Miracle-dz/UniFAR-FTUs huggingface dataset:
Suppression of chromosome instability by targeting a DNA helicase in budding yeast

Chromosome instability (CIN) is an important driver of cancer initiation, progression, drug resistance, and aging. As such, genes whose inhibition suppresses CIN are potential therapeutic targets. We report here that deletion of an accessory DNA helicase, Rrm3, suppresses high CIN caused by a wide range of genetic or pharmacological perturbations in yeast. Although this helicase mutant has altered cell cycle dynamics, suppression of CIN by rrm3∆ is independent of the DNA damage and spindle assembly checkpoints. Instead, the rrm3∆ mutant may have increased kinetochore–microtubule error correction due to an altered localization of Aurora B kinase and associated phosphatase, PP2A-Rts1.
Multi-distance frequency-domain optical measurements of coherent cerebral hemodynamics

We report non-invasive, bilateral optical measurements on the forehead of five healthy human subjects, of 0.1 Hz oscillatory hemodynamics elicited either by cyclic inflation of pneumatic thigh cuffs, or by paced breathing. Optical intensity and the phase of photon-density waves were collected with frequency-domain near-infrared spectroscopy at seven source-detector distances (11-40 mm). Coherent hemodynamic oscillations are represented by phasors of oxyhemoglobin (O) and deoxyhemoglobin (D) concentrations, and by the vector D/O that represents the amplitude ratio and phase difference of D and O. We found that, on average, the amplitude ratio (|D/O|) and the phase difference (∠(D/O)) obtained with single-distance intensity at 11-40 mm increase from 0.1 and −330°, to 0.2 and −200°, respectively. Single-distance phase and the intensity slope featured a weaker dependence on source-detector separation, and yielded |D/O| and ∠(D/O) values of about 0.5 and −200°, respectively, at distances greater than 20 mm. The key findings are: (1) single-distance phase and intensity slope are sensitive to deeper tissue compared to single-distance intensity; (2) deeper tissue hemodynamic oscillations, which more closely represent the brain, feature D and O phasors that are consistent with a greater relative flow-to-volume contributions in brain tissue compared to extracerebral, superficial tissue.
Optimization of port size of high power density permanent magnet synchronous motor

The application of high power density motors is increasingly widespread, but the motor power density has been limited by the thermal load and the performance of the electromagnetic material. In order to reduce the thermal load of the motor, the relationship between the size of the motor Hs0 and Bs0 and the core loss of the motor is studied in this paper. It is found that the decrease of Hs0 and the increase of Hs0 can reduce the core loss of the motor. Meanwhile, with the increase of Bs0, the output torque of the motor increases first and then decreases. As the Hs0 increases, the output torque of the motor increases gradually. According to the above conclusions, the size of the notch of a high power density permanent magnet synchronous motor is optimized, and the core loss of the motor is reduced without affecting the output torque of the motor.
InGaN-Based MSM Visible Light Photodiodes With Recessed Anode

In<sub>0.17</sub>Ga<sub>0.83N</sub>-based metal-semiconductor-metal photo-diodes (MSM-PDs) with recessed anode electrodes were fabricated and characterized. The photodiodes exhibited low dark current of <inline-formula> <tex-math notation="LaTeX">$8\,\times \, 10^{-12}$ </tex-math></inline-formula> A at 5 V, which was one order lower than that of the conventional planar MSM-PDs. Peak responsivity up to 0.22 A/W was obtained at 430 nm and 1.5 V, corresponding to an external quantum efficiency of 63%. The 440 nm/490 nm rejection ratios of the recessed and planar MSM-PDs were ~10<sup>3</sup> and 10<sup>2</sup>, respectively. The improvements were attributed to the suppression of lateral surface leakage current and the enhancement of the internal electric field by the recessed anode electrodes.
Parallel performance assessment of a pseudo-spectral solver for transition and turbulent boundary layer flows

