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Autonomous Driving (AD) has entered a period of rapid development in recent years. With the amount of sensors and control logics installed increasing tremendously to guarantee robustness, a big challenge is posed for AD middleware. Both the academia and the industry are eager for an investigation of the performance of middlewares in Autonomous Driving Vehicles (AVs). To fill this gap, we summarize typical communication scenarios of AVs and evaluate different communication mechanisms of three popular open-source middlewares comprehensively. Besides, we construct a benchmark pack named ComP which consists of a perception communication scenario and a group of real AD applications for researchers to assess middleware performance. Our findings provide useful guidelines for researchers and insightful optimization advice for designing middlewares.

Foodborne diseases have become a significant threat to public health worldwide. Development of analytical techniques that enable fast and accurate detection of foodborne pathogens is significant for food science and safety research. Assays based on lanthanide (Ln) ion-doped upconversion nanoparticles (UCNPs) show up as a cutting edge platform in biomedical fields because of the superior physicochemical features of UCNPs, including negligible autofluorescence, large signal-to-noise ratio, minimum photodamage to biological samples, high penetration depth, and attractive optical and chemical features. In recent decades, this novel and promising technology has been gradually introduced to food safety research. Herein, we have reviewed the recent progress of Ln3+-doped UCNPs in food safety research with emphasis on the following aspects: 1) the upconversion mechanism and detection principles; 2) the history of UCNPs development in analytical chemistry; 3) the in-depth state-of-the-art synthesis strategies, including synthesis protocols for UCNPs, luminescence, structure, morphology, and surface engineering; 4) applications of UCNPs in foodborne pathogens detection, including mycotoxins, heavy metal ions, pesticide residue, antibiotics, estrogen residue, and pathogenic bacteria; and 5) the challenging and future perspectives of using UCNPs in food safety research. Considering the diversity and complexity of the foodborne harmful substances, developing novel detections and quantification techniques and the rigorous investigations about the effect of the harmful substances on human health should be accelerated.

A new framework allows intelligence on mainstream end devices without special hardware.

Three-beam laser internal coaxial wire feeding cladding is regarded as a promising additive manufacturing technique because it is highly efficient and controllable. In this study, the effects of the defocus distance on cladding using a three-beam laser with internal wire feeding are experimentally and numerically studied. A process map indicating the surface characteristics at different defocus distances with various parameter combinations was developed. The transmission characteristics including laser intensity, beam size, and laser spot distance of the three-beam laser at different defocus distances were analyzed using TracePro software. Based on the TracePro results as heat source, a three-dimensional transient finite element (FE) thermal model was formulated to predict the thermal field, temperature history and molten pool shape at different defocus distances. A molten pool with a flat bottom and low melting depth is generated when the defocus distance is − 2.5 mm, whereas when this distance is − 1.5 mm, a pool with a valley-shaped bond and high melting depth is formed. The simulated results of the temperature cycle and clad geometry are both validated and found to well agree with experimental measurements. The influence of the defocus distance on the microstructure and microhardness are discussed based on the temperature history and cooling rate. With the increase in the absolute defocus distance, the height and dilution of the clad decreased, whereas the width increased. In addition, the effects of defocus distance with various parameter combinations on clad geometry were explored using the formulated FE model.

We propose P-RT, the first robotic vision runtime framework to efficiently manage dynamic task executions on mobile systems with multiple accelerators as well as on the cloud to achieve better performance and energy savings. With P-RT, we enable a robot to simultaneously perform autonomous navigation.

Few data are available quantifying the proportion of amyloid deposition in renal biopsy specimens. The aim of the study is to investigate the correlation between the proportion of amyloid deposition in renal biopsy and clinical characteristics of Chinese patients with immunoglobulin light-chain amyloidosis (AL amyloidosis). 259 patients diagnosed with renal AL amyloidosis between 2003 and 2015 were studied retrospectively. We developed a digital, automated quantification method to evaluate amyloid deposits in glomeruli, vessels and interstitium on digital whole-slide images (WSIs). The associations between the proportion of amyloid-positive area in the renal biopsy and clinical manifestations were analyzed. The proportion (%) of amyloid-positive area in glomeruli, vessels, interstitium and the whole renal tissue were 11.81 ± 11.38, 14.14 ± 14.05, 3.34 ± 5.36 and 4.25 ± 5.77, respectively. The proportion of amyloid deposition in glomeruli, vessels and interstitium was positively correlated with serum creatinine (Scr), estimated glomerular filtration rate (eGFR) and urinary retinol binding protein (RBP). The proportion of glomerular amyloid deposition, age, urinary N-acetyl-b-D-glucosaminidase (NAG) and urinary RBP could independently predict the risk for overall death. The proportion (%) of amyloid-positive area in blood vessels, interstitium and the whole renal tissue, Scr, and urinary RBP were independent risk factors associated with renal survival. A novel digital analysis algorithm was firstly developed to quantify the proportion of amyloid deposits in renal tissues based on digital WSIs. The degree and localization of amyloid deposits in the kidney evaluated by digital WSIs may have predictive value in assessing risk of outcome of AL amyloidosis.

PurposeThis paper aims to analyze how a real-time COVID-19 pandemic is impacting Macao’s hospitality industry, and illustrates why lessons from COVID-19 are an opportunity for further development for the city.Design/methodology/approachThis case study highlights local government and hospitality industry responses to a real-time crisis. Academic studies, media news and reports have been collected to illustrate why the Macao’s response to the COVID-19 pandemic could be taken as a city case study example. Previous crisis experience provided guidance to Macao’s success in this pandemic.FindingsMacao has succeeded in managing the adverse effects of COVID-19, illustrating the coexistence of challenges and opportunities from experiencing the epidemic. With no COVID-19 cases in the city, cross-border tourism with China resumed in September. Macao is undeniably over reliant on the gambling industry to provide tax income and employment, creating an unbalanced industrial structure. However, the Chinese and Macao Governments, the hospitality industry and other stakeholders, have presented high levels of engagement, unity and rational courses of action during the pandemic. This paper examines Macao’s two orientations – intra and post-coronavirus – which are shown to be instrumental in the city’s future tourism development.Practical implicationsAs the paper is Macao-specific, some generalization may not be applicable. The lessons and strategies proposed in the paper may only be theoretically and temporarily workable in this real-time situation. However, as COVID-19 will remain for some time globally, the efficacy of the findings justifies further ongoing analysis and application beyond Macao.Originality/valueThe case offers a first-hand analysis on the governance of Macao to negate the impacts of COVID-19, enabling a comprehensive review on the practices and policies that were effective during the virus outbreak. There is reference for researchers and practitioners in the public policy domain, and particularly in the area of crisis management and destination resilience. The result is worthy of future exploration on how the mechanism of centralized government facilitates risk management, and the rebuilding of a tourism economy in a crisis context, comparing this to other national systems.

