Similar Distribution Research Articles

Catamicrophyllum beroni sp. nov.the first European record of the genus Catamicrophyllum Verhoeff, 1901 (Diplopoda: Julida: Julidae).

A new species of Catamicrophyllum Verhoeff, 1901, Catamicrophyllum beroni sp. nov., is described from Rila Mts, southwest Bulgaria. The new species is compared to its most similar congener, Catamicrophyllum caucasicum (Attems, 1901) known from the Caucasus and Eastern Anatolia, including descriptive notes and scanning electron micrographs of the latter. The remarkably disjunct distribution areas of the two species are briefly discussed in the context of similar distribution patterns in other members of Julidae. In addition, some ecological notes and conservation issues in connection with the climatic changes occurring in the area of the type locality of C. beroni sp. nov. are presented.

Processing of Porous-Core Materials for Bone Implant Applications: A Permeability and Mechanical Strength Analysis

This study presents a methodology to fabricate Ti6Al4V cylindrical compacts with a highly porous core and dense shell with the aim to mimic the bone microstructure. Compacts with different core diameters were obtained via conventional pressing and sintering. Large pores were created with the aid of pore formers. Dilatometry was used to determine the sintering kinetics, while X-ray computed tomography was used for characterization. Also, the permeability was evaluated on the 3D microstructure, and the mechanical strength was evaluated via compression tests. The results indicated that sintering was constrained by the different densification rates of the porous and dense layers. However, defect-free compacts were obtained due to neck bonding between the Ti6Al4V particles. Large pores were located in the designed core with a similar pore size distribution. The permeability increased following a power law as a function of the pore volume fraction. The porous core drove the stiffness of the bilayer components, while the combination of both layers increased their strength. The bilayer materials showed permeability (1.36 × 10−10 m2), mechanical properties (E = 6.83 GPa and σy = 299 MPa), and admissible strain (σy/E = 43 × 10−3) similar to those of human bones.

Dynamic characteristics analysis and valve core optimization for second stage hydrogen pressure reducer of hydrogen decompression valve

As an important component of pressure management system, hydrogen decompression valve (HDV) is used in hydrogen fuel cell vehicles, hydrogen refueling stations, etc. The high-pressure difference causes severe pressure fluctuation. Thus, the HDV is composed of multi-stage pressure reducers. Specially, the outlet pressure from the HDV highly affects the pressure of fuel cell. The service life and operation condition of fuel cell is affected significantly by the HDV. This paper conducted the research of the second stage hydrogen pressure reducer (SHPR) of on-boarding hydrogen decompression valve. The force and dynamic characteristics of the valve core are obtained and the flow characteristic is analyzed through the steady and transient flow model. The results are shown that the fluid force and combined force on the valve core exhibit linear increase with inlet pressure and throttling area. The flow characteristics in the throttling gap exhibit similar distribution law under different throttling lengths and inlet pressures. The pressure-drop at entrance and exit of the throttling gap is drastic. Besides, the spring stiffness has a significant impact on the dynamic characteristics of the valve core. With the increase of spring stiffness, the dynamic characteristics change from unstable-state to stable-state under the sudden increase of inlet pressure. The larger spring stiffness initially causes displacement fluctuation of the valve core and then the valve core maintains a stable opening under the stable state. Finally, the optimized structure of valve core is proposed and the better stability of SHPR has been achieved. Meanwhile, there is no significant difference in flow performance but the dynamic characteristics are improved.

