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With the increasing of the installed capacity of wind power, the condition monitoring and maintains technique is becoming more important. Wind Turbines (WT) gearbox is one of the key wind power components as it plays the role of power transmission and speed regulation. Towards this, a number of scholars have pay attention to the fault diagnosis of WT gearbox. The efficiency of Machine Learning (ML) algorithms is highly correlated with signal type, data quality, and extracted features employed. The implementation of ML techniques has proven to be advantageous in simplifying the comprehension prerequisites for fault diagnosis technology concerning fault mechanisms. More and more current studies predominantly concentrate on the utilization and fine-tuning of ML algorithms, while providing limited insights into the features of the acquired data. Therefore, it is necessary to review the research in recent years from the perspective of the combination of feature extraction and ML algorithms, and provide a detailed direction for future WT gearbox fault diagnosis technology research. In this paper, data processing algorithms and typical fault diagnosis methods based on ML methods for WT gearbox are reviewed. For the using of ML method in WT gearbox fault diagnosis, the data prepared for training is very important. The paper firstly reviewed the data analysing method which will support the ML method. The data analysing methods include data acquisition, data preprocessing and feature extraction method. Feature extraction plays a pivotal role in the realm of gearbox fault diagnosis, as it serves as the essence of effective detection. This review will primarily focus on exploring methods that enable the utilization of efficient features in combination with ML techniques to achieve accurate gearbox fault diagnosis. Then typical ML method for WT gearbox fault diagnosis are carefully reviewed. Moreover, some prospects for future research directions are discussed in the end.

Abstract Background The use of the apparent transverse relaxation rate (R2*) in nasopharyngeal carcinoma (NPC) has not been previously reported in the literature. The aim of this study was to investigate the role of the R2* value in evaluating response to concurrent chemoradiotherapy (CCRT) in patients with NPC. Methods Forty-one patients with locoregionally advanced NPC confirmed by pathology were examined by blood oxygenation level-dependent (BOLD) magnetic resonance imaging (MRI) before and after CCRT, and conventional MRI was performed 3 months after the completion of CCRT. All patients were divided into a responding group (RG) and a nonresponding group (NRG), according to MRI findings 3 months after the end of treatment. The R2* values before (R2*preT) and after (R2* postT) CCRT and the ΔR2* (ΔR2*=R2* postT – R2* preT) were calculated in the tumor. Results Among the 41 patients, 26 were in the RG and 15 were in the NRG. There was no statistical difference in the R2* preT between RG and NRG (P = 0.307); however, there were significant differences in R2* postT and ΔR2* (P

Variable air volume (VAV) air-conditioning (AC) systems are widely employed to achieve a comfortable room thermal and humid environment depending on its better regulation performance and energy efficiency. In the single coil VAV AC system, conventional proportional-integral (PI) control algorithm is usually adopted to track the set-points of the room temperature and humidity by regulating the supply air flow rate and the chilled water flow rate, respectively. However, the control performance is usually not good due to the high coupling of the heat and mass transfer in the air-handling unit (AHU). A model-based control method is developed to realize the decoupling control of the room temperature and humidity according to the bilinear characteristics of the temperature and humidity variation. In this control method, a bilinear room temperature controller is used to track the room temperature set-point based on the real-time cooling load, while a room humidity controller is used to track the room humidity set-point depending on the real-time humidity load. The control performance was validated in a simulated VAV AC system. The test results show that comparing with the conventional PI control, the room temperature and humidity are controlled much more robustly and accurately by using the proposed model-based control method.