Non-immune complex (IC)-mediated renal thrombotic microangiopathy (TMA) has been reported in patients with systemic lupus erythematosus (SLE), but most studies included patients with both renal TMA and IC-mediated lupus nephritis (LN). In this study, the clinicopathological features and outcomes of renal injury characterised by only renal TMA were retrospectively analyzed. Patients with glomerular and/or vascular TMA in the absence of subendothelial or epithelial immune deposits were screened from 2,332 biopsied of SLE patients. The TMA lesions were divided into glomerular, vascular or both. Acute tubular-interstitial injury was semi-quantitatively analyzed. The podocyte foot process effacement (FPE) was measured by electronic microscopy. Two hundred fifty-seven (11.0%) renal biopsies revealed TMA, among which 237 biopsies showed TMA coexisting with LN, and 20 (0.9%) biopsies had only renal TMA without or with only mesangial immune deposits. All patients manifested with acute kidney injury and haematological disorders. Among them, 11 (55%) required renal replacement therapy, 12 (60%) had nephrotic syndrome and 13 (65.0%) showed microvascular haemolytic anaemia with thrombocytopenia. Seventeen (85%) biopsies revealed both glomerular TMA and vascular TMA, two had only glomerular TMA and one had vascular TMA. Eight (40%) had no glomerular immune deposits and 12 (60%) showed only mesangial immune deposits. The acute tubulointerstitial injury in patients requiring dialysis was more severe than those not needing dialysis ((43.6 ± 24.9) % vs. (21.7 ± 20.1) %, p = 0.047). FPE of podocytes was positively correlated with proteinuria (r2 = 0.347, p = 0.006). All patients received high-dose methylprednisolone pulse therapy. Four patients received plasma exchange. The renal function of 11 patients requiring dialysis initially recovered after 16.0 (interquartile range [IQR] 9.0, 30.0) days of treatment. During the follow-up of 58.0 (IQR 36.0, 92.3) months, remission was achieved in 19 (95%) patients; only one patient had no response. No patient died or progressed to end-stage renal disease; six patients (30%) relapsed. Renal TMA, usually accompanying severe renal injury, was not uncommon in SLE patients with renal disease and should be distinguished from immune complex–mediated severe classes of LN. Early intensive immunosuppressive treatment may be associated with a good long-term renal outcome.

Introduction: Transplant glomerulopathy (TG) is a morphological lesion resulting from chronic glomerular endothelium injury, and it is strongly associated with poor graft survival. TG coexisting with focal segmental glomerulosclerosis (FSGS) can be found in renal allograft biopsies, but few related studies are available. Methods: Consecutive kidney transplant recipients with biopsy-proven TG were studied retrospectively. Patients concomitant with FSGS were identified and compared with those without FSGS. The influence of FSGS on allograft outcomes was assessed using univariate and multivariate Cox regression models. Results: Of the 66 patients with TG, 40 (60.6%) had concomitant FSGS. TG patients with FSGS had higher proteinuria (median, 2.6 vs. 0.8 g/24 h, p < 0.001) and serum creatinine levels (median, 2.5 vs. 2.1 mg/dL, p = 0.04), lower serum albumin levels, higher chronic glomerulopathy (cg) score, larger glomerular tuft area, lower number of podocytes, and higher incidences of podocyte hyperplasia, pseudotubule formation, and diffuse foot process effacement than those without FSGS (all p < 0.05). The kidney allograft loss rate of patients with FSGS was higher than that of patients without FSGS (65.7% vs. 37.5%, p = 0.03). The presence of FSGS was independently associated with allograft loss in TG (hazard ratio (HR) = 3.42, 95% confidence interval (CI): 1.30–8.98, p = 0.01). Other independent predictors were proteinuria (HR = 1.18, 95% CI: 1.02–1.37, p = 0.02), estimated glomerular filtration rate (HR = 0.94, 95% CI: 0.91–0.97, p < 0.001), and panel reactive antibody (HR = 3.99, 95% CI: 1.14–13.99, p = 0.03). Moreover, FSGS (odds ratio (OR) = 4.39, 95% CI: 1.29–14.92, p = 0.02) and cg (OR = 5.36, 95% CI: 1.56–18.40, p = 0.01) were independent risk factors for proteinuria. Conclusion: In this cohort of patients with TG, the presence of FSGS was strongly associated with more severe clinicopathological features and worse allograft survival.

Objective Drug-induced acute interstitial nephritis (DAIN) is often associated with improved outcomes, whereas some patients may still progress to chronic kidney disease (CKD). The aim of this study was to evaluate the prognosis of patients with severe DAIN requiring renal replacement therapy (RRT) at baseline, and to explore the risk factors of progression to CKD. Methods We performed a retrospective study of patients with severe DAIN confirmed by renal biopsies in our center over a 10 years period, all the patients received RRT at presentation. The clinical and pathological characteristics at baseline were recorded, and the outcomes (renal function recovered or progressed to CKD) during follow-ups were also evaluated. Univariate and multivariate logistic regression analysis were performed to identify the independent risk factors of progression to CKD. Results Seventy-two patients who met the inclusion criteria were enrolled, 13 patients (18.0%) progressed to CKD (GFR < 60 ml/min/1.73 m2) after at least 6 months of follow-up, the remaining 59 patients achieved a favorable renal function recovery. Compared with patients who achieved renal function recovery (recovery group), the patients progressed to CKD (progression group) were older and had longer interval from symptom onset to treatment with steroids. The peak serum cystatin C concentration was higher in progression group than recovery group. Higher score of interstitial fibrosis/tubular atrophy (IFTA) and more interstitial inflammatory cells infiltration were detected in renal tissue in progression group. According to multivariable analysis, higher peak cystatin C concentration (OR = 2.443, 95% CI 1.257, 4.746, p = 0.008), longer interval to treatment with corticosteroids (OR = 1.183, 95% CI 1.035, 1.352, p = 0.014) were independent risk factors of progression to CKD. The cutoff value of cystatin C concentration was 4.34 mg/L, at which the sensitivity and specificity were 76.9% and 89.3%, respectively; the cutoff value of interval to treatment with corticosteroids was 22.5 days, at which the sensitivity and specificity were 81.8% and 79.5%, respectively. Conclusion Renal function was reversible in majority of patients with severe DAIN requiring RRT when early identification and treatment. Higher peak cystatin C concentration and longer interval to treatment with corticosteroids associated with worse renal prognosis.