A new species of Bryconamericus (Characidae: Stevardiinae) with breeding tubercles from the upper rio Paraná basin

Abstract Five species of Bryconamericus are known from the upper rio Paraná basin: ‘B.’ aff. iheringii, ‘B.’ coeruleus, B.stramineus, ‘B.’ turiuba and the non-native B. exodon. The new species can be easily distinguished from them by its body depth (27.8–31.8% SL) and the teeth aligned in the outer row of the premaxilla (except ‘B.’ aff. iheringii). The new species is distributed in tributaries to the Piquiri, Ivaí and Tibagi rivers, at altitudes between 498 and 900 m a.s.l. The geographic distribution of the new species is similar to the congener ‘B.’ coeruleus. Other species with similar distribution are Apareiodon vladii and Planaltina kaingang, although they only occur in the Piquiri and Ivaí river basins. Furthermore, this work records the new species with the presence of breeding tubercles. These tubercles are located on the dorsal and lateral portions of the head and on the posterior margin of the scales of mature males; and in females, when present, they are smaller and restricted to the posterior margin of the scales. Comments are made on the presence of breeding tubercles in other groups of fishes, and also on some dimorphic characters present in the new species.

A Fast Granular-Ball-Based Density Peaks Clustering Algorithm for Large-Scale Data.

Density peaks clustering algorithm (DP) has difficulty in clustering large-scale data, because it requires the distance matrix to compute the density and δ -distance for each object, which has O(n2) time complexity. Granular ball (GB) is a coarse-grained representation of data. It is based on the fact that an object and its local neighbors have similar distribution and they have high possibility of belonging to the same class. It has been introduced into supervised learning by Xia et al. to improve the efficiency of supervised learning, such as support vector machine, k -nearest neighbor classification, rough set, etc. Inspired by the idea of GB, we introduce it into unsupervised learning for the first time and propose a GB-based DP algorithm, called GB-DP. First, it generates GBs from the original data with an unsupervised partitioning method. Then, it defines the density of GBs, instead of the density of objects, according to the centers, radius, and distances between its members and centers, without setting any parameters. After that, it computes the distance between the centers of GBs as the distance between GBs and defines the δ -distance of GBs. Finally, it uses GBs' density and δ -distance to plot the decision graph, employs DP algorithm to cluster them, and expands the clustering result to the original data. Since there is no need to calculate the distance between any two objects and the number of GBs is far less than the scale of a data, it greatly reduces the running time of DP algorithm. By comparing with k -means, ball k -means, DP, DPC-KNN-PCA, FastDPeak, and DLORE-DP, GB-DP can get similar or even better clustering results in much less running time without setting any parameters. The source code is available at https://github.com/DongdongCheng/GB-DP.

Nanotopography and oral bacterial adhesion on titanium surfaces: in vitro and in vivo studies.

The present study aimed to evaluate the influence of titanium surface nanotopography on the initial bacterial adhesion process by in vivo and in vitro study models. Titanium disks were produced and characterized according to their surface topography: machined (Ti-M), microtopography (Ti-Micro), and nanotopography (Ti-Nano). For the in vivo study, 18 subjects wore oral acrylic splints containing 2 disks from each group for 24 h (n = 36). After this period, the disks were removed from the splints and evaluated by microbial culture method, scanning electron microscopy (SEM), and qPCR for quantification of Streptococcus oralis, Actinomyces naeslundii, Fusobacterium nucleatum, as well as total bacteria. For the in vitro study, adhesion tests were performed with the species S. oralis and A. naeslundii for 24 h. Data were compared by ANOVA, with Tukey's post-test. Regarding the in vivo study, both the total aerobic and total anaerobic bacteria counts were similar among groups (p > 0.05). In qPCR, there was no difference among groups of bacteria adhered to the disks (p > 0.05), except for A. naeslundii, which was found in lower proportions in the Ti-Nano group (p < 0.05). In the SEM analysis, the groups had a similar bacterial distribution, with a predominance of cocci and few bacilli. In the in vitro study, there was no difference in the adhesion profile for S. oralis and A. naeslundii after 24 h of biofilm formation (p > 0.05). Thus, we conclude that micro- and nanotopography do not affect bacterial adhesion, considering an initial period of biofilm formation.

Alzheimer's disease biomarker utilization at first referral enhances differential diagnostic precision with simultaneous exclusion of Creutzfeldt-Jakob disease.

