Individual Spots Research Articles

Individual decision styles as predictors for bias susceptibility and bias blind spots in managerial decisions

Purpose This paper aims to managerial decision styles, following the General Decision-Making Style Inventory, as potential predictors of individual bias awareness and bias blind spots, with a focus on the rational decision style. Design/methodology/approach The research is based on a survey of 50°C-1 level managers within Forbes 2000 companies. It explores their decision styles and their assessments of their own and others’ decision behavior. Findings The results show that the awareness of one’s own susceptibility to biases and bias blind spots is highly dependent on an individual’s (self-declared) decision style and type of cognitive bias; decision-makers with a strong tendency toward a rational or spontaneous decision style see themselves as less vulnerable to cognitive biases but also show a much stronger bias blind spot than those with a tendency toward other decision styles. Meanwhile, decision-makers with a strong tendency toward an intuitive decision style tend to recognize their own vulnerability to cognitive biases and even show a negative blind spot, thus seeing themselves as more affected by cognitive biases than others. Originality/value To date, decision styles have not been used as a lens through which to view susceptibility to cognitive biases and bias blind spots in managerial decision-making. As demonstrated in this article, decision styles can serve as predictors of individual awareness and susceptibility to cognitive biases and bias blind spots for managers.

Machinability analysis of Albromet W130 copper alloy by WEDM

The unconventional wire electrical discharge machining (WEDM) technology represents a vital manufacturing technology in different industrial branches, such as aviation, military, automotive or energy industry. The WEDM energy demand is considerable and it is, therefore, desirable to reduce the machining time by optimising the machining parameters. In the study, the chosen parameters were Pulse off time, Gap voltage, Discharge current, Pulse on time, and Wire feed. Another factor we investigated in our Box-Behnken design of the experiment was the workpiece thickness. The cutting speed, topography, and surface morphology were analysed in the samples produced for the design of the experiment. This investigation was carried out using electron microscopy. The chemical composition of individual spots was analysed as well. The samples were found not to have significant differences in the appearance of craters on the edge and in the centre. Similarly, there was no significant difference observed between thicknesses and different parameter settings. The surfaces also show a large number of small bubbles. There were, however, no cracks or other defects found, even in the cross-sections of all samples.

First Report of Powdery Mildew on Cardamine violifolia in China.

Cardamine violifolia, also called Cardamine hupingshanensis, is an economically important medicinal plant renowned for accumulating selenium (Guo et al., 2022). Selenium is an essential trace element with anti-oxidant, anti-inflammatory, anti-cancer, and immune regulatory functions. In July 2023, an outbreak of powdery mildew was detected, infecting the leaves of numerous C. violifolia plants in Enshi (30°11'5.27''N; 109°48'48.45''E), Hubei Province, China. This disease caused severe damage to plant leaves and stems, starting as individual spots and merging into a large mold that covers the entire leaf. It affected nearly 25% all C. violifolia plants, resulting in significant yield loss, disruption of normal metabolism, and premature aging. The lower leaf blades and underside of the leaves were particularly vulnerable. The affected leaves were collected and subjected to morphological diagnostic analysis (Mori et al., 2000) (Fig. S1). The powdery mildew species aggressively spread throughout the leaves, pedicels, and pods, persisting until present and often covering the entire surface. The conidiophores were upright, cylindrical, composed of 3 to 4 cells, and measured 92.3 ± 12.9 × 9.2 ± 0.6 μm (n = 30). Conidial pedicels had 21.6 ± 3.4 μm (n = 50) long cylindrical podocytes. The monoconidia were columnar or barrel-columnar, 30.60-55.59 × 9.11-20.00 μm in size. Conidia lacked an obvious cellulose body. The bud tubes formed from the end of conidia, and papillary appressoria developed on the epiphytic mycelia. ITS region sequences were amplified using the specific powdery mildew universal primers ITS1 (5'-TCCGTAGGTGAACCTGCGG-3'), PM6 (5'-GYCRCYCTGTCGCGAG-3') for partial sequences of 18S and 28S ribosomal DNA genes (Takamatsu et al., 2001). The sequence was deposited in the GenBank under the accession number OR506156 and aligned with available sequences on NCBI, which were 99.2%(528/532) identical to the E. cruciferarum (MT309701, MF192845, and KY660929) sequences (Fig. S2). The ITS sequence from GenBank was used to conduct maximum likelihood phylogenetic analysis using MEGA 11.0. The analysis results showed both the strain and E. cruciferarum clustered on the same branch. To confirm Koch's postulates, pathogenicity testing was carried out using an illuminating incubator. Infected leaves were attached to healthy leaves of C. violifolia seedlings (n=8). All the plants were incubated under 25℃ and >80% relative humidity. After one month, all inoculated plants presented the same symptoms as those initially observed in the field. Morphological and molecular analysis confirmed the isolated fungi's identity as the same pathogen. Therefore, C. violifolia is a suitable host for E. cruciferarum in China. The growers must be informed of these findings to prevent serious economic losses caused by this pathogenic white powder and to prepare for proper management practices. To our knowledge, this is the first report of E. cruciferarum infecting C. violifolia in China.

