Complete Identification Research Articles

Weld Seam Recognition and Tracking With Omnidirectional Wall-Climbing Robot for Spherical Tank Inspection

Abstract Weld seams of in-service pressure storage equipment, such as spherical tanks, require regular inspection to ensure safe operation. Wall-climbing robots can replace manual operations, increasing inspection efficiency and reducing maintenance costs. High precision and fast weld seam identification and tracking are beneficial for improving the automated navigation and spatial positioning of wall-climbing robots. This study proposes a weld seam recognition and tracking method with the omnidirectional wall-climbing robot for spherical tank inspection. Based on deep learning networks, the robot has a front-mounted camera to recognize weld seams and extract weld paths. Weld seam deviation data (drift angle and offset distance) were used in real time to provide feedback on the robot's relative position. For the robot to quickly correct deviations and track weld seams, a seam path-tracking controller based on sliding mode control was designed and simulated. Weld recognition experiments revealed that the robot can accurately recognize and extract weld paths, and the recognition time for each image was approximately 0.25 s. In the weld seam tracking experiments, the robot could successfully track longitudinal and transverse weld seams at different speeds (from 0.05 to 0.2 m/s). During the process of weld seam tracking, the robot angle error was kept within ±3 deg, and the maximum offset distance was less than ±35 mm. Field tests on a 3000-m3 spherical tank were conducted to verify the practicability and effectiveness of the weld seam tracking system. This robotic system can autonomously complete weld seam identification and tracking, which promotes the automation of spherical tank inspection and maintenance.

Prevalence of multidrug-, extensively drug-, and pandrug-resistant bacteria in clinical isolates from King Khaled Hospital, Najran, Saudi Arabia

Abstract Background Saudi Arabia faces a growing antimicrobial resistance (AMR) problem, exacerbated by the widespread use of antibiotics in clinical and agricultural settings. Despite this, AMR surveillance has been limited, particularly in regions like Najran, making this study critical for informing local and national public health strategies. Aim This study explored the prevalence of multidrug-resistant, extensively drug-resistant, and Pandrug-resistant bacteria in Najran, Saudi Arabia. Study design This is a cross-sectional study. Methods This study included 559 diverse clinical samples (urine, wound, etc.) collected from various departments in King Khaled Hospital, Saudi Arabia. The Phoenix BD instrument was used for complete bacterial identification and antibiotic sensitivity testing. Demographic and clinical data were analyzed statistically. Results Of the 559 samples, the culture positivity rates were as follows: 51% for Escherichia coli, 22% for Staphylococcus aureus, 14% for Klebsiella pneumoniae, 6% for Acinetobacter baumannii, 6% for Pseudomonas aeruginosa, and 1% for Enterococcus faecium. Majority of the cases were from male (57%), and age 50+ (59%) recorded highest cases. Participants from outpatient department (OPD) ward recorded the highest (56%) cases, while urine sample recorded the highest (49%) cases. About 84% of the isolates were multidrug‑resistance (MDR), 10% were extensively drug‑resistance (XDR), and 6% pandrug‑resistance (PDR). Our analysis showed high sensitivity to Oxazolidonone, Tetracycline, carbapenems, Lipopeptide, Aminoglycopeptide classes of antibiotics. Conclusions The study revealed a high prevalence of drug resistance, highlighting the critical importance of continued surveillance and research to mitigate the spread of antimicrobial resistance and preserve the effectiveness of existing therapies.

Dynamic Stakeholder Analysis Through Process Mapping

ABSTRACTIdentification of stakeholders and their importance is critical to the design of accountability and performance management systems. Conventional stakeholder analysis approaches provide a static view of stakeholders and overlook that accountability is a dynamic process encompassing multiple temporally separated (or distinct) stages. We approach stakeholder analysis from a process perspective to ensure a more complete identification of stakeholders and to capture the dynamic nature of stakeholder emergence, retirement, and changes in relative importance. We used a participatory action research methodology to investigate contracting services in a community health setting and employed process mapping to reveal contracting activities undertaken in sequential stages of Deming's Plan–Do–Check–Act (PDCA) cycle. Stakeholders engage at different stages with different activities of a process so that in multi‐stage processes, stakeholder analysis needs to be repeated at each stage and is specific to each stage. Our use of the PDCA is broader than traditional applications and provides a suitable framework for a more complete identification of stakeholders across the entire process while aligning well with accountability and management control notions. The contribution is an approach that not only better identifies stakeholders but also recognizes the dynamics of multi‐stage processes for stakeholder interest and influence. The recurring nature of many processes (such as contracting) implies that roles remain the same even if an organization is restructured so that process mapping will still identify roles and stakeholders. This approach can be used by other organizations to better identify stakeholders and their dynamics in the planning and delivery processes.

