Miracle-dz/UniFAR-FTUs huggingface dataset:
Attitudes and perceptions of teachers toward mental health literacy: A case of Odzi High School, Mutare District, Zimbabwe

In dealing with adolescent mental health, teachers and school institutions have a critical role in minimizing the challenges of mental health. However, the success of such a measure is dependent on teachers’ attitudes and perceptions of mental health literacy. Adolescent mental health disorders have become a major global concern with heightened increases and prevalence in secondary schools. In Zimbabwe, a dearth of knowledge exists in understanding the perceptions and attitudes of teachers in maximizing student mental health and positive educational outcomes. The aim of the research was to understand the attitudes and perceptions of teachers toward mental health literacy. Using a qualitative approach to understanding attitudes and perceptions, a case study was carried out at Odzi High School. A total of 12 teachers were purposively sampled for data generation on knowledge, attitudes, perceptions, and strategies that can be used to inform adolescent mental health. Data were collected using semi-structured interview(s). Emergent themes of the study were knowledge, stigma, training, and development. Using thematic analysis, the data showed that there was generalized knowledge of mental health and there were disparities in effective and efficient responses to gender sensitivity issues. Additionally, this knowledge was not put into practice because of attitudes and perceptions toward mental health. Recommendations from the study include developing of mental health training for teachers, equipping teachers with skills in psychosocial support in schools’ mental health, and enabling teachers to be able to link adolescents to appropriate care within the school and community-based settings. Teachers have the responsibility of promoting the wellbeing of the students, thus minimizing the adverse effects. Outcomes for positive mental health may be the result of teachers’ informed perceptions and positive attitudes on mental health literacy.
Bioassay-guided isolation of Fenghuang Dancong tea constituents with α-glucosidase inhibition activities

An α-glucosidase inhibition assay showed the ethanolic extract of Fenghuang Dancong tea had potential α-glucosidase inhibitory activity. The most bioactive fraction, which was obtained via bioassay-guided isolation of the extract, was further purified to create five compounds, including three novel compounds (1–3). These compounds were analyzed and identified in detail using high-resolution-mass spectrometry and extensive one-dimensional and two-dimensional NMR spectroscopy experiments. Among the compounds, compound 1 contained cis double bonds and showed the strongest α-glucosidase inhibitory activity with an IC50 value of 7.51 μM, which is significantly lower than that of compound 2 with trans double bonds. Enzyme kinetic experiments showed that 1 was a reversible non-competitive α-glucosidase inhibitor.
Research on application of tumor treating fields in glioblastoma: A bibliometric and visual analysis

Background Glioblastoma, one of the common tumors of the central nervous system (CNS), is prone to recurrence even after standard treatment protocols. As an innovative physiotherapy method emerging in recent years, the tumor treating fields (TTFields) technique has been approved for the treatment of glioblastoma due to its non-invasive and portable features. The purpose of this study is to visualize and analyze the scientific results and research trends in TTFields therapy for glioblastoma. Methods Publications related to TTFields therapy for glioblastoma were searched in the Web of Science Core Collection (WoSCC) database in September 2022. A bibliometric and visual analysis of publications in this field was performed mainly using CiteSpace and R software for country/region, author, journal, reference and keyword. Results A total of 618 publications in this field were retrieved, and 248 were finally obtained according to the search criteria, including 159 articles (64.11%) and 89 reviews (37.89%). The cumulative number of publications increased year by year, with an average growth rate (AGR) of 28.50%. The test results of Pearson correlation coefficient showed a high positive correlation between publications and citations (r=0.937, p<0.001). The USA had the largest number of publications (123, 49.60%), followed by Germany (32, 12.90%) and China (30, 12.10%). As for the country/region collaborations, the USA cooperated most closely with other countries/regions, followed by Germany and China. The degree of collaboration (DC) between countries/regions was 25.81%. The institutions with the largest number of publications were Tel Aviv Univ (10), Harvard Med Sch (10) and Novocure Ltd (10). Moreover, Wong E (18) possessed the greatest number of publications, followed by Weinberg U (11) and Kirson E (10). The DC between authors was 97.58%. STUPP R (236) was the most cited author followed by KIRSON ED (164) and GILADI M (104). JOURNAL OF NEURO-ONCOLOGY (22) was the journal with the largest number of published publications (75), followed by FRONTIERS IN ONCOLOGY (15) and CANCERS (13). The top 10 keywords that occurred frequently included glioblastoma (156), tumor treating field (152), temozolomide (134), randomized phase III (48), brain (46), survivor (46), cancer (44), trial (42), alternating electric field (42) and radiotherapy (36). Furthermore, cluster analysis was performed on the basis of keyword co-occurrence, and finally 15 clusters were formed to determine the current research status and future development trend of TTFields therapy for glioblastoma. Conclusion TTFields has been increasingly known as the fourth novel physical anti-tumor therapy in addition to surgery, radiotherapy and anti-tumor drugs. Cooperation and communication between countries/regions need to be enhanced in future research. Several studies have demonstrated the therapeutic potential of TTFields in glioma, and its application alone or in combination with other treatments has become a current research hotspot.
Magnetization reversal condition for a nanomagnet within a rotating magnetic field

