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Transverse myelitis is the second most common symptoms in myelin oligodendrocyte antibody-associated diseases (MOGAD), causing obvious clinical manifestation. T2-hyperintense lesions mainly restricted to the gray matter in the spinal cord on axial magnetic resonance imaging, produce the H-sign, which is thought to be the typical finding of MOGAD. Contrast enhancement can be observed in some cases of myelin oligodendrocyte antibody-associated transverse myelitis (MOG-TM). However, reports on the enhancement pattern associated with the H-sign are rarely seen. In this report, we describe a case of pediatric MOG-TM in which the H-sign was observed without enhancement, while the surrounding white matter exhibited enhancement. This pattern contradicts the previously observed gray matter involvement. Then we reviewed the literatures of myelin oligodendrocyte antibody-positive myelitis to focus on the neuroimaging features and discuss the implications of our finding.

Soluble sugar content in seeds is an important quality trait of soybean. In this study, 57 quantitative trait loci (QTLs) related to soluble sugar contents in soybean seeds were collected from databases and published papers. After meta-overview-collinearity integrated analysis to refine QTL intervals, eight consensus QTLs were identified. To further verify the consensus QTLs, a population of chromosome segment substitution lines (CSSLs) was analyzed. Two lines containing fragments covering the regions of consensus QTLs and the recurrent parent were selected: one line showed high soluble sugar contents associated with a consensus QTL fragment, and the other line showed low soluble sugar contents. Transcriptome sequencing was conducted for these two lines at the early, middle, and late stages of seed development, which identified 158, 109 and 329 differentially expressed genes, respectively. Based on the analyses of re-sequencing data of the CSSLs and the consensus QTL region, three candidate genes (Glyma.19G146800, Glyma.19G122500, and Glyma.19G128500) were identified in the genetic fragments introduced from wild soybean. Sequence comparisons between the two CSSL parents SN14 and ZYD00006 revealed a single nucleotide polymorphism (SNP) mutation in the coding sequence of Glyma.19G122500, causing a non-synonymous mutation in the amino acid sequence that affected the predicted protein structure. A Kompetitive allele-specific PCR (KASP) marker was developed based on this SNP and used to evaluate the CSSLs. These results lay the foundation for further research to identify genes related to soluble sugar contents in soybean seeds and for future soybean breeding.

The determination of charged particle trajectories in collisions at the CERN Large Hadron Collider (LHC) is an important but challenging problem, especially in the high interaction density conditions expected during the future high-luminosity phase of the LHC (HL-LHC). Graph neural networks (GNNs) are a type of geometric deep learning algorithm that has successfully been applied to this task by embedding tracker data as a graph—nodes represent hits, while edges represent possible track segments—and classifying the edges as true or fake track segments. However, their study in hardware- or software-based trigger applications has been limited due to their large computational cost. In this paper, we introduce an automated translation workflow, integrated into a broader tool called hls4ml, for converting GNNs into firmware for field-programmable gate arrays (FPGAs). We use this translation tool to implement GNNs for charged particle tracking, trained using the TrackML challenge dataset, on FPGAs with designs targeting different graph sizes, task complexites, and latency/throughput requirements. This work could enable the inclusion of charged particle tracking GNNs at the trigger level for HL-LHC experiments.

In this paper, we present a cell-based delay-locked loop (DLL) with an enhanced continuous tracking range. The main contribution is a novel delay line architecture called ping-pong delay line, making it highly resilient to process and temperature variation. In such a DLL design, two cell-based delay lines are incorporated in a way that they exchange their role of command dynamically like in a ping-pong game, and therefore the joint ping-pong delay line can react to severe environmental changes over a very wide range without disruption to the system's operation. The post-layout simulation using a 90-nm complimentary metal-oxide silicon (CMOS) process technology has demonstrated its advantages. A DLL using such a feature can operate reliably even under an extremely hostile environment when the supply voltage drops from 1 to 0.9 V within a timeframe of 4us.

Reliability of an electronic device, concerning if it can function reliably over its designated lifetime in the field (such as 10 or 15 years), has become more and more important in today's safety-critical applications such as automotive electronics. Traditionally, the ageing has been performed in an offline setting where stress test has been applied to accelerate the ageing process and then a model is established to make the futuristic prediction. This kind of offline method has a drawback of not being able to take into account the factor of the unique operating condition and environment that a device could have experienced in the field. In this work, we present the first cloud-based ageing monitoring system to the best of our knowledge, for the Internet-of-Things (IoT) devices. It has many advantages. First of all, one can know of the ageing status of an IoT device remotely and continuously. Secondly, through data analysis in a cloud server, more accurate prediction can be achieved. Thirdly, an ageing hazard can be alarmed in advance before it actually strikes, and thereby pre-caution actions (such as online repair, or even call-for-maintenance request) can be taken in advance to avoid unnecessary system fatal failure. A prototype system using test chips with built-in design-for-ageing-monitoring circuitry will be demonstrated with measurement data collected through a cloud server.

