Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Bone-Conducted Cross-Talk Sound in the Head for Biometric Identification

Just like a fingerprint, every human head has its own uniqueness. To take advantage of its unique geometrical and physical characteristics, we can insert an inward-facing microphone into the ear canal to record sound coming from a bone conduction transducer on the mastoid on the contralateral side of the head. This sound is known as “cross-talk” sound, which is unique for each individual. In this study, we present an evaluation of bone-conducted “cross-talk” sound in the head for biometric user identification. Our approach relies on “cross-talk” sounds to estimate impulse responses (IRs) and uses them to identify the corresponding users. Mel frequency cepstral coefficients (MFCCs) are extracted from a 16-ms IR as acoustic features, and 1-nearest neighbor (1NN) classifier is used for making a decision. Finally, we evaluated the proposed approach with ten participants. Our results showed that “cross-talk” sounds could be used to identify users with an average accuracy of up to 99.8%, and the equal error rate (EER) obtained was 2.6% in user authentication. In addition, the IRs dataset and a video demonstrating how the system worked were made available on GitHub and YouTube.
Feature-Interaction Sampling for Scenario-based Testing of Advanced Driver Assistance Systems✱

Scenario-based testing is considered state-of-the-art to verify and validate Advanced Driver Assistance Systems. However, two essential unsolved challenges prevent the practical application of scenario-based testing according to the SOTIF-standard: (1) how to select a set of representative test scenarios, and (2) how to assess the effectiveness of a test scenario suite. In this paper, we leverage variability modelling techniques to select scenarios from a scenario space and assess the resulting scenario suites with a mutation score as metric. We capture the scenario space in a feature model and generate representative subsets with feature-interaction coverage sampling. The mutation score assesses the failure-finding effectiveness of these samples. We evaluate our concepts by sampling scenario suites for two independent Autonomous Emergency Braking function implementations and executing them on an industrial-strength simulator. Our results show that the feature model captures a scenario space that is relevant to identify all mutants. We show that sampling based on interaction coverage reduces the testing effort significantly while maintaining effectiveness in terms of mutation scores. Our results underline the potential of feature model sampling for testing in the automotive industry.
Software safety test case design method based on Fuzzy Fault Tree Analysis

Aiming at the problems of insufficient software safety testing and incomplete aerospace data, combined with fuzzy set theory, a design methodology for safety test cases of aerospace software is proposed. A fuzzy fault tree of aerospace software is established on the basis of fault tree analysis technology and expert investigation method, the trapezoidal fuzzy numbers are used to replace the failure probabilities of the bottom events, and then obtain the minimum cut sets through the qualitative analysis of the fault tree, the minimum safety test cases is designed according to the minimum cut sets. Finally, different test cases are prioritized by the cut set importance results calculated by the quantitative analysis of the fuzzy fault tree. According to the experimental results, the proposed method provides a reference for improving the safety of the aerospace system while reducing the number of test cases and ensuring the sufficiency and efficiency of the software safety test cases.
Medical Subject Headings (MeSH) Indexing Using Unsupervised Learningfor Low-resource Controlled Vocabulary

Medical subject heading indexing is a process to assign Medical Subject Headings (MeSH) to the biomedical literatures, such as abstracts or articles. The indexing process was done manually by human MeSH indexer. There is also indexing that was done by machine learning algorithms like supervised learning. Both of processes requires MeSH labels or terms to be assigned manually to an articles, which is a tedious task and requires a lot of hand-crafted labels from domain experts. In order to do MeSH indexing without manually assigned labels, the unsupervised learning algorithm like LDA (Latent Dirichlet allocation) was performed and analyzed. LDA is kind of unsupervised learning, which can generate topics in a collection of texts, and then automatically classify any individual texts within the collection into a relevant generated topics. In term of MeSH indexing, topic in LDA is a MeSH label or term. LDA was able to generate topics from biomedical literatures with high similarity, which is 74% similar to MeSH terms provided by domain experts. We confirmed that unsupervised learning algorithm like LDA is a promising approach for MeSH indexing with a lack of MeSH labels provided by a domain experts.
Having the ‘right’ microbiome matters for host trait expression and the strength of mutualism between duckweeds and microbes

