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Geometric map features, such as line segments and planes, are receiving increasing attention due to their advantages in simultaneous localization and mapping applications. However, large structures in different environments are very likely to appear repeatedly in several consecutive time steps, resulting in redundant features in the final map. These redundant features should be properly fused, in order to avoid ambiguity and reduce the computation load. In this paper, three criteria are proposed to evaluate the closeness between any two features extracted at two different times, in terms of their included angle, feature circle overlapping and relative distance. These criteria determine whether any two features should be fused in the mapping process. Using the three criteria, all features in the global map are categorized into different clusters with distinct labels, and a fused feature is then generated for each cluster by means of least squares fitting. Two competing methods are employed for comparative verification. The comparison results indicate that using the commonly used KITTI dataset and the commercial software PreScan, the proposed feature fusion method outperforms the competing methods in terms of conciseness and accuracy.

In this paper, an economy-oriented car-following control (EOCFC) strategy is proposed for electric vehicles in car-following scenarios. Specifically, a controller based on model predictive control (MPC) is developed to optimize the host vehicle’s speed for better energy economy while ensuring good car-following performance and ride comfort. The vehicle’s energy consumption is accurately quantified in the form of demand power, which is incorporated in the cost function for energy optimization. The proposed EOCFC strategy is evaluated using three standard test cycles, i.e., New European Driving Cycle (NEDC), Urban Dynamometer Driving Schedule (UDDS) and Worldwide Harmonized Light Vehicles Test Cycle (WLTC), in comparison with a typical multi-objective adaptive cruise control strategy. The evaluation results demonstrate that the proposed EOCFC improves the energy economy of the host vehicle by 0.53%, 3.33% and 1.51%, under the NEDC, UDDS and WLTC test cycles respectively.

Regenerative braking is the key to achieve efficient use of energy and extend the driving range in pure electric vehicles. This study proposes a new predictive control method integrating adaptive cubic exponential prediction and dynamic programming to address the problem of efficient energy recovery during the regular braking process of four-wheel pure electric vehicles. The method considers the dynamic characteristics of an electro-hydraulic combined braking system. The adaptive cubic exponential prediction is adopted to predict the vehicle velocity and braking intensity. The dynamic programming is employed to optimize the motor braking torques and wheel cylinder pressures under the condition of braking regulations, road constraints, and vehicle constraints. To verify the effectiveness of the new predictive control method, the ideal and multi-stage braking force distribution methods are employed for comparison. The results confirm that, under gradual braking conditions, the energy recovery efficiency achieved via the proposed method is improved by 1.55% and 6.40% considering the ideal and multi-stage braking force distribution methods, respectively.

The existing energy management strategies for four-wheel-drive electric vehicles only take into account the vehicle energy consumption under static adhesion constraints. However, the front and rear axle loads transfer under dynamic conditions lead to the variations of vehicle adhesion characteristics, which results in the changes of vehicle energy consumptions. In this paper, a multi-objective optimal torque distribution strategy is proposed, taking into account the front and rear axle load transfer and the variations of adhesion characteristics. The advantages of the proposed strategy are verified through simulation studies in terms of vehicle energy consumption and wheel slip ratio, in comparison with the average torque distribution strategy and the optimal torque distribution strategy based on Sequential Quadratic Programming Algorithm. The simulation results show that the economy performance of the proposed strategy is superior to those of the competing methods. Furthermore, the proposed strategy provides good power performance and eliminates excessive wheel slip, which in turn ensures vehicle longitudinal stability and avoids energy loss resulting from frequent ASR interventions.

Adaptive cruise control (ACC) systems are designed to provide longitudinal assistance for drivers to enhance safety and reduce workload. As the core of all ACC control algorithms, the spacing policy plays a crucial role in various aspects. This paper presents a comprehensive survey on spacing policies for existing ACC solutions in the literature. The objectives of this paper are to clarify the operating mechanisms and characteristics of the common spacing policies, and to reveal their advantages and shortcomings by means of a comparative study. In this survey, the general evaluation criteria for spacing policies are first introduced. Then, the existing spacing policies are categorized into different types according to their operating mechanisms, and their characteristics are carefully reviewed and explained. A comparative study is followed to analyze the performances of five typical spacing policies in the literature, including the constant spacing policy, constant time headway, traffic flow stability, constant safety factor and human driving behavior spacing policies. The contents provided in this paper serve as a tool for understanding current ACC spacing policies, and pave the way for future ACC enhancement.