The reversal condition of magnetization in a nanomagnet under the effect of rotating magnetic field generated by a microwave is theoretically studied based on the Landau-Lifshitz-Gilbert equation. In a rotating frame, the microwave produces a dc magnetic field pointing in the reversed direction, which energetically stabilizes the reversed state. We find that the microwave simultaneously produces a torque preventing the reversal. It is pointed out that this torque leads to a jump in the reversal field with respect to the frequency. We derive the equations determining the reversal fields in both the low- and high-frequency regions from the energy balance equation. The validities of the formulas are confirmed by a comparison with the numerical simulation of the Landau-Lifshitz-Gilbert equation.
DUST PROPERTIES IN THE AFTERGLOW OF GRB 071025 AT z ∼ 5

At high redshift, the universe is so young that core-collapse supernovae (SNe) are suspected to be the dominant source of dust production. However, some observations indicate that the dust production by SNe is an inefficient process, casting doubts on the existence of abundant SNe-dust in the early universe. Recently, Perley et al. reported that the afterglow of GRB 071025—an unusually red gamma-ray burst (GRB) at z ∼ 5—shows evidence for SNe-produced dust. Since this is perhaps the only high-redshift GRB exhibiting compelling evidence for SNe-dust but the result could easily be affected by small systematics in photometry, we re-examined the extinction properties of GRB 071025 using our own optical/near-infrared data at a different epoch. In addition, we tested SNe-dust models with different progenitor masses and dust destruction efficiencies to constrain the dust formation mechanisms. By searching for the best-fit model of the afterglow spectral energy distribution, we confirm the previous claim that the dust in GRB 071025 is most likely to originate from SNe. We also find that the SNe-dust model of 13 or 25 M☉ without dust destruction fits the extinction property of GRB 071025 best, while pair-instability SNe models with a 170 M☉ progenitor poorly fit the data. Our results indicate that, at least in some systems at high redshift, SNe with intermediate initial masses within 10–30 M☉ were the main contributors for the dust enrichment, and the dust destruction effect due to reverse shock was negligible.
Oxygen abundance maps of CALIFA galaxies

We construct maps of the oxygen abundance distribution across the disks of 88 galaxies using CALIFA data release 2 (DR2) spectra. The position of the center of a galaxy (coordinates on the plate) were also taken from the CALIFA DR2. The galaxy inclination, the position angle of the major axis, and the optical radius were determined from the analysis of the surface brightnesses in the SDSS $g$ and $r$ bands of the photometric maps of SDSS data release 9. We explore the global azimuthal abundance asymmetry in the disks of the CALIFA galaxies and the presence of a break in the radial oxygen abundance distribution. We found that there is no significant global azimuthal asymmetry for our sample of galaxies, i.e., the asymmetry is small, usually lower than 0.05 dex. The scatter in oxygen abundances around the abundance gradient has a comparable value, $\lesssim 0.05$ dex. A significant (possibly dominant) fraction of the asymmetry can be attributed to the uncertainties in the geometrical parameters of these galaxies. There is evidence for a flattening of the radial abundance gradient in the central part of 18 galaxies. We also estimated the geometric parameters (coordinates of the center, the galaxy inclination and the position angle of the major axis) of our galaxies from the analysis of the abundance map. The photometry-map-based and the abundance-map-based geometrical parameters are relatively close to each other for the majority of the galaxies but the discrepancy is large for a few galaxies with a flat radial abundance gradient.
On Reward Binarisation and Bayesian Agents