Identification of glomerular lesions and structures is a key point for pathological diagnosis, treatment instructions, and prognosis evaluation in kidney diseases. These time‐consuming tasks require a more accurate and reproducible quantitative analysis method. We established derivation and validation cohorts composed of 400 Chinese patients with immunoglobulin A nephropathy (IgAN) retrospectively. Deep convolutional neural networks and biomedical image processing algorithms were implemented to locate glomeruli, identify glomerular lesions (global and segmental glomerular sclerosis, crescent, and none of the above), identify and quantify different intrinsic glomerular cells, and assess a network‐based mesangial hypercellularity score in periodic acid–Schiff (PAS)‐stained slides. Our framework achieved 93.1% average precision and 94.9% average recall for location of glomeruli, and a total Cohen's kappa of 0.912 [95% confidence interval (CI), 0.892–0.932] for glomerular lesion classification. The evaluation of global, segmental glomerular sclerosis, and crescents achieved Cohen's kappa values of 1.0, 0.776, 0.861, and 95% CI of (1.0, 1.0), (0.727, 0.825), (0.824, 0.898), respectively. The well‐designed neural network can identify three kinds of intrinsic glomerular cells with 92.2% accuracy, surpassing the about 5–11% average accuracy of junior pathologists. Statistical interpretation shows that there was a significant difference (P value

Objectives. To investigate the diagnostic value of contrast-enhanced ultrasound- (CEUS-) guided contrast injection via an endoscopic nasobiliary drainage (ENBD) tube on the evaluation for residual stones in common bile duct (CBD). Methods. 116 patients with CBD stones were treated by endoscopic retrograde cholangiopancreatography and duodenoscopic sphincterotomy incision surgery and ENBD. The US group consisted of 54 patients who underwent US-guided saline injection via the ENBD tube to evaluate for residual CBD stones. The CEUS group consisted of 62 patients who underwent CEUS-guided contrast injection via the ENBD tube to evaluate for residual CBD stones. The length and width of CBD and the detection rate of residual stones before and after NS injection were compared. Results. In both the US group and the CEUS group, the rate of complete demonstration and the average length and width of CBD before and after injection of NS were all increased significantly. In the US group, 6 patients had verified residual stones, 1 of which was detected by conventional US (detection rate, 1/6), 5 of which were detected by saline injection ultrasound (detection rate, 5/6), and 4 of which were detected by ENBD cholangiography (detection rate, 4/6). There was 1 false positive result on saline injection US and 2 false positives on ENBD cholangiography. In the CEUS group, 6 patients had verified residual stones, none of which were detected by conventional US (detection rate, 0/6), all of which were detected by saline injection CEUS (detection rate, 6/6), and 4 of which were detected by ENBD cholangiography (detection rate, 4/6). There was 1 false positive result on ENBD cholangiography. Conclusions. CEUS-guided contrast injection via an ENBD tube helps to provide clear observation of residual stones in the CBD after ERCP with EST and provides comprehensive information for follow-up.

Fibrillary glomerulonephritis (FGN) is a rare glomerular disease. DNAJB9 as a new reliable diagnostic marker for the diagnosis of FGN was discovered recently. To investigate the clinicopathological features and prognosis of DNAJB9-positive FGN, we report on a case series in a single center in China. DNAJB9 immunohistochemistry was performed on renal biopsy samples from patients with FGN (n = 7), and non-FGN glomerular diseases (n = 27) were used as controls. The patients with DNAJB9-positive FGN were retrospectively analyzed. Strong DNAJB9 staining of glomerular extracellular deposits was observed in 6 cases of originally diagnosed FGN. One man and 5 women with a median age of 26 years were studied. The patients presented with renal insufficiency in 1 case, proteinuria in 6 cases, nephrotic syndrome in 3 cases, and microscopic hematuria in 2 cases. The histologic pattern was mesangial proliferative glomerulonephritis in 1 case and membranoproliferative glomerulonephritis in 5 cases. The glomerular deposits stained for polytypic IgG and both kappa and lambda in 3 cases, polytypic IgG without kappa or lambda in 1, monotypic IgG1-kappa in 1 and IgG1-lambda in 1. Extraglomerular deposits were identified in all cases. Congo red positivity was observed in 3 cases. All of the patients received renin–angiotensin–aldosterone system blockade and 5 of them received glucocorticoid and/or immunosuppression. At a median time of 36.2 months after biopsy, 2 cases had partial remission, 3 cases displayed no remission, and 1 case progressed to end-stage renal disease. Extraglomerular deposits in the FGN were common. Monotypic FGN was found in young patients with a favorable renal outcome.

In-memory big data computing, widely used in hot areas such as deep learning and artificial intelligence, can meet the demands of ultra-low latency service and real-time data analysis. However, existing in-memory computing frameworks usually use memory in an aggressive way. Memory space is quickly exhausted and leads to great performance degradation or even task failure. On the other hand, the increasing volumes of raw data and intermediate data introduce huge memory demands, which further deteriorate the short of memory. To release the pressure on memory, those in-memory frameworks provide various storage schemes options for caching data, which determines where and how data is cached. But their storage scheme selection mechanisms are simple and insufficient, always manually set by users. Besides, those coarse-grained data storage mechanisms cannot satisfy memory access patterns of each computing unit which works on only part of the data. In this paper, we proposed a novel task-aware fine-grained storage scheme auto-selection mechanism. It automatically determines the storage scheme for caching each data block, which is the smallest unit during computing. The caching decision is made by considering the future tasks, real-time resource utilization, and storage costs, including block creation costs, I/O costs, and serialization costs under each storage scenario. The experiments show that our proposed mechanism, compared with the default storage setting, can offer great performance improvement, especially in memory-constrained circumstances it can be as much as 78%.

The United States is facing many internal and external challenges. Internally, the productivity growth rate has slowed down significantly; externally, rising powers, such as China and Russia, are challenging American global competitiveness. In this article, we argue that the Defense Advanced Research Projects Agency (DARPA) is a differentiator that enables the U.S. to help address these challenges. DARPA has been a core engine for breakthrough technologies and innovations. We examine how DARPA has delivered breakthrough technologies—many that drive economic growth—and the impacts of DARPA technologies on the U.S. economy. We also compare DARPA's performance against some of the world's leading technology venture capital firms. We conclude that DARPA is a major national differentiator buttressing U.S. strength in innovation, technology, and the economy. Also, based on the observations in this article, we provide a few managerial and organizational takeaways for private organizations.

Rationale & Objective Heavy chain deposition disease (HCDD) is a rare consequence of monoclonal immunoglobulin deposition disease that has not been well characterized in non-white populations. To explore the clinicopathologic characteristics and outcomes of HCDD in Chinese individuals, we report on a case series assembled in a single center in China. Study Design Case series. Setting & Participants 25 patients with biopsy-proven HCDD were studied retrospectively. Results 14 men and 11 women with an average age of 50.3 years were studied. The patients presented with hypertension (76%), edema (96%), anemia (84%), serum creatinine level > 1.2mg/dL (68%), nephrotic-range proteinuria (56%), and microscopic hematuria (80%). One (4%) patient had multiple myeloma diagnosed. Serum immunofixation electrophoresis showed that 10 of 21 (48%) patients were positive for monoclonal immunoglobulin. Hypocomplementemia of C3 was found in 68% of patients. Nodular mesangial sclerosis was identified in all patients by using light microscopy. Using immunofluorescence, all 25 patients had deposition of heavy chains of immunoglobulin G class (γ1, 13; γ2, 2; γ3, 6; γ4, 2; γ1 and γ4, 1; and γ2 and γ4, 1). During an average of 40.1 months of follow-up of 20 patients, 65% had improved kidney function, 10% had worsening kidney function, and 25% progressed to kidney failure. Mean values for kidney and patient survival were 37.8 and 40.1 months, respectively. Kidney survival was higher among patients who received chemotherapy. Limitations Retrospective study, single-center experience. Conclusions In this case series of HCDD in a single center in China, the heavy chain deposits seen in the kidney biopies of all individuals were of immunoglobulin G class. Chemotherapy improved kidney function, especially among individuals in an early stage of the disease.

