Remote terahertz wireless power transfer with self-resonating spoof plasmonic structures.

In this paper, we use a pair of self-resonating subwavelength spoof plasmonic structures to achieve remote non-radiative terahertz wireless power transfer, while nearly without affecting the electromagnetic environment of free space around the structure. The resonating frequency and quality factor of the magnetic dipole mode supported by the spoof plasmonic structures can be freely tuned by tailoring the geometric structure. By putting the weak source and detector into the self-resonating structures, we can find that the effective non-radiative terahertz power transferring distance can reach several hundred times the radius of the structures. Finally, we also demonstrate the efficient wireless power transfer capability for the multi-target receiving system. These results may provide a novel approach to the design of non-radiative terahertz wireless power transfer and communications.

Unveiling microbial biomarkers of ruminant methane emission through machine learning.

Background: Enteric methane from cow burps, which results from microbial fermentation of high-fiber feed in the rumen, is a significant contributor to greenhouse gas emissions. A promising strategy to address this problem is microbiome-based precision feed, which involves identifying key microorganisms for methane production. While machine learning algorithms have shown success in associating human gut microbiome with various human diseases, there have been limited efforts to employ these algorithms to establish microbial biomarkers for methane emissions in ruminants. Methods: In this study, we aim to identify potential methane biomarkers for methane emission from ruminants by employing regression algorithms commonly used in human microbiome studies, coupled with different feature selection methods. To achieve this, we analyzed the microbiome compositions and identified possible confounding metadata variables in two large public datasets of Holstein cows. Using both the microbiome features and identified metadata variables, we trained different regressors to predict methane emission. With the optimized models, permutation tests were used to determine feature importance to find informative microbial features. Results: Among the regression algorithms tested, random forest regression outperformed others and allowed the identification of several crucial microbial taxa for methane emission as members of the native rumen microbiome, including the genera Piromyces, Succinivibrionaceae UCG-002, and Acetobacter. Additionally, our results revealed that certain herd locations and feed composition markers, such as the lipid intake and neutral-detergent fiber intake, are also predictive features for methane emissions. Conclusion: We demonstrated that machine learning, particularly regression algorithms, can effectively predict cow methane emissions and identify relevant rumen microorganisms. Our findings offer valuable insights for the development of microbiome-based precision feed strategies aiming at reducing methane emissions.

Effect of wastewater COD/N ratio on aerobic nitrifying sludge granulation and microbial population shift.

The effect of COD/N ratio on the granulation process and microbial population succession was investigated. Four identical sequencing batch reactors, R1, R2, R3 and R4, were operated with various initial COD/N ratios ranging from 0/200 to 800/200 (m/m). Ethanol was fed as the source of COD. Aerobic granules were successfully cultivated in R2 and R3, operating with the COD/N ratio of 200/200 and 400/200, respectively. Scanning electron microscope observations indicated that short rod-shaped and spherical bacteria were dominant in R2, while granules produced in R3 were surrounded with a large amount of filamentous bacteria. The average specific nitritation rate in R2 and R3 were 0.019 and 0.008 mg N/(mg MLVSS x hr), respectively. Fluorescence in situ hybridization results demonstrated that nitrifying bacteria population was enriched remarkably in R2. It indicated that nitrification ability and nitrifying bacteria population were enriched remarkably at low COD/N ratio. However, no granules were formed in R1 and R4 which might attribute to either limited or excessive extracellular polymeric substances production. This study contributed to a better understanding of the role of COD/N ratio in nitrifying sludge granulation.

Evaluating long-read de novo assembly tools for eukaryotic genomes: insights and considerations.

