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Although image change detection (ICD) methods provide good detection accuracy for many scenarios, most existing methods rely on place-specific background modeling. The time/space cost for such place-specific models is prohibitive for large-scale scenarios, such as long-term robotic visual simultaneous localization and mapping (SLAM). Therefore, we propose a novel ICD framework that is specifically customized for long-term SLAM. This study is inspired by the multi-map-based SLAM framework, where multiple maps can perform mutual diagnosis and hence do not require any explicit background modeling/model. We extend this multi-map-based diagnosis approach to a more generic single-map-based object-level diagnosis framework (i.e., ICD), where the self-localization module of SLAM, which is the change object indicator, can be used in its original form. Furthermore, we consider map diagnosis on a state-of-the-art deep convolutional neural network (DCN)-based SLAM system (instead of on conventional bag-of-words or landmark-based systems), in which the blackbox nature of the DCN complicates the diagnosis problem. Additionally, we consider a three-dimensional point cloud (PC)-based (instead of typical monocular color image-based) SLAM and adopt a state-of-the-art scan context PC descriptor for map diagnosis for the first time.

Highlights • Uterine laceration is extremely rare and little known, however it sometimes causes massive intraperitoneal bleeding and has poor prognosis. • Inner myometrial laceration may be caused by intrapartum physical stress, whereas uterine laceration in relatively early pregnancy might be occurred by tissue inadaptable for uterine enlargement. • To diagnosis uterine laceration in early pregnancy is quite difficult because of the absence of specific clinical findings. • Not only uterine rupture but also uterine laceration should be considered, and exploratory laparotomy should be performed appropriately when hemoperitoneum is strongly suspected., Introduction Although uterine rupture is well discussed, uterine laceration and partial myometrial laceration are little known. A previous report hypothesized that the stress of labor was associated with uterine laceration. Presentation of case We present a rare case of uterine laceration in a patient in the second trimester. A 34-year-old primigravida woman at 16 weeks’ gestation without a history of uterine surgery complained of sudden low abdominal pain. Ultrasonography showed fetal death and intraperitoneal free fluid. A laparotomy was performed, and partial uterine laceration in the posterior wall along with active bleeding was confirmed. Discussion The etiology of uterine laceration in early pregnancy might be different from both classical uterine rupture and previously published uterine laceration. We hypothesized that tissue inadaptable for uterine enlargement, such as that owing to endometriosis and subtle injury by surgical approach, may be associated with the onset mechanism. Conclusion The diagnosis of uterine laceration in early pregnancy is quite difficult because of the absence of specific clinical findings. However, it sometimes causes massive intraperitoneal bleeding and has poor prognosis. Therefore, when uterine laceration is suspected as a cause of hemoperitoneum in a pregnant women, clinicians should perfume exploratory laparotomy appropriately.

Image change detection is a fundamental problem for robotic map maintenance and long-term map learning. Local feature-based image comparison is one of the most basic schemes for addressing this problem. However, the local-feature approach encounters difficulties when the query and reference images involve different domains (e.g., time of the day, weather, season). In this paper, we address the local-feature approach from the novel perspective of object-level region features. This study is inspired by the recent success of object-level region features in cross-domain visual place recognition (CD-VPR). Unlike the previous contributions of the CD-VPR task, in the cross-domain change detection (CD-CD) tasks, we consider matching a small part (i.e., the change) of the scene and not the entire image, which is considerably more demanding. To address this issue, we explore the use of two independent object proposal techniques: supervised object proposal (e.g., YOLO) and unsupervised object proposal (e.g., BING). We combine these techniques and compute appearance features of their arbitrarily shaped objects by aggregating local features from a deep convolutional neural network (DCN). Experiments using a publicly available cross-season NCLT dataset validate the efficacy of the proposed approach.

We report the case of a 70-year-old man who developed a splenic infarction due to a thrombus in the pulmonary vein (PV) stump after left upper lobectomy (LUL). Preoperative imaging showed a mass measuring > 5 cm in the upper lobe of the left lung, and sputum cytology revealed squamous cell carcinoma. Therefore, video-assisted thoracoscopic LUL was performed. The postoperative course was uneventful but biochemical blood tests showed an increased inflammatory response. Contrast-enhanced computed tomography revealed splenic infarction and a thrombus in the left superior PV stump. Prompt treatment with anticoagulants was administered, and the patient was discharged with mild recovery. However, the patient developed cerebral infarction after discharge and died 33 days after the surgery. Splenic infarction is a rare postoperative complication, with only three reported cases, including this report. However, this condition should be considered along with PV thrombus when evaluating an increased inflammatory response after LUL.

