Miracle-dz/UniFAR-FTUs huggingface dataset:
Monogenic diabetes in New Zealand - An audit based revision of the monogenic diabetes genetic testing pathway in New Zealand

Aims To evaluate (a) the diagnostic yield of genetic testing for monogenic diabetes when using single gene and gene panel-based testing approaches in the New Zealand (NZ) population, (b) whether the MODY (Maturity Onset Diabetes of the Young) pre-test probability calculator can be used to guide referrals for testing in NZ, (c) the number of referrals for testing for Māori/Pacific ethnicities compared to NZ European, and (d) the volume of proband vs cascade tests being requested. Methods A retrospective audit of 495 referrals, from NZ, for testing of monogenic diabetes genes was performed. Referrals sent to LabPlus (Auckland) laboratory for single gene testing or small multi-gene panel testing, or to the Exeter Genomics Laboratory, UK, for a large gene panel, received from January 2014 – December 2021 were included. Detection rates of single gene, small multi-gene and large gene panels (neonatal and non-neonatal), and cascade testing were analysed. Pre-test probability was calculated using the Exeter MODY probability calculator and ethnicity data was also collected. Results The diagnostic detection rate varied across genes, from 32% in GCK, to 2% in HNF4A, with single gene or small gene panel testing averaging a 12% detection rate. Detection rate by type of panel was 9% for small gene panel, 23% for non-neonatal monogenic diabetes large gene panel and 40% for neonatal monogenic diabetes large gene panel. 45% (67/147) of patients aged 1-35 years at diabetes diagnosis scored <20% on MODY pre-test probability, of whom 3 had class 4/5 variants in HNF1A, HNF4A or HNF1B. Ethnicity data of those selected for genetic testing correlated with population diabetes prevalence for Māori (15% vs 16%), but Pacific People appeared under-represented (8% vs 14%). Only 1 in 6 probands generated a cascade test. Conclusions A new monogenic diabetes testing algorithm for NZ is proposed, which directs clinicians to choose a large gene panel in patients without syndromic features who score a pre-test MODY probability of above 20%.
Teachers’ perceived usefulness, ease of use, and challenges with e-learning utilization sustainability after COVID-19 pandemic in Oyo state, Nigeria

This study examined teachers’ perceived usefulness, ease of use, and challenges with e-learning utilization sustainability after COVID-19pandemic. The research was designed as a descriptive survey research and purposive sampling technique was used to select 30 schoolsand 300 teachers from 630 secondary schools in Oyo State in Nigeria. A questionnaire was developed tagged as teachers’ perceptionson sustainable utilization of e-learning after COVID-19 pandemic with a 0.82 reliability index obtained. The data collected were analyzedusing simple percentage, mean scores, and standard deviation. The results revealed that teachers’ perceived usefulness and ease of use ofe-learning were positive and high. In addition, the study has reported that some factors like irregular network service, no direct trainingfor teachers, and many others were identified as challenges to the use of e-learning for instructional delivery. It was recommended amongothers that policymakers should infuse e-learning instructional strategy into the curriculum for teaching/learning process.
Progranulin Gene Mutations in Chinese Patients with Frontotemporal Dementia: A Case Report and Literature Review

Background: Progranulin (GRN) mutations in frontotemporal dementia (FTD) have been less frequently reported in China than in Western countries. Objective: This study reports a novel GRN mutation and summarizes the genetic and clinical features of patients with GRN mutations in China. Methods: Comprehensive clinical, genetic, and neuroimaging examinations were conducted on a 58-year-old female patient diagnosed with semantic variant primary progressive aphasia. A literature review was also conducted and clinical and genetic features of patients with GRN mutations in China were summarized. Results: Neuroimaging revealed marked lateral atrophy and hypometabolism in the left frontal, temporal, and parietal lobes. The patient was negative for pathologic amyloid and tau deposition by positron emission tomography. A novel heterozygous 45-bp deletion (c.1414-14_1444delCCCTTCCCCGCCAGGCTGTGTGCTGCGAGGATCGCCAGCACTGCT) was detected by whole-exome sequencing of the patient’s genomic DNA. Nonsense-mediated mRNA decay was presumed to be involved in the degradation of the mutant gene transcript. The mutation was deemed pathogenic according to American College of Medical Genetics and Genomics criteria. The patient had a reduced plasma GRN level. In the literature, there were reports of 13 Chinese patients – mostly female – with GRN mutations; the prevalence was 1.2% –2.6% and patients mostly had early disease onset. Conclusion: Our findings expand the mutation profile of GRN in China, which can aid the diagnosis and treatment of FTD.
An attention‐guided convolution neural network for denoising of distributed acoustic sensing–vertical seismic profile data