Most suspected Creutzfeldt-Jakob disease (CJD) cases are eventually diagnosed with other disorders. We assessed the utility of investigating Alzheimer's disease (AD) biomarkers and neurofilament light (NfL) in patients when CJD is suspected. The study cohort consisted of cerebrospinal fluid (CSF) samples referred for CJD biomarker screening wherein amyloid beta 1-42 (Aβ1-42), phosphorylated tau 181 (p-tau181), and total tau (t-tau) could be assessed via Elecsys immunoassays (n=419) and NfL via enzyme-linked immunosorbent assay (ELISA; n=161). In the non-CJD sub cohort (n=371), 59% (219/371) had A+T- (abnormal Aβ1-42 only) and 21% (79/371) returned A+T+ (abnormal Aβ1-42 and p-tau181). In the 48 CJD subjects, a similar AD biomarker profile distribution was observed. To partially address the prevalence of likely pre-symptomatic AD, NfL was utilized to assess for neuronal damage. NfL was abnormal in 76% (25/33) of A+T- subjects 40 to 69 years of age, 80% (20/25) of whom had normal t-tau. This study reinforces AD as an important differential diagnosis of suspected CJD, highlighting that incorporating AD biomarkers and NfL at initial testing is worthwhile.

Differential distribution of intermediate filament proteins in the bovine and ovine tongues.

Intermediate filaments constitute the most heterogeneous class among the major classes of cytoskeletal proteins of mammalian cells. The 40 or more intermediate filament proteins have been classified into five types which show very specific rules of expression in specialized cell types. This study aimed to investigate the immunohistochemical distribution of cytokeratins (CKs) 8, 18, and 19 as well as the intermediate filaments vimentin, laminin, and desmin in bovine and ovine tongues. Immunohistochemical staining was performed for CKs 8, 18, 19, vimentin, laminin, and desmin. Our results revealed similar immunostaining intensity and distribution among various CKs, contrasting with distinct patterns for vimentin, laminin, and desmin. Immunoreactions were primarily localized in serous acini and ductal epithelium for cytokeratins, while vimentin and laminin were evident in connective tissue, endothelium, serous acini, and desmin in striated and smooth muscles. This study highlighted the absence of CKs 8, 18, 19, vimentin, and desmin in the lingual epithelium of bovine and ovine tongues. These findings enabled the classification of epithelial cells based on their specific cytokeratin patterns. Furthermore, vimentin was identified in mesodermal tissues and organs, desmin in muscle tissue, and laminin played crucial roles in basement membrane formation, nerve tissue regeneration, innervation of epithelial taste buds, and tissue separation and connection. Our findings provide essential insights into intermediate filament dynamics at the cellular and tissue levels. They serve as a foundation for future studies using systematic molecular biological techniques in this field.

Categorization of Spatial and Temporal Ejecta Outcomes in Binary Systems Based on Variations of the Didymos System

With the increasing number of binary asteroid systems being discovered, ejecta studies must expand from solely investigating single-body systems to modeling more complex multiple-body systems. For example, the Double Asteroid Redirection Test provides an opportunity to study the dynamics of a debris cloud around Didymos and Dimorphos, a near-Earth binary asteroid system. Here we simulate 72 variations on the Didymos system in order to categorize types of ejecta outcomes and analyze the influence of the varying system parameters on each outcome. We have varied five parameters: the system separation, the mass ratio between the two bodies, the impact location, the target-body shape, and the target-body rotation period. The resulting provenance maps of the final ejecta distributions were blindly sorted into five categories, while the resulting cumulative distribution functions (CDFs), describing the rate at which particles hit the surface, were blindly sorted into eight categories. We count the occurrences of the parameter values in each of the categories and apply a Cramer’s V statistical test to evaluate the significance of the association between each varied effect and the overall grouping of the provenance maps and CDFs. We conclude that more dominant effects, such as a small rotation period, produce notably similar ejecta distributions that result in being assigned to the same category. Less dominant effects, such as target-body location, are sorted into several categories due to the larger influence of varying dominant effects.

Comparative analyses of the Smith-Magenis syndrome protein RAI1 in mice and common marmoset monkeys.

