variational inference

Researchers commonly perform sentiment analysis on large collections of short texts like tweets, Reddit posts or newspaper headlines that are all focused on a specific topic, theme or event. Usually, general-purpose sentiment analysis methods are used. These perform well on average but miss the variation in meaning that happens across different contexts, for example, the word "active" has a very different intention and valence in the phrase "active lifestyle" versus "active volcano". This work presents a new approach, CIDER (Context Informed Dictionary and sEmantic Reasoner), which performs context-sensitive linguistic analysis, where the valence of sentiment-laden terms is inferred from the whole corpus before being used to score the individual texts...

AbstractThe nonrandom association between landscape characteristics and the dominant life history strategies observed in species pools is a typical pattern in nature. Here, we argue that these associations determine predictable changes in the relative importance of assembly mechanisms along broadscale geographic gradients (i.e., the geographic context of metacommunity dynamics). To demonstrate that, we employed simulation models in which groups of species with the same initial distribution of niche breadths and dispersal abilities interacted across a wide range of landscapes with contrasting characteristics...

The family Sisoridae is one of the largest and most diverse Asiatic catfish families, with most species occurring in the water systems of the Qinhai-Tibetan Plateau and East Himalayas. At present, the phylogenetic relationship of the Sisoridae is relatively chaotic. In this study, the mitochondrial genomes (mitogenomes) of three species Creteuchiloglanis kamengensis, Glaridoglanis andersonii, and Exostoma sp. were systematically investigated, the phylogenetic relationships of the family were reconstructed and to determine the phylogenetic position of Exostoma sp...

BACKGROUND: Dengue is the most prevalent mosquito-borne viral disease and a major public health problem worldwide. Most primary infections with the four dengue virus serotypes (DENV1-4) are inapparent; nevertheless, prior research has primarily focused on symptomatic infections, which has limited our understanding of the epidemiological burden and spectrum of disease of each DENV serotype. Our study addresses this bottleneck in dengue research by providing a new method and a detailed examination of primary inapparent infections...

BACKGROUND: Hyaluronan-mediated motility receptor (HMMR) is overexpressed in multiple carcinomas and influences the development and treatment of several cancers. However, its role in hepatocellular carcinoma (HCC) remains unclear. METHODS: The "limma" and "GSVA" packages in R were used to perform differential expression analysis and to assess the activity of signalling pathways, respectively. InferCNV was used to infer copy number variation (CNV) for each hepatocyte and "CellChat" was used to analyse intercellular communication networks...

BACKGROUND: Most existing clinical prediction models do not allow predictions under interventions. Such predictions allow predicted risk under different proposed strategies to be compared and are therefore useful to support clinical decision making. We aimed to compare methodological approaches for predicting individual level cardiovascular risk under three interventions: smoking cessation, reducing blood pressure, and reducing cholesterol. METHODS: We used data from the PREDICT prospective cohort study in New Zealand to calculate cardiovascular risk in a primary care setting...

Network inference is used to model transcriptional, signaling, and metabolic interactions among genes, proteins, and metabolites that identify biological pathways influencing disease pathogenesis. Advances in machine learning (ML)-based inference models exhibit the predictive capabilities of capturing latent patterns in genomic data. Such models are emerging as an alternative to the statistical models identifying causative factors driving complex diseases. We present CoVar, an ML-based framework that builds upon the properties of existing inference models, to find the central genes driving perturbed gene expression across biological states...

Wastewater-based epidemiology is a promising public health tool that can yield a more representative view of the population than case reporting. However, only about 80% of the U.S. population is connected to public sewers, and the characteristics of populations missed by wastewater-based epidemiology are unclear. To address this gap, we used publicly available datasets to assess sewer connectivity in the U.S. by location, demographic groups, and economic groups. Data from the U.S. Census' American Housing Survey revealed that sewer connectivity was lower than average when the head of household was American Indian and Alaskan Native, White, non-Hispanic, older, and for larger households and those with higher income, but smaller geographic scales revealed local variations from this national connectivity pattern...

Bayesian coalescent skyline plot models are widely used to infer demographic histories. The first (non-Bayesian) coalescent skyline plot model assumed a known genealogy as data, while subsequent models and implementations jointly inferred the genealogy and demographic history from sequence data, including heterochronous samples. Overall, there exist multiple different Bayesian coalescent skyline plot models which mainly differ in two key aspects: (1) how changes in population size are modeled through independent or autocorrelated prior distributions, and (2) how many change-points in the demographic history are used, where they occur and if the number is pre-specified or inferred...