Lightweight U-Net-Based Method for Estimating the Severity of Wheat Fusarium Head Blight

Wheat Fusarium head blight is one of the major diseases affecting the yield and quality of wheat. Accurate and rapid estimation of disease severity is crucial for implementing disease-resistant breeding and scientific management strategies. Traditional methods for estimating disease severity are complex and inefficient, often failing to provide accurate assessments under field conditions. Therefore, this paper proposes a method using a lightweight U-Net model for segmenting wheat spike disease spots to estimate disease severity. Firstly, the model employs MobileNetv3 as its backbone for feature extraction, significantly reducing the number of parameters and computational demand, thus enhancing segmentation efficiency. Secondly, the backbone network has been augmented with a lightweight Coordinate Attention (CA) module, which integrates lesion position information through channel attention and aggregates features across two spatial dimensions. This allows the model to capture long-range feature correlations and maintain positional information, effectively enhancing the segmentation of wheat spike disease spots while ensuring the model’s lightweight and efficient characteristics. Lastly, depthwise separable convolutions have been introduced in the decoder in place of standard convolutions, further reducing the model’s parameter count while maintaining performance. Experimental results show that the model’s segmentation Mean Intersection over Union (MIoU) reached 88.87%, surpassing the U-Net model by 3.49 percentage points, with a total parameter count of only 4.52 M, one-sixth of the original model. The improved model demonstrates its capability to segment individual wheat spike disease spots under field conditions and estimate the severity of infestation, providing technical support for disease identification research.

Combined optimization of spot positions and weights for better FLASH proton therapy

Objective. In Intensity Modulated Proton Therapy (IMPT), the weights of individual pencil-beams or spots are optimized to fulfil dosimetric constraints. Theses spots are usually located on a regular lattice and their positions are fixed during optimization. In many cases, the range of spot weights may however be limited, leading sometimes to sub-optimal plan quality. An emblematic use case is the delivery of a plan at ultra-high dose rate (FLASH-RT), for which the spot weights are typically constrained to high values. Approach. To improve further the quality of IMPT FLASH plans, we propose here a novel algorithm to optimize both the spot weights and positions directly based on the objectives defined by the treatment planner. Main results. For all cases considered, optimizing the spot positions lead to an enhanced dosimetric score, while maintaining a high dose rate. Significance. Overall, this approach resulted in a substantial plan quality improvement compared to optimizing only the spot weights, and in a similar execution time.

SpotSweeper: spatially-aware quality control for spatial transcriptomics.

Quality control (QC) is a crucial step to ensure the reliability and accuracy of the data obtained from RNA sequencing experiments, including spatially-resolved transcriptomics (SRT). Existing QC approaches for SRT that have been adopted from single-nucleus RNA sequencing (snRNA-seq) methods are confounded by spatial biology and are inappropriate for SRT data. In addition, no methods currently exist for identifying histological tissue artifacts unique to SRT. Here, we introduce SpotSweeper, spatially-aware QC methods for identifying local outliers and regional artifacts in SRT. SpotSweeper evaluates the quality of individual spots relative to their local neighborhood, thus minimizing bias due to biological heterogeneity, and uses multiscale methods to detect regional artifacts. Using SpotSweeper on publicly available data, we identified a consistent set of Visium barcodes/spots as systematically low quality and demonstrate that SpotSweeper accurately identifies two distinct types of regional artifacts, resulting in improved downstream clustering and marker gene detection for spatial domains.