Distributed acoustic sensing technology is a new type of signal acquisition technology, and this technology has been widely used in obtaining vertical seismic profile data in recent years. Distributed acoustic sensing technology has the advantages of high sampling density and strong tolerance to a harsh environment. However, in the real distributed acoustic sensing–vertical seismic profile data, the effective signal will be annihilated by various noises, which significantly complicates data analysis and interpretation. Deep learning approaches have developed rapidly in the noise suppression field in recent years. In order to eliminate the noise in distributed acoustic sensing–vertical seismic profile data, based on traditional convolution neural network, we add channel attention and spatial attention modules to the network to enhance the feature extraction ability of the network and use extended convolution to increase the receptive field to build a more efficient denoising model. In addition, we use different indicators to evaluate the quality of denoising, including signal‐to‐noise ratio, mean absolute error, kurtosis and skewness. The experimental results show that our method can recover the uplink wave field and downlink wave field, remove horizontal noise, optical system noise, random noise and other noises and improve the overall signal‐to‐noise ratio before and after denoising by 22 dB, reflecting a good ability of denoising and recovering effective signals.
How Robust Are Multirater Interrater Reliability Indices to Changes in Frequency Distribution?

ABSTRACT Interrater reliability studies are used in a diverse set of fields. Often, these investigations involve three or more raters, and thus, require the use of indices such as Fleiss’s kappa, Conger’s kappa, or Krippendorff’s alpha. Through two motivating examples—one theoretical and one from practice—this article exposes limitations of these indices when the units to be rated are not well-distributed across the rating categories. Then, using a Monte Carlo simulation and information visualizations, we argue for the use of two alternative indices, the Brennan–Prediger coefficient and Gwet’s AC2, because the agreement levels reported by these indices are more robust to variation in the distribution of units that raters encounter. The article concludes by exploring the complex, interwoven relationship between the number of levels in a rating instrument, the agreement level present among raters, and the distribution of units that are to be scored. Supplementary materials for this article are available online.
Centimeter-Scale Underwater Robot With High-Speed Inspired by Jellyfish

Centimeter-scale underwater robots have important applications in underwater resource exploration, environmental monitoring, equipment fault diagnosis, and military applications. However, developing small underwater robots remains a challenge because of the limitation of miniaturized structures. In this study, we developed a small underwater robot (JR) with high-speed, inspired by the jellyfish ephyra, composed of a dish-shaped wing, a flexible joint, a rigid support, a semicircular air chamber, with a magnet and a coil integrated as the driving source. Robot JR combines the advantages of electromagnetic drive, flexible structures, miniaturization of the jellyfish robot is realized and high-speed swimming. The size of robot JR was only Φ 5 × 3 cm, which is the smallest besides the jellyfish robot driven by an external magnetic field. Meanwhile, its maximum movement speed reached 4.6 BL/s, which is also considerably faster than that of other jellyfish robots. The design and control strategies of our research will provide a reference for future design and lay a solid foundation for the practical use of small underwater robots.
Cross-modal image segmentation and synthesis in medical imaging

