Understanding the Automotive Pedal Usage and Foot Movement Characteristics of Older Drivers

The purpose of this study was to understand the pedal usage characteristics of older drivers in various driving tasks using an instrumented vehicle. This study stemmed from the prevalence of the pedal application errors (PAEs) and the older drivers’overrepresentation in crashes caused by PAEs. With the population increasing and becoming older, it is estimated that in 2020 there will be 40 million drivers over the age of 65 in the United States. Compared with their younger counterparts, older drivers are facing declining cognitive and physical abilities, such as impaired vision, slower reaction time and diminishing range of limb motion. Because these abilities are closely associated both with the driving task and the ability to recover from a crash, older drivers are overrepresented in vehicle crash involvement rate, and they are especially vulnerable to injuries caused by the crashes. Pedal misapplication crash is a type of crash preceded by a driver mistakenly pressing the accelerator pedal. Recently, the National Highway Traffic Safety Administration issued a report on PAE. The report reveals that older drivers are overrepresented in pedal misapplication crashes and that several driving tasks are overrepresented, such as emergency stopping, parking lot maneuvers and reaching out of the vehicle to interact with a curb-side device such as a card reader, mailbox, or ATM. Existing research has investigated the PAEs from different perspectives, but questions remain as to why older drivers are more likely to commit PAEs in these driving tasks. The current study investigated the pedal usage characteristics of 26 older drivers in driving tasks, such as startle-braking, forward parking and reaching out from the vehicle, which are scenarios associated with higher risk of PAEs. Ten stopping tasks were also investigated as baseline tasks. The study was conducted on-road using an instrumented vehicle. The data collected by the instrumented vehicle included pedal travel (potentiometer), force applied on the pedals (Tekscan sensor), and video recordings of each driver’s upper body and his or her foot movement. The study findings include the following: a) There are significantly positive correlations between a driver’s stature and the percent of foot pivoting, as well as between the shoe length and the percent of foot pivoting, which means the taller the driver or the longer the driver’s shoe, the more likely the driver will use foot pivoting instead of foot lifting in the baseline stopping tasks; b) In the startle-braking task, the driver is more likely to use foot lifting than that in the baseline tasks; c) The foot movement strategy is not found to affect lateral foot placement in either the baseline stopping tasks or the startle-braking task; d) When reaching out of the driver’s window to swipe a card at a card reader, the lateral foot placement on the brake pedal will bias rightward, compared with the lateral foot placement prior to reaching out; e) Approaching a gated access or parking in a dark, relatively confined parking space does not significantly slow down a driver’ foot transfer from the accelerator pedal to the brake pedal; f) Stature of a driver does not significantly affect the time required to successfully complete a card-swiping task. A driver’s pedal operation characteristics are associated with many factors, among which four factors are identified to be relevant to the driver’s pedal operation: stature, shoe length, startle stimuli and reaching out of the driver’s window. To identify the direct causes of PAEs, future research should investigate the pedal operation characteristics in a more controlled environment. For example, an eye-tracking device can be used to study the relationship between gaze direction and foot movement. Other driving scenarios, such as reversing, should be studied as well. In addition, a study with a larger sample size and novice drivers is necessary to validate the findings of the current study and to understand the PAEs among the population with little driving experience. The current study has both clinical and engineering implications. For occupational therapists and driving rehabilitation specialists, factors such as stature, leg length, footwear, vehicle type and pedal configuration may provide information about driver’s foot behaviors. For example, drivers with flat-soled shoes may tend to use foot lifting and drivers with wedged shoes may tend to use foot pivoting. Drivers with very wide shoes may get the shoe caught under the brake pedal when pivoting from the accelerator pedal to the brake pedal. Drivers with short leg length may be able to use foot pivoting when driving a sports vehicle, but they would have to use foot lifting when driving a large truck. Drivers tend to use foot lifting when the pedals are higher above from the vehicle floor and drivers tend to use foot pivoting when the pedals are lower above the vehicle floor. An in-clinic test of a driver’s lower extremity functions prior to on-road assessment helps to select the appropriate test vehicles. For example, it is recommended that shorter drivers with weaker lower extremity functions use vehicles of which the pedals are lower above the vehicle floor. To reduce the chance of a driver’s foot slipping off the brake pedal, engineers should consider redesigning the pedal pad to increase the friction coefficient of shoe-pedal contact. For example, using tread width of 2mm produces higher friction values. In addition, Automatic Vehicle Identification can be implemented so that the drivers do not have to reach out of the window to swipe card and to enter a gated access. Other driver assistance systems such as Autonomous Emergency Braking and Automated Parking System can either mitigate the damage or eliminate the chance of a human error