Screening and Identification Quality Markers for Antioxidant Activity ofTetrastigma hemsleyanumfrom Different Origins using Spectrum-effect Correlation Analysis

Background::Tetrastigma hemsleyanum (THL) is a traditional medicinal plant with various biological activities, it has been validated that several THL extracts have strong pharmacological activities. Until now, there is no complete and systematic germplasm identification and quality evaluation standard.Objective::Establishing fingerprint spectra of THL from different sources, evaluating their antioxidant activity and identifying quality markers.Methods::In this paper, establishing fingerprints and identifying quality markers through UPLC-QTOF- MS/MS. The antioxidant capacity of forty-one batches of THL from multiple regions was determined by 1,1-Diphenyl-2-picrylhydrazyl radical (DPPH), 2,2'-Azinobis-(3-ethylbenzthiazoline-6- sulphonate) (ABTS), and Ferric reducing antioxidant power (FRAP) assays.Results::The results indicated that THL methanol extracts showed good antioxidative activity and eight THL samples, including THL aerial parts, showed high antioxidative activity. Besides, Ultra Performance Liquid Chromatography (UPLC) fingerprints of THL from different places were established and chromatographic peaks probably correlated with antioxidant capacity were screened by principal component analysis (PCA) and partial least square regression (PLS) analysis.Conclusion::The chemical constituents of these peaks were identified as possible quality markers for THL quality evaluation. In this study, twelve effective substances were preliminarily determined, such as isovitexin, L-epicatechin, procyanidin B, sitosterol, etc.

Direct Identification of the Continuous Relaxation Time and Frequency Spectra of Viscoelastic Materials

Relaxation time and frequency spectra are not directly available by measurement. To determine them, an ill-posed inverse problem must be solved based on relaxation stress or oscillatory shear relaxation data. Therefore, the quality of spectra models has only been assessed indirectly by examining the fit of the experiment data to the relaxation modulus or dynamic moduli models. As the measures of data fitting, the mean sum of the moduli square errors were usually used, the minimization of which was an essential step of the identification algorithms. The aim of this paper was to determine a relaxation spectrum model that best approximates the real unknown spectrum in a direct manner. It was assumed that discrete-time noise-corrupted measurements of a relaxation modulus obtained in the stress relaxation experiment are available for identification. A modified relaxation frequency spectrum was defined as a quotient of the real relaxation spectrum and relaxation frequency and expanded into a series of linearly independent exponential functions that are known to constitute a basis of the space of square-integrable functions. The spectrum model, given by a finite series of these basis functions, was assumed. An integral-square error between the real unknown modified spectrum and the spectrum model was taken as a measure of the model quality. This index was proved to be expressed in terms of the measurable relaxation modulus at uniquely defined sampling instants. Next, an empirical identification index was introduced in which the values of the real relaxation modulus are replaced by their noisy measurements. The identification consists of determining the spectrum model that minimizes this empirical index. Tikhonov regularization was applied to guarantee model smoothness and noise robustness. A simple analytical formula was derived to calculate the optimal model parameters and expressed in terms of the singular value decomposition. A complete identification algorithm was developed. The analysis of the model smoothness and model accuracy for noisy measurements was carried out. The equivalence of the direct identification of the relaxation frequency and time spectra has been demonstrated when the time spectrum is modeled by a series of functions given by the product of the relaxation frequency and its exponential function. The direct identification concept can be applied to both viscoelastic fluids and solids; however, some limitations to its applicability have been pointed out. Numerical studies have shown that the proposed identification algorithm can be successfully used to identify Gaussian-like and Kohlrausch–Williams–Watt relaxation spectra. The applicability of this approach to determining other commonly used classes of relaxation spectra was also examined.

Distinguishing Artifactual Fatty Acid Dimers from Fatty Acid Esters of Hydroxy Fatty Acids in Untargeted LC-MS Pipelines.