The computational performance and accuracy of a parallel pseudo-spectral solver is assessed, and the solver is validated for direct numerical simulations (DNS) of bypass transition and turbulent boundary layer flows. The solver shows spatial order of accuracy of 6.8 and 3.7 for laminar and turbulent flow simulations, respectively, and scalability up to 16 thousand processors. DNS predictions for plane channel and flat plate bypass transition flows compare very well with the benchmark results available in the literature. Analysis of the turbulent structures shows counter-rotating longitudinal structures in the sub/buffer layers, which inducing lifting on each other to generate series of sweep and ejection events. These events generate shear stress which transfers energy from mean flow to streamwise turbulent fluctuations. The energy is then redistributed to other turbulent velocity fluctuations via pressure-strain. Temporal DNS of bypass pass transition flow compare very well with spatial DNS using an order of magnitude lower computational cost, thus is identified to be a viable alternative for transition flow physics simulations.
Kinematic-based locomotion mode recognition for power augmentation exoskeleton

This article presents a kinematic-based method for locomotion mode recognition, for use in the control of an exoskeleton for power augmentation, to implement natural and smooth locomotion transition. The difference in vertical foot position between a foot already in contact with ground and a foot newly in contact with the ground was calculated via kinematics for the entire exoskeleton and used to identify the locomotion mode with other sensor data including data on the knee joint angle and inclination of the thigh, shank, and foot. Locomotion on five different types of terrain—level-ground walking, stair ascent, stair descent, ramp ascent, and ramp descent—were identified using two-layer decision tree classes. An updating process is proposed to improve identification of the transition and accuracy using the foot inclination at the mid-stance. An average identification accuracy of more than 99% was achieved in experiments with eight subjects for single terrains (no terrain transitions) and hybrid terrains. The experimental results show that the proposed method can achieve high accuracy without significant misrecognition and minimize the delay in locomotion mode recognition of the exoskeleton.
Broadband, dual‐band reflectarray with dual orthogonal polarisation for single and multi‐beam patterns

Two single-layered broadband dual-band dual orthogonal polarisation reflectarrays are designed and developed in the X- and Ku-bands. The well-known holographic technique is employed such that one antenna generates a single radiation beam in two bands and another generates a five-beam pattern in two bands simultaneously. For both antennas, a subwavelength Jerusalem-Shaped unit cell is employed to independently realise two impedance distributions for each band and, consequently, not only broaden the operational bandwidths for both bands, but also limit the mutual coupling between two sets of impedances. As a typical case, an X/Ku band 20 cm × 20 cm five-beam dual-band reflectarray with dual linear polarisation is designed and fabricated for the experimental verification. The measurement results show that the fabricated antenna has 21% 1-dB gain bandwidth (from 8.5 to 10.5 GHz) with vertical polarisation and has 8.8% 1-dB gain bandwidth (from 14.65 to 16 GHz) with horizontal polarisation. Furthermore, the maximum measured aperture efficiencies in the X- and Ku-bands are 57 and 69%, respectively.
Fluid Flow and Entropy Generation Analysis of Al2O3–Water Nanofluid in Microchannel Plate Fin Heat Sinks

The flow in channels of microdevices is usually in the developing regime. Three-dimensional laminar flow characteristics of a nanofluid in microchannel plate fin heat sinks are investigated numerically in this paper. Deionized water and Al2O3–water nanofluid are employed as the cooling fluid in our work. The effects of the Reynolds number (100 < Re < 1000), channel aspect ratio (0 < ε < 1), and nanoparticle volume fraction (0.5% < Φ < 5%) on pressure drop and entropy generation in microchannel plate fin heat sinks are examined in detail. Herein, the general expression of the entropy generation rate considering entrance effects is developed. The results revealed that the frictional entropy generation and pressure drop increase as nanoparticle volume fraction and Reynolds number increase, while decrease as the channel aspect ratio increases. When the nanoparticle volume fraction increases from 0 to 3% at Re = 500, the pressure drop of microchannel plate fin heat sinks with ε = 0.5 increases by 9%. It is demonstrated that the effect of the entrance region is crucial for evaluating the performance of microchannel plate fin heat sinks. The study may shed some light on the design and optimization of microchannel heat sinks.
Neural networks for analysing music and environmental audio

