Water and energy are key sustainability issues that need to be addressed. Photocatalysis represents an attractive means to not only remediate polluted waters, but also harness solar energy. ...Unfortunately, the employment of photocatalysts remains a practical challenge in terms of high cost, low efficiency, secondary pollution and unexploited water matrices influence. This study investigated the feasibility of photocatalysis to both treat water and produce hydrogen with practical water systems. Polymeric carbon nitride foam (CNF) with large surface area and mesoporous structure was successfully prepared via the bubble-template effect of ammonium chloride decomposition during thermal condensation. The reaction kinetics, mechanisms, and effect of natural water matrices and wastewater on CNF-based photocatalytic removal of tetracycline hydrochloride (TC-HCl) were systematically investigated. Furthermore, the efficiency of clean hydrogen energy from natural water matrices and wastewater was also evaluated. It was found that the photocatalytic performance of CNF for TC-HCl removal was principally affected by calcination temperature in the presence of NH4Cl. The degradation rates of CNF-4 (calcined at 550 °C) were approximately 1.84, 2.49 and 7.47 times than that of the CNF-2 (calcined at 600 °C), CNF-1 (calcined at 500 °C) and GCN (without NH4Cl), respectively. Results indicate that the improved photocatalytic performance was predominantly ascribed to the large specific surface area, increased availability of exposed active sites, and enhanced transport and separation efficiency of the photogenerated carrier. Based on electron spin resonance, chemical trapping experiment and density functional theory calculation, photoinduced oxidizing species (·O2− and holes) initially attacked the C-N-C fragment of TC molecules, which were finally mineralized to CO2, water and inorganic matters. Under the synergistic influence of water constituents (including acidity and alkalinity, ion species and dissolved organic substances), various water matrices greatly affected the degradation rate of TC-HCl, with the highest removal efficiency of 78.9% in natural seawater, followed by reservoir water (75.0%), tap water (62.3%), deionized water (49.8%), reverse osmosis concentrate (32.7%) and pharmaceutical wastewater (18.9%). Interestingly, low amounts of the emerging microplastics slightly improved TC-HCl removal, whereas high amounts (1.428 × 107 P/cm3) restricted removal due to light absorption and the intrinsic adsorption interaction. Moreover, the photocatalysts were able over repeated usage. Notably, the hydrogen yields rates of polymeric carbon nitride foam were 352.2, 299.8, 184.9 and 94.3 μmol/g/h in natural seawater, pharmaceutical wastewater, water from reservoir and tap water, respectively. This study proves the potential of novel nonmetal porous photocatalyst to simultaneously treat wastewater while converting solar energy into clean hydrogen energy.
•Bubble-templated CNF for photo-induced decomposition of tetracyclines.•Higher degradation efficiencies of TC-HCl observed in all natural water matrices.•The C-N-C moiety of TC-HCl was identified as the initially reactive site for attack.•Microplastics affected the photocatalytic removal of TC-HCl.•Hydrogen energy was photocatalytically reclaimed from natural water matrices.
Owing to the critical roles it plays for both structure and functionality, hydrogen bonding has high hopes for the orientated applications in hydrogen‐bonded organic frameworks (HOFs). Here in this ...work, a hydrogen‐bonding strategy is performed for adjusting the structure and functionality of a heme‐like ligand meso‐tetra(carboxy‐phenyl)‐porphyrin (TCPP) with co‐former 1,3‐di(4‐pyridyl) propane (1,3‐DPP). A 3D dynamic HOF TCPP‐1,3–DPP, with permanent porosity is obtained. For this HOF, the two components form novel robust 1D porous stripes, with the 1,3‐DPP molecules acting as the lining for the pores that are confined within the region between adjacent carboxyphenyl moieties of TCPP. This confinement has tuned the affinities of TCPP from hydrophobic into hydrophilic. Interestingly, the 1D stripes are further stacked by weak π…π interactions into a 3D framework, the latter is highly dynamic with 1D stripes sliding back and forth, upon pressurized and water adsorption in the solid‐state under ambient conditions, respectively. The activated TCPP‐1,3–DPP has a Brunauer–Emmett–Teller surface area of 258 m2 g−1, and shows a maximum adsorption capacity about 9.8% for water during the adsorption–desorption cycles, demonstrating a promising candidate for the real‐world application in effective dehydration of industrial gases under ambient conditions.
A 3D dynamic hydrogen‐bonded organic framework TCPP‐1,3–DPP, which is composed of 1D porous stripes, shows permanent porosity and highly affinity to water. The activated species exhibit a maximum adsorption capacity about 9.8% for water during the adsorption–desorption cycles, demonstrating a promise for the real‐world application in effective dehydration of industrial gas under ambient condition.
Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates. However, it is different from real-world scenarios where ...the annotations of pedestrian bounding boxes are unavailable and the target person needs to be searched from a gallery of whole scene images. To close the gap, we propose a new deep learning framework for person search. Instead of breaking it down into two separate tasks-pedestrian detection and person re-identification, we jointly handle both aspects in a single convolutional neural network. An Online Instance Matching (OIM) loss function is proposed to train the network effectively, which is scalable to datasets with numerous identities. To validate our approach, we collect and annotate a large-scale benchmark dataset for person search. It contains 18,184 images, 8,432 identities, and 96,143 pedestrian bounding boxes. Experiments show that our framework outperforms other separate approaches, and the proposed OIM loss function converges much faster and better than the conventional Softmax loss.
Covalent organic frameworks (COFs) have received increased interest in recent years as an advanced class of materials. By virtue of the available monomers, multiple conformations and various ...linkages, COFs offer a wide range of opportunities for complex structural design and specific functional development of materials, which has facilitated the widespread application in many fields, including multi‐valent metal ion batteries (MVMIBs), described as the attractive candidate replacing lithium‐ion batteries (LIBs). With their robust skeletons, diverse pores, flexible structures and abundant functional groups, COFs are expected to help realize a high performance MVMIBs. In this review, we present an overview of COFs, describe advances in topology design and synthetic reactions, and study the application of COFs in MVMIBs, as well as discuss challenges and solutions in the preparation of COFs electrodes, in the hope of providing constructive insights into the future direction of COFs.
Covalent organic frameworks (COFs) offer an opportunity for complex structural design and specific functional development, facilitating, for example, the applications of multi‐valent metal ion batteries (Zn2+, Mg2+, Al3+). This comprehensive review describes COF synthesis and applications, provides advances in topology design and synthetic reactions, surveys the application of COFs in multi‐valent ion batteries, discusses the key issues of COF electrodes, and predicts future applications.
► A novel chaotic map is proposed and the new chaotic characteristics are proved. ► A new Cat map is designed for permutation based on multiple-dimensional chaotic maps. ► A encryption algorithm is ...proposed based on the chaos, and has higher speed. ► The tests show that the novel image scheme solves the short cycle and low precision.
In order to solve the problem that chaos is degenerated in limited computer precision and Cat map is the small key space, this paper presents a chaotic map based on topological conjugacy and the chaotic characteristics are proved by Devaney definition. In order to produce a large key space, a Cat map named block Cat map is also designed for permutation process based on multiple-dimensional chaotic maps. The image encryption algorithm is based on permutation–substitution, and each key is controlled by different chaotic maps. The entropy analysis, differential analysis, weak-keys analysis, statistical analysis, cipher random analysis, and cipher sensibility analysis depending on key and plaintext are introduced to test the security of the new image encryption scheme. Through the comparison to the proposed scheme with AES, DES and Logistic encryption methods, we come to the conclusion that the image encryption method solves the problem of low precision of one dimensional chaotic function and has higher speed and higher security.
This work addresses the problem of cross-domain few-shot classification which aims at recognizing novel categories in unseen domains with only a few labeled data samples. We think that the ...pre-trained model contains the redundant elements which are useless or even harmful for the downstream tasks. To remedy the drawback, we introduce an L 2 -SP regularized dense-sparse-dense (DSD) fine-tuning flow for regularizing the capacity of pre-trained networks and achieving efficient few-shot domain adaptation. Given a pre-trained model from the source domain, we start by carrying out a conventional dense fine-tuning step using the target data. Then we execute a sparse pruning step that prunes the unimportant connections and fine-tunes the weights of sub-network. Finally, initialized with the fine-tuned sub-network, we retrain the original dense network as the output model for the target domain. The whole fine-tuning procedure is regularized by an L 2 -SP term. In contrast to the existing methods that either tune the weights or prune the network structure for domain adaptation, our regularized DSD fine-tuning flow simultaneously exploits the benefits of sparsity regularity and dense network capacity to gain the best of both worlds. Our method can be applied in a plug-and-play manner to improve the existing fine-tuning methods. Extensive experimental results on benchmark datasets demonstrate that our method in many cases outperforms the existing cross-domain few-shot classification methods in significant margins. Our code will be released soon.
