Miracle-dz/UniFAR-FTUs huggingface dataset:
Histone Hyperacetylation Up-regulates Protein Kinase C (cid:2) in Dopaminergic Neurons to Induce Cell Death RELEVANCE TO EPIGENETIC MECHANISMS OF NEURODEGENERATION IN PARKINSON DISEASE

Background: Dysregulation of neuronal acetylation homeostasis promotes neurodegeneration. Results: Histone hyperacetylation up-regulates PKC (cid:2) in dopaminergic neurons and augments susceptibility to oxidative damage. Conclusion: Epigenetic regulation of PKC (cid:2) plays a proapoptotic role in neuronal cell death. Significance: The up-regulation of PKC (cid:2) expression by hyperacetylation provides an epigenetic molecular basis of neurodegenerative disease. The oxidative stress-sensitive protein kinase C (cid:2) (PKC (cid:2) ) has been implicated in dopaminergic neuronal cell death. However, little is known about the epigenetic mechanisms regulating PKC (cid:2) expression in neurons. Here, we report a novel mechanism by which the PKC (cid:2) gene can be regulated by histone acetylation. Treatment with histone deacetylase (HDAC) inhibitor sodium butyrate (NaBu) induced PKC (cid:2) expression in cultured neurons, brain slices, and animal models. Several other HDAC inhibitors also mimicked NaBu. The chromatin immunoprecipitation analysis revealed that hyperacetylation of histone H4 by NaBu is associated with the PKC (cid:2) promoter. Deletion analysis of the PKC (cid:2) promoter mapped the NaBu-responsive element to an 81-bp minimal promoter region. Detailed mutagenesis studies within this region revealed that four GC boxes conferred hyperacetylation-induced PKC (cid:2) promoter activation. Cotransfection experiments and Sp inhibitor studies demonstrated that Sp1, Sp3, and Sp4 regulated NaBu-induced PKC (cid:2) up-regula-tion. However, NaBu did not alter the DNA binding activities of Spproteinsortheirexpression.Interestingly,aone-hybridanal-ysis revealed that NaBu enhanced transcriptional activity of Sp1/Sp3. Overexpression of the p300/cAMP-response element-binding protein-binding protein (CBP) potentiated the NaBu-mediated transactivation potential of Sp1/Sp3, but expressing severalHDACsattenuatedthiseffect,suggestingthatp300/CBP and HDACs act as coactivators or corepressors in histone acety-lation-induced PKC (cid:2) up-regulation. Finally, using genetic and pharmacological approaches, we showed that NaBu up-regula-tion of PKC (cid:2) sensitizes neurons to cell death in a human dopaminergic cell model and brain slice cultures. Together, these results indicate that histone acetylation regulates PKC (cid:2) expression to augment nigrostriatal dopaminergic cell death, which could contribute to the progressive neuropathogenesis of Parkinson disease.
A Monte-Carlo approach of remanence enhancement effect in ferroelectric Potts lattice

Abstract The hysteresis dynamics of a multi-domain Potts lattice with non-zero domain wall width is simulated using kinetic Monte-Carlo method. The remanence enhancement effect is investigated, taking into account polarization relaxation in domain walls. Significant enhancement of the remanence and weakening of the coercivity with increasing domain walls are revealed. The hysteresis area is conserved against variation of domain size and wall width, which predicts that no excess energy is required for the polar relaxation in domain walls, thus the remanence enhancement. The theoretically predicted scaling relation on the remanence enhancement is confirmed with the present simulation.
Scalar dark matter, GUT baryogenesis, and radiative neutrino mass

We investigate an interesting correlation among dark matter phenomenology, neutrino mass generation and GUT baryogenesis, based on the scotogenic model. The model contains additional right-handed neutrinos $N$ and a second Higgs doublet $\Phi$, both of which are odd under an imposed $Z_2$ symmetry. The neutral component of $\Phi$, i.e. the lightest of the $Z_2$-odd particles, is the dark matter candidate. Due to a Yukawa coupling involving $\Phi$, $N$ and the Standard Model leptons, the lepton asymmetry is converted into the dark matter asymmetry so that a non-vanishing $B-L$ asymmetry can arise from $(B-L)$-conserving GUT baryogenesis, leading to a nonzero baryon asymmetry after the sphalerons decouple. On the other hand, $\Phi$ can also generate neutrino masses radiatively. In other words, the existence of $\Phi$ as the dark matter candidate resuscitates GUT baryogenesis and realizes neutrino masses.
Effects of tidal gravitational fields in clustering dark energy models