Air-permeable building envelopes (APBEs) utilize the infiltrated or exfiltrated airflow within porous materials to directly change their temperature distribution to reduce heat loss/gain. APBEs effectively integrate building ventilation and heat recovery to achieve excellent thermal insulation while improving indoor air quality. This paper presents a comprehensive review of the fundamentals and classifications, historical evolution over time, opportunities and benefits, and future views on APBEs. It can be treated as a responsive building envelope that enables building envelopes to dynamically change the U-values by varying the infiltrated or exfiltrated airflow rate within a porous material. Previous studies have indicated that the U-value of 0.1 W/(m2·K) can be realized by employing APBEs. Moreover, some research demonstrates that APBEs could act as high-performance air filters that reduce over 90% of particulate matter within fresh, ventilated air. Some factors, such as airflow rate, thickness, and thermal conductivity of porous materials, have a significant influence on the effectiveness of APBEs. For practical applications, integrating the APBE with passive building ventilation can help reduce the initial cost and facilitate decarbonization in buildings. Moreover, advanced control strategies could collaboratively optimize the operation of ABPEs and build energy systems to maximize their energy-saving potential.

Highlights Design and fabrication of MXene-based soft actuators with angle-independent structural color. The nanostructured MXene can not only facilitate the formation of short-range ordered 3D amorphous photonic crystals, but also help significantly improve structural color saturation. The soft actuators exhibit brilliant angle-independent structural color, ultrafast actuation and recovery speeds in response to vapor.

The task of Point-of-Interest (POI) recommendation is to recommend the next interest locations for users. Gated Graph Neural Network (GGNN) has been proved to be effective on POI recommendation tasks. However, existing GGNN solutions rarely consider the spatiotemporal information between nodes in the sequence graph, which is essential for modeling user check-in behaviors in next POI recommendation. In this paper, we propose an attention-based spatiotemporal gated graph neural network model (ATST-GGNN) for next POI recommendation. Firstly, the user’s check-in sequence is represented as a graph structure. Secondly, we use spatiotemporal context information to dynamically update nodes in the sequence graph, and obtain the complex transfer relationships between the check-ins. Thirdly, each session is then represented as the composition of the long and short preference using an attention network. However, current short preference fails to model union-level sequential patterns, we improve the local embedding representation of graph nodes by window pooling method, as well as the global embedding representation of graph nodes by integrating it into attention mechanism. Finally, the objective function is constructed by cross entropy and the model parameters are learned. The experimental results show that the precision rate and mean reciprocal ranking of ATST-GGNN method are greatly improved compared with the state-of-art methods. It has good application prospect.

Recent study shows that recommendation system not only relys on user’s static preference, but also dynamic preference. Consequently, it leads to the emergence of session-based recommendation. With the development of recurrent neural network, this kind of method can capture representations of users’ sequential behaviors from a large number of sessions. However it is prone to spurious dependency problem. Recently, convolutional neural network has also shown its potential in modelling session, especially in extracting complex local pattern of subsequence. Therefore, we propose a hybrid neural model, called SGPD, for learning sequential general pattern and dependency for session-based recommendation. In SGPD, we propose recurrent residual convolution network to extract general pattern of subsequence in a session. Furthermore, the SGPD scans sequence from forward and reverse direction by bidirectional recurrent neural network, and learns sequential dependency of a session. Finally, the objective function is constructed by cross entropy and the model parameters are learned. The experimental results show that the precision rate, recall rate and mean reciprocal ranking of SGPD are greatly improved compared with the state-of-art methods. It has good application prospect.

The number of people living with Alzheimer's disease (AD) is increasing alongside with aging of the population. Systemic chronic inflammation and microbial imbalance may play an important role in the pathogenesis of AD. Inflammatory diets regulate both the host microbiomes and inflammatory status. This study aimed to explore the impact of inflammatory diets on oral-gut microbes in patients with AD and the relationship between microbes and markers of systemic inflammation. The dietary inflammatory properties and the oral and gut microorganisms were analyzed using the dietary inflammatory index (DII) and 16S RNA in 60 patients with AD. The α-diversity was not related to the DII (p > 0.05), whereas the β-diversity was different in the oral microbiomes (R2 = 0.061, p = 0.013). In the most anti-inflammatory diet group, Prevotella and Olsenella were more abundant in oral microbiomes and Alistipes, Ruminococcus, Odoribacter, and unclassified Firmicutes were in the gut microbiomes (p < 0.05). Specific oral and gut genera were associated with interleukin-6 (IL)-6, complement 3 (C3), high-sensitivity C-reactive protein (hs-CRP), IL-1β, IL-4, IL-10, IL-12, and tumor necrosis factor-α (TNF-α) (p < 0.05). In conclusion, anti-inflammatory diets seem to be associated with increased abundance of beneficial microbes, and specific oral and gut microbial composition was associated with inflammatory markers.