Computer vision is an essential part of the modular design methodology for building autonomous vehicles and robots. It provides two essential functions: localization, which answers the question of where I am, and perception, which answers the question of what is around me. This chapter reviews the details of computer vision technologies. It begins with computer vision hardware design and introduces the challenges of building computer vision hardware. The chapter then introduces the concept of calibration and delves into a few calibration techniques. Next, it explains how a person can use computer vision for localization and how he/she can use computer vision for perception. The chapter also presents a case study of PerceptIn's DragonFly computer vision module. The chapter helps readers to understand how to use computer vision technologies in their autonomous vehicle and robot designs, as well as how to combine computer vision and other sensors to achieve better localization and perception results.

Commercial Global Positioning System (GPS) receivers, such as the ones in cell phones, usually can provide meter‐level accuracy in the best case. However, this is not enough for autonomous vehicles, which require centimeter‐level localization. One technology to achieve centimeter accuracy is the real‐time kinematic (RTK) Global Navigation Satellite System (GNSS). This chapter introduces localization with RTK GNSS and its role in an autonomous driving technology stack. It provides an overview of GNSS technologies and presents a step‐to‐step detailed guide on setting up one's own RTK GNSS system for high‐precision localization. The chapter discusses RTK‐GNSS architecture and demonstrates how to setup a cloud server to broadcast base station correction signal, or the Radio Technical Commission for Maritime Services (RTCM) signal. When a cloud server is not a good option, it also demonstrates how to set up FreeWave radio to broadcast RTCM signals.

One key component in the modular design architecture is the in‐vehicle communication network, which allows Electronic Control Units, sensors, and other components to communicate with each other. The Controller Area Network (CAN) bus is the most widely used in‐vehicle communication network due to its simplicity. This chapter provides an introduction to the following in‐vehicle communication systems: CAN, FlexRay, and CANopen. FlexRay is meant to gradually replace CAN as the default in‐vehicle communication network. CANopen is a communication protocol and device profile specification for embedded systems used in automation. The CANopen communication protocol has support for network management, device monitoring, and communication between nodes, including a simple transport layer for message segmentation and desegmentation. CANopen distinguishes two basic data transmission mechanisms: the access to entries of the object dictionary through “Service Data Objects” and the exchange of process data through “Process Data Objects”.

This chapter provides a thorough case study of Perceptln's DragonFly Pod and DragonFly bus, which were developed using the modular design approach. First, it introduces the chassis specifications of these two vehicles, so that readers can understand the physical differences of these vehicles. Secondly, The chapter reveals the sensor configurations on these two chassis, so that readers can understand how perception and localization modules are deployed. Thirdly, it describes the ‘anatomy’ of the DragonFly system, or the software architecture enabling autonomous driving on these vehicles, so that readers can understand how different modules work together to form a system. Fourthly, the chapter discusses the ‘physiology’ of the DragonFly system, or the mechanism of the autonomous vehicles, so that readers understand the life cycle of the autonomous driving software. Finally, it shows how users can interact with the autonomous vehicles through a simple user interface.

This chapter introduces the basic chassis technologies, especially drive‐by‐wire, required for building autonomous vehicles and robots. It also introduces two open source projects, the Open Source Car Control (OSCC) and OpenCaret. OSCC is an assemblage of software and hardware designs that enable computer control of modern cars in order to facilitate the development of autonomous vehicle technology. It is a modular and stable way of using software to interface with a vehicle's communications network and control systems. OpenCaret builds on top of OSCC to enable a L3 highway autopilot system for modern cars. Finally, the chapter presents a detailed case study, the PerceptIn Chassis Software Adaptation Layer, which provides a layer of abstraction for different chassis, so that chassis manufacturers can easily integrate PerceptIn's autonomous driving technology stack to convert their chassis into autonomous vehicles.

In an autonomous driving system, there are usually two different perception systems: active and passive. In modular design architecture, there are three layers of protection: computer vision (active perception) for long‐range obstacle detection; millimeter wave (mmWave) radar for mid‐range obstacle detection; and sonar for short‐range obstacle detection. This chapter first introduces the fundamentals of mmWave radar technologies and then explains how we can deploy mmWave radar as well as sonar for passive perception. Radar systems transmit electromagnetic wave signals that objects in their path then reflect. By capturing the reflected signal, a radar system can determine the range, velocity, and angle of the objects. Sonars can detect certain objects that radar and Light Detection and Ranging may not be able to detect. Sonar sensors are unaffected by the color of the material they are sensing.

This chapter breaks down the costs of existing autonomous driving systems and demonstrates that the high costs of sensors, computing systems, and High‐Definition maps are the major barriers of autonomous driving deployment. The typical sensors used in autonomous driving include Global Navigation Satellite System (GNSS), Light Detection and Ranging, cameras, radar and sonar: GNSS receivers, especially those with real‐time kinematic capabilities, help autonomous vehicles localize themselves by updating global positions with at least meter‐level accuracy. Many major autonomous driving companies, such as Waymo, Baidu, and Uber, and several others are engaged in a competition to design and deploy the ultimate ubiquitous autonomous vehicle which can operate reliably and affordably, even in the most extreme environments. The keys to enable affordability and reliability include using sensor fusion, modular design, and high‐precision visual maps. The chapter also presents an overview of the key concepts discussed in the subsequent chapters of this book.

Many young urbanites don't want to own a car, and unlike earlier generations, they don't have to rely on mass transit. Instead they treat mobility as a service: When they need to travel significant distances, say, more than 5 miles (8 kilometers), they use their phones to summon an Uber (or a car from a similar ride-sharing company). If they have less than a mile or so to go, they either walk or use various “micromobility” services, such as the increasingly ubiquitous Lime and Bird scooters or, in some cities, bike sharing. The problem is that today's mobility-as-a-service ecosystem often doesn't do a good job covering intermediate distances, say a few miles. Hiring an Uber or Lyft for such short trips proves frustratingly expensive, and riding a scooter or bike more than a mile or so can be taxing to many people. So getting yourself to a destination that is from 1 to 5 miles away can be a challenge. Yet such trips account for about half of the total passenger miles traveled. Many of these intermediate-distance trips take place in environments with limited traffic, such as university campuses and industrial parks, where it is now both economically reasonable and technologically possible to deploy small, low-speed autonomous vehicles powered by electricity. We've been involved with a startup that intends to make this form of transportation popular. The company, PerceptIn, has autonomous vehicles operating at tourist sites in Nara and Fukuoka, Japan; at an industrial park in Shenzhen, China; and is just now arranging for its vehicles to shuttle people around Fishers, Ind., the location of the company's headquarters.