BACKGROUND: Approximately 15–29.6% of patients with thymoma have myasthenia gravis (MG). Some of these patients develop MG after thymectomy despite having no history of MG or related symptoms. Few previous studies have examined the risk factors for the development of post-thymectomy MG in patients with thymoma. Herein, we retrospectively reviewed our institutional experience with patients with thymoma who developed MG after thymectomy. METHODS: Twenty-six patients with thymoma but without MG, who were tested preoperatively for anti-acetylcholine receptor antibody (anti-AChR-Ab) levels, underwent surgical resection at our hospital between 2013 and 2020. Patients with thymic carcinoma were excluded from the study. We evaluated the association of outcomes with preoperative anti-AChR-Ab levels and post-thymectomy MG. We performed a χ(2) test for bivariate analysis of categorical data. Differences were considered significant at P0.3 nmol/L) preoperative anti-AChR-Ab levels. Post-thymectomy MG occurred in two of the five patients (40%) with high preoperative anti-AChR-Ab levels. A high preoperative serum anti-AChR-Ab titer was significantly associated with post-thymectomy MG (P=0.0267). The anti-AChR-Ab titer was also measured postoperatively in four of the five (80%) patients with high preoperative levels. The anti-AChR-Ab titer decreased in two of these four patients, and neither developed postoperative MG. CONCLUSIONS: Preoperative and postoperative anti-AChR-Ab positivity might be associated with post-thymectomy MG. Therefore, regular measurement of anti-AChR-Ab levels after thymectomy is required.

Impetigo herpetiformis (IH) is a rare variant of generalized pustular psoriasis (GPP), which develops during pregnancy. GPP is associated with mutations of IL36RN, but it is still unclear whether the same is true of IH. A 20-year-old Japanese woman developed erythema and pustules on her trunk during the 27th week of her first pregnancy. Within 1 month, the skin lesions spread over her whole body, accompanied by fever. Skin biopsy revealed Kogoj's spongiform pustules in the epidermis and she was diagnosed with IH. Systemic administration of prednisolone failed to resolve the skin eruption, but it was partially improved by the addition of cyclosporin. The patient gave birth to a healthy female infant. After delivery, her erythema relapsed and the effect of granulocyte and monocyte adsorption apheresis was limited. Thus, secukinumab was administrated, and since then, she has maintained complete remission. Mutation analysis revealed a homozygous c.28C>T (p.Arg10X) mutation in IL36RN. Twelve cases of IH, including that presented here, have been reported together with the results of IL36RN genetic analyses, and 10 of the 12 cases occurred in East Asia (Japan and China) despite the fact that IL36RN mutations in GPP have been reported worldwide. Among 10 IH patients of East Asian descent, seven had IL36RN mutations, all of which were founder mutations causing GPP in East Asia: c.28C>T (p.Arg10X) or c.115+6T>C (p.Arg10ArgfsX1). Thus, East Asian founder mutations may play an important role in the pathogenesis of IH. IH patients with IL36RN mutations have a tendency to require biologics to resolve postpartum flare-ups or sustained psoriatic skin lesions. Because IL36RN mutation status may help predict postpartum flare-ups in IH patients, mutation analysis should be considered to enable preparation for biologic therapy of intractable flare-ups.

This paper addresses the problem of cross-season visual place classification (VPC) from the novel perspective of long-term map learning. Our goal is to enable transfer learning efficiently from one season to the next, at a small constant cost, and without wasting the robot’s available long-term-memory by memorizing very large amounts of training data. To achieve a good tradeoff between generalization and specialization abilities, we employ an ensemble of deep convolutional neural network (DCN) classifiers and consider the task of scheduling (when and which classifiers to retrain), given a previous season’s DCN classifiers as the sole prior knowledge. We present a unified framework for retraining scheduling and we discuss practical implementation strategies. Furthermore, we address the task of partitioning a robot’s workspace into places to define place classes in an unsupervised manner, as opposed to using uniform partitioning, so as to maximize VPC performance. Experiments using the publicly available NCLT dataset revealed that retraining scheduling of a DCN classifier ensemble is crucial in achieving a good balance between generalization and specialization. Additionally, it was found that the performance is significantly improved when using planned scheduling.