Untargeted metabolomics is a powerful profiling tool for the discovery of possible biomarkers of disease onset and progression. Analytical pipelines applying liquid chromatography (LC) and mass spectrometry (MS)-based methods are widely used to survey a broad range of metabolites within various metabolic pathways, including organic acids, amino acids, nucleosides, and lipids. Accurate and complete identification of putative metabolites is an ongoing challenge in untargeted metabolomics studies. Highly sensitive instrumentation can result in the detection of adduct and fragment ions that form reproducibly and contain identifiable ions that are difficult to distinguish from metabolic pathway intermediates, which may result in false-positive identification. At concentrations as low as 10μM, free fatty acids have been found to form homo- and heterodimers in untargeted metabolomics pipelines that resemble the lipid class fatty acid esters of hydroxy fatty acids (FAHFAs), resulting in misidentification. This chapter details a protocol for LC-MS-based untargeted metabolomics using hydrophilic interaction chromatography (HILIC) that specifically aids in distinguishing artifactual fatty acid dimers from endogenous FAHFAs.

Blade tip timing signals parameters identification based on Displacement Offset Decreased and Compressed Sensing

High-speed rotating blade vibration monitoring is of great significance for the safe operation of turbomachinery. Blade Tip Timing (BTT) is considered a promising technology in the field of blade vibration monitoring. The BTT signal analysis has the following problem, the displacement offset was caused by speed variation which affected the accuracy of the blade vibration parameter identification. Owing to the under-sampled characteristics of the BTT signals and multiple sensor data are required to identify the parameters. The accurate extraction of blade vibration characteristics is challenging. Thus, a vibration analysis method is proposed based on Displacement Offset Decreased and Compressed Sensing (DOD-CS). Firstly, the BTT signal pairwise is subtracted to reduce the impact of the displacement offset, and based on the subtractive results, a basis function is constructed to rebuild the dictionary matrix of the compressed sensing method. Then, we solved the signal sparse representation equation and obtained the spectrum estimation result, that is, the structure vibration parameters. The analysis of simulation data shows that the parameter identification accuracy of the DOD-CS method is higher than that of the OMP-CS (Orthogonal Matching Pursuit and Compressed Sensing) method, and the identification errors of frequency and amplitude are within 1% and 5%, respectively. The experimental results confirm the feasibility of the proposed method in identifying vibration parameters. Compared with existing methods, the innovation of the proposed method is that it eliminates the influence of displacement offset on the accuracy of parameter identification. For under-sampled signals, only two sensor data information are needed to complete spectrum estimation and parameter identification.

GlyCombo Enables Rapid, Complete Glycan Composition Identification across Diverse Glycomic Sample Types.

Glycans are sugar-based polymers found to modify biomolecules, including lipids and proteins, as well as occur unconjugated as free polysaccharides. Due to their ubiquitous cellular presentation, glycans mediate crucial biological processes and are frequently sought after as biomarkers for a wide range of diseases. Identification of glycans present in samples acquired with mass spectrometry (MS) is a cornerstone of glycomics research; thus, the ability to rapidly identify glycans in each acquisition is integral to glycomics analysis pipelines. Here we introduce GlyCombo (https://github.com/Protea-Glycosciences/GlyCombo), an open-source, freely available software tool designed to rapidly assign monosaccharide combinations to glycan precursor masses including those subjected to MS2 in LC-MS/MS experiments. GlyCombo was evaluated across six diverse data sets, demonstrating MS vendor, derivatization, and glycan-type neutrality. Compositional assignments using GlyCombo are shown to be faster than the current predominant approach, GlycoMod, a closed-source web application. Two unique features of GlyCombo, multiple adduct search and off-by-one error anticipation, reduced unassigned MS2 scans in a benchmark data set by 40%. Finally, the comprehensiveness of glycan feature identification is exhibited in Skyline, a software that requires predefined transitions that are derived from GlyCombo output files.

Systematic synthesis and identification of monolignol pathway metabolites.

Monolignol serves as the building blocks to constitute lignin, the second abundant polymer on Earth. Despite two decades of diligent efforts, complete identification of all metabolites in the currently proposed monolignol biosynthesis pathway has proven elusive. This limitation also hampers their potential application. One of the primary obstacles is the challenge of assembling a collection of all molecules, because many are commercially unavailable or prohibitively costly. In this study, we established systematic pipelines to synthesize all 24 molecules through the conversions between functional groups on a core structure followed by the application to other core structures. We successfully identified all of them in Populus trichocarpa and Eucalyptus grandis, two representative species respectively from malpighiales and myrtales in angiosperms. Knowledge about monolignol metabolite chemosynthesis and identification will form the foundation for future studies.