Two-Dimensional Thin-Layer Chromatography as an Accessible, Low-Cost Tool for Lipid-Class Profile Screening

The interest in lipid composition profiling is significantly increasing as research reveals the immense importance of lipids in medicine, plant science, food and agriculture. However, lipidomic analysis requires high-end specialty equipment. We used two-dimensional thin-layer chromatography (2D-TLC) as a readily available, low-cost tool for basic lipidomic profiling of lipid classes in algal samples in the models Chlamydomonas reinhardtii, Auxenochlorella protothecoides, and Euglena gracilis, validating lipid class identification using an LC-MS/MS analysis. Algal lipid extracts were separated on a 2D-TLC plate, and TLC analysis was followed by scraping individual TLC spots off the plate, and a subsequent liquid chromatography separation and tandem mass spectrometry (LC-MS/MS) analysis. For comparison, crude lipid extracts were also injected directly to the LC-MS/MS system. Lipid class annotation was achieved by a combination of accurate mass, retention time information, neutral loss and fragment ion analysis by MS2Analyzer, and by matching spectra to LipidBlast MS/MS library. Overall, we were able to identify 15 lipid classes, and to adequately profile the lipid classes in all three organisms. This TLC method is thus suggested as an accessible tool for lipid class profiling of algal, plant, and food lipids, alike, when a rapid and simple analysis is required, e.g., for screening purposes.

Abstract 6226: Identifying nested spatial units as a conserved organizing principle of the spatial tumor microenvironment

Abstract Heterogeneity of therapeutic response amongst cancer patients has a profound impact on cancer-related mortality. It has been widely hypothesized that diversity in clinical outcomes is driven by variability in tumor biology at scales ranging from inter-patient to inter-cellular. Indeed, the advent of technologies describing the tumor microenvironment (TME) at cellular resolution has demonstrated that TME organization is heterogeneous with respect to intra-tumor spatial location, body tumor location (primary vs metastatic), patient, and tumor type. However, the organizing principles that govern TME heterogeneity remain unclear. Without such organizing principles, it remains an arduous task to link descriptions of tumor biology heterogeneity to clinical outcomes in a mechanistically explainable manner. Through the application of network statistical inference models to spatial transcriptomic data, we have identified that nested spatial units (NSUs) are a core organizing principle of the TME. We find that NSUs are widely conserved across 96 patient biopsies of 14 distinct tumor types and 3 body locations (primary, abdominal metastases, brain metastases). Moreover, NSUs represent a transferrable organizing blueprint that allows for the spatial location of individual spots (5-50 cells) in a tumor biopsy to be predicted by the NSUs of a secondary, unrelated biopsy (Pearson correlation of spot-spot distance: 0.04 - 0.71, median 0.25). By using NSUs as the organizing unit of comparison, we identify variation in gene expression, biological pathways, and multicellular structures occurring across tumors in a distance-dependent manner. In summary, NSUs provide a foundation for the comparative analysis of tumor spatial biology and a path by which spatial biology can be mechanistically linked to patient outcomes. Citation Format: Vivek Behera, Hannah Giba, Benjamin A. Doran, Justin P. Kline, Arjun S. Raman. Identifying nested spatial units as a conserved organizing principle of the spatial tumor microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6226.

Modeling of the Combined Effect of the Surface Roughness and Coatings in Contact Interaction

The model of indentation of a spherical punch with a rough surface into a thin elastic layer lying on an elastic half-space has been developed. A numerical-analytical solution is suggested based on the two-scales approach. At macroscale, the integral equation of the second kind is reduced to calculate the nominal contact characteristics, taking into account the surface layer thickness and its mechanical characteristics, as well as additional compliance due to surface roughness calculated from the microscale analysis. The influence of the punch roughness and the surface layer mechanical and geometrical characteristics on the nominal contact pressure distribution, on the nominal contact area and the indentation depth, as well as on the real contact area and pressures at the individual contact spots, is analyzed. The developed contact model can be used to analyze the indentation of the punch into the layered elastic base, taking into account the roughness of the punch surface, and can also be used to give a complete analysis of the roughness effect on the contact process at both scale levels. The results can be used to control the indentation of the rough-coated bodies.

