Bis(2,6-dihy­droxy­benzoato-κ2 O 1,O 1′)(nitrato-κ2 O,O′)bis­(1,10-phenanthroline-κ2 N,N′)praseodymium(III)

The mononuclear title complex, [Pr(C7H5O3)2(NO3)(C12H8N2)2], is isostructural with related complexes of other lanthanides. The Pr(III) atom is in a pseudo-bicapped square-anti­prismatic geometry, formed by four N atoms from two chelating 1,10-phenanthroline (phen) ligands and six O atoms, four from two 2,6-dihy­droxy­benzoate (DHB) ligands and the other two from nitrate anions. π–π stacking inter­actions between the phen and DHB ligands [centroid–centroid distances = 3.518 (2) and 3.778 (2) Å] and the phen and phen ligands [face-to-face separation = 3.427 (6) Å] of adjacent complexes stabilize the crystal structure. Intra­molecular O—H⋯O hydrogen bonds are observed in the DHB ligands

Bis(2,6-dihy­droxy­benzoato-κ2 O 1 ,O 1′)(nitrato-κ2 O,O′)bis­(1,10-phenanthroline-κ2 N,N′)europium(III)

The title mononuclear complex, [Eu(C7H5O3)2(NO3)(C12H8N2)2], is isostructural with those of other lanthanides. The Eu atom is in a pseudo-bicapped square-anti­prismatic geometry, formed by four N atoms from two chelating 1,10-phenanthroline (phen) ligands and by six O atoms, four from two 2,6-dihy­droxy­benzoate (DHB) ligands and the other two from a nitrate anion. π–π stacking inter­actions between phen and DHB ligands [centroid–centroid distances = 3.5312 (19) and 3.8347 (16) Å], and between phen and phen ligands [face-to-face separation = 3.433 (4) Å] of adjacent complexes stabilize the crystal structure. Intra­molecular O—H⋯O hydrogen bonds are observed in the DHB ligands

Air-water exchange and distribution pattern of organochlorine pesticides in the atmosphere and surface water of the open Pacific ocean

Surface seawater and lower atmosphere gas samples were collected simultaneously between 18°N and 40°S in the open Pacific Ocean in 2006–2007. Samples were analyzed for organochlorine pesticides (OCPs) to assess their distribution patterns, the role of ocean in the long-range transport (LRT), and the air-water exchange directions in the open Pacific Ocean. Such open ocean studies can yield useful information such as establishing temporal and spatial trends and assessing primary vs secondary emissions of legacy OCPs. Target compounds included hexachlorocyclohexanes (HCHs), dichlorodiphenyltrichloroethanes (DDTs) and its derivatives, and chlordane compounds. Concentrations for α-HCH, γ-HCH, trans-chlordane (TC), and cis-chlordane (CC) were higher in the Northern Hemisphere (NH) than the Southern Hemisphere (SH) in both gaseous and dissolved phases, while the distribution patterns of DDTs and heptachlor exo-epoxide (HEPX) showed a reversed pattern. In the N Pacific, concentrations of α-HCH and γ-HCH in the present work were lower by 63 and 16 times than those observed in 1989–1990. The distribution patterns of DDT suggested there was usage in the SH around 2006. Calculated fugacity ratios suggested that γ-HCH was volatilizing from surface water to the atmosphere, and the air-water exchange fluxes were 0.3–11.1 ng m−2 day−1. This is the first field study that reported the open Pacific Ocean has become the secondary source for γ-HCH and implied that ocean could affect LRT of OCPs by supplying these compounds via air-sea exchange

Rapid changes in heatwaves pose dual challenge in Eastern China and its adjacent seas