Objective Pregnancy is an opportunity for women to become aware of their risk of cardiovascular disease (CVD), because physiologic responses to dynamic hemodynamic changes can be observed during pregnancy. Accordingly, we hypothesized that blood pressure levels during pregnancy may be associated with the risk of CVD later in life. Study design We used data from the Iwaki Health Promotion Project and designed a population-based, cross-sectional study. In this study, Maternity Health Record Books were collected from women over 40 years of age in order to obtain reliable data regarding past pregnancies. Of a total of 642 women, 432 were selected according to the study criteria. Main outcome measures The associations between blood pressure levels during pregnancy and major CVD risk factors (hypertension and dyslipidemia) were analyzed retrospectively. Results A 10 mmHg increase in the mean diastolic blood pressure level between gestational weeks 12 and 42 conferred a 1.70- and 1.55-fold increase in the risk of hypertension and dyslipidemia, respectively, in later life. Conclusions Blood pressure levels during pregnancy may be associated with CVD risk and could therefore be a useful predictive marker.

Map matching, the ability to match a local map built by a mobile robot to previously built maps, is crucial in many robotic mapping, self-localization, and simultaneous localization and mapping (SL...

This paper addresses the problem of change detection from a novel perspective of long-term map learning. We are particularly interested in designing an approach that can scale to large maps and that can function under global uncertainty in the viewpoint (i.e., GPS-denied situations). Our approach, which utilizes a compact bag-of-words (BoW) scene model, makes several contributions to the problem: 1) Two kinds of prior information are extracted from the view sequence map and used for change detection. Further, we propose a novel type of prior, called motion prior, to predict the relative motions of stationary objects and anomaly ego-motion detection. The proposed prior is also useful for distinguishing stationary from non-stationary objects. 2) A small set of good reference images (e.g., 10) are efficiently retrieved from the view sequence map by employing the recently developed Bag-of-Local-Convolutional-Features (BoLCF) scene model. 3) Change detection is reformulated as a scene retrieval over these reference images to find changed objects using a novel spatial Bag-of-Words (SBoW) scene model. Evaluations conducted of individual techniques and also their combinations on a challenging dataset of highly dynamic scenes in the publicly available Malaga dataset verify their efficacy.

This paper addresses the problem of cross-domain change detection from a novel perspective of image-to-image translation. In general, change detection aims to identify interesting changes between a given query image and a reference image of the same scene taken at a different time. This problem becomes a challenging one when query and reference images involve different domains (e.g., time of the day, weather, and season) due to variations in object appearance and a limited amount of training examples. In this study, we address the above issue by leveraging a generative adversarial network (GAN). Our key concept is to use a limited amount of training data to train a GAN-based image translator that maps a reference image to a virtual image that cannot be discriminated from query domain images. This enables us to treat the cross-domain change detection task as an in-domain image comparison. This allows us to leverage the large body of literature on in-domain generic change detectors. As a part of our contribution, we investigate to what extent the usage of the translation GAN can alleviate the issue of domain shift by developing and evaluating several change detection algorithms. In addition, we also consider the use of visual place recognition as a method for mining more appropriate reference images over the space of virtual images. Experimental results on cross-season change detection using the publicly available North Campus Long-Term autonomy dataset validate the efficacy of the proposed approach.

In exploring the 1-to-Nmap matching problem that exploits a compact map data description, we hope to improve map matching scalability used in robot vision tasks. We propose explicitly targeting fast succinct map matching, which consists of map matching subtasks alone. These tasks include offline map matching attempts to find compact part-based scene models that effectively explain individual maps by using fewer larger parts. These tasks also include online map matching to find correspondence between part-based maps efficiently. Our part-based scene modeling approach is unsupervised and uses common pattern discovery (CPD) between input and known reference maps. Results of our experiments, which use a publicly available radish dataset, confirm the effectiveness of our proposed approach.

Implicit learning and transfer in sequence acquisition play important roles in daily life. Several previous studies have found that even when participants are not aware that a transfer sequence has been transformed from the learning sequence, they are able to perform the transfer sequence faster and more accurately; this suggests implicit transfer of visuomotor sequences. Here, we investigated whether implicit transfer could be modulated by the number of trials completed in a learning session. Participants learned a sequence through trial and error, known as the m × n task (Hikosaka et al. in J Neurophysiol 74:1652-1661, 1995). In the learning session, participants were required to successfully perform the same sequence 4, 12, 16, or 20 times. In the transfer session, participants then learned one of two other sequences: one where the button configuration Vertically Mirrored the learning sequence, or a randomly generated sequence. Our results show that even when participants did not notice the alternation rule (i.e., vertical mirroring), their total working time was less and their total number of errors was lower in the transfer session compared with those who performed a Random sequence, irrespective of the number of trials completed in the learning session. This result suggests that implicit transfer likely occurs even over a shorter learning duration.

