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Background: Following the remarkable spread of coronavirus disease 2019 (COVID-19), worldwide, it quickly became apparent that many public health systems worldwide were not prepared to manage such a pandemic. We aimed to assess the perceptions of primary care physicians (PCPs) in Jordan toward their role during COVID-19. Methods: A cross-sectional study using a self-administered questionnaire was performed. The study participants included PCPs from the Ministry of Health, academic institutions, and the private sector in Jordan. Results: A total of 221 PCPs participated in the study. Most participants reported not having received any training on infection control (59.7%) or COVID-19 (81%). More than half PCPs (53.4%) felt positive about the way patients received and/or complied with their instructions. More than half PCPs (55.7%) educated their patients on protective measures against COVID-19 infection and considered this as part of their role and responsibility. Over 80% of the participants would apply social distancing, hand sanitation, facial masks, and patient education, but only half (51.1%) reported planning to order COVID-19 test kits. Conclusions: PCPs had a positive attitude toward controlling COVID-19 infection and showed a willingness to educate patients on how to protect themselves. However, PCPs should be provided special training on COVID-19.

Abstract Like other East African countries, Sudan experienced circulation of several SAT2 topotypes. In Sudan, topotype XIII and VII of SAT2 virus were recorded. This work meant to evaluate the impact of such diversity on diagnosis and control. A Sudanese SAT2 foot-and-mouth disease virus (FMDV) of topotype VII originated in 2010 showed poor antigenic relationship (r1 value ≈ 0.00) with Sudanese SAT2 FMDV from 2008 when topotype XIII was circulating. After one or three doses of a vaccine derived from SAT2 virus in 2010, heterologous antibody titres with SAT2 virus in 2008 were ≤ 1.2 log 10, not consistent with likely protection, while homologous titres were 1.65 (after one dose) or 1.95 and 2.55 log10 (after 3 doses). SAT2 positive field sera from Sudan in 2016 were not unvaryingly identified by virus neutralization tests (VNT) employing SAT2 viruses from 2010 and 2008. Proportions of positive sera by SAT2 virus from 2010 were always higher than those by viruses from 2008; consistent with the more frequent and recent circulation of topotype VII prior to 2016. Proportions by SAT2 virus from 2010 were 0.68 (±0.1) in one location (n=72), 0.39 (±0.1) in another one (n=94) and 0.52 (±0.1) in the whole test group (n=166). Corresponding values by viruses of 2008 were 0.53 (±0.1), 0.27 (±0.1) and 0.38 (±0.1). In the whole test group, differences were statistically significant (p=.02339). Like post-vaccination sera, field sera (natural immunity) showed no considerable cross neutralization between topotype VII and presumably XIII; almost 45% (43/96) of SAT2 positive field sera were positive to one topotype but not to the other. Experimental and surveillance findings emphasized the implication of SAT2 diversity in Sudan. It is concluded that it is difficult to control SAT2 infection in Sudan using a monovalent vaccine. Beside a prophylactic vaccine from topotype VII, stockpiling of antigens from topotype XIII and rapid genotyping and matching studies are necessary approaches. When more frequent circulation of more than one topotype occurs, retrospective diagnosis by serological surveys could be problematic or imprecise.

By doubling the target space of a canonical Courant algebroid and subsequently projecting down to a specific subbundle, we identify the data of double field theory (DFT) and hence define its algebroid structure. We specify the properties of the DFT algebroid. We show that one of the Courant algebroid properties plays the role of the strong constraint in the context of DFT. The DFT algebroid is a special example when properties of a Courant algebroid are relaxed in a specific and dependent manner. When otherwise, we uncover additional structures. Comment: 11 pages; proceedings of "Dualities and Generalized Geometries", Corfu Summer Institute 2018. v2: typo corrected, reference added