This paper performs a comparative analysis of the spatiotemporal variations of the statistical characteristics of both atmospheric heatwaves over the land (AHWs) in eastern China and marine heatwaves (MHWs) in adjacent seas using a unified heatwave definition. The multi-year average total days and frequency of MHWs during 1982-2019 were 5 and 2 times higher than those of AHWs, respectively, while the mean intensities of AHWs and MHWs were unchanged. The future frequency and duration of AHWs will continue to increase, leading to a superimposed increase in AHW total days. The decreasing frequency and increasing duration of MHWs will result in nearly year-round MHWs from 2060. Under the control of high-pressure systems, clear skies dominate the summer weather conditions in eastern China and its adjacent seas, which will trigger heatwaves. Heatwaves in turn can release substantial ocean latent heat. Enhanced convection and heating will further drive a stronger anticyclone over the western North Pacific, leading to a stronger and more westwardextending western North Pacific subtropical high (WNPSH). Moreover, super El Niño can promote an anomalous WNPSH in decaying summer, which may cause more serious heatwaves. The multi-year average persons affected by AHWs (PAHWs) during 1982-2019 were larger in the North China Plain, Yangtze River Delta, and Sichuan Basin with the regional sum exceeding 3 million. The future maximum PAHWs under SSP2-4.5 and SSP5-8.5 scenarios will be 3.9 billion in 2076 and 4.7 billion in 2085, respectively. Marine ecosystems like artificial ranches and coral reefs will be more threatened by longerlasting MHWs

Shift invariant sparse coding ensemble and its application in rolling bearing fault diagnosis

This paper proposes an automatic diagnostic scheme without manual feature extraction or signal pre-processing. It directly handles the original data from sensors and determines the condition of the rolling bearing. With proper application of the new technique of shift invariant sparse coding (SISC), it is much easier to recognize the fault. Yet, this SISC, though being a powerful machine learning algorithm to train and test the original signals, is quite demanding computationally. Therefore, this paper proposes a highly efficient SISC which has been proved by experiments to be capable of representing signals better and making converges faster. For better performance, the AdaBoost algorithm is also combined with SISC classifier. Validated by the fault diagnosis of bearings and compared with other methods, this algorithm has higher accuracy rate and is more robust to load as well as to certain variation of speed

A hydraulic fault diagnosis method based on sliding-window spectrum feature and deep belief network

The vibration signal of hydraulic system contains abundant state information, so vibration testing technology is an effective way to realize the fault diagnosis of hydraulic system. However, the mapping relation between signal characteristic and system state is complex and the expression meaning of characteristic is obscure, which brings a great challenge to the hydraulic fault diagnosis. The DBN, a newly proposed deep learning model, has an advantage of autonomously learning and reasoning. And it is good at studying the concealed representation of data and highlighting the feature expression. So, it is contributive to deal with the problems of large capacity data like high dimension, redundancy, and nonlinear etc. Therefore, DBN is chosen as the fault diagnosis method in this paper. Meanwhile, given that the difficulty in feature extraction of hydraulic vibration signal and the important influence of input feature vector to the diagnosing of DBN, a fast and effectively feature extraction method based on sliding-window spectrum feature (SWSF) is proposed. It is effective in remaining the integrity of feature, avoiding the risking of relative shifting of characteristic spectrum, and decreasing the dimensions of feature vector. The experimental results demonstrate that the combination of SWSF and DBN is a fast and effective approach to realize the fault diagnosis of hydraulic system

Critical factors driving spatiotemporal variability in the phytoplankton community structure of the coral habitat in Dongshan Bay, China

This study investigated the spatiotemporal distribution of the phytoplankton in the coral habitat of Dongshan Bay (China), along with critical factors affecting the distribution, during June, August, and December 2022. Phytoplankton abundance in Dongshan Bay exhibited considerably temporal variation, peaking in June 2022, gradually decreasing thereafter, and reaching its lowest point in December 2022. The abundance of bottom-layer phytoplankton consistently exceeded that of the surface layer throughout all seasons. The average phytoplankton abundance in the coral habitat of Dongshan Bay was lower than that in non-coral habitat areas. Fluctuations in the Zhangjiang River and coastal upwelling influenced the diversity and community structure of the phytoplankton. Critical factors causing spatiotemporal variability in phytoplankton community structure included nutrient concentrations and seawater temperature. Nutrients played key roles in influencing various phytoplankton groups. Dominant diatom species, such as Thalassionema nitzschioides and Thalassiosira diporocyclus, were positively correlated with ammonia nitrogen, seawater salinity, coral cover, and the number of coral species present. In winter, Calanus sinicus exhibited a negative correlation with harmful algal bloom species. Additionally, it was found that both in the coral habitat and surrounding open sea, currents, nutrients, and zooplankton may play crucial roles in determining the spatiotemporal variability in the phytoplankton community structure