Radio Continuum and Water Maser Observations of the High-mass Protostar IRAS 19035+0641 A

We present Very Large Array 1.3 cm continuum and 22.2 GHz H2O maser observations of the high-mass protostellar object IRAS 19035+0641 A. Our observations unveil an elongated bipolar 1.3 cm continuum structure at scales ≲500 au, which, together with a rising in-band spectral index, strongly suggests that the radio emission toward IRAS 19035+0641 A arises from an ionized jet. In addition, eight individual water maser spots well aligned with the jet axis were identified. The Stokes V spectrum of the brightest H2O maser line (∼100 Jy) shows a possible Zeeman splitting and is well represented by the derivatives of two Gaussian components fitted to the Stokes I profile. The measured B los are 123 (±27) and 156 (±8) mG, translating to a preshock magnetic field of ≈7 mG. Subsequent observations to confirm the Zeeman splitting showed intense variability in all the water maser spots, with the brightest maser completely disappearing. The observed variability in a 1 yr timescale could be the result of an accretion event. These findings strengthen our interpretation of IRAS 19035+0641 A as a high-mass protostar in an early accretion/outflow evolutionary phase.

First Report of Pseudocercospora oenotherae Causing Leaf Spot in Rhinacanthus nasutus in China

Rhinacanthus nasutus (L.) Kurz is a traditional Chinese medicine in China. In August 2022, leaf spots were observed on R. nasutus in a Chinese herbal garden in Zhanjiang, Guangdong Province, China (21°17′30″N, 110°18′25″E). Disease incidence was 90% (n = 100 investigated plants from about 800 plants). The yellow spots were round, gray in the center and scattered on the leaves. The coalescence of the individual spot eventually led to leaf wilt. Ten symptomatic leaves from 10 plants were sampled. The margins of the samples were cut into 2 mm × 2 mm pieces. The tissue surface was disinfected with 75% ethanol for 30 s and 2% sodium hypochlorite for 60 s. Thereafter, the samples were rinsed three times in sterile water, placed on potato dextrose agar (PDA), and incubated at 28 °C. Pure cultures were obtained by transferring hyphal tips to new PDA plates. Twenty-eight isolates were obtained (isolation frequency = 28/4 × 10 = 70%). Three representative single-spore isolates (RNPO-1, RNPO-2, and RNPO-3) by a single-spore isolation method (Fang. 1998) were used for further study. The colonies of isolates on PDA were olive green in 7 days at 28 °C. Conidiogenous cells were unbranched, geniculate–sinuous, tapered toward the apex, and 10 to 20 × 3 μm (n = 20). Conidia were solitary, smooth, straight or curved, pale brown, 3 to 8-septate, apex acute, base truncate, and 50.5 to 88.5 × 2.0 to 3.5 μm (n = 50). For molecular identification, the colony PCR method with Taq DNA polymerase and MightyAmp DNA Polymerase (Lu et al. 2012) was used to amplify the internal transcribed spacer (ITS), translation elongation factor 1-α gene (TEF1), actin (ACT) , and RNA polymerase II second largest subunit (RPB2) loci of the isolates using primer pairs ITS1/ITS4, EF1/EF2, ACT-512F/ACT-783R, and RPB2-7CF/fRPB2-11aR, respectively (O’Donnell et al. 1998; O’Donnell et al. 2010). Their sequences were deposited in GenBank under nos. OP963568 to OP963570 (ITS), OP998376 to OP998378 (TEF1), OP998373 to OP998375 (ACT), and OP998379 to OP998381 (RPB2). By using the Maximum Likelihood method, a phylogenetic tree was generated on the basis of the concatenated data from the sequences of ITS, TEF1, ACT, and RPB2 that clustered the isolates with P. oenotherae (the type strain CBS 131920). The fungus was thus identified as P. oenotherae basing on these morphological and molecular characteristics (Guo and Liu. 1992; Kirschner. 2015). Pathogenicity testing was performed in a greenhouse with 80% relative humidity at 28 °C to 30 °C. Healthy plants of R. nasutus were grown in pots, with one plant in each pot. Sterile cotton balls were immersed in the spore suspension (1 × 105 per mL) of the isolates for about 15 s before they were adhered to the leaves for 3 days. Each isolate was inoculated with three plants (2 month old), and each plant was inoculated with five leaves. Sterile distilled water was as the control and same treatment. The test was performed three times. Symptom were found on the inoculated plants after 2 weeks with the disease incidence 100%, whereas the control plants remained healthy. The fungus was re-isolated from the infected leaves and confirmed as the same isolates by morphological and ITS analyses. No pathogen was isolated from the control plants. P. oenotherae caused leaf spot on Oenothera biennis L. (Guo and Liu. 1992). To the best of our knowledge, this is the first report that R. nasutus is the new host of P. oenotherae (Crous et al. 2013). Thus, this work provides an important reference for the control of this disease in the future.