An organism’s phenotypes and fitness often depend on interactive effects of its genome (Ghost), microbiome (Gmicrobe), and environment (E). These G xG, G xE, and G xG xE effects fundamentally shape host-microbiome (co)evolution and may be widespread, but are rarely compared within a single experiment. We collected and cultured Lemna minor (duckweed) and its associated microbiome from 10 sites across an urban-to-rural ecotone. We factorially manipulated host genotype and microbiome in two environments (low and high zinc, an urban aquatic stressor) in an experiment with 200 treatments: 10 host genotypes × 10 microbiomes × 2 environments. Host genotype explained the most variation in L. minor fitness and traits, while microbiome effects depended on host genotype (G xG) or environment (G xE). Hosts had higher fitness and microbes grew fastest when tested microbiomes more closely matched field microbiomes, suggesting some local adaptation between hosts and their microbiota. High microbiome similarity also led to more predictable host trait expression. In contrast, although zinc decreased host fitness, we observed no local adaptation of urban duckweed or microbes to high-zinc conditions. Thus, we found that host fitness and trait expression are contingent on microbiome composition, with implications for microbiome engineering and host-microbiome evolution.
First whole-genome sequence of Cervid atadenovirus A outside of the United States from an Adenoviral hemorrhagic disease epizootic of black-tailed deer in Canada

A complete 30,616 nucleotide Cervid atadenovirus A genome was determined from tissues of a black-tailed deer that died in 2020 in British Columbia, Canada. Unique, non-synonymous SNPs in the E1B, Iva2 and E4.3 coding regions, and deletions totalling 74 nucleotides not observed in moose and red deer isolates were present.
Does Financial Technology Improve Health in Asian Economies?

The progress of the health sector in a sustainable manner is crucial for the development of human capital, a significant and vital driver of economic growth. Hence, we aim to investigate the impact of FinTech on health outcomes in Asian economies over the period 2007–2019. The empirical estimation of the study is based on the 2SLS and GMM techniques. The outcomes confirmed the negative impact of ATMs and Debit cards on the infant mortality rate in both 2SLS and GMM models. Whereas, ATMs and Debit cards positively impact the life expectancy of people living in Asian economies irrespective of the estimation technique. Similarly, the association between the Internet and infant mortality rate is negative; whereas, this association is positive in the context of the Internet and life expectancy both with 2SLS and GMM. From these findings, we can confirm that the amalgamation of technology and the financial sector helps to improve health outcomes in Asian economies. Therefore, the integration of FinTech into the health sector should be part and parcel of every health policy in emerging Asian economies.
Rapid design and prototyping of biocatalytic virus-like particle nanoreactors

Protein cages are attractive as molecular scaffolds for the fundamental study of enzymes and metabolons, and for the creation of biocatalytic nanoreactors for in vitro and in vivo use. Virus-like particles (VLPs) such as those derived from the P22 bacteriophage capsid protein make versatile self-assembling protein cages and can be used to encapsulate a broad range of protein cargos. In vivo encapsulation of enzymes within VLPs requires fusion to the coat protein or a scaffold protein. However, the expression level, stability and activity of cargo proteins can vary upon fusion. Moreover, it has been shown that molecular crowding of enzymes inside virus-like particles can affect their catalytic properties. Consequently, testing of numerous parameters is required for production of the most efficient nanoreactor for a given cargo enzyme. Here we present a set of acceptor vectors that provide a quick and efficient way to build, test and optimise cargo loading inside P22 virus-like particles. We prototyped the system using yellow fluorescent protein then applied it to mevalonate kinases, a key enzyme class in the industrially important terpene (isoprenoid) synthesis pathway. Different mevalonate kinases required considerably different approaches to deliver maximal encapsulation as well as optimal kinetic parameters, demonstrating the value of being able to rapidly access a variety of encapsulation strategies. The vector system described here provides an approach to optimise cargo enzyme behaviour in bespoke P22 nanoreactors. This will facilitate industrial applications as well as basic research on nanoreactor-cargo behaviour.
Increased prevalence of a frontoparietal brain state is associated with better motor recovery after stroke affecting dominant-hand corticospinal tract