Dynamics Parameter Identification of Articulated Robot

Dynamics parameter identification in the establishment of a multiple degree-of-freedom (DOF) robot’s dynamics model poses significant challenges. This study employs a non-symbolic numerical method to establish a dynamics model based on the Newton–Euler formula and then derives a proper dynamics model through decoupling. Initially, a minimum inertial parameter set is acquired by using QR decomposition, with the inclusion of a friction model in the robot dynamics model. Subsequently, the least squares method is employed to solve for the minimum inertial parameters, forming the basis for a comprehensive robot dynamics parameter identification system. Then, after the optimization of the genetic algorithm, the Fourier series trajectory function is used to derive the trajectory function for parameter identification. Validation of the robot’s dynamics parameter identification is performed through simulation and experimentation on a 6-DOF robot, leading to a precise identification value of the robot’s inertial parameters. Furthermore, two methods are employed to verify the inertia parameters, with analysis of experimental errors demonstrating the effectiveness of the robot dynamics parameter identification method. Overall, the effectiveness of the entire calibration system is verified by experiments, which can provide valuable insights for practical engineering applications, and a complete and effective robot dynamics parameter identification scheme for a 6-DOF robot is established and improved.

MALDI-TOF mass spectrometry from nucleic acid: development and evaluation of a novel platform for identification of mycobacteria and detection of genetic markers of resistance.

Complete identification methods are critical for evaluating nontuberculous mycobacteria (NTM). Here, we describe a novel diagnostic method for identification of eight NTM, Mycobacterium tuberculosis complex, and three drug resistance markers using PCR/matrix-assisted, laser-desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) from cultured organisms. With this technology, a multiplex end-point PCR is performed for targets of interest. Detection probes that are extended in the presence of a target are added. The extended probes have greater molecular weight and can be detected by MALDI-TOF MS. An AFB Primary Panel was designed to differentiate Mycobacterium avium; Mycobacterium intracellulare subsp. chimaera; Mycobacterium avium complex (other); Mycobacterium abscessus subsp. abscessus, bolletii, and massiliense; Mycobacterium kansasii, and M. tuberculosis complex. This design should cover 90% (3,483/3,691) of mycobacteria seen onsite. A development set of unblinded isolates (n = 217) was used to develop PCR primers, detection probes, and probe barcodes. It demonstrated 99.1% (215/217) agreement with reference methods. An evaluation set using blinded isolates (n = 320) showed an overall sensitivity of 94.3% (range by target: 90.0-100%). Overall specificity from negative media, non-target mycobacteria, and bacteria was 99.1% (108/109; range by target: 94.4-100%). Three drug resistance markers erm (41), rrl, and rrs demonstrated 100%, 91%, and 100% sensitivity, respectively, and >99% specificity. Limit of detection per target ranged from 2.2 × 103 to 9.9 × 106 CFU/mL. The AFB Primary Panel allows for mycobacterial speciation, subspeciation, and resistance mutation detection, which is essential for diagnosis, appropriate therapy, identifying outbreaks, and managing treatment-refractory disease. It can perform with high-throughput and high specificity and sensitivity from isolates.IMPORTANCEEven closely related mycobacteria can have unique treatment patterns, but differentiating these organisms is a challenge. Here, we tested an innovative platform that combines two commonly used technologies and creates something new: matrix-assisted, laser-desorption ionization time-of flight mass spectrometry was performed on PCR amplicons instead of on proteins. This created a robust system with the advantages of PCR (high discriminatory power, high throughput, detection of resistance) with the advantages of mass spectrometry (more targets, lower operational cost) in order to identify closely related mycobacterial organisms.

Heralded high-efficiency entanglement concentration of cluster states for photon systems with linear optics via time-delay effect

Entanglement concentration stands as a pivotal technique to safeguard against degraded fidelity in long-distance quantum communication. In this manuscript, propose ultra-efficient entanglement concentration protocols (ECPs) tailored for less-entangled two-photon cluster states and four-photon cluster states with two unknown parameters, leveraging simple linear optical elements and acute single-photon detectors. Additionally, ancillary photons, post-selection techniques, or photon-number-resolving detectors are unnecessary for complete identification of the parity-check measurement. By coordinating auxiliary time degrees of freedom and implementing multiple recycling conditions, the success of two ECPs can be heralded by detection signatures without compromising the incident qubits, thereby allowing their efficiencies to be close to 0.75, in principle. The combination of heralded detection and basic linear optical elements renders our practical ECPs accessible for experimental exploration with current technology.