Investigation into the mechanism of surface atom emission from an individual cathode spot using molecular dynamics simulation

Contact erosion on the cathode of a vacuum arc is determined by the behaviours of the cathode spots, where the plasma–surface interactions take place. A comprehensive model of a single cathode spot is developed in this work based on the molecular dynamics method, where an atomic copper substrate in the size of nanometres is built and the contributions to the development of cathode spot from leftover plasma ions, surface electron emission, surface atom emission, back ions, Nottingham heating and Joule heating are integrated. Defined based on the surface temperature distribution, a cathode spot is observed in the simulation results. The surface atom emission, which is the origin of mass loss, can be directly detected by the atoms being isolated from the surface. Two routes of surface atom emission are observed as the sources of mass loss, including evaporation, and atom sputtering or splashing. It is found that in the high-temperature region, atom sputtering or splashing dominates the surface atom emission, which leads to considerable mass losses. The simulation results are consistent with previous experimental and other simulation findings, providing fundamental insights into the cathode spot formation mechanism from a microscopic perspective.

Exploring definitions of daily enteric methane emission phenotypes for genetic evaluations using a population of indoor-fed multi-breed growing cattle with feed intake data.

Genetic selection has been identified as a promising approach for reducing enteric methane (CH4) emissions; a prerequisite for genetic evaluations; however, these are estimates of the necessary genetic parameters based on a population representative of where the genetic evaluations will be used. The objective of this study was, therefore, to derive genetic parameters for a series of definitions of CH4, carbon dioxide (CO2), and dry matter intake (DMI) as well as genetic correlations between CH4, CO2, and DMI in a bid to address the paucity of studies involving methane emissions measured in beef cattle using GreenFeed systems. Lastly, estimated breeding values (EBV) were generated for nine alternative definitions of CH4 using the derived genetic parameters; the EBV were validated against both phenotypic performance (adjusted for non-genetic effects) and the Legarra and Reverter method comparing EBV generated for a subset of the dataset compared to EBV generated from the entire dataset. Individual animal CH4 and CO2 records were available from a population of 1,508 multi-breed growing beef cattle using 10 GreenFeed Emission Monitoring systems. Nine trait definitions for CH4 and CO2 were derived: individual spot measures, the average of all spot measures within a 3-h, 6-h, 12-h, 1-d, 5-d, 10-d, and 15-d period and the average of all spot measures across the full test period (20 to 114 d on test). Heritability estimates from 1,155 animals, for CH4, increased as the length of the averaging period increased and ranged from 0.09 ± 0.03 for the individual spot measures trait to 0.43 ± 0.11 for the full test average trait; a similar trend existed for CO2 with the estimated heritability ranging from 0.17 ± 0.04 to 0.50 ± 0.11. Enteric CH4 was moderately to strongly genetically correlated with DMI with a genetic correlation of 0.72 ± 0.02 between the spot measures of CH4 and a 1-d average DMI. Correlations, adjusted for heritability, between the adjusted phenotype and (parental average) EBV ranged from 0.56 to 1.14 across CH4 definitions and the slope between the adjusted phenotype and EBV ranged from 0.92 to 1.16 (expectation = 1). Validation results from the Legarra and Reverter regression method revealed a level bias of between -0.81 and -0.45, a dispersion bias of between 0.93 and 1.17, and ratio accuracy (ratio of the partial evaluation accuracies on whole evaluation accuracies) from 0.28 to 0.38. While EBV validation results yielded no consensus, CH4 is a moderately heritable trait, and selection for reduced CH4 is achievable.

Research on the Role of Geographic Literature in the Establishment of Tourism Image in the Context of Informatization

Abstract This paper utilizes web crawler in network text mining technology to obtain the Jiangsu garden review data on several OTAs and tourism UGC platforms, such as Baidu Tourism, Ctrip.com, and Ma’s Nest. The data preprocessing work such as text de-weighting, word frequency classification, and parameter solving is carried out on the document dataset by using the lexical algorithm, and the preprocessed text data is subjected to TF-IDF keyword extraction and LDA topic extraction. Starting from the characteristics of the cultural lineage, the intrinsic attraction elements affecting the commercial transformation of tourist attractions are explored, and taking the planning of the industrial, cultural tourism town in Ezhou as an example, the process of planning and designing from the establishment of tourism planning concepts, and thus the completion of the visual IP image, is elaborated. The tourism image perception of the four major gardens in Jiangsu is examined from both cognitive and emotional perspectives using the results of TF-IDF and LDA extraction. The results show that the trend of the frequency of each fraction of the emotion of the Humble Administrator’s Garden, Liouyuan Garden, Lion Grove, and Canglang Pavilion scenic spots is roughly the same, and the mean value of emotion is 0.758, 0.851, 0.828, and 0.845, respectively, reflecting the tourists’ average emotional perception of the individual scenic spots. This study provides new methods and ideas for promoting the integrated development of culture, commerce and tourism in small and medium-sized cities so that the culture and tourism industry can be developed sustainably.