Strokes cause lesions that damage brain tissue, disrupt normal brain activity patterns and can lead to impairments in cognition and motor function. Although modulation of cortical activity is central to stimulation-based rehabilitative therapies, aberrant and adaptive patterns of brain activity after stroke have not yet been fully characterized. Here, we apply a brain dynamics analysis approach to study longitudinal brain activity patterns in individuals with ischemic pontine stroke. We first found 4 commonly occurring brain states largely characterized by high amplitude activations in the visual, frontoparietal, default mode, and motor networks. Stroke subjects spent less time in the frontoparietal state compared to controls. For individuals with dominant-hand CST damage, increased time spent in the frontoparietal state from 1 week to 3-6 months post-stroke was associated with better motor recovery over the same time period, an association which was independent of baseline impairment. Furthermore, the amount of time spent in brain states was linked theoretically and empirically to functional connectivity. This work suggests that when the dominant-hand CST is compromised in stroke, resting state configurations may shift to include increased activation of the frontoparietal network, which may facilitate compensatory neural pathways that support recovery of motor function when traditional motor circuits of the dominant-hemisphere CST are compromised.
Spatial patterns from a dispersal limitation perspective: revealing biotic interactions

Local spatial distributions of populations are often studied in comparison to Complete Spatial Randomness (CSR) and are found to be ubiquitously aggregated, likely due to dispersal limitation. Here we theoretically examine the advantages of comparing observed distributions to simulated populations subject only to drift and Dispersal Limitation (DL). Compared to this DL null, local competition produces overdispersion out to surprisingly large scales—much larger than the scale of competitive interactions. Furthermore, strong overdispersion provides a hallmark that a key requirement of stable coexistence is met, as it can only be observed if intraspecific competition is substantially stronger than interspecific competition. Dispersion compared to CSR is insensitive to competition and as a result unreflective of its presence. Hence, we suggest DL as a complement to CSR since the former focuses on biologically relevant spatial scales and has the potential to detect biotic interactions and habitat specificity.
RNA polymerase redistribution and increased gene dosage support growth in E. coli strains with a minimal number of ribosomal RNA operons

Bacterial transcription by RNA polymerase (RNAP) is spatially organised. RNAPs transcribing highly expressed genes locate in the nucleoid periphery, and form clusters in rich media, with several studies linking RNAP clustering and transcription of ribosomal RNA (rrn). However, the nature of RNAP clusters and their association with rrn transcription remains unclear. Here we address these questions by using single-molecule tracking to monitor the subcellular distribution of mobile and immobile RNAP in strains with a heavily reduced number of chromosomal rrn operons (Δrrn strains). Strikingly, we find that the fraction of chromosome-associated RNAP (which is mainly engaged in transcription) is robust to deleting 5 or 6 of the 7 chromosomal rrn operons. Spatial analysis in Δrrn strains showed substantial RNAP redistribution during moderate growth, with clustering increasing at the cell end-caps, where the remaining rrn operons reside. These results support a model where RNAPs in Δrrn strains relocate to copies of the remaining rrn operons. We also show that Δrrn strains experience increased rrn gene dosage in rich media, minimising growth defects due to rrn deletions. Our study further links RNAP clusters and rrn transcription, and offers insight on how bacteria maintain growth in the presence of only 1-2 rrn operons.
Altered Intra- and Inter-Network Connectivity in Drug-Naïve Patients With Early Parkinson’s Disease

