Miracle-dz/UniFAR-FTUs huggingface dataset:
OFIDS : Online Learning-Enabled and Fingerprint-Based Intrusion Detection System in Controller Area Networks

As a widely used industrial field bus, the controller area network (CAN) lacks security mechanisms (e.g., encryption and authentication) and is vulnerable to security attacks (e.g., masquerade). A fingerprint-based intrusion detection system (IDS) in CAN networks can detect masquerade attacks by scanning the unique clock signals of CAN devices. However, most state-of-the-art fingerprint-based IDSs commonly use an analog-to-digital converter module with a low frequency of 60 MHz to sample CAN signals, lowering the detection accuracy of fingerprint-based IDSs. In addition, almost all fingerprint-based IDSs are trained offline and then detected online, ignoring that system clock signals of hardware change over time, resulting in degraded detection performance. This paper proposes an online learning-enabled and fingerprint-based IDS (OFIDS) in CAN networks to increase the sampling frequency, shorten the detection response time, and increase the detection accuracy. OFIDS uses a high-speed comparator (i.e., TLV3501) and FPGA (i.e., Xilinx ZYNQ-7010) to sample the CAN_High signal, achieving a low sampling delay time of 4.5 ns and a high sampling frequency of 1 GHz. The self-adaptability of the backpropagation neural network is taken advantage of and used to train the OFIDS model with a detection accuracy of 99.9992%. OFIDS is deployed to a CAN network prototype with five CAN devices (i.e., two Arduino UNO boards and three STM32 microcontrollers) and a real vehicle. Experimental results show that OFIDS can achieve at least 99.99% detection accuracy within 0. 18μs in a CAN network prototype and can achieve 98% detection accuracy in a real vehicle.
A Novel Reflection-Mode Fabry–Perot Cavity Antenna With Broadband High Gain and Large Beam-Scanning Angle by Janus Partially Reflective Surface

Operational mechanism and design methodology of a novel reflection-mode (R-mode) Fabry–Perot cavity antenna (FPCA) are proposed in this article. Unlike common transmissive-mode (T-mode) FPCAs, the R-mode one places the feed antenna outside the cavity and introduces a Janus partially reflective surface (PRS), reducing the coupling between the feed and the FP cavity, while obtaining flexible displacement freedom of the feed to achieve a large beam scanning angle. The proposed R-mode FPCA employs a compact triple-layered Janus PRS, a simple ground plane, and a linearly polarized microstrip feed. The Janus PRS is applied to achieve bidirectional asymmetric transmission from the outside to the inside of the cavity to ensure the excitation efficiency and gain enhancement. In addition, a beam scanning model is proposed to obtain the spatial position of the feed and the maximum beam scanning angle under the specific antenna size. Finally, a proof-of-concept prototype is designed, fabricated, and measured at X-band. The measurement results agree well with the simulation, the 3 dB gain bandwidth of 19.7% is achieved. The peak gain in this range is 17.35 dBi and a large 3-D beam scanning range of [−35°, 35°] is also obtained.
MPC-Based Flux Weakening Control for Induction Motor Drive With DTC for Electric Vehicles

Induction motors require high speed (over the rated speed) in working areas such as electric vehicles, which is achieved through flux weakening control. A new flux weakening control approach for a direct torque controlled induction motor operating at high speeds is recommended in this article. The proposed model predictive control (MPC) based flux weakening strategy enhanced criteria such as time to reach steady state, ripple, and so on, in addition to operating the induction motor over its nominal speed. The induction motor has been driven with direct torque control (DTC) in the flux weakening study because it has the least dependence on the parameters and can react more quickly to torque/speed changes. DTC controlled induction motor includes features such as being able to adapt quickly to changes in torque/speed references, low dependency on system parameters, reaching high speeds, time to reach steady-state, and low steady-state error using the proposed MPC-based flux weakening control.
Improved hemophagocytic lymphohistiocytosis index predicts prognosis of adult Epstein-Barr virus-associated HLH patients