The mammalian distal convoluted tubule (DCT) makes an important contribution to potassium homeostasis by modulating NaCl transport. The thiazide-sensitive Na
/Cl
cotransporter (NCC) is activated by ...low potassium intake and by hypokalemia. Coupled with suppression of aldosterone secretion, activation of NCC helps to retain potassium by increasing electroneutral NaCl reabsorption, therefore reducing Na
/K
exchange. Yet the mechanisms by which DCT cells sense plasma potassium concentration and transmit the information to the apical membrane are not clear. Here, we tested the hypothesis that the potassium channel Kir4.1 is the potassium sensor of DCT cells. We generated mice in which Kir4.1 could be deleted in the kidney after the mice are fully developed. Deletion of Kir4.1 in these mice led to moderate salt wasting, low BP, and profound potassium wasting. Basolateral membranes of DCT cells were depolarized, nearly devoid of conductive potassium transport, and unresponsive to plasma potassium concentration. Although renal WNK4 abundance increased after Kir4.1 deletion, NCC abundance and function decreased, suggesting that membrane depolarization uncouples WNK kinases from NCC. Together, these results indicate that Kir4.1 mediates potassium sensing by DCT cells and couples this signal to apical transport processes.
Herein, we report a one-step synthesis of a hollow Fe-N/C catalyst
via
a hard-templating strategy, in which FeN
x
sites are well dispersed on the carbon sphere. In particular, we found an optimal ...iron ratio on the catalyst surface for an enhanced alkaline oxygen reduction reaction (ORR). The catalyst with a high specific surface area of 311.71 m
2
g
−1
exposes abundant electroactive sites that facilitate the adsorption of oxygen intermediates, thus exhibiting superior ORR activity in alkaline solution.
Molecular design to validation of relevant Fe-O bonds, performance tests and characterization results demonstrate that an FeN
2+2
-O coupled hollow carbon structure as an active site can exhibits superior cell performance.
In this paper, we analyze the generalization performance of the Iterative Hard Thresholding (IHT) algorithm widely used for sparse recovery problems. The parameter estimation and sparsity recovery ...consistency of IHT has long been known in compressed sensing. From the perspective of statistical learning, another fundamental question is how well the IHT estimation would predict on unseen data. This paper makes progress towards answering this open question by introducing a novel sparse generalization theory for IHT under the notion of algorithmic stability. Our theory reveals that: 1) under natural conditions on the empirical risk function over <inline-formula> <tex-math notation="LaTeX">n </tex-math></inline-formula> samples of dimension <inline-formula> <tex-math notation="LaTeX">p </tex-math></inline-formula>, IHT with sparsity level <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> enjoys an <inline-formula> <tex-math notation="LaTeX">\tilde {\mathcal {O}}(n^{-1/2}\sqrt {k\log (n)\log (p)}) </tex-math></inline-formula> rate of convergence in sparse excess risk; 2) a tighter <inline-formula> <tex-math notation="LaTeX">\tilde {\mathcal {O}}(n^{-1/2}\sqrt {\log (n)}) </tex-math></inline-formula> bound can be established by imposing an additional iteration stability condition on a hypothetical IHT procedure invoked to the population risk; and 3) a fast rate of order <inline-formula> <tex-math notation="LaTeX">\tilde {\mathcal {O}}\left ({n^{-1}k(\log ^{3}(n)+\log (p))}\right) </tex-math></inline-formula> can be derived for strongly convex risk function under proper strong-signal conditions. The results have been substantialized to sparse linear regression and sparse logistic regression models to demonstrate the applicability of our theory. Preliminary numerical evidence is provided to support our theoretical predictions.
Sunset yellow (SY) is a synthetic colorant which can cause allergies, diarrhea and other symptoms in sensitive people. When ingested too much, it can accumulate in the body and cause damage to the ...kidneys and liver. Therefore, the content of SY in food must be strictly controlled. In order to regulate their use and ensure food quality, simple and cost-effective methods need to be developed to identify them. In this experiment, fluorescent silicon nanoparticles (SiNPs) were prepared by a one-step method, which is simple, mild and less time-consuming. The fluorescent SiNPs prepared had good thermal stability, excellent salt resistance and pH stability. SY effectively quenched the fluorescence of SiNPs by fluorescence resonance energy transfer when added to the system as an interfering substance. The method had a good linear relationship in the range of SY concentration of 0.050 – 14.0 μg mL−1 and the detection limit is 0.023 μg mL−1. The established sensor was applied to the detection of SY in beverages, and the recovery rate was 93.8 – 102.4%. Based on the excellent selectivity and sensitivity of the method, it could provide a convenient way for the detection of SY in food samples.
PDF
