Ligand-to-Metal Charge Transfer (LMCT) Catalysis: Harnessing Simple Cerium Catalysts for Selective Functionalization of Inert C-H and C-C Bonds.

ConspectusChemists have long pursued harnessing light energy and photoexcitation processes for synthetic transformations. Ligand-to-metal charge transfer (LMCT) in high-valent metal complexes often triggers bond homolysis, generating oxidized ligand-centered radicals and reduced metal centers. While photoinduced oxidative activations can be enabled, this process, typically seen as photochemical decomposition, remains underexplored in catalytic applications. To mitigate decomposition during LMCT excitation, we developed a catalytic cycle integrating in situ coordination, LMCT, and ligand homolysis to activate ligated alcohols transiently into alkoxy radicals. This catalytic approach leverages Ce(IV) LMCT excitation and highly reactive alkoxy radical intermediates for selective functionalizations of C(sp3)-H and C(sp3)-C(sp3) bonds under mild conditions. In this Account, we discuss these advancements, highlighting the practical utility of cost-effective cerium salts as catalysts and their potential to develop innovative transformations, addressing long-standing synthetic challenges.Selective functionalization of chemically inert C(sp3)-H bonds has long posed a significant challenge. We first detail our research using LMCT-enabled alkoxy radical-mediated hydrogen atom transfer (HAT) processes for selective C(sp3)-H functionalizations. Using readily available CeCl3, we established a general protocol for employing free alcohols in the Barton reaction. By integrating LMCT and HAT catalysis, we introduced a selective photocatalytic strategy for functionalizing feedstock alkanes, converting gaseous hydrocarbons into valuable products. Employing simple cerium salts like Ce(OTf)3 and CeCl3, we achieved selective C-H amination of methane and ethane at ambient temperature, achieving turnover numbers of 2900 and 9700, respectively. This catalytic manifold has been further exploited to address the site-selectivity challenge in the C-H functionalization of linear alkanes. The use of methanol as a cocatalyst enabled preferential functionalization of the most electron-rich sites, achieving a high intrinsic selectivity over 12:1 of secondary vs primary sites in pentane and hexane.Next, we discuss the catalytic utilization of alkoxy-radical-mediated ß-scission, a frequently encountered side reaction in HAT transformations, for selective cleavage and functionalization of C-C bonds. The versatility of the LMCT catalytic platform facilitates the generation of alkoxy radicals from various free alcohols. In our initial demonstration of LMCT-enabled C(sp3)-C(sp3) bond activation, we developed a cerium-catalyzed ring-opening and amination of cycloalkanols, providing an effective protocol for cleaving unstrained C-C bonds. This strategy has been successfully applied to various radical cross-coupling processes, leading to innovative transformations such as ring expansions of cycloalkanols, dehydroxymethylative alkylation, amination, alkenylation, and ring expansions of cyclic ketones. These results highlight the synthetic potential of employing LMCT-mediated ß-scission and ubiquitous C-C bonds as unconventional functional handles for generating molecular complexity.Lastly, we delve into our mechanistic investigations. Beyond the catalytic application of Ce(IV) LMCT in various transformations, we have undertaken comprehensive mechanistic studies. These investigations encompass characterization of Ce(IV) alkoxide complexes to elucidate their structures, evaluation of their photoactivity and selectivity in radical generation, and elucidation of kinetic pathways associated with transient LMCT excited states. Our research has revealed ultrafast bond homolysis, back electron transfer, and the selectivity of heteroleptic complexes in homolysis, providing crucial insights for advancing LMCT catalysis.

Alkoxy Radicals See the Light: New Paradigms of Photochemical Synthesis.

Alkoxy radicals are highly reactive species that have long been recognized as versatile intermediates in organic synthesis. However, their development has long been impeded due to a lack of convenient methods for their generation. Thanks to advances in photoredox catalysis, enabling facile access to alkoxy radicals from bench-stable precursors and free alcohols under mild conditions, research interest in this field has been renewed. This review comprehensively summarizes the recent progress in alkoxy radical-mediated transformations under visible light irradiation. Elementary steps for alkoxy radical generation from either radical precursors or free alcohols are central to reaction development; thus, each section is categorized and discussed accordingly. Throughout this review, we have focused on the different mechanisms of alkoxy radical generation as well as their impact on synthetic utilizations. Notably, the catalytic generation of alkoxy radicals from abundant alcohols is still in the early stage, providing intriguing opportunities to exploit alkoxy radicals for diverse synthetic paradigms.