Autonomous driving is one of the most innovative applications nowadays. However, autonomous driving is still suffering from heavy calculation, high energy consumption and strict real-time execution constraints. Different from cloud computing, edge computing deploys calculation, storage and service on the edge of network. It is a better platform to serve efficiency and privacy oriented autonomous driving service offloading. To this end, we proposed a container-based edge offloading framework for autonomous driving. This framework builds an Offloading Decision Module, an Offloading Scheduler Module and an Edge Offloading Middleware on top of the lightweight virtualization. It provides the abstraction and management of the execution environment in the granularity of containers on edge. Therefore, it enables the privacy preserve and resource isolation for autonomous driving execution constraints. Its utility preferable offloading schedule strategy formalized the multi-application multi-edge nodes mapping problem into a multiple multidimensional knapsack problem (MMKP) and gave a utility oriented greedy algorithm (GA) for real-time solving. The experimental results show that the proposed framework has high feasibility and isolation meanwhile can guarantee millisecond-level autonomous driving offloading on edge.

In contrast to sending humans to explore space, the applicat ion of autonomous robots reduces safety concerns and extends the possible mission distance since return transportation is not necessary. In addition, the use of robots decreases complexities and costs because there is no need for onboard life-support systems; robots can withstand and operate in harsh conditions, such as extreme temperature, pressure, and radiation, where humans cannot survive.

To simultaneously enable multiple autonomous driving services on affordable embedded systems, we designed and implemented LoPECS, a Low-Power Edge Computing System for real-time autonomous robots and vehicles services. The contributions of this paper are three-fold: first, we developed a Heterogeneity-Aware Runtime Layer to fully utilize vehicle's heterogeneous computing resources to fulfill the real-time requirement of autonomous driving applications; second, we developed a vehicle-edge Coordinator to dynamically offload vehicle tasks to edge cloudlet to further optimize user experience in the way of prolonged battery life; third, we successfully integrated these components into LoPECS system and implemented it on Nvidia Jetson TX1. To the best of our knowledge, this is the first complete edge computing system in a production autonomous vehicle. Our implementation on Nvidia Jetson demonstrated that it could successfully support multiple autonomous driving services with only 11 W of power consumption, and hence proves the effectiveness of the proposed LoPECS system.

Purpose This study aimed to compare the efficacy and safety of ultrasound-guided percutaneous microwave ablation (MWA) for hepatocellular carcinoma (HCC) adjacent to large vessels with those far from large vessels. Methods The clinical data of patients who underwent ultrasound-guided percutaneous MWA for HCC were retrospectively analyzed between January 2011 and December 2018 in Shengjing Hospital. Patients with HCC adjacent to large vessels were included in the Vessel group, the remaining patients were included in the Control group. Propensity score matching analysis was used to reduce confounding bias. The rates of complete ablation, local recurrence, recurrence-free survival (RFS), overall survival (OS) and complications were compared between the two groups. Results A total of 134 patients with 157 nodules (size range, 0.6–3.8 cm) were enrolled in this study, 23 in the Vessel group and 111 in the Control group. A total of 21 patients in the Vessel group (91.3%) and 105 patients in the Control group (94.6%) achieved complete ablation (p = .902). Following 1:2 propensity score matching, 22 patients were included in the Vessel group and 40 patients were enrolled in the Control group. Local recurrence was observed in 2 (9.1%) patients in the Vessel group and 5 (12.5%) in the Control group (p = .86). No significant difference in local recurrence rate, RFS and OS were observed between the two groups. Conclusions Ultrasound-guided percutaneous MWA appears to be a safe procedure and can achieve comparable oncological efficacy for HCC abutting large vessels.

The burgeoning of Internet of Things (IoT) and camera-equipped mobile devices contributes a tremendous amount of video data generated at the edge of the network. At the same time, we have witnessed the fast deployment of many video-based application services, such as plate recognition for public safety, intelligent transportation, Industry 4.0 and so on. The success of these services, in turn, requires large-scale video data being learned, stored, and retrieved in a more efficient way. A generic software and hardware framework for large-scale IoT video analysis and service support is still missing. To address this challenge, we present π -Hub, PerceptIn’s robotic cloud solution which supports large-scale video data analysis, storage, and query by implementing the learn-store-retrieve paradigm. Interestingly, we found that among the learning, storage, and retrieval services each of them stresses one type of resources on heterogeneous computing servers, i.e., GPU, CPU, and Memory, respectively, therefore it is extremely cost-efficient to co-locate these services together to fully utilize the resources. In addition, several optimization techniques for data writing, reading, and data reduction are proposed and evaluated. The evaluation results show that these techniques improve the performance of the learning, storage and retrieval services significantly as well as notably reduce the cost of the system. We also verify π -Hub’s scalability by reliably running a 1000-machine deployment to support up to one million users. Finally, we conclude the paper by discussing several lessons learned from this study and future work.

Platelets have been recognized as key players in hemostasis, thrombosis, and cancer. Preclinical and clinical researches evidenced that tumorigenesis and metastasis can be promoted by platelets through a wide variety of crosstalk between cancer cells and platelets. Pancreatic cancer is a devastating disease with high morbidity and mortality worldwide. Although the relationship between pancreatic cancer and platelets in clinical diagnosis is described, the interplay between pancreatic cancer and platelets, the underlying pathological mechanism and pathways remain a matter of intensive study. This review summaries recent researches in connections between platelets and pancreatic cancer. The existing data showed different underlying mechanisms were involved in their complex crosstalk. Typically, pancreatic tumor accelerates platelet aggregation which forms thrombosis. Furthermore, extracellular vesicles released by platelets promote communication in a neoplastic microenvironment and illustrate how these interactions drive disease progression. We also discuss the advantages of novel model organoids in pancreatic cancer research. A more in-depth understanding of tumor and platelets crosstalk which is based on organoids and translational therapies may provide potential diagnostic and therapeutic strategies for pancreatic cancer progression.

Background: Mitochondria are dynamic organelles whose structure are maintained by continuous fusion and fission. During acute kidney injury (AKI) progression, mitochondrial fission in renal tubular cells was elevated, characterized by mitochondrial fragmentation. It is tightly associated with mitochondrial dysfunction, which has been proven as a critical mechanism responsible for AKI. However, the initiating factor for the disruption of mitochondrial dynamics in AKI was not well understood. Objectives: To explore the molecular mechanisms of mitochondrial disorders and kidney damage. Methods: We established cisplatin-induced AKI model in C57BL/6 mice and proximal tubular cells, and detected the expression of miR-125b by qPCR. Then we delivered miR-125b antagomir after cisplatin treatment in mice via hydrodynamic-based gene transfer technique. Subsequently, we performed luciferase reporter and immunoblotting ­assays to prove miR-125b could directly modulate mitofusin1 (MFN1) expression. We also tested the role of miR-125b in mitochondrial and renal injury through immunofluorescent staining, qPCR, and immunoblotting assays. Results: miR-125b levels were induced in cisplatin-challenged mice and cultured tubular cells. Anti-miR-125b could effectively alleviate cisplatin-induced mitochondrial fragmentation and kidney injury both in vitro and in vivo. Furthermore, miR-125b could directly regulate MFN1, which is a key regulator of mitochondrial fusion. Our study indicated that miR-125b is upregulated during cisplatin-induced AKI. Inhibition of miR-125b may suppress mitochondrial and renal damage through upregulating MFN1. This study suggests that miR-125b could be a potential therapeutic target in AKI.