Abstract Background Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (EBV-HLH) is a common subtype of HLH with heterogeneous clinical presentations from self-limited to death, of which adults are worse than children. Objective To establish predictors of mortality risk in adult EBV-HLH patients for timely and appropriate treatment. Methods Patients with confirmed EBV-HLH admitted to Beijing Friendship Hospital from January 2015 to December 2019 were enrolled and statistical analysis of their laboratory test results was performed. Results Among 246 adult patients with EBV-HLH, the deceased were older (p < 0.05), with fewer blood cells (p < 0.05), poorer renal function (p < 0.01), higher levels of procalcitonin (PCT) (p < 0.01), as well as soluble interleukin-2 receptor (sCD25) (p < 0.01). The overall median survival time of patients was 135 days, 87 days for patients without transplantation and 294 days with transplantation (p < 0.001). A combined index of sCD25, PCT, and estimated glomerular filtration rate (eGFR) was obtained to predict prognosis, named the Improved HLH index (IH index), and patients were divided into three groups meeting IH- (i.e. sCD25 ≤ 18,000 pg/mL, PCT ≤ 1.8 ng/mL, eGFR ≥ 90 mL/min/1.73m2), IH1+ (i.e. only sCD25 > 18,000 pg/mL or only eGFR < 90 mL/min/1.73m2), and IH2+ (i.e. the rest), respectively. In patients with the HScore ≥ 169 or meeting HLH-04, those meeting IH2+ had significantly worse prognoses than those who met IH1+ or IH- (p < 0.001). In the group meeting IH + or IH2+, patients who received allo-HSCT had better prognoses than those who did not (p < 0.05), but there was still a significant difference in prognosis among the three groups in transplanted patients (p < 0.001). Conclusion The IH index can early identify adult patients with a poor prognosis of EBV-HLH, initiating timely and appropriate treatment. KEY MESSAGES A combined index of sCD25, PCT, and eGFR was obtained to predict prognosis, named the Improved Hemophagocytic Lymphohistiocytosis index (IH index). IH index can early identify adult patients with a poor prognosis of EBV-HLH, initiating timely and appropriate treatment.
The Factors Driving the Consumer Purchasing Intentions in Social Commerce

The traditional concept of e-commerce has gradually shifted to social commerce due to the faster integration of social media into the traditional e-commerce environment. The understanding of the determinants and reasons accounting for the acceptance of social commerce among the people is critical to practitioners and scholars alike to properly implement social media strategies to drive up social commerce purchases. This study thus examined the intention to purchase in social commerce among Chinese citizens based on the Technology Acceptance Model (TAM) and Social Exchange Theory (SET). The data (632 valid responses) generated through a research questionnaire was analyzed by the use of structural equation modeling (SEM) aided by AMOS statistical software. The results indicate that trusting beliefs such as trust in social networks, the integrity of the seller, and the benevolence of the seller were significant predictors of the intention to engage in social commerce purchase intention. However, the competency of the seller was not a significant determinant of the intention to purchase in social commerce. Other results showed that the consumer experience in social commerce was significant in predicting the trust in social networks, the integrity of the seller, the competency of the seller, and the benevolence of the seller in social commerce interaction. The validations of the significant impact of consumer experience on the four-trusting belief factors (trust in social networks, the integrity of the seller, competency of the seller, and benevolence of the seller) are among the major contributions of this study to the e-commerce and social commerce literature. Practical and research implications are discussed.
Laser vibrometry exploitation for vehicle identification

Vibration signatures sensed from distant vehicles using laser vibrometry systems provide valuable information that may be used to help identify key vehicle features such as engine type, engine speed, and number of cylinders. Through the use of physics models of the vibration phenomenology, features are chosen to support classification algorithms. Various individual exploitation algorithms were developed using these models to classify vibration signatures into engine type (piston vs. turbine), engine configuration (Inline 4 vs. Inline 6 vs. V6 vs. V8 vs. V12) and vehicle type. The results of these algorithms will be presented for an 8 class problem. Finally, the benefits of using a factor graph representation to link these independent algorithms together will be presented which constructs a classification hierarchy for the vibration exploitation problem.
Long Noncoding RNAs in the Pathogenesis of Insulin Resistance

