Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance evaluation of an architecturally-designed vertical high capacity linear slot diffuser in a tropical atrium

This paper proposed a new approach for the efficient air conditioning of large tropical buildings. The current study has two objectives: the design and numerical investigations of the performance of vertically oriented high capacity linear slot diffusers (HCLSD) in an atrium building and the verification and validation of the different turbulence models through laboratory-scale experiments. The HCLSD was investigated with varying angles of inclination of the blades (ϕ = 0o to 25o) for the in-depth performance analyses. The performance was evaluated by monitoring and comparing the velocity and temperature profiles along the vertical lines drawn at different locations in the studied domain. A relatively longer jet throw was noticed through quantitative analysis at ϕ = 0o. Note that more than 33% increment in the face velocity was recorded at this angle. The corresponding terminal velocity of 0.225 m/s was observed at 8 m distance from the diffuser face. The detailed investigations at 0o deflector angle (case-1) were carried out for velocity, temperature field, and thermal comfort indices, i.e. PMV and PPD models. For the occupied zone, the thermal comfort indices were found within the acceptable ranges (i.e. PMV = + 0.1 to +0.9 and PPD = 4% to 20%). Abbreviations: ACMV: Air conditioning and mechanical ventilation; CFD: Computational fluid dynamics; CMH: Cubic meter per hour; DV: Displacement ventilation; HCLSD: High capacity linear slot diffuser; IAQ: Indoor air quality; MV: Mixing ventilation; PMV: Predicted mean vote; PPD: Predicted percentage dissatisfied; RANS: Reynolds-Averaged Navier – Stokes; RNG: Re-Normalization Group; SST: Shear-Stress Transport: SIMPLE: Semi-implicit method for pressure linked equations; VAV: Variable air volume; VSD: Variable speed drives
Multiple founding paternal lineages inferred from the newly-developed SNPSeqTyper 639 Y-SNP panel suggested the complex admixture and migration history of Chinese people

Non-recombining regions of the Y-chromosome are inherited male-specifically and recorded the evolutionary traces of male human populations. Recent whole Y-chromosome sequencing studies have identified previously unrecognized population divergence, expansion and admixture processes, which promotes a better understanding and application of the observed patterns of Y-chromosome genetic diversity. Here, we developed one highest-resolution Y-SNP panel for forensic pedigree search and paternal biogeographical ancestry inference, which included 639 phylogenetically informative SNPs (Y-SNPs). We genotyped these loci in 1033 Chinese male individuals from 33 ethnolinguistically diverse populations and identified 257 terminal Y-chromosomal lineages with frequency ranging from 0.010 (singleton) to 0.0687. We identified six dominant common founding lineages associated with different ethnolinguistic backgrounds, which included O2a2b1a1a1a1a1a1a1-M6539, O2a1b1a1a1a1a1a1-F17, O2a2b1a1a1a1a1b1a1b-MF15397, O2a2b2a1b1-A16609, O1b1a1a1a1b2a1a1-F2517 and O2a2b1a1a1a1a1a1-F155. The AMOVA and nucleotide diversity estimates revealed considerable differences and high genetic diversity among ethnolinguistically different populations. We constructed one representative phylogenetic tree among 33 studied populations based on the haplogroup frequency spectrum and sequence variations. Clustering patterns in principal component analysis and multidimensional scaling results showed a genetic differentiation between Tai-Kadai-speaking Li, Mongolic-speaking Mongolian and other Sinitic-speaking Han Chinese populations. Phylogenetic topology inferred from the BEAST and Network relationships reconstructed from the popART further showed the founding lineages from culturally/linguistically diverse populations, such as C2a/C2b was dominant in Mongolian people and O1a/O1b was dominant in island Li people. We also identified many lineages shared by more than two ethnolinguistically different populations with a high proportion, suggesting their extensive admixture and migration history. Our findings indicated that our developed high-resolution Y-SNP panel included major dominant Y-lineages of Chinese populations from different ethnic groups and geographical regions, which can be used as the primary and powerful tool for forensic practice. We should emphasize the necessity and importance of whole-sequencing of more ethnolinguistically different populations, which can help identify more unrecognized population-specific variations for the final promotion of Y-chromosome-based forensic applications.
Progressive spreading of DNA methylation in the GSTP1 promoter CpG island across transitions from precursors to invasive prostate cancer