In this thesis, we consider the analysis of music and environmental audio recordings with neural networks. Recently, neural networks have been shown to be an effective family of models for speech recognition, computer vision, natural language processing and a number of other statistical modelling problems. The composite layer-wise structure of neural networks allows for flexible model design, where prior knowledge about the domain of application can be used to inform the design and architecture of the neural network models. Additionally, it has been shown that when trained on sufficient quantities of data, neural networks can be directly applied to low-level features to learn mappings to high level concepts like phonemes in speech and object classes in computer vision. In this thesis we investigate whether neural network models can be usefully applied to processing music and environmental audio. With regards to music signal analysis, we investigate 2 different problems. The first problem, automatic music transcription, aims to identify the score or the sequence of musical notes that comprise an audio recording. We also consider the problem of automatic chord transcription, where the aim is to identify the sequence of chords in a given audio recording. For both problems, we design neural network acoustic models which are applied to low-level time-frequency features in order to detect the presence of notes or chords. Our results demonstrate that the neural network acoustic models perform similarly to state-of-the-art acoustic models, without the need for any feature engineering. The networks are able to learn complex transformations from time-frequency features to the desired outputs, given sufficient amounts of training data. Additionally, we use recurrent neural networks to model the temporal structure of sequences of notes or chords, similar to language modelling in speech. Our results demonstrate that the combination of the acoustic and language model predictions yields improved performance over the acoustic models alone. We also observe that convolutional neural networks yield better performance compared to other neural network architectures for acoustic modelling. For the analysis of environmental audio recordings, we consider the problem of acoustic event detection. Acoustic event detection has a similar structure to automatic music and chord transcription, where the system is required to output the correct sequence of semantic labels along with onset and offset times. We compare the performance of neural network architectures against Gaussian mixture models and support vector machines. In order to account for the fact that such systems are typically deployed on embedded devices, we compare performance as a function of the computational cost of each model. We evaluate the models on 2 large datasets of real-world recordings of baby cries and smoke alarms. Our results demonstrate that the neural networks clearly outperform the other models and they are able to do so without incurring a heavy computation cost.
Correlation between Ocular Axial Length and Body Mass Index in a Black Population

Aim: To determine the correlation between Ocular axial length (AL) and body mass index (BMI) in a black population. Methods: This was a descriptive cross sectional study carried out in Port Harcourt City LGA, Nigeria. Subjects were selected using multistage random sampling with inclusion criteria of Visual Acuity > 6/18, age greater than 18 years with no history of past ocular surgeries or trauma. Socio demographic data was obtained through an interviewer based structured proforma. Data obtained included age, sex, tribe, occupation and level of education. Weight, height and Body Mass Index (BMI) were measured using a standard height and weight automated scale (SECA 769,220). Ocular examinations done included visual acuity, applanation tonometry and ophthalmoscopy. Axial length (AL) was measured using Amplitude (A) scan ultrasonography (SONOMED PACSCAN 300AP). Data obtained from one eye of the subjects were analyzed using SPSS (Version 17), and p value was set at ≤ 0.05. Results: Four hundred and sixty six (466) subjects participated in the study made up of two hundred and twelve (212) males (45.5%) and two hundred and fifty four (254) females (54.5%) with M: F ratio of 1:1.2. The age range was 18-92 years and mean age of the subjects studied 43.0±14.2 years. Findings revealed mean AL, Body Mass Index, Height and Weight to be (23.2±1.0 mm), (26.9±6.2 kg/m2), (162.5±9 cm) and (70.5±14.8 kg) respectively. The mean AL was greater in males than females. There was no statistically significant relationship between age and axial length. There was a statistically significant relationship between height and AL in both gender with AL increasing by 0.035 mm (p=0.001, r=0.261) with one centimeter change in height in males and 0.025 mm (p=0.001, r=0.2680) in females and between AL and level of education (p=0.001). There was also a statistically significant (0.009 mm) increase in AL per one kilogramme change in weight in females (p=0.0001, r=0.188). Males had longer AL than females in all the BMI groups with a statistically significant difference found between the different BMI classes. Conclusion: This study noted that although there is no statistically significant relationship between AL and BMI, there are significant relationships between AL and height and weight respectively. Estimated AL in mm= 16.91 + 0.039 (height in cm).
Multifunctional Nanoionic Devices Enabling Simultaneous Heterosynaptic Plasticity and Efficient In‐Memory Boolean Logic