H6N2 reassortant avian influenza virus isolate in wild birds in Jiangxi Province, China.

H6 avian influenza virus is widely prevalent in wild birds and poultry and has caused human infection in 2013 in Taiwan, China. During our active influenza surveillance program in wild waterfowl at Poyang Lake, Jiangxi Province, an H6N2 AIV was isolated and named A/bean goose/JiangXi/452-4/2013(H6N2). The isolate was characterized as a typical low pathogenic avian influenza virus (LPAIV) due to the presence of the amino acid sequence PQIETR↓GLFGAI at the cleavage site of the hemagglutinin (HA) protein. The genetic evolution analysis revealed that the NA gene of the isolate originated from North America and exhibited the highest nucleotide identity (99.29%) with a virus recovered from wild bird samples in North America, specifically A/bufflehead/California/4935/2012(H11N2). Additionally, while the HA and PB1 genes belonged to the Eurasian lineage, they displayed frequent genetic interactions with the North American lineage. The remaining genes showed close genetic relationships with Eurasian viruses. The H6N2 isolate possessed a complex genome, indicating it is a multi-gene recombinant virus with genetic material from both Eurasian and North American lineages.

Exosomes derived from mir-337-3p over-expressing tendon stem cells protect against apoptosis of tenocytes via targeting caspase3.

BACKGROUND: Tendons are important dense fibrous structures connecting muscle to bone, and tendon stem cells (TDSCs) affect their repair and regeneration. The role of TDSC-derived exosomes (TDSC-Exos) is still being unexplored; therefore, this study aimed to investigate the protective effect of TDSC-Exos on tenocytes. METHODS: The TDSCs and tenocytes were all derived from Sprague Dawley (SD) rats. The expression of positive and negative markers of TDSCs were detected by flow cytometry, and the multi-differentiation ability was also detected to identify TDSCs. Exos were derived from TDSCs using ultracentrifugation; furthermore, Exos enriched with microRNA(miR)-377-3p were generated from TDSCs stably overexpressing miR-377-3p after transfection, identified with transmission electron microscopy (TEM), western blot and PKH26 staining assay. Moreover, the cell functions of tenocytes were evaluated by MTT, EdU, transwell, and flow cytometry. Dual luciferase reporter and RNA pull-down assays were used to verify the binding sites of miR-337-3p and caspase3 (CASP3) predicted by Targetscan. RESULTS: Exos (miR-337-3p) were taken up by tenocytes, and promoted the proliferation, migration, and invasion and suppressed the apoptosis of tenocytes in a dose-dependent manner. Bioinformatics analysis showed that CASP3 was a target of miR-377-3p, which was further verified by luciferase and RNA pull-down assays. Moreover, over-expressed CASP3 reversed the effects of Exos (miR-337-3p) on cell functions of tenocytes. CONCLUSIONS: Our findings suggest that Exos derived from miR-337-3p over-expressing TDSCs could potentially protect against tenocyte apoptosis by regulating CASP3. This novel therapeutic approach holds promise for the treatment of tendon injury, offering a glimmer of hope for improved patient outcomes.

Identification of Alkoxy Radicals as Hydrogen Atom Transfer Agents in Ce-Catalyzed C-H Functionalization.

