Logging practices in software engineering : A systematic mapping study

Background: Logging practices provide the ability to record valuable runtime information of software systems to support operations tasks such as service monitoring and troubleshooting. However, current logging practices face common challenges. On the one hand, although the importance of logging practices has been broadly recognized, most of them are still conducted in an arbitrary or ad-hoc manner, ending up with questionable or inadequate support to perform these tasks. On the other hand, considerable research effort has been carried out on logging practices, however, few of the proposed techniques or methods have been widely adopted in industry. Objective: This study aims to establish a comprehensive understanding of the research state of logging practices, with a focus on unveiling possible problems and gaps which further shed light on the potential future research directions. Method: We carried out a systematic mapping study on logging practices with 56 primary studies. Results: This study provides a holistic report of the existing research on logging practices by systematically synthesizing and analyzing the focus and inter-relationship of the existing research in terms of issues, research topics and solution approaches. Using 3W1H — Why to log , Where to log , What to log and How well is the logging —as the categorization standard, we find that: (1) the best known issues in logging practices have been repeatedly investigated; (2) the issues are often studied separately without considering their intricate relationships; (3) the Where and What questions have attracted the majority of research attention while little research effort has been made on the Why and How well questions; and (4) the relationships between issues, research topics, and approaches regarding logging practices appear many-to-many, which indicates a lack of profound understanding of the issues in practice and how they should be appropriately tackled. Conclusions: This study indicates a need to advance the state of research on logging practices. For example, more research effort should be invested on why to log to set the anchor of logging practices as well as on how well is the logging to close the loop. In addition, a holistic process perspective should be taken into account in both the research and the adoption related to logging practices

Occurrence and distribution of Amphidomataceae (Dinophyceae) in Danish coastal waters of the North Sea, the Limfjord and the Kattegat/Belt area

Some species of the dinophytes Azadinium and Amphidoma (Amphidomataceae) produce azaspiracids (AZA), lipophilic polyether compounds responsible for Azaspiracid Shellfish Poisoning (AZP) in humans after consumption of contaminated seafood. Toxigenic Amphidomataceae are known to occur in the North Atlantic and the North Sea area, but little is known about their importance in Danish coastal waters. In 2016, 44 Stations were sampled on a survey along the Danish coastline, covering the German Bight, Limfjord, the Kattegat area, Great Belt and Kiel Bight. Samples were analysed by live microscopy, liquid chromatography-tandem mass spectrometry (LC–MS/MS) and quantitative polymerase-chain-reaction (qPCR) on the presence of Amphidomataceae and AZA. Amphidomataceae were widely distributed in the area, but were below detection limit on most of the inner Limfjord stations. Cell abundances of the three toxigenic species, determined with species-specific qPCR assays on Azadinium spinosum, Az. poporum and Amphidoma languida, were generally low and restricted to the North Sea and the northern Kattegat, which was in agreement with the distribution of the generally low AZA abundances in plankton samples. Among the toxigenic species, Amphidoma languida was dominant with highest cell densities up to 3×103 cells L−1 on North Sea stations and at the western entrance of the Limfjord. Azaspiracids detected in plankton samples include low levels of AZA-1 at one station of the North Sea, and higher levels of AZA-38 and -39 (up to 1.5 ng L−1) in the North Sea and the Limfjord entrance. Furthermore, one new AZA (named AZA-63) was discovered in plankton of two North Sea stations. Morphological, molecular, and toxinological characterisation of 26 newly established strains from the area confirmed the presence of four amphidomatacean species (Az. obesum, Az. dalianense, Az. poporum and Am. languida). The single new strain of Az. poporum turned out as a member of Ribotype A2, which was previously only known from the Mediterranean. Consistent with some of these Mediterranean A2 strains, but different to the previously established AZA-37 producing Az. poporum Ribotype A1 strains from Denmark, the new strain did not contain any AZA. Azaspiracids were also absent in all Az. obesum and Az. dalianense strains, but AZA-38 and -39 were found in all Am. languida strains with total AZA cell quotas ranging from 0.08 up to 94 fg cell−1. In conclusion, AZA-producing microalgae and their respective toxins were low in abundance but widely present in the area, and thus might be considered in local monitoring programs to preserve seafood safety in Danish coastal waters

