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Background: CAR-T therapy has emerged as a potentially effective treatment for individuals diagnosed with hematologic malignancies. Understanding patients’ unique experiences with this therapeutic approach is essential. This knowledge will enable the development of tailored nursing interventions that align with the increasing importance of patient-centered care. Objective: To examine and synthesize qualitative data on patients and their family caregivers’ experiences during the treatment journey. Design: We conducted a systematic review and qualitative meta-synthesis. Eligible studies contained adult patient or family caregiver quotes about experiences of CAR-T therapy, published in English or Chinese in a peer-reviewed journal since 2015. Data sources included MEDLINE, CINAHL, Embase, PsycINFO, Web of Science, Scopus, Cochrane Library, CNKI, and WanFang. Methods: Systematic search yielded 6373 identified articles. Of these, 12 reports were included in the analysis, which covered 11 separate studies. Two reviewers independently extracted data into NVIVO 12.0. Qualitative meta-synthesis was performed through line-by-line coding of full text, organization of codes into descriptive themes, and development themes. Results: The qualitative meta-synthesis yielded eight primary themes. Noteworthy revelations from patients and their family caregivers regarding the CAR-T therapy journey encompassed various aspects. Prior to CAR-T therapy, patients experienced a lack of actual choice, struggled with expectations for treatment outcomes, and encountered intricate emotional experiences. During or immediately after CAR-T therapy, patients reported both comfortable and uncomfortable experiences. Additionally, patients emphasized that concerns regarding treatment efficacy and adverse reactions intensified treatment-related distress. After CAR-T therapy, significant changes were observed, and the burden of home-based rehabilitation. Additionally, we found factors contributed to the high CAR-T therapy cost. Conclusions: To ensure the safety and sustainability of CAR-T therapy, it is crucial to address the physical and psychological aspects of the patient's experience. Effective communication and comprehensive management are highly valued by patients and their caregivers. Further research should investigate ways to reduce burdens and develop self-management education programs for patients and their families. [ABSTRACT FROM AUTHOR]

Graph representation is a critical technology in the field of knowledge engineering and knowledge-based applications since most knowledge bases are represented in the graph structure. Nowadays, contrastive learning has become a prominent way for graph representation by contrasting positive–positive and positive–negative node pairs between two augmentation graphs. It has achieved new state-of-the-art in the field of self-supervised graph representation. However, existing contrastive graph representation methods mainly focus on modifying (normally removing some edges/nodes) the original graph structure to generate the augmentation graph for the contrastive. It inevitably changes the original graph structures, meaning the generated augmentation graph is no longer equivalent to the original graph. This harms the performance of the representation in many structure-sensitive graphs such as protein graphs, chemical graphs, molecular graphs, etc. Moreover, there is only one positive–positive node pair but relatively massive positive–negative node pairs in the self-supervised graph contrastive learning. This can lead to the same class, or very similar samples are considered negative samples. To this end, in this work, we propose a Virtual Masking Augmentation (VMA) to generate an augmentation graph without changing any structures from the original graph. Meanwhile, a node augmentation method is proposed to augment the positive node pairs by discovering the most similar nodes in the same graph. Then, two different augmentation graphs are generated and put into a contrastive learning model to learn the graph representation. Extensive experiments on massive datasets demonstrate that our method achieves new state-of-the-art results on self-supervised graph representation. The source code of the proposed method is available at https://github.com/DuanhaoranCC/CGRA. [ABSTRACT FROM AUTHOR]

eIF3, whose subunits are frequently overexpressed in cancer, regulates mRNA translation from initiation to termination, but mRNA‐selective functions of individual subunits remain poorly defined. Using multiomic profiling upon acute depletion of eIF3 subunits, we observed that while eIF3a, b, e, and f markedly differed in their impact on eIF3 holo‐complex formation and translation, they were each required for cancer cell proliferation and tumor growth. Remarkably, eIF3k showed the opposite pattern with depletion promoting global translation, cell proliferation, tumor growth, and stress resistance through repressing the synthesis of ribosomal proteins, especially RPS15A. Whereas ectopic expression of RPS15A mimicked the anabolic effects of eIF3k depletion, disruption of eIF3 binding to the 5′‐UTR of RSP15A mRNA negated them. eIF3k and eIF3l are selectively downregulated in response to endoplasmic reticulum and oxidative stress. Supported by mathematical modeling, our data uncover eIF3k‐l as a mRNA‐specific module which, through controlling RPS15A translation, serves as a rheostat of ribosome content, possibly to secure spare translational capacity that can be mobilized during stress. Are there mRNA‐selective functions of individual eIF3 subunits? Here, multiomic profiling upon acute depletion of eIF3 subunits uncovers eIF3k‐l as an mRNA‐specific module that serves as a rheostat of ribosome content, securing spare translational capacity that can be mobilized during stress. Acute depletion of eIF3 subunits has subunit‐selective impact on holo‐eIF3 architecture.eIF3k depletion uniquely causes increased tumor growth and ribosome content.eIF3k depletion boosts the translation of RPS15A mRNA through an eIF3‐binding site in the 5′‐UTR.eIF3k and eIF3l are selectively downregulated by cellular stress, thus promoting cell survival. [ABSTRACT FROM AUTHOR]

Self-supervised graph representation Learning (SSGRL) is an emerging technique for machine learning-based expert applications. SSGRL can effectively encode unlabeled data into machine-understandable knowledge embeddings that can be used in downstream expert tasks. Recently, Masked-Graph-Model (MGM) has achieved extraordinary performances in the field of SSGRL. However, MGM inevitably suffers from a so-called Negative-Migration (NM) problem on unbalanced datasets for specific tasks such as graph classification. The NM problem forces the MGM to predict (reconstruct) the dominant nodes causing the ignoring of the minority but critical nodes. To this end, a novel online prediction module is proposed to dynamically predict the nodes with extended contexts that enable minority nodes can have more weights in the model. Based on the online prediction module, a graph representation learning model is proposed to alleviate the NM problem. Extensive experiments demonstrate that the model outperforms state-of-the-art methods on unbalanced datasets and achieves competitive performance on balanced datasets. Moreover, extra experiments demonstrate that the proposed method requires less computational resource overhead than existing methods. The code is available at: https://github.com/DuanhaoranCC/SimGOP. • This paper explores the negative migration problem encountered in unbalanced datasets. • We propose online predict contextual node features, but the not the original data. • The results of graph classification show that the proposed method achieves SOTA results. [ABSTRACT FROM AUTHOR]

• Dosing Mg (OH) 2 in sewers increases sewage pH and reduces the transfer of H 2 S. • Long-term pH elevation partially inhibits biological processes in sewers. • Mg (OH) 2 offers additional alkalinity which improves nitrification rate. • In sewer Mg (OH) 2 -dosing reduces soluble phosphate concentration in digested sludge. • Mg (OH) 2 -dosing improves sludge settleability and digested sludge dewaterability. Magnesium hydroxide [ Mg (OH) 2 ] is a non-hazardous chemical widely applied in sewer systems for managing odour and corrosion. Despite its proven effectiveness in mitigating these issues, the impacts of dosing Mg (OH) 2 in sewers on downstream wastewater treatment plants have not been comprehensively investigated. Through a one-year operation of laboratory-scale urban wastewater systems, including sewer reactors, sequencing batch reactors, and anaerobic sludge digesters, the findings indicated that Mg (OH) 2 dosing in sewer systems had multifaceted benefits on downstream treatment processes. Compared to the control, the Mg (OH) 2 -dosed experimental system displayed elevated sewage pH (8.8 ± 0.1 vs 7.1 ± 0.1), reduced sulfide concentration by 35.1 % ± 4.9 % (6.7 ± 0.9 mg S L − 1 ), and lower methane concentration by 58.0 % ± 4.9 % (19.1 ± 3.6 mg COD L − 1 ). Additionally, it increased alkalinity by 16.3 % ± 2.2 % (51.9 ± 5.4 mg CaC O 3 L − 1 ), and volatile fatty acids concentration by 207.4 % ± 22.2 % (56.6 ± 9.0 mg COD L − 1 ) in sewer effluent. While these changes offered limited advantages for downstream nitrogen removal in systems with sufficient alkalinity and carbon sources, significant improvements in ammonium oxidation rate and NOx reduction rate were observed in cases with limited alkalinity and carbon sources availability. Moreover, Mg (OH) 2 dosing in upstream did not have any detrimental effects on anaerobic sludge digesters. Magnesium-phosphate precipitation led to a 31.7 % ± 4.1 % reduction in phosphate concertation in anaerobic digester sludge supernatant (56.1 ± 10.4 mg P L − 1 ). The retention of magnesium in sludge increased settleability by 13.9 % ± 1.6 % and improved digested sludge dewaterability by 10.7 % ± 5.3 %. Consequently, the use of Mg (OH) 2 dosing in sewers could potentially reduce downstream chemical demand and costs for carbon sources (e.g., acetate), pH adjustment and sludge dewatering. [Display omitted] [ABSTRACT FROM AUTHOR]