Inductive Data Types Based on Fibrations Theory in Programming

Traditional methods including algebra and category theory have some deficiencies in analyzing semantics properties and describing inductive rules of inductive data types, we present a method based on Fibrations theory aiming at those questions above. We systematically analyze some basic logical structures of inductive data types about a fibration such as re-indexing functor, truth functor and comprehension functor, make semantics models of non-indexed fibration, single-sorted indexed fibration and many-sorted indexed fibration respectively. On this basis, we thoroughly discuss semantics properties of fibred, single-sorted indexed and many-sorted indexed inductive data types, and abstractly describe their inductive rules with universality. Furthermore, we briefly introduce applications of the three inductive dana types for analyzing semantics properties and describing inductive rules based on Fibrations theory via some examples. Compared with traditional methods, our works have the following three advantages. Firstly, brief descriptions and flexible expansibility of Fibrations theory can analyze semantics properties of inductive data types accurately, whose semantics are computed automatically. Secondly, superior abstractness of Fibrations theory does not rely on particular computing environments to depict inductive rules of inductive data types with universality. Thirdly, its rigorousness and consistence provide sound basis for testing and maintenance of software development

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Low FT3/FT4 Ratio Is Linked to Poor Prognosis of Acute Myocardial Infarction in Euthyroid Patients with Type 2 Diabetes Mellitus

This is an observational, retrospective, single-center study aimed to determine whether the free triiodothyronine (FT3) to free thyroxine (FT4) ratio was related to acute myocardial infarction (AMI) prognosis in individuals with type 2 diabetes mellitus (T2DM). A total of 294 euthyroid T2DM patients with new-onset AMI were enrolled. FT3/FT4 ratio tertiles were used to categorize patients into Group 1 (FT3/FT4 ≥ 4.3), Group 2 (3.5 ≤ FT3/FT4 < 4.3), and Group 3 (FT3/FT4 < 3.5). Major adverse cardiac events (MACE), including nonfatal myocardial infarction, target vessel revascularization (TVR), and cardiac mortality, served as the primary endpoint. Group 3 demonstrated a considerably higher incidence of MACE than the other two groups over the average follow-up duration of 21 ± 6.5 months (all p < 0.001). Multivariable Cox regression analysis showed that a low FT3/FT4 ratio was an independent risk factor for MACE after AMI (Group 1 as a reference; Group 2: hazard ratio [HR] 1.275, 95% confidence interval [CI]: 0.563–2.889, p = 0.561; Group 3: HR 2.456, 95% CI: 1.105–5.459, p = 0.027). Moreover, the area under the receiver-operating characteristic curve (AUC) indicates a good predictive value of FT3/FT4 ratio for MACE (AUC = 0.70). Therefore, in T2DM patients with AMI, a low FT3/FT4 ratio was strongly linked to poor prognosis

Desertification Extraction Based on a Microwave Backscattering Contribution Decomposition Model at the Dry Bottom of the Aral Sea