Preferences for colors and geometric shapes vary considerably across individuals. Studies have demonstrated these variations in preference separately for colors and shapes, but the relationships between preference variations for colors and shapes are not yet known. By measuring individual preferences for basic colors and shapes, we found that color preferences and shape preferences were partly, but systematically, correlated. People who preferred some simple shapes (e.g., cone, pyramid) tended to prefer some light or warm colors (e.g., yellow, orange). In contrast, people who preferred some complex shapes (e.g., scrambled truncated-pyramid, scrambled pyramid) tended to prefer some dark or cold colors (e.g., blue, blue-green). That is, people who like “simple” or “complex” visual features might tend to like “light or warm” or “dark or cold” visual features. These results indicate that individual preferences for colors and shapes might not be independent, but could be correlated and intertwined to some extent. We suggest that the semantic information associated with colors and shapes underlies the cross preferences. © 2015 Wiley Periodicals, Inc. Col Res Appl, 41, 188–195, 2016

Hypertensive disorders of pregnancy (HDP) and chronic kidney disease (CKD) are well-known risk factors for cardiovascular disease (CVD) in later life. However, few studies have investigated the association of HDP with CKD. Moreover, these studies utilized either registry- or clinical-based data and did not include subclinical CKD patients. To address this gap in the literature, we investigated whether HDP is related to CKD, diagnosed based on the estimated glomerular filtration rate (eGFR), in later life. We designed a population-based, retrospective study, and reviewed the results of blood and physiological examinations as well as the results of pregnancy data available in patients' Maternity Health Record Books for 312 women. We identified 15 women with a diagnosis of CKD based on the eGFR, and 14 women with HDP. We found that women who experienced HDP had a high risk of CKD in later life compared with women without HDP (odds ratio (OR): 4.854; 95% confidence interval (CI): 1.042-22.621). Compared with normotensive women, those who were hypertensive at the time of the examination were significantly associated with CKD (OR: 3.109; 95% CI: 1.213-11.510). Awareness regarding the risk for CKD and CVD in a relatively young age can enable women to prevent diseases effectively.

We propose a novel bag-of-words (BoW) framework for building and retrieving a compact database of view images for use in robotic localization, mapping, and SLAM applications. Unlike most previous methods, our method does not describe an image based on its many small local features (e.g., bag-of-SIFT-features). Instead, the proposed bag-of-bounding-boxes (BoBB) approach attempts to describe an image based on fewer larger object patterns, which leads to a semantic and compact image descriptor. To make the view retrieval systemmore practical and autonomous, the object pattern discovery process is unsupervised through a common pattern discovery (CPD) between the input and known reference images without requiring the use of a pre-trained object detector. Moreover, our CPD subtask does not rely on good image segmentation techniques and is able to handle scale variations by exploiting the recently developed CPD technique, i.e., a spatial randompartition. Following a traditional bounding-box based object annotation and knowledge transfer, we compactly describe an image in a BoBB form. Using a slightly modified inverted file system, we efficiently index and/or search for the BoBB descriptors. Experiments using the publicly available “Robot-Car” dataset show that the proposed method achieves accurate object-level view image retrieval using significantly compact image descriptors, e.g., 20 words per image.

Objective: We aimed to investigate how ordered mappings (e.g., left-to-right and right-to-left order representations) would interfere with each other. Background: Mental representations of numbers and letters are linked with spatial representation and can be changed intentionally. Method: The experiment consisted of three sessions. In the digit-alone session, two digits randomly selected from [1], [2], and [3] were shown. If the two digits were the same, participants pressed the button corresponding to the digit, and if the digits differed, they pressed the remaining button. The response buttons were ordered [1][2][3] from the left. In the letter-alone session, three different button configurations were prepared: sequential [A][B][C], reversed [C][B][A], or partially reversed [B][A][C]. The same-versus-different rules were basically identical to those in the digit task. In the mixed session, trials of the digit task and those of the letter task were randomly mixed. Results: We found that two ordinal representations did not interfere with each other when they shared the same direction of order ([1][2][3] vs. [A][B][C]), two ordinal mappings interfered with each other when they had different directions of order ([1][2][3] vs. [C][B][A]), and an ordinal mapping ([1][2][3]) was affected by a nonordinal mapping ([B][A][C]), but the nonordinal mapping was less affected by the ordinal mapping. Conclusion: The mapping between ordinal information and space can be modulated by top-down processes, and it is prone to interference depending on the nature of another coexisting mapping. Application: Our findings may be used in designing response assignments for input devices for multiple functions.