Ultrasound has in the past few decades found applications in a variety of disciplines including chemistry, medicine, physics, and to a much less extent microbiology. Our previous studies found that ultrasonic treatment increases the activity of ammonia-oxidizing bacteria (AOB) while suppressing nitrite-oxidizing bacteria (NOB), resulting in beneficial effects in wastewater treatment. In this study, the kinetic and microbiological features of nitrifying microorganisms in activated sludge intermittently treated with ultrasound were investigated to gain an improved understanding of the mechanism involved in ultrasound-induced stimulation of AOB kinetics. The nitrifying microorganisms were initially enriched over 100 days in a laboratory sequential batch reactor (SBR). Ultrasonic treatment of the sludge was then applied with the treatment time in each 12 h SBR cycle progressively increased from 4 to 24 min. Application of the treatment for 21 days led to a doubled maximum specific ammonia oxidation rate, and also the enhanced dominance of known AOB Nitrosomonas genus in the biomass. This stimulatory effect is well described by a modified enzyme catalyzed reaction model, showing a good linear relationship between the natural logarithm value of μ max,AOB and the applied ultrasonic energy density. This result suggests that ultrasonic treatment likely reduced the activation energy of key enzymes involved in ammonium oxidation. Unlabelled Image • Ultrasonic treatment significantly enhances specific ammonia oxidation rate. • Dominance of known AOB Nitrosomonas genus is also enhanced in the biomass. • A modified enzyme catalyzed reaction model is proposed. • A good linear relationship between ln(μ max,AOB) and ultrasonic energy density. • The model can well describe the ultrasonic-assisted ammonia oxidation reaction. [ABSTRACT FROM AUTHOR]

Sidestream sludge treatment approaches have been developed in recent years to achieve mainstream nitrite shunt or partial nitritation, where NOB are selectively inactivated by biocidal factors such as free nitrous acid (FNA) or free ammonium (FA) in a sidestream reactor. The existence of NOB in raw wastewater has been increasingly realized and could pose critical challenge to stable NOB suppressions in those systems. This study, for the first time, evaluated the impact of influent NOB on the NOB suppressions in a mainstream nitrite shunt system achieved through sidestream sludge treatment. An over 500-day sequential batch reactor operation with six experimental phases rigorously demonstrated the negative effects of influent NOB on mainstream NOB control. Continuously seeding of NOB contained in influent stimulated NOB community shifts, leading to different extents of ineffective NOB suppression. The role of primary wastewater treatment in NOB removal from raw wastewater was also investigated. Results suggest primary settling and High Rate Activated Sludge system could remove a large part of NOB contained in raw wastewater. Primary treatment for raw wastewater is necessary for ensuring stable mainstream NOB suppressions. Image 1 • Influent NOB challenge NOB suppression by stimulating community shift and resistance. • Primary settling substantially reduces NOB in raw wastewater. • High-rate activated sludge treatment substantially reduces NOB in raw wastewater. • This study expanded the current knowledge of mainstream NOB suppression. [ABSTRACT FROM AUTHOR]

Abstract Free nitrous acid (FNA) pre-treatment has been previously demonstrated to be effective in enhancing methane production and volatile solids (VS) destruction in the anaerobic digestion of waste activated sludge for an equivalent hydraulic retention time (HRT). We hypothesise that, due to enhancement of hydrolysis kinetics, FNA pre-treatment will also allow reduction in the HRT while retaining performance. This would allow for improvement of capacity constrained digesters. Two anaerobic sludge digesters (control-experiment) were fed with the same thickened waste activated sludge (TWAS) from a full-scale plant for 6 months. With 24 h pre-treatment of TWAS at an FNA concentration of 6.1 mgN/L (NO 2 -N = 250 mg/L, pH = 5.0, T = 25 °C), the HRT for the experimental anaerobic digester was progressively reduced from 15 days to 12 days and then to 7.5 days. In comparison, the control reactor was operated at a constant HRT of 15 days, representing typical loading conditions. With the shortened HRTs, the experimental AD reactor achieved VS destruction at 36.9 ± 0.8% (12 days) and 36.8 ± 1.0% (7.5 days), representing 30–40% relative increase in comparison to the control reactor (at 26.5 ± 0.8% and 28.3 ± 0.7%, respectively, in the same two periods). This was supported by a similar (31–35%) increase in the methane production per unit of VS fed. The volumetric methane production rate of the experimental digester was increased by 165% at HRT of 7.5 days compared with the control digester at HRT of 15 days. The results demonstrated that FNA pre-treatment of TWAS can substantially increase the capacity of an anaerobic sludge digester, with a highly favourable economic outcome. Graphical abstract Image 1 Highlights • FNA pre-treatment enables higher VS removal and CH 4 production in AD at reduced HRT. • FNA pre-treatment enables reduction of anaerobic sludge digester HRT by up to 50%. • This study provides a retrofitting method for enhancing capacity of AD digesters. • FNA pre-treatment does not cause acidification of AD due to enhanced NH 4 + release. [ABSTRACT FROM AUTHOR]

Abstract Inline sludge treatment using free nitrous acid (FNA) was recently shown to be effective in establishing the nitrite pathway in a biological nitrogen removal system. However, the effects of FNA treatment conditions on the nitrite pathway performance remained to be investigated. In this study, three different FNA treatment frequencies (daily sludge treatment ratios of 0.22, 0.31 and 0.38, respectively), two FNA concentrations (1.35 mgN/L and 4.23 mgN/L, respectively) and two influent feeding regimes (one- and two-step feeding) were investigated in four laboratory-scale sequencing batch reactors. The nitrite accumulation ratio was positively correlated to the FNA treatment frequency. However, when a high treatment frequency was used e.g., daily sludge treatment ratio of 0.38, a significant reduction in ammonia oxidizing bacteria (AOB) activity occurred, leading to poor ammonium oxidation. AOB were able to acclimatise to FNA concentrations up to of 4.23 mgN/L, whereas nitrite oxidizing bacteria (NOB) were limited by an FNA concentration of 1.35 mgN/L over the duration of the study (up to 120 days). This difference in sensitivity to FNA could be used to further enhance nitrite accumulation, with 90% accumulation achieved at an FNA concentration of 4.23 mgN/L and a daily sludge treatment ratio of 0.31 in this study. However, this high level of nitrite accumulation led to increased N 2 O emission, with emission factors of up to 3.9% observed. The N 2 O emission was mitigated (reduced to 1.3%) by applying two-step feeding resulting in a nitrite accumulation ratio of 45.1%. Economic analysis showed that choosing the optimal FNA treatment conditions depends on a combination of the wastewater characteristics, the nitrogen discharge standards, and the operational costs. This study provides important information for the optimisation and practical application of FNA-based sludge treatment technology for achieving the mainstream stable nitrite pathway. Graphical abstract Unlabelled Image Highlights • Study result and analysis guide free nitrous acid treatment condition determination • Stable mainstream nitrite pathway reached with nitrite accumulation ratio over 90%. • Distinct nitrifying bacteria acclimation behaviours to high treatment concentration • Treatment frequency negatively related to in-reactor nitrifying bacteria activities. • N 2 O emission mainly from nitrifier denitrification, can be reduced by multi-feeding. [ABSTRACT FROM AUTHOR]

• ·The determining role on N 2 O production transited from NO 2 − to FNA especially beyond 0.015 mg HNO 2 -N/L. • ·pH affected N 2 O pathway regulation but not the overall N 2 O production rate. • ·Elevated pH promoted NN while decreased pH promoted ND pathway. • ·NO 2 − promoted ND N 2 O production pathway, while high FNA inhibited it. • ·The susceptibility of NO production to FNA lagged behind that of N 2 O. In the pursuit of energy and carbon neutrality, nitrogen removal technologies have been developed featuring nitrite (NO 2 −) accumulation. However, high NO 2 − accumulations are often associated with stimulated greenhouse gas (i.e., nitrous oxide, N 2 O) emissions. Furthermore, the coexistence of free nitrous acid (FNA) formed by NO 2 − and proton (pH) makes the consequence of NO 2 − accumulation on N 2 O emissions complicated. The concurrent three factors, NO 2 −, pH and FNA may play different roles on N 2 O and nitric oxide (NO) emissions simultaneously, which has not been systematically studied. This study aims to decouple the effects of NO 2 − (0-200 mg N/L), pH (6.5-8) and FNA (0-0.15 mg N/L) on the N 2 O and NO production rates and the production pathways by ammonia oxidizing bacteria (AOB), with the use of a series of precisely executed batch tests and isotope site-preference analysis. Results suggested the dominant factors affecting the N 2 O production rate were NO 2 − and FNA concentrations, while pH alone played a relatively insignificant role. The most influential factor shifted from NO 2 − to FNA as FNA concentrations increased from 0 to 0.15 mg N/L. At concentrations below 0.0045 mg HNO 2 -N/L, nitrite rather than FNA played a significant role stimulating N 2 O production at elevated nitrite concentrations. The inhibition effect of FNA emerged with further increase of FNA between 0.0045-0.015 mg HNO 2 -N/L, weakening the promoting effect of increased nitrite. While at concentrations above 0.015 mg HNO 2 -N/L, FNA inhibited N 2 O production especially from nitrifier denitrification pathway with the level of inhibition linearly correlated with the FNA concentration. pH and the nitrite concentration regulated the production pathways, with elevated pH promoting the nitrifier nitrification pathway, while elevated NO 2 − concentrations promoting the nitrifier denitrification pathway. In contrast to N 2 O, NO emission was less susceptible to FNA at concentrations up to 0.015 mg N/L but was stimulated by increasing NO 2 − concentrations. This study, for the first time, distinguished the effects of pH, NO 2 − and FNA on N 2 O and NO production, thereby providing support to the design and operation of novel nitrogen removal systems with NO 2 − accumulation. [Display omitted] [ABSTRACT FROM AUTHOR]