Medical image is an important type of evidence for diagnosising disease. However, some patients can not receive a complete radiological examination due to the damage of radiation, medical cost or individual differences, so the transmembrane of medical images is essential. Genrative adversarial network (GAN) is an unsupervised deep learning model, which is widely used in the synthesis of medical images. In this research, paired data set which has MRI images of brain is used to compare the ability of transforming T1 of T2 images by pix2pix and cycleGAN. Peak signal to ratio (PSNR) and Mean absolute error (MAE) are used to evaluate the quantity of predicted T2 images. The weight of idenitity loss and hyperpremeters are adjusted to explore a better model of cycleGAN. The conclusion is that cycleGAN with low weight of identity loss is better than that with high weight of identity loss.
Natural language processing: mining adverse drug reactions from medical texts

Adverse drug reaction detection has always been a medical challenge. However, social media can uncover more information about adverse reactions that go unnoticed than traditional clinical reports. In this work, we focused on a dataset on adverse drug reactions obtained from Twitter. We define this problem as a sentiment classification problem and test the performance of machine learning models, convolutional neural networks (CNN), and recurrent neural networks (RNN) on this problem. Moreover, we try to find the ideal architecture to optimize the performance of the neural network by ablation experiments.
Simultaneous cooling and trapping of atoms by a single cavity-field mode

The optical dipole trap scheme is generalized by considering the laser as a dynamical cavity field mode. For a large enough finesse, the far-detuned trapping field itself exerts a significant friction force on the atom. Unlike in free-space far-off resonance dipole traps, here the trapping is stable in the steady state. The scheme in principle applies to arbitrary linearly polarizable particles, e.g., molecules.
Robust TDOA-Based Indoor Localization Using Improved Clock-Sync-Scheme and Multilevel Constrained ARPF

The need for indoor positioning research is driven by the contradiction between the lack of satisfactory location information available indoors and the emergence of an increasing number of indoor location-based services. The ability of ultrawideband (UWB) technology to effectively estimate the signal arrival time and thereby obtain highly accurate ranging information makes it a research hotspot for indoor positioning systems. However, the scalability, user capacity, and ranging performance degradation under nonline-of-sight (NLOS) conditions are challenges that hinder its wide application. To address these issues, this article proposes an improved highly available indoor positioning system that uses a time difference of arrival (TDOA)-based UWB. Within this system, a novel UWB wireless clock synchronization scheme was designed to reduce synchronization errors, improve ranging accuracy, reduce synchronization frequency, and allocate more channel time for positioning. To identify observations with NLOS errors and mitigate their effects on localization, this article implements an adaptive robust particle filtering (ARPF) algorithm based on multiple robustness factors. The multilevel constrained ARPF considers information, such as signal quality, historical observations, and floor map. In a real-world environment, the proposed method is tested using multiple forms of tag devices. The results show that the proposed method outperforms the general particle filter (GPF), cutting the relative error by about the half, especially in the worst badge tests.
A Standardized Protocol for Assuring the Validity of Proteomics Results from Liquid Chromatography–High-Resolution Mass Spectrometry

Significant advances in the technological development of mass spectrometry in the field of proteomics and the generation of extremely large amounts of data require a very critical approach to assure the validity of results. Commonly used procedures involved liquid chromatography followed by high-resolution mass spectrometry measurements. Proteomics analysis is used in many fields including the investigation of the metabolism of biologically active substances in organisms. Thus, there is a need to care about the validity of the obtained results. In this work, we proposed a standardized protocol for proteomic analysis using liquid chromatography–high-resolution mass spectrometry, which covers all of these analytical steps to ensure the validity of the results. For this purpose, we explored the requirements of the ISO/IEC 17025:2017 standard as a reference document for quality control in biochemistry research-based mass spectrometry.
CompCube: A Space-Time-Request Resource Trading Framework for Edge-Cloud Service Market