Retinoic acid-induced 1 (RAI1) encodes a transcriptional regulator critical for brain development and function. RAI1 haploinsufficiency in humans causes a syndromic autism spectrum disorder known as Smith-Magenis syndrome (SMS). The neuroanatomical distribution of RAI1 has not been quantitatively analyzed during the development of the prefrontal cortex, a brain region critical for cognitive function and social behaviors and commonly implicated in autism spectrum disorders, including SMS. Here, we performed comparative analyses to uncover the evolutionarily convergent and divergent expression profiles of RAI1 in major cell types during prefrontal cortex maturation in common marmoset monkeys (Callithrix jacchus) and mice (Mus musculus). We found that while RAI1 in both species is enriched in neurons, the percentage of excitatory neurons that express RAI1 is higher in newborn mice than in newborn marmosets. By contrast, RAI1 shows similar neural distribution in adult marmosets and adult mice. In marmosets, RAI1 is expressed in several primate-specific cell types, including intralaminar astrocytes and MEIS2-expressing prefrontal GABAergic neurons. At the molecular level, we discovered that RAI1 forms a protein complex with transcription factor 20 (TCF20), PHD finger protein 14 (PHF14), and high mobility group 20A (HMG20A) in the marmoset brain. In vitro assays in human cells revealed that TCF20 regulates RAI1 protein abundance. This work demonstrates that RAI1 expression and protein interactions are largely conserved but with some unique expression in primate-specific cells. The results also suggest that altered RAI1 abundance could contribute to disease features in disorders caused by TCF20 dosage imbalance.

GCVC: Graph Convolution Vector Distribution Calibration for Fish Group Activity Recognition

Only a few key fish individuals can play a dominant role in actual fish group, therefore, it is reasonable to infer group activities from the relationship between individual actions. However, the complex underwater environment, rapid and similar fish individual movements are likely to cause the indistinct action characteristics, as well as adhesion of data distribution, and it is difficult to infer the relationship between individual actions directly by using graph convolutional network (GCN). Therefore, this paper proposes a graph convolution vector calibration (GCVC) network for fish group activity recognition through individual action relationship reasoning. By improving reasoning ability of GCN, an activity feature vector calibration module is designed to solve the data adhesion and mismatch between the estimated and true distribution. The idea is to first count the distribution of the original data, and make each dimension of its active feature vector follow the Gaussian distribution, so as to generate a better similar category distribution. In addition, we also produced a fish activity dataset to verify the performance of the proposed algorithm. The experimental results show that the GCVC achieves a group activity recognition accuracy of 93.33 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , and the Macro-F1 is 93.25 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , which is 19.21 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and 24.2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> higher than before, respectively. By using GCVC, the corrected activity feature vector distribution is more consistent, and the data adhesion is reduced, the model can achieve more fully supervised learning. The fish group activity dataset is available on Github: <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/crazysboy/GCVC/tree/master</uri> .

RF-Siamese: Approaching Accurate RFID Gesture Recognition With One Sample

Performing accurate sensing in diverse environments is a challenging issue in wireless sensing technologies. Existing solutions usually require collecting a large number of samples to train a classifier for every environment, or further assume similar sample distribution between different environments such that a model trained in one environment can be transferred to another. In this paper, we propose RF-Siamese, an RFID-based gesture sensing approach that achieves comparable accuracy to existing solutions but requires only a few samples in each eivironment. RF-Siamese leverages Siamese networks to distinguish different gestures with only a small number of samples and is enhanced by several novel designs to achieve high accuracy in diverse environments. First, the network structure and parameters (e.g., loss function and distance metric) are carefully designed to be suitable for RFID gesture recognition. Second, a permutation-based dataset generation strategy is proposed to make full use of the collected samples to enhance the recognition accuracy. Third, a template matching method is proposed to extend the Siamese network to classify multiple gestures. Extensive experiments on commercial RFID devices demonstrate that RF-Siamese achieves a high accuracy of 0.93 with only one sample of each gesture when recognizing 18 different gestures, while state-of-the-art approaches based on transfer learning and meta learning achieve an accuracy of only 0.59 and 0.70, respectively.