BACKGROUND: Assembly algorithm choice should be a deliberate, well-justified decision when researchers create genome assemblies for eukaryotic organisms from third-generation sequencing technologies. While third-generation sequencing by Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) has overcome the disadvantages of short read lengths specific to next-generation sequencing (NGS), third-generation sequencers are known to produce more error-prone reads, thereby generating a new set of challenges for assembly algorithms and pipelines. However, the introduction of HiFi reads, which offer substantially reduced error rates, has provided a promising solution for more accurate assembly outcomes. Since the introduction of third-generation sequencing technologies, many tools have been developed that aim to take advantage of the longer reads, and researchers need to choose the correct assembler for their projects. RESULTS: We benchmarked state-of-the-art long-read de novo assemblers to help readers make a balanced choice for the assembly of eukaryotes. To this end, we used 12 real and 64 simulated datasets from different eukaryotic genomes, with different read length distributions, imitating PacBio continuous long-read (CLR), PacBio high-fidelity (HiFi), and ONT sequencing to evaluate the assemblers. We include 5 commonly used long-read assemblers in our benchmark: Canu, Flye, Miniasm, Raven, and wtdbg2 for ONT and PacBio CLR reads. For PacBio HiFi reads , we include 5 state-of-the-art HiFi assemblers: HiCanu, Flye, Hifiasm, LJA, and MBG. Evaluation categories address the following metrics: reference-based metrics, assembly statistics, misassembly count, BUSCO completeness, runtime, and RAM usage. Additionally, we investigated the effect of increased read length on the quality of the assemblies and report that read length can, but does not always, positively impact assembly quality. CONCLUSIONS: Our benchmark concludes that there is no assembler that performs the best in all the evaluation categories. However, our results show that overall Flye is the best-performing assembler for PacBio CLR and ONT reads, both on real and simulated data. Meanwhile, best-performing PacBio HiFi assemblers are Hifiasm and LJA. Next, the benchmarking using longer reads shows that the increased read length improves assembly quality, but the extent to which that can be achieved depends on the size and complexity of the reference genome.

CADA: phenotype-driven gene prioritization based on a case-enriched knowledge graph.

Many rare syndromes can be well described and delineated from other disorders by a combination of characteristic symptoms. These phenotypic features are best documented with terms of the Human Phenotype Ontology (HPO), which are increasingly used in electronic health records (EHRs), too. Many algorithms that perform HPO-based gene prioritization have also been developed; however, the performance of many such tools suffers from an over-representation of atypical cases in the medical literature. This is certainly the case if the algorithm cannot handle features that occur with reduced frequency in a disorder. With Cada, we built a knowledge graph based on both case annotations and disorder annotations. Using network representation learning, we achieve gene prioritization by link prediction. Our results suggest that Cada exhibits superior performance particularly for patients that present with the pathognomonic findings of a disease. Additionally, information about the frequency of occurrence of a feature can readily be incorporated, when available. Crucial in the design of our approach is the use of the growing amount of phenotype-genotype information that diagnostic labs deposit in databases such as ClinVar. By this means, Cada is an ideal reference tool for differential diagnostics in rare disorders that can also be updated regularly.

Effect of influent nutrient ratios and temperature on simultaneous phosphorus and nitrogen removal in a step-feed CAST.

A step-feed cyclic activated sludge technology (CAST) with a working volume of 72 L treating real municipal wastewater was operated to examine the effect of varying ratios of influent COD/TN and COD/P on the nutrient removal. With the increased COD/P and COD/TN, the phosphorus and nitrogen removals exhibited an upward trend. The TN removals had a positive linear correlation with the phosphorus removal efficiencies, mainly because the presence of nitrate in the anaerobic zone negatively affected the phosphorus release thus the nitrogen removal process took priority over the phosphorus removal process to utilize the limited carbon source in the influent in step-feed CAST where simultaneous removals of nitrogen and phosphorus were achieved. By employing the effective step-feed strategy with alternating anoxic/oxic operation, efficient phosphorus and nitrogen removals of 95.8 and 89.3% were obtained with lower influent COD/P and COD/TN ratios of 61.9 and 5.2, respectively. It was also found that lower temperature, e.g. 13 ~ 16°C, did not deteriorate the phosphorus removal, though the nitrogen removal decreased significantly due to incomplete nitrification. As the temperature increased further, TN removal efficiency increased gradually and nitrogen removal via nitrite pathway was successfully achieved with average nitrite accumulation rate above 90% in the system.

Nitrogen removal via nitrite from municipal landfill leachate.

A system consisting of a two-stage up-flow anaerobic sludge blanket (UASB), an anoxic/aerobic (A/O) reactor and a sequencing batch reactor (SBR), was used to treat landfill leachate. During operation, denitrification and methanogenesis took place simultaneously in the first stage UASB, and the effluent chemical oxygen demand (COD) was further removed in the second stage UASB. Then the denitrification of nitrite and nitrate in the returned sludge by using the residual COD was accomplished in the A/O reactor, and ammonia was removed via nitrite in it. Last but not least, the residual ammonia was removed in SBR as well as nitrite and nitrate which were produced by nitrification. The results over 120 d (60 d for phase I and 60 d for phase II) were as follows: when the total nitrogen (TN) concentration of influent leachate was about 2500 mg/L and the ammonia nitrogen concentration was about 2000 mg/L, the short-cut nitrification with 85%-90% nitrite accumulation was achieved stably in the A/O reactor. The TN and ammonia nitrogen removal efficiencies of the system were 98% and 97%, respectively. The residual ammonia, nitrite and nitrate produced during nitrification in the A/O reactor could be washed out almost completely in SBR. The TN and ammonia nitrogen concentrations of final effluent were about 39 mg/L and 12 mg/L, respectively.