A secondary loop cooling battery thermal management system is designed, and then, a phased control strategy for adjusting the compressor speed according to the battery temperature interval is proposed. On this basis, the compressor speed as the decision variable, and the energy consumption of the compressor and the aging losses of the battery are as the optimization goals, which constitute a multi-objective optimization model, and a genetic algorithm is adopted to solve it. Under different weight coefficients, the Pareto Frontier of the energy consumption of the compressor and the aging losses of the battery are established. The simulation analysis is conducted on high speed dynamic conditions at an ambient temperature of 30 °C. The effects of coolant flow rate and compressor speed on battery pack temperature rise and temperature uniformity are analyzed. The simulation results show that the energy consumption of the phased control strategy is reduced by 10.7% compared with the traditional constant compressor speed control strategy under the same conditions. Under different weight coefficients, different simulation results and control strategies can be obtained, and results show that the maximum temperature and temperature uniformity can meet the requirements. There is a contradiction between the energy consumption of compressor and the aging losses of battery, but both them are highly sensitive. According to the Pareto Frontier curve, when the weight coefficient is 0.17, a balanced control strategy can be obtained, which can reduce the battery aging losses of 61.8% by only sacrificing 9.22% of the vehicle driving mileage.

The economy of electrified vehicles can be improved by using the motor to recover the energy released during braking. However, the vehicle's regenerative braking system (RBS) and anti-lock braking system (ABS) are not compatible, so the energy dissipated during braking cannot be recovered under emergency braking conditions. This paper employs the method of logic threshold control combined with phase plane theory to analyze the relationship between the slip rate and the braking torque during the ABS braking process and to obtain the composition rule of the braking torque required for ABS braking. Based on this rule, a control strategy to coordinate RBS and ABS when triggering ABS is proposed to improve the efficiency of braking energy recovery. Furthermore, a comparative simulation is conducted to analyze the braking performance of electrified vehicle on roads with different adhesion coefficients by adopting the proposed control strategy and the traditional control strategy. The results show that, compared with the traditional coordinated control strategy, the braking energy recovery efficiency of the proposed coordinated control strategy is improved by 23.08%-38.54%, and can effectively shorten the braking distance and braking time, with better braking performance. Therefore, this paper offers a useful theoretical reference to the design of RBS and ABS coordinated control strategies for electrified vehicles.

This study is aimed at revealing the dynamic response characteristics of a power-split hybrid electric vehicle (HEV) during the mode transition process with the engine starting. In this paper, for a hybrid powertrain system whose engine is directly connected to a compound power-split transmission, the equivalent lever method is first used to analyze the mode transition process with the engine starting. Then, based on the theoretical formulations and lookup tables, a dynamic model of the compound power-split HEV is established in detail, taking into consideration the engine ripple torque, battery-motor characteristics, dynamic meshing force between gears, and shaft spring-damping characteristics. The powertrain dynamic model is verified by a bench test. Moreover, taking the vehicle jerk and engine starting time as the evaluation indexes of the dynamic response characteristics, the influencing factors of the dynamic response characteristics in the engine starting process are analyzed comprehensively from the aspects of the engine, battery-motor, and engine starting condition. Finally, the engine starting process is synthetically optimized based on the obtained impact law of different influencing factors. The simulation results show that the synthesis optimization method can effectively reduce vehicle jerks and the engine starting time and improve driving comfort during the engine starting process.