The distribution and enrichment characteristics of rare earth elements between coals and coal ashes from four coal-fired power plants.

Coal and coal ash (slag and fly ash) have emerged as important potential sources for rare earth elements (REY). The distribution and enrichment of REY during coal combustion from coal-fired power plants are of great significance for the recovery of REY. In this study, the concentration of REY in coal and coal ash from four coal-fired power plants in China was determined using microwave digestion-inductively coupled plasma mass spectrometry. The distribution and enrichment characteristics of REY in coal and coal ash were studied. The coal ash contains 310-683 μg g-1 of REY, and the proportion of critical REY was greater than 30%, which is higher than the extraction concentration (300 μg g-1) recommended by the United States Department of Energy, indicating significant REY recovery potential. The concentration of REY in coal was positively correlated with ash yield, which could be explained by the fact that REY are mainly distributed in minerals. Coal and coal ash show similar REY distribution patterns, indicating that REY were not fractionated during the coal combustion. In addition, the enrichment coefficient of REY in fly ash was greater than that in slag, which revealed that REY were mainly enriched in fly ash. Therefore, the REY in fly ash has more recycling potential.

Occurrence and Distribution of Cancers with Emphasis Upon Oral Cancers in Registered Oncology Institutes of South India - A Retrospective Study.

In the past two decades, the growing economy associated with changes in lifestyle-related behavior is partially responsible for the increasing cancer burden in India. To assess the occurrence and distribution of oral cancer based on the analysis of hospital records from registered oncology institutes of South India over a period of three years. A multicenter, retrospective study was conducted at seven major hospitals in South India to assess the incidence and distribution of cancer among patients over a period of three years (2016-2018). Data were collected on a custom-made validated proforma. Analysis was done using R commander software. A total of 156090 various types of cancers were reported to the included institutes over a three-year period, an almost similar gender distribution was observed, males (n = 78806, 42.99% per lakh) compared to their female counterparts (n = 77284, 42.16% per lakh). Among males' lung cancer was the most common type with 17709 cases (9.65% per lakh) and among females, breast cancer was the leading cancer type with 22855 total cases (12.46% per lakh). Over a period of three years, a total of 21084 records of malignancies pertaining to oral cavity were identified accounting for 13.51% of cases. Among oral cancers, tongue was the most common site to be involved accounting for 44.22% (2016-2018) cases followed by buccal mucosa (14.69%), least common site to be involved was lip which accounted for 3.49% of the total oral cancer cases. Breast cancer was the most common cancer followed by lung cancer. Oral cancers occupied second among males and fifth rank in the order of occurrence among females. Tongue was the most common site followed by buccal mucosa. The least common site affected by oral cancer was the lip.

Assessment of Clinical and Biochemical Cardiac Risk Factors in Patients with Subclinical Hypothyroidism: A Cross-sectional Study

Introduction: Cardiovascular diseases (CVD) are among the leading causes of morbidity and mortality in the current era, and the focus is gradually shifting towards identifying the risk factors and pathways leading to CVD. While hypothyroidism has been extensively studied and linked to CVD risk, the association between subclinical hypothyroidism and CVD risk factors is not well established. Aim: To investigate the association between subclinical hypothyroidism and cardiac risk factors such as obesity indicators {Body Mass Index (BMI) and Waist-hip Ratio (WHR)}, blood pressure, and lipid parameters. Materials and Methods: This cross-sectional study was conducted at the Department of Medicine, ESI PGIMSR, Basaidarapur, New Delhi, India, from December 2020 to April 2022. The study included 200 patients, with 100 patients recruited in the subclinical hypothyroidism group (Thyroid Stimulating Hormone (TSH) &gt;4.8 μIU/mL with normal fT4) and 100 patients with euthyroid status (TSH 0.5-4.8 μIU/mL and normal fT4) included in the comparison group. Both groups were assessed for CVD risk factors including obesity indicators (BMI and WHR), blood pressure, and lipid parameters. The two groups were analysed for statistical significance using Student’s t-test. Results: Both groups had similar age distributions. However, there was a greater percentage of female patients in the subclinical hypothyroidism group (61%) compared to the euthyroid group (52%). As expected, TSH levels in the subclinical hypothyroidism group were significantly higher than in the euthyroid group. The subclinical hypothyroidism group recorded significantly higher mean values of BMI, Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), total cholesterol, and triglycerides, which were higher by 18%, 17%, 17%, 41%, and 16% compared to the euthyroid group, respectively. Other parameters like WHR and Low-Density Lipoprotein-Cholesterol (LDL-C) were found to be raised in subclinical hypothyroidism compared to the euthyroid group, while High-Density Lipoprotein-Cholesterol (HDL-C) levels were significantly lower by 16% in subclinical hypothyroidism. Conclusion: Subclinical hypothyroidism is significantly associated with cardiac risk factors like obesity indicators (BMI and WHR), blood pressure, and lipid parameters.