In this paper we continue studying the decay of unstable FZZT branes initiated in [1],[2]. The mass of tachyonic mode in this model can be chosen arbitrarily small and we use it as a perturbative parameter. In [2] a time-dependent boundary conformal field theory (BCFT) describing the decay process was studied and it was shown that in a certain sense this BCFT interpolates between two stationary BCFT's corresponding to the UV and IR fixed points of the associated RG flow. In the present work we find in the leading order vertex operators of the time-dependent BCFT. We identify the "in" and "out" vertex operators assigned to the UV and IR fixed points and compute the related Bogolyubov coefficients. We show that there is a codimension one subspace of the out-going states for which pair creation amplitudes are independent of the initial wave function of the tachyonic mode. We demonstrate that such amplitudes can be computed within the framework of first quantized open string theory via suitably defined string two-point functions. We also evaluate a three point function which we interpret as an amplitude for string triplet creation due to interaction. Some peculiarities of scattering amplitudes in the presence of tachyonic modes in the far past are discussed. Comment: 1+39 pages, Latex; v.2: minor improvements all over the text

Enzymatic degradation of organic pollutants is a new and promising remediation approach. Peroxidases are one of the most commonly used classes of enzymes to degrade organic pollutants. However, it is generally assumed that all peroxidases behave similarly and produce similar degradation products. In this study, we conducted detailed studies of the degradation of a model aromatic pollutant, Sulforhodamine B dye (SRB dye), using two peroxidases—soybean peroxidase (SBP) and chloroperoxidase (CPO). Our results show that these two related enzymes had different optimum conditions (pH, temperature, H2O2 concentration...etc.) for efficiently degrading SRB dye. High-performance liquid chromatography and LC-mass spectrometry analyses confirmed that both SBP and CPO transformed the SRB dye into low molecular weight intermediates. While most of the intermediates produced by the two enzymes were the same, the CPO treatment produced at least one different intermediate. Furthermore, toxicological evaluation using lettuce (Lactuca sativa) seeds demonstrated that the SBP-based treatment was able to eliminate the phytotoxicity of SRB dye, but the CPO-based treatment did not. Our results show, for the first time, that while both of these related enzymes can be used to efficiently degrade organic pollutants, they have different optimum reaction conditions and may not be equally efficient in detoxification of organic pollutants.

Solar flares - bursts of high-energy radiation responsible for severe space-weather effects - are a consequence of the occasional destabilization of magnetic fields rooted in active regions (ARs). The complexity of AR evolution is a barrier to a comprehensive understanding of flaring processes and accurate prediction. Though machine learning (ML) has been used to improve flare predictions, the potential for revealing precursors and associated physics has been underexploited. Here, we train ML algorithms to classify between vector-magnetic-field observations from flaring ARs, producing at least one M-/X-class flare, and non-flaring ARs. Analysis of magnetic-field observations accurately classified by the machine presents statistical evidence for (1) ARs persisting in flare-productive states --- characterized by AR area --- for days, before and after M- and X-class flare events, (2) systematic pre-flare build-up of free energy in the form of electric currents, suggesting that associated subsurface magnetic field is twisted, (3) intensification of Maxwell stresses in the corona above newly emerging ARs, days before first flares. These results provide new insights into flare physics and improving flare forecasting. Comment: Related code is available at https://github.com/dbdhuri/ML-SolarFlare-Analysis

Abstract Background: This research aims to identify the most common morphology of the upper premolars in a group of local and nonlocal people in the UAE using cone-beam computed tomography (CBCT).Methods: CBCT images of a total of 214 intact maxillary premolars were analysed with 3D reconstruction GALAXIS viewer software. The Pearson Chi squared test and the two samples t test were applied.Results: In all, 90% of the maxillary first premolars had two roots (92% females, 88% males, 83% locals, 96% nonlocals). A total of 52% of maxillary second premolars had two roots (47% females, 56% males, 38% locals, 67% nonlocals). Two cases had three roots among local males. A significant difference of one root in the maxillary second premolar was observed between locals (63%) and nonlocals (33%), while two roots were higher among nonlocals (67%) than locals (37%, p = 0.002). Three roots were discovered in two teeth of the local UAE first premolar. The most common canal morphology in the maxillary first premolar group among local UAE subjects was type V (52%), and among nonlocal UAE subjects was type V (59%). Additional types included 7 (13.2%) identified and unrelated to the Vertucci classification. The dominant canal morphology in the maxillary second premolar among local UAE subjects was type II (32%), and among nonlocal UAE subjects was type V (25%); among the additional types, 12 (23.1%) were identified and not related to the Vertucci classification. There was a significant difference in the distance from the pulp chamber roof to the cementoenamel junction (CEJ) and the measurement between the single-rooted maxillary premolar CBCT for local UAE subjects was 1.36 mm (SD ±0.75) and for nonlocal subjects was 1 mm (SD ±0.27, p = 0.049). There were statistically significant differences in all measurements between multiple rooted maxillary premolar CBCTs for local UAE and South Asian subjects (p < 0.05)Conclusions: The results suggest a more quantitative approach to maxillary first and second premolar access cavity preparation in the UAE population to prevent errors and iatrogenic damage when identifying the canals; using CBCT measurements for more precise access preparations may be advantageous.