ObjectiveAlterations in the oral or gut microbiotas have been reported in patients with subjective and mild cognitive impairment or AD dementia. However, whether these microbiotas change with the severity of the AD spectrum (mild, moderate, and severe AD) remains unknown. Thus, we compared alterations in the composition and gene functions of the oral and gut microbiota between different phases of AD.MethodsWe recruited 172 individuals and classified these into three groups: healthy controls (n = 40), a mild AD group (n = 43) and a moderate AD group (n = 89). Subgingival plaques and fecal samples were collected from all individuals. Then, we conducted 16S ribosomal RNA. sequencing to analyze the microbiotas.ResultsIn order of the severity of cognition impairment (from normal to mild and to moderate AD), the oral abundances of the phyla Firmicutes and Fusobacteria showed a gradual upwards trend, while the abundance of the Proteobacteria phylum gradually decreased. In contrast, the abundance of the Firmicutes and Bacteroidetes phyla in the gut decreased progressively, while that of the Proteobacteria, Verrucomicrobia and Actinobacteria phyla increased gradually. Key differences were identified in the microbiomes when compared between the mild AD and moderate AD groups when applying the linear discriminant analysis effect size (LEfSe) algorithm. LEfSe analysis revealed alterations that were similar to those described above; furthermore, different bacterial taxa were associated with MMSE scores and age. KEGG analysis showed that the functional pathways associated with the oral microbiota were mainly involved in membrane transport and carbohydrate metabolism, while the gene functions of the fecal microbiota related to metabolism of amino acids, energy, cofactors and vitamins; identified significant differences among the three groups. Venn diagram analysis revealed that the number of genera that were present in both the oral and gut microbiota increased progressively from NC to mild AD and then to moderate AD.ConclusionsThis study is the first to report a comparative analysis of the oral and fecal microbiota of patients with mild and moderate AD. The compositions and functions of the oral and gut microbiotas differed when compared between different stages of AD.

ObjectiveTo evaluate the efficacy and safety of sintilimab combined with apatinib plus capecitabine in the treatment of unresectable hepatocellular carcinoma (HCC) to provide a more effective first-line treatment for patients with advanced HCC.MethodsThis open-label, prospective, phase II study included patients with unresectable HCC who did not receive systematic treatment. The patients were treated with sintilimab (200 mg, intravenous drip, once every 3 weeks) combined with apatinib (250 mg, oral administration, once a day) plus capecitabine (1000 mg/m2, twice a day; after 2 weeks of oral administration, the drug was stopped for 1 week; course of treatment, 3 weeks). The primary endpoint was the objective response rate (ORR). The secondary endpoints included disease control rate (DCR), progression-free survival (PFS), duration of response (DoR), overall survival (OS), and safety.ResultsForty-seven patients (1 lost to follow-up) were enrolled in the study. As of March 1, 2022, the ORR and DCR were 50.0% (95% CI: 34.9–65.1%) and 91.3% (95% CI: 79.2–97.6%), respectively, after blind, independent imaging evaluation. The median follow-up time was 18.7 months (95% CI: 17.2–20.2 months). The median PFS was 9.0 months (95% CI: 7.1–10.9 months). The median DoR was 10.8 months (95% CI: 4.8–16.8 months). The median OS was not reached, and the 1-year OS rate was 71.7% (95% CI: 56.5–84.0%). Only 28.3% (13/46) of patients had grade 3/4 treatment-related adverse events.ConclusionSintilimab combined with apatinib plus capecitabine has good safety and anti-tumor activity as a first-line treatment for unresectable HCC. This is worthy of further multi-center, prospective, randomized, large-sample clinical studies.Clinical Trial Registrationhttps://ClinicalTrials.gov, identifier NCT04411706.