To further improve the energy economy of a four-wheel independent drive electric vehicle (FWIDEV) in the process of vehicle stability control, in this paper, the influence of different wheel torque distributions on vehicle stability and energy economy during vehicle steering is analyzed in depth. Then the wheel torque distribution scheme when the vehicle steering is established. Combined with the economic-based torque distribution strategy applied in the straight running condition, an optimal wheel torque distribution strategy is proposed for FWIDEV to adapt different driving conditions. And the controller designed in this paper adopts hierarchical control structure. The upper controller calculate the corrective yaw moment based on the sliding mode control. The lower controller implements wheel torque distribution according to the proposed strategy. Finally, the simulation results under different driving scenarios indicate that the proposed control strategy can achieve the same effect as the conventional control strategy in terms of vehicle stability, but the energy economy is improved by about 2.4%.

Background: The incidence of congenital hypothyroidism (CH) differs significantly among different ethnicities and regions, and early differentiation of transient CH is important to avoid unnecessary prolonged treatment with L-T4. Objective: To investigate the incidence of CH based on the newborn screening program in Guangxi Zhuang Autonomous Region, China, and to analyze the predictors that might allow for an early differentiation between permanent (P) and transient (T) CH. Design and methods: Data from newborn screening program over a seven-year period (January 2009 to January 2016) at Guangxi Maternal and Child Health Hospital are analyzed. Blood samples were collected on filter paper between 3 and 7 days after birth, and TSH level was measured by time-resolved fluorescence assay. Individuals with increased TSH (TSH ≥ 8 IU/L) levels detected by newborn screening were recalled for further evaluation. Serum TSH, FT3 and FT4 were determined by electrochemiluminescence assay using venous blood samples. Diagnosis of CH is based on elevated TSH levels (>10 IU/L) and decreased FT4 levels (30 μg/day) has the highest predictive value for PCH. Earlier differentiation of PCH and TCH helps to determine appropriate treatment course.

Abstract Background Silver-Russell syndrome (SRS) is one of the imprinting disorders characterized by prenatal and postnatal growth restriction, relative macrocephaly, body asymmetry and characteristic facial features. ~ 10% of SRS cases are known to be associated with maternal uniparental disomy of chromosome 7 (UPD(7)mat). Mosaic maternal segmental UPD of 7q (UPD(7q)mat) is very rare, had only been described in one case before. Case presentation We reported a second case of mosaic segmental UPD involving 7q. The patient presented with dysmorphic features including thin and short stature, triangular face, moderate protruding forehead, relative macrocephaly, fifth toe clinodactyly and irregular teeth, meeting the clinical diagnosed criteria of SRS. This case indicated that ~ 80% of mosaic UPD(7q)mat lead to the manifestation of main phenotypes of Silver-Russell syndrome. Conclusions Our case support the notion that there are genes control postnatal growth on long arm of chromosome 7 and indicate that ~ 80% of UPD(7q)mat mosaicism level was contributed to the SRS phenotype.

For a power-split plug-in hybrid electric vehicle (PS-PHEV), the control system cannot effectively reduce jerks under some engine-starting conditions due to the pulsating torque of the engine, elastic characteristics of the transmission, battery power limitations, and the limitation of the maximum torque of the motor. To solve this problem, a dynamic torque-coordinated control method considering engine starting conditions (DTCC-ESC) is proposed in this paper. The proposed DTCC-ESC mainly includes three parts: the engine segment active control before and after engine ignition to minimize the impact of the engine ripple torque on the shocks of the powertrain system; the feedforward control of the engine starting conditions and the feedback control of the engine’s optimal target speed; and the active damping feedback compensation control for system resonance to reduce system vibrations. The results show that the proposed DTCC-ESC can effectively improve driving comfort under different engine starting conditions.

In the process of vehicle braking, braking intensity has a significant impact on vehicle comfort, and studies on this aspect have been limited. Therefore, an equivalent 4-degree-of-freedom half-vehicle model including the braking intensity influence was established in this study. Subsequently, considering braking intensity as the interference quantity that is the uncontrollable input, a model predictive control (MPC) strategy in which the vertical velocities of front body, rear body, front wheel, and rear wheel are the control targets was proposed. Based on Lyapunov’s stability theory, the stability of the MPC system was proven. Finally, a dual-loop control (DLC) strategy was used for comparison to verify the superiority of the MPC strategy. The results indicate that compared with the DLC strategy under the gradual braking condition, the root mean square of the front and rear body vertical velocities, body pitch angle, and body pitch angle velocity under the MPC strategy were all reduced by more than 70%, thus improving the ride comfort of the vehicle.