AbstractOnly a few studies have assessed the long-term duration of the humoral immune response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).In this nationwide longitudinal study from the Faroe Islands with close to full participation of all individuals on the Islands with PCR confirmed COVID-19 during the two waves of infections in the spring and autumn 2020 (n=172 & n=233), samples were drawn at three longitudinal time points (3, 7 and 12 months and 1, 3 and 7 months after disease onset, respectively).Serum was analyzed with a direct quantitative IgG antibody binding ELISA to detect anti–SARS-CoV-2 spike RBD antibodies and a commercially available qualitative sandwich RBD ELISA kit measuring total antibody binding.The seropositive rate in the convalescent individuals was above 95 % at all sampling time points for both assays. There was an overall decline in IgG titers over time in both waves (p < 0.001). Pairwise comparison showed that IgG declined significantly from the first sample until approximately 7 months in both waves (p < 0.001). After that, the antibody level still declined significantly (p < 0.001), but decelerated with an altered slope remaining fairly stable from 7 months to 12 months after infection. Interestingly, the IgG titers followed a U-shaped curve with higher antibody levels among the oldest (67+) and the youngest (0– 17) age groups compared to intermediate groups (p < 0.001).Our results indicate that COVID-19 convalescent individuals are likely to be protected from reinfection up to 12 months after symptom onset and maybe even longer. We believe our results can add to the understanding of natural immunity and the expected durability of SARS-CoV-2 vaccine immune responses.

We study the effect of spin-phonon coupling in small magnetic clusters, concentrating on a S=1/2 ring of 4 spins coupled antiferromagnetically. If the phonons are treated as classical variables, there is a critical value of the spin-phonon coupling above which a static distortion occurs. This is a good approximation if the zero point energy is small compared to the energy gain due to the distortion, which is true for large exchange interactions compared to the phonons energy ($J\gg\hbar\omega$). In the opposite limit, one can integrate out the phonon degrees of freedom and get an effective spin hamiltonian. Using exact diagonalizations to include the quantum nature of both spins and phonons, we obtain the spectrum in the whole range of parameters and explicit the crossover between the classical and quantum regimes. We then establish quantitatively the limits of validity of two widely used approaches (one in the quantum and one in the classical limits) and show that they are quite poor for small magnetic clusters. We also show that upon reducing $\hbar\omega/J$ the first excitation of a 4-site cluster becomes a singlet, a result that could be relevant for Cu$_2$Te$_2$O$_5$Br$_2$.

The embedding and extraction of useful knowledge is a recent trend in machine learning applications, e.g., to supplement existing datasets that are small. Whilst, as the increasing use of machine learning models in security-critical applications, the embedding and extraction of malicious knowledge are equivalent to the notorious backdoor attack and its defence, respectively. This paper studies the embedding and extraction of knowledge in tree ensemble classifiers, and focuses on knowledge expressible with a generic form of Boolean formulas, e.g., robustness properties and backdoor attacks. For the embedding, it is required to be preservative(the original performance of the classifier is preserved), verifiable(the knowledge can be attested), and stealthy(the embedding cannot be easily detected). To facilitate this, we propose two novel, and effective, embedding algorithms, one of which is for black-box settings and the other for white-box settings.The embedding can be done in PTIME. Beyond the embedding, we develop an algorithm to extract the embedded knowledge, by reducing the problem to be solvable with an SMT (satisfiability modulo theories) solver. While this novel algorithm can successfully extract knowledge, the reduction leads to an NP computation. Therefore, if applying embedding as backdoor attacks and extraction as defence, our results suggest a complexity gap (P vs. NP) between the attack and defence when working with tree ensemble classifiers. We apply our algorithms toa diverse set of datasets to validate our conclusion extensively.