We extend a previous work by Reischke et al., 2016 by studying the effects of tidal shear on clustering dark energy models within the framework of the extended spherical collapse model and using the Zel'dovich approximation. As in previous works on clustering dark energy, we assumed a vanishing effective sound speed describing the perturbations in dark energy models. To be self-consistent, our treatment is valid only on linear scales since we do not intend to introduce any heuristic models. This approach makes the linear overdensity $\delta_{\rm c}$ mass dependent and similarly to the case of smooth dark energy, its effects are predominant at small masses and redshifts. Tidal shear has effects of the order of percent or less, regardless of the model and preserves a well known feature of clustering dark energy: When dark energy perturbations are included, the models resemble better the $\Lambda$CDM evolution of perturbations. We also showed that effects on the comoving number density of halos are small and qualitatively and quantitatively in agreement with what previously found for smooth dark energy models.
Unveiling the nature of candidate high-mass young stellar objects in the Magellanic Clouds with near-IR spectroscopy

As nearby neighbors to the Milky Way, the Large and Small Magellanic Clouds (LMC and SMC) provide a unique opportunity to study star formation in the context of their galactic ecosystems. Thousands of young stellar objects (YSOs) have been characterized with large-scale Spitzer and Herschel surveys. In this paper, we present new near-IR spectroscopy of five high-mass YSOs in the LMC and one in the SMC. We detect multiple hydrogen recombination lines, as well as He I 2.058 $\mu$m, H$_2$, [Fe II], and [S III] in these highly excited sources. We estimate the internal extinction of each source and find that it is highest for sources with the youngest evolutionary classifications. Using line ratios, we assess the dominant excitation mechanism in the three sources where we detect both H$_2$ 2.12 $\mu$m and [Fe II] 1.64 $\mu$m. In each case, photoexcitation dominates over shock excitation. Finally, we detect CO bandhead absorption in one of our LMC sources. While this feature is often associated with evolved stars, this object is likely young with strong PAH and fine-structure emission lines tracing an H II region detected at longer wavelengths. Compared to high-mass YSOs in the Galaxy, our sources have higher bolometric and line luminosities, consistent with their selection as some of the brightest sources in the LMC and SMC.
Hybrid Single and Multiobjective Optimization for Engineering Design without Exact Speciﬁcations

—A challenge in engineering design optimization is that sufﬁcient information may not be available to deﬁne the exact speciﬁcations beforehand. While iterative trial optimization using different speciﬁcations is widely used in industry, multiobjective optimization is attracting much attention in the academic ﬁeld. However, off-the-shelf methods in both categories are time-consuming due to the involved computationally expensive simu- lations. In this paper, the characteristics of the targeted problem are summarized; the gap between off-the-shelf methods and the practical need is then analyzed. A simple yet effective framework, called two-stage multi-ﬁdelity surrogate model-assisted optimization (TMSO), is proposed to improve efﬁciency. TSMO is implemented by two state-of-the-art optimization algorithms and two real-world design cases demonstrate its effectiveness in practice. The research topics in multiobjective optimization and surrogate model-assisted optimization inspired by the TSMO framework is ﬁnally discussed.
Modelling dielectric-constant values of concrete: an aid to shielding effectiveness prediction and ground-penetrating radar wave technique interpretation

A number of efficient and diverse mathematical methods have been used to model electromagnetic wave propagation. Each of these methods possesses a set of key elements which eases its understanding. However, the modelling of the propagation in concrete becomes impossible without modelling its electrical properties. In addition to experimental measurements; material theoretical and empirical models can be useful to investigate the behaviour of concrete's electrical properties with respect to frequency, moisture content (MC) or other factors. These models can be used in different fields of civil engineering such as (1) electromagnetic compatibility which predicts the shielding effectiveness (SE) of a concrete structure against external electromagnetic waves and (2) in non-destructive testing to predict the radar wave reflected on a concrete slab. This paper presents a comparison between the Jonscher model and the Debye models which is suitable to represent the dielectric properties of concrete, although dielectric and conduction losses are taken into consideration in these models. The Jonscher model gives values of permittivity, SE and radar wave reflected in a very good agreement with those given by experimental measurements and this for different MCs. Compared with other models, the Jonscher model is very effective and is the most appropriate to represent the electric properties of concrete.
Confronting Models of Massive Star Evolution and Explosions with Remnant Mass Measurements