Lead poisoning (LP) is less commonly encountered in emergency departments (ED). However, lead exposure still occurs, and new sources of poisoning have emerged. LP often goes unrecognized due to a low index of suspicion and nonspecific symptoms. We present a case of a 48-year-old man who had recurring abdominal pain with anemia that was misdiagnosed. His condition was initially diagnosed as nonspecific abdominal pain and acute porphyria. Acute porphyria-like symptoms with a positive urine porphyrin test result led to the misdiagnosis; testing for heme precursors in urine is the key to the differential diagnosis between LP and acute porphyria. The final definitive diagnosis of lead toxicity was confirmed based on high blood lead levels after detailed medical history taking. The lead poisoning was caused by traditional Chinese herbal pills. The abdominal pain disappeared after a course of chelating treatment. The triad for the diagnosis of lead poisoning should be a history of medicine intake, anemia with basophilic stippling, and recurrent abdominal pain.

We aimed to develop and validate a risk score to aid in the early identification of laboratory-confirmed dengue patients at high risk of severe dengue (SD) (i.e. severe plasma leakage with shock or respiratory distress, or severe bleeding or organ impairment). We retrospectively analyzed data of 1184 non-SD patients at hospital presentation and 69 SD patients before SD onset. We fit a logistic regression model using 85% of the population and converted the model coefficients to a numeric risk score. Subsequently, we validated the score using the remaining 15% of patients. Using the derivation cohort, two scoring algorithms for predicting SD were developed: models 1 (dengue illness ≤4 days) and 2 (dengue illness >4 days). In model 1, we identified four variables: age ≥65 years, minor gastrointestinal bleeding, leukocytosis, and platelet count ≥100×10(9) cells/L. Model 1 (ranging from -2 to +6 points) showed good discrimination between SD and non-SD, with an area under the receiver operating characteristic curve (AUC) of 0.848 (95% confidence interval [CI], 0.771-0.924). The optimal cutoff value for model 1 was 1 point, with a sensitivity and specificity for predicting SD of 70.3% and 90.6%, respectively. In model 2 (ranging from 0 to +3 points), significant predictors were age ≥65 years and leukocytosis. Model 2 showed an AUC of 0.859 (95% CI, 0.756-0.963), with an optimal cutoff value of 1 point (sensitivity, 80.3%; specificity, 85.8%). The median interval from hospital presentation to SD was 1 day. This finding underscores the importance of close monitoring, timely resuscitation of shock including intravenous fluid adjustment and early correction of dengue-related complications to prevent the progressive dengue severity. In the validation data, AUCs of 0.904 (95% CI, 0.825-0.983) and 0.917 (95% CI, 0.833-1.0) in models 1 and 2, respectively, were achieved. The observed SD rates (in both cohorts) were 50% for those with a score of ≥2 points, irrespective of the day of illness onset, suggesting that our simple risk score can be easily implemented in resource-limited countries for early prediction of dengue patients at risk of SD provided that they have rapid dengue confirmed tests. For patients with other acute febrile illnesses or bacterial infections usually have SD risk score of >1. Thus, these scoring algorithms cannot totally replace good clinical judgement of the physician, and most importantly, early differentiating dengue from other febrile illnesses is critical for appropriate monitoring and management.

Scrub typhus is a clinically important endemic disease in Taiwan. The aims of this study were to analyze the clinical manifestations, laboratory data and complications of pediatric scrub typhus in eastern Taiwan. Patients and Methods: We searched medical records for all patients with scrub typhus who were hospitalized between 1992 and 2002 at the Taitung branch of Mackay Memorial Hospital, Taiwan. Records of children under the age of 18 with a confirmed diagnosis were selected for retrospective review. Results: During the study period, 145 patients fulfilled the diagnostic criteria for scrub typhus, of whom 106 (73%) were adults and 39 (27%) were children. The mean age of the children was 7.6 ± 4.6 years. The most common clinical manifestations of pediatric scrub typhus were fever (n = 39; 100%), cough (n = 28; 72%), anorexia (72%), eschar (69%), chill (67%) and lymphadenopathy (64%). The most common complications were hepatic dysfunction (77%) and pneumonitis (54%). Three children (8%) required intensive care, but the overall survival rate was 97%. One child died with multi-organ failure within 8 hours after admission. Conclusion: Scrub typhus should be considered in children with fever and hepatic dysfunction, particularly in those with a history of environmental exposure in an endemic area for scrub typhus. The presence of an eschar offers an important diagnostic clue, but not for all cases. Children with scrub typhus may develop serious complications and may even die if appropriate treatment is not given. Doxycycline is an effective antibiotic for pediatric scrub typhus in Taiwan.

Simultaneous Localization and Mapping (SLAM) is an important technique for robotic system navigation. Due to the high complexity of the algorithm, SLAM usually needs long computational time or large amount of memory to achieve accurate results. In this paper, we present a lightweight Rao-Blackwellized particle filter- (RBPF-) based SLAM algorithm for indoor environments, which uses line segments extracted from the laser range finder as the fundamental map structure so as to reduce the memory usage. Since most major structures of indoor environments are usually orthogonal to each other, we can also efficiently increase the accuracy and reduce the complexity of our algorithm by exploiting this orthogonal property of line segments, that is, we treat line segments that are parallel or perpendicular to each other in a special way when calculating the importance weight of each particle. Experimental results shows that our work is capable of drawing maps in complex indoor environments, needing only very low amount of memory and much less computational time as compared to other grid map-based RBPF SLAM algorithms.