The first example of paired electrolysis-enabled cyanation of diaryl diselenides, with KSCN as the green cyanating agent, has been developed. A broad range of aryl selenocyanates can be efficiently synthesized under chemical-oxidant- and additive-free, energy-saving and mild conditions.

Detailed monitoring of loads can provide sufficient information about buildings and help in improving the operation of energy systems. Non-intrusive load monitoring (NILM) has become popular owing to its low cost and lack of disturbance in the occupied space. In this study, NILM methods based on artificial neural network (ANN) and random forest (RF) are proposed and compared to obtain the sub-loads of cooling loads. The cooling loads are disaggregated into four sub-loads: occupant load, equipment load, fresh air load, and building envelope load. Results showed both NILM methods could achieve load disaggregation accurately, but the RF-based NILM method performs better than that based on ANN. Moreover, the RF-based NILM method has mean relative errors (MREs) between 2.5% and 13.0%, while the ANN-based NILM method has MREs between 3.1% and 12.9%. Among the four sub-loads, the equipment load could be disaggregated with the highest accuracy. The detailed sub-loads obtained using the proposed NILM methods can guide building renovation and optimization design of building energy systems.

Introduction Alzheimer’s disease (AD) is the most common neurodegenerative disease and is characterised by cognitive impairment. Non-pharmacological treatments such as diet therapy have been widely investigated in studies on AD. Given the synergistic effects of nutrients present in foods, considering overall dietary composition rather than focusing on a single nutrient may be more useful for evaluating the relationship between diet and AD cognition. The present study aimed to assess the efficacy of different dietary interventions (eg, ketogenic and Mediterranean diets) on cognitive function in patients with AD in a systematic review and pairwise and network meta-analyses of randomised controlled trials or clinical trials.Methods and analysis Two reviewers will independently conduct searches of PubMed, Cochrane Central Register of Controlled Trials, Embase, CINAHL, PsycINFO and China National Knowledge Infrastructure databases. Data will be extracted from selected studies and risk of bias will be assessed using the revised Cochrane risk-of-bias tool, and evidence quality will be assessed according to the Grading of Recommendations, Assessment, Development and Evaluation framework. The primary outcome of interest is cognitive function in patients with AD; secondary outcomes include biochemical biomarkers of AD and oxidative stress and/or inflammatory biomarkers in cerebrospinal fluid or plasma. For each outcome, random-effects pairwise and network meta-analyses will be carried out to determine the pooled relative effect of each intervention relative to every other intervention.Ethics and dissemination As this study is based solely on published literature, no ethics approval is required. The research will be published in a peer-reviewed journal.

Abstract Uniform dispersion of two-dimensional (2D) graphene materials in polymer matrices remains challenging. In this work, a novel layer-by-layer assembly strategy was developed to prepare a sophisticated nanostructure with highly dispersed 2D graphene oxide in a three-dimensional matrix consisting of one-dimensional bacterial cellulose (BC) nanofibers. This method is a breakthrough, with respect to the conventional static culture method for BC that involves multiple in situ layer-by-layer assembly steps at the interface between previously grown BC and the culture medium. In the as-prepared BC/GO nanocomposites, the GO nanosheets are mechanically bundled and chemically bonded with BC nanofibers via hydrogen bonding, forming an intriguing nanostructure. The sophisticated nanostructure of the BC/GO leads to greatly enhanced mechanical properties compared to those of bare BC. This strategy is versatile, facile, scalable, and can be promising for the development of high-performance BC-based nanocomposite hydrogels.