Despite many recent efforts, accelerating robotic computing is still fundamentally challenging for two reasons. First, robotics software stack is extremely complicated. Manually designing an accelerator while meeting the latency, power, and resource specifications is unscalable. Second, the environment in which an autonomous machine operates constantly changes; a static accelerator design leads to wasteful computation. This paper takes a first step in tackling these two challenges using localization as a case study. We describe, a framework that automatically generates a synthesizable accelerator from the high-level algorithm description while meeting design constraints. The accelerator continuously optimizes itself at run time according to the operating environment to save power while sustaining performance and accuracy. is able to generate FPGA-based accelerator designs that cover large a design space and achieve orders of magnitude performance improvement and/or energy savings compared to state-of-the-art baselines.

Background Medial patellofemoral ligament reconstruction (MPFLR) is a well-established procedure for addressing recurrent patellar dislocation (RPD) in young patients. However, despite being a promising procedure for RPD with genu valgum, there is a scarcity of reports on simultaneous MPFLR and closing-wedge distal femoral osteotomy (CWDFO). The purpose of the present study was to observe and analyse the clinical and imaging findings of CWDFO combined with MPFLR for RPD with genu valgum. Methods From May 2015 to April 2018, 25 patients with RPD and genu valgum were surgically treated in our department. Anteroposterior long-leg, weight-bearing, lower-extremity radiographs, lateral radiographs and computed tomography (CT) scans of the patellofemoral joint were obtained, and the anatomical femorotibial angle (aFTA), mechanical lateral distal femoral angle (mLDFA), weight-bearing line rate (WBLR), patellar height, patellar lateral shift (PLS) and tibial tubercle–trochlear groove (TT-TG) distance were analysed. Validated knee scores, such as the Kujala, Lysholm, visual analogue scale (VAS) scores and Tegner socres, were evaluated preoperatively and 2 years postoperatively. Results 25 patients, with an average age of 19.8 years (14–27), were evaluated. During the 2-year follow-up period, all patients were able to achieve a better sports level without any problems, with no recurrence of patellar instability. Compared with preoperation, the aFTA, mLDFA, WBLR and PLS showed statistically significant improvement following the procedure (p < 0.001). Meanwhile, no significant differences in the Insall index and TT-TG distance were found. The mean Kujala score, average Lysholm score, VAS score and Tegner socres showed significant postoperative improvement. Conclusions CWDFO combined with MPFLR is a suitable treatment for RPD with genu valgum, and can lead to significant improvement in the clinical and imaging findings of the knee in the short term.

Connected and autonomous vehicles (CAVs) are promising due to their potential safety and efficiency benefits and have attracted massive investment and interest from government agencies, industry, and academia. With more computing and communication resources are available, both vehicles and edge servers are equipped with a set of camera-based vision sensors, also known as Visual IoT (V-IoT) techniques, for sensing and perception. Tremendous efforts have been made for achieving programmable communication, computation, and control. However, they are conducted mainly in the silo mode, limiting the responsiveness and efficiency of handling challenging scenarios in the real world. To improve the end-to-end performance, we envision that future CAVs require the co-design of communication, computation, and control. This paper presents our vision of the end-to-end design principle for CAVs, called 4C, which extends the V-IoT system by providing a unified communication, computation, and control co-design framework. With programmable communications, fine-grained heterogeneous computation, and efficient vehicle controls in 4C, CAVs can handle critical scenarios and achieve energy-efficient autonomous driving. Finally, we present several challenges to achieving the vision of the 4C framework., 7 pages, 4 figures, accepted by IEEE Wireless Communication Magazine

In recent years, intelligent vehicles like autonomous vehicles generate a huge amount of sensing data continuously. The computations on those data streams are far beyond the processing capacity of on-board computing. To deal with the streaming data process in real-time, the deployment of streaming data processing system by edge turns to the first choice in terms of performance. However, the existing frameworks cannot satisfy the complicated demands from autonomous driving tasks and lack the ability in supporting the task priority scheduling. In this paper, we propose a streaming data priority scheduling framework for autonomous driving by edge on Spark Streaming and make an implementation on Spark 2.3.0. The proposed framework can identify the priorities among different data processing tasks and implement the task scheduling based on non-preemptive priority queuing theory. To meet differentiated service level requirements, the proposed non-preemptive priority queuing scheduling mechanism considers the priority category of tasks, the distance between vehicles and edge nodes, and the priority weight of vehicles. Experiments show that this mechanism can effectively identify the priority information of different tasks from different vehicles and reduce the end-to-end latency of high-priority tasks by up to 46% than low-priority tasks.

In our past few years' of commercial deployment experiences, we identify localization as a critical task in autonomous machine applications, and a great acceleration target. In this paper, based on the observation that the visual frontend is a major performance and energy consumption bottleneck, we present our design and implementation of an energy-efficient hardware architecture for ORB (Oriented-Fast and Rotated- BRIEF) based localization system on FPGAs. To support our multi-sensor autonomous machine localization system, we present hardware synchronization, frame-multiplexing, and parallelization techniques, which are integrated in our design. Compared to Nvidia TX1 and Intel i7, our FPGA-based implementation achieves 5.6x and 3.4x speedup, as well as 3.0x and 34.6x power reduction, respectively., To appear in IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), June 6-9, 2021, Virtual

Safety is the most important requirement for autonomous vehicles; hence, the ultimate challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver enough computing power, redundancy, and security so as to guarantee the safety of autonomous vehicles. Specifically, autonomous driving systems are extremely complex; they tightly integrate many technologies, including sensing, localization, perception, decision making, as well as the smooth interactions with cloud platforms for high-definition (HD) map generation and data storage. These complexities impose numerous challenges for the design of autonomous driving edge computing systems. First, edge computing systems for autonomous driving need to process an enormous amount of data in real time, and often the incoming data from different sensors are highly heterogeneous. Since autonomous driving edge computing systems are mobile, they often have very strict energy consumption restrictions. Thus, it is imperative to deliver sufficient computing power with reasonable energy consumption, to guarantee the safety of autonomous vehicles, even at high speed. Second, in addition to the edge system design, vehicle-to-everything (V2X) provides redundancy for autonomous driving workloads and alleviates stringent performance and energy constraints on the edge side. With V2X, more research is required to define how vehicles cooperate with each other and the infrastructure. Last, safety cannot be guaranteed when security is compromised. Thus, protecting autonomous driving edge computing systems against attacks at different layers of the sensing and computing stack is of paramount concern. In this paper, we review state-of-the-art approaches in these areas as well as explore potential solutions to address these challenges.