Glutathione S-transferase pi 1 (GSTP1) is lowly expressed in normal prostate luminal cells and becomes induced in most proliferative inflammatory atrophy lesions (PIA). GSTP1 becomes silenced in prostatic intraepithelial neoplasia (PIN) and prostate adenocarcinoma (CaP) via cytosine-phospho-guanine (CpG) island promoter hypermethylation. However, GSTP1 methylation patterns in PIA and PIN, and their relationship to patterns in CaP are poorly understood. We used bisulfite genomic sequencing to examine patterns of GSTP1 promoter CpG island methylation in laser capture microdissected benign, PIA, PIN, and CaP regions from 32 subjects that underwent radical prostatectomy. We analyzed 908 sequence clones across 24 normal epithelium, 37 PIA, 18 PIN, and 23 CaP regions, allowing assessment of 34,863 CpG sites with allelic phasing. Normal and PIA lesions were mostly unmethylated with 0.52 and 1.3% of total CpG sites methylated, respectively. PIN and CaP lesions had greater methylation with 24% and 51% of total CpG sites methylated, respectively. The degree of GSTP1 methylation showed progression from PIA ≪ PIN < CaP. PIN lesions showed more partial methylation compared to CaP lesions. Partially methylated lesions were enriched for methylation changes at AP1 and SP1 transcription factor binding sites. These results demonstrate that methylation density in the GSTP1 CpG island in PIN was intermediate relative to that in normal prostate epithelium/PIA and CaP lesions. These results are consistent with gradual spreading of DNA methylation centered at the SP1/AP1 transcription factor binding sites in precursor lesions, with subsequent spreading of methylation across the entire CpG island in transition to CaP.
Test-Retest Reliability of the Human Connectome: An OPM-MEG study

Magnetoencephalography with optically pumped magnetometers (OPM-MEG) offers a new way to record electrophysiological brain function, with significant advantages over conventional MEG including adaptability to head shape/size, free movement during scanning, better spatial resolution, increased signal, and no reliance on cryogenics. However, OPM-MEG remains in its infancy, with significant questions to be answered regarding optimal system design and robustness. Here, we present an open-source dataset acquired using a newly constructed OPM-MEG system with a triaxial sensor design averaging 168 channels. Using OPM-optimised magnetic shielding and active background-field control, we measure the test-retest reliability of the human connectome. We employ amplitude envelope correlation to measure whole-brain functional connectivity in 10 individuals whilst they watch a 600 s move clip. Our results show high repeatability between experimental runs at the group level, with a correlation coefficient of 0.81 in the theta, 0.93 in alpha and 0.94 in beta frequency ranges. At the individual subject level, we found marked differences between individuals, but high within-subject robustness (correlations of 0.56 ± 0.25, 0.72 ± 0.15 and 0.78 ± 0.13 in theta, alpha and beta respectively). These results compare well to previously reported findings using conventional MEG; they show that OPM-MEG is a viable way to characterise whole brain connectivity and add significant weight to a growing argument that OPMs can overtake cryogenic sensors as the fundamental building block of MEG systems.
Multiomic Analysis of Adult Diapause in Drosophila melanogaster Identifies Hallmarks of Cellular Quiescence