Most reported wearable electronic devices lack self-healing chemistry and flexible function to maintain stable energy output while irreversible damages and complex deformations. In this work, we report a dual-dynamic network electrolyte synthesized by micellar elastomers introduced into strong hydrogel matrix. The gel electrolyte is fabricated by physically cross-linking the borax-polyvinyl alcohol (B-PVA) network as tough matrix and poly (ethylene oxide) (PEO)-poly (propylene oxide) (PPO)-poly (ethylene oxide) (Pluronic) to frame elastic network, followed by immersion in potassium chloride solution. Under the action of dynamic borate ester bond and multi-network hydrogen bond, the as-prepared electrolyte exhibits high stretchability (1535%) and good self-healing efficiency. Based on the electrolyte, we assemble the interfacial compatible micro-supercapacitor (MSC) by multi-walled carbon nanotubes (MWCNT) interdigital electrode printed on cellulosic paper by direct ink writing (DIW) technique. Thanks to the large specific area and compressive deformation resistance of cellulosic paper, the MSC with tightly interfacial contact achieves high volumetric capacitance of 801.9 mF cm−3 at the current density of 20 μA cm−2. In the absence of stimulation of the external environment, the self-healing MSC demonstrates an ideal capacity retention (90.43%) after five physical damaged/healing cycles. Our research provides a clean and effective strategy to construct wearable MSC.

Abstract The observed strong sorption of hydrophobic organic contaminants (HOCs) to biochar presents potential implications for HOCs bioavailability and bioaccessibility in sediments, while biochar could impact sediment microbial ecology. However, the comprehensive study on the effects of biochar on HOC biodegradation coupled with bioavailability and microbial ecology are rarely documented. In this paper, the effects of biochar on the biodegradation of nonylphenol (NP) were investigated using 3 different NP concentrations (20, 50 and 500 mg/Kg) in sediments amended with different percentage of rice straw biochar (RC). Results showed that the influence of RC on NP biodegradation varied with different NP concentrations. At low NP concentrations, RC suppressed NP biodegradation by reducing NP bioavailability, while at high NP concentrations, moderate RC addition promoted biodegradation by reducing toxicity of NP to microbes. The effects of NP on microbial community structures were significant (P 0.05). The RC affected microorganisms through altering NP toxicity, microbial quantity and activity, but not microbial community structures. This study indicated that there could be an optimal biochar percentage in biochar-sediment systems at different HOC concentrations, which strengthened HOC biodegradation process and accelerated biodegradation rate, forming adsorption-biodegradation coupled bioremediation.

Flavonoids are natural polyphenolic compounds produced by many aquatic plants and released in their environments. In this study, the effects of several aquatic flavonoids on cyanobacterial Microcystis aeruginosa, especially in relation to the cell growth, photosynthetic activity, cell morphology, and cell membrane integrity, were investigated. Significant growth inhibition was observed when the cyanobacteria were exposed to three flavonoids, namely, 5,4'-dihydroxyflavone (DHF), apigenin, and luteolin. Luteolin reduced the effective quantum yield, photosynthetic efficiency, and maximal electron transport rate by 70%, 59% and 44%, respectively, whereas 5,4'-DHF and apigenin slightly affected these parameters, which implies that luteolin disrupts the photosynthetic system. Moreover, 5,4'-DHF and apigenin compromised the membrane integrity, and induced membrane depolarization in 52% and 38%, and permeabilization in 30% and 44% of the cells, respectively. The 5,4'-DHF and apigenin showed more pronounced effects on M. aeruginosa morphology and membrane integrity, compared to the luteolin. These results suggest that flavonoids could have significant effects on growth and physiological functions in cyanobacterial species.