When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the environment. Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM. This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps. These map-merging approaches are classified based on their working mechanism or the type of features they deal with. The concepts and characteristics of these map-merging methods are elaborated in this review. The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.

ABSTRACT Objective Pendred syndrome (PS) is an autosomal recessive disorder characterised by sensorineural hearing loss and thyroid dyshormonogenesis. It is caused by biallelic mutations in the SLC26A4 gene encoding for pendrin. Hypothyroidism in PS can be present from birth and therefore diagnosed by neonatal screening. The aim of this study was to examine the SLC26A4 mutation spectrum and prevalence among congenital hypothyroidism (CH) patients in the Guangxi Zhuang Autonomous Region of China and to establish how frequently PS causes hearing impairment in our patients with CH. Subjects and methods Blood samples were collected from 192 CH patients in Guangxi Zhuang Autonomous Region, China, and genomic DNA was extracted from peripheral blood leukocytes. All exons of the SLC26A4 gene together with their exon-intron boundaries were screened by next-generation sequencing. Patients with SLC26A4 mutations underwent a complete audiological evaluation including otoscopic examination, audiometry and morphological evaluation of the inner ear. Results Next generation sequencing analysis of SLC26A4 in 192 CH patients revealed five different heterozygous variations in eight individuals (8/192, 4%). The prevalence of SLC26A4 mutations was 4% among studied Chinese CH. Three of the eight were diagnosed as enlargement of the vestibular aqueduct (EVA), no PS were found in our 192 CH patients. The mutations included one novel missense variant p.P469S, as well as four known missense variants, namely p.V233L, p.M147I, p.V609G and p.D661E. Of the eight patients identified with SLC26A4 variations in our study, seven patients showed normal size/location of thyroid gland, and one patients showed a decreased size one. Conclusions The prevalence of SLC26A4 pathogenic variants was 4% among studied Chinese patients with CH. Our study expanded the SLC26A4 mutation spectrum, provided the best estimation of SLC26A4 mutation rate for Chinese CH patients and indicated the rarity of PS as a cause of CH.

To accurately estimate the state of charge (SOC) of lithium-ion power batteries in the event of errors in the battery model or unknown external noise, an SOC estimation method based on the H-infinity filter (HIF) algorithm is proposed in this paper. Firstly, a fractional-order battery model based on a dual polarization equivalent circuit model is established. Then, the parameters of the fractional-order battery model are identified by the hybrid particle swarm optimization (HPSO) algorithm, based on a genetic crossover factor. Finally, the accuracy of the SOC estimation results of the lithium-ion batteries, using the HIF algorithm and extended Kalman filter (EKF) algorithm, are verified and compared under three conditions: uncertain measurement accuracy, uncertain SOC initial value, and uncertain application conditions. The simulation results show that the SOC estimation method based on HIF can ensure that the SOC estimation error value fluctuates within ±0.02 in any case, and is slightly affected by environmental and other factors. It provides a way to improve the accuracy of SOC estimation in a battery management system.

A novel lane detection approach, based on the dynamic region of interest (DROI) selection in the horizontal and vertical safety vision, is proposed to improve the accuracy of lane detection in this paper. The curvature of each point on the edge of the road and the maximum safe distance, which are solved by the lane line equation and vehicle speed data of the previous frame, are used to accurately select the DROI at the current moment. Next, the global search of DROI is applied to identify the lane line feature points. Subsequently, the discontinuous points are processed by interpolation. To fulfill fast and accurate matching of lane feature points and mathematical equations, the lane line is fitted in the polar coordinate equation. The proposed approach was verified by the Caltech database, under the premise of ensuring real-time performance. The accuracy rate was 99.21% which is superior to other mainstream methods described in the literature. Furthermore, to test the robustness of the proposed method, it was tested in 5683 frames of complicated real road pictures, and the positive detection rate was 99.07%.