As the footing stone of artificial intelligence (AI), ubiquitous computing resource is beginning to receive interest. With this trend, a new form of edge-cloud service market dedicated to collecting, trading, and scheduling computing resources is rising. The computing participants in the service market, as providers and demanders of computing resources, are becoming more diversified and open. As such, the intriguing economic phenomenon and the circulation mechanism have emerged. These bring inherent challenges, such as a volatile market, the ossification of pricing, isolation, and inefficiency. In this article, we propose a novel space-time-request trading framework for the edge-cloud service market, namely CompCube. To ensure stability, CompCube adopts the dual-circulation futures-spot trading method, including space-time dynamic pricing in the macro-cycle, request intention conversion, and resource matching in the micro-cycle. Among this, an incomplete information game model is designed to determine the long-term trading pricing in the macro-cycle. Then, to tackle the indicator isolation problem due to the inconsistency between the user's requests and the computing-power provider's (CPP’s) resources, we focus on minimizing the rental cost of computing resources while satisfying diverse service level agreements (SLA) of users. To address this problem, a spatiotemporal scale Lyapunov optimization and an alternating actor-critic algorithm, A2SC, are developed. Besides, in the micro-cycle, a discriminatory double auction helps to determine the computing resource matching results efficiently and impersonally. We evaluate the CompCube of the A2SC algorithm with realistic datasets. Compared to other baselines, i.e., DYRECEIVE, Price Preferred, and Random, A2SC reduces the average rental cost by 30.45%, 5.74%, and 17.57%, respectively. Furthermore, CompCube can improve SLA satisfaction, as well as promote resource efficiency and social welfare compared with the traditional methods.
A homogenized model accounting for dispersion, interfaces and source points for transient waves in 1D periodic media

A homogenized model is proposed for linear waves in 1D microstructured media. It combines second-order asymptotic homogenization (to account for dispersion) and interface correctors (for transmission from or towards homogeneous media). A new bound on a second-order effective coefficient is proven, ensuring well-posedness of the homogenized model whatever the microstructure. Based on an analogy with existing enriched continua, the evolution equations are reformulated as a dispersive hyperbolic system. The efficiency of the model is illustrated via time-domain numerical simulations. An extension to Dirac source terms is also proposed.
Pico calorimeter for detection of heat produced in an individual brown fat cell

A pico calorimeter with a highly sensitive sensor for detecting heat from a biological cell is developed and evaluated, and also the heat detection of a single brown fat cell has been demonstrated. The measurement principle relies on resonant frequency tracking of a resonator in temperature variation due to the heat from the sample; the resonator is placed in vacuum, and heat is conducted from the sample in the microfluidic channel via a heat guide. This configuration can prevent heat loss from the resonator to the surroundings and damping in water. The heat resolution of the fabricated sensor is 5.2 pJ. Heat emissions from single cells are detected as pulsed or continuous in the absence and presence of stimulation, respectively.
Insights from an Exploratory Retrospective Cohort Study: Are Face-to-Face Follow-Up Consultations after Colonoscopy a Thing of the Past?

Background: Colonoscopy is a commonly performed procedure, but most patients will not actually be found with colorectal cancer. Subsequent face-to-face consultations to explain post-colonoscopy findings are common despite the time and cost-saving benefits of teleconsultation, especially in a post-COVID-19 era. This exploratory retrospective study examined the proportion of post-colonoscopy follow-up consultations that could have been converted to teleconsultation within a tertiary hospital in Singapore. Methods: A retrospective cohort of all patients who underwent colonoscopy in the institution from July to September 2019 was identified. All follow-up face-to-face consultations related to the index colonoscopy from the scope date to 6 months post-colonoscopy were traced. Clinical data relevant to the index colonoscopy and these consultations were extracted from electronic medical records. Results: The cohort consisted of 859 patients (68.5% male, age range: 18–96 years). Of these, 15 (1.7%) had colorectal cancer, but the majority (n = 643, 74.9%) were scheduled for at least one post-colonoscopy visit – a total of 884 face-to-face clinical visits. The final sample was 682 (77.1%) face-to-face post-colonoscopy visits that did not involve any procedures performed or indicated the need for any subsequent follow-up. Conclusion: If such “unnecessary” post-colonoscopy consultations exist within our institution, then similar situations possibly occur elsewhere. As COVID-19 continues to periodically tax healthcare systems worldwide, preservation of resources will remain integral alongside quality standards of routine patient care. There is a need for detailed analyses and modeling to hypothesize potential savings by also considering the start-up and maintenance costs of switching to a teleconsultation-dominated system.
Advances in treating HIV-1 infections

