Anonymous Announcement System (AAS) for electric vehicle in VANETs

Vehicular Ad Hoc Network (VANET) allows vehicles to exchange information about road and traffic conditions through wireless communications. Nevertheless, providing reliable and authenticated information without violating the user\u27s privacy seems contradictory. In this paper, we propose an Anonymous Announcement System especially designed for Electric Vehicle (EV) in VANETs to achieve the aforementioned contradictory goals. We demonstrated the feasibility of the protocol with a prototype implementation on a suitable device and a network simulation with our protocol added on top of a normal VANET

Discontiguous or Contiguous Spread Patterns Affect the Functional Staging in Patients With Sporadic Amyotrophic Lateral Sclerosis

Objective: This study aimed to investigate whether the spread pattern affects functional staging in amyotrophic lateral sclerosis (ALS). We examined the spreading patterns of disease following symptom onset and the affected regions in ALS using electromyography.Methods: This study reviewed the medical records of 103 patients with sporadic ALS in the Second Hospital of Hebei Medical University from 2012 to 2017. According to the clinical manifestation and the distribution of the affected regions on electromyography, spread patterns were classified as discontiguous or contiguous. The patients were graded according to the ALS-Milano-Torino staging (MITOS) system.Results: The clinical spread patterns were contiguous in 91.5% of patients and discontiguous in 8.5% of patients. The electrophysiological spread patterns were contiguous in 87.4% of patients and discontiguous in 12.6% of patients. Sex, age, or delay in diagnosis did not affect the clinical or electrophysiological spread patterns. No significant correlation was observed between the clinical classification and the ALS-MITOS grade, but the electrophysiological spread was significantly correlated with the ALS-MITOS.Conclusion: This study provides evidence that not all ALS patients show contiguous clinical or electrophysiological spread patterns. The electrophysiological spread pattern can affect the functional staging in ALS patients

Development and Validation of a Novel LC–MS/MS Method for Simultaneous Determination of Abiraterone and its Seven Steroidal Metabolites in Human Serum: Innovation in Separation of Diastereoisomers Without Use of a Chiral Column

Abiraterone acetate (AA), the prodrug of abiraterone, is FDA-approved for the treatment of castration-resistant prostate cancer. Abiraterone is metabolized in patients to a more potent analogue, D4A. However, we have recently reported that this analogue is further metabolized to additional metabolites in patients treated with AA. Here, we present a liquid chromatography-tandem mass spectrometry method developed to resolve and detect abiraterone and its seven metabolites in human serum using an AB Sciex Qtrap 5500 mass analyzer coupled with a Shimadzu Nexera UPLC station. Analytes and the internal standard (abiraterone-d4) were extracted from human serum using the liquid–liquid extraction procedure. The analytes were separated using a Zorbax Eclipse Plus C18 150 × 2.1 mm, 3.5 μm column at 40 °C and an isocratic mobile phase 35% A (0.1% formic acid in water), 65% B (0.1% formic acid in methanol:acetonitrile; 60:40). Electrospray ionization in positive mode was applied with multiple reaction monitoring in a total run time of 13 min. Abiraterone detection was linear in the range 2–400 ng/mL and all metabolites from 0.1–20 ng/mL. The method was validated following US FDA guidelines for bioanalytical method validation, and all the metabolite results were within the acceptance limits. Despite the similarity in structure and mass transition between the metabolites, the validated method separated all the metabolites, including diastereomers, to allow accurate identification and quantitation of each compound

Armature MMF and electromagnetic performance analysis of dual three-phase 10-pole/24-slot permanent magnet synchronous machine

Fractional-slot concentrated-winding permanent magnet synchronous machines (FSCW-PMSMs) have a good prospect of application in the drive system of electric and hybrid electric vehicles. However, the armature magnetomotive force (MMF) of FSCWPMSM contains a large number of space harmonics, which induce large magnet eddycurrent loss (ECL). To solve this problem, a dual three-phase 10-pole and 24-slot winding layout is proposed.MMFharmonic analysis shows that the 1st, 7th and 17th space-harmonic winding factors of the proposed winding can be reduced by 100%, 87% and 87% respectively, compared with a dual three-phase 10-pole and 12-slot winding. Electromagnetic performances of the proposed machine under rated sinusoidal current supply and space vector pulse-width-modulated (SVPWM) voltage supply are investigated based on 2D finite-element analysis. It is shown that the proposed machine can meet the requirement of torque and efficiency in the full speed range. Especially, magnet ECL can be reduced greatly due to the reduction of the 7th and 17th space harmonics

Chloroplast Protein 12 Expression Alters Growth and Chilling Tolerance in Tropical Forage Stylosanthes guianensis (Aublet) Sw