Reward binarisation is a common heuristically applied technique which can potentially simplify a given reinforcement learning problem. However this procedure done without care can modify the original problem, or throw away essential information. In this paper we study a number of natural forms of reward binarisation, and characterise their effects in terms of problem expressivity. We show positive results for MDPs, POMDPs, and k -order MDPs and a negative result for general history based reinforcement learning agents. Furthermore we show that binary Bayesian reinforcement learning agents enjoy convergence properties similar to their non-binarised counterparts.
OpenMP scheduling on ARM big.LITTLE architecture

Single-ISA heterogeneous multicore systems are emerging as a promising direction to achieve a more suitable balance between performance and energy consumption. However, a proper utilization of these architectures is essential to reach the energy bene(cid:12)ts. In this paper, we demonstrate the ineﬀectiveness of popular OpenMP scheduling policies executing Rodinia benchmark on the Exynos 5 Octa (5422) SoC, which integrates the ARM big.LITTLE architecture.
New Constructions of Existential Unforgeable Aggregate Signature Scheme from CSP

In future, hundreds of years of mathematical problems that the security of public key cryptography algorithms rely on may be defeated by quantum algorithms. How can a digital signature scheme gracefully balance security and efciency? Tis study uses the conjugate search problem and the left self-distributive system to combine and uses the RSA-like algorithm as the underlying structure to propose a new aggregated signature scheme. We, through the EUF game, under the random metaphor model, prove that the security of the scheme satisfes the adaptation unforgeability under selective message attack, the scheme can be fnally reduced to the discrete logarithm problem or large prime number decomposition problem. In addition, we can achieve anti-quantum attack and exhaustive attack by performing matrix calculations on the message, defning and changing the structure of the matrix by encoding, and setting thresholds for the matrix dimension and the length of the private key. In terms of efciency, the message signature implementation is linear compared with the expansion rate in terms of storage and computing overhead, and the generation and verifcation of the fnal signature pair have nothing to do with the number of users. In addition, the length of the signature is fxed and the size is only the length of a single group, which efectively reduces the generation of public and private key pairs and saves a lot of storage space. Te storage space and computational complexity are also efectively improved compared with other solutions.
Edinburgh Research Explorer Regularization or lexical probability-matching? How German speakers generalize plural morphology

Artificial language learning research has shown that, under some conditions, adult speakers tend to probability-match to inconsistent variation in their input, while in others, they regularize by reducing that variation. We demonstrate that this framework can characterize speaker behavior in a natural-language morphological inflection task: the lexicon can be used to estimate variation in speaker productions. In the task of German plural inflection, we find that speakers probability-match a lexical distribution conditioned on phonology, and largely disregard an alternative possible strategy of conditional regularization based on grammatical gender.
Grad's Moment Method for a Low-Density Granular Gas. Navier-Stokes Transport Coefficients

The Navier-Stokes transport coefficients for a granular gas of smooth inelastic hard disks or spheres are determined from the inelastic Boltzmann equation by means of Grad's moment method. The shear viscosity $\eta$, the thermal conductivity $\kappa$ and the new transport coefficient $\mu$ (not present for elastic collisions) are explicitly obtained as nonlinear functions of the (constant) coefficient of restitution $\alpha$. The expressions of $\eta$, $\kappa$, and $\mu$ agree with those previously obtained from the Chapman-Enskog method by using the first Sonine approximation. A comparison with previous results derived from Grad's moment method for two and three dimensions is also carried out.
THE SYSTEMATICS OF STRONG LENS MODELING QUANTIFIED: THE EFFECTS OF CONSTRAINT SELECTION AND REDSHIFT INFORMATION ON MAGNIFICATION, MASS, AND MULTIPLE IMAGE PREDICTABILITY