The mass distribution of compact objects provides a fossil record that can be studied to uncover information on the late stages of massive star evolution, the supernova explosion mechanism, and the dense matter equation of state. Observations of neutron star masses indicate a bimodal Gaussian distribution, while the observed black hole mass distribution decays exponentially for stellar-mass black holes. We use these observed distributions to directly confront the predictions of stellar evolution models and the neutrino-driven supernova simulations of Sukhbold et al. We find strong agreement between the black hole and low-mass neutron star distributions created by these simulations and the observations. We show that a large fraction of the stellar envelope must be ejected, either during the formation of stellar-mass black holes or prior to the implosion through tidal stripping due to a binary companion, in order to reproduce the observed black hole mass distribution. We also determine the origins of the bimodal peaks of the neutron star mass distribution, finding that the low-mass peak (centered at ∼1.4 M⊙) originates from progenitors with MZAMS ≈ 9–18 M⊙. The simulations fail to reproduce the observed peak of high-mass neutron stars (centered at ∼1.8 M⊙) and we explore several possible explanations. We argue that the close agreement between the observed and predicted black hole and low-mass neutron star mass distributions provides new, promising evidence that these stellar evolution and explosion models capture the majority of relevant stellar, nuclear, and explosion physics involved in the formation of compact objects.
Automatic Query Quality Prediction Using Feed Forward Neural Network

Text retrieval activity involves retrieving the source code which software developers conduct on a daily basis. Current methods for retrieving source code rely on regular expressions and assume that the developers searching the code base are well-versed in the source code. Software developers ought to possess freedom to formulate queries on the codebase using natural language sentences as opposed to a search being a keyword or pattern-based, which are difficult to remember. When a bug is raised, developers who are new to the source code base may issue an NLQ to the code base to obtain the code where they must provide a fix. Nevertheless, the performance of a text search is highly dependent on query quality, and it succeeds when the textual query is of good quality. Predicting query quality in advance on a source code retrieval system can alert developers when a query is unlikely to succeed, thereby saving them time and effort from going through a long list of results. In this paper, the quality of the query is predicted using a back-propagation approach to train a feed-forward neural network (multi-layer perceptron). The model is trained and evaluated on a dataset that is created from the source code documentation. Natural language processing pre-retrieval metrics are exploited to study the significance of training the model. The model proves to be a good predictor of query quality with 85.75% accuracy.
A systematic review of interleukin-2-based immunotherapies in clinical trials for cancer and autoimmune diseases

Background: The cytokine interleukin-2 (IL-2) can stimulate both effector immune cells and regulatory T (Treg) cells. The ability of selectively engaging either of these effects has spurred interest in using IL-2 for immunotherapy of cancer and autoimmune diseases. Thus, numerous IL-2-based biologic agents with improved bias or delivery toward effector immune cells or Treg cells have been developed. These improved IL-2-based compounds recently entered clinical trials. Objective: This study systematically reviews clinical results of improved IL-2-based compounds for the treatment of cancer or autoimmune diseases. Methods: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), searched the ClinicalTrials.gov database for registered IL-2 trials using improved IL-2-based agents and different databases for available results of these studies. Results: We identified 547 registered clinical trials, of which we extracted 36 studies on improved IL-2-based compounds. Moreover, we assessed another 9 agents reported in two recent literature reviews and based on our knowledge, totaling in 45 improved IL-2-based compounds. A secondary search for registered clinical trials of each of these improved 45 compounds resulted in 139 clinical trials included in this systematic review, with 29 trials reporting clinical results. Conclusions: As of yet, none of the improved IL-2-based compounds gained regulatory approval for the treatment of cancer or autoimmune diseases. Three compounds treating cancer have entered phase 3 trials with two studies still ongoing. NKTR-214 is the only compound that has completed phase 3 studies. The PIVOT IO-001 study testing the combination of NKTR-214 plus Pembrolizumab compared to Pembrolizumab monotherapy in metastatic melanoma missed its primary endpoint of superior objective response rate and progression-free survival. The PIVOT-09 study, combining NKTR-214 with Nivolumab compared to Sunitinib or Cabozantinib in advanced renal cell carcinoma, missed its primary endpoint of improved objective response rate. Trials in autoimmune diseases are currently in early stages, thus not allowing conclusions on efficacy. Results of ongoing trials will provide insight into which improved IL-2-based compounds will be beneficial for cancer and autoimmune diseases.
Prevalence of Congenital Heart Defects in Individuals With Down Syndrome in Saudi Arabia: A Systematic Review and Meta-Analysis

