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• Mn-MOF derived MnS was synthesized for heterogeneous PMS activation. • An electron-transfer dominated process was verified in α-MnS/PMS system. • The presence of 1O2 and free radicals promoted the degradation of LVF. • The application potential of α-MnS/PMS system was evaluated. Recently, transition metal sulfides have attracted much attention due to their better catalytic capacities as peroxymonosulfate (PMS) activator than their metal oxide counterparts. However, the systematic studies on PMS activation using transition metal sulfides are still lacking. In this work, manganese sulfide (MnS) materials were synthesized via a MOFs-derived method and utilized for PMS activation to degrade levofloxacin (LVF) in water for the first time. As expected, MnS exhibited remarkable LVF degradation efficiency by PMS activation, which was distinctly higher than Mn 2 O 3. The results of quenching experiments, electro spin resonance identification and electrochemical tests indicated that electron-transfer progress was the dominant mechanism in α-MnS/PMS system. Meanwhile, the presence of 1O 2 and radicals further became the removal of LVF by α-MnS/PMS system into a radical/nonradical coupling process. The superior electrical conductivity of α-MnS than α-Mn 2 O 3 was revealed by DFT calculations, which resulted in the higher catalytic capacity of α-MnS. The result of XPS also indicated the S species in MnS accelerated the recycle of Mn(IV)/Mn(II) and then promoted the generation of radicals. Furthermore, the influence of various environmental conditions on LVF removal and the reusability of α-MnS were also investigated, which demonstrated the high application potential of α-MnS/PMS system. Finally, six possible pathways of LVF oxidation in the system were proposed based on the identified byproducts and their ecotoxicity was evaluated with ECOSAR method. This work promotes the fundamental understanding of PMS activation by α-MnS and provides useful information for practical application of manganese sulfide in water treatment. [ABSTRACT FROM AUTHOR]

Incident detection (ID), or the automatic discovery of anomalies from road traffic data (e.g., road sensor and GPS data), enables emergency actions (e.g., rescuing injured people) to be carried out in a timely fashion. Existing ID solutions based on data mining or machine learning often rely on dense traffic data; for instance, sensors installed in highways provide frequent updates of road information. In this paper, we ask the question: can ID be performed on sparse traffic data (e.g., location data obtained from GPS devices equipped on vehicles)? As these data may not be enough to describe the state of the roads involved, they can undermine the effectiveness of existing ID solutions. To tackle this challenge, we borrow an important insight from the transportation area, which uses trajectories (i.e., moving histories of vehicles) to derive incident patterns. We study how to obtain incident patterns from trajectories and devise a new solution (called F ilter- D iscovery- M atch (FDM)) to detect anomalies in sparse traffic data. We have also developed a fast algorithm to support FDM. Experiments on a taxi dataset in Hong Kong and a simulated dataset show that FDM is more effective than state-of-the-art ID solutions on sparse traffic data, and is also efficient. [ABSTRACT FROM AUTHOR]

In this work, the presence of ascorbic acid (AsA) in MIL-88B(Fe) / H 2 O 2 system was demonstrated to significantly increase the sulfamethoxazole (SMX) degradation efficiency. The SMX degradation rate in AsA/MIL-88B(Fe) / H 2 O 2 system was 0.177 L/(mg∙min), which was 60 times that of the MIL-88B(Fe) / H 2 O 2 system. Moreover, the study shows that AsA not only promotes SMX degradation in Fenton-like systems but also expands its pH application range. The effect of coexisting anions on the catalytic performance of the AsA/MIL-88B(Fe) / H 2 O 2 system was also investigated. Then, reactive species were detected via quenching experiments, which indicated •OH as the dominant free radical contributing to SMX degradation. Meanwhile, ESR determinations confirmed the existence of •OH and O2 − • in AsA/MIL-88B(Fe) / H 2 O 2 system. The high activity of the AsA/MIL-88B(Fe) / H 2 O 2 system was attributed to the effective surface Fe(III)/Fe(II) cycle promoted by AsA, and a possible mechanism of the AsA/MIL-88B(Fe) / H 2 O 2 system is proposed. The possible pathways for SMX and AsA degradation in the AsA/MIL-88B(Fe) / H 2 O 2 system are proposed based on the identified intermediates and the ecotoxicity analysis was conducted by ECOSAR. Finally, experimental results using the actual surface water and groundwater revealed the excellent availability of AsA/MIL-88B(Fe)/H 2 O 2 system in remediating SMX contaminated water. This study presents a novel, efficient Fenton-like system using AsA and iron-based metal-organic frameworks for sulfonamide removal from water. • ASA significantly increased the SMX degradation efficiency. • ASA expanded the pH application range in Fenton-like process. • •OH was the dominant free radical contributed to the SMX degradation. • The surface Fe(III)/Fe(II) cycle on MIL-88B(Fe) was promoted by ASA. • The notable reusability and stability of MIL-88B(Fe) was revealed. [ABSTRACT FROM AUTHOR]