Analysis and identification of gas-liquid two-phase flow pattern based on multivariate multi-scale dispersion entropy and interconnected dispersion pattern complex network

Gas-liquid two-phase flow is polymorphic and unstable. The investigation of the flow behavior of two-phase flow is vital for the application of gas-liquid transport in ocean engineering areas. We propose an analytical framework that combines multivariate multi-scale dispersion entropy (mvMDE) and interconnected dispersion pattern complex networks (IDPCN) for flow patterns. The resistance sensor array is used to capture the two-phase flow fluctuation signals in the riser, and the dimensionally reduced time series are nonlinearly mapped into a multivariate symbolic sequence. The mvMDE of the multivariate symbolic sequence is computed to measure the complexity of the flow pattern signals at the level of amplitude variation. In addition, a new multis-cale complex network based on the symbolic sequence is proposed to study the pseudo spatial coupling behavior of flow patterns. The evolution of the flow pattern from bubble to churn flow is quantitatively characterized using the mean value of the complex network indices in the optimal scale range. Finally, we construct the joint plane of mvMDE and two network indices to complete flow pattern identification. The research results show that the framework can effectively fuse multi-channel flow pattern information at different time scales to reveal the evolution mechanism of gas-liquid two-phase flow.

Multi-stage damage identification method for PC structures based on machine learning driven by piezoelectric singular feature

Efficient and accurate damage identification methods are great significant for ensuring the structural safety. This study proposes a multi-stage damage identification method for prestressed concrete (PC) structures based on machine learning driven by piezoelectric singular feature to improve the identification accuracy. This method extracts the singular value vector in the piezoelectric signal as the damage feature by multi-layer wavelet packet transform and singular value decomposition. The singular value vectors are put into the improved back propagation neural network (BPNN) model to achieve complete damage identification. This method is verified by analyzing the piezoelectric signals collected by PZT patches based on the static load failure test. The results show that the amplitude and energy of the signal gradually decreases and the frequency subject gradually develops from high frequency to low frequency with the development of damage. The extracted singular values effectively retain the main information of the piezoelectric signal as damage feature. The peak singular value decreases from fast to slow with the development of damage, which finally tends to be stable. The improved BPNN model has strong flexibility and adaptability, which enhances its ability of damage identification. The proposed method can achieve high-precision damage identification using piezoelectric signals, which has great application potential in the field of damage identification for PC structures.

Complete Chromosome Wise Identification of SSRs in the Two Published Chicken Genome Assemblies

Background: Microsatellites are short repeat motifs consisting 1-6 base pair (bp) and have a high degree of length polymorphism and are useful to study the genetic diversity. In Chicken, no micro satellite markers were demarcated to different chromosomes, viz., 29, 34, 35, 36, 37, 38 and 39 in the genome. In the present study, we carried out chromosome-wise identification of SSRs that will be of great use in diversity and gene mapping studies in chicken. Methods: The perl script of MISA tool was used to screen the polymorphic microsatellites with different thresholds level. Result: We identified a total of 397877 SSRs from the latest chicken genome assembly (GRCg7b), of which mononucleotides, dinucleotides, trinucleotides, tetranucleotides, pentanucleotides and hexanucleotides composed of 307453 (77.27%), 40991 (10.30%), 23059 (5.79%), 16723 (4.20%), 8127 (2.04%) and 1524 (0.38%), respectively.

Identification of dynamic coefficient matrix for drilling process simulations from measured tool geometry, axial force and torque

This paper aims to quantitatively analyze the relationship between forces acting on the tool tip and tool movement during drilling operations. The study encompasses axial and lateral vibrations superimposed on the nominal tool movement, arising from rigid body motion (rotational and axial velocities). Specifically, only forces attributed to the cutting process are considered, excluding considerations of indentation forces around the chisel edge. The research adopts a generalized approach, spanning from tool measurements to establishing the force model. The investigation involves measuring cutting forces and correlating them with the varying rake and inclination angles of the drill’s cutting edges. An analytical model is proposed to describe the distribution of all local force components along drill edges, considering the evolution of forces and geometry. The dynamic coefficient matrix is evaluated by using the identified cutting coefficient and tool geometry. Validation of the proposed methodology is demonstrated through drilling experiments on Ti6Al4V alloy, utilizing three solid carbide drills with distinct geometries. The proposed procedure allows complete identification of the dynamic characteristics from the measurements taken at the entrance stage of hole drilling operation. Moreover, the influence of tool geometry on cutting coefficients and dynamic coefficient matrices are discussed.