The intermediacy of alkoxy radicals in cerium-catalyzed C-H functionalization via H-atom abstraction has been unambiguously confirmed. Catalytically relevant Ce(IV)-alkoxide complexes have been synthesized and characterized by X-ray diffraction. Operando electron paramagnetic resonance and transient absorption spectroscopy experiments on isolated pentachloro Ce(IV) alkoxides identified alkoxy radicals as the sole heteroatom-centered radical species generated via ligand-to-metal charge transfer (LMCT) excitation. Alkoxy-radical-mediated hydrogen atom transfer (HAT) has been verified via kinetic analysis, density functional theory (DFT) calculations, and reactions under strictly chloride-free conditions. These experimental findings unambiguously establish the critical role of alkoxy radicals in Ce-LMCT catalysis and definitively preclude the involvement of chlorine radical. This study has also reinforced the necessity of a high relative ratio of alcohol vs Ce for the selective alkoxy-radical-mediated HAT, as seemingly trivial changes in the relative ratio of alcohol vs Ce can lead to drastically different mechanistic pathways. Importantly, the previously proposed chlorine radical-alcohol complex, postulated to explain alkoxy-radical-enabled selectivities in this system, has been examined under scrutiny and ruled out by regioselectivity studies, transient absorption experiments, and high-level calculations. Moreover, the peculiar selectivity of alkoxy radical generation in the LMCT homolysis of Ce(IV) heteroleptic complexes has been analyzed and back-electron transfer (BET) may have regulated the efficiency and selectivity for the formation of ligand-centered radicals.

Emergence, Evolution, and Pathogenicity of Influenza A(H7N4) Virus in Shorebirds in China.

A 2-year surveillance study of influenza A viruses in migratory birds was conducted to understand the subsequent risk during the migratory seasons in Dandong Yalu River Estuary Coastal Wetland National Nature Reserve, Liaoning Province, China, a major stopover site on the East Asian-Australasian flyway. Overall, we isolated 27 influenza A viruses with multiple subtypes, including H3N8 (n = 2), H4N6 (n = 2), H4N7 (n = 2), H7N4 (n = 9), H7N7 (n = 1), H10N7 (n = 7), and H13N6 (n = 4). Particularly, a novel reassortant influenza A(H7N4) virus was first identified in a woman and her backyard poultry flock in Jiangsu Province, China, posing a serious threat to public health. Here, we describe the genetic characterization and pathogenicity of the nine influenza A(H7N4) isolates. Phylogenetic analysis indicated that complex viral gene flow occurred among Asian countries. We also demonstrated a similar evolutionary trajectory of the surface genes of the A(H7N4) isolates and Jiangsu human-related A(H7N4) viruses. Our A(H7N4) isolates exhibited differing degrees of virulence in mice, suggesting a potential risk to other mammalian species, including humans. We revealed multiple mutations that might affect viral virulence in mice. Our report highlights the importance and need for the long-term surveillance of avian influenza virus in migratory birds combined with domestic poultry surveillance along migratory routes and flyways and, thereby, the development of measures to manage potential health threats. IMPORTANCE The H7 subtype avian influenza viruses, such as H7N2, H7N3, H7N4, H7N7, and H7N9, were documented as being capable of infecting humans, and the H7 subtype low pathogenicity avian influenza viruses are capable of mutating into highly pathogenic avian influenza; therefore, they pose a serious threat to public health. Here, we investigated the evolutionary history, molecular characteristics, and pathogenicity of shorebird-origin influenza A(H7N4) viruses, showing a similar evolutionary trajectory with Jiangsu human A(H7N4) viruses in HA and NA genes. Moreover, our isolates exhibited variable virulence (including moderate virulence) in mice, suggesting a potential risk to other mammalian species, including humans.

Genomic vulnerability to climate change in Quercus acutissima, a dominant tree species in East Asian deciduous forests.

Understanding the evolutionary processes that shape the landscape of genetic variation and influence the response of species to future climate change is critical for biodiversity conservation. Here, we sampled 27 populations across the distribution range of a dominant forest tree, Quercus acutissima, in East Asia, and applied genome-wide analyses to track the evolutionary history and predict the fate of populations under future climate. We found two genetic groups (East and West) in Q. acutissima that diverged during Pliocene. We also found a heterogeneous landscape of genomic variation in this species, which may have been shaped by population demography and linked selections. Using genotype-environment association analyses, we identified climate-associated SNPs in a diverse set of genes and functional categories, indicating a model of polygenic adaptation in Q. acutissima. We further estimated three genetic offset metrics to quantify genomic vulnerability of this species to climate change due to the complex interplay between local adaptation and migration. We found that marginal populations are under higher risk of local extinction because of future climate change, and may not be able to track suitable habitats to maintain the gene-environment relationships observed under the current climate. We also detected higher reverse genetic offsets in northern China, indicating that genetic variation currently present in the whole range of Q. acutissima may not adapt to future climate conditions in this area. Overall, this study illustrates how evolutionary processes have shaped the landscape of genomic variation, and provides a comprehensive genome-wide view of climate maladaptation in Q. acutissima.

