m/s/pulse), which can improve the dynamic accuracy of the PIGA.
Detailed Analysis of Nearby Bulgelike Dwarf Stars. I. Stellar Parameters, Kinematics, and Oxygen Abundances

High-resolution échelle spectra were obtained with the Fiber-fed Extended Range Optical Spectrograph at the 1.5 m ESO telescope for 35 nearby bulgelike stars with metallicities in the range -0.8 ≤ [Fe/H] ≤ +0.4. Geneva photometry, astrometric data from Hipparcos, and radial velocities from CORAVEL are available for these stars. From Hipparcos data, it appears that the turnoff of this population indicates an age of 10-11 Gyr (as stated by Grenon in 1999). Detailed analysis of the sample stars is carried out, and atmospheric parameters derived from spectroscopic and photometric determinations are presented. Oxygen abundances are derived based on the forbidden [O I] 6300.3 Å line. The results show an oxygen overabundance pattern for most of the sample stars when compared to their disk counterparts.
Finite Element Modeling for Virtual Design to Miniaturize Medical Implants Manufactured of Nanostructured Titanium with Enhanced Mechanical Performance

The study is aimed to virtually miniaturize medical implants produced of the biocompatible Ti with improved mechanical performance. The results on the simulation-driven design of medical implants fabricated of nanostructured commercially pure Ti with significantly enhanced mechanical properties are presented. The microstructure of initially coarse-grained Ti has been refined to ultrafine grain size by severe plastic deformation. The ultrafine-grained (UFG) Ti exhibits remarkably high static and cyclic strength, allowing to design new dental and surgical implants with miniaturized geometry. The possibilities to reduce the implant dimensions via virtual fatigue tests for the digital twins of two particular medical devices (a dental implant and a maxillofacial surgery plate) are explored with the help of finite element modeling. Additionally, the effect of variation in loading direction and the fixation methods for the tested implants are studied in order to investigate the sensitivity of the fatigue test results to the testing conditions. It is shown that the UFG materials are promising for the design of a new generation of medical products.
Data-driven deconvolution for large eddy simulations of Kraichnan turbulence

In this article, we demonstrate the use of artificial neural networks as optimal maps which are utilized for convolution and deconvolution of coarse-grained fields to account for sub-grid scale turbulence effects. We demonstrate that an effective eddy-viscosity is predicted by our purely data-driven large eddy simulation framework without explicit utilization of phenomenological arguments. In addition, our data-driven framework precludes the knowledge of true sub-grid stress information during the training phase due to its focus on estimating an effective filter and its inverse so that grid-resolved variables may be related to direct numerical simulation data statistically. The proposed predictive framework is also combined with a statistical truncation mechanism for ensuring numerical realizability in an explicit formulation. Through this, we seek to unite structural and functional modeling strategies for modeling non-linear partial differential equations using reduced degrees of freedom. Both a priori and a posteriori results are shown for a two-dimensional decaying turbulence case in addition to a detailed description of validation and testing. A hyperparameter sensitivity study also shows that the proposed dual network framework simplifies learning complexity and is viable with exceedingly simple network architectures. Our findings indicate that the proposed framework approximates a robust and stable sub-grid closure which compares favorably to the Smagorinsky and Leith hypotheses for capturing the theoretical k−3 scaling in Kraichnan turbulence.In this article, we demonstrate the use of artificial neural networks as optimal maps which are utilized for convolution and deconvolution of coarse-grained fields to account for sub-grid scale turbulence effects. We demonstrate that an effective eddy-viscosity is predicted by our purely data-driven large eddy simulation framework without explicit utilization of phenomenological arguments. In addition, our data-driven framework precludes the knowledge of true sub-grid stress information during the training phase due to its focus on estimating an effective filter and its inverse so that grid-resolved variables may be related to direct numerical simulation data statistically. The proposed predictive framework is also combined with a statistical truncation mechanism for ensuring numerical realizability in an explicit formulation. Through this, we seek to unite structural and functional modeling strategies for modeling non-linear partial differential equations using reduced degrees of freedom. Both a priori a.