Until now, systematic errors in strong gravitational lens modeling have been acknowledged but have never been fully quantified. Here, we launch an investigation into the systematics induced by constraint selection. We model the simulated cluster Ares 362 times using random selections of image systems with and without spectroscopic redshifts and quantify the systematics using several diagnostics: image predictability, accuracy of model-predicted redshifts, enclosed mass, and magnification. We find that for models with >15 image systems, the image plane rms does not decrease significantly when more systems are added; however, the rms values quoted in the literature may be misleading as to the ability of a model to predict new multiple images. The mass is well constrained near the Einstein radius in all cases, and systematic error drops to <2% for models using >10 image systems. Magnification errors are smallest along the straight portions of the critical curve, and the value of the magnification is systematically lower near curved portions. For >15 systems, the systematic error on magnification is ∼2%. We report no trend in magnification error with the fraction of spectroscopic image systems when selecting constraints at random; however, when using the same selection of constraints, increasing this fraction up to ∼0.5 will increase model accuracy. The results suggest that the selection of constraints, rather than quantity alone, determines the accuracy of the magnification. We note that spectroscopic follow-up of at least a few image systems is crucial because models without any spectroscopic redshifts are inaccurate across all of our diagnostics.
MODELING BRIGHT γ-RAY AND RADIO EMISSION AT FAST CLOUD SHOCKS

Recent observations by the Large Area Telescope on board the Fermi satellite have revealed bright γ-ray emission from middle-aged supernova remnants (SNRs) inside our Galaxy. These remnants, which also possess bright non-thermal radio shells, are often found to be interacting directly with surrounding gas clouds. We explore the non-thermal emission mechanism at these dynamically evolved SNRs by constructing a hydrodynamical model. Two scenarios of particle acceleration, either a re-acceleration of Galactic cosmic rays or an efficient nonlinear diffusive shock acceleration (NLDSA) of particles injected from downstream, are considered. Using parameters inferred from observations, our models are contrasted with the observed spectra of SNR W44. For the re-acceleration case, we predict a significant enhancement of radio and GeV emission as the SNR undergoes a transition into the radiative phase. If sufficiently strong magnetic turbulence is present in the molecular cloud, the re-acceleration scenario can explain the observed broadband spectral properties. The NLDSA scenario also succeeds in explaining the γ-ray spectrum but fails to reproduce the radio spectral index. Efficient NLDSA also results in a significant post-shock non-thermal pressure that limits the compression during cooling and prevents the formation of a prominent dense shell. Some other interesting differences between the two models in hydrodynamical behavior and resulting spectral features are illustrated.
Liver transplantation and intrahepatic cholangiocarcinoma: time to go forward again?

Purpose of review Liver transplantation for intrahepatic cholangiocarcinoma (iCCA) has been mired in controversy. High rates of recurrence posttransplant combined with donor organ scarcity resulted in most transplant centers treating iCCA as a contraindication for liver transplantation. Recent findings Recent studies have shown that carefully selected patients with unresectable iCCA can have good outcomes after liver transplantation. Better outcomes have been seen in patients with smaller tumors and favorable tumor biology. Summary Because many patients are diagnosed with iCCA at later stages, tumor biology and genetics are useful tools to identify patients who will have excellent overall and recurrence-free survival after liver transplantation. Further larger multicenter prospective studies are needed to identify patients who would benefit from liver transplantation with good outcomes. Additional advances will come through early diagnosis and utilizing a combination of chemotherapy and locoregional modalities as a bridge to transplant. There is also a need to recognize and develop additional neo- and adjuvant therapies for patients whose tumor biology currently precludes their inclusion on the liver transplantation waitlist.
Adhesion energy of single wall carbon nanotube loops on various substrates