Cloud-based training and edge-based inference modes for Artificial Intelligence of Medical Things (AIoMT) applications suffer from accuracy degradation due to physiological signal variations among patients. On-chip learning can overcome this issue by online adaptation of neural network parameters for user-specific tasks. However, existing on-chip learning processors have limitations in terms of versatility, resource utilization, and energy efficiency. We propose HybMED, which is a novel neural signal processor that supports on-chip hybrid neural network training using a composite direct feedback alignment-based paradigm...

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient...

Alterations in attention to cues signaling the need for inhibitory control play a significant role in a wide range of psychopathology. However, the degree to which motivational and attentional factors shape the neurocomputations of proactive inhibitory control remains poorly understood. The present study investigated how variation in monetary incentive valence and stake modulate the neurocomputational signatures of proactive inhibitory control. Adults ( N = 46) completed a Stop-Signal Task (SST) with concurrent EEG recording under four conditions associated with stop performance feedback: low and high punishment (following unsuccessful stops) and low and high reward (following successful stops)...

Darwin attributed the absence of species transitions in the fossil record to his hypothesis that speciation occurs within isolated habitat patches too geographically restricted to be captured by fossil sequences. Mayr's peripatric speciation model added that such speciation would be rapid, further explaining missing evidence of diversification. Indeed, Eldredge and Gould's original punctuated equilibrium model combined Darwin's conjecture, Mayr's model and 124 years of unsuccessfully sampling the fossil record for transitions...

BACKGROUND: Genomes are inherently inhomogeneous, with features such as base composition, recombination, gene density, and gene expression varying along chromosomes. Evolutionary, biological, and biomedical analyses aim to quantify this variation, account for it during inference procedures, and ultimately determine the causal processes behind it. Since sequential observations along chromosomes are not independent, it is unsurprising that autocorrelation patterns have been observed e.g...

Incorporating statistical characteristics of stimuli in perceptual processing can be highly beneficial for reliable estimation from noisy sensory measurements but may generate perceptual bias. According to Bayesian inference, perceptual biases arise from the integration of internal priors with noisy sensory inputs. In this study, we used a Bayesian observer model to derive biases and priors in hue perception based on discrimination data for hue ensembles with varying levels of chromatic noise. Our results showed that discrimination thresholds for isoluminant stimuli with hue defined by azimuth angle in cone-opponent color space exhibited a bimodal pattern, with lowest thresholds near a non-cardinal blue-yellow axis that aligns closely with the variation of natural daylights...

Understanding the interactions of pathogenic droplets with surfaces is crucial to biomedical applications. In this study, using E. coli as the model microbe, we investigate the impact of a bacteria-laden droplet on different substrates, both bare and antimicrobial. In doing so, we unveil the significance of kinetic energy and spreading parameters of the impacting droplet in determining the microbes' proliferation capabilities. Our results indicate an inverse relationship between the impact Weber number and the bacterial ability to proliferate...

Rubus chingii and R. chingii var. suavissimus are unique dual-purpose plant resources, with significant nutraceutical, pharmaceutical, and economic value, as well as promising prospects for further development. To investigate the genetic structure and evolutionary characteristics of these two varieties, this study conducted plastome sequencing using the Illumina HiSeq XTen sequencing platform. Subsequently, the study performed assembly, annotation, and characterization of the genomes, followed by a comparative plastome and phylogenetic analysis using bioinformatics techniques...

Wastewater surveillance has been increasingly acknowledged as a useful tool for monitoring transmission dynamics of infections of public health concern, including the coronavirus disease (COVID-19). While a range of models have been proposed to estimate the time-varying effective reproduction number (Rt ) utilizing clinical data, few have harnessed the viral concentration in wastewater samples to do so, leaving uncertainties about the potential precision gains with its use. In this study, we developed a Bayesian hierarchical model which simultaneously reconstructed the latent infection trajectory and estimated Rt ...

Physical-layer authentication (PLA) based on hardware fingerprints can safeguard optical networks against large-scale masquerade or active injection attacks. However, traditional schemes rely on massive labeled close-set data. Here, we propose an unsupervised hardware fingerprint authentication based on a variational autoencoder (VAE). Specifically, the triplets are generated through variational inference on unlabeled optical spectra and then applied to train the feature extractor, which has an excellent generalization ability and enables fingerprint feature extraction from previously unknown optical transmitters...

OBJECTIVE: Mendelian randomization (MR) was used to explore the causal relationship between diabetes (type 1 and type 2) and prostate cancer (PCa) in East Asian population. METHODS: Mendelian randomization is a causal inference method based on genetic variation, which uses the influence of randomly assigned genotypes in nature on phenotype to infer the impact of biological factors on diseases. This study used genetic variation genes related to inflammatory biomarkers as instrumental variables to improve inference, and patient data was obtained from the GWAS database's aggregated association results...