Obtaining a compact representation of a large-size datapoint map built by mapper robots is a critical issue for recent SLAM applications. This ”map compression” problem is explored from a novel perspective of dictionary-based map compression in the paper. The primary contribution of the paper is proposal of an incremental scheme for simultaneous mapping and map-compression applications. An incremental map compressor is presented by employing a modified RANSAC map-matching scheme as well as the compact projection technique. Experiments show promising results in terms of compression speed, compactness of data and structure, as well as an application to the compression distance.

Map retrieval, the problem of similarity search among a large collection of 2D pointset maps previously built by mobile robots, is crucial for autonomous navigation in both indoor and outdoor environments. Unlike previous Bag-of-words scene model which lacks spatial layout information, we exploit a holistic local map descriptor which is view-independent and highly discriminative. The current study is inspired by our recent papers on “local map descriptor”, in which the viewpoint or the origin of local map coordinate is planned by scene parsing and the spatial layout of a local map is represented with respect to the planned viewpoint. The main contribution of this study is to build on the framework of local map descriptor and experimentally evaluate the effectiveness of the proposed method. The key observation is that accuracy of the spatial layout should be improved by introducing an accurate local mapping technique. To this end, we implemented the state-of-the-art particle filter-based mapping algorithm of Grid Mapping. The next contribution is that we conducted map retrieval experiments using a real mobile robot in feature-less office-like environments. We experimentally demonstrate the effectiveness of the proposed approach.

In the present study, we examined the effects of explicit knowledge, obtained through instruction or spontaneous detection, on the transfer of visuomotor sequence learning. In the learning session, participants learned a visuomotor sequence, via trial and error. In the transfer session, the order of the sequence was reversed from that of the learning session. Before the commencement of the transfer session, some participants received explicit instruction regarding the reversal rule (i.e., Instruction group), while the others did not receive any information and were sorted into either an Aware or Unaware group, as assessed by interview conducted after the transfer session. Participants in the Instruction and Aware groups performed with fewer errors than the Unaware group in the transfer session. The participants in the Instruction group showed slower speed than the Aware and Unaware groups in the transfer session, and the sluggishness likely persisted even in late learning. These results suggest that explicit knowledge reduces errors in visuomotor skill transfer, but may interfere with performance speed, particularly when explicit knowledge is provided, as opposed to being spontaneously discovered.

Through practice, people are able to integrate a secondary sequence (e.g., a stimulus-based sequence) into a primary sequence (e.g., a response-based sequence), but it is still controversial whether the integrated sequences lead to better learning than only the primary sequence. In the present study, we aimed to investigate the effects of a sequence that integrated space and color sequences on early and late learning phases (corresponding to effector-independent and effector-dependent learning, respectively) and how the effects differed in the integrated and primary sequences in each learning phase. In the task, the participants were required to learn a sequence of button presses using trial-and-error and to perform the sequence successfully for 20 trials (m × n task). First, in the baseline task, all participants learned a non-colored sequence, in which the response button always turned red. Then, in the learning task, the participants were assigned to two groups: a colored sequence group (i.e., space and color) or a non-colored sequence group (i.e., space). In the colored sequence, the response button turned a pre-determined color and the participants were instructed to attend to the sequences of both location and color as much as they could. The results showed that the participants who performed the colored sequence acquired the correct button presses of the sequence earlier, but showed a slower mean performance time than those who performed the non-colored sequence. Moreover, the slower performance time in the colored sequence group remained in a subsequent transfer task in which the spatial configurations of the buttons were vertically mirrored from the learning task. These results indicated that if participants explicitly attended to both the spatial response sequence and color stimulus sequence at the same time, they could develop their spatial representations of the sequence earlier (i.e., early development of the effector-independent learning), but might not be able to enhance their motor representations of the sequence (i.e., late development of the effector-dependent learning). Thus, the undeveloped effector-dependent representations in the colored sequence group directly led to a long performance time in the transfer sequence.