The first case of HIV infection had appeared and was diagnosed in the last century, the 1980s. From then on, this virus comes into people's view and gradually catches scientists' attention. This type of virus infects people by targeting the T cells in people's immune system, and it may develop AIDS, which is a deadly disease that has a high fatality rate and has no cures currently. People with AIDS will have an under-functioning immune system that could be easily infected by other lethal pathogens and then cause severe symptoms and irreversible damage to the human body. Existing research from the global shows that a treatment called antiretroviral therapy has a positive effect on controlling HIV infection hence reducing the probability of developing AIDS. However, many problems still have not been solved until now, for example, the development of drug resistance, and the side effects of drugs act on patients, also there are currently no effective medicines that can be used to cure the HIV-1 infection has been discovered. This paper reviews relevant literature and reviews this virus and disease based on the latest consensus globally, to increase the understanding of HIV infection and lay a foundation for future drug research and clinical treatment.
Relative Individual Sprint in Most Demanding Passages of Play in Spanish Professional Soccer Matches

(1) Background: The objective of this research was to analyse the most demanding passages (MDP) considering the sprint variable relative to the maximum level of sprint ability of each player as a function of player position, final outcome and part of the match during the competitive phase of a professional soccer season. (2) Methods: Global positioning system (GPS) data were collected from 22 players according to their playing position in the last 19 match days of the Spanish La Liga professional soccer in the 2020/2021 season. MDP were calculated from 80% of the maximum sprint speed of each player. (3) Results: Wide midfielders covered the greatest distance at >80% of the maximum speed (2.4 ± 1.63 seg) and the longest duration (21.91 ± 13.35 m) in their MDP. When the whole team was losing, it demonstrated greater distances (20.23 ± 13.04 m) and longer durations (2.24 ± 1.58 seg) compared to games in which it was winning. When the team ended up drawing, the relative sprint distance covered in the second half was significantly greater than in the first (16.12 ± 21.02; SD = 0.26 ± 0.28 (−0.03/−0.54). (4) Conclusions: Different demands of MDP, according to the sprint variable relative to the maximum individual capacity in competition, are required when contextual game factors are considered.
Fano resonances and topological optics: an interplay of far- and near-field interference phenomena

Fano resonances and optical vortices originate from two types of interference phenomena. Usually, these effects are considered to be completely independent, and in many cases Fano resonances are observed without any link to vortices, as well as vortices with a singular phase structure that are not accompanied by Fano resonances. However, this situation changes dramatically when we study light scattering at the nanoscale. In this paper, we demonstrate that Fano resonances observed for light scattering by nanoparticles are accompanied by the singular phase effects usually associated with singular optics, and we introduce and describe optical vortices with characteristic core sizes well below the diffraction limit.
I am mine: From phenomenology of self-awareness to metaphysics of selfhood

I aim to show that, contrary to standard deflationary or eliminativist theories of the self, we can argue from the phenomenology of pre-reflective self-awareness for the thesis that subjects of experience are substances. The phenomenological datum of subjectivity points to a specific metaphysical structure of our experience, that is, towards the substance view rather than the bundle or the minimal self view. Drawing on modern philosophical accounts of pre-reflective self-awareness, mineness and (self-) acquaintance, I will argue that a subject is aware of being the one individual who has many experiences and that it is revealed to the subject that it is the bearer of experiences and their unifier. The subject is present in pre-reflective awareness and known as the subject of experiences, and even this minimal self-awareness gives us reason to favour the substance view. Thus, one can demonstrate how the debates on the phenomenology of pre-reflective self-awareness and the metaphysics of selfhood intersect.