Age is a fundamental aspect of biology that underlies the efficacy of a broad range of functions. Identifying determinants for how quickly or slowly we age will contribute greatly to our understanding of age as a modifier of overall health, particularly to the advancement of therapeutic interventions designed to mitigate or delay age-associated disorders. While much work has been devoted to the study of genetic or pharmacological interventions that extend lifespan, this approach does not necessarily recapitulate the physiological profile of naturally long-lived individuals. Diapause and diapause-like states constitute natural, inducible and evolutionarily conserved examples of lifespan plasticity that are well-suited to serve as physiologically accurate models of longevity. Here, we leveraged a metabolically critical signaling organ in Drosophila, the fat body, to examine diapause-associated transcription in the context of chromatin accessibility and the regulation of lifespan. Through a combination of ATAC-seq and RNA-seq, our observations suggest chromatin is globally reorganized in diapause and may assume a poised conformation to facilitate the rapid transcription of pro-development genes upon diapause termination. We found particular significance of GAF, NELF, and RNA polymerase III in this context. Congruently, transcription during diapause appears to favor many processes supporting the maintenance of cellular quiescence and the inhibition of differentiation. Our data are consistent with a model wherein diapause induces cellular quiescence in the fat body, as was additionally supported through fluorescent microscopy and comparison with public ChIP-seq data for developmentally juvenile files. This work opens the possibility that longevity in diapause may be partially determined through a lack of mitogenic signaling from the quiescent niche, concurrent with changes to the hormonal and immunological profiles that skew metabolism towards tissue maintenance.
Investigating the Similarity of Court Decisions

The association between words, phrases, and documents is referred to as semantic similarity. Semantic similarity has played a significant role in internet search engines regarding content ranking. It also has wide applications in information retrieval, artificial intelligence, etc., to name a few. This paper reviews the general architecture, categorization of approaches, and techniques and metrics for determining semantic similarity between documents in a comprehensive way. We have conducted experiments on the different statistical methods, viz., word vector-based techniques (TF-IDF, LDA, Word2Vec, Doc2Vec, Glove, and fastText), and transformer-based techniques (Longformer-base, Sentence-BERT-large-nli, Sentence-BERT-large-nli-stsb, and Sentence-RoBERTa-large-nli-stsb) over Indian Supreme Court decisions and discussed the results. The Doc2Vec approach over the whole document is found to correlate the most with the expert judgment.
Towards a multi-faceted framework for planning and evaluating innovation in Engineering Education

For universities, educational change at institutional level is a slow process [1], [2]. To keep up with societal and technological advancement, education innovation project leaders at universities need practical guidelines and procedures in place that will enable sustainable and scalable innovation that can meet the needs of industry as we transition from Industry 4.0 to Industry 5.0 [3]. To develop such guidelines and procedures, we need to conduct socially responsible, evidence-based educational research [4]. This paper is part of a larger study during which we will conceptualize the planning and evaluation of innovation in engineering education at the Delft University of Technology (TU Delft). From this conceptualization, a framework for planning and evaluation of education innovation will emerge. The data collection process will take place in six phases: (1) Exploration of the problem (2) feasibility studies; (3) conceptualization and development of the framework; (4) piloting of the framework and its associated processes; (5) field study; and lastly, (6) evaluation of the framework. This paper provides an initial overview of the literature, as well as an explanation of the proposed research methodology.
Detecting Lies in the Wild: Creativity and Learning @ the Maker Faire Rome

Creativity is one of the most powerful skills humans can rely on to overcome daily challenges. While most of the research has focused on the positive facet of creativity, like problem-solving and art, a few contributions explored its dark side: lying and deception. Virtual and embodied intelligent agents approaching the real world will soon face humans’ deception with poor means to understand and unmask it. In a previous study, we asked participants to describe a set of gaming cards to the humanoid robot iCub, either describing what they saw or producing a creative and deceiving description; The robot autonomously classified players’ behavior with a pupillometry-based heuristic method. After collecting an in-laboratory dataset, we trained a Random Forest classifier enabling the humanoid robot iCub to detect lie-related creativity autonomously during informal human-robot interactions. In this manuscript, aiming at real-world applications, we challenged our classifier on a diametrically opposite environment: the Maker Faire Rome 2022. Moreover, we compared its performance with respect to an Adaptive Random Forest twin, able to learn online after each interaction. The performance of the two models and the detection of concept and data drift give relevant insight into how adaptivity would be the key to developing more effective intelligent agents.
Effects of Display Modulation Transfer Function with Different Subpixel Layouts on Subjective Spatial Resolution

