Robert Bosch (Netherlands)

This study examined 758 deep inferior epigastric perforator flaps for breast reconstruction, with respect to risk factors and associated complications. Risk factors that demonstrated significant association with any breast or abdominal complication included smoking (p = 0.0000), postreconstruction radiotherapy (p = 0.0000), and hypertension (p = 0.0370). Ninety-eight flaps (12.9 percent) developed fat necrosis. Associated risk factors were smoking (p = 0.0226) and postreconstruction radiotherapy (p = 0.0000). Interestingly, as the number of perforators increased, so did the incidence of fat necrosis. There were only 19 cases (2.5 percent) of partial flap loss and four cases (0.5 percent) of total flap loss. Patients with 45 flaps (5.9 percent) were returned to the operating room before the second-stage procedure. Patients with 29 flaps (3.8 percent) were returned to the operating room because of venous congestion. Venous congestion and any complication were observed to be statistically unrelated to the number of venous anastomoses. Overall, postoperative abdominal hernia or bulge occurred after only five reconstructions (0.7 percent). Complication rates in this large series were comparable to those in retrospective reviews of pedicle and free transverse rectus abdominis musculocutaneous flaps. Previous studies of the free transverse rectus abdominis musculocutaneous flap described breast complication rates ranging from 8 to 13 percent and abdominal complication rates ranging from 0 to 82 percent. It was noted that, with experience in microsurgical techniques and perforator selection, the deep inferior epigastric perforator flap offers distinct advantages to patients, in terms of decreased donor-site morbidity and shorter recovery periods. Mastery of this flap provides reconstructive surgeons with more extensive options for the treatment of postmastectomy patients.

Although the total number of car occupants involved in accidents in Germany has not significantly reduced during the past 10 years, the number of fatalities has steadily decreased. Most of the severe accidents result from a loss of control of the car. The problem of the driver losing control of his car will be explained. This problem is then used to formulate the goal for the vehicle dynamics control system ESP (Electronic Stability Program, also known as VDC). The approach chosen to reach this goal will then be shown. It will be shown that the vehicle slip angle is a crucial indicator for the maneuverability of the automobile. Since the complete vehicle state is not readily available, estimation algorithms are used to supply the control algorithms with sufficient information. With the automatic control of the slip angle the required yaw moment can be generated by individual wheel slip control. By using two examples it will be shown, that ESP can significantly improve vehicle handling in extreme maneuvers by automatically controlling the brakes and the engine.

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others (‘reinventing the wheel’). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available (‘having tunnel vision’). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its ‘leading principle’, there are many opportunities for combining approaches. We take the point of view that a single ‘right’ approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

The vision of Internet of Things calls for connectivity not only to consumer electronics and home appliances, but also to small battery powered devices which cannot be recharged. Such small devices, often various types of sensors and actuators, are required to sustain reliable operation for years on batteries even in the presence of heavy interference. The IEEE 802.11 standard has established itself as one of the most popular wireless technologies offering connectivity. Using commercially available chips, we demonstrate the feasibility of low-power Wi-Fi technology to enable IP connectivity of battery powered devices. Three typical sensor application scenarios are investigated. We evaluate the power consumption of Wi-Fi enabled devices for each of the scenarios, investigate the impact of interference, and measure the range performance.

Over the last two decades, manufacturing across the globe has evolved to be more intel-ligent and data driven. In the age of industrial Internet of Things, a smart production unit can be perceived as a large connected industrial system of materials, parts, machines, tools, inventory, and logistics that can relay data and communicate with each other. While, traditionally, the focus has been on machine health and predictive maintenance, the manufacturing industry has also started focusing on analyzing data from the entire production line. These applications bring a new set of analytics challenges. Unlike traditional data mining analysis, which consists of lean datasets (that is, datasets with few features), manufacturing has fat datasets. In addition, previous approaches to manufacturing analytics restricted themselves to small time periods of data. The latest advances in big data analytics allows researchers to do a deep dive into years of data. Bosch collects and utilizes all available information about its products to increase its understanding of complex linear and nonlinear relationships between parts, machines, and assembly lines. This helps in use cases such as the discovery of the root cause of internal defects. This article presents a case study and provides detail about challenges and approaches in data extraction, modeling, and visualization.