Nitrous oxide (N 2 O) is an important greenhouse gas and an ozone-depleting substance which can be emitted from wastewater treatment systems (WWTS) causing significant environmental impacts. Understanding the N 2 O production pathways and their contribution to total emissions is the key to effective mitigation. Isotope technology is a promising method that has been applied to WWTS for quantifying the N 2 O production pathways. Within the scope of WWTS, this article reviews the current status of different isotope approaches, including both natural abundance and labelled isotope approaches, to N 2 O production pathways quantification. It identifies the limitations and potential problems with these approaches, as well as improvement opportunities. We conclude that, while the capabilities of isotope technology have been largely recognized, the quantification of N 2 O production pathways with isotope technology in WWTS require further improvement, particularly in relation to its accuracy and reliability. [ABSTRACT FROM AUTHOR]

Biological nitrogen removal through the nitrite pathway (NH4+ → NO2- → N2) is favorable for wastewater treatment plants without sufficient carbon sources. This study demonstrates an innovative approach for attaining the nitrite pathway based on sludge treatment using free ammonia (FA, i.e., NH3). This approach is based on our innovative discovery in this study that FA at 210 mg NH3-N/L is far less biocidal to ammonium-oxidizing bacteria (AOB) than to nitrite-oxidizing bacteria (NOB). A total of 22% of the activated sludge from the sequencing batch reactor (SBR) receiving synthetic domestic wastewater was treated in an FA treatment unit at 210 mg NH3-N/L for 1 day. The FA-treated sludge was afterward recirculated back to the SBR. A nitrite accumulation ratio of above 90% was quickly achieved (in 40 days) and maintained stably in the SBR, indicating the establishment of the nitrite pathway. The NOB population and activity after implementing FA treatment was less than 5% of those without FA treatment, suggesting the washout of NOB. In contrast, the AOB population and activity in the SBR were not affected. The nitrogen-removal performance was significantly improved after incorporating the FA approach. The FA approach is a closed-loop approach and is economically and environmentally attractive. [ABSTRACT FROM AUTHOR]

With the growing concern of global warming, many water utilities are pioneering in mitigating greenhouse gas (GHG) emissions, with some water utilities aiming to achieve net-zero emissions operation in the next decade. However, for wastewater treatment plants (WWTPs), the carbon footprint of different treatment technologies and its contribution among various units within each treatment configuration is still unclear. This study evaluates the impacts of process design on the carbon footprint of WWTPs through the analysis of scope 1 (direct emission), scope 2 (indirect emission), and scope 3 (value chain emission) emissions. The comprehensive configuration design in this work considered three nutrient removal processes including typical aerobic and anaerobic wastewater treatment technologies. Emissions from the sludge management processes are also calculated, including aerobic and anaerobic sludge stabilization processes, short-term and long-term sludge storage, and three sludge disposal options. In total, 45 processes were analysed and the results were compared. The results showed the carbon footprints are highly dependent on the treatment configurations of WWTPs. Analysis suggested scope 2 & 3 emissions can be reduced by selecting suitable processes. In general, anaerobic wastewater and sludge stabilization technologies are more suitable than aerobic technologies to reduce scope 2 & 3 emissions, leading to a lower overall carbon footprint. In comparison, configuration design offers limited opportunities to reduce scope 1 emissions, which may be the future challenge for WWTP to achieve carbon neutrality. [Display omitted] [ABSTRACT FROM AUTHOR]

With the growing concern of global warming, many water utilities are pioneering in mitigating greenhouse gas (GHG) emissions, with some water utilities aiming to achieve net-zero emissions operation in the next decade. However, for wastewater treatment plants (WWTPs), the carbon footprint of different treatment technologies and its contribution among various units within each treatment configuration is still unclear. This study evaluates the impacts of process design on the carbon footprint of WWTPs through the analysis of scope 1 (direct emission), scope 2 (indirect emission), and scope 3 (value chain emission) emissions. The comprehensive configuration design in this work considered three nutrient removal processes including typical aerobic and anaerobic wastewater treatment technologies. Emissions from the sludge management processes are also calculated, including aerobic and anaerobic sludge stabilization processes, short-term and long-term sludge storage, and three sludge disposal options. In total, 45 processes were analysed and the results were compared. The results showed the carbon footprints are highly dependent on the treatment configurations of WWTPs. Analysis suggested scope 2 & 3 emissions can be reduced by selecting suitable processes. In general, anaerobic wastewater and sludge stabilization technologies are more suitable than aerobic technologies to reduce scope 2 & 3 emissions, leading to a lower overall carbon footprint. In comparison, configuration design offers limited opportunities to reduce scope 1 emissions, which may be the future challenge for WWTP to achieve carbon neutrality. [Display omitted] [ABSTRACT FROM AUTHOR]

• Evaluation of two novel sidestream treatment-based strategies for nitrite shunt. • Pilot-scale systems operated for >850 days to assess the process robustness. • Solely alternating sludge treatment approach is challenged by NOB adaptation. • Robust nitrite shunt process for 1 yr. by integrating sludge treatment and step-feed. • Kinetic analysis suggests integrated strategy is key to robust nitrite shunt. As a promising energy- and carbon efficient process for nitrogen removal from wastewater, mainstream nitrite shunt has been extensively researched. However, beyond the laboratory it is challenging to maintain stable performance by suppressing nitrite-oxidising bacteria (NOB). In this study, a pilot-scale reactor system receiving real sewage was operated in two stages for >850 days to evaluate two novel NOB suppression strategies for achieving nitrite shunt: i) sidestream sludge treatment based on alternating free nitrous acid (FNA) and free ammonia (FA) and ii) sidestream FNA/FA sludge treatment integrated with in-situ NOB suppression via step-feed. The results showed that, with sidestream sludge treatment alone, NOB developed resistance relatively quickly to the treatment, leading to unstable nitrite shunt. In contrast, robust nitrite shunt was achieved and stably maintained for more than a year when sidestream sludge treatment was integrated with a step-feed strategy. Kinetic analyses suggested that sludge treatment and step-feed worked in synergy, leading to stable NOB suppression. The integrated strategy demonstrated in this study removes a key barrier to the implementation of stable mainstream nitrite shunt. [Display omitted] [ABSTRACT FROM AUTHOR]

• First investigation of key FNA pre-treatment condition in continuous AD operation. • CH 4 production and VS destruction are positively correlated to viscosity reduction. • Solubilization is inconsistent with long-term results potentially due to inhibitions. • Optimal condition identified to be FNA level of 7.2 mgN/L and duration of 24-hour. • Optimized pre-treatment is competitive with other pre-treatment technologies. Free Nitrous Acid (FNA) pre-treatment is a promising technology demonstrated effective in improving waste activated sludge degradability and anaerobic digestion (AD) performance. Pre-treatment conditions including FNA concentration and treatment duration determine operational and capital cost of full-scale implementation, which have not been studied in long-term experiments. The knowledge of FNA pre-treatment conditions improving the AD performance is urgently required to determine suitable conditions for the technology implementation. In this work, five different FNA concentrations (2.2, 4.4, 7.2, 12 mgN/L and nitrite only without pH adjustment) and three treatment durations (8, 24 and 48 h) were studied in four lab-scale semi-continuous AD reactors for over 300 days. FNA pre-treatment was shown under all tested conditions effective in enhancing AD performances, while its effectiveness and resulted benefits varied substantially amongst different pre-treatment conditions. The long-term experiment demonstrated that the methane production, sludge reduction and digested sludge viscosity of AD are positively correlated with the FNA concentration and durations, until an optimal condition is reached, which was identified in this work to be FNA concentration of 7.2 mgN/L and treatment duration of 24 h. Microbial community changes supported the apparent observation of enhanced sludge degradation at elevating FNA concentrations applied during pre-treatment. The short-term sludge solubilization results were inconsistent with the long-term AD performance, which was potentially caused by inhibitions from stringent FNA pre-treatment conditions applied (FNA = 12 mgN/L with 24-hour treatment & FNA = 7.2 mgN/L with 48-hour treatment). Overall, results suggested FNA pre-treatment at the optimized condition is highly beneficial to WWTPs and competitive with other pre-treatment technologies, e.g., thermal hydrolysis pre-treatment. This work comprehensively evaluated the key design parameters of FNA pre-treatment process, reached a major milestone in the development and applications of FNA technologies. [ABSTRACT FROM AUTHOR]