Although a typical display consists of red-green-blue (RGB) subpixels, displays with various subpixel layouts have been used owing to their various advantages such as luminous efficiency. The purpose of this study is to verify the effects of display MTF on subjective spatial resolution by creating new subpixel layouts. We designed BRGRB and BRGRB525 subpixel layouts with slightly higher and much higher MTF than RGB subpixel layouts, and conducted visual evaluation experiments with RGB, PenTile RGBG and the two new subpixel layouts at 20 and 30 cycles per degree. It was verified that subjective spatial resolution generally follows the large and small relationship of display MTF. Additional experiments showed that the integral of the product of the contrast sensitivity function and MTF was highly correlated with the subjective spatial resolution.
Towards a computer-assisted Computational Thinking assessment system in higher education

With the vision to promote CT to a wider group of audiences, this PhD project explores the formative assessment of CT skills in Programming Education to support students to learn CT skills in Higher Education. In this project, we plan to investigate the importance of CT in the context of Higher Education, explore the relationship between CT skills and programming skills, build a model to assess learners’ CT skills and develop a computer-assisted assessment system with automated components to enhance students’ CT competences in Higher Education. Mixed-method research methodologies will be employed in distinct phases of the project accordingly. A system which allows formative assessment of CT skills will be iteratively designed and constructed throughout the project. The outcome of the project should support the CT learning process, make CT more visible for people from diverse backgrounds and empower them with a CT mindset to embrace the digitalization of society.
A SEARCH FOR GALAXIES PRODUCING METAL-RICH QUASAR ABSORBERS

We have carried out optical and near-IR imaging of three fields with metal-rich damped or sub-damped Lyα quasar absorption systems, using the Goddard Fabry–Pérot system and the Near-IR Camera and Fabry–Pérot Spectrometer at the Apache Point Observatory 3.5 m telescope. The aim of these observations was to detect the underlying galaxies and search for their redshifted [O ii] λ3727 emission and optical/near-IR continuum. Candidate absorber galaxies separated by 2. ″5–8. ″8 from the quasars are detected in two of three absorber fields in the H and KS bands at >3σ level. The potentially high success rate in finding galaxy counterparts of metal-rich absorbers suggests that the metal-rich absorbers may be easier to detect in imaging observations than the metal-poor absorbers targeted in many previous imaging studies of damped Lyα absorbers. Of course, spectroscopic confirmation of the candidate galaxies is necessary to establish whether they are at the absorber redshifts. Interestingly, no significant [O ii] emission is detected in any of the fields at >3σ level, implying limits on the star formation rate (SFR) of 0.7–2.6 M☉ yr−1 per 0. ″76 × 0. ″76 region, if no dust extinction is assumed. The 3σ sensitivity levels in the narrowband images (tuned to the expected positions of the redshifted [O ii] λ3727) ranged between 1.3 × 10−17 and 3.3 × 10−17 erg s−1 cm−2 in observed frame. If the candidate galaxies are at the absorber redshifts, the lack of [O ii] emission would suggest that the metal-rich absorbers may arise in early-type or S0 galaxies that do not have significant “current” star formation. We compare our results with those compiled from the literature and with predictions of global average SFR based on the models of cosmic chemical evolution. Together, these studies indicate SFRs much lower than the predictions for the global mean SFR.
Faulted Line-Section Location in Distribution System With Inverter-Interfaced DGs Using Sparse Meters

