Miracle-dz/UniFAR-FTUs huggingface dataset:
Epidemiology of Sleep Apnea Analytic Epidemiology Studies of Sleep Disordered Breathing-What Explains the Gender Difference in Sleep Disordered Breathing?

Epidemiology is a research method with a unique population focus for investigating the distribution and determinants of disease. In sleep disordered breathing (SDB) research, epidemiologic study aims include es timating patterns of occurrence across the spectrum of SDB, documenting natural history from the onset of pathophysiology to end-organ effects, identifying risk factors and estimating the public health impact of treated and untreated sleep disordered breathing. In this report, the current need to shift emphasis from descriptive to hypothesis-testing studies is stressed and the methodologic issues of analytic epidemiologic in vestigations are identified. In addition, hypotheses to explain the consistently reported gender difference in SDB prevalence are explored, using analytic study techniques and data from the University of Wisconsin Sleep Cohort Study, a longitudinal study of SDB. Initial population-based studies focused on the first
Engineering Distributed Adaptive Systems using Components

One of the major issues in the domain of dynamically evolving distributed systems composed of autonomous and (self-) adaptive components is the task of systematically addressing the design complexity of their communication and composition. This is caused mainly by the inherent dynamism of such systems, where components may appear and disappear without anti-cipation. Addressing this issue, we employ separation of concerns by introducing a mechanism of implicit communication over implicit bindings, enabling components to dynamically form implicitly interacting groups – ensembles. Speciﬁcally, we present the DEECo component model, which based on this mechanism.
Lexical Ambiguity in Nouns: Frequency Dominance and Declensional Classes

The existence of differences in lexical processing between ambiguous and unambiguous words is still controversial. Many factors seem to play a role in determining different ambiguity effects in word recognition, such as ambiguity type, experimental paradigm, frequency dominance, etc. The aim of this study is to investigate the role played by frequency dominance and declensional class in recognizing Italian homonymous nouns, namely, forms with multiple unrelated meanings. We report the results of two visual lexical decision experiments, in which these factors are manipulated. An ambiguity disadvantage effect is found for words belonging to two different declensional classes (Exp. 2, e.g., conte), while an absence of processing differences is reported for ambiguous words within the same declensional class (Exp. 1, e.g., credenza). Moreover, an interaction between condition and frequency is found: the inhibitory effects are stronger for ambiguous nouns with two frequency-balanced meanings than for ambiguous nouns with a strongly dominant meaning. The results are compatible with the idea that several factors should be taken into account in order to disentangle competing accounts of lexical ambiguity processing. We discuss these results in terms of how variables such as frequency dominance and declensional class affect the activation of lexical representations and play a role in determining different ambiguity effects in lexical access.
Metabolic Modeling and Bidirectional Culturing of Two Gut Microbes Reveal Cross-Feeding Interactions and Protective Effects on Intestinal Cells

Microbial interactions represent the inner connections in the gut microbiome. By integrating mathematical modeling tools and microbial bidirectional culturing, we determined how two gut commensals engage in the exchange of cross-feeding metabolites, lactate and succinate, for increased growth in two fibers. ABSTRACT The gut microbiota is constituted by thousands of microbial interactions, some of which correspond to the exchange of metabolic by-products or cross-feeding. Inulin and xylan are two major dietary polysaccharides that are fermented by members of the human gut microbiota, resulting in different metabolic profiles. Here, we integrated community modeling and bidirectional culturing assays to study the metabolic interactions between two gut microbes, Phocaeicola dorei and Lachnoclostridium symbiosum, growing in inulin or xylan, and how they provide a protective effect in cultured cells. P. dorei (previously belonging to the Bacteroides genus) was able to consume inulin and xylan, while L. symposium only used certain inulin fractions to produce butyrate as a major end product. Constrained-based flux simulations of refined genome-scale metabolic models of both microbes predicted high lactate and succinate cross-feeding fluxes between P. dorei and L. symbiosum when growing in each fiber. Bidirectional culture assays in both substrates revealed that L. symbiosum growth increased in the presence of P. dorei. Carbohydrate consumption analyses showed a faster carbohydrate consumption in cocultures compared to monocultures. Lactate and succinate concentrations in bidirectional cocultures were lower than in monocultures, pointing to cross-feeding as initially suggested by the model. Butyrate concentrations were similar across all conditions. Finally, supernatants from both bacteria cultured in xylan in bioreactors significantly reduced tumor necrosis factor-α-induced inflammation in HT-29 cells and exerted a protective effect against the TcdB toxin in Caco-2 epithelial cells. Surprisingly, this effect was not observed in inulin cocultures. Overall, these results highlight the predictive value of metabolic models integrated with microbial culture assays for probing microbial interactions in the gut microbiota. They also provide an example of how metabolic exchange could lead to potential beneficial effects in the host. IMPORTANCE Microbial interactions represent the inner connections in the gut microbiome. By integrating mathematical modeling tools and microbial bidirectional culturing, we determined how two gut commensals engage in the exchange of cross-feeding metabolites, lactate and succinate, for increased growth in two fibers. These interactions underpinned butyrate production in cocultures, resulting in a significant reduction in cellular inflammation and protection against microbial toxins when applied to cellular models.
Engineered Fluorescent Strains of Cryptococcus neoformans: a Versatile Toolbox for Studies of Host-Pathogen Interactions and Fungal Biology, Including the Viable but Nonculturable State