• Stable P removal (> 120 d) was achieved via nitrite pathway in a single sludge system. • The two classical PAOs Accumulibacter and Dechloromonas , were eliminated from the system. • Side-stream treatment favours the selection of high FNA-tolerance PAOs. • Economic analysis reveals up to 27% saving of this new option for BNR in WWTPs. Biological nitrogen (N) removal via the short-cut pathway (NH 4 +-N→NO 2 −-N→N 2) is economically attractive in wastewater treatment plants (WWTPs). However, biological phosphorus (P) removal processes remain a bottleneck in these systems due to the strong inhibitory effect of nitrite or its protonated form (HNO 2 , free nitrous acid - FNA) on polyphosphate accumulating organisms (PAOs). In this study, a novel combined nitrogen and phosphorus removal strategy was verified and achieved in a biological short-cut nitrogen removal system via side-stream sludge treatment with FNA, and the mechanisms impacting this process were investigated. The side-stream FNA treatment process applied here led to a significant reduction in the real sludge retention time (SRT) in the mainstream (approximately 2.7 days) based on the biocidal effect of FNA to the majority of the organisms. This work also found that around 40% of the P uptake activity was still maintained at a much higher FNA level of 38 μg N/L with potential PAOs, which highly broadened the current knowledge of PAOs community. An economic analysis revealed advantages of the proposed as compared to conventional biological nitrogen and phosphorus removal (13% savings in total cost), biological short-cut nitrogen removal (via FNA treatment) with chemical phosphorus precipitation (21% savings) and conventional biological nitrogen removal with chemical precipitation (27% savings). Overall, this study presents a novel and viable retrofit strategy in integrating biological short-cut nitrogen removal with EBPR for next generation WWTPs. [Display omitted] [ABSTRACT FROM AUTHOR]

• A new Fe-dosing strategy proposes centralized dosage into returned sludge than sewage. • Centralized Fe-dosing acidifies sludge and resulted in free nitrous acid accumulation. • The new strategy achieves less biomass production and shortcut nitrogen removal. • The new strategy still provides the same benefits as common mainstream Fe-dosing. Iron salts (i.e. FeCl 3) are the most used chemicals in the urban wastewater system. Iron is commonly dosed into sewage or the mainstream system, which provides multiple benefits such as enhanced phosphorus removal and improved sludge settleability/dewaterability. This study reported and demonstrated a new approach that dosed FeCl 3 into returned sludge in order to bring two more benefits to wastewater management: short-cut nitrogen removal via the nitrite pathway and less biomass production. This approach is achieved based on our findings that with similar amount of FeCl 3 , centralized iron dosing into a sidestream sludge unit generated iron concentration two orders of magnitude higher than the common mainstream dosing (e.g. 10–40 mg Fe/L-wastewater), leading to sludge acidification (pH = 2.1) with Fe (III) hydrolysis. Together with accumulated nitrite in the supernatant of the sludge, ppm-level of free nitrous acid was generated and thus enabled sludge disintegration, cell lysis, and selective elimination of nitrite-oxidizing bacteria (NOB). Long-term effects on nitrifying bacteria and overall reactor performance were evaluated using two laboratory reactor experiments for over one year. The experimental reactor showed stable nitrite accumulation with an average NO 2 −/(NO 2 − + NO 3 −) ratio above 80% and ∼30% observed biomass yield reduction compared to those in control reactors. In addition, the centralized sludge dosing strategy still provided benefits such as improved settleability and dewaterability of sludge and enhanced phosphorus removal. [Display omitted] [ABSTRACT FROM AUTHOR]

• A pretreatment method is developed to yield multiple benefits for AD process. • Combined FeCl 3 and nitrite pretreatment favors the formation of ppm-level FNA. • Degradability of WAS is significantly enhanced after 24-hour pretreatment. • Dosed Fe also improves biogas quality and vivianite recovery from digested sludge. Anaerobic digestion (AD) is an essential process in wastewater treatment plants as it can reduce the amount of waste activated sludge (WAS) for disposal, and also enables the recovery of bioenergy (i.e. methane). Here, a new pretreatment method to enhance anaerobic digestion was achieved by treating thickened WAS (TWAS) with ferric (as FeCl 3) and nitrite simultaneously for 24-hour at room temperature. Biochemical methane potential tests showed markedly improved degradability in the pretreated TWAS, with a relative increase in hydrolysis rate by 30%. A comparative experiment with the operation of two continuous-flow anaerobic digesters further demonstrated the improvement in biogas quantity and quality, digestate disposal, and phosphorus recovery in the experimental digester. The dosed FeCl 3 (i.e. ~6 mM) decreased the pH of TWAS to ~5, which led to the formation of free nitrous acid (FNA, HNO 2) at parts per million levels (i.e. ~6 mg N/L), after dosing nitrite at 250 mg NO 2 −–N/L. This FNA treatment caused a 26% increase in methane yield and volatile solids destruction, 55% reduction in the viscosity of sludge in digester, and 24% less polymer required in further digestate dewatering. In addition, the dosed Fe(III) was reduced to Fe(II) which precipitated sulfide and phosphorus, leading to decreased hydrogen sulfide concentration in biogas, and increased percentage of vivianite in the total crystalline iron species in digested sludge. Our study experimentally demonstrated that combined dosing of FeCl 3 and nitrite is a useful pretreatment strategy for improving anaerobic digestion of WAS. [Display omitted] [ABSTRACT FROM AUTHOR]

• Wind power prediction problem is formulated as a min-max game based on GAN. • Semi-supervised regression is used for the point prediction of wind power. • A double objective model is designed for data augmentation and feature extraction. • A self-tuning strategy is proposed for forecasting of wind power ramp events. Short-term predictions of wind power and its ramp events play a critical role in economic operation and risk management of smart grid. This paper proposes a hybrid forecasting model based on semi-supervised generative adversarial network (GAN) to solve the short-term wind power outputs and ramp event forecasting problems. In the proposed model, the original time series of wind energy data can be decomposed into several sub-series characterized by intrinsic mode functions (IMFs) with different frequencies, and the semi-supervised regression with label learning is employed for data augmentation to extract non-linear and dynamic behaviors from each IMF. Then, the GAN generative model is used to obtain unlabeled virtual samples for capturing data distribution characteristics of wind power outputs, while the discriminative model is redesigned with a semi-supervised regression layer to perform the point prediction of wind power. These two GAN models form a min-max game so as to improve the sample generation quality and reduce forecasting errors. Moreover, a self-tuning forecasting strategy with multi-label classifier is proposed to facilitate the forecasting of wind power ramp events. Finally, the real data of a wind farm from Belgium is collected in the case study to demonstrate the superior performance of the proposed approach compared with other forecasting algorithms. [ABSTRACT FROM AUTHOR]

As the critical parts of wind turbines, rolling bearings are prone to faults due to the extreme operating conditions. To avoid the influence of the faults on wind turbine performance and asset damages, many methods have been developed to monitor the health of bearings by accurately analyzing their vibration signals. Stochastic resonance (SR)-based signal enhancement is one of effective methods to extract the characteristic frequencies of weak fault signals. This paper constructs a new SR model, which is established based on the joint properties of both Power Function Type Single-Well and Woods-Saxon (PWS), and used to make fault frequency easy to detect. However, the collected vibration signals usually contain strong noise interference, which leads to poor effect when using the SR analysis method alone. Therefore, this paper combines the Fourier Decomposition Method (FDM) and SR to improve the detection accuracy of bearing fault signals feature. Here, the FDM is an alternative method of empirical mode decomposition (EMD), which is widely used in nonlinear signal analysis to eliminate the interference of low-frequency coupled signals. In this paper, a new stochastic resonance model (PWS) is constructed and combined with FDM to enhance the vibration signals of the input and output shaft of the wind turbine gearbox bearing, make the bearing fault signals can be easily detected. The results show that the combination of the two methods can detect the frequency of a bearing failure, thereby reminding maintenance personnel to urgently develop a maintenance plan. [ABSTRACT FROM AUTHOR]

