Identifying accident causes of driver-vehicle interactions using system theoretic process analysis (STPA)

Latest generations of automobiles are gradually being equipped with technologies that have increasing automation, a trend which had led to increase in the system complexity as well as increased human-automation interactions. Failures in such complex human-automation interactions increasingly occur due to the mismatch between what operators know about the system and what the designers expect operators to know. Causes of road accidents also change due to role shift of drivers from controlling the vehicle to monitoring the in-vehicle controllers. Failures in such complex systems involving human-automation interactions increasingly occur due to the emergent behaviours from the interactions, and are less likely due to reliability of individual components. Traditional safety analysis methods fall short in identifying such emergent failures. This paper focuses on using a systems thinking inspired safety analysis method called System Theoretic Process Analysis (STPA) to identify potential failures. The analysis focuses on a SAE Level-4 Vehicle that is in the development phase, and is controlled partially by a safety driver and its built-in Autonomous Driving System (ADS). The analysis yields that while increase in complexity does increase system functionality, it also brings a challenge to evaluate the safety of the system and potentially causes incorrect human-automation interactions, leading to an accident. After the possible inadequate driver-vehicle interactions are identified by STPA, corresponding requirements were then proposed in order to avoid the unsafe behaviour and thus preventing the hazards

Temperature dependence of angular momentum transport across interfaces

Angular momentum transport in magnetic multilayered structures plays a central role in spintronic physics and devices. The angular momentum currents or spin currents are carried by either quasi-particles such as electrons and magnons, or by macroscopic order parameters such as local magnetization of ferromagnets. Based on the generic interface exchange interaction, we develop a microscopic theory that describes interfacial spin conductance for various interfaces among non-magnetic metals, ferromagnetic and antiferromagnetic insulators. Spin conductance and its temperature dependence are obtained for different spin batteries including spin pumping, temperature gradient and spin Hall effect. As an application of our theory, we calculate the spin current in a trilayer made of a ferromagnetic insulator, an antiferromagnetic insulator and a non-magnetic heavy metal. The calculated results on the temperature dependence of spin conductance quantitatively agree with the existing experiments

Concurrent nephrotic syndrome and acute renal failure caused by chronic lymphocytic leukemia (CLL): a case report and literature review

Kidney injury associated with lymphocytic leukemia (CLL) is typically caused by direct tumor infiltration which occasionally results in acute renal failure. Glomerular involvement presenting as proteinuria or even nephrotic syndrome is exceptionally rare. Here we report a case of 54-year-old male CLL patient with nephrotic syndrome and renal failure. The lymph node biopsy confirmed that the patients had CLL with remarkable immunoglobulin light chain amyloid deposition. The renal biopsy demonstrated the concurrence of AL amyloidosis and neoplastic infiltration. Combined treatment of fludarabine, cyclophosphamide and rituximab resulted in remission of CLL, as well as the renal disfunction and nephrotic syndrome, without recurrence during a 12-month follow-up. To our knowledge, this is the first case of CLL patient showing the nephrotic syndrome and acute renal failure caused by AL amyloidosis and neoplastic infiltration. Though AL amyloidosis caused by plasma cell dyscrasia usually responses poorly to chemotherapy, this patient exhibited a satisfactory clinical outcome due to successful inhibition of the production of amylodogenic light chains by combined chemotherapy

High-resolution characterization of the coagulation and drying processes of whole blood based on optical coherence tomography

Introduction: Escaping whole blood exhibits biochemical and physical coupled mechanisms such as coagulation and drying. However, there is no method for simultaneously monitoring the coagulation and drying procedure.Methods: In this study, a new method based on optical coherence tomography (OCT) combined with speckle variance and thickness is presented for simultaneously capturing spatially high-resolved characteristics of coagulation and drying of whole blood during the procedure. Deep learning based on a convolutional neural network (CNN) is employed for collecting OCT images with a resolution of micron order and quantitatively obtaining pixel-wise information of whole blood.Results and discussion: Then, the pixel-wise thickness map provides high-resolved temporal–spatial dynamics of whole blood during the drying procedure, and the corresponding speckle variance can uncover information of whole blood coagulation. The results demonstrate that coagulation and drying of whole blood have spatially inhomogeneous features. This method could provide the potential for revealing the coupling mechanism between coagulation and drying