The development of smart, scalable, and power efficient computers relies on innovative technologies that can distribute memory alongside processing, such as emerging neuromorphic computing and in‐memory logic technologies. Here, a type of vertical 3‐terminal oxide based nanoionic device capable of implementing heterosynaptic plasticity and nonvolatile Boolean logic simultaneously is demonstrated. The heterosynaptic plasticity endows the devices with facilely tunable synaptic kinetics via tailoring modulatory signals, which is shown to be crucial for achieving optimized learning scheme, therefore offering promising building blocks for neuromorphic computing. Furthermore, it is demonstrated that these heterosynaptic devices can simultaneously be utilized to implement nonvolatile Boolean logic with improved efficiency compared with existing approaches, therefore implying in‐memory computing potentialities. The heterosynaptic devices with such multifunctionality thus hold great potential for next‐generation non‐von Neumann computing applications.
The role of epistemic and social characteristics in children's selective trust: Three meta-analyses.

Over the last 15 years, researchers have been increasingly interested in understanding the nature and development of children's selective trust. Three meta-analyses were conducted on a total of 51 unique studies (88 experiments) to provide a quantitative overview of 3- to 6-year-old children's selective trust in an informant based on the informant's epistemic or social characteristics, and to examine the relation between age and children's selective trust decisions. The first and second meta-analyses found that children displayed medium-to-large pooled effects in favor of trusting the informant who was knowledgeable or the informant with positive social characteristics. Moderator analyses revealed that 4-year-olds were more likely to endorse knowledgeable informants than 3-year-olds. The third meta-analysis examined cases where two informants simultaneously differed in their epistemic and social characteristics. The results revealed that 3-year-old children did not selectively endorse informants who were more knowledgeable but had negative social characteristics over informants who were less knowledgeable but had positive social characteristics. However, 4- to 6-year-olds consistently prioritized epistemic cues over social characteristics when deciding who to trust. Together, these meta-analyses suggest that epistemic and social characteristics are both valuable to children when they evaluate the reliability of informants. Moreover, with age, children place greater value on epistemic characteristics when deciding whether to endorse an informant's testimony. Implications for the development of epistemic trust and the design of studies of children's selective trust are discussed. This article is protected by copyright. All rights reserved.
Extremely large sweep amplitude enables high wing loading in giant hovering insects