Research on Safety Helmet Detection Algorithm Based on Improved YOLOv5s.

Safety helmets are essential in various indoor and outdoor workplaces, such as metallurgical high-temperature operations and high-rise building construction, to avoid injuries and ensure safety in production. However, manual supervision is costly and prone to lack of enforcement and interference from other human factors. Moreover, small target object detection frequently lacks precision. Improving safety helmets based on the helmet detection algorithm can address these issues and is a promising approach. In this study, we proposed a modified version of the YOLOv5s network, a lightweight deep learning-based object identification network model. The proposed model extends the YOLOv5s network model and enhances its performance by recalculating the prediction frames, utilizing the IoU metric for clustering, and modifying the anchor frames with the K-means++ method. The global attention mechanism (GAM) and the convolutional block attention module (CBAM) were added to the YOLOv5s network to improve its backbone and neck networks. By minimizing information feature loss and enhancing the representation of global interactions, these attention processes enhance deep learning neural networks' capacity for feature extraction. Furthermore, the CBAM is integrated into the CSP module to improve target feature extraction while minimizing computation for model operation. In order to significantly increase the efficiency and precision of the prediction box regression, the proposed model additionally makes use of the most recent SIoU (SCYLLA-IoU LOSS) as the bounding box loss function. Based on the improved YOLOv5s model, knowledge distillation technology is leveraged to realize the light weight of the network model, thereby reducing the computational workload of the model and improving the detection speed to meet the needs of real-time monitoring. The experimental results demonstrate that the proposed model outperforms the original YOLOv5s network model in terms of accuracy (Precision), recall rate (Recall), and mean average precision (mAP). The proposed model may more effectively identify helmet use in low-light situations and at a variety of distances.

Promotion of methane production and degradation of pyrolysis oil during its co-anaerobic digestion process via addition of N-doping hydro-chars.

Pyrolysis of wastes usually produces toxic pyrolysis oil (PO), which has complex ingredients, including benzene series and long-chain macromolecule organic pollutants. Co-anaerobic digestion (co-AD) can be an economic and high-efficiency method for PO degradation and recovery of methane simultaneously, but complete degradation of PO has not been achieved yet. Addition of a hydro-char in the process is beneficial to PO degradation and methane production. In this study, to further enhance the effectiveness of the hydro-char, nitrogen (N) was doped into the hydro-char by plasma modification in a NH3 atmosphere; and the effectiveness of the N-doped hydro-chars for promoting PO degradation and methane production during the co-AD process were evaluated. The experimental results indicated that all the hydro-chars can reduce the biotoxicity of the PO, improve its degradation during the co-AD process, and increase the methane yield. Compared with the plain hydro-char (HC), the hydro-chars modified at ambient temperature (HC-NH3-P-25) and at 500 °C (HC-NH3-P-500) can help achieving complete PO degradation and increasing the methane yield more effectively. The anaerobic digestor containing the HC-NH3-P-500 had the highest apparent methane yield (169.03 mLCH4/mLPO) and highest COD removal rate (79.5%). The nitrogen content, specific surface area, and electron transfer capability are found to be the key factors affecting PO degradation and methane yield; and the HC-NH3-P-500 had the highest N-doping, most specific surface area and electron transfer capability, explaining its best performance. The microbial communities of the digestate with the addition of the hydro-chars were founded to be richer with Clostridia and Methanosarcina, which could enhance the electron transfer between different microorganisms and contribute to the PO degradation.

Highly Pathogenic Avian Influenza A(H5N8) Clade 2.3.4.4b Viruses in Satellite-Tracked Wild Ducks, Ningxia, China, 2020.