This study investigates how different gamification implementations can increase crowdsourcees' motivation and participation in crowdsourcing (CS). To this end, we review empirical literature that has investigated the use of gamification in crowdsourcing settings. Overall, the results of the review indicate that gamification has been an effective approach for increasing crowdsourcing participation. When comparing crowdcreating, -solving, -processing and-rating CS approaches, the results show differences in the use of gamification across CS types. Crowdsourcing initiatives that provide more monotonous tasks most commonly used mere points and other simpler gamification implementations, whereas CS initiatives that seek for diverse and creative contributions have employed gamification in more manifold ways employing a richer set of mechanics. These findings provide insights for designers of gamified systems and further research on the topics of gamification and crowdsourcing.

During recent years, gamification has become a popular method of enriching information technologies. Popular business analysts have made promising predictions about penetration of gamification, however, it has also been estimated that most gamification efforts will fail due to poor understanding of how gamification should be designed and implemented. Therefore, in this paper we seek to advance the understanding of best practices related to the gamification design process. We approach this research problem via a design science research approach; firstly, by synthesizing the current body of literature on gamification design methods and interviewing 25 gamification experts. Secondly, we develop a method for gamification design, based on the gathered knowledge. Finally, we conduct an evaluation of the method via interviews of 10 gamification experts. The results indicate that the developed method is comprehensive, complete and provides practical utility. We deliver a comprehensive overview of gamification guidelines and shed novel insights into the overall nature of the gamification development and design discourse.

BACKGROUND: Many treatments are available for whiplash patients but there is little scientific evidence for their accepted use. Patients with whiplash-associated disorders (WAD) can be classified by the severity of signs and symptoms from Grade 0 (no complaints or physical signs) to Grade 4 (fracture or dislocation). OBJECTIVES: To assess the effectiveness of conservative treatment for patients with whiplash injuries rated as Grades 1 or 2 (neck and musculoskeletal complaints). SEARCH STRATEGY: We searched the Cochrane Central Register of Controlled Trials (The Cochrane Library, 2006, Issue 3), MEDLINE, CINAHL, PsycINFO, and PEDro to November 2006 and screened references of identified randomised trials and relevant systematic reviews. SELECTION CRITERIA: We selected randomised controlled trials published in English, French, German or Dutch, that included patients with a whiplash-injury, conservative interventions, outcomes of pain, global perceived effect or participation in daily activities. DATA COLLECTION AND ANALYSIS: Two authors independently assessed the methodological quality using the Delphi criteria and extracted the data onto standardised data-extraction forms. We did not pool the results because of the heterogeneity of the population, intervention and outcomes and lack of data. A pre-planned stratified analysis was performed for three different comparisons. MAIN RESULTS: Twenty-three studies (2344 participants) were included in this update, including nine new studies. A broad variety of conservative interventions were evaluated. Two studies included patients with chronic symptoms (longer than three months), two included subacute (four to six weeks) symptoms, two had undefined duration of symptoms, and 17 studied patients with acute (less than three weeks) symptoms. Only eight studies (33.3%) satisfied one of our criteria of high quality, indicating overall, a poor methodological quality. Interventions were divided into passive (such as rest, immobilisation, ultrasound, etc) and active interventions (such as exercises, act as usual approach, etc.) and were compared with no treatment, a placebo or each other. Clinical and statistical heterogeneity and lack of data precluded pooling. Individual studies demonstrated effectiveness of one treatment over another, but the comparisons were varied and results inconsistent. Therefore, the evidence neither supports nor refutes the effectiveness of either passive or active treatments to relieve the symptoms of WAD, Grades 1 or 2. AUTHORS' CONCLUSIONS: The current literature is of poor methodological quality and is insufficiently homogeneous to allow the pooling of results. Therefore, clearly effective treatments are not supported at this time for the treatment of acute, subacute or chronic symptoms of whiplash-associated disorders.