Hybrid ground-source heat pump system has been widely used for mitigating the heat accumulation problem of conventional ground-source heat pump systems. This article proposes a wet-bulb temperature-based control method for a hybrid ground-source heat pump system which comprises a ground-source heat pump and a conventional water-cooled chiller using a cooling tower. With this method, the operation priority between the ground-source heat pump and the water-cooled chiller is determined according to the outdoor wet-bulb temperature. A TRNSYS platform of the system is developed, and simulations are carried out to investigate the system performance under the proposed control method. Meanwhile, simulations with two other control methods (reference methods), that is, the ground-source heat pump–prioritized method and water-cooled chiller–prioritized method, are also conducted. The study results show that the proposed control method has obvious advantage in controlling the heat balance of the ground-source heat exchangers, and in the meantime, no more energy is consumed when compared with the two reference control methods.

Due to the significant impact of indoor humidity on indoor air quality, human comfort, and energy consumption, many researchers have investigated the use of various hygroscopic materials to moderate indoor humidity levels and save energy. The results show that the indoor relative humidity of the room with hygroscopic materials is more stable and moderate. Hygroscopic materials can be also used to reduce the energy consumption of heating, ventilation, and air-conditioning system. Although many laboratory measurements and numerical simulation studies have been done for hygroscopic materials, there is little study on moisture penetration in materials with limited thickness in practical engineering application. Moisture penetration depth has great influence on material moisture parameters and indoor humidity simulation model, such as effective moisture penetration depth model. In this article, a theoretical moisture penetration depth model is developed, and the theoretical moisture penetration depths of conventional building materials are calculated. The results show that when the wall material thickness is below the 1/e theoretical moisture penetration depth, the proportional relationship between the moisture buffer value and the square root of time is not kept. When the wall material thickness is thinner than its theoretical moisture penetration depth, ignoring the material thickness might cause significant error in indoor moisture content calculation using effective moisture penetration depth model.

The adsorptive removal of As(V) from aqueous solutions using iron-coated honeycomb briquette cinder (Fe-HBC) is presented. Low cost mechanical granulation process was integrated with surface amendment technology to prepare iron-oxide modified granular adsorbent for clean water production. Detailed characterizations were performed using FTIR, XRD, EDS and SEM techniques. Operating parameters including initial As(V) concentration, pH, contact time, adsorbent dose, iron leaching and the effects of competing ions on As(V) removal were evaluated. Results demonstrated that high amount of arsenate (961.5 μg g−1) was adsorbed at pH 7.5 in 14 h contact time. Langmuir, Freundlich and Temkin isotherm models were used to analyze the adsorption data, whereas Langmuir model was found to best represent the data with a correlation co-efficient (R2 = 0.999). Thus, As(V) sorption on Fe-HBC surface suggested monolayer adsorption and indicated surface homogeneity. Moreover, the dimensionless parameter (RL) value calculated to be about 0.118 that reiterated the process is favorable and spontaneous. The influences of competing ions on As(V) removal decreased in the following order:PO43−>HCO3−>F−>Cl−. The profound inhibition effects ofPO43− revealed a high affinity toward iron(oxy) hydroxide. Life-cycle assessment confirmed that spent HBC is non-hazardous and can be used as a promising sorbent for arsenic removal.

Soil biogeochemical processes and the ecological stability of wetland ecosystems under global warming scenarios have gained increasing attention worldwide. Changes in the capacity of microorganisms to maintain stoichiometric homeostasis, or relatively stable internal concentrations of elements, may serve as an indicator of alterations to soil biogeochemical processes and their associated ecological feedbacks. In this study, an outdoor computerized microcosm was set up to simulate a warmed (+5°C) climate scenario, using novel, minute-scale temperature manipulation technology. The principle of stoichiometric homeostasis was adopted to illustrate phosphorus (P) biogeochemical cycling coupled with carbon (C) dynamics within the soil-microorganism complex. We hypothesized that enhancing the flux of P from soil to water under warming scenarios is tightly coupled with a decrease in homeostatic regulation ability in wetland ecosystems. Results indicate that experimental warming impaired the ability of stoichiometric homeostasis (H) to regulate biogeochemical processes, enhancing the ecological role of wetland soil as an ecological source for both P and C. The potential P flux from soil to water ranged from 0.11 to 34.51 mg m(-2) d(-1) in the control and 0.07 to 61.26 mg m(-2) d(-1) in the warmed treatment. The synergistic function of C-P acquisition is an important mechanism underlying C∶P stoichiometric balance for soil microorganisms under warming. For both treatment groups, strongly significant (p