It has been known remembered locations of visual stimuli are systematically distorted in a two-dimensional (i.e., retinal) coordinate, which includes the foveal bias, memory averaging, and landmark effect. The present study aimed at examining how the remembered depth position of a visual target would be distorted. Also, we examined whether depth distortion would differ for perceptual and motor-related tasks. In the experiments, a visual target was presented for one second at various distances from the observers by using a 3D projector. The fixation distance was also varied. After the disappearance of the target, observers performed either perceptual judgment (the method of constant to estimate the point of psychological subjective equality) or motor response (by using a 3D mouse) for the remembered target distance. The results showed that the remembered depth of the target was compressed toward the averaged depth of the possible depth range for both perceptual and motor responses. In addition, however, the perceptual responses tended to overestimate the depth when the fixation depth was closer than or the same as the nearest possible depth of the target. No bias was observed when the fixation depth was farther than the nearest possible depth. For the motor responses, there was a general underestimation irrespective of fixation depth. These results suggest that spatial memory of depth for visual stimuli may be qualitatively different between perceptual and motor responses.

Retrieving a large collection of environment maps built by mapper robots is a key problem in mobile robot self-localization. The map retrieval problem is studied from the novel perspective of the multi-scale Bag-Of-Features (BOF) approach in this paper. In general, the multi-scale approach is advantageous in capturing both the global structure and the local details of a given map. BOF map retrieval is advantageous in its compact map representation as well as the efficient map retrieval using an inverted file system. The main contribution of this paper is combining the advantages of both approaches. Our approach is based on multi cue BOF as well as packing BOF, and achieves the efficiency and compactness of the map retrieval system. Experiments evaluate the effectiveness of the techniques presented using a large collection of environment maps.

Obtaining a compact representation of a large-size feature map built by mapper robots is a critical issue in recent mobile robotics. This “map compression” problem is explored from a novel perspective of dictionary-based data compression techniques in the paper. The primary contribution of the paper is the proposal of the dictionary-based map compression approach. A map compression system is presented by employing RANSAC map matching and sparse coding as building blocks. The effectiveness levels of the proposed techniques is investigated in terms of map compression ratio, compression speed, the retrieval performance of compressed/decompressed maps, as well as applications to the Kolmogorov complexity.

Introduction Hypertensive disorders of pregnancy (HDP) and chronic kidney disease (CKD) are well-known risk factors for cardiovascular disease (CVD) in later life. However, few studies have investigated the association of HDP with CKD. Moreover, these studies utilized either registry- or clinical-based data and did not include subclinical CKD patients. Objective To address this gap in the literature, we investigated whether HDP is related to CKD, diagnosed based on the estimated glomerular filtration rate (eGFR), in later life. Methods We designed a population-based, retrospective study, and reviewed the results of blood and physiological examinations as well as the results of pregnancy data available in patients’ Maternity Health Record Books for 312 women. Results We identified 15 women with a diagnosis of CKD based on the eGFR, and 14 women with HDP. We found that women who experienced HDP had a high risk of CKD in later life compared with women without HDP (odds ratio (OR): 4.854; 95% confidence interval (CI): 1.042–22.621). Compared with normotensive women, those who were hypertensive at the time of the examination were significantly associated with CKD (OR: 3.109; 95% CI: 1.213–11.510). Discussion Awareness regarding the risk for CKD and CVD in a relatively young age can enable women to prevent diseases effectively.

Aim To clarify the appropriate management of hypertensive disorder of pregnancy (HDP) and establish a long-term follow-up system for women with HDP after delivery. We investigated issues with HDP management approaches by evaluating blood pressure measurement on medical examination, home blood pressure measurement (HBPM) penetration rate, time of blood pressure examination during labor, and follow-up procedure after delivery in women with HDP. Methods We distributed questionnaires on blood pressure management during pregnancy, at delivery, and after delivery to 53 obstetrics and gynecology departments of professional medical institutions in Aomori prefecture, Japan. Results We retrieved completed questionnaires from 52 institutions, and analyzed responses to questionnaires from pregnant women in 39 institutions. Some institutions reported that antihypertensive medication was begun for mild hypertension (140/90 mmHg); these institutions had set a lower target BP. Only 56% of institutions measured blood pressure after labor pain onset. The postpartum follow-up was carried out not only by obstetric and gynecological clinics, but also by many institutions. However, sufficient education on the risk of recurrence in a subsequent pregnancy and lifestyle guidance were not provided. Conclusions There is little consensus on the timing of antihypertensive medication initiation or the appropriate level of blood pressure control. Labor onset hypertension may have been overlooked. Short-term follow-up of women with HDP was found to be frequently carried out; however, long-term follow-up was not. We will continue to provide the appropriate follow-up duration and approach to women with a history of HDP and to proactively engage in lifestyle interventions with the aim of improving longevity.