Multi-focus image fusion (MFIF) attempts to achieve an “all-focused” image from multiple source images with the same scene but different focused objects. Given the lack of multi-focus image sets for network training, we propose a self-supervised residual feature learning model in this paper. The model consists of a feature extraction network and a fusion module. We select image super-resolution as a pretext task in the MFIF field, which is supported by a new residual gradient prior discovered by our theoretical study for low- and high-resolution (LR-HR) image pairs, as well as for multi-focus images. In the pretext task, our network’s training set is LR-HR image pairs generated from natural images, and HR images can be regarded as pseudo-labels of LR images. In the fusion task, the trained network extracts residual features of multi-focus images firstly. Secondly, the fusion module, consisting of an activity level measurement and a new boundary refinement method, is leveraged for the features to generated decision maps. Experimental results, both subjective evaluations and objective evaluations, demonstrate that our approach outperforms other state-of-the-art fusion algorithms. [ABSTRACT FROM AUTHOR]

The goal of our work is to generate high-quality novel views from monocular videos of complex and dynamic scenes. Prior methods, such as DynamicNeRF, have shown impressive performance by leveraging time-varying dynamic radiation fields. However, these methods have limitations when it comes to accurately modeling the motion of complex objects, which can lead to inaccurate and blurry renderings of details. To address this limitation, we propose a novel approach that builds upon a recent generalization NeRF, which aggregates nearby views onto new viewpoints. However, such methods are typically only effective for static scenes. To overcome this challenge, we introduce a module that operates in both the time and frequency domains to aggregate the features of object motion. This allows us to learn the relationship between frames and generate higher-quality images. Our experiments demonstrate significant improvements over state-of-the-art methods on dynamic scene datasets. Specifically, our approach outperforms existing methods in terms of both the accuracy and visual quality of the synthesized views. Our code is available on https://github.com/xingy038/CTNeRF. • Presented a novel dynamic neural rendering approach for dynamic monocular videos, leveraging the aggregation of multi-view feature vectors to enhance the quality of rendering novel views. • Combining multi-frame feature vectors can lead to the loss or merging of intricate details, risking the preservation of crucial characteristics from the original data. To address this, we introduce a Ray-based cross-time transformer. • To mitigate potential blurring effects during feature aggregation, we propose the incorporation of a Global Spatio-Temporal Filter. [ABSTRACT FROM AUTHOR]

• First reported N 2 O mitigation strategy permanently implemented at full-scale. • 35% N 2 O emission reduction was achieved with 20% less operational cost. • N 2 O mitigation did not affect nutrient removal performance. • Validated multi-pathway N 2 O model at full-scale to evaluate mitigation strategies. • Proposed a standard approach for mitigating N 2 O emissions at full-scale plants. Mitigation of nitrous oxide (N 2 O) emissions is of primary importance to meet the targets of reducing carbon footprints of wastewater treatment plants (WWTPs). Despite of a large amount of N 2 O mitigation studies conducted in laboratories, full-scale implementation of N 2 O mitigation is scarce, mainly due to uncertainties of mitigation effectiveness, validation of N 2 O mathematical model, risks to nutrient removal performance and additional costs. This study aims to address the uncertainties by investigating the quantification, development and implementation of N 2 O mitigation strategies at a full-scale sequencing batch reactor (SBR). To achieve this, N 2 O emission dynamics, nutrient removal performance and operation of the SBR were monitored to quantify N 2 O emissions, and identify the N 2 O generation mechanisms. N 2 O mitigation strategies centered on reducing dissolved oxygen (DO) levels were consequently proposed and evaluated using a multi-pathway N 2 O production mathematical model before implementation. The implemented mitigation strategy resulted in a 35% reduction in N 2 O emissions (from the emission factor of 0.89 ± 0.05 to 0.58 ± 0.06%), which was equivalent to annual reduction of 2.35 tonne of N 2 O from the studied WWTP. This could be mainly attributed to reductions in N 2 O generated via the NH 2 OH oxidation pathway due to the lowering of DO level. As the first reported mitigation strategy permanently implemented at a full scale WWTP, it showcased that the mitigation of N 2 O emissions at full-scale is feasible and that widely accepted N 2 O mitigation strategies developed in laboratory studies are also likely effective in full-scale plants. Furthermore, the close agreement between the validated and predicted N 2 O emission factors (0.58% vs 0.55%, respectively), showed that the N 2 O mathematical model is a useful tool to evaluate N 2 O mitigation strategies at full-scale. Importantly this work demonstrated that N 2 O mitigation does not necessarily require additional operational cost to meet reduction targets. In contrast, the N 2 O mitigation applied here reduced energy requirements for aeration by 20%. Equally important, long-term monitoring identified that N 2 O mitigation did not affect the nutrient removal performance of the plant. Finally, with the knowledge acquired in this study, a standard approach for mitigating N 2 O emissions from full-scale treatment plants was proposed. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Sludge treatment using free ammonia (FA) is an innovative approach that was recently reported effective achieving stable mainstream nitrogen removal via the nitrite pathway. This study aims to investigate the adaptation of nitrifying community and the response of nitrification performance to high-level of FA exposure under real wastewater conditions. Two parallel lab-scale sequencing batch reactors were operated and fed with real municipal wastewater, with one receiving sludge treatment by FA and another as a control. While the FA approach rapidly achieved partial nitrification with a nitrite accumulation ratio (NAR) of approximately 60%, the partial nitrification eventually failed due to nitrite-oxidizing bacteria (NOB) adaptation to FA inactivation. NOB activity in the inoculum was suppressed by 82% after exposure to FA at ~220 mg NH 3 -N/L. However, towards the end of the experiments, significantly higher NOB activities were observed after exposure to the same level of FA. Distinct behaviours of NOB observed in batch tests during the study supported the reactor operational data and strongly suggested the adaptation of NOB under the FA stress. Furthermore, microbial community analysis revealed the underlying mechanism of the observed adaptation: the dominant NOB changed from Nitrospira to Candidatus Nitrotoga. It is for the first time shown that Ca. Nitrotoga are highly resistant to FA inhibition and inactivation in comparison to Nitrospira and Nitrobacter. In addition, while the Nitrosomonas genus was always the dominant ammonia-oxidizing bacteria (AOB) throughout the study, different shift in a species level was observed. Unlabelled Image • Inactivation and adaptation of nitrifiers exposed to FA were investigated. • Dominant NOB genus shifted from Nitrospira to Ca. Nitrotoga under FA stress. • Ca. Nitrotoga are resistant to FA inhibition/inactivation compared with other NOB. • Nitrosomonas were always dominant AOB genus under FA stress. [ABSTRACT FROM AUTHOR]

In this study, the effects of free nitrous acid (FNA) pre-treatment on the rheological properties of digested sludge were investigated at a pilot-scale, along with the improvement in volatile solids (VS) destruction and biogas production. Two pilot-scale anaerobic sludge digesters were operated for one year, one receiving thickened waste activated sludge (TWAS) without pre-treatment (control) and one receiving TWAS pre-treated for 24 h at an FNA concentration of 4.9–6.1 mgN/L (nitrite = 250 mgN/L, pH = 5.0, T = 22–30 °C). The results confirmed the enhancing effect of FNA pre-treatment on methane production (37 ± 1%), consistent with previous laboratory studies. Equally importantly, FNA pre-treatment substantially reduced the shear viscosity of TWAS by 51 ± 8% at 100 s−1 and 49 ± 7% at 250 s−1, likely due to the solubilization of the TWAS (11.1 ± 0.8%). Similarly, FNA pre-treatment also reduced these viscosity parameters of the digested sludge by 80 ± 4% and 78 ± 4%, respectively, caused by both enhanced VS destruction and disintegration of the digested sludge. The dewaterability of digested sludge, assessed by dewatered solids content, capillary suction time and specific resistance to filtration, was not improved by FNA pre-treatment. The polymer requirement for dewatering was reduced by 24 ± 0.6% due to the lower solids concentration in the digested sludge achieved with FNA pre-treatment. The changes to sludge rheological properties revealed in this study further enhances the business case for the FNA pre-treatment technology. Image 1 • Effects of FNA pre-treatment of WAS on anaerobic digestion assessed at pilot-scale. • FNA pre-treatment enhances methane production and VS destruction. • FNA pre-treatment reduces viscosity of treated WAS and also the digested sludge. • The reduction in viscosity increases the capacity of anaerobic digesters. [ABSTRACT FROM AUTHOR]