During October 2020, we identified 13 highly pathogenic avian influenza A(H5N8) clade 2.3.4.4b viruses from wild ducks in Ningxia, China. These viruses were genetically related to H5N8 viruses circulating mainly in poultry in Europe during early 2020. We also determined movements of H5N8 virus‒infected wild ducks and evidence for spreading of viruses.

Linked selection shapes the landscape of genomic variation in three oak species.

Natural selection shapes genome-wide patterns of diversity within species and divergence between species. However, quantifying the efficacy of selection and elucidating the relative importance of different types of selection in shaping genomic variation remain challenging. We sequenced whole genomes of 101 individuals of three closely related oak species to track the divergence history, and to dissect the impacts of selective sweeps and background selection on patterns of genomic variation. We estimated that the three species diverged around the late Neogene and experienced a bottleneck during the Pleistocene. We detected genomic regions with elevated relative differentiation ('FST -islands'). Population genetic inferences from the site frequency spectrum and ancestral recombination graph indicated that FST -islands were formed by selective sweeps. We also found extensive positive selection; the fixation of adaptive mutations and reduction neutral diversity around substitutions generated a signature of selective sweeps. Prevalent negative selection and background selection have reduced genetic diversity in both genic and intergenic regions, and contributed substantially to the baseline variation in genetic diversity. Our results demonstrate the importance of linked selection in shaping genomic variation, and illustrate how the extent and strength of different selection models vary across the genome.

Comparison between chronic spontaneous urticaria and chronic induced urticaria on the efficacy of omalizumab treatment: A systematic review and meta-analysis.

This meta-analysis aimed to assess the efficacy of omalizumab in the treatment of refractory-to-antihistamines chronic induced urticaria (CIndU) in comparison with that of refractory-to-antihistamines chronic spontaneous urticaria (CSU). We retrieved interventional studies and observational studies on omalizumab efficacy to CIndU patients and efficacy comparison between CSU and CIndU both refractory to H1-antihistamines in electronic databases (accessed till May 2022). The odd ratio (OR) and 95% confidence interval (CI) was calculated with a random-effect model in this meta-analysis. The majority of patients with different CIndU subtypes gained complete or partial response and good safety after omalizumab treatment. A total of five studies with 355 CSU patients and 103 CIndU patients were included for the meta-analysis. There was no significant difference in the efficacy of omalizumab in the treatment of CSU and CIndU (OR -0.83, 95% CI [0.84, 2.21], P > 0.05). Based on the validity of omalizumab in the treatment of various CIndU subtypes and non-differential efficacy between CSU and CIndU, it is reasonable to list omalizumab as a third-line treatment of refractory CIndU.

Effects of different depth of anesthesia on perioperative inflammatory reaction and hospital outcomes in elderly patients undergoing laparoscopic radical gastrectomy.

BACKGROUND: To investigate the effect of different depth of anesthesia on inflammatory factors and hospital outcomes in elderly patients undergoing laparoscopic radical gastrectomy for gastric cancer, in order to select an appropriate depth of anesthesia to improve the prognosis of patients undergoing surgery and improve the quality of life of patients. METHODS: A total of 80 elderly patients aged 65 and above who underwent laparoscopic radical gastrectomy in our hospital were by convenience sampling and randomly divided into two groups : 55 groups ( group H ) and 45 groups ( group L ), 40 cases in each group. The depth of anesthesia was maintained using a closed-loop target-controlled infusion system: the EEG bispectral index was set to 55 in the H group and 45 in the L group. Venous blood samples were collected 2 h (T2), 24 h (T3) and 72 h (T4) after the start of surgery. The intraoperative dosage of propofol and remifentanil, operation duration, postoperative PACU stay time, intraoperative consciousness occurrence, postoperative hospital stay and postoperative pulmonary inflammatory events were recorded. RESULTS: The patient characteristic of the two groups had no statistical difference and were comparable (P > 0.05). The intraoperative dosage of propofol in group H was lower than that in group L (P < 0.05). Compared with the L group, the plasma IL-6 and IL-10 concentrations in the H group were significantly increased at T2 (P < 0.05), and the plasma IL-10 concentration was significantly increased at T4 (P < 0.05). The plasma concentrations of IL-6 and IL-10 were higher in both groups at T2, T3 and T4 than at T1, while at T4, the concentration of TNF-α in group H was higher than at T1 (P < 0.05). CONCLUSION: When the BIS value of the depth of anesthesia is 45, the perioperative release of inflammatory factors in elderly patients with laparoscopic radical gastrectomy for gastric cancer is less than BIS 55, and does not affect the prognosis.

