Harmonizing Output Imbalance for semantic segmentation on extremely-imbalanced input data

Semantic segmentation is a high level computer vision task that assigns a label for each pixel of an image. It is challenging to deal with extremely-imbalanced data in which the ratio of target pixels to background pixels is lower than 1:1000. Such severe input imbalance leads to output imbalance for poor model training. This paper considers three issues for extremely-imbalanced data: inspired by the region-based Dice loss, an implicit measure for the output imbalance is proposed, and an adaptive algorithm is designed for guiding the output imbalance hyperparameter selection; then it is generalized to distribution-based loss for dealing with output imbalance; and finally a compound loss with our adaptive hyperparameter selection algorithm can keep the consistency of training and inference for harmonizing the output imbalance. With four popular deep architectures on our private dataset from three different input imbalance scales and three public datasets, extensive experiments demonstrate the competitive/promising performance of the proposed method.Comment: 18 pages, 13 figures, 2 appendixe

Metagenomic analysis of microbial consortia enriched from compost: new insights into the role of Actinobacteria in lignocellulose decomposition

Additional file 11: Table S7. Summary of de novo assembly results (37 k)

A missing link in the estuarine nitrogen cycle?: coupled nitrification-denitrification mediated by suspended particulate matter

In estuarine and coastal ecosystems, the majority of previous studies have considered coupled nitrification-denitrification (CND) processes to be exclusively sediment based, with little focus onsuspended particulate matter (SPM) in the water column. Here, we present evidence of CND processes in the water column of Hangzhou Bay, one of the largest macrotidal embayments in the world

Mapping the Galactic disk with the LAMOST and Gaia Red clump sample: I: precise distances, masses, ages and 3D velocities of ∼\sim 140000 red clump stars

We present a sample of $\sim$ 140,000 primary red clump (RC) stars of spectral signal-to-noise ratios higher than 20 from the LAMOST Galactic spectroscopic surveys, selected based on their positions in the metallicity-dependent effective temperature--surface gravity and color--metallicity diagrams, supervised by high-quality $Kepler$ asteroseismology data. The stellar masses and ages of those stars are further determined from the LAMOST spectra, using the Kernel Principal Component Analysis method, trained with thousands of RCs in the LAMOST-$Kepler$ fields with accurate asteroseismic mass measurements. The purity and completeness of our primary RC sample are generally higher than 80 per cent. For the mass and age, a variety of tests show typical uncertainties of 15 and 30 per cent, respectively. Using over ten thousand primary RCs with accurate distance measurements from the parallaxes of Gaia DR2, we re-calibrate the $K_{\rm s}$ absolute magnitudes of primary RCs by, for the first time, considering both the metallicity and age dependencies. With the the new calibration, distances are derived for all the primary RCs, with a typical uncertainty of 5--10 per cent, even better than the values yielded by the Gaia parallax measurements for stars beyond 3--4 kpc. The sample covers a significant volume of the Galactic disk of $4 \leq R \leq 16$ kpc, $|Z| \leq 5$ kpc, and $-20 \leq \phi \leq 50^{\circ}$. Stellar atmospheric parameters, line-of-sight velocities and elemental abundances derived from the LAMOST spectra and proper motions of Gaia DR2 are also provided for the sample stars. Finally, the selection function of the sample is carefully evaluated in the color-magnitude plane for different sky areas. The sample is publicly available.Comment: 16 pages, 19 figures, 3 tables, accepted for publication in ApJ

A missing link in the estuarine nitrogen cycle?: coupled nitrification-denitrification mediated by suspended particulate matter

In estuarine and coastal ecosystems, the majority of previous studies have considered coupled nitrification-denitrification (CND) processes to be exclusively sediment based, with little focus onsuspended particulate matter (SPM) in the water column. Here, we present evidence of CND processes in the water column of Hangzhou Bay, one of the largest macrotidal embayments in the world

NormExpression: An R Package to Normalize Gene Expression Data Using Evaluated Methods

Data normalization is a crucial step in the gene expression analysis as it ensures the validity of its downstream analyses. Although many metrics have been designed to evaluate the existing normalization methods, different metrics or different datasets by the same metric yield inconsistent results, particularly for the single-cell RNA sequencing (scRNA-seq) data. The worst situations could be that one method evaluated as the best by one metric is evaluated as the poorest by another metric, or one method evaluated as the best using one dataset is evaluated as the poorest using another dataset. Here raises an open question: principles need to be established to guide the evaluation of normalization methods. In this study, we propose a principle that one normalization method evaluated as the best by one metric should also be evaluated as the best by another metric (the consistency of metrics) and one method evaluated as the best using scRNA-seq data should also be evaluated as the best using bulk RNA-seq data or microarray data (the consistency of datasets). Then, we designed a new metric named Area Under normalized CV threshold Curve (AUCVC) and applied it with another metric mSCC to evaluate 14 commonly used normalization methods using both scRNA-seq data and bulk RNA-seq data, satisfying the consistency of metrics and the consistency of datasets. Our findings paved the way to guide future studies in the normalization of gene expression data with its evaluation. The raw gene expression data, normalization methods, and evaluation metrics used in this study have been included in an R package named NormExpression. NormExpression provides a framework and a fast and simple way for researchers to select the best method for the normalization of their gene expression data based on the evaluation of different methods (particularly some data-driven methods or their own methods) in the principle of the consistency of metrics and the consistency of datasets

Simultaneously enhancing adsorbed hydrogen and dinitrogen to enable efficient electrochemical NH3 synthesis on Sm(OH)3