Free nitrous acid (FNA), the protonated form of nitrite, has historically been an unwanted substance in wastewater systems due to its inhibition on a wide range of microorganisms. However, in recent years, advanced understanding of FNA inhibitory and biocidal effects on microorganisms has led to the development of a series of FNA-based applications that improve wastewater management practices. FNA has been used in sewer systems to control sewer corrosion and odor; in wastewater treatment to achieve carbon and energy efficient nitrogen removal; in sludge management to improve the sludge reduction and energy recovery; in membrane systems to address membrane fouling; and in wastewater algae systems to facilitate algae harvesting. This paper aims to comprehensively and critically review the current status of FNA-based applications in improving wastewater management. The underlying mechanisms of FNA inhibitory and biocidal effects are also reviewed and discussed. Knowledge gaps and current limitations of the FNA-based applications are identified; and perspectives on the development of FNA-based applications are discussed. We conclude that the FNA-based technologies have great potential for enhancing the performance of wastewater systems; however, further development and demonstration at larger scales are still required for their wider applications. Image 1 • Underlying mechanisms of FNA inhibitory and biocidal effects are reviewed. • FNA is used to control sewer corrosion and odor, and membrane fouling. • FNA improves wastewater treatment, sludge management and algae harvesting. • Knowledge gaps and current limitations of the FNA-based applications are identified. • Perspectives on the development of FNA-based applications are discussed. [ABSTRACT FROM AUTHOR]

Summary: Frequency‐domain detection stands as a critical method in remote geophysical exploration; however, its practical application is constrained by the considerable size of the requisite instrumentation. In this paper, we present a compact frequency domain electromagnetic detection system. The integration of intelligent power devices and a novel hardware architecture substantially diminishes the system's dimensions, thereby enhancing its portability. Furthermore, the system design incorporates sinusoidal pulse width modulation and digital phase‐locked amplification to ensure the efficacy of the proposed system. Both the transmitter and receiver system are constrained to dimensions smaller than 1.5 m. Subsequent experimental validation attests to the exemplary hardware performance of the proposed system, with the transmitting voltage of the transmitter circuit attaining 500 V, and the receiver circuit exhibiting a sensitivity as low as 10−8 V. Significantly, this design paradigm not only facilitates the integration of transmitter and receiver systems for frequency‐domain electromagnetic detection but also introduces novel prospects for the application of frequency‐domain electromagnetic detection methods across diverse fields. [ABSTRACT FROM AUTHOR]

Crowd counting is still a practical and challenging problem owing to scale variations and information loss. Most existing methods based on the straightforward fusion of different features from a deep neural network seem to eliminate this limitation. However, these features are difficult to be fused since they often differ significantly in modality and dimensionality. Unlike previous works, a multi‐level features extraction network with gating mechanism for crowd counting is proposed. Specifically, a multi‐channel gated unit to adaptively extract features in different levels of the network is proposed, which can avoid interference from confusing information. To fully aggregate features via multi‐level fusion, multi‐level features extraction scheme is presented. The multi‐level features extraction network learns to fuse features from multiple levels and reduce false predictions. Extensive experiments and evaluations clearly illustrate that the proposed approach achieves state‐of‐the‐art counting performance against other methods on four mainstream crowd counting benchmarks. [ABSTRACT FROM AUTHOR]

Zero-shot learning (ZSL) methods currently employed to identify seen or unseen classes rely on semantic attribute prototypes or class information. However, hand-annotated attributes are only for the category rather than for each image belonging to that category. Furthermore, attribute information is inconsistent across different images of the same category due to variant views. Therefore, we propose a dynamic visual-guided selection (DVGS) which helps dynamically focus on different regions and refines class prototype on each image. Instead of directly aligning an image's global feature with its semantic class vector or its local features with all attribute vectors, the proposed method learns a vision-guided soft mask to refine the class prototype for each image. Additionally, it discovers the most task-relevant regions for fine-grained recognition with the refined class prototype. Extensive experiments on three benchmarks verify the effectiveness of our DVGS and achieve the new state-of-the-art. Our DVGS achieved the best results on fine-grained datasets within both the conventional zero-shot learning (CZSL) and generalized zero-shot learning (GZSL) settings. In particular, on the SUN dataset, our DVGS demonstrates a significant superiority of 10.2% in the CZSL setting compared with the second-best approach. Similarly, our method outperforms the second-best method by an average of 4% on CUB in both the CZSL and GZSL settings. Despite securing the second-best result on the AWA2 dataset, DVGS remains closely competitive, trailing the best performance by a mere 3.4% in CZSL and 1.2% in GZSL. [ABSTRACT FROM AUTHOR]

[Display omitted] • The accuracy of species distribution models is influenced by physiological tolerance data. • The red-eared slider, as a typical invasive alien species, is widespread in China. • The embryo temperature tolerance range of the red-eared slider was between 21.8 °C and 33.1 °C. • Red-eared slider's high suitability areas mainly in south and central. The suitability areas predicted by the SDMs reduced 20% when considering embryo temperature tolerance data of red-eared slider. • The high suitability areas for red-eared sliders are mainly concentrated in South China, Central China, and East China. Species distribution models (SDMs) have been widely used to predict potentially suitable habitats for invasive alien species (IAS) and evaluate invasion risk. However, SDMs have been discredited because they ignore the physiological processes by which species respond to their environment. Integrating physiological tolerance into the model is essential to improve the prediction accuracy of SDMs. Currently, this approach has not been applied in the study of the worldwide invasive species, the red-eared slider (Trachemys scripta elegans), which is one of the world's 100 worst invasive species and is widespread in China. In this study, based on hatching experiments, we found that the embryo temperature tolerance range of the red-eared slider was between 21.8 °C and 33.1 °C. Further, we studied the effect of embryo temperature tolerance on the prediction of potential invasion areas for this alien reptile species. The high suitability area (530,214.71 km2) predicted by the SDM incorporating embryo temperature tolerance data were 20.9% smaller than that (641,107.60 km2) predicted by the SDM without considering embryo temperature tolerance. The difference between the two SDMs is primarily concentrated at the edges of the high suitability areas. The incorporation of embryo temperature tolerance data influenced the model's predictions by effectively reducing the extent of edges of the high suitability areas. High suitability areas for red-eared sliders are mainly concentrated in South China, Central China, and East China, with a few in North and Southwest China. There is almost no invasion risk in most of the northeast and northwest provinces of China. This study not only has theoretical significance for optimizing model predictions, but also provides an important scientific basis for prevention and risk assessment of invasion by red-eared sliders in China. [ABSTRACT FROM AUTHOR]

Generating the decision map with accurate boundaries is the key to fusing multi-focus images. In this paper, we introduce edge-preservation (EP) techniques into neural networks to improve the quality of decision maps, supported by an interesting phenomenon we found: the maps generated by traditional EP techniques are similar to the feature maps in the trained network with excellent performance. Based on the manifold theory in the field of edge-preservation, we propose a novel edge-aware layer derived from isometric domain transformation and a recursive filter, which effectively eliminates burrs and pseudo-edges in the decision map by highlighting the edge discrepancy between the focused and defocused regions. This edge-aware layer is incorporated to a Siamese-style encoder and a decoder to form a complete segmentation architecture, termed Y-Net, which can contrastively learn and capture the feature differences of the sourced images with a relatively small number of training data (i.e., 10,000 image pairs). In addition, a new strategy based on randomization is devised to generate masks and simulate multi-focus images with natural images, which alleviates the absence of ground-truth and the lack of training sets in multi-focus image fusion (MFIF) task. The experimental results on four publicly available datasets demonstrate that Y-Net with the edge-aware layers is superior to other state-of-the-art fusion networks in terms of qualitative and quantitative comparison. [ABSTRACT FROM AUTHOR]

Zero-shot learning (ZSL) aims to predict unseen classes without using samples of these classes in model training. The ZSL has been widely used in many knowledge-based models and applications to predict various parameters, including categories, subjects, and anomalies, in different domains. Nonetheless, most existing ZSL methods require the pre-defined semantics or attributes of particular data environments. Therefore, these methods are difficult to be applied to general data environments, such as ImageNet and other real-world datasets and applications. Recent research has tried to use open knowledge to enhance the ZSL methods to adapt it to an open data environment. However, the performance of these methods is relatively low, namely the accuracy is normally below 10%, which is due to the inadequate semantics that can be used from open knowledge. Moreover, the latest methods suffer from a significant "semantic gap" problem between the generated features of unseen classes and the real features of seen classes. To this end, this paper proposes a multi-view graph representation with a similarity diffusion model, applying the ZSL tasks to general data environments. This model applies a multi-view graph to enhance the semantics fully and proposes an innovative diffusion method to augment the graph representation. In addition, a feature diffusion method is proposed to augment the multi-view graph representation and bridge the semantic gap to realize zero-shot predicting. The results of numerous experiments in general data environments and on benchmark datasets show that the proposed method can achieve new state-of-the-art results in the field of general zero-shot learning. Furthermore, seven ablation studies analyze the effects of the settings and different modules of the proposed method on its performance in detail and prove the effectiveness of each module. [ABSTRACT FROM AUTHOR]