Intelligent Scheduling Methodology for UAV Swarm Remote Sensing in Distributed Photovoltaic Array Maintenance.

In recent years, the unmanned aerial vehicle (UAV) remote sensing technology has been widely used in the planning, design and maintenance of urban distributed photovoltaic arrays (UDPA). However, the existing studies rarely concern the UAV swarm scheduling problem when applied to remoting sensing in UDPA maintenance. In this study, a novel scheduling model and algorithm for UAV swarm remote sensing in UDPA maintenance are developed. Firstly, the UAV swarm scheduling tasks in UDPA maintenance are described as a large-scale global optimization (LSGO) problem, in which the constraints are defined as penalty functions. Secondly, an adaptive multiple variable-grouping optimization strategy including adaptive random grouping, UAV grouping and task grouping is developed. Finally, a novel evolutionary algorithm, namely cooperatively coevolving particle swarm optimization with adaptive multiple variable-grouping and context vector crossover/mutation strategies (CCPSO-mg-cvcm), is developed in order to effectively optimize the aforementioned UAV swarm scheduling model. The results of the case study show that the developed CCPSO-mg-cvcm significantly outperforms the existing algorithms, and the UAV swarm remote sensing in large-scale UDPA maintenance can be optimally scheduled by the developed methodology.

EPSDNet: Efficient Campus Parking Space Detection via Convolutional Neural Networks and Vehicle Image Recognition for Intelligent Human-Computer Interactions.

The parking problem, which is caused by a low parking space utilization ratio, has always plagued drivers. In this work, we proposed an intelligent detection method based on deep learning technology. First, we constructed a TensorFlow deep learning platform for detecting vehicles. Second, the optimal time interval for extracting video stream images was determined in accordance with the judgment time for finding a parking space and the length of time taken by a vehicle from arrival to departure. Finally, the parking space order and number were obtained in accordance with the data layering method and the TimSort algorithm, and parking space vacancy was judged via the indirect Monte Carlo method. To improve the detection accuracy between vehicles and parking spaces, the distance between the vehicles in the training dataset was greater than that of the vehicles observed during detection. A case study verified the reliability of the parking space order and number and the judgment of parking space vacancies.

A Robust Fire Detection Model via Convolution Neural Networks for Intelligent Robot Vision Sensing.

Accurate fire identification can help to control fires. Traditional fire detection methods are mainly based on temperature or smoke detectors. These detectors are susceptible to damage or interference from the outside environment. Meanwhile, most of the current deep learning methods are less discriminative with respect to dynamic fire and have lower detection precision when a fire changes. Therefore, we propose a dynamic convolution YOLOv5 fire detection method using a video sequence. Our method first uses the K-mean++ algorithm to optimize anchor box clustering; this significantly reduces the rate of classification error. Then, the dynamic convolution is introduced into the convolution layer of YOLOv5. Finally, pruning of the network heads of YOLOv5's neck and head is carried out to improve the detection speed. Experimental results verify that the proposed dynamic convolution YOLOv5 fire detection method demonstrates better performance than the YOLOv5 method in recall, precision and F1-score. In particular, compared with three other deep learning methods, the precision of the proposed algorithm is improved by 13.7%, 10.8% and 6.1%, respectively, while the F1-score is improved by 15.8%, 12% and 3.8%, respectively. The method described in this paper is applicable not only to short-range indoor fire identification but also to long-range outdoor fire detection.

Intelligent Detection of Hazardous Goods Vehicles and Determination of Risk Grade Based on Deep Learning.