The physics of adhesion of one-dimensional nano structures such as nanotubes, nano wires, and biopolymers on different material substrates is of great interest for the study of biological adhesion and the development of nano electronics and nano mechanics. In this paper, we present force spectroscopy experiments of a single wall carbon nanotube loop using our home-made interferometric atomic force microscope. Characteristic force plateaux during the peeling process allows us to access to quantitative values of the adhesion energy per unit length on various substrates: graphite, mica, platinum, gold and silicon. By combining a time-frequency analysis of the deflexion of the cantilever, we access to the dynamic stiffness of the contact, providing more information on the nanotube configurations and its intrinsic mechanical properties.
Integrated broadband bowtie antenna on transparent substrate

The bowtie antenna is a topic of growing interest in recent years. In this paper, we design, fabricate, and characterize a modified gold bowtie antenna integrated on a transparent glass substrate. We numerically investigate the antenna characteristics, specifically its resonant frequency and enhancement factor. We simulate the dependence of resonance frequency on bowtie geometry, and verify the simulation results through experimental investigation, by fabricating different sets of bowtie antennas on glass substrates utilizing CMOS compatible processes and measuring their resonance frequencies. Our designed bowtie antenna provides a strong broadband electric field enhancement in its feed gap. The far-field radiation pattern of the bowtie antenna is measured, and it shows dipole-like characteristics with large beam width. Such a broadband antenna will be useful for a myriad of applications, ranging from wireless communications to electromagnetic wave detection.
Instrumenting an ultrasound probe with a force sensor may improve thenon-invasive measurement of arterial biomechanical parameters (diameter, pulsatility, intima-media thickness and flow-dependent dilation) by measuring and controlling the force

Ultrasound examination is the first line procedure for the diagnosis and follow-up of cardiovascular diseases. Instrumenting an ultrasound probe with a force sensor may improve thenon-invasive measurement of arterial biomechanical parameters (diameter, pulsatility, intima-media thickness and flow-dependent dilation) by measuring and controlling the force exerted by the sonographer. We present here the results obtained with this approach coupled with image processing for the measurement of arterial diameter changes during the cardiac cycle and dynamic tests. The analysis of artery force feedback provided non-invasively an estimation of blood pressure waveform.
Bulletin of Electrical Engineering and Informatics

Received May 29, 2022 Revised Oct 7, 2022 Accepted Oct 26, 2022 The aim of this study is to propose a new robust face recognition algorithm by combining principal component analysis (PCA), Triplet Similarity Embedding based technique and Projection as a similarity metric at the different stages of the recognition processes. The main idea is to use PCA for feature extraction and dimensionality reduction, then train the triplet similarity embedding to accommodate changes in the facial poses, and finally use orthogonal projection as a similarity metric for classification. We use the open source ORL dataset to conduct the experiments to find the recognition rates of the proposed algorithm and compare them to the performance of one of the very well-known machine learning algorithms k-Nearest Neighbor classifier. Our experimental results show that the proposed model outperforms the kNN. Moreover, when the training set is smaller than the test set, the performance contribution of triplet similarity embedding during the learning phase becomes more visible compared to without it.
Noncommutative gravity with self-dual variables

We build a noncommutative extension of Palatini–Holst theory on a twist-deformed spacetime, generalizing a model that has been previously proposed by Aschieri and Castellani. The twist deformation entails an enlargement of the gauge group, and leads to the introduction of new gravitational degrees of freedom. In particular, the tetrad degrees of freedom must be doubled, thus leading to a bitetrad theory of gravity. The model is shown to exhibit new duality symmetries. The introduction of the Holst term leads to a dramatic simplification of the dynamics, which is achieved when the Barbero–Immirzi parameter takes the value , corresponding to a self-dual action. We study in detail the commutative limit of the model, focusing in particular on the role of torsion and non-metricity. The effects of spacetime noncommutativity are taken into account perturbatively, and are computed explicitly in a simple example. Connections with bimetric theories and the role of local conformal invariance in the commutative limit are also explored.