Stylosanthes guianensis (Aublet) Sw. is a tropical forage legume with soil acidity tolerance and excellent adaptation to infertile soils, but sensitive to chilling. To understand the molecular responses of S. guianensis to chilling, differentially expressed genes between a chilling tolerant mutant 7–1 and the wild type were identified using suppression subtractive hybridization, and eight of them were confirmed and the regulation pattern were analyzed using quantitative reverse transcription PCR (qRT-PCR). Chloroplast protein 12 (CP12) functions to regulate the Calvin cycle by forming a ternary complex with glyceraldehyde 3-phosphate dehydrogenase (GAPDH) and phosphoribulokinase (PRK). SgCP12 transcript was induced by chilling in both plants, and higher levels were observed in 7–1 than in the wild type, implying a potential role of SgCP12 in chilling tolerance. To confirm this, transgenic S. guianensis plants over-expressing or down-regulating SgCP12 were generated, respectively. Higher Fv/Fm and survival rate and lower ion leakage were observed in transgenic plants overexpressing SgCP12 as compared with the wild type after chilling treatment, while lower Fv/Fm and survival rate and higher ion leakage were found in SgCP12 antisense plants. SgCP12 overexpression plants showed promoted growth with increased plant height and fresh weight, while the antisense plants exhibited reduced growth with decreased plant height and fresh weight as compared with the wild type. The results indicated that regulation of SgCP12 expression alters plant growth and chilling tolerance in S. guianensis. In addition, higher levels of net photosynthetic rate (Pn), GAPDH and PRK activities were observed in SgCP12 overexpression transgenic plants, while lower levels in antisense plants than in the wild type under both control and chilling conditions, indicating that altered activities of GAPDH and PRK were associated with the changed Pn in transgenic S. guianensis. Our results suggest that SgCP12 regulates GAPDH and PRK activities, Pn, and chilling tolerance in S. guianensis

LAMM: Language-Assisted Multi-Modal Instruction-Tuning Dataset, Framework, and Benchmark

Large language models have become a potential pathway toward achieving artificial general intelligence. Recent works on multi-modal large language models have demonstrated their effectiveness in handling visual modalities. In this work, we extend the research of MLLMs to point clouds and present the LAMM-Dataset and LAMM-Benchmark for 2D image and 3D point cloud understanding. We also establish an extensible framework to facilitate the extension of MLLMs to additional modalities. Our main contribution is three-fold: 1) We present the LAMM-Dataset and LAMM-Benchmark, which cover almost all high-level vision tasks for 2D and 3D vision. Extensive experiments validate the effectiveness of our dataset and benchmark. 2) We demonstrate the detailed methods of constructing instruction-tuning datasets and benchmarks for MLLMs, which will enable future research on MLLMs to scale up and extend to other domains, tasks, and modalities faster. 3) We provide a primary but potential MLLM training framework optimized for modalities' extension. We also provide baseline models, comprehensive experimental observations, and analysis to accelerate future research. Codes and datasets are now available at https://github.com/OpenLAMM/LAMM.Comment: 37 pages, 33 figures. Code available at https://github.com/OpenLAMM/LAMM ; Project page: https://openlamm.github.io

Establishment and validation of a clinical nomogram model based on serum YKL-40 to predict major adverse cardiovascular events during hospitalization in patients with acute ST-segment elevation myocardial infarction

ObjectiveThis study aimed to investigate the predictive value of a clinical nomogram model based on serum YKL-40 for major adverse cardiovascular events (MACE) during hospitalization in patients with acute ST-segment elevation myocardial infarction (STEMI).MethodsIn this study, 295 STEMI patients from October 2020 to March 2023 in the Second People’s Hospital of Hefei were randomly divided into a training group (n = 206) and a validation group (n = 89). Machine learning random forest model was used to select important variables and multivariate logistic regression was included to analyze the influencing factors of in-hospital MACE in STEMI patients; a nomogram model was constructed and the discrimination, calibration, and clinical effectiveness of the model were verified.ResultsAccording to the results of random forest and multivariate analysis, we identified serum YKL-40, albumin, blood glucose, hemoglobin, LVEF, and uric acid as independent predictors of in-hospital MACE in STEMI patients. Using the above parameters to establish a nomogram, the model C-index was 0.843 (95% CI: 0.79–0.897) in the training group; the model C-index was 0.863 (95% CI: 0.789–0.936) in the validation group, with good predictive power; the AUC (0.843) in the training group was greater than the TIMI risk score (0.648), p < 0.05; and the AUC (0.863) in the validation group was greater than the TIMI risk score (0.795). The calibration curve showed good predictive values and observed values of the nomogram; the DCA results showed that the graph had a high clinical application value.ConclusionIn conclusion, we constructed and validated a nomogram based on serum YKL-40 to predict the risk of in-hospital MACE in STEMI patients. This model can provide a scientific reference for predicting the occurrence of in-hospital MACE and improving the prognosis of STEMI patients