Infrared spectroscopy of small-molecule endofullerenes

Hydrogen is one of the few molecules which has been incarcerated in the molecular cage of C$_{60}$ and forms endohedral supramolecular complex H$_2$@C$_{60}$. In this confinement hydrogen acquires new properties. Its translational motion becomes quantized and is correlated with its rotations. We applied infrared spectroscopy to study the dynamics of hydrogen isotopologs H$_2$, D$_2$ and HD incarcerated in C$_{60}$. The translational and rotational modes appear as side bands to the hydrogen vibrational mode in the mid infrared part of the absorption spectrum. Because of the large mass difference of hydrogen and C$_{60}$ and the high symmetry of C$_{60}$ the problem is identical to a problem of a vibrating rotor moving in a three-dimensional spherical potential. The translational motion within the C$_{60}$ cavity breaks the inversion symmetry and induces optical activity of H$_2$. We derive potential, rotational, vibrational and dipole moment parameters from the analysis of the infrared absorption spectra. Our results were used to derive the parameters of a pairwise additive five-dimensional potential energy surface for H$_2$@C$_{60}$. The same parameters were used to predict H$_2$ energies inside C$_{70}$[Xu et al., J. Chem. Phys., {\bf 130}, 224306 (2009)]. We compare the predicted energies and the low temperature infrared absorption spectra of H$_2$@C$_{70}$.Comment: Updated author lis

A large area, high counting rate micromegas-based neutron detector for BNCT

Beam monitoring and evaluation are very important to boron neutron capture therapy (BNCT), and a variety of detectors have been developed for these applications. However, most of the detectors used in BNCT only have a small detection area, leading to the inconvenience of the full-scale 2-D measurement of the beam. Based on micromegas technology, we designed a neutron detector with large detection area and high counting rate. This detector has a detection area of 288 mm multiples 288 mm and can measure thermal, epithermal, and fast neutrons with different detector settings. The BNCT experiments demonstrated that this detector has a very good 2-D imaging performance for the thermal, epithermal, fast neutron and gamma components, a highest counting rate of 94 kHz/channel, and a good linearity response to the beam power. Additionally, the flux fraction of each component can be calculated based on the measurement results. The Am-Be neutron source experiment indicates that this detector has a spatial resolution of approximately 1.4 mm, meeting the requirements of applications in BNCT. It is evident that this micromegas-based neutron detector with a large area and high counting rate capability has great development prospects in BNCT beam monitoring and evaluation applications

Predictive nomogram model for major adverse kidney events within 30 days in sepsis patients with type 2 diabetes mellitus

BackgroundIn sepsis patients, Type 2 Diabetes Mellitus (T2DM) was associated with an increased risk of kidney injury. Furthermore, kidney damage is among the dangerous complications, with a high mortality rate in sepsis patients. However, the underlying predictive model on the prediction of major adverse kidney events within 30 days (MAKE30) in sepsis patients with T2DM has not been reported by any study.MethodsA total of 406 sepsis patients with T2DM were retrospectively enrolled and divided into a non-MAKE30 group (261 cases) and a MAKE30 group (145 cases). In sepsis patients with T2DM, univariate and multivariate logistic regression analyses were conducted to identify independent predictors of MAKE30. Based on the findings of multivariate logistic regression analysis, the corresponding nomogram was constructed. The nomogram was evaluated using the calibration curve, Receiver Operating Characteristic (ROC) curve, and decision curve analysis. A composite of death, new Renal Replacement Therapy (RRT), or Persistent Renal Dysfunction (PRD) comprised MAKE30. Finally, subgroup analyses of the nomogram for 30-day mortality, new RRT, and PRD were performed.ResultsIn sepsis patients with T2DM, Mean Arterial Pressure (MAP), Platelet (PLT), cystatin C, High-Density Lipoprotein (HDL), and apolipoprotein E (apoE) were independent predictors for MAKE30. According to the ROC curve, calibration curve, and decision curve analysis, the nomogram model based on those predictors had satisfactory discrimination (AUC = 0.916), good calibration, and clinical application. Additionally, in sepsis patients with T2DM, the nomogram model exhibited a high ability to predict the occurrence of 30-day mortality (AUC = 0.822), new RRT (AUC = 0.874), and PRD (AUC = 0.801).ConclusionThe nomogram model, which is available within 24 hours after admission, had a robust and accurate assessment for the MAKE30 occurrence, and it provided information to better manage sepsis patients with T2DM