AIMS: Remote patient management (telemonitoring) may help to detect early signs of cardiac decompensation, allowing optimization of and adherence to treatments in chronic heart failure (CHF). Two meta-analyses have suggested that telemedicine in CHF can reduce mortality by 30-35%. The aim of the TIM-HF study was to investigate the impact of telemedical management on mortality in ambulatory CHF patients. Methods CHF patients [New York Heart Association (NYHA) II/III, left ventricular ejection fraction (LVEF)≤35%] with a history of cardiac decompensation with hospitalization in the past or therapy with intravenous diuretics in the prior 24 months (no decompensation required if LVEF≤25%) were randomized 1:1 to an intervention group of daily remote device monitoring (electrocardiogram, blood pressure, body weight) coupled with medical telephone support or to usual care led by the patients' local physician. In the intervention group, 24/7 physician-led medical support was provided by two central telemedical centres. A clinical event committee blinded to treatment allocation assessed cause of death and reason for hospitalization. The primary endpoint was total mortality. The first secondary endpoint was a composite of cardiovascular mortality or hospitalization due to heart failure. Other secondary endpoints included cardiovascular mortality, all-cause and cause-specific hospitalizations (all time to first event) as well as days lost due to heart failure hospitalization or cardiovascular death (in % of follow-up time), and changes in quality of life and NYHA class. Overall, 710 CHF patients were recruited. The mean follow-up was 21.5±7.2 months, with a minimum of 12 months. Perspective The study will provide important prospective outcome data on the impact of telemedical management in patients with CHF.

Simple yet effective data augmentation techniques have been proposed for sentence-level and sentence-pair natural language processing tasks.Inspired by these efforts, we design and compare data augmentation for named entity recognition, which is usually modeled as a token-level sequence labeling problem.Through experiments on two data sets from the biomedical and materials science domains (i2b2-2010 and MaSciP), we show that simple augmentation can boost performance for both recurrent and transformer-based models, especially for small training sets.

With increasingly stringent emissions regulations and concurrent requirements for enhanced engine thermal efficiency, a comprehensive characterization of the automotive gasoline fuel spray has become essential. The acquisition of accurate and repeatable spray data is even more critical when a combustion strategy such as gasoline direct injection is to be utilized. Without industry-wide standardization of testing procedures, large variablilities have been experienced in attempts to verify the claimed spray performance values for the Sauter mean diameter, Dv90, tip penetration and cone angle of many types of fuel sprays. A new SAE Recommended Practice document, J2715, has been developed by the SAE Gasoline Fuel Injection Standards Committee (GFISC) and is now available for the measurement and characterization of the fuel sprays from both gasoline direct injection and port fuel injection injectors. A primary motivation for the development of the standardized procedures for test configuration, data acquisition, data reduction and reporting was to achieve significant reductions in the test-to-test and laboratory-to-laboratory variabilities of such reported spray data. All of the major areas of fuel injector spray testing and characterization are addressed in detail in the document, including spray imaging, high-resolution patternation and drop sizing by both phase-Doppler interferometry and laser diffraction. Valuable lessons regarding the definitions and interpretations of commonly-used spray parameters were learned during the development of the J2715 document, and these are presented and discussed. Based upon the five years of committee discussions and consensus decisions, five key recommendations on fuel spray measurement and characterization are made to the worldwide automotive industry. The first, and most important, recommendation is that the Recommended Practices in SAE J2715 be utilized by the spray laboratories of all automotive companies and injector manufacturers in place of the myriad of in-house test protocols that are currently being used. To evaluate and quantify the efficacy of the new Recommended Practices in J2715, a comprehensive program of round-robin spray characterization tests was designed, and is currently being conducted in the spray testing laboratories of six injector manufacturers and end-users worldwide. This two-year testing protocol will be completed in mid-2008 and will compare the results of in-house testing procedures to those obtained using the J2715 procedures. This round-robin test program is described in detail, and an informative example of the initial test results for the direct-injection spray angle and spray-tip penetration is provided and discussed.