The electro-hydraulic composite braking system of a pure electric vehicle can select different braking modes according to braking conditions. However, the differences in dynamic response characteristics between the motor braking system (MBS) and hydraulic braking system (HBS) cause total braking torque to fluctuate significantly during mode switching, resulting in jerking of the vehicle and affecting ride comfort. In this paper, torque coordination control during mode switching is studied for a four-wheel-drive pure electric vehicle with a dual motor. After the dynamic analysis of braking, a braking force distribution control strategy is developed based on the I-curve, and the boundary conditions of mode switching are determined. A novel combined pressure control algorithm, which contains a PID (proportional-integral-derivative) and fuzzy controller, is used to control the brake pressure of each wheel cylinder, to realize precise control of the hydraulic brake torque. Then, a novel torque coordination control strategy is proposed based on brake pedal stroke and its change rate, to modify the target hydraulic braking torque and reflect the driver’s braking intention. Meanwhile, motor braking torque is used to compensate for the insufficient braking torque caused by HBS, so as to realize a smooth transition between the braking modes. Simulation results show that the proposed coordination control strategy can effectively reduce torque fluctuation and vehicle jerk during mode switching.

Accurate estimation of the state of charge (SOC) is an important criterion to prevent the batteries from being over-charged or over-discharged, and this assures an electric vehicle’s safety and reliability. To investigate the effect of different operating conditions on the SOC estimation results, a dual-polarization model (DPM) and a fractional-order model (FOM) are established in this study, taking into account the prediction accuracy and structural complexity of a battery model. Based on these two battery equivalent circuit models (ECMs), a hybrid Kalman filter (HKF) algorithm is adopted to estimate the SOC of the battery; the algorithm comprehensively utilizes the ampere-hour (Ah) integration method, the Kalman filter (KF) algorithm, and the extended Kalman filter (EKF) algorithm. The SOC estimation results of the DPM and FOM, under the dynamic stress test (DST), federal urban driving schedule (FUDS), and hybrid pulse power characteristic (HPPC) cycle conditions, are compared and analyzed through six sets of experiments. Simulation results show that the SOC estimation accuracy of both the models is high and that the errors are within the range of ±0.06. Under any operating conditions, the SOC estimation error, based on the FOM, is always lower than the SOC estimation error of the DPM, but the adaptability of the FOM is not as high as that of the DPM.

The regenerative braking system of electric vehicles can not only achieve the task of braking but also recover the braking energy. However, due to the lack of in-depth analysis of the energy loss mechanism in electric braking, the energy cannot be fully recovered. In this study, the energy recovery problem of regenerative braking using the independent front axle and rear axle motor drive system is investigated. The accurate motor model is established, and various losses are analyzed. Based on the principle of minimum losses, the motor control strategy is designed. Furthermore, the power flow characteristics in electric braking are analyzed, and the optimal continuously variable transmission (CVT) speed ratio under different working conditions is obtained through optimization. To understand the potential of dual-motor energy recovery, a regenerative braking control strategy is proposed by optimizing the dynamic distribution coefficient of the dual-electric mechanism and considering the restrictions of regulations and the I curve. The simulation results under typical operating conditions and the New York City Cycle (NYCC) proposed conditions indicate that the improved strategy has higher joint efficiency. The energy recovery rate of the proposed strategy is increased by 1.18% in comparison with the typical braking strategy.

For the oil−electric−hydraulic hybrid power system, a logic threshold energy management strategy based on the optimal working curve is proposed, and the optimal working curve in each mode is determined. A genetic algorithm is used to determine the optimal parameters. For driving conditions, a real-time energy management strategy based on the lowest instantaneous energy cost is proposed. For braking conditions and subject to the European Commission for Europe (ECE) regulations, a braking force distribution strategy based on hydraulic pumps/motors and supplemented by motors is proposed. A global optimization energy management strategy is used to evaluate the strategy. Simulation results show that the strategy can achieve the expected control target and save about 32.14% compared with the fuel consumption cost of the original model 100 km 8 L. Under the New European Driving Cycle (NEDC) working conditions, the energy-saving effect of this strategy is close to that of the global optimization energy management strategy and has obvious cost advantages. The system design and control strategy are validated.