The aim of our study was to investigate differences in whole brain connectivity at different levels between drug-naïve individuals with early Parkinson’s disease (PD) and healthy controls (HCs). Resting-state functional magnetic resonance imaging data were collected from 47 patients with early-stage, drug-naïve PD and 50 HCs. Functional brain connectivity was analyzed at the integrity, network, and edge levels; UPDRS-III, MMSE, MOCA, HAMA, and HAMD scores, reflecting the symptoms of PD, were collected for further regression analysis. Compared with age-matched HCs, reduced functional connectivity were mainly observed in the visual (VSN), somatomotor (SMN), limbic (LBN), and deep gray matter networks (DGN) at integrity level [p < 0.05, false discovery rate (FDR) corrected]. Intra-network analysis indicated decreased functional connectivity in DGN, SMN, LBN, and ventral attention networks (VAN). Inter-network analysis indicated reduced functional connectivity in nine pairs of resting-state networks. At the edge level, the LBN was the center of abnormal functional connectivity (p < 0.05, FDR corrected). MOCA score was associated with the intra-network functional connectivity strength (FC) of the DGN, and inter-network FC of the DGN-VAN. HAMA and HAMD scores were associated with the FC of the SMN and DGN, and either the LBN or VAN, respectively. We demonstrated variations in whole brain connections of drug-naïve patients with early PD. Major changes involved the SMN, DGN, LBN, and VSN, which may be relevant to symptoms of early PD. Additionally, our results support PD as a disconnection syndrome.
Effect of Early-Stage Human Breast Carcinoma on Monocyte Programming

Circulating monocytes are a major source of tumor-associated macrophages (TAMs). TAMs in human breast cancer (BC) support primary tumor growth and metastasis. Neoadjuvant chemotherapy (NAC) is a commonly used treatment for BC patients. The absence of the response to NAC has major negative consequences for the patient: increase of tumor mass, delayed surgery, and unnecessary toxicity. We aimed to identify the effect of BC on the subpopulation content and transcriptome of circulating monocytes. We examined how monocyte phenotypes correlate with the response to NAC. The percentage of CD14-, CD16-, CD163-, and HLA-DR-expressing monocytes was quantified by flow cytometry for patients with T1-4N0-3M0 before NAC. The clinical efficacy of NAC was assessed by RECIST criteria of RECIST 1.1 and by the pathological complete response (pCR). The percentage of CD14+ and СD16+ monocytes did not differ between healthy women and BC patients and did not differ between NAC responders and non-responders. The percentage of CD163-expressing CD14lowCD16+ and CD14+CD16+ monocytes was increased in BC patients compared to healthy women (99.08% vs. 60.00%, p = 0.039, and 98.08% vs. 86.96%, p = 0.046, respectively). Quantitative immunohistology and confocal microscopy demonstrated that increased levels of CD163+ monocytes are recruited in the tumor after NAC. The percentage of CD14lowCD16+ in the total monocyte population positively correlated with the response to NAC assessed by pCR: 8.3% patients with pCR versus 2.5% without pCR (p = 0.018). Search for the specific monocyte surface markers correlating with NAC response evaluated by RECIST 1.1 revealed that patients with no response to NAC had a significantly lower amount of CD14lowCD16+HLA-DR+ cells compared to the patients with clinical response to NAC (55.12% vs. 84.62%, p = 0.005). NGS identified significant changes in the whole transcriptome of monocytes of BC patients. Regulators of inflammation and monocyte migration were upregulated, and genes responsible for the chromatin remodeling were suppressed in monocyte BC patients. In summary, our study demonstrated that presence of BC before distant metastasis is detectable, significantly effects on both monocyte phenotype and transcriptome. The most striking surface markers were CD163 for the presence of BC, and HLA-DR (CD14lowCD16+HLA-DR+) for the response to NAC.
Cell Division Cycle-Associated Genes Are Potential Immune Regulators in Nasopharyngeal Carcinoma