The orientation selectivity, ocular dominance, and binocular disparity tuning of 272 cells in areas 17 and 18 of barbiturate-anesthetized, paralyzed cats were studied with automated, quantitative techniques. Disparity was varied along the axis orthogonal to each cell's best orientation. Binocular correspondence was established by means of a reference electrode positioned at the boundary of lamina A and A1 in the area centralis representation of the lateral geniculate nucleus. Measures were derived that expressed each cell's disparity sensitivity and best disparity and the shape and slope of its tuning curve. Cells were found that corresponded to categories described by previous authors ("disparity-insensitive," "tuned excitatory," "near," and "far" cells), but many others had intermediate response patterns, or patterns that were difficult to categorize. Quantitative analysis suggested that the various types belong to a continuum. No relationship could be established between a cell's best orientation and its ocular dominance or any aspect of its disparity tuning. There was no relationship between a cell's ocular dominance and its sensitivity to disparity. Ocular dominance and best disparity were related. As reported by others, cells with best disparities close to zero (the fixation plane) tended to have balanced ocularity, while cells with best disparities in the near or far range had a broad distribution of ocular dominance. Among cells with receptive fields near the vertical meridian, those preferring far disparities tended to be dominated by the contralateral eye, and those preferring near disparities by the ipsilateral eye. It is suggested that this relationship follows from the geometry of near and far images and the pattern of decussation in the visual pathway. There was a significant grouping of cells with similar best disparities along tangential electrode tracks. We believe that this grouping is due to the columnar organization for ocular dominance and the relationship between ocular dominance and best disparity. No evidence was found for a columnar segregation of disparity-sensitive and disparity-insensitive cells.

We consider the problem of next-best view selection for volumetric reconstruction of an object by a mobile robot equipped with a camera. Based on a probabilistic volumetric map that is built in real time, the robot can quantify the expected information gain from a set of discrete candidate views. We propose and evaluate several formulations to quantify this information gain for the volumetric reconstruction task, including visibility likelihood and the likelihood of seeing new parts of the object. These metrics are combined with the cost of robot movement in utility functions. The next best view is selected by optimizing these functions, aiming to maximize the likelihood of discovering new parts of the object. We evaluate the functions with simulated and real world experiments within a modular software system that is adaptable to other robotic platforms and reconstruction problems. We release our implementation open source.

Influenza virus epidemics are associated with excess mortality due to cardiovascular diseases. There are several case reports of excessive coagulation during generalised influenza virus infection. In this study, we demonstrate the ability of respiratory viruses (influenza A, influenza B, parainfluenza-1, respiratory syncytial virus, adenovirus, cytomegalovirus) to infect lung fibroblasts and human umbilical vein endothelial cells in culture. All viral pathogens induced procoagulant activity in infected endothelial cells, as determined in a one-stage clotting assay, by causing an average 55% reduction in the clotting time. When factor VII deficient plasma was used clotting time was not reduced. The induction of procoagulant activity was associated with a 4- to 5-fold increase in the expression of tissue factor, as measured by the generation of factor Xa. Both experiments indicate that the procoagulant activity of endothelial cells in response to infection with respiratory viruses is caused by upregulation of the extrinsic pathway. Although both enveloped viruses and a non-enveloped virus (adenovirus) induced procoagulant activity in endothelial cells by stimulating tissue factor expression, the role of the viral envelope in the assembly of the prothrombinase complex remains uncertain. We conclude that both enveloped and non-enveloped respiratory viruses are capable of infecting cultured human endothelial cells and causing a shift from anticoagulant to procoagulant activity associated with the induction of tissue factor expression.