Direct yaw-moment control systems have been proven effective in enhancing vehicle stability and handling. The existing direct yaw-moment control designs commonly involve computation of tire side-slip angles, which is susceptible to measurement and estimation errors. The fixed control gain of the conventional sliding mode direct yaw-moment control design cannot adapt to variations and uncertainties in vehicle parameters. As a result, its robustness against parametric variations and uncertainties is limited. To improve the control performance, a novel adaptive sliding mode direct yaw-moment control approach is proposed in this article for electric vehicles with independent motors. The proposed method utilizes a varying control gain to adapt to the variations of front and rear tire side-slip angles. Comparative simulation results show that the proposed scheme outperforms the conventional method with inaccurate tire side-slip angle feedback. With the proposed direct yaw-moment control system on-board, the adverse effects of inaccuracies on tire side-slip angles are suppressed and the vehicle’s robustness against parametric variations and uncertainties is enhanced.

Abstract Background: Congenital heart defects (CHD), as the most common congenital anomaly, have been reported to be associated with chromosomal abnormalities. Currently, patients with CHD are routinely offered karyotyping and chromosomal microarray (CMA) testing, but the genotype-phenotype relationship has not yet been fully established. Objective: To determine the type and frequency of chromosomal abnormalities in fetuses with CHD and to analyze pregnancy outcomes of fetuses with heart abnormalities caused by different genetic factors. Methods: A total of 362 cases of CHD were enrolled from 2009 to 2016. Detailed ultrasound and laboratory examinations, including karyotyping and CMA, were performed. Outcome was obtained from discharge summaries. Results: Of the 362 fetuses, 220 were found with an isolated CHD, and 142 had CHD with extracardiac anomaly. Among these 362 fetuses, 140 were identified with a genetic cause, including 111 cases with aneuploidy, 10 cases with abnormality of chromosomal structure by karyotyping and 19 cases with pathogenic or likely pathogenic copy-number variations (CNVs) by CMA. The detection rate is close to 38.7%. Only one (identified as trisomy 18 syndrome) in 140 positive cases resulted in perinatal death, with the others being induced. The remaining 222 cases had negative results for both genetic testing and of these cases, 56 resulted in induced labor, and 77 had natural childbirth or caesarean births. The pregnancy outcome of the remaining 89 cases was uncertain. Conclusions: Karyotyping and CMA are effective and accurate prenatal genetic techniques for identifying fetal chromosomal abnormalities associated with cardiac defects, and this can assist clinical doctors to perform appropriate genetic counselling with regard to the etiology and outcome of CHD.

Along with the advent of four-wheel-drive electric vehicles, plenty of control strategies have been proposed for such vehicles to coordinate the torque distribution between the four driving wheels. However, how the torque distribution fundamentally affects stability and handling and how the stability/handling characteristics shed light on control system design still require more in-depth investigation. In this article, the stability and handling performances of such electric vehicles are investigated by means of CarSim–Simulink co-simulation. Based on the stability/handling characteristics, a controller is designed to actively adjust the front–rear torque distribution, and another controller is devised to actively tune the left–right torque distribution. The effectiveness of the proposed controllers is verified through CarSim–Simulink co-simulation. The simulation results indicate that the former controller improves stability especially on slippery road surfaces, and the latter controller not only enhances handling in common driving scenarios but also guarantees stability in critical driving conditions.

To tackle the excessive output torque ripple during engine starting process of parallel hybrid electric vehicles, the engine starting process is divided into three phases in this study: engine cranking phase, speed synchronization phase, and after synchronization phase. The expressions of the vehicle jerk are derived from the vehicle dynamic formula in each phase, and the influences of various parameters on the jerk are analyzed. The coordinated control strategy for the clutch pressure and motor torque and that for the motor torque and engine torque are proposed. The simulation model for the single-motor parallel hybrid electric vehicle is established using MATLAB/Simulink, and the effectiveness of the proposed control algorithms is verified. Besides, a bench test is conducted and the test results show that the selected change rates of clutch pressure, motor torque, and engine torque can effectively coordinate the relation between clutch, motor, and engine. It can be concluded that the proposed control strategy satisfies the requirement of vehicle ride performance in engine starting in-motion process.