Beetle Allomyrina dichotoma is one of the largest insects that performs many remarkable modes of locomotion, particularly hovering flight capability. In order to stay airborne, its flexible hindwings are flapped so as to work as a thrust generator. However, the wing loading of the beetle is relatively large (38.94 ± 3.73 N m−2) compared to those of other insects and hummingbirds, indicating that it is challenging for it to achieve flight. Here, we measured the hindwing morphology and kinematics of the beetle in order to discover its flight performance. Unlike many other insects, the beetle flaps its hindwings with an extremely large sweep amplitude of about 191.33 ± 6.12 deg at high flapping frequencies ranging from 36 to 41 Hz (mean wing tip speed ≈ 13.45 ± 0.58 m s−1). These capabilities enable the beetle to produce enough lift force to stay airborne with its bulky body (4–10 g). In order to investigate how the sweep amplitude affects the beetle’s flight efficiency, we utilized the unsteady blade element model to estimate the power requirements of the same vertical force production for various sweep amplitudes. The results indicate that the sweep amplitude as high as 190 deg is more beneficial for power requirements than the smaller amplitudes, which require higher frequencies resulting in higher inertial powers to produce the same vertical force. Thus, for this large beetle, high sweep amplitude may be a biological strategy for staying airborne. In addition, we thoroughly discussed the effects of input constraints on the outcome by investigating power loadings for variable sweep amplitudes at a constant vertical force, mean wing tip speed, and flapping frequency. Effect of wing surface area was also investigated and discussed to provide useful information for the development of an insect-inspired flapping-wing robot.
Effect of corruption on perceived difficulties in healthcare access in sub-Saharan Africa

Background Achieving Universal Health Coverage (UHC) by improving financial protection and effective service coverage is target 3.8 of the Sustainable Development Goals. Little is known, however, about the extent to which paying bribes within healthcare acts as a financial barrier to access and, thus, UHC. Methods Using survey data in adults from 32 sub-Saharan African countries in 2014–2015, we constructed a multilevel model to evaluate the relationship between paying bribes and reported difficulties of obtaining medical care. We controlled for individual-, region-, and country-level variables. Results Having paid bribes for medical care significantly increased the odds of reporting difficulties in obtaining care by 4.11 (CI: 3.70–4.57) compared to those who never paid bribes, and more than doubled for those who paid bribes often (OR = 9.52; 95% CI: 7.77–11.67). Respondents with higher levels of education and more lived poverty also had increased odds. Those who lived in rural areas or within walking distance to a health clinic had reduced odds of reporting difficulties. Sex, age, living in a capital region, healthcare expenditures per capita, and country Corruption Perception Index were not significant predictors. Conclusions We found that bribery in healthcare is a significant barrier to healthcare access, negatively affecting the potential of African countries to make progress toward UHC. Future increases in health expenditures—which are needed in many countries to achieve UHC—should be accompanied by greater efforts to fight corruption in order to avoid wasting money. Measuring and tracking health sector-specific corruption is critical for progress toward UHC.
A SNP Mutation of SiCRC Regulates Seed Number Per Capsule and Capsule Length of cs1 Mutant in Sesame

Seed number per capsule (SNC) is a major factor influencing seed yield and is an important trait with complex gene interaction effects. We first performed genetic analysis, gene cloning, and molecular mechanism study for an EMS-induced sesame mutant cs1 with fewer SNC and shorter capsule length (CL). The mutant traits were due to the pleiotropism of a regressive gene (Sics1). Capsule hormone determination showed that five out of 12 hormones, including auxin indole-3-acetic acid (IAA), had significantly different levels between wild type (WT) and mutant type (MT). KEGG pathway analysis showed that plant hormone signal transduction, especially the auxin signal transduction pathway, was the most abundant differentially expressed signaling pathway. After the cross-population association and regional genome screening, we found that three homozygous loci were retained in cs1. Further analysis of these three loci resulted in the identification of SiCRC as the candidate gene for cs1. SiCRC consists of seven exons and six introns encoding 163 amino acids. The SiCRC in cs1 showed a point mutation at intron 5 and exon 6 junction, resulting in the splice site being frame-shifted eight nucleotides further downstream, causing incorrect splicing. Taken together, we assumed the SNP mutation in SiCRC disrupted the function of the transcription factor, which might act downstream of the CRC-auxin signal transduction pathway, resulting in a shorter CL and less SNC mutation of cs1 in sesame. Our results highlight the molecular framework underlying the transcription factor CRC-mediated role of auxin transduction in SNC and CL development.