Patients with Down syndrome (DS) are commonly diagnosed with congenital heart disease (CHD), which is the leading cause of mortality in this group during the first two years of life. This systematic review and meta-analysis aims to review the current publications to assess the pooled prevalence of overall CHDs in individuals with DS in KSA. We conducted the search on the databases PubMed, EBSCO, Scopus, Web of Science through Clarivate, and Google Scholar using Boolean operators and various keywords. The Rayyan - Intelligent Systematic Reviews website (https://www.rayyan.ai/) was used for citation management and MedCalc® Statistical Software version 20.115 was used for the quantitative data synthesis (MedCalc Software Ltd., 2022, Ostend Belgium). We initially retrieved a total of 402 citations from the primary search and 10 articles were finally included after title screening and full-text assessment. A total of 1590 subjects were enrolled in the pooled analyses. The pooled prevalence of CHDs was found to be 66.1% (95% CI: 57.2% to 74.5%). There was significant heterogeneity (I2 = 92.2%), and inspection of the funnel plot shows the symmetrical distribution of plotted data. According to our study, 66% of DS patients in Saudi Arabia had one or more congenital cardiac defects. Due to the significant inter-study heterogeneity, the reliability of our results is, nevertheless, limited. We advise conducting more research to provide better data for determining the prevalence of CHD.
Attention-Based Fusion Factor to FPN for Small Object Detection

FPN-based detectors have made notable progress in general object detection, but the performance and efficiency of detecting small objects are far from satisfactory. Even through FPN can fuse semantic information from deep layers to shallow layers, it also brings noise containing spatial information of large objects to shallow layers. To address this challenge, we propose an attention-based fusion factor (AFF) consisting of two components, $\boldsymbol{\alpha}-\mathbf{CBAM}$ and $\boldsymbol{\alpha}-\mathbf{Query}$, to enhance the semantic information of small objects in the fusion process. The $\boldsymbol{\alpha}-\mathbf{CBAM}$ can be used to learn the vertical fusion factor of the FPN to control the information passed from deep to shallow layers. The $\boldsymbol{\alpha}-\mathbf{Query}$ acts as an fusion factor to control the horizontal transfer impact of FPN. $\boldsymbol{\alpha}-\mathbf{Query}$ first predicts the coarse locations of small objects in low-resolution feature maps and then increases their weights in high-resolution feature maps. Ablation studies on the publicly available dataset PASCAL VOC are conducted to demonstrate the effectiveness of $\boldsymbol{\alpha}-\mathbf{CBAM}$ and $\boldsymbol{\alpha}-\mathbf{Query}$. Moreover, experimental results on the datasets MS COCO and VisDrone show that the baseline model with additional AFF evidently outperforms itself in almost all the related metrics.
PENDAMPINGAN PENYUSUNAN ASESMEN PEMBELAJARAN PEMODELAN MATEMATIKA BAGI GURU MATEMATIKA MAITREYAWIRA UNTUK MENGUKUR KEMAMPUAN PEMODELAN PESERTA DIDIK