РОССИЙСКАЯ ФЕДЕРАЦИЯ КАК ЦЕНТР НАУЧНО-ТЕХНИЧЕСКОЙ КООПЕРАЦИИ СТРАН-ЧЛЕНОВ ЕАЭС: АНАЛИЗ ПУБЛИКАЦИОННОЙ АКТИВНОСТИ И ПЕРСПЕКТИВЫ РАЗВИТИЯ

The study examines the representation of scientific research outcomes from member countries of the Eurasian Economic Union (EAEU) within the Russian scientific database eLIBRARY.RU in the field of economics and economic sciences. Methods of scientometric and bibliometric analysis were employed to analyze metadata from over 12 publications available in the scientific databases eLIBRARY.RU, Scopus, and Crossref. Recommendations have been formulated for the overall development of the Russian Federation and, specifically, for the eLIBRARY.RU platform as a center for scientific and technical cooperation among EAEU member countries. The results show that among the authors registered on the platform from the EAEU countries (other than the Russian Federation), the share of authors-economists from Belarus is higher than from Kyrgyzstan, Kazakhstan and Armenia, however, it is generally small. The authors from Kazakhstan, Kyrgyzstan and Armenia have a similar distribution of average values in terms of published materials, however, unlike Belarus, there are almost no registered economic authors with a significant number of publications in these countries. A significant absence of previously published works, archival data and an extremely small number of indexed economic scientific peer-reviewed publications from the EAEU member states were also revealed on the platform. None of the journals of Russia’s EAEU counterpart countries presented on the eLIBRARY.RU, is not included in the list of the Higher Attestation Commission, the core of the RSCI, Web of Science or Scopus. In addition, it was determined that in the EAEU countries there is a wide range of thematic areas of economic and interdisciplinary research covering education, digital technologies, agriculture and other areas. Among them there are general thematic areas that unite science in the EAEU countries, including globalization, digital transformation, agriculture, sustainable development, innovation, education and others. Based on the results obtained, the team of authors formed recommendations for the development of the Russian Federation as a whole, and the eLIBRARY. RU, in particular, as a center for scientific and technical cooperation of the EAEU member states.

Mechanical Difference Analysis of Single-row and Double-row Side Piles in Stations by PBA Method Based on Model Test

This study employs the pile-beam-arch (PBA) method to investigate the force-evolution law of micro-steel pipe piles during the excavation process, focusing on a Guangzhou metro-station project. Through laboratory model tests, we compared and analyzed the mechanical evolution laws of single-row and double-row side piles. Our findings revealed a significant soil arch effect in both single-row and double-row piles; with similar distribution patterns and peak-stress range. As soil excavation progresses, the soil arching effect shifts downward. Notably, the stress concentration in double-row piles is weaker than that in single-row piles, especially in the soil range of 0–50 mm after the piles. This is attributed to the looser soil between single-row piles, resulting in more evident stress release. The attenuation amplitude of the Y-direction stress of the double-row piles was considerably smaller than that of the single-row piles. The soil arching between the back-row piles in doublerow configurations exhibits shielding effects on the force of front-row piles, significantly weakening the soil pressure on them. This impact alters the force of the front-row piles, even causing the tip of the front-row piles to bend in reverse. The research results provide important insights for similar projects and can serve as a valuable reference.