The electrochemical N2 reduction reaction (ENRR), driven by renewable electricity and run under ambient conditions, offers a promising sustainable avenue for carbon-neutral NH3 production. Yet, to efficiently bind and activate the inert N2 remains challenge. Herein, effective and stable electrochemical NH3 synthesis on Sm(OH)3 via enhanced adsorption of hydrogen and dinitrogen by dual integration of sulfur dopants and oxygen vacancies (VO) is reported. The resulting S-doped lanthanide electrocatalyst attains both a good NH3 yield rate, exceeding 21 μgNH3 h−1 mgcat.−1, and an NH3 faradaic efficiency of over 29% at −0.3 V (vs reversible hydrogen electrode) in an H-type cell using a neutral electrolyte, figures of merit that are largely maintained after 2 days of consecutive polarization. Density functional theory calculations show that the adsorption energy barrier of N2 on S-Sm(OH)3(VO) is greatly lowered by the introduction of VO. In addition, the S sites improve the adsorption of hydrogen produced via the Volmer reaction, which is conducive to the formation of the *N–NH intermediate (i.e., the potential determining step, PDS) on adjacent Sm sites, and thereby significantly promotes the reaction kinetics of ENRR. The PDS free energy for the catalyst is comparable with the values at the peak of the ENRR volcano plots of leading transition metal catalyst surfaces

13C pulse-chase labeling comparative assessment of the active methanogenic archaeal community composition in the transgenic and nontransgenic parental rice rhizospheres

Rhabdosargus holubi (Steindachner, 1881) is a small (maximum size = 450 mm total length; Heemstra and Heemstra 2004) sparid that is distributed along the south-east coast of Africa from St Helena Bay, South Africa, to Maputo, Mozambique (Götz and Cowley 2013). Spawning occurs in the nearshore marine environment primarily during winter, specifically May–August in KwaZulu-Natal (KZN) (Wallace 1975) and July–February in the South-Eastern Cape (Whitfield 1998). Individuals reach 50% sexual maturity at approximately 150 mm standard length (SL) in the Eastern Cape (Whitfield 1998). The early life stages are transported by the south-westward-flowing Agulhas Current, and recruit as post-flexion larvae and early juveniles into estuaries during late winter and early summer (Blaber 1974). The warm temperatures and high nutrient levels in estuaries favour fast growth (Blaber 1973a), and fish spend their first year of life in these environments, migrating back out to sea after reaching approximately 120 mm SL. Some individuals remain trapped in closed estuaries, where they may reach sizes greater than 200 mm SL (James et al. 2007a). Rhabdosargus holubi is the dominant estuarine-dependent marine teleost species recorded in permanently open and temporarily open/closed estuaries in the warm-temperate region, which spans the south, south-east and east coast of South Africa (Harrison 2005). The species is also an important component of the linefishery in many SouthAfrican estuaries (10–15.6% by number) (Pradervand and Baird 2002), particularly in Eastern Cape estuaries (Cowley et al. 2003). These figures underestimate the presence of R. holubi, as most individuals making use of estuaries are young, feeding predominately on filamentous macroalgae and diatom flora, and are generally too small to be caught with hook and line (De Wet and Marais 1990). James et al. (2007b) showed that R. holubi made up 34–92% of the annual seine-net catch in the East Kleinemonde Estuary. Rhabdosargus holubi is also important in the KZN shorebased linefishery, representing 4.6% of the total landed catch (Dunlop and Mann 2012)More and more investigations indicate that genetic modification has no significant or persistent effects on microbial community composition in the rice rhizosphere. Very few studies, however, have focused on its impact on functional microorganisms. This study completed a 13C-CO2 pulse-chase labeling experiment comparing the potential effects of cry1Ab gene transformation on 13C tissue distribution and rhizosphere methanogenic archaeal community composition with its parental rice variety (Ck) and a distant parental rice variety (Dp). Results showed that 13C partitioning in aboveground biomass (mainly in stems) and roots of Dp was significantly lower than that of Ck. However, there were no significant differences in 13C partitioning between the Bt transgenic rice line (Bt) and Ck. RNA-stable isotope probing combined with clone library analyses inferred that the group Methanosaetaceae was the predominant methanogenic Archaea in all three rice rhizospheres. The active methanogenic archaeal community in the Bt rhizosphere was dominated by Methanosarcinaceae, Methanosaetaceae, and Methanomicrobiaceae, while there were only two main methanogenic clusters (Methanosaetaceae and Methanomicrobiaceae) in the Ck and Dp rhizospheres. These results indicate that the insertion of cry1Ab gene into the rice genome has the potential to result in the modification of methanogenic community composition in its rhizosphere

Assisted child-minding based on visual activity monitoring in a home camera surveillance system

Child minding has always been a challenging task for most parents especially for those with kids aged one to five years old. This is the crucial period of growing up whereby children begin to walk and run about, start to play with their toys and the time when their curiosity about the surroundings slowly develops. During this period, children often unknowingly place themselves in danger which makes looking after them a tedious task for caregivers. The proposed automated surveillance system in this project aims to enable caregivers to minimize the amount of attention needed and at the same time provide alerts and ample time for caregivers to respond accordingly to the situation. Firstly, the proposed system will require the user to identify the estimated location of the child and define a danger zone of which the child may endanger himself if he should come into contact with. After which, background subtraction was used to segment the moving and non-moving parts of the surveillance video. The system will then use kernel-based mean shift tracking using the Epanechnikov kernel to track the child and prompt alerts if the child comes into contact with the danger zone. In this manner, the child-minder will then be able to carry on with their routine tasks without requiring additional attention. The system was tested using surveillance videos recorded in various real home environments where children under the age of five resided. The system could effectively track the children and provide audible alerts when they approached dangerous areas. This shows that the system can provide caregivers with a means to reduce the amount of attention spent on monitoring children. Various possible built-in features to improve the system such as a task scheduler and the collection of statistics of the child’s daily activities were also discussed in the later part of the project.Bachelor of Engineering (Computer Science