Insulin resistance (IR), designated as the blunted response of insulin target tissues to physiological level of insulin, plays crucial roles in the development and progression of diabetes, nonalcoholic fatty liver disease (NAFLD) and other diseases. So far, the distinct mechanism(s) of IR still needs further exploration. Long non-coding RNA (lncRNA) is a class of non-protein coding RNA molecules with a length greater than 200 nucleotides. LncRNAs are widely involved in many biological processes including cell differentiation, proliferation, apoptosis and metabolism. More recently, there has been increasing evidence that lncRNAs participated in the pathogenesis of IR, and the dysregulated lncRNA profile played important roles in the pathogenesis of metabolic diseases including obesity, diabetes and NAFLD. For example, the lncRNAs MEG3, H19, MALAT1, GAS5, lncSHGL and several other lncRNAs have been shown to regulate insulin signaling and glucose/lipid metabolism in various tissues. In this review, we briefly introduced the general features of lncRNA and the methods for lncRNA research, and then summarized and discussed the recent advances on the roles and mechanisms of lncRNAs in IR, particularly focused on liver, skeletal muscle and adipose tissues.
Hybrid Coronary Revascularization: Early Outcomes and Midterm Follow-Up in Patients Undergoing Single or Multivessel Robotic TECAB and PCI

Objective: Hybrid coronary revascularization (HCR) is the integration of sternal-sparing coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) in patients with multivessel coronary artery disease (CAD). It is traditionally performed with single-vessel bypass (left internal mammary artery [LIMA] to left anterior descending artery [LAD]) and PCI but can also be accomplished with multiple arterial grafts using bilateral IMA conduits. We sought to review our HCR experience over an 8-year period with robotic totally endoscopic coronary artery bypass (TECAB) and PCI. Methods: Of 694 patients undergoing beating-heart TECAB from August 2013 to June 2022, 306 patients were designated as intention-to-treat HCR candidates. Patients underwent PCI prior to, the same day as, or following TECAB, performed using single or bilateral IMA grafts. We retrospectively reviewed early and midterm outcomes up to 8 years in this cohort of patients. Results: The mean Society of Thoracic Surgeons predicted risk of mortality was 1.5% ± 2.5%. There were 44 patients (14%) who had ≥70% left main disease and 218 patients (71%) who had triple-vessel disease. A total of 193 patients (63%) underwent multivessel grafting (advanced HCR), with 83% bilateral IMA use. Mean operative time was 263 ± 80 min, and mean length of stay was 2.6 days. The mean number of vessels bypassed per patient was 1.7 ± 0.6. The mean number of vessels stented was 1.2 ± 0.5. Of the patients, 84% underwent TECAB first, 14% PCI first, and 2% same-day TECAB/PCI. Mortality was 0.6% (observed to expected ratio: 0.42). Early graft patency was 97% (328 of 339 grafts); LIMA-LAD patency was 98%. At 8-year follow-up (mean 37 ± 26 months), all-cause and cardiac-related mortality were 13% and 2.6%, respectively. Freedom from major adverse cardiac and cerebrovascular events was 92%. Conclusions: In patients with multivessel CAD, integrating robotic single and multivessel TECAB with PCI resulted in excellent early and midterm outcomes. In experienced hands, the robotic endoscopic approach allows the routine use of multiple arterial grafting during HCR.
Theoretical research on insulation thickness design of 66 kV AC submarine cables