• A practical solution for sewer control without chemical dosing was developed. • This new approach is based on urine separation, collection and intermittent dosing. • Sulfide and methane production in sewer sediments were simultaneously reduced. • The proposed approach was cost-effective and greenhouse-gas reductive. Sulfide and methane production are a major concern in sewer management. Many solutions with the use of chemicals have been proposed yet incurring huge costs. Here, this study reports an alternative solution to reduce sulfide and methane production in sewer sediments. This is achieved through integration of urine source separation, rapid storage, and intermittent in situ re-dosing into a sewer. Based on a reasonable capacity of urine collection, an intermittent dosing strategy (i.e. 40 min per day) was designed and then experimentally tested using two laboratory sewer sediment reactors. The long-term operation showed that the proposed urine dosing in the experimental reactor effectively reduced sulfidogenic and methanogenic activities by 54% and 83%, compared to those in the control reactor. In-sediment chemical and microbial analyses revealed that the short-term exposure to urine wastewater was effective in suppressing sulfate-reducing bacteria and methanogenic archaea, particularly within a surface active zone of sediments (0–0.5 cm) likely attributed to the biocidal effect of urine free ammonia. Economic and environmental assessments indicated that the proposed urine approach can save 91% in total costs, 80% in energy consumption and 96% in greenhouse gas emissions compared to the conventional use of chemicals (including ferric salt, nitrate, sodium hydroxide, and magnesium hydroxide). These results collectively demonstrated a practical solution without chemical input to improve sewer management. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • The sludge anaerobic fermentation process efficiently reduces Fe3+ to Fe2+. • The acid-elutriation solubilizes Fe and P from the solid phase to the liquid phase. • The acid-elutriation significantly enhances the liquid–solid separation. • High-quality vivianite is harvested via neutralizing sludge eluate. The waste activated sludge (WAS) of wastewater treatment system is often rich in phosphorus (P), which is a basic element of human life and could use up in the near future. This study proposed an integrated approach to efficiently recover P as vivianite from WAS and simultaneously enhance the sludge dewaterability. The raw WAS was first acidified using FeCl 3 , which was then fed to anaerobic fermenter for Fe3+ reduction. After fermentation, a technology named acid-elutriation was introduced to convert Fe and P from solid phase to liquid phase and concomitantly enhance the liquor-solid separation. Finally, vivianite was obtained via sludge eluate neutralization. The enhanced sludge dewaterability not only increases the recovery efficiency of Fe and P but also decreases the cost of sludge disposal. [ABSTRACT FROM AUTHOR]

• Significant loss of total nitrogen is observed in an acidic aerobic sludge digester. • Nitrite is mainly reduced to NO and N 2 O under the acidic aerobic condition. • Rate of aerobic nitrite reduction is comparable to that of aerobic ammonia oxidation. • Controlling the nitrite reduction is critical to development of acidic sludge treatment. The acidic (i.e., pH ∼5) activated sludge process is attracting attention because it enables stable nitrite accumulation and enhances sludge reduction and stabilization, compared to the conventional process at neutral pH. Here, this study examined the production and potential pathways of nitric oxide (NO) and nitrous oxide (N 2 O) during acidic sludge digestion. With continuous operation of a laboratory-scale aerobic digester at high dissolved oxygen concentration (DO>4 mg O 2 L−1) and low pH (4.7±0.6), a significant amount of total nitrogen (TN) loss (i.e., 18.6±1.5% of TN in feed sludge) was detected. Notably, ∼40% of the removed TN was emitted as NO, with ∼8% as N 2 O. A series of batch assays were then designed to explain the observed TN loss under aerobic conditions. All assays were conducted with a low concentration of volatile solids (VS), i.e., VS<4.5 g L−1. This VS concentration is commensurate with the values commonly found in the aeration tanks of full-scale wastewater treatment systems, and thus no significant nitrogen loss should be expected when DO is controlled above 4 mg O 2 L−1. However, nitrite disappeared at a significant rate (with the chemical decomposition of nitrite excluded), leading to NO production in the batch assays at pH 5. The nitrite reduction could be associated with endogenous microbial activities, e.g., nitrite detoxification. The significant NO production illustrates the importance of aerobic nitrite reduction during acidic aerobic sludge digestion, suggesting this process cannot be neglected in developing acidic activated sludge technology. [Display omitted] [ABSTRACT FROM AUTHOR]

[Display omitted] • A new biotechnology was conceived to produce carboxylates and alcohols from WAS. • Highest MCFAs yield from WAS was achieved by the lowest Lactobacillu s inoculation. • High alcohols production was achieved under higher Lactobacillu s inoculation. • A metabolic route for carboxylates and alcohols production was established. Producing medium chain fatty acids (MCFAs) from waste activated sludge (WAS) is crucial for sustainable chemical industries. This study addressed the electron donor requirement for MCFAs production by inoculating Lactobacillus at varying concentrations (7.94 × 1010, 3.18 × 1011, and 6.35 × 1011 cell/L) to supply lactate internally. Interestingly, the highest MCFAs yield (∼2000 mg COD/L) occurred at the lowest Lactobacillus inoculation. Higher inoculation concentrations redirected more carbon from WAS towards alcohols production rather than MCFAs generation, with up to 2852 mg COD/L alcohols obtained under 6.35 × 1011 cell/L inoculation. Clostridium dominance and increased genes abundance for substrate hydrolysis, lactate conversion, and MCFAs/alcohol production collectively enhanced WAS-derived MCFAs and alcohols synthesis after Lactobacillus inoculation. Overall, the strategy of Lactobacillus inoculation regulated fermentation outcomes and subsequent carbon recovery in WAS, presenting a sustainable technology to achieve liquid bio-energy production from underutilized wet wastes. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel three-stage process, comprising PN/A, acidic PN, and anammox, is proposed. • The PN/A unit requires residual ammonium to suppress nitrite-oxidizing bacteria (NOB). • The acidic PN unit provides stable nitrite sources to the anammox unit. • The anammox unit removes the residual ammonium and nitrite from the PN/A and the acidic PN units. • The overall nitrogen removal efficiency is higher than 90% based on model simulation. Sewage treatment with partial nitritation and anammox (PN/A, also termed as deammonification) has gained widespread attentions over the past decade, driven by the need of establishing energy-neutral/positive sewage treatment plants (STPs). However, a key challenge for the mainstream deammonification is to achieve stable suppression of nitrite-oxidizing bacteria (NOB). Deammonification can be configured in either one reactor or two reactors (where PN and anammox are separated), known as one-stage and two-stage configurations, respectively. This study first analyses the current bottlenecks in one-stage and two-stage deammonification. To address these issues, a new, three-stage configuration is proposed. Three-stage deammonification comprises three components, including a PN/A reactor, an acidic PN reactor, and an anammox reactor. The majority of sewage is allocated to the PN/A reactor, which produces an effluent with an elevated level of residual ammonium (2–40 mg N L−1), as required for NOB suppression in this reactor. The residual ammonium is removed in the anammox reactor, using the nitrite supplied from the acidic PN reactor. The acidic PN reactor is fed with a mixture of sewage and anaerobic digestion liquor with a ratio that allows the attainment of a low pH (<6.0) and NOB suppression. This three-stage process was shown applicable to a wide range of municipal wastewaters which have a HCO 3 –/ NH 4 + mole ratio of 1.17–2.41, based on mass balance. Further, simulation indicates that this three-stage process can deliver a stable and high-quality effluent, with the total nitrogen < 10 mg N L−1 and the nitrogen removal efficiency > 90%. [ABSTRACT FROM AUTHOR]

Background: Emerging evidence identifies enhancer RNAs (eRNAs) as a class of regulatory ncRNAs that can contribute to the transcription of target genes. In this study, we used an integrated data analysis method to identify the important role of eRNAs in ovarian cancer (OC). Methods: Gene expression profiles and clinical information from The Cancer Genome Atlas (TCGA) database were used for this study. Based on expression analysis using GEPIA2 gene and Kaplan–Meier survival was performed to ensure the significance of the selected enhancer RNA ADCY10P1 in OC. Next, we explored the correlation and clinical significance between ADCY10P1 and target gene NFYA. Furthermore, we evaluated the effects of overexpression of ADCY10P1 on the proliferation, migration, invasion and epithelial-mesenchymal transformation (EMT) of OC cell lines. We also investigated the biological function enrichment score of ADCY10P1 and verified it with OC cell lines. Finally, external validation was conducted, and the prognostic value of the ADCY10P1 in different tumors was demonstrated. Results: We selected the eRNA ADCY10P1 associated with OC prognosis, with NFYA as its predicted target gene. Low ADCY10P1 expression was found to be associated with poor overall survival, high histological grade, and advanced stage of OC. Additionally, overexpression of ADCY10P1 inhibited the proliferation, migration, invasion and EMT phenotype of OC cell lines. Furthermore, ADCY10P1 was observed to inhibit glycolysis and fatty acid metabolism, thereby affecting OC progression. Meanwhile, OC tissue samples were externally validated. In addition, the pan-cancer analysis revealed that ADCY10P1 had prognostic value in other cancers. Conclusions: This study showed that ADCY10P1 plays a key role in OC progression and may facilitate prognosis prediction. [ABSTRACT FROM AUTHOR]