This paper investigates the performance changes of nickel−metal hydride (Ni-MH) battery modules for hybrid electric vehicles (HEVs) using different storage and maintenance methods. The effects of charge−discharge mode, maintenance period, rest time, charge rate, and storage state of charge (SOC) on the storage performance of Ni-MH battery modules are studied. Based on the experimental results and engineering application requirements, this paper proposes some important recommendations and methods for storage and maintenance of Ni-MH battery modules for HEVs. The experimental results show that, compared with the six benchmark methods, the proposed storage and maintenance method provides superior storage and maintenance outcomes and significantly saves maintenance time.

There is a large body of literature on solving the SLAM problem for various autonomous vehicle applications. A substantial part of the solutions is formulated based on using statistical (mainly Bayesian) filters such as Kalman filter and its extended version. In such solutions, the measurements are commonly some point features or detections collected by the sensor(s) on board the autonomous vehicle. With the increasing utilization of scanners with common autonomous cars, and availability of 3D point clouds in real-time and at fast rates, it is now possible to use more sophisticated features extracted from the point clouds for filtering. This paper presents the idea of using planar features with multi-object Bayesian filters for SLAM. With Bayesian filters, the first step is prediction, where the object states are propagated to the next time based on a stochastic transition model. We first present how such a transition model can be developed, and then propose a solution for state prediction. In the simulation studies, using a dataset of measurements acquired from real vehicle sensors, we apply the proposed model to predict the next planar features and vehicle states. The results show reasonable accuracy and efficiency for statistical filtering-based SLAM applications.

Nuclear hormone receptor family member PPARγ plays an important role in mammary gland tumorigenesis. Previous studies have shown PPARγ has cytoplasmic activities upon tetradecanoyl phorbol acetate (TPA) stimulation. However, the clinical pathological significance of cytoplasmic PPARγ is not completely understood in human breast cancer. Skp2 is oncogenic, and its frequent amplification and overexpression correlated with the grade of malignancy. In this study, the role of cytoplasmic PPARγ and Skp2 expression was investigated in human breast cancer progression. Therefore, immunohistochemical analysis was performed on formalin-fixed paraffin sections of 70 specimens. Furthermore, Western blot and immunofluorescence microscopy analysis were used to study the relationship between expression of cytoplasmic PPARγ and Skp2 expression in human breast cancer cells in vitro. Results showed that the expression of cytoplasmic PPARγ was positively correlated with Skp2 expression (p < 0.05), and correlated significantly with estrogen receptor (p = 0.026) and pathological grade (p = 0.029), respectively. In addition, Skp2 overexpression can provoke cytoplasmic localization of PPARγ upon MEK1-dependent mechanisms in human breast cancer cells by nuclear-cytosolic fractionation technology and immunofluorescence microscopy analysis. Using RNA interference technology, we also found that down-regulated Skp2 reduced the phosphorylation level of MEK1 and significantly reversed TPA-induced nuclear export of PPARγ in MDA-MB-231 cells. The changes in the subcellular localization of PPARγ may represent a novel target for selective interference in patients with breast cancer.

Background: Neonatal lupus erythematosus (NLE) is an acquired autoimmune disease. NLE with liver function damage and cytomegalovirus colonization is rarely reported. Methods: This case describes a newborn male's laboratory testing found sustained liver function damage when he came to see the doctor due to oral candidiasis. The cause was identified through clinical symptoms, laboratory tests, auxiliary examinations, and family history of the patient. Results: The final diagnosis of the child was NLE with liver function damage and cytomegalovirus colonization according to comprehensive analysis and follow-up observation. Conclusions: NLE and cytomegalovirus colonization can both lead to liver function damage. When the organ function of newborns is abnormal, it is necessary to promptly investigate the cause and determine whether it is NLE. [ABSTRACT FROM AUTHOR]