The CCS greensand project: CO2 pilot injection and monitoring

The CCS greensand project: CO2 pilot injection and monitoring

First Report of Pseudocercospora paraguayensis Causing Leaf Spots on Bixa orellana from Chinese Mainland.

Bixa orellana L. is a traditional Chinese medicine. In December 2019, a leaf spot disease was observed on B. orellana from a field in Zhanjiang (21°18'12''N, 110°17'22''E), China. Disease incidence was around 85% (n = 100 investigated plants from about 30 hectares).Initial leaf spots were circular, and the center of the lesions was grayish-white with a purple black border. The coalescence of individual spots eventually led to leaf wilt. Ten symptomatic leaves from 10 plants were sampled. The margins of the samples were cut into 2 mm × 2 mm pieces, and the surfaces were disinfected with 75% ethanol for 30 sec, and 2% sodium hypochlorite for 60 sec. The the samples were then rinsed three times in sterile water, plated on potato dextrose agar (PDA), and incubated at 28 °C. Pure cultures were obtained by transferring the hyphal tips to new PDA plates. Three representative isolates (BOPP-1, BOPP-2, and BOPP-3) were used for further study. The colonies of isolates on PDA were dark olive green with off-white aerial mycelia after 7 days at 28 °C. Conidia were solitary, smooth to verrucous, olive to light brown, slightly curved, narrowly obclavate, apex obtuse, base obconic-truncate, had 2-4 septa, and 30.4-55.5×2.0-3.5 μm in size.. These morphological characteristics showed did not differ from the description of Pseudocercospora paraguayensis (Crous et al. 1997). For molecular identification, the internal transcribed spacer (ITS) region, the translation elongation factor 1-α (TEF1) gene, and actin (ACT) gene were amplified using primer pairs ITS1/ITS4 (White et al., 1990), EF1/EF2 ( O'Donnell et al. 1998), and ACT-512F/ACT-783R (Carbone and Kohn, 1999) and sequenced from DNA extracted from the three isolates, respectively. Sequences were deposited in GenBank under accession no. MZ363823-MZ363825 (ITS), MZ614954-MZ614956 (TEF1), and MZ614951-MZ614953 (ACT). A phylogenetic tree was generated on the basis of the concatenated data from the sequences of ITS, TEF1, and ACT that the three isolates were nested within the clade containing the type specimen of P. paraguayensis (CBS 111286) but not within P. bixae (the type specimen CPC 25244). Pathogenicity was tested through in vivo experiments. Inoculation and control seedlings (n = 5, 1-month-old) were sprayed with a spore suspension (1 × 105 per ml) of P. paraguayensis and sterile distilled water (control), respectively, until run-off (Fang. 1998). The plants were grown in pots in a greenhouse at 28°C, with at approximately80% RH. The test was performed three times. Symptoms similar to those in the field were observed on the inoculated plants after two weeks. The control plants remained healthy. The fungus was re-isolated from the infected leaves and confirmed as the same isolatesby morphological and comparison of ITS sequences with 100% identical to those of isolates. No original fungi were isolated from the control plants. A previous study reported that P. paraguayensis caused leaf spots on pistachio and eucalypts, and the fungus causing the leaf spots of B. orellana was redescribed as P. bixae (Crous et al. 2019). However, multilocus phylogenetic analyses differentiated P. paraguayensis from P. bixae. In the present study, P. paraguayensis was distinguished from P. bixae due to the absence of catenulate conidia and the presence of finely verruculose conidia (Crous et al. 2013). P. eucalypti as a synonyms was reported in Taiwan (www.MycoBank.org). The current study is the first to report P. paraguayensis causing leaf spots on B. orellana from Chinese Mainland. This finding will help to provide a scientific basis for the disease detection.

Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter

Objective. Proton therapy is highly sensitive to range uncertainties due to the nature of the dose deposition of charged particles. To ensure treatment quality, range verification methods can be used to verify that the individual spots in a pencil beam scanning treatment fraction match the treatment plan. This study introduces a novel metric for proton therapy quality control based on uncertainties in range verification of individual spots. Approach. We employ uncertainty-aware deep neural networks to predict the Bragg peak depth in an anthropomorphic phantom based on secondary charged particle detection in a silicon pixel telescope designed for proton computed tomography. The subsequently predicted Bragg peak positions, along with their uncertainties, are compared to the treatment plan, rejecting spots which are predicted to be outside the 95% confidence interval. The such-produced spot rejection rate presents a metric for the quality of the treatment fraction. Main results. The introduced spot rejection rate metric is shown to be well-defined for range predictors with well-calibrated uncertainties. Using this method, treatment errors in the form of lateral shifts can be detected down to 1 mm after around 1400 treated spots with spot intensities of 1 × 107 protons. The range verification model used in this metric predicts the Bragg peak depth to a mean absolute error of 1.107 ± 0.015 mm. Significance. Uncertainty-aware machine learning has potential applications in proton therapy quality control. This work presents the foundation for future developments in this area.

Can lithium contents in mica be correctly calculated? Tischendorf́s proposal (Mineralogical Magazine 61/1997) 25 years after

AbstractMicas are the most common hosts of lithium in granitoid igneous rocks. Unfortunately, their Li contents cannot be determined by electron-probe microanalysis (EPMA) which is the most common method of mineral analysis. In an effort to avoid the use of other, technically more complex and expensive methods, several empirical schemes for the estimation of Li-contents from EPMA data have been developed. The methods proposed by Tischendorf (Mineralogical Magazine, 1997) have found the widest application. After 25 years of common usage, we have evaluated these methods by direct Li determination using laser ablation-inductively coupled plasma-mass spectrometry (LA–ICP–MS). Approximately 3000 spot analyses of Li in micas from eight areas worldwide obtained by LA–ICP–MS were compared with the values yielded by the methods of Tischendorf. We conclude that none of the lithium estimation methods can compensate fully for a real local analysis by LA–ICP–MS or secondary-ion mass spectrometry (SIMS). Generally, SiO2-based estimation for trioctahedral micas provides a better match to the analysed values than F-based estimation for dioctahedral micas. The Rb-based estimation for dioctahedral micas does not provide acceptable results. The usage of averaged Si- and F-based estimations can be accepted in common petrological studies for a general characterisation of mica species. Large errors of individual spot estimations preclude their usage in detailed mineralogical studies.

Predicting methane emissions of individual grazing dairy cows from spectral analyses of their milk samples

Data on the enteric methane emissions of individual cows are useful not just in assisting management decisions and calculating herd inventories but also as inputs for animal genetic evaluations. Data generation for many animal characteristics, including enteric methane emissions, can be expensive and time consuming, so being able to extract as much information as possible from available samples or data sources is worthy of investigation. The objective of the present study was to attempt to predict individual cow methane emissions from the information contained within milk samples, specifically the spectrum of light transmittance across different wavelengths of the mid-infrared (MIR) region of the electromagnetic spectrum. A total of 93,888 individual spot measures of methane (i.e., individual samples of an animal's breath when using the GreenFeed technology) from 384 lactations on 277 grazing dairy cows were collapsed into weekly averages expressed as grams per day; each weekly average coincided with a MIR spectral analysis of a morning or evening individual cow milk sample. Associations between the spectra and enteric methane measures were performed separately using partial least squares regression or neural networks with different tuning parameters evaluated. Several alternative definitions of the enteric methane phenotype (i.e., average enteric methane in the 6 d preceding or 6 d following taking the milk sample or the average of the 6 d before and after the milk sample, all of which also included the enteric methane emitted on the day of milk sampling), the candidate model features (e.g., milk yield, milk composition, and milk MIR) as well as validation strategy (i.e., cross-validation or leave-one-experimental treatment-out) were evaluated. Irrespective of the validation method, the prediction accuracy was best when the average of the milk MIR from the morning and evening milk sample was used and the prediction model was developed using neural networks; concurrently including milk yield and days in milk in the prediction model generated superior predictions relative to just the spectral information alone. Furthermore, prediction accuracy was best when the enteric methane phenotype was the average of at least 20 methane spot measures across a 6-d period flanking each side of the milk sample with associated spectral data. Based on the strategy that achieved the best accuracy of prediction, the correlation between the actual and predicted daily methane emissions when based on 4-fold cross-validation varied per validation stratum from 0.68 to 0.75; the corresponding range when validated on each of the 8 different experimental treatments focusing on alternative pasture grazing systems represented in the dataset varied from 0.55 to 0.71. The root mean square error of prediction across the 4-folds of cross-validation was 37.46 g/d, whereas the root mean square error averaged across all folds of leave-one-treatment-out was 37.50 g/d. Results suggest that even with the likely measurement errors contained within the MIR spectrum and gold standard enteric methane phenotype, enteric methane can be reasonably well predicted from the infrared spectrum of milk samples. What is yet to be established, however, is whether (a) genetic variation exists in this predicted enteric methane phenotype and (b) selection on estimates of genetic merit for this phenotype translate to actual phenotypic differences in enteric methane emissions.