Micromachined angular rate sensors are key elements in several automotive systems, thus enabling highly sophisticated applications like rollover detection and mitigation, navigation systems, electronic stability program, and other future vehicle stabilizing and dynamics control systems. New automotive systems are demanding higher accuracy, better signal-to-noise ratio, higher robustness and insensitivity against external perturbations, better system availability and reliability, as well as easy application of the gyros. This paper is presenting the recent development, now the third generation, of micromachined angular rate sensors at Robert Bosch GmbH. Mass production was started in spring 2005. These surface micromachined gyroscopes exhibit outstanding performance compared to similar designs, especially in term of resolution, noise, and insensitivity against external perturbations

This paper proposes a machine vision approach for plant classification without segmentation and its application in agriculture. Our system can discriminate crop and weed plants growing in commercial fields where crop and weed grow close together and handles overlap between plants. Automated crop / weed discrimination enables weed control strategies with specific treatment of weeds to save cost and mitigate environmental impact. Instead of segmenting the image into individual leaves or plants, we use a Random Forest classifier to estimate crop/weed certainty at sparse pixel positions based on features extracted from a large overlapping neighborhood. These individual sparse results are spatially smoothed using a Markov Random Field and continuous crop/weed regions are inferred in full image resolution through interpolation. We evaluate our approach using a dataset of images captured in an organic carrot farm with an autonomous field robot under field conditions. Applying the plant classification system to images from our dataset and performing cross-validation in a leave one out scheme yields an average classification accuracy of 93.8 %.

The use of robots in precision farming has the potential to reduce the reliance on herbicides and pesticides through selectively spraying individual plants or through manual weed removal. A prerequisite for that is the ability of the robot to separate and identify the value crops and the weeds in the field. Based on the output of the robot's perception system, it can trigger the actuators for spraying or removal. In this paper, we address the problem of detecting sugar beet plants as well as weeds using a camera installed on a mobile field robot. We propose a system that performs vegetation detection, local as well as object‐based feature extraction, random forest classification, and smoothing through a Markov random field to obtain an accurate estimate of crops and weeds. We implemented and thoroughly evaluated our system using a real farm robot in different sugar beet fields, and we illustrate that our approach allows for accurately identifying weeds in a field.

A new generation of production-ready dual function sensor which combines a yaw rate sensor with a linear accelerometer, based on silicon micromachining, is presented. The sensor is designed for mass production and high performance applications such as vehicle control systems. A combination of surface and bulk micromachining leads to an advantage in design, signal evaluation and packaging. This paper discusses the design of the sensing elements: the yaw rate sensor consists of two bulk micromachined oscillating masses each of which supports a surface micromachined accelerometer for detection of the coriolis force. The sensing element for the linear acceleration is a separate surface micromachined accelerometer. The electrodynamic actuation and high Q-value of the oscillator allow packaging at atmospheric pressure. Characterization results of the device are presented.

Advancements in AI led to the emergence of in-memory-computing architectures as a promising solution for the associated computing and memory challenges. This study introduces a novel in-memory-computing (IMC) crossbar macro utilizing a multi-level ferroelectric field-effect transistor (FeFET) cell for multi-bit multiply and accumulate (MAC) operations. The proposed 1FeFET-1R cell design stores multi-bit information while minimizing device variability effects on accuracy. Experimental validation was performed using 28 nm HKMG technology-based FeFET devices. Unlike traditional resistive memory-based analog computing, our approach leverages the electrical characteristics of stored data within the memory cell to derive MAC operation results encoded in activation time and accumulated current. Remarkably, our design achieves 96.6% accuracy for handwriting recognition and 91.5% accuracy for image classification without extra training. Furthermore, it demonstrates exceptional performance, achieving 885.4 TOPS/W-nearly double that of existing designs. This study represents the first successful implementation of an in-memory macro using a multi-state FeFET cell for complete MAC operations, preserving crossbar density without additional structural overhead.

A monolithic sensor, fabricated using a technology that combines surface micromachining with a BiCMOS process, is described. The capacitive sensing element consists of a 10/spl mu/m thick layer of polysilicon that is deposited in an early stage of the IC fabrication sequence. A high degree of synergy is achieved and conflicting issues regarding the merging of the processes are avoided by us ing IC processing steps for manufacturing of the sensor element. Adhesion between parts of the sensor structure, during their release, is eliminated by using an HF vapor phase etching process for the sacrificial layer. The completed sensor has been characterized successfully.