Cryptococcus neoformans is a human-pathogenic yeast that can undergo a dormant state and is responsible for over 180,000 deaths annually worldwide. We engineered a set of fluorescent transformants to aid in research on C. neoformans. ABSTRACT Cryptococcus neoformans is an opportunistic fungal pathogen known for its remarkable ability to infect and subvert phagocytes. This ability provides survival and persistence within the host and relies on phenotypic plasticity. The viable but nonculturable (VBNC) phenotype was recently described in C. neoformans, whose study is promising in understanding the pathophysiology of cryptococcosis. The use of fluorescent strains is improving host interaction research, but it is still underexploited. Here, we fused histone H3 or the poly(A) binding protein (Pab) to enhanced green fluorescent protein (eGFP) or mCherry, obtaining a set of C. neoformans transformants with different colors, patterns of fluorescence, and selective markers (hygromycin B resistance [Hygr] or neomycin resistance [Neor]). We validated their similarity to the parental strain in the stress response, the expression of virulence-related phenotypes, mating, virulence in Galleria mellonella, and survival within murine macrophages. PAB-GFP, the brightest transformant, was successfully applied for the analysis of phagocytosis by flow cytometry and fluorescence microscopy. Moreover, we demonstrated that an engineered fluorescent strain of C. neoformans was able to generate VBNC cells. GFP-tagged Pab1, a key regulator of the stress response, evidenced nuclear retention of Pab1 and the assembly of cytoplasmic stress granules, unveiling posttranscriptional mechanisms associated with dormant C. neoformans cells. Our results support that the PAB-GFP strain is a useful tool for research on C. neoformans. IMPORTANCE Cryptococcus neoformans is a human-pathogenic yeast that can undergo a dormant state and is responsible for over 180,000 deaths annually worldwide. We engineered a set of fluorescent transformants to aid in research on C. neoformans. A mutant with GFP-tagged Pab1 improved fluorescence-based techniques used in host interaction studies. Moreover, this mutant induced a viable but nonculturable phenotype and uncovered posttranscriptional mechanisms associated with dormant C. neoformans. The experimental use of fluorescent mutants may shed light on C. neoformans-host interactions and fungal biology, including dormant phenotypes.
DeviceWatch: A Data-Driven Network Analysis Approach to Identifying Compromised Mobile Devices with Graph-Inference

We propose to identify compromised mobile devices from a network administrator’s point of view. Intuitively, inadvertent users (and thus their devices) who download apps through untrustworthy markets are often lured to install malicious apps through in-app advertisements or phishing. We thus hypothesize that devices sharing similar apps would have a similar likelihood of being compromised, resulting in an association between a compromised device and its apps. We propose to leverage such associations to identify unknown compromised devices using the guilt-by-association principle. Admittedly, such associations could be relatively weak as it is hard, if not impossible, for an app to automatically download and install other apps without explicit user initiation. We describe how we can magnify such associations by carefully choosing parameters when applying graph-based inferences. We empirically evaluate the effectiveness of our approach on real datasets provided by a major mobile service provider. Specifically, we show that our approach achieves nearly 98% AUC (area under the ROC curve) and further detects as many as 6 ~ 7 times of new compromised devices not covered by the ground truth by expanding the limited knowledge on known devices. We show that the newly detected devices indeed present undesirable behavior in terms of leaking private information and accessing risky IPs and domains. We further conduct in-depth analysis of the effectiveness of graph inferences to understand the unique structure of the associations between mobile devices and their apps, and its impact on graph inferences, based on which we propose how to choose key parameters.
Context Prior Guided Semantic Modeling for Biomedical Image Segmentation