Intercross real-time control strategy in alternating activated sludge process for short-cut biological nitrogen removal treating domestic wastewater.

To develop technically feasible and economically favorable dynamic process control (DPC) strategies for an alternating activated sludge (AAS) system, a bench-scale continuous-flow alternating aerobic and anoxic reactor, performing short-cut nitrogen removal from real domestic wastewater was operated under different control strategies for more than five months. A fixed-time control (FTC) study showed that bending-points on pH and oxidation-reduction potential (ORP) profiles accurately coincided with the major biological activities. "Ammonia valley" on the pH profile represented the end of nitrification, whereas, the "nitrite knee" on the ORP profile and "nitrite apex" on the pH profile both indicated the end of denitrification. Therefore, a new reliable and effective real-time control strategy was developed using pH and ORP as control parameters, to improve the performance of the AAS process. The online control strategy could achieve up to 87% of the total nitrogen (TN) removal efficiency on an average, and saving approximately 20% aeration energy, as compared to the conventional steady-state control systems. Moreover, stable short-cut nitrification and denitrification were successfully achieved with an average nitrite accumulation ratio of above 95%.

Effect of nitrate recycling ratio on simultaneous biological nutrient removal in a novel anaerobic/anoxic/oxic (A2/O)-biological aerated filter (BAF) system.

A novel system integrating anaerobic/anoxic/oxic (A(2)/O) and biological aerated filter (BAF), which could solve the sludge retention time (SRT) conflicting problem between nitrifiers and polyphosphate accumulating organisms (PAOs) by shortening SRT for PAOs in A(2)/O and lengthening SRT for nitrifiers in BAF, was investigated in this study. Various nitrate recycling ratios (100%, 200%, 300% and 400%) were applied to a lab-scaled A(2)/O-BAF system to detect the simultaneous biological nitrogen and phosphorus removal performance while treating real domestic wastewater with low carbon to nitrogen (C/N) ratio. The concentrations of chemical oxygen demand (COD), NH(4)(+)-N and total phosphorus (TP) in the effluent were less than 50.0, 0.5 and 0.5mg/L, respectively, throughout the experiments. The removal efficiencies of total nitrogen (TN) were 64.9%, 77.0%, 82.0% and 87.0%, under respective nitrate recycling ratios (increasing from 100% to 400%). By contrast, nitrate recycling ratios had neglectable effect on the removal efficiencies of COD and NH(4)(+)-N.

Energy saving achieved by limited filamentous bulking sludge under low dissolved oxygen.

Limited filamentous bulking caused by low dissolved oxygen (DO) was proposed to establish a low energy consumption wastewater treatment system. This method for energy saving was derived from two full-scale field observations, which showed pollutants removal would be enhanced and energy consumption could be reduced by at least 10% using limited filamentous bulking. Furthermore, preliminary investigation including the abundance evaluation and the identification of filamentous bacteria demonstrated that the limited filamentous bulking could be repeated steadily in a lab-scale anoxic-oxic reactor fed with domestic wastewater. The sludge loss did not occur in the secondary clarifier, while COD and total nitrogen removal efficiencies were improved by controlling DO for optimal filamentous bacterial population. Suspended solids in effluent were negligible and turbidity was lower than 2 NTU, which were distinctly lower than those under no bulking. Theoretical and experimental results indicated the aeration consumption could be saved by the application of limited filamentous bulking.

N(2)O production during nitrogen removal via nitrite from domestic wastewater: main sources and control method.

Nitrite has been commonly recognized as an important factor causing N(2)O production, which weakened the advantages of nitrogen removal via nitrite. To reduce and control N(2)O production from wastewater treatment plants, both long-term and batch tests were carried out to investigate main sources and pathways of N(2)O production during nitrogen removal via nitrite from real domestic wastewater. The obtained results showed that N(2)O production during nitrogen removal via nitrite was 1.5 times as much as that during nitrogen removal via nitrate. It was further demonstrated that ammonia oxidization were main source of N(2)O production during nitrogen removal from domestic wastewater; whereas, almost no N(2)O was produced during nitrite oxidization and anoxic denitrification. N(2)O production during nitrogen removal via nitrite decreased about 50% by applying the step-feed SBR, due to the effective control of nitrite and ammonia, the precursors of N(2)O production. Therefore, the step-feed system is recommended as an effective method to reduce N(2)O production during nitrogen removal via nitrite from domestic wastewater.