With the accelerated green energy development, offshore wind power generation become more and more attractive. Currently, several types of research present that the application of array submarine cables operating at high-voltage 66 kV instead of medium-voltage 35 kV shows considerable advantages on offshore wind farm systems. Insulation thickness is one of the crucial factors for the safe and reliable operation of submarine cables. In engineering applications, a high safety margin is often maintained to ensure a low electrical field in the cable insulation. However, an excessively high insulation thickness design in submarine cables can block the heat dissipation of the conductor, lower the current-carrying capacity, and raise production costs. In this work, the theoretical design of insulation thickness for 66 kV AC submarine cable are studied based on AC and impulse breakdown test. The AC and impulse breakdown strength of XLPE insulation with various temperatures from 30°C to 90°C and thickness from 0.2 mm to 0.4 mm were carried out, respectively. The temperature coefficient under AC and impulse voltage are both obtained at around 1.10 and 1.23 by comparing the breakdown strength at 30°C and 90°C. Besides, it is found that the AC breakdown strength is increased with the temperature from 30°C to 90°C, and then decreased with the temperature further rising from 50°C to 90°C. The thickness coefficients are also obtained by fitting the AC and impulse breakdown strength of the specimens with a thickness of 0.2 mm, 0.3 mm, and 0.4 mm. Step-stress test is also carried out to calculate the life exponent and deterioration coefficient of XLPE insulation based on the inverse power model. The life exponent of the XLPE insulation is evaluated at 30°C and 90°C, which is 13.9 and 15.1, respectively. It is found that the internal maximum AC and impulse field strength that cable insulation can bear during operation are 60 kV/mm and 145 kV/mm, respectively. Finally, an appropriate insulation thickness of ~8.9 mm is recommended based on the obtained internal maximum field strength, which is considered to meet the demand for 66 kV AC submarine cable. This study could provide an experimental and theoretical reference for the thickness design of submarine cables and will be helpful for the future development of light AC submarine cables.
Design of Double Mode SAW Filters Using IDT/(100) ZnO/(111) Diamond Structure

Propagation characteristics of surface acoustic waves (SAWs) in interdigital transducers (IDT)/(100) ZnO/diamond structures are investigated in this study using the finite element method. The effects of electrodes on phase velocity, coupling coefficient, and reflectivity of SAWs in the layered structures are illustrated. The extracted coupling-of-mode parameters are then applied to calculate frequency responses of double mode SAW filters using the transmission matrix method. Simulation results show a tailored filter applicable for wideband code division multiple access systems can be achieved.
Maximum Likelihood Estimation in the Proportional Odds Model

Abstract We consider maximum likelihood estimation of the parameters in the proportional odds model with right-censored data. The estimator of the regression coefficient is shown to be asymptotically normal with efficient variance. The maximum likelihood estimator of the unknown monotonic transformation of the survival time converges uniformly at a parametric rate to the true transformation. Estimates for the standard errors of the estimated regression coefficients are obtained by differentiation of the profile likelihood and are shown to be consistent. A likelihood ratio test for the regression coefficient is also considered.
Next in Surgical Data Science: Autonomous Non-Technical Skill Assessment in Minimally Invasive Surgery Training

Background: It is well understood that surgical skills largely define patient outcomes both in Minimally Invasive Surgery (MIS) and Robot-Assisted MIS (RAMIS). Non-technical surgical skills, including stress and distraction resilience, decision-making and situation awareness also contribute significantly. Autonomous, technologically supported objective skill assessment can be efficient tools to improve patient outcomes without the need to involve expert surgeon reviewers. However, autonomous non-technical skill assessments are unstandardized and open for more research. Recently, Surgical Data Science (SDS) has become able to improve the quality of interventional healthcare with big data and data processing techniques (capture, organization, analysis and modeling of data). SDS techniques can also help to achieve autonomous non-technical surgical skill assessments. Methods: An MIS training experiment is introduced to autonomously assess non-technical skills and to analyse the workload based on sensory data (video image and force) and a self-rating questionnaire (SURG-TLX). A sensorized surgical skill training phantom and adjacent training workflow were designed to simulate a complicated Laparoscopic Cholecystectomy task; the dissection of the cholecyst’s peritonial layer and the safe clip application on the cystic artery in an uncomfortable environment. A total of 20 training sessions were recorded from 7 subjects (3 non-medicals, 2 residents, 1 expert surgeon and 1 expert MIS surgeon). Workload and learning curves were studied via SURG-TLX. For autonomous non-technical skill assessment, video image data with tracked instruments based on Channel and Spatial Reliability Tracker (CSRT) and force data were utilized. An autonomous time series classification was achieved by a Fully Convolutional Neural Network (FCN), where the class labels were provided by SURG-TLX. Results: With unpaired t-tests, significant differences were found between the two groups (medical professionals and control) in certain workload components (mental demands, physical demands, and situational stress, p<0.0001, 95% confidence interval, p<0.05 for task complexity). With paired t-tests, the learning curves of the trials were also studied; the task complexity resulted in a significant difference between the first and the second trials. Autonomous non-technical skill classification was based on the FCN by applying the tool trajectories and force data as input. This resulted in a high accuracy (85%) on temporal demands classification based on the z component of the used forces and 75% accuracy for classifying mental demands/situational stress with the x component of the used forces validated with Leave One Out Cross-Validation. Conclusions: Non-technical skills and workload components can be classified autonomously based on measured training data. SDS can be effective via automated non-technical skill assessment.
One-Step Synthesized Iron-Carbon Core-Shell Nanoparticles to Activate Persulfate for Effective Degradation of Tetrabromobisphenol A: Performance and Activation Mechanism