This paper presents a novel approach for robot localization using landmark maps. With recent progress in SLAM researches, it has become crucial for a robot to obtain and use large-size maps that are incrementally built by other mapper robots. Our localization approach successfully works with such incremental and large-size maps. In literature, RANSAC map-matching has been a promising approach for large-size maps. We extend the RANSAC map-matching so as to deal with incremental maps. We combine the incremental RANSAC with an incremental LSH database and develop a hybrid of the position-based and the appearance-based approaches. A series of experiments using radish dataset show promising results.

Aim: Hyaluronate plays an important role in the regulation of cervical function during parturition. In our previous study we showed that 4-methylumbelliferone (MU) suppresses hyaluronate synthesis by cultured human skin fibroblasts. The present study investigated the effects of MU on fibroblasts obtained from the human uterine cervix and assessed the possibility of controlling cervical ripening with MU. Methods: Human uterine cervical fibroblasts were collected from uterine cervices obtained from the uteri of three patients who had a total hysterectomy for uterine myoma at Hirosaki University Hospital. The fibroblasts were cultured in Dulbecco's modified Eagle's medium until confluence. They were then cultured in medium containing [3H]glucosamine (0.074 MBq/mL) with various MU doses. Hyaluronate synthesis was evaluated by assessing the incorporation of [3H]glucosamine into the soluble fraction of hyaluronate. Three independent studies were carried out on each specimen to clarify whether MU causes compositional changes or promotes hyaluronate degradation, whether the inhibitory effects of MU on hyaluronate synthesis are dose-dependent, and whether the effects of MU are reversible. Results: MU added to the medium of the cultured cells reduced the synthesis of hyaluronate in a dose-dependent manner. After MU was removed from the medium, hyaluronate synthesis recommenced, and the amount of [3H]hyaluronate synthesized was similar to the control level. Conclusions: MU inhibits the synthesis of hyaluronate in human uterine cervical fibroblasts.

This work is concerned with the problem of robot localization using standard RFID tags as landmarks and an RFID reader as a landmark sensor. A main advantage of such an RFID-based localization system is the availability of landmark ID measurement, which trivially solves the data association problem. While the main drawback of an RFID system is its low spatial accuracy. The result in this paper is an improvement of the localization accuracy for a standard short-range RFID sensor. One of the main contributions is a proposal of a machine learning approach in which multiple classifiers are trained to distinguish RFID-signal features of each location. Another contribution is a design tool for tag arrangement by which the tag configuration needs not be manually designed by the user, but can be automatically recommended by the system. The effectiveness of the proposed technique is evaluated experimentally with a real mobile robot and an RFID system.

A problem of probabilistic vision-based multi-person tracking with a monocular camera in a cluttered office environment is addressed. In such a case, it is often difficult to obtain reliable measurements of the absolute position of a person on the floor plane due to the inherent uncertainty in depth. To deal with this problem, a novel measurement technique based on occlusion reasoning is proposed and combined with a standard particle filtering technique. This technique is based on the relative position of a person with respect to background objects. The effectiveness of the proposed technique is investigated in an experiment where two persons overlap on the image plane.

Vehicle relocation is the problem in which a mobile robot has to estimate the self-position with respect to an a priori map of landmarks using the perception and the motion measurements without using any knowledge of the initial self-position. Recently, RANdom SAmple Consensus (RANSAC), a robust multi-hypothesis estimator, has been successfully applied to offline relocation in static environments. On the other hand, online relocation in dynamic environments is still a difficult problem, for available computation time is always limited, and for measurement include many outliers. To realize real time algorithm for such an online process, we have developed an incremental version of RANSAC algorithm by extending an efficient preemption RANSAC scheme. This novel scheme named incremental RANSAC is able to find inlier hypotheses of self-positions out of large number of outlier hypotheses contaminated by outlier measurements., Comment: Offprint of ICRA2006 paper