Most state-of-the-art deep networks proposed for biomedical image segmentation are developed based on U-Net. While remarkable success has been achieved, its inherent limitations hinder it from yielding more precise segmentation. First, its receptive field is limited due to the fixed kernel size, which prevents the network from modeling global context information. Second, when spatial information captured by shallower layer is directly transmitted to higher layers by skip connections, the process inevitably introduces noise and irrelevant information to feature maps and blurs their semantic meanings. In this article, we propose a novel segmentation network equipped with a new context prior guidance (CPG) module to overcome these limitations for biomedical image segmentation, namely context prior guidance network (CPG-Net). Specifically, we first extract a set of context priors under the supervision of a coarse segmentation and then employ these context priors to model the global context information and bridge the spatial-semantic gap between high-level features and low-level features. The CPG module contains two major components: context prior representation (CPR) and semantic complement flow (SCF). CPR is used to extract pixels belonging to the same objects and hence produce more discriminative features to distinguish different objects. We further introduce deep semantic information for each CPR by the SCF mechanism to compensate the semantic information diluted during the decoding. We extensively evaluate the proposed CPG-Net on three famous biomedical image segmentation tasks with diverse imaging modalities and semantic environments. Experimental results demonstrate the effectiveness of our network, consistently outperforming state-of-the-art segmentation networks in all the three tasks. Codes are available at https://github.com/zzw-szu/CPGNet.
Institutional Knowledge at Singapore Management University

In this paper, we present I 4 S , a system that identiﬁes item interactions of customers in a retail store through sensor data fusion from smartwatches, smartphones and distributed BLE beacons. To identify these interactions, I 4 S builds a gesture-triggered pipeline that (a) detects the occurrence of “item picks”, and (b) performs ﬁne-grained localization of such pickup gestures. By analyzing data collected from 31 shoppers visiting a mid-sized stationary store, we show that we can identify person-independent picking gestures with a precision of over 88%, and identify the rack from where the pick occurred with 91%+ precision (for popular racks).
Is vascular stiffness associated with the

performed between aortic abdominal diameter, aortic inﬂow diameter, logarithmic conversion of systemic arterial compliance, PWV, cholesterol, calf–brachial systolic blood pressure ratio, height and BMI. suggests a possible utilization of PWV for early identiﬁcation of subjects with an increased risk of developing AAA.
ESTIMATION OF UNEVEN DEVELOPMENT OF LITHUANIAN REGIONS

The researchers have aimed to analyse the processes of divergent development of Lithuanian regions by estimating the basic parameters of the process of inter-regional stratification. We have carried out an estimation of the process of differentiation using three parameters: per capita gross regional product (further GRP), per worker GRP and per capita foreign direct investment (further FDI) in a separate region. Using these indicators and the economic classical con vergence-divergence approaches of analysis, the principal dimensions of the unequal development of territorial units in Lithuania have been assessed.
Estimating door-to-door travel time using a synthetic population enriched with smart card data

Abstract Many modern planning systems aim to reduce average within-city commuting time to 30 min or less, a concept termed the 30-minute city. However, travel time for many large cities exceeds planning targets, and this can subsequently affect commuter health and wellbeing. Although data is often lacking for the ‘first-mile’ and ‘last-mile’ segments of public transport journeys, realistic calculations of the 30-minute city and other chrono-urbanism targets need to include door-to-door travel time. Here, we describe an approach to estimate door-to-door public transport travel time by enriching a synthetic population with smart card data without the need for mobile phone or travel survey data. The algorithm is applied to Sydney, Australia, and is used to measure how effectively a chrono-urbanism target is met in terms of door-to-door travel time compared to travel time without the first- and last-mile. Only 21.7% of validated commuters were modelled to have door-to-door travel time of 30 min or less for the journey to work. This is substantially lower than the 62.0% estimated using calculations without the first- and last-mile.
Advances in nanocomposite material for Fused Filament Fabrication

ABSTRACT Additive manufacturing (AM) is fast becoming the most flexible technique for creating different products, including prototypes and end-use products. Fused filament fabrication (FFF) is the most frequently employed AM technique which is primarily due to the exploration of new materials. Several research work have been done to investigate the development of new composite filaments with improved or distinct properties than the parent thermoplastics by incorporating various usable fillers. This research does a detailed evaluation of the existing literature on FFF nanocomposites and mainly intended for providing a comprehensive review on nanocomposite material processing using FFF processes. Graphical abstract
Effect of genotype and sex on carcase composition, physicochemical properties, texture and microstructure of meat from geese after four reproductive seasons

ABSTRACT 1. The objective of this study was to compare carcase weight and composition and meat quality traits of Landes, Slovak White and Kuban geese after four reproductive seasons. A total of 42 goose carcases (seven males and seven females from each breed) were assessed. 2. After four reproductive seasons, the breeds differed in eviscerated carcase weight. Slovak White geese showed more breast muscle with a cooking loss, whereas Kuban geese had a higher percentage of neck and carcase discards compared to the other breeds. The breeds differed in the chemical composition of breast and leg muscles, except for collagen in breast muscles and protein in leg muscles. 3. Regardless of breed, males had heavier carcase weight and higher breast muscle, leg muscle, neck and wings and lower percentages of skin with subcutaneous fat and abdominal fat relative to body weight compared to females. Sex had a significant effect on the fat and salt content, meat lightness, most textural characteristics and endomysium thickness of breast muscle. The same differences in leg muscles for chemical composition (except for protein percentage) and lightness were recorded. 4. Breed x sex interactions were significant for the proportion of leg muscle, chemical composition of breast and leg muscles (except for leg protein content), muscle fibre cross-sectional area and fibre perimeter of pectoralis major muscle. 5. The results showed that the carcases and meat of the goose breeds after four reproductive seasons were suitable for consumers and meat processors, due to favourable composition, high nutritive value and good technological properties.
NANOGP1, a tandem duplicate of NANOG, exhibits partial functional conservation in human naïve pluripotent stem cells