The fine particles produced during the desertification process provide a rich material source for sand and dust activities. Accurately locating the desertified areas is a prerequisite for human intervention in sand and dust activities. In arid and semi-arid regions, due to very sparse vegetation coverage, the microwave surface scattering model is very suitable for describing the variation of topsoil property during the process of desertification. However, the microwave backscattering coefficient (MBC) trend of the soil during the desertification process is still unclear now. Moreover, the MBC of a resolution unit usually involves the contribution of soil and vegetation. These problems seriously limit the application of microwave remote sensing technology in desertification identification. In this paper, we studied the soil MBC change trend during the desertification process and proposed a microwave backscattering contribution decomposition (MBCD) model to estimate the soil MBC of a resolution unit. Furthermore, a simple microwave backscattering threshold (SMSBT) model was established to describe the severity of desertification. The MBCD and SMSBT models were verified qualitatively through landscape photos of sampling points from a field survey in November 2018. The results showed that the MBC would gradually decline with the deepening degree of desertification. The MBCD model and the corresponding least squares method can be used to estimate the soil MBC accurately, and the SMSBT model can accurately distinguish different degrees of desertification. The results of desertification classification showed that more than 68% of the dry bottom of the Aral Sea is suffering from different degrees of desertification

UMI-77 Modulates the Complement Cascade Pathway and Inhibits Inflammatory Factor Storm in Sepsis Based on TMT Proteomics and Inflammation Array Glass Chip

Sepsis is a systemic inflammatory response syndrome caused by infection, which has no specific drug at present. UMI-77 can significantly improve the survival rate of septic mice; the detailed role of UMI-77 and its underlying mechanisms in sepsis are not clear. Inflammation array glass chip and proteomic analyses were performed to elucidate the latent mechanism of UMI-77 in the treatment of sepsis. The results showed that 7.0 mg/kg UMI-77 improved the 5 day survival rate in septic mice compared to the LPS group (60.964 vs 9.779%) and ameliorated the pathological conditions. Inflammation array glass chip analysis showed that sepsis treatment with UMI-77 may eventually through the suppression of the characteristic inflammatory storm-related cytokines such as KC, RANTES, LIX, IL-6, eotaxin, TARC, IL-1β, and so on. Proteomics analysis showed that 213 differential expression proteins and complement and coagulation cascades were significantly associated with the process for the UMI-77 treatment of sepsis. The top 10 proteins including Apoa2, Tgfb1, Serpinc1, Vtn, Apoa4, Cat, Hp, Serpinf2, Fgb, and Serpine1 were identified and verified, which play important roles in the mechanism of UMI-77 in the treatment of sepsis. Our findings indicate that UMI-77 exerts an antisepsis effect by modulating the complement cascade pathway and inhibiting inflammatory storm factors

UMI-77 Modulates the Complement Cascade Pathway and Inhibits Inflammatory Factor Storm in Sepsis Based on TMT Proteomics and Inflammation Array Glass Chip

Sepsis is a systemic inflammatory response syndrome caused by infection, which has no specific drug at present. UMI-77 can significantly improve the survival rate of septic mice; the detailed role of UMI-77 and its underlying mechanisms in sepsis are not clear. Inflammation array glass chip and proteomic analyses were performed to elucidate the latent mechanism of UMI-77 in the treatment of sepsis. The results showed that 7.0 mg/kg UMI-77 improved the 5 day survival rate in septic mice compared to the LPS group (60.964 vs 9.779%) and ameliorated the pathological conditions. Inflammation array glass chip analysis showed that sepsis treatment with UMI-77 may eventually through the suppression of the characteristic inflammatory storm-related cytokines such as KC, RANTES, LIX, IL-6, eotaxin, TARC, IL-1β, and so on. Proteomics analysis showed that 213 differential expression proteins and complement and coagulation cascades were significantly associated with the process for the UMI-77 treatment of sepsis. The top 10 proteins including Apoa2, Tgfb1, Serpinc1, Vtn, Apoa4, Cat, Hp, Serpinf2, Fgb, and Serpine1 were identified and verified, which play important roles in the mechanism of UMI-77 in the treatment of sepsis. Our findings indicate that UMI-77 exerts an antisepsis effect by modulating the complement cascade pathway and inhibiting inflammatory storm factors