Background Human papilloma virus (HPV) infection and condyloma acuminatum (CA) in the genital area often exist in extensive and multi-point fashion. Laser ablation combined with topical photodynamic therapy (PDT) is a feasible approach for genital CA but its effectiveness and limitations need to be evaluated. Methods This single-arm prospective study consisted of 100 newly diagnosed CA cases of both sexes. All patients underwent laser ablation and then three times aminolaevulinic acid-based photodynamic therapy (ALA-PDT). The outcomes were evaluated and analyzed 3 months after the treatment. Results A total of 98 patients completed the study. Except for 6 patients (4 males and 2 females) showed some residual lesions other 92 patients (93.8%) showed complete cure. However, there were 18 patients (10 males and 8 females) showed new lesions near the treated areas. Although the HPV types of 18 patients before and after treatment were not completely consistent, 94.4% percent of patients (17/18) had the same HPV type as the primary lesion, which suggested that these late-onset CA might have latent infection or subclinical infection in the early stage of the disease but the length of the incubation period was longer. Conclusion Combination approach is effective in treating genital CA and preventing CA recurrence. But its limitations need to be recognized as the late-onset CA might occur near the treated area. The treatment plan needs to be optimized for multiple genital CA lesions.

To retrospectively investigate the clinical and histological features and outcomes of ANCA-associated glomerulonephritis (AAGN) with different ANCA serotypes.A total of 467 AAGN patients were divided into MPO-AAGN (MPO) and PR3-AAGN (PR3) groups according to ANCA serotype. Clinical and histological features and renal outcomes were compared.In this study, 429 (91.9%) patients tested positive for MPO-ANCA, and 38 (8.1%) for PR3-ANCA. The median age at diagnosis (P = 0.017) and proportion of females (P = 0.003) were higher in the MPO group. Joint (P 0.001), ENT (P = 0.000), skin (P = 0.007), and eye (P = 0.014) involvements were more common in the PR3 group. Compared with that in the PR3-group, a higher proportion of patients in the MPO group had microscopic polyangiitis (P = 0.000), and a lower proportion of exhibited granulomatosis with polyangiitis (P = 0.000). Patients in the MPO group also exhibited lower BVAS scores (P = 0.003) and higher serum albumin levels (P = 0.009). Histologically, a lower proportion of MPO patients had crescentic glomerulonephritis (P = 0.028) and acute tubule-interstitial lesion scores (P = 0.007), but a higher proportion of these patients exhibited mixed class glomerulonephritis (P = 0.032) than in the PR3 group. The relapse rate was lower (P = 0.020), and the 5-year relapse-free survival rate (P = 0.003) was higher in the MPO group than in the PR3 group. However, the 5-year renal survival rates (P = 0.106) were not significantly different.MPO-ANCA was predominant in Chinese patients with ANCA-associated vasculitis and renal disease. The epidemiological characteristics, extra-renal involvement, and histopathological classes and outcomes were different between MPO-positive and PR3-positive patients, implying that they might be two different disease entities.

Background Aberrant expression of miR-532-3p was involved in progression and development of multiple cancers, whereas miR-532-3p has not been reported in hepatocellular carcinoma (HCC). The aim of this study was to elucidate the functions of miR-532-3p in progression of HCC. Methods Real-time PCR in HCC tissues and cell lines and database analysis were conducted for detection of the expression of miR-532-3p in HCC. Then, the association of miR-532-3p with clinicopathological features and prognosis of HCC patients were statistically measured. Subsequently, we attempted to observe the effects of miR-532-3p on migration, invasion and proliferation of HCC cells by Wound healing assay, Transwell assays, MTT assay and EdU assay. Furthermore, bioinformatics tools, database analysis, luciferase reporter gene assay and rescue experiments were conducted to explore the target of miR-532-3p in HCC, and to explore whether the target mediated the effects of miR-532-3p on HCC cells. Results Our findings and data from databases consistently indicated that the miR-532-3p expression level was higher in HCC. In addition, high miR-532-3p expression was found to be closely related to larger tumor size (P = 0.0027), presence of vascular invasion (P = 0.015), and advanced TNM stage (P = 0.015). In addition, experiments in vitro revealed that miR-532-3p promotes migration, invasion and proliferation of HCC cells. Furthermore, receptor protein tyrosine phosphatase T (PTPRT) was identified as the target and mediator of miR-532-3p in HCC cells. Conclusion Our results demonstrate that miR-532-3p, which is frequently up-regulated in HCC, contributes to HCC cells mobility and proliferation through targeting PTPRT.

Autosomal dominant tubulointerstitial kidney disease due to UMOD (encoding uromodulin) mutation (ADTKD-UMOD) is a rare hereditary disease. In the present study, we reported 2 ADTKD cases with confirmed UMOD mutations (Arg185His, Trp258Gly) by gene testing. They were young men and presented with hyperuricemia and renal dysfunction with no hematuria or proteinuria. Renal histology showed chronic tubulointerstitial nephropathy with fibrillar inclusions in the cells of distal tubules. Electron microscopy illustrated extensive bundled and cystic endoplasmic reticulum. Immunohistological analysis confirmed intracytoplasmic aggregates of uromodulin in the distal tubules. Since ADTKD-UMOD is an underdiagnosed disease, electron microscopy and immunohistochemical staining for uromodulin are helpful in the diagnosis of ADTKD-UMOD and genetic analysis is the gold standard.

Time synchronization is a critical task in robotic computing such as autonomous driving. In the past few years, as we developed advanced robotic applications, our synchronization system has evolved as well. In this paper, we first introduce the time synchronization problem and explain the challenges of time synchronization, especially in robotic workloads. Summarizing these challenges, we then present a general hardware synchronization system for robotic computing, which delivers high synchronization accuracy while maintaining low energy and resource consumption. The proposed hardware synchronization system is a key building block in our future robotic products.

Facing the difficulty and inefficiency of creating and maintaining High-Definition (HD) maps in our commercial deployments, we have developed an edge-based crowdsourcing task distribution framework for HD Map in autonomous driving. Our key observation is that: HD map data crowdsourcing exhibits the diminishing marginal utility thus there exists an inflection point for maximum utility, meanwhile its premature convergence of utility will leave some map updates not notified in time. Based on this observation, we develop a periodic crowdsourcing task distribution framework. It discretizes the demands for collecting source data into different periods and uses an optimal stopping rule to terminate the data collection for the maximum crowdsourcing utility. The experimental results verify that our crowdsourcing framework can achieve high time coverage and high efficiency with lower cost.