Gene duplication events are important drivers of evolution by providing genetic material for new gene functions. They also create opportunities for diverse developmental strategies to emerge between species. To study the contribution of duplicated genes to human early development, we examined the evolution and function of NANOGP1, a tandem duplicate of the key transcription factor NANOG. We found that NANOGP1 and NANOG have overlapping but distinct expression profiles, with high NANOGP1 expression restricted to early epiblast cells and naïve-state pluripotent stem cells. Sequence analysis and epitope-tagging of the endogenous locus revealed that NANOGP1 is protein-coding with an intact homeobox domain. NANOGP1 has been retained only in great apes, whereas Old World monkeys have disabled the gene in different ways including point mutations in the homeodomain. NANOGP1 is a strong inducer of naïve pluripotency; however, unlike NANOG, it is not required to maintain the undifferentiated status of human naïve pluripotent cells. By retaining expression, sequence and partial functional conservation with its ancestral copy, NANOGP1 exemplifies how gene duplication and subfunctionalisation can contribute to transcription factor activity in human pluripotency and development. Summary statement Establishing that NANOGP1 has retained partial functional conservation with its ancestral copy NANOG sheds light on the role of gene duplication and subfunctionalisation in human pluripotency and development.
Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons

Coastal lagoons are transitional ecosystems that host a unique diversity of species and support many ecosystem services. Owing to their position at the interface between land and sea, they are also subject to increasing human impacts, which alter their ecological functioning. Because coastal lagoons are naturally highly variable in their environmental conditions, disentangling the effects of anthropogenic disturbances like eutrophication from those of natural variability is a challenging, yet necessary issue to address. Here, we analyze a dataset composed of macrobenthic invertebrate abundances and environmental variables (hydro-morphology, water, sediment and macrophytes) gathered across 29 Mediterranean coastal lagoons located in France, to characterize the main drivers of community composition and structure. Using correlograms, linear models and variance partitioning, we found that lagoon hydro-morphology (connection to the sea and lagoon surface), which affects the level of environmental variability (salinity and temperature), as well as lagoon-scale benthic habitat diversity (using macrophyte morphotypes) seemed to regulate macrofauna distribution, while eutrophication and associated stressors like low dissolved oxygen, acted upon the existing communities, mainly by reducing species richness and diversity. Furthermore, M-AMBI, a multivariate index composed of species richness, Shannon diversity and AMBI (AZTI’s Marine Biotic Index) and currently used to evaluate the ecological state of French coastal lagoons, was more sensitive to eutrophication (18%) than to natural variability (9%), with nonetheless 49% of its variability explained jointly by both. To improve the robustness of benthic indicators like M-AMBI and increase the effectiveness of lagoon benthic habitat management, we call for a revision of the ecological groups at the base of the AMBI index and of the current lagoon typology which could be inspired by the lagoon-sea connection levels used in this study.
Asymmetric expression of homoeologous genes in wheat roots modulates the early phase of iron-deficiency signalling

Iron (Fe) limitation leads to dramatic changes in gene expression in plants, to induce iron uptake and mobilization, while at the same time restrict Fe-dependent metabolism and growth. Although transcriptional changes in response to Fe deficiency have recently been charted in wheat, this was performed at a stage when photosynthesis and growth were severely impacted, confounding primary and secondary responses. Here, we specifically uncover the transcriptional landscape of wheat roots during the early stages of the Fe deficiency response (4 and 8 days) and after Fe resupply. Root growth was significantly inhibited at day 4, but chlorosis only became apparent on day 8. The number of differentially expressed genes increased from 1386 on day 4 to 3538 on day 8, with an overlap of 2006 genes. Genes with dynamic changes in expression patterns include membrane transporters and transcription factors shown to be involved in Fe homeostasis in other plant species. Comparative analysis of the Fe deficiency response at 4, 8 and 20 days identified a core set of Fe-regulated genes. Analysis of the expression of homoeologs suggests an increase in induction bias at 8 days compared to 4 days particularly, A genome contributing high at 4 days and the A+D genomes at 8 days. Overall, our work will contribute towards fundamental knowledge of the Fe signalling networks in wheat and point to the interplay of the three sub-genomes in this hexaploid species to fine tune the transcriptional response.