Knowledge graph (KG) embedding methods are at the basis of many KG-based data mining tasks, such as link prediction and node clustering. However, graphs may contain confidential information about people or organizations, which may be leaked via embeddings. Research recently studied how to apply differential privacy to a number of graphs (and KG) analyses, but embedding methods have not been considered so far. This study moves a step toward filling such a gap, by proposing the Differential Private Knowledge Graph Embedding (DPKGE) framework. DPKGE extends existing KG embedding methods (e.g., TransE, TransM, RESCAL, and DistMult) and processes KGs containing both confidential and unrestricted statements. The resulting embeddings protect the presence of any of the former statements in the embedding space using differential privacy. Our experiments identify the cases where DPKGE produces useful embeddings, by analyzing the training process and tasks executed on top of the resulting embeddings. [ABSTRACT FROM AUTHOR]

Abstract: Structural damage localization plays an important role in structural damage identification. An cumulative structural damage localization method based on evidence theory is studied in this paper. An algorithm for cumulative fusion of primary localization information is presented. In the numerical study, a fixed-end beam is inspected. Two damage cases are studied, one with single damage and the other with multiple damages. White noises are added to the beam mode shapes of the first five orders to simulate the measurement noises. First, Modal Strain Energy Change Ratio (MSECR) method is used to localize the damage elements using the noise-contaminated mode shapes. Then, the locations determined by MSECR are taken as primary information and fused cumulatively. In both the single-damage-case and the multiple-damage-case, the fused results show that damaged elements are accurately identified. Furthermore, the damage elements are distinguished much more clearly than those identified from MSECR. [Copyright &y& Elsevier]

• Genetic mutation score (GMS) could be a biomarker of normal karyotype acute myeloid leukemia (AML) relapse. • GMS nomogram (GMSN) was a model that integrated GMS, measurable residual disease, and clinical factors. • GMSN exhibited superior predictive potential for relapse of normal karyotype AML. Risk stratification for normal karyotype acute myeloid leukemia (NK-AML) remains unsatisfactory, which is reflected by the high incidence of leukemia relapse. This study aimed to evaluate the role of gene mutations and clinical characterization in predicting the relapse of patients with NK-AML. A prognostic system for NK-AML was constructed. A panel of gene mutations was explored using next-generation sequencing. A nomogram algorithm was used to build a genomic mutation signature (GMS) nomogram (GMSN) model that combines GMS, measurable residual disease, and clinical factors to predict relapse in 347 patients with NK-AML from four centers. Patients in the GMS-high group had a higher 5-year incidence of relapse than those in the GMS-low group (p < 0.001). The 5-year incidence of relapse was also higher in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001). The 5-year disease-free survival and overall survival rates were lower in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (p < 0.001) as confirmed by training and validation cohorts. This study illustrates the potential of GMSN as a predictor of NK-AML relapse. [ABSTRACT FROM AUTHOR]

We explored the feasibility and removal mechanism of removing 2-chlorobiphenyl (2-ClBP) from soil–water system using granular activated carbon (GAC) impregnated with nanoscale zerovalent iron (reactive activated carbon or RAC). The RAC samples were successfully synthesized by the liquid precipitation method. The mesoporous GAC based RAC with low iron content (1.32%) exhibited higher 2-ClBP removal efficiency (54.6%) in the water phase. The result of Langmuir–Hinshelwood kinetic model implied that the different molecular structures between 2-ClBP and trichloroethylene (TCE) resulted in more difference in dechlorination reaction rates on RAC than adsorption capacities. Compared to removing 2-ClBP in the water phase, RAC removed the 2-ClBP more slowly in the soil phase due to the significant external mass transfer resistance. However, in the soil phase, a better removal capacity of RAC was observed than its base GAC because the chemical dechlorination played a more important role in total removal process for 2-ClBP. This important result verified the effectiveness of RAC for removing 2-ClBP in the soil phase. Although reducing the total RAC removal rate of 2-ClBP, soil organic matter (SOM), especially the soft carbon, also served as an electron transfer medium to promote the dechlorination of 2-ClBP in the long term. [ABSTRACT FROM AUTHOR]

Abstract: Structural stability is an vital aspect for structural health monitoring of transmission lines. This paper presents a novel method to evaluate the structural status of transmission line based on dynamic and stability analysis. A newly built long-span transmission tower-line system that crosses the Huaihe River in China with a span of 1083m was studied as an example. Finite element model of the transmission tower-line system was constructed. Nonlinear buckling analysis for both the tower and tower-line system were performed to determine the critical wind loads. Dynamic properties of both the tower and tower-line system under different levels of wind loads were analyzed. Numerical results show the law that modal frequency of low order modes decreases when the wind velocity increases before the structural instability happens for both cases. Therefore, for the structural health monitoring of transmission lines, frequency decrease of low order mode is an useful indicator to predict the happening of structural instability. This conclusion could be taken as the reference in the design of structural health monitoring system for transmission lines. [Copyright &y& Elsevier]

Highlights: [•] S supply can alleviate Cd toxicity. [•] Cd accumulation in rice root was more than in shoot. [•] Without S supply Cd distributed in the bottom of root while equally in shoot. [•] S addition could facilitate Cd transfer to the top of shoot. [•] S and Cd addition promoted the synthesis of thiol pool. [ABSTRACT FROM AUTHOR]