Dynamics of the Toxic Dinoflagellate Alexandrium pacificum in the Taiwan Strait and Its Linkages to Surrounding Populations

The dinoflagellate Alexandrium pacificum can produce paralytic shellfish toxins and is mainly distributed in the Pacific. Blooms of A. pacificum have been frequently reported in offshore areas of the East China Sea, but not along the coast. To investigate the bloom dynamics of A. pacificum and their potential origins in the Taiwan Strait, we performed intensive sampling of both water and sediments from 2017 to 2020. Ellipsoidal cysts were identified as A. pacificum and enumerated based on microscopic observation. Their abundances were quite low but there was a maximum of 9.6 cysts cm−3 in the sediment near the Minjiang River estuary in May 2020, consistent with the high cell abundance in the water column in this area. Cells of A. pacificum were examined using a quantitative polymerase chain reaction, and they appeared to be persistent in the water column across the seasons. High densities of A. pacificum (103 cells L−1) were observed near the Jiulongjiang and Minjiang River estuary in early May 2020, where high nutrients (dissolved inorganic nitrogen and phosphate), and relatively low temperatures (20–21 ◦C) were also recorded. Strains isolated from the East and South China Sea exhibited the highest division rate (0.63 and 0.93 divisions d−1) at 20 and 23 ◦C, respectively, but the strain from the Yellow Sea showed the highest division (0.40 divisions d−1) at 17–23 ◦C. Strains from the East and South China Sea shared similar toxin profiles dominated by the N-sulfocarbamoyl toxins C1/2, but the strain from the Yellow Sea predominantly produced the carbamoyl toxins GTX1/4 and no C1/2. Our results suggest that both cyst germination and persistent cells in the water column might contribute to the bloom formation in the Taiwan Strait. Our results also indicate that the East and South China Sea populations are connected genetically through similar toxin formation but separated from the Yellow Sea population geographically

Research progress in brain-targeted nasal drug delivery

The unique anatomical and physiological connections between the nasal cavity and brain provide a pathway for bypassing the blood–brain barrier to allow for direct brain-targeted drug delivery through nasal administration. There are several advantages of nasal administration compared with other routes; for example, the first-pass effect that leads to the metabolism of orally administered drugs can be bypassed, and the poor compliance associated with injections can be minimized. Nasal administration can also help maximize brain-targeted drug delivery, allowing for high pharmacological activity at lower drug dosages, thereby minimizing the likelihood of adverse effects and providing a highly promising drug delivery pathway for the treatment of central nervous system diseases. The aim of this review article was to briefly describe the physiological structures of the nasal cavity and brain, the pathways through which drugs can enter the brain through the nose, the factors affecting brain-targeted nasal drug delivery, methods to improve brain-targeted nasal drug delivery systems through the application of related biomaterials, common experimental methods used in intranasal drug delivery research, and the current limitations of such approaches, providing a solid foundation for further in-depth research on intranasal brain-targeted drug delivery systems (see Graphical Abstract)

Molecular identification and toxin analysis of Alexandrium spp. in the Beibu Gulf: first report of toxic A. tamiyavanichii in Chinese coastal waters