Plan complexity metrics for head and neck VMAT competition plans

Previous plan competitions have largely focused on dose metric assessments. However, whether the submitted plans were realistic and reasonable from a quality assurance (QA) perspective remains unclear. This study aimed to investigate the relationship between aperture-based plan complexity metrics (PCM) in volumetric modulated arc therapy (VMAT) competition plans and clinical treatment plans verified through patient-specific QA (PSQA). In addition, the association of PCMs with plan quality was examined. A head and neck (HN) plan competition was held for Japanese institutions from June 2019 to July 2019, in which 210 competition plans were submitted. Dose distribution quality was quantified based on dose-volume histogram (DVH) metrics by calculating the dose distribution plan score (DDPS). Differences in PCMs between the two VMAT treatment plan groups (HN plan competitions held in Japan and clinically accepted HN VMAT plans through PSQA) were investigated. The mean (± standard deviation) DDPS for the 98 HN competition plans was 158.5 ± 20.6 (maximum DDPS: 200). DDPS showed a weak correlation with PCMs with a maximum r of 0.45 for monitor unit (MU); its correlation with some PCMs was "very weak." Significant differences were found in some PCMs between plans with the highest 20% DDPSs and the remaining plans. The clinical VMAT and competition plans revealed similar distributions for some PCMs. Deviations in PCMs for the two groups were comparable, indicating considerable variability among planners regarding planning skills. The plan complexity for HN VMAT competition plans increased for high-quality plans, as shown by the dose distribution. Direct comparison of PCMs between competition plans and clinically accepted plans showed that the submitted HN VMAT competition plans were realistic and reasonable from the QA perspective. This evaluation may provide a set of criteria for evaluating plan quality in plan competitions.

Lessons from two series by physicians and caregivers' self-reported data in DDX3X-related disorders.

We report two series of individuals with DDX3X variations, one (48 individuals) from physicians and one (44 individuals) from caregivers. These two series include several symptoms in common, with fairly similar distribution, which suggests that caregivers' data are close to physicians' data. For example, both series identified early childhood symptoms that were not previously described: feeding difficulties, mean walking age, and age at first words. Each of the two datasets provides complementary knowledge. We confirmed that symptoms are similar to those in the literature and provides more details on feeding difficulties. Caregivers considered that the symptom attention-deficit/hyperactivity disorder were most worrisome. Both series also reported sleep disturbance. Recently, anxiety has been reported in individuals with DDX3X variants. We strongly suggest that attention-deficit/hyperactivity disorder, anxiety, and sleep disorders need to be treated.

Automatic Encoding of Unlabeled Two Dimensional Data Enabling Similarity Searches: Electron Diffusion Regions and Auroral Arcs

AbstractCritically important phenomena in Earth’s magnetosphere often occur briefly, or in small spatial regions. These processes are sampled with orbiting spacecraft or by fixed ground observatories and so rarely appear in data. Identifying such intervals can be an incredibly time consuming task. We apply a novel, powerful method by which two dimensional data can be automatically processed and embeddings created that contain key features of the data. The distance between embedding vectors serves as a measure of similarity. We apply the state‐of‐the‐art method to two example datasets: MMS electron velocity distributions and auroral all sky images. We show that the technique creates embeddings that group together visually similar observations. When provided with novel example images the method correctly identifies similar intervals: when provided with an electron distribution sampled during an encounter with an electron diffusion region the method recovers similar distributions obtained during two other known diffusion region encounters. Similarly, when provided with an interesting auroral structure the method highlights the same structure observed from an adjacent location and at other close time intervals. The method promises to be a useful tool to expand interesting case studies to multiple events, without requiring manual data labeling. Further, the models could be fine‐tuned with relatively small set of labeled example data to perform tasks such as classification. The embeddings can also be used as input to deep learning models, providing a key intermediary step—capturing the key features within the data.