This paper proposes a faulted line-section location method using sparse meters for the distribution networks (DNs) with high penetration of inverter interfaced distributed generations (IIDGs). By modeling the IIDGs as equivalent impedances instead of current sources, the fault component model of the DN with IIDGs can be transferred from a multi-current feeding system towards the sole-current feeding system. On this basis, the Bayesian Compressed Sensing (BCS) algorithm is applied to achieve the sparse solution of the fault current to indicate the faulted line-section. Moreover, to reduce the required meters for monitoring the IIDGs, a node partition scheme is designed based on the analysis of IIDG with different control strategies. The proposed fault location method requires only 15 meters for an IEEE 69-node distribution network with 20 IIDGs. Simulation results show that the location success rate is beyond 95% for various fault scenarios which is a 55% improvement over the existing BCS-based method.
Effect of Armature Reaction on Asymmetric PM Loss and Temperature Distributions in V-shape Interior Permanent Magnet Synchronous Machines

In this paper, the effect of armature reaction on asymmetric distributions of permanent magnet (PM) eddy current loss and temperature in a double-layer V-shape interior permanent magnet synchronous machine (IPMSM) for electric vehicles is investigated. Lumped parameter thermal network model and analytical method are established to predict the average temperature distribution and identify the hotspot in the winding. 2D finite element analysis (FEA) is used to calculate PM eddy current loss distributions and other loss density distributions, which are coupled into the 3D thermal FEA model to investigate the PM temperature distribution. It reveals that the phase currents with different advancing angles lead to asymmetric eddy current loss and thermal distributions among PMs of the same pole.
Development of Reference Current Calculation Scheme for Grid-Side Converter during Unbalanced Faults

The share of renewable energy is increasing day by day. The European Union set its target to double the share of solar and wind power by 2025 and to triple it by 2030. The renewable energy sources are mostly connected to the grid with converters. Due to the large penetration of the converters, the grid operators demand a specific negative sequence current injection from the converters for the safe and reliable operation. The grid codes define the response of the grid connected converters in case of a fault. The conventional control scheme of the converter is unable to operate properly in unbalanced situations. This paper presents a new control scheme for generating the reference converter’s current consisting of positive and negative sequences while ensuring the safety of the converter. It is capable of injecting the negative sequence current to fulfil the recent grid codes, in addition, it complies with the converter’s current limitation. The conventional and proposed methods are compared for different types of unbalanced faults. The results demonstrate the capability of the proposed scheme to fulfil the recent grid code requirements while ensuring the safe operation of the converter.
TDOA-based Target Localization Under Distance-dependent Noise Model

This paper focuses on target localization utilizing time difference of arrival (TDOA) measurements in 2-dimensional spaces. Differently from existing researches that the variance of TDOA measurement noise is independent of sensor-to-target distance, we set up the more practical model under the model of the distance-dependent noises. Firstly, we derive maximum likelihood estimator (MLE) and the Cramer-Rao lower bound (CRLB). Then, this instrumental variable (IVE) and this pseudolinear estimator (PLE) are introduced. Finally, simulation results show the bias norm and RMSE performance of PLE, IVE and MLE, and compared with the CRLB.
Research on fire detection based on YOLOv5

Fire is a frequent and hugely harmful disaster accident in people's daily life, which will seriously threaten people's life and property safety. Therefore, fire detection is very important in safety inspection, and people can effectively reduce losses based on early warning. Traditional fire detection methods have obvious limitations, such as temperature detectors, smoke detectors, thermal cameras, etc. These devices are often expensive, vulnerable, inaccurate, and prone to excessive false positives. In recent years, human beings have entered a highly information age. Fire detection technology based on computer vision has begun to enter people's field of vision, especially the rapid development of deep learning provides a new direction for fire detection. In recent years, human beings have entered a highly information age. Fire detection and monitoring platforms based on UAV technology, 5G technology, ultra-broadband transmission technology, and high-speed Internet of Things technology are more and more widely used. Although this solves the problem of the data transmission rate, the detection performance of the terminal needs to be improved. Fire detection technology based on computer vision has begun to enter people's field of vision, especially the rapid development of deep learning provides a new direction for fire detection. This paper first analyzes the advantages and disadvantages of four commonly used deep learning-based target detection algorithms, then uses the latest YOLOv5 target detection algorithm for experiments, and finally uses PyQT5 to make a fire detection system demo. The experimental results show that fire detection based on YOLOv5 can achieve better detection accuracy.