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Xu, Y., He, X., Li, H., Zhang, T., Lei, F., Gu, H., & Anderson, D. M. Molecular identification and toxin analysis of Alexandrium spp. in the Beibu Gulf: first report of toxic A. tamiyavanichii in Chinese coastal waters. Toxins, 13(2), (2021): 161, https://doi.org/10.3390/toxins13020161.The frequency of harmful algal blooms (HABs) has increased in China in recent years. Information about harmful dinoflagellates and paralytic shellfish toxins (PSTs) is still limited in China, especially in the Beibu Gulf, where PSTs in shellfish have exceeded food safety guidelines on multiple occasions. To explore the nature of the threat from PSTs in the region, eight Alexandrium strains were isolated from waters of the Beibu Gulf and examined using phylogenetic analyses of large subunit (LSU) rDNA, small subunit (SSU) rDNA, and internal transcribed spacer (ITS) sequences. Their toxin composition profiles were also determined using liquid chromatography-tandem mass spectrometry (LC-MS/MS). All eight strains clustered in the phylogenetic tree with A. pseudogonyaulax, A. affine, and A. tamiyavanichii from other locations, forming three well-resolved groups. The intraspecific genetic distances of the three Alexandrium species were significantly smaller than interspecific genetic distances for Alexandrium species. Beibu Gulf isolates were therefore classified as A. pseudogonyaulax, A. affine, and A. tamiyavanichii. No PSTs were identified in A. pseudogonyaulax, but low levels of gonyautoxins (GTXs) 1 to 5, and saxitoxin (STX) were detected in A. tamiyavanichii (a total of 4.60 fmol/cell). The extremely low level of toxicity is inconsistent with PST detection above regulatory levels on multiple occasions within the Beibu Gulf, suggesting that higher toxicity strains may occur in those waters, but were unsampled. Other explanations including biotransformation of PSTs in shellfish and the presence of other PST-producing algae are also suggested. Understanding the toxicity and phylogeny of Alexandrium species provides foundational data for the protection of public health in the Beibu Gulf region and the mitigation of HAB events.This research was funded by the National Natural Science Foundation of China (41976155, 41506137), the Natural Science Foundation of Guangxi Province (2020GXNSFDA297001, 2016GXNSFBA380037), the Woods Hole Center for Oceans and Human Health (National Science Foundation grant OCE-1840381 and National Institutes of Health grants NIEHS-1P01-ES028938-01), the Opening Project of Guangxi Laboratory on the Study of Coral Reefs in the South China Sea (GXLSCRSCS2019002), the Opening Foundation of Key Laboratory of Environment Change and Resources Use in Beibu Gulf Ministry of Education (Nanning Normal University), and the Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation (Nanning Normal University) (GTEU-KLOP-K1803)

Enhanced performance of Al₂O₃–SiC–C castables via in-situ formation of multi-reinforced phases by introducing surface treated composite metal powders

Al2O3–SiC–C (ASC) castables were prepared with bauxite and silicon carbide as major raw materials and introducing large amount of surface treated composite metal powders (STCMPs) as antioxidant. Their comprehensive properties were greatly improved attributed to the in situ formation of multi-reinforced phases including carbide silicon whiskers and mullite fibers in the matrix. Compared with the corresponding samples without STCMPs, the high temperature modulus of rupture of those with 6 wt% STCMPs calcined in air increased by 47.3% and with 8 wt% STCMPs calcined in reducing atmosphere increased by 220%. The retained CMOR ratio of the sample with 6 wt% STCMPs calcined in reducing atmosphere was high up to 50% after 5 cycles thermal shocks. Moreover, the oxidation index and slag erosion index of samples with 6 wt% STCMPs were decreased by 45% and 74%. This work provides a new perspective for the preparation of ASC castables with excellent high-temperature performance.</p

Size and Location Diagnosis of Rolling Bearing Faults: An Approach of Kernel Principal Component Analysis and Deep Belief Network

Diagnosing incipient faults of rotating machines is very important for reducing economic losses and avoiding accidents caused by faults. However, diagnoses of locations and sizes of incipient faults are very difficult in a noisy background. In this paper, we propose a fault diagnosis method that combines kernel principal component analysis (KPCA) and deep belief network (DBN) to detect sizes and locations of incipient faults on rolling bearings. Effective information of raw vibration signals processed by KPCA method is used as input signals of the DBN of which weights of the first RBM are initialized by contribution rates of principal components. A DBN with complex structures can be cut into a briefer network by KPCA-DBN model. That model reduces network structure and increases convergence rate. As a result, an average test accuracy by KPCA-DBN can reach 99.1% for identification of 12 labels including incipient faults and the training time is 28s which is half of that by DBN model. The average accuracy of rolling bearing location detection nearly gets to 100% and the average accuracy of fault size detection is above 99%. Compared with SVM, BP, CNN, Deep EMD-PCA (Empirical Mode Decomposition-Principal Component Analysis), CNN-SVM and DBN, it is found that training time can be shortened and detection accuracy can be improved by KPCA-DBN model. The proposed method is beneficial to realize sizes and locations detection of incipient faults online