Background Cell division cycle-associated (CDCA) gene family is essential to cell cycle regulation. Numerous studies have illuminated that dysfunction of CDCA genes may not only lead to uncontrolled cell proliferation resulting in tumorigenesis but also influence immune cell infiltration in tumors. However, the role of the CDCA gene family on the prognosis and immune infiltration in nasopharyngeal carcinoma (NPC) remains to be unclear. Methods SBC human ceRNA array V1.0 was used to measure mRNA expression in three pairs of NPC tissues and nasopharyngitis tissues. The expression of CDCA8 was confirmed in an IHC microarray containing 130 NPC patients. Two external GEO cohorts were enrolled for further analysis. Prognosis analysis was performed using the Kaplan–Meier method. Gene set enrichment analysis (GSEA) was applied to explore the potential mechanism of CDCA genes in NPC. The relationship between CDCA gene family and immune infiltration in NPC was evaluated using the Xcell tool. Results CDCA genes were broadly upregulated in NPC tissues compared to nasopharyngitis tissues, and high expression of CDCA3/5/8 indicated worse prognosis in NPC. Besides cell cycle pathways, we found that CDCA3/5/8 were involved in multiple immune-related pathways. Overexpression of CDCA8 was strongly associated with less infiltration of CD8+ T cells and more infiltration of CD4+ Th1 cells and was negatively correlated with immune checkpoint blockade (ICB)-related genes. Conclusion CDCA gene family was upregulated in NPC, and their expressions were associated with adverse prognosis. High expression of CDCA8 was associated not only with poor prognosis, but also with less immune infiltration and downregulation of ICB-related genes in NPC.
Concussion in Women's Flat-Track Roller Derby

Concussions are common among flat-track roller derby players, a unique and under-studied sport, but little has been done to assess how common they are or what players can do to manage injury risk. The purpose of this study is to provide an epidemiological investigation of concussion incidence and experience in a large international sampling of roller derby players. Six hundred sixty-five roller derby players from 25 countries responded to a comprehensive online survey about injury and sport participation. Participants also responded to a battery of psychometric assessment tools targeting risk-factors for poor injury recovery (negative bias, social support, mental toughness) and players' thoughts and feelings in response to injury. Per 1,000 athletes, 790.98 concussions were reported. Current players reported an average of 2.2 concussions, while former players reported 3.1 concussions. However, groups were matched when these figures were corrected for differences in years of play (approximately one concussion every 2 years). Other frequent injuries included fractures in extremities and upper limbs, torn knee ligaments, and sprained ankles. We found no evidence that players' position, full-contact scrimmages, or flooring impacted number of concussions. However, neurological history and uncorrected vision were more influential predictors of an individual's number of concussions during roller derby than years of participation or age, though all four contributed significantly. These findings should assist athletes in making informed decisions about participation in roller derby, though more work is needed to understand the nature of risk.
Sterol Metabolism Differentially Contributes to Maintenance and Exit of Quiescence

Nutrient starvation initiates cell cycle exit and entry into quiescence, a reversible, non-proliferative state characterized by stress tolerance, longevity and large-scale remodeling of subcellular structures. Depending on the nature of the depleted nutrient, yeast cells are assumed to enter heterogeneous quiescent states with unique but mostly unexplored characteristics. Here, we show that storage and consumption of neutral lipids in lipid droplets (LDs) differentially impacts the regulation of quiescence driven by glucose or phosphate starvation. Upon prolonged glucose exhaustion, LDs were degraded in the vacuole via Atg1-dependent lipophagy. In contrast, yeast cells entering quiescence due to phosphate exhaustion massively over-accumulated LDs that clustered at the vacuolar surface but were not engulfed via lipophagy. Excessive LD biogenesis required contact formation between the endoplasmic reticulum and the vacuole at nucleus-vacuole junctions and was accompanied by a shift of the cellular lipid profile from membrane towards storage lipids, driven by a transcriptional upregulation of enzymes generating neutral lipids, in particular sterol esters. Importantly, sterol ester biogenesis was critical for long-term survival of phosphate-exhausted cells and supported rapid quiescence exit upon nutrient replenishment, but was dispensable for survival and regrowth of glucose-exhausted cells. Instead, these cells relied on de novo synthesis of sterols and fatty acids for quiescence exit and regrowth. Phosphate-exhausted cells efficiently mobilized storage lipids to support several rounds of cell division even in presence of inhibitors of fatty acid and sterol biosynthesis. In sum, our results show that neutral lipid biosynthesis and mobilization to support quiescence maintenance and exit is tailored to the respective nutrient scarcity.