• Post-treatment improves dewaterability of anaerobically digested (AD) sludge. • Post-treatment further reduces solid concentration and stabilizes AD sludge. • Post-treatment of AD sludge efficiently removes toxic metals. • Current limitations of post-treatment options are identified. • Perspectives on the AD sludge post-treatment technologies are discussed. Anaerobic digestion is the most commonly used sludge treatment technology in large-scale wastewater treatment plants (WWTPs), generating two main products, i.e., biogas and anaerobically digested (AD) sludge. Biogas can be used as a source of renewable energy, and AD sludge is often transported for agricultural land application. Land application of AD sludge is confronted with ever-increasing economic and regulatory pressures due to its high water content, high organic content and related odour and pathogen content (if poorly stabilized), as well as potential toxic metal and organic contaminants. To address these challenges, a number of technologies have been developed for the further treatment of AD sludge before final disposal. This review aims to critically evaluate these state-of-the-art technologies. These technologies were categorized based on their primary aims: 1) dewaterability enhancement; 2) solids reduction and stabilization; 3) toxic metals removal. At present, the goal of post-treatment mainly focuses on dewaterability enhancement, to reduce transport costs. In future, we propose that the post-treatment of AD sludge should orient towards multiple aims, i.e., an integrated approach enabling sludge volume reduction, stabilization (including pathogen removal), and metal solubilization simultaneously. Two promising technical routes are suggested as examples, i.e. physio-chemical iron-based advanced oxidation and biological acidic aerobic digestion, while more approaches need to be developed in future studies. We concluded that post-treatment of AD sludge will promote the AD sludge management towards a more economically favourable, socially acceptable, and environmentally sustainable way; however, further development and rigorous evaluation are required for a wider adoption. [Display omitted] [ABSTRACT FROM AUTHOR]

• Solved the problem that CNN cannot be directly used for medical image fusion. • Using CNN to replace artificially designed fusion rules. • Proposing a new CNN (PHF-CNN) to select high frequency subband coefficients. Although many powerful convolutional neural networks (CNN) have been applied to various image processing fields, due to the lack of datasets for network training and the significant different intensities of diverse multi-modal source images at the same location, CNN cannot be directly used for the field of medical image fusion (MIF), which is a major problem and limits the development of this field. In this article, a novel multimodal medical image fusion method based on non-subsampled contourlet transform (NSCT) and CNN is presented. The proposed algorithm not only solves this problem, but also exploits the advantages of both NSCT and CNN to obtain better fusion results. In the proposed algorithm, source multi-modality images are decomposed into low and high frequency subbands. For high frequency subbands, a new perceptual high frequency CNN (PHF-CNN), which is trained in the frequency domain, is designed as an adaptive fusion rule. In the matter of the low frequency subband, two result maps are adopted to generate the decision map. Finally, fused frequency subbands are integrated by the inverse NSCT. To verify the effectiveness of the proposed algorithm, ten state-of-the-art MIF algorithms are selected as comparative algorithms. Subjective evaluations by five doctors as well as objective evaluations by seven image quality metrics, demonstrate that the proposed algorithm is superior to the other comparative algorithms in terms of fusing multimodal medical images. [ABSTRACT FROM AUTHOR]

Background: Ovarian cancer is a common cancer type in women and is often associated with onset of malnutrition. Total parenteral nutrition (TPN) is a nutritional intervention method that has been reported to have controversial effect on cancer patients. In the present retrospective study, we sought to explore the prevalence of malnutrition assessed by the Nutritional Risk Index (NRI) and its association with survival in advanced stage ovarian cancer patients. We also compared the post-operative outcome of the malnourished patients treated with either TPN or conservative management.Results: A total of 415 patients with advanced stage ovarian cancer were separated into 4 nutrition groups based on the NRI scores. We found that a number of factors were significantly different among the 4 nutrition groups, including age, serum albumin level, BMI and NRI; among which serum albumin level and NRI were identified to be independent predictors of progression-free and overall survival. In the moderately and severely malnourished patients, those who were treated with TPN had significantly shorter hospitalization period, lower serum albumin level and lower BMI after surgery. In addition, serum albumin level, use of TPN and number of patients with complications were closely related to the hospital stay duration.Conclusion: Malnutrition status is closely associated with survival of advanced stage ovarian cancer patients. These patients may benefit from TPN treatment for reduced hospitalization, especially with the onset of hypoalbuminemia. [ABSTRACT FROM AUTHOR]

This review provides a comprehensive overview of the occurrence, fate, treatment and multi-criteria analysis of microplastics (MPs) and organic contaminants (OCs) in biosolids. A meta-analysis was complementarily analysed through the literature to map out the occurrence and fate of MPs and 10 different groups of OCs. The data demonstrate that MPs (54.7% occurrence rate) and linear alkylbenzene sulfonate surfactants (44.2% occurrence rate) account for the highest prevalence of contaminants in biosolids. In turn, dioxin, polychlorinated biphenyls (PCBs) and phosphorus flame retardants (PFRs) have the lowest rates (<0.01%). The occurrence of several OCs (e.g., dioxin, per- and polyfluoroalkyl substances, polycyclic aromatic hydrocarbons, pharmaceutical and personal care products, ultraviolet filters, phosphate flame retardants) in Europe appear at higher rates than in Asia and the Americas. However, MP concentrations in biosolids from Australia are reported to be 10 times higher than in America and Europe, which required more measurement data for in-depth analysis. Amongst the OC groups, brominated flame retardants exhibited exceptional sorption to biosolids with partitioning coefficients (log K d) higher than 4. To remove these contaminants from biosolids, a wide range of technologies have been developed. Our multicriteria analysis shows that anaerobic digestion is the most mature and practical. Thermal treatment is a viable option; however, it still requires additional improvements in infrastructure, legislation, and public acceptance. [Display omitted] • LAS (44.2%) and microplastic (54.7%) account for the highest prevalence in biosolids. • Occurrence of several OCs in Europe is higher than in Asia and America. • Australia has microplastic in biosolids 10 times higher than other continents. • Anaerobic digestion is the most mature and practical for OCs treatment in biosolids. • Thermal treatment is a viable option but still requires additional improvements. [ABSTRACT FROM AUTHOR]

• An acidic aerobic digestion system treating anaerobically-digested sludge was established. • The acidic condition (4.8 ± 0.2) was self-sustained by Ca. Nitrosoglobus. • The total solids of anaerobically-digested sludge was markedly reduced by 22.6 ± 5.5%. • The stabilization level of anaerobically-digested sludge was improved to class A. Anaerobic digestion is a commonly used process for the reduction and stabilization of wasted activated sludge generated in wastewater treatment plants. However, anaerobically-digested (AD) sludge is still a problematic waste stream due to its large volume and often poor quality. In this study, two aerobic digesters were set up to treat anaerobically-digested sludge, with one digester operated in self-generated acidic condition as the experimental reactor, and one at neutral pH as the control reactor. The acidic condition in the experimental reactor was driven by an inoculated special ammonia-oxidizing bacterium, ' Candidatus Nitrosoglobus', which can tolerate low pH. As a result of ammonium oxidation by Ca. Nitrosoglobus, the pH decreased to 4.8 ± 0.2 and nitrite accumulated to and stayed at 200.0 ± 17.2 mg N L−1, from which free nitrous acid (FNA) at 8.5 ± 1.8 mg HNO 2 N L−1 formed in-situ. As a combined effect of low pH and high concentration of FNA, the experimental reactor reduced the total solids (TS), volatile solids (VS) and non-volatile solids (NVS) in the AD sludge by 25.2 ± 7.0%, 29.8 ± 4.3%, and 22.6 ± 5.5%, respectively. In contrast, the control reactor without Ca. Nitrosoglobus inoculation (operated at a near-neutral pH of 6.8 ± 0.3 and no FNA formation) only reduced VS in the AD sludge by 10.4 ± 4.3%, along with negligible NVS reduction. Additionally, the acidic aerobic digestion in the experimental reactor significantly stabilized AD sludge, decreasing the specific oxygen uptake rate (SOUR) to 0.5 ± 0.1 mg O 2 g−1VS h−1 and the most probable number (MPN) of Faecal Coliforms to 2.4 ± 0.1 log(MPN g−1TS), both of which meet USEPA standards for Class A biosolids. In comparison, the control reactor produced biosolids at Class B level only, with an SOUR of 1.8 ± 0.2 mg O 2 g−1VS h−1 and a Faecal Coliforms MPN of 3.6 ± 0.1 log(MPN g−1TS). By reducing the volume and improving the quality of the AD sludge, the acidic aerobic digestion of AD sludge enabled by Ca. Nitrosoglobus has the potential to significantly save the sludge disposal costs in wastewater treatment. [Display omitted] [ABSTRACT FROM AUTHOR]