Tetrabromobisphenol A (TBBPA), as an emerging endocrine disrupter, has been considered one of the persistent organic contaminants in water. It is urgently necessary to develop an efficient technique for the effective removal of TBBPA from water. Herein, a one-step hydrothermal synthesis route was employed to prepare a novel iron-carbon core-shell nanoparticle (Fe@MC) for effectively activating persulfate (PS) to degrade TBBPA. Morphological and structural characterization indicated that the prepared Fe@MC had a typical core-shell structure composed of a 5 nm thick graphene-like carbon shell and a multi-valence iron core. It can be seen that 94.9% of TBBPA (10 mg/L) could be degraded within 30 min at pH = 7. This excellent catalytic activity was attributed to the synergistic effect of the porous carbon shell and a multi-valence iron core. The porous carbon shell could effectively prevent the leaching of metal ions and facilitate PS activation due to its electron transfer capability. Furthermore, numerous micro-reaction zones could be formed on the surface of Fe@MC during the rapid TBBPA removal process. Radical quenching experiments and electron paramagnetic resonance (EPR) technology indicated that reactive oxygen species (ROS), including OH, SO4−, O2−, and 1O2, were involved in the TBBPA degradation process. Based on density functional theory (DFT) calculation, the carbon atoms linked by phenolic hydroxyl groups would be more vulnerable to attack by electron-rich groups; the central carbon was cracked and hydroxylated to generate short-chain aliphatic acids. The toxicity evaluation provides clear evidence for the promising application potential of our prepared material for the efficient removal of TBBPA from water.
Multi-Scope Feature Extraction for Intracranial Aneurysm 3D Point Cloud Completion

3D point clouds are gradually becoming more widely used in the medical field, however, they are rarely used for 3D representation of intracranial vessels and aneurysms due to the time-consuming data reconstruction. In this paper, we simulate the incomplete intracranial vessels (including aneurysms) in the actual collection from different angles, then propose Multi-Scope Feature Extraction Network (MSENet) for Intracranial Aneurysm 3D Point Cloud Completion. MSENet adopts a multi-scope feature extraction encoder to extract the global features from the incomplete point cloud. This encoder utilizes different scopes to fuse the neighborhood information for each point fully. Then a folding-based decoder is applied to obtain the complete 3D shape. To enable the decoder to intuitively match the original geometric structure, we engage the original points coordinates input to perform residual linking. Finally, we merge and sample the complete but coarse point cloud from the decoder to obtain the final refined complete 3D point cloud shape. We conduct extensive experiments on both 3D intracranial aneurysm datasets and general 3D vision PCN datasets. The results demonstrate the effectiveness of the proposed method on three evaluation metrics compared to baseline: our model increases the F-score to 0.379 (+21.1%)/0.320 (+7.7%), reduces Chamfer Distance score to 0.998 (−33.8%)/0.974 (−6.4%), and reduces the Earth Mover’s Distance to 2.750 (17.8%)/2.858 (−0.8%).