First Report of Pseudocercospora oenotherae Causing Leaf spot in Hymenocallis littoralis in China.

Hymenocallis littoralis (Jacq.) Salisb. is a common ornamental plant in China. In November 2021, leaf spots were observed on H. littoralis in a public garden in Zhanjiang, Guangdong Province, China (21°17'25″N, 110°18'12″E). Disease incidence was 82% (n = 100 investigated plants from about 10 ha). Initial small white dots densely distributed on the leaves and gradually expanded into round lesions with purple centers typically surrounded by yellow halos. The coalescence of the individual spot eventually led to leaf wilt. Ten symptomatic leaves from 10 plants were sampled. The margins of the samples were cut into 2 mm × 2 mm pieces. The tissue surface was disinfected with 75% ethanol for 30 s and 2% sodium hypochlorite for 60 s. Thereafter, the samples were rinsed three times in sterile water, placed on potato dextrose agar (PDA), and incubated at 28 °C. Pure cultures were obtained by transferring hyphal tips to new PDA plates. Twenty-eight isolates were obtained (isolation frequency = 28/4 × 10 = 70%). Three representative single-spore isolates (HPO-1, HPO-2, and HPO-3) by a single-spore isolation method (Fang. 1998) were used for further study. The colonies of isolates on PDA were olive green in 7 days at 28 °C. Conidiogenous cells were unbranched, straight to geniculate-sinuous, tapered toward the apex, and 12-19 × 3 μm (n = 20). Conidia were solitary, smooth, straight or curved, pale brown, 3-8-septate, apex acute, base truncate, and 55.3-86.5 × 2.0-3.5 μm (n = 50). The morphological characteristics were consistent with the description of Pseudocercospora oenotherae (Guo and Liu. 1992; Kirschner. 2015). For molecular identification, the colony PCR method with Taq DNA polymerase and MightyAmp DNA Polymerase (Lu et al. 2012) was used to amplify the internal transcribed spacer (ITS), translation elongation factor 1-α gene (TEF1), and actin (ACT) loci of the isolates using primer pairs ITS1/ITS4, EF1/EF2, and ACT-512F/ACT-783R, respectively (O'Donnell et al. 1998). Their sequences were deposited in GenBank under nos. OM654573-OM654575 (ITS), OM831379-OM831381 (TEF1), and OM831349-OM831351 (ACT). A phylogenetic tree was generated on the basis of the concatenated data from the sequences of ITS, TEF1, and ACT that clustered the isolates with P. oenotherae (the type strain CBS 131920). Pathogenicity testing was performed in a greenhouse with 80% relative humidity at 28 °C to 30 °C. Healthy plants of H. littoralis were grown in pots, with one plant in each pot. They were inoculated with a spore suspension (1 × 105 per mL) of the isolates and sterile distilled water (control). Sterile cotton balls were immersed in the spore suspension and sterile distilled water for about 15 s before they were adhered to the leaves for 3 days. Each isolate was inoculated with three plants (1 month old), and each plant was inoculated with two leaves. The test was performed three times. Symptom were found on the inoculated plants after 2 weeks with the disease incidence 88.89%, whereas the control plants remained healthy. The fungus was re-isolated from the infected leaves and confirmed as the same isolates by morphological and ITS analyses. No fungus was isolated from the control plants. P. oenotherae caused leaf spot on OenotherabiennisL. (Guo and Liu. 1992). H. littoralis is the second host of the fungus investigated in this study firstly (Crous, et al. 2013). Thus, this work provides an important reference for the control of this disease in the future.