Peran asesmen pemodelan matematika sangat penting dalam menilai pembelajaran yang mengintegrasikan situasi dunia nyata dan ide-ide matematika dalam suatu permasalahan matematika. Penyusunan asesmen pemodelan matematika belum terlaksanakan secara maksimal dalam pembelajaran karena masih terbatasnya sumber yang menyediakan bentuk-bentuk permasalahan pemodelan matematika dan sumber yang mendukung pengembangan kemampuan guru dalam menyusun asesmen pembelajaran pemodelan. Kegiatan pendampingan pada pengabdian masyarakat ini disusun untuk Guru Matematika Maitreyawira pada jenjang SD, SMP, dan SMA dari berbagai provinsi di Indonesia dengan tujuan untuk melatih kemampuan guru dalam menyusun asesmen pembelajaran pemodelan matematika. Kegiatan terintegrasi dengan kegiatan akademi, praktik lapangan dan riset mahasiswa dengan melibatkan dosen sebagai pendamping. Kegiatan ini dilaksanakan secara tatap maya dengan pemaparan asesmen pembelajaran pemodelan matematika, pendampingan penyusunan asesmen pemodelan matematika dan presentasi tugas penyusunan asesmen. Data yang diperoleh dari kegiatan ini adalah persepsi guru terhadap kegiatan asesmen pemodelan matematika dan tugas peserta dalam menyusun asesmen yang dianalisis secara deskriptif kuantitatif. Hasil pelaksanaan kegiatan pengabdian masyarakat menunjukkan bahwa tanggapan peserta terhadap kegiatan baik.
Quantum walks with entangled coins

We present a mathematical formalism for the description of un- restricted quantum walks with entangled coins and one walker. The numerical behaviour of such walks is examined when using a Bell state as the initial coin state, with two different coin operators, two different shift operators, and one walker. We compare and contrast the performance of these quantum walks with that of a classical random walk consisting of one walker and two maximally correlated coins as well as quantum walks with coins sharing different degrees of entanglement. We illustrate that the behaviour of our walk with entangled coins can be very different in comparison to the usual quantum walk with a single coin. We also demonstrate that simply by changing the shift operator, we can generate widely different distributions. We also compare the behaviour of quantum walks with maximally entangled coins with that of quantum walks with non-entangled coins. Finally, we show that the use of different shift operators on two and three qubit coins leads to different position probability distributions in one- and two-dimensional graphs.
Action research to reassess the acceptance and use of technology in a blended learning approach amongst postgraduate business students

Abstract Although the pedagogy of blended learning in higher education has been well-accepted since 2000, its dimension has been changing, mainly due to the incessant technological innovations. The impact recorded on students’ experience has been reliant on various factors. Some of these factors are cultural diversity, technical abilities, level of organisational support, language difficulties, educational background, learning environment, and instructional design, among others. In this study, the acceptance and use of technology by international MBA students have been reassessed in the blended learning environment. The motivation for the selection of the cohort of international MBA students as a sample was to enable the inclusion of diversity as one of the focal points of the study. A two-cycle model of action research was adopted to reassess the use of technology and compare the attainment of learning outcomes between the blended and traditional learning approaches. Moreover, multiple regressions were employed using the unified theory of acceptance and use of technology (UTAUT) to test the significance of each variable collected from the survey on the students’ learning experience and engagement. Our results have suggested that students’ engagement is determined by positive learning experience without any bias toward traditional or blended learning approach. Students’ age group was found to be relevant in the determination of behavioural intention, social influence, effort expectancy, performance expectancy and facilitating conditions towards the effective use of technology and blended learning. Students’ gender was an irrelevant factor in the success of a blended learning approach.
XMM–Newton observations of GB B1428+4217: confirmation of intrinsic soft X-ray absorption

We report the results of XMM-Newton observations of the X-ray bright, radio-loud blazar GB B1428+4217 at a redshift of z = 4.72. We confirm the presence of soft X-ray spectral flattening at energies ? 0.7 keV as reported in previous ROSAT and BeppoSAX observations. At hard X-ray energies, the spectrum is consistent with a power law, although we find that the spectral slope varied between both XMM-Newton observations and it is also significantly different from that reported previously. Whilst we cannot rule out intrinsic cold absorption to explain the spectral depression, we favour a dust-free warm absorber. Cold absorption requires a column density ∼1.4-1.6 x 10 22 cm -2 , whilst a warm absorber could have up to ∼10 23 cm -2 and an ionization parameter ∼10 2 . The spectrum of GB B1428+4217 shows remarkable parallels with that of the z = 4.4 blazar PMN J0525-3343, in which the available evidence is also most consistent with a warm absorber model.