In autonomous driving, 3D object detection is es-sential as it provides basic knowledge about the environment. However, as deep learning based 3D detection methods are usually computation intensive, it is challenging to support realtime 3D object detection on edge-computing devices in selfdriving cars with limited computation and memory resources. To facilitate this, we propose a compiler-aware pruning search framework, to achieve real-time inference of 3D object detection on the resource-limited mobile devices. Specifically, a generator is applied to sample better pruning proposals in the search space based on current proposals with their performance, and an evaluator is adopted to evaluate the sampled pruning proposal performance. To accelerate the search, the evaluator employs Bayesian optimization with an ensemble of neural predictors. We demonstrate in experiments that for the first time, the pruning search framework can achieve real-time 3D object detection on mobile (Samsung Galaxy S20 phone) with state-of-the-art detection performance.

We develop and commercialize autonomous machines, such as logistic robots and self-driving cars, around the globe. A critical challenge to our—and any—autonomous machine is accurate and efficient localization under resource constraints, which has fueled specialized localization accelerators recently. Prior acceleration efforts are point solutions in that they each specialize for a specific localization algorithm. In real-world commercial deployments, however, autonomous machines routinely operate under different environments and no single localization algorithm fits all the environments. Simply stacking together point solutions not only leads to cost and power budget overrun, but also results in an overly complicated software stack.This paper demonstrates our new software-hardware co-designed framework for autonomous machine localization, which adapts to different operating scenarios by fusing fundamental algorithmic primitives. Through characterizing the software framework, we identify ideal acceleration candidates that contribute significantly to the end-to-end latency and/or latency variation. We show how to co-design a hardware accelerator to systematically exploit the parallelisms, locality, and common building blocks inherent in the localization framework. We build, deploy, and evaluate an FPGA prototype on our next-generation self-driving cars. To demonstrate the flexibility of our framework, we also instantiate another FPGA prototype targeting drones, which represent mobile autonomous machines. We achieve about $2 \times$ speedup and $4 \times$ energy reduction compared to widely-deployed, optimized implementations on general-purpose platforms.

Introduction: Secondary oxalate nephropathy (OxN) is associated with a variety of causes and has not been well characterized in Chinese population. To investigate the etiology, clinicopathological features, and outcomes of secondary OxN, we report a case series from a single center in China. Methods: A retrospective analysis of 68 patients diagnosed with secondary OxN by renal biopsy from January 2013 to February 2019 in Jinling Hospital was performed. Results: Secondary OxN accounted for 0.23% of the renal biopsies and 2.31% of patients who received renal biopsies due to acute kidney injury (AKI). A total of 49 men and 19 women with an average age of 51.6 ± 11.8 years were enrolled. The most common cause was iatrogenic medication, followed by oxalate-rich diet and industry exposure. Stage 1, 2, and 3 AKI and AKI on chronic kidney disease (ACKD) were found in 4.4, 8.8, 69.1, and 17.6% of the patients, respectively. The peak serum creatinine during hospitalization was 8.62 ± 4.67 mg/dL. The median urinary oxalate excretion was 51.5 (23.2–147.1) mg/24 h. Kidney biopsy showed extensive calcium oxalate crystal deposits with acute tubulointerstitial nephritis. Thirty-four patients (50.0%) required renal replacement therapy. At the end of a follow-up that lasted 8.7 (0.1–72.1) months, 81.0% of patients achieved renal function recovery in 50 (14–432) days. Patients with renal function recovery had a lower rate of ACKD, a higher level of hemoglobin, a lower level of urine lysozyme, and a lower degree of interstitial fibrosis/tubular atrophy, interstitial inflammation, and global glomerulosclerosis than those in the nonrecovery group. Conclusions: In this case series of secondary OxN, the most common cause was iatrogenic medication, and it presented with AKI or ACKD. Half of the patients required renal replacement therapy, and in most of them, the renal function was reversible. Renal biopsy played an important role in diagnosis and prognosis evaluation.

Background: Neutrophil extracellular traps (NETs) have been studied as crucial components of thrombi in stroke patients. Little is known about the dramatic changes of circulating NETs in the process of thrombolysis treatment. Our study aimed to investigate the potential role of NETs and their interaction with endothelial dysfunction in the process of thrombolysis treatment. Methods: NET markers were detected by ELISA in 13 healthy subjects and 25 stroke patients who received thrombolysis treatment. NETting neutrophils and neutrophil-platelet (PLT) aggregates were detected in blood samples from healthy subjects and stroke patients analyzed by confocal microscopy and flow cytometry. Endothelial cells (ECs) were treated with NETs, and the expression of vascular endothelial (VE)-cadherin, zonula occludens (ZO)-1, occludin, Claudin-5, tissue factor (TF), phosphatidylserine (PS) and plasminogen activator inhibitor-1 (PAI-1) was detected. Findings: The plasma levels of NETs showed no significant differences before and after thrombolysis treatment, but neutrophils from patients showed a stronger ability to generate NETs after treatment. TLR9-PF4 signaling was upregulated in platelets from patients and induced NET formation. NETs enhanced PCA though tissue factor and phosphatidylserine and by activating platelets. NETs also induced the disruption of the endothelial barrier and drove ECs toward a procoagulant phenotype. Interpretation: NET formation mediated by activated platelets enhances thrombogenicity, which could result in tissue plasminogen activator (t-PA) resistance. Funding Information: This work was supported by grants from the National Natural Science Foundation of China (grant nos. 61575058, 81903144, 81970415). Declaration of Interests: Nothing to report. Ethics Approval Statement: This study was approved by the Ethics Committee of Harbin Medical University and was conducted following the specifications of the Declaration of Helsinki. Blood from healthy subjects and patients was obtained with informed consent.

Chemical reactions that convert sp2 to sp3 hybridization have been demonstrated to be a fascinating yet challenging route to functionalize graphene. So far it has not been possible to precisely control the reaction sites nor their lateral order at the atomic/molecular scale. The application prospects have been limited for reactions that require long soaking, heating, electric pulses or probe-tip press. Here we demonstrate a spatially selective photocycloaddition reaction of a two-dimensional molecular network with defect-free basal plane of single-layer graphene. Directly visualized at the submolecular level, the cycloaddition is triggered by ultraviolet irradiation in ultrahigh vacuum, requiring no aid of the graphene Moiré pattern. The reaction involves both [2+2] and [2+4] cycloadditions, with the reaction sites aligned into a two-dimensional extended and well-ordered array, inducing a bandgap for the reacted graphene layer. This work provides a solid base for designing and engineering graphene-based optoelectronic and microelectronic devices. [Figure not available: see fulltext.].

In this paper, we propose π-map, a tightly coupled fusion mechanism that dynamically consumes LiDAR and sonar data to generate reliable and scalable indoor maps for autonomous robot navigation. The key novelty of π-map over previous attempts is the utilization of a fusion mechanism that works in three stages: the first LiDAR scan matching stage efficiently generates initial key localization poses; the second optimization stage is used to eliminate errors accumulated from the previous stage and guarantees that accurate large-scale maps can be generated; then the final revisit scan fusion stage effectively fuses the LiDAR map and the sonar map to generate a highly accurate representation of the indoor environment. We evaluate π-map on both large and small environments and verify its superiority over existing fusion methods.