Root rot of spinach caused by Pythium myriotylum and P. aphanidermatum in Taiwan.

Spinach (Spinacia oleracea) is a commonly used green vegetable. During September and October in both 2022 and 2023, a vegetable nursery company located among paddy rice fields in Taichung City, Taiwan, reported significant failures in spinach seedling production in net-houses with mean outdoor temperatures of 28.7℃. Abnormal growth was observed in approximately 30% of the spinach seedlings in each batch (n = 2,000 to 3,000), with aboveground tissues showing stunting, yellowing, and wilt, and underground tissues displaying root rot. The symptoms resembled the spinach damping-off documented in Taiwan in extension articles but which lacked complete pathogen identification. A total of 110 plants from two batches were used for pathogen isolation by placing roots on water agar incubated at 25℃ or were examined for the presence of oospores in diseased roots. Eighty-one percent of these plants were associated with Pythium. Nine Pythium isolates were used in subsequent analyses. Genomic DNA from these isolates was subjected to amplification of ITS, β-tubulin gene (TUB2), and cytochrome C oxidase subunit Ⅱ (COXII) gene with primer pairs ITS1 / ITS4, BT5 / BT6, and FM58 / FM66 (Villa et al. 2006). Sequences of ITS (PP209187-PP209195), TUB2 (PP212864-PP212872), and COXII (PP212855-PP212863) were deposited in GenBank. Four isolates (sp01, sp02, sp03, and sp04) were 100% identical to the neotype strain (CBS 118.80) of Pythium aphanidermatum (Edson) Fitzp. for the ITS (761 bp), TUB2 (583 bp), and COXII (547 bp). Five isolates (2sp, 3sp, ND2-4sp, D3-4sp, and ND3-3sp) were 99.87%, 100%, and 99% identical to the reference strain (CBS 254.70) of Pythium myriotylum Drechsler for the ITS (762 bp), TUB2 (602 bp), and COXII (556 bp), respectively. Phylogenetic analysis of Pythium isolates inferred from concatenated sequences of the three genes (LéVesque and De Cock 2004; Villa et al. 2006) revealed that the same four isolates grouped with the neotype strain of P. aphanidermatum, and the five isolates clustered with the reference strain of P. myriotylum, each with a 100% bootstrap support. Morphological features of isolates ND3-3sp and sp01 were used for identification. Isolate ND3-3sp produced inflated lobulate sporangia and aplerotic and smooth oospores (16.3 to 25.1 um; n = 30) attached with three to five antheridia, consistent with identification as P. myriotylum. Isolate sp01 produced inflated lobulate sporangia and aplerotic and smooth oospores (17.0 to 24.0 um; n= 30) attached with a single intercalary antheridium, agreeing with the morphology of P. aphanidermatum (Van der Plaats-Niterink 1981). To investigate the pathogenicity of the nine Pythium isolates on spinach, 20 mycelial agar discs (4 mm in diameter) from a 2-day-old V8 culture of each isolate were used to induce sporangia and zoospores in 20 ml sterilized water at 25℃ with a 12 h light / dark regime. A 1.5 ml zoospore suspension (6 × 103 zoospores / ml) was dropped into BVB growth substrate of two spinach seedlings in 2-week-old at 25℃ with 12 h light / dark regime, resulting in symptoms resembling those observed in commercial nurseries at 7 days post-inoculation (dpi). Each Pythium isolate inoculated 20 seedlings in 10 cells of a planting tray. At 14 dpi, disease incidences were 95 to 100% for P. myriotylum isolates and 60 to 85% for P. aphanidermatum isolates, while control plants treated with water showed no symptoms. Re-isolated pathogens from the inoculated plants were morphologically identical to the inoculated isolates, completing Koch's postulates. Results of the pathogenicity assay, along with molecular and morphological identification, conclude that the root rot of spinach was caused by P. myriotylum and P. aphanidermatum. The two oomycetes were not formally documented to cause spinach diseases in Taiwan. Although P. myriotylum has been isolated from spinach (Wang et al. 2003), its pathogenicity to spinach was not documented worldwide. Root rot of spinach caused by P. aphanidermatum has been reported in the United States (Bates and Stanghellini 1984), Korea (Cho and Shin 2004), and Italy (Garibaldi et al. 2015). These pathogens thrive in humid and hot weather (Littrell and McCarter, 1970). Producing spinach in cooler weather or in a temperature-controlled environment may help prevent severe occurrence of the disease.