The presence of elevated concentration of arsenic in water sources is considered to be health hazard globally. Calcination process is known to change the surface efficacy of the adsorbent. In current study, five adsorbent composites: uncalcined and calcined Fe3O4-HBC prepared at different temperatures (400°C and 1000°C) and environment (air and nitrogen) were investigated for the adsorptive removal of As(V) and As(III) from aqueous solutions determining the influence of solution's pH, contact time, temperature, arsenic concentration and phosphate anions. Characterizations from FTIR, XRD, HT-XRD, BET and SEM analyses revealed that the Fe3O4-HBC composite at higher calcination temperature under nitrogen formed a new product (fayalite, Fe2SiO4) via phase transformation. In aqueous medium, ligand exchange between arsenic and the effective sorbent site ( = FeOOH) was established from the release of hydroxyl group. Langmuir model suggested data of the five adsorbent composites follow the order: Fe3O4-HBC-1000°C(N2)>Fe3O4-HBC (uncalcined)>Fe3O4-HBC-400°C(N2)>Fe3O4-HBC-400°C(air)>Fe3O4-HBC-1000°C(air) and the maximum As(V) and As(III) adsorption capacities were found to be about 3.35 mg g(-1) and 3.07 mg g(-1), respectively. The adsorption of As(V) and As(III) remained stable in a wider pH range (4-10) using Fe3O4-HBC-1000°C(N2). Additionally, adsorption data fitted well in pseudo-second-order (R2>0.99) rather than pseudo-first-order kinetics model. The adsorption of As(V) and As(III) onto adsorbent composites increase with increase in temperatures indicating that it is an endothermic process. Phosphate concentration (0.0l mM or higher) strongly inhibited As(V) and As(III) removal through the mechanism of competitive adsorption. This study suggests that the selective calcination process could be useful to improve the adsorbent efficiency for enhanced arsenic removal from contaminated water.

Nonradicals are effective in selectively degrading electron-rich organic contaminants, which unfortunately suffer from unsatisfactory yield and uncontrollable composition due to the competitive generation of radicals. Herein, we precisely construct a local microenvironment of the carbon nitride--supported high-loading (~9 wt.%) Fe single-atom catalyst (Fe SAC) with sulfur via a facile supermolecular self-assembly strategy. Short-distance S coordination boosts the peroxymonosulfate (PMS) activation and selectively generates high-valent iron--oxo species (FeIV =O) along with singlet oxygen (¹O2), significantly increasing the ¹O2 yield, PMS utilization, and p-chlorophenol reactivity by 6.0, 3.0, and 8.4 times, respectively. The composition of nonradicals is controllable by simply changing the S content. In contrast, long-distance S coordination generates both radicals and nonradicals, and could not promote reactivity. Experimental and theoretical analyses suggest that the short-distance S upshifts the d-band center of the Fe atom, i.e., being close to the Fermi level, which changes the binding mode between the Fe atom and O site of PMS to selectively generate ¹O2 and FeIV =O with a high yield. The short-distance S-coordinated Fe SAC exhibits excellent application potential in various water matrices. These findings can guide the rational design of robust SACs toward a selective and controllable generation of nonradicals with high yield and PMS utilization. [ABSTRACT FROM AUTHOR]