Currently, deep learning has been widely applied in the field of object detection, and some relevant scholars have applied it to vehicle detection. In this paper, the deep learning EfficientDet model is analyzed, and the advantages of the model in the detection of hazardous good vehicles are determined. The adaptive training model is built based on the optimization of the training process, and the training model is used to detect hazardous goods vehicles. The detection results are compared with Cascade R-CNN and CenterNet, and the results show that the proposed method is superior to the other two methods in two aspects of computational complexity and detection accuracy. Simultaneously, the proposed method is suitable for the detection of hazardous goods vehicles in different scenarios. We make statistics on the number of detected hazardous goods vehicles at different times and places. The risk grade of different locations is determined according to the statistical results. Finally, the case study shows that the proposed method can be used to detect hazardous goods vehicles and determine the risk level of different places.

Modification of hydro-chars by non-thermal plasma to enhance co-anaerobic digestion and degradation of sewage sludge pyrolysis oil.

The pyrolysis oil produced from the sewage sludge pyrolysis process is a complex admixture of organic substances, which is difficult to be degraded in a normal anaerobic digestion (AD) process. In this study, the hydro-chars produced at 200, 240, and 280 °C were modified by non-thermal plasma (NTP) and then they were used to promote pyrolysis oil degradation and biogas production in a co-AD digester. The experimental results revealed that after NTP modification, the specific surface areas of the hydro-chars produced at 200 °C (SW200+P) and 240 °C were increased from 28.0 to 39.3 m2g-1 and from 36.2 to 45.4 m2g-1, respectively. Their pore volumes also increased by more than 10%. The SW200+P hydro-char exhibited the highest chemical oxygen demand (COD) removal rate (60.49%) and the highest CH4 yield, which is 6.3 times of the digester with pyrolysis oil but without hydro-char addition (PO + CC). Additionally, the benzene series in the pyrolysis oil can be completely degraded in all digesters with the hydro-char addition. With addition of the SW200+P hydro-char, the Clostridia increased most significantly to become the predominant bacteria community at the class level, and the Methanosarcina became the predominant archaea community at the genus level, which contributed to the increased CH4 yield. The hydro-char addition also increased Dietzia and Cellulosimicrobium, which promoted the degradation of benzene series in the pyrolysis oil. The investigation results suggest that the NTP modification technique can be a potential solution to effectively utilize the hydro-char and help pyrolysis oil degradation via the co-AD process.

Blind Additive Gaussian White Noise Level Estimation from a Single Image by Employing Chi-Square Distribution.

The additive Gaussian white noise (AGWN) level in real-life images is usually unknown, for which the empirical setting will make the denoising methods over-smooth fine structures or remove noise incompletely. The previous noise level estimation methods are easily lost in accurately estimating them from images with complicated structures. To cope with this issue, we propose a novel noise level estimation scheme based on Chi-square distribution, including the following key points: First, a degraded image is divided into many image patches through a sliding window. Then, flat patches are selected by using a patch selection strategy on the gradient maps of those image patches. Next, the initial noise level is calculated by employing Chi-square distribution on the selected flat patches. Finally, the stable noise level is optimized by an iterative strategy. Quantitative, with association, to qualitative results of experiments on synthetic real-life images validate that the proposed noise level estimation method is effective and even superior to the state-of-the-art methods. Extensive experiments on noise removal using BM3D further illustrate that the proposed noise level estimation method is more beneficial for achieving favorable denoising performance with detail preservation.

Photocatalytic Dehydroxymethylative Arylation by Synergistic Cerium and Nickel Catalysis.

Under mild reaction conditions with inexpensive cerium and nickel catalysts, easily accessible free alcohols can now be utilized as operationally simple and robust carbon pronucleophiles in selective C(sp3)-C(sp2) cross-couplings. Facilitated by automated high-throughput experimentation, sterically encumbered benzoate ligands have been identified for robust cerium complexes, enabling the synergistic cooperation of cerium catalysis in the emerging metallaphotoredox catalysis. A broad range of free alcohols and aromatic halides can be facilely employed in this transformation, representing a new paradigm for the C(sp3)-C(sp2) bond construction between free alcohols and aryl halides with the extrusion of formaldehyde. Moreover, mechanistic investigations have been conducted, leading to the identification of a tribenzoate cerium(III) complex as a viable intermediate.