Evaluation of Left Truncation and Censoring When Changing the Use of the International Classification of Diseases Eighth Revision Codes to Tenth Revision Codes in the Danish National Patient Registry.

In the Danish National Patient Registry (DNPR), covering all Danish hospitals and widely used in research, diseases have been recorded using International Classification of Diseases (ICD) codes, transitioning from the Eighth to the Tenth revision in 1994. Uncertainty exists regarding whether including ICD-8 codes alongside ICD-10 is needed for complete disease identification. We assessed the extent of left-truncation and left-censoring in the DNPR arising from omitting ICD-8 codes. We sampled 500,000 Danes ≥40 years of age in 1995, 2010, and 2018. From the DNPR, we identified cardiovascular, endocrine, gastrointestinal, neurological, pulmonary, rheumatic, and urogenital diseases as well as fractures. We obtained the number of people with a disease recorded with ICD-8 codes only (ie, the ICD-8 record would be left-truncated by not using ICD-8 codes), ICD-8 plus ICD-10 codes (ie, the ICD-8 record would be left-censored by not using ICD-8 codes), and ICD-10 codes only. For each ICD group, we calculated the proportion of people with the disease relative to the total sample (ie, 500,000 people) and the total number of people with the disease across all ICD groups. Overall, the left-truncation issue decreased over the years. Relative to all people with a disease, the left-truncated proportion was for example 59% in 1995 and <2% in 2018 for diabetes mellitus; 93% in 1995, and 54% in 2018 for appendicitis. The left-truncation issue increased with age group for most diseases. The proportion of disease records left-censored by not using ICD-8 codes was generally low but highest for chronic diseases. The left-truncation issue diminished over sample years, particularly for chronic diseases, yet remained rather high for selected surgical diseases. The left-truncation issue increased with age group for most diseases. Left-censoring was overall a minor issue that primarily concerned chronic diseases.

STUDY ON ANATOMICAL CHARATERIZATION OF MICROCOCCUS PANICULATA L

Micrococcus paniculata L., one of the important medicinal plants, commonly known as Cherikkotta, Kotta, Kottakka or Pottanga, of plant family Tiliaceae and are generally seen at the steep forested regions and also in scared grooves. The plant parts were utilized for the treatment of variety of diseases or conditions, including dysmenorrhea, paratyphoid, bone fractures, jaundice, kidney stones, dyspepsia, heat stroke, cold, fever, diarrhoea, hepatitis B, ingestion, and anthelmintic medication. It is widely distributed along the Western Ghats of India. Eventually, complete identification and authentication of plant material is needed to avoid confusion of species by non-taxonomist. Anatomical study supplement classical methods of identification. Specimen were examined by morphological and anatomical characteristics. Leaf and petiole anatomical profiling of this species Micrococcus paniculata occurring in of Kerala was investigated in this study. The study aims to search for the stable features marking out Micrococcus species. The species were distinguished based on the anatomical difference in the vascular bundles in midrib and petiole, palisade layer and type of stomata. The anatomical features of stem might be very useful for the identification of this plant species. Through this anatomical study, we concluded that this species has some unique features to its environmental habitat.

Un « cheval ombrageux »

&lt;p&gt;The article aims to grasp the role of the symbolic code in the scaffolding of the narrative unity of Le Rouge et le Noir, through the theme of the horse. Although the symbolic dimension seems excluded from Stendhal's poetics (Racine &amp;amp; Shakspeare), and many of its commentators criticize it for « a writing without images », equestrian themes and symbols nevertheless play a central role in as elements guaranteeing the coherence of the narrative discourse. The article first presents the symbolic potentialities underlying the Stendhalian poetics of the novel. Then, the topos of the horse is presented both as a theme and as a symbol in the narrative structure of the Le Rouge et le Noir. Finally, the use of symbolism in Le Rouge et le Noir is seen as a tool to confess the fictional artifice itself, so as to compromise the "perfect illusion" of the fiction and, therefore, prevent any complete identification of the readership with the figure of Julien.&lt;/p&gt;