Summary The surgical management of axillary lymph nodes in early breast cancer remains controversial, although several maneuvers have been developed such as axillary node clearance (ANC), four node axillary sampling (4NAS), and sentinel node biopsy. A total of 237 cases of primary breast cancer at stages I and II were studied prospectively to elucidate the correlation between 4NAS and ANC. All calculated values by 4NAS showed high sensitivity, specificity, and overall accuracy as follows in this study: 92.9%, 100% and 98.5% for stage I, and 93.8%, 100% and 98.3% for stage II. Likewise, the false negative (FN) rates were 7.1% for stage I, 6.3% for stage II, 6.7% for T1, 6.4% for T2, 7.4% for N0, 0% for N1, and 6.5% for all cases. These rates were very low, although 7.4% for N0 and 0% for N1 were quite clearly different. This implies that all FN cases were N0, and were caused by micrometastases with normal consistency and size. 4NAS may be as accurate a procedure as ANC in assessing axillary nodal stage.

Global localization is the problem in which a mobile robot has to estimate the self-position with respect to an a priori given map as it navigates without using any a priori knowledge of the initial self-position. Previous studies on global localization mainly focused on static environments, where the a priori map is almost correct. On the other hand, in dynamic environments, there are several sources of computational complexity. For example, not only the self-position but also the map should be estimated due to the map errors. The main contribution of this paper is to address such computational complexity by decomposing our global localization problem into two smaller subproblems, and solving the subproblems in a practical computation time. Also, we demonstrate the robustness and the efficiency of the proposed method in various large and complex environments.

The Nottingham Prognostic Index (NPI) is used to predict survival in patients with breast cancer. This index is based on tumor size, lymph node stage, and histological grade and allows the stratification of patients into three different prognostic groups. Our aim was to verify the effect of some prognostic variables on survival and to establish the independent influence of each of these variables by a survival regression analysis. We applied the NPI to the same group of patients to assess its predictive power and reproducibility. We evaluated 311 women with breast cancer treated between January 1993 and December 1998. In a multivariate analysis (Cox proportional hazard model), only size, lymph node involvement, and histological grade were independent prognostic factors. The survival curves obtained after applying the NPI were similar to those for the factors with independent prognostic significance derived from our multivariate analysis. The NPI allows us to accurately predict prognosis, and we advocate its standardized use.

Background. Breast carcinoma and precancer are thought to start in the lining of the milk duct or lobule. Methods. At 5weeks of age, rats received a intraperitoneal (ip) injection of MNU for carcinogenesis. After mammary tumors were identified macroscopically using fiberscope, the rats were treated with perductal (pd) or ip injection of paclitaxel tri-weekly. At 36 weeks after MNU injection, tumor burden (No. of >1cm palpable mammary tumors/rat), total number of mammary carcinoma, apoptosis (AI), and microvessel density (MVD) were measured. Results. The administration of paclitaxel through the duct did not produce any toxic side effect. The tumor burden and total number of mammary carcinoma in the pd paclitaxel-treated group were significantly reduced compared to those seen in the ip paclitaxel-treated group. In addition, in the pd paclitaxel-treated group, AI was also increased and MVD was decreased, compared to those in the ip paclitaxel-treated group. Conclusion. Local administration of paclitaxel may be useful for treatment of breast cancer.

日常診療において線維腺腫に乳癌を合併した症例に遭遇することは稀である.通常,線維腺腫はマンモグラフィ,乳腺エコー後に穿刺・吸引細胞診を施行し良性と診断され経過観察されていることが多い. 約20年前に穿刺・吸引細胞診で良性と診断されていた線維腺腫が,今回,乳頭異常分泌・乳頭痛にて乳管・腫瘍切除術を施行したところ,線維腺腫の中心部にDCISを認めた稀な症例を経験したので,文献的考察を含め報告する.

1Department of Obstetrics & Gynecology Nara Medical University, 2Nagoya City West Medical Center, 3Osaka City General Hospital, 4Juntendo University, 5Tohoku University, 6Osaka University, 7Japanese Red Cross Katsushika Maternity Hospital, 8Hokkaido University, 9Saitama Medical University, 10Tokyo Medical University Hachioji Medical Center, 11Ohno Ladies’ Clinic, 12Hamamatsu Medical University, 13Nagoya University, 14Hirosaki University, 15Aichi Medical University

Ninty-three cases of both invasive ductal and lobular carcinoma were examined to clarify the relationship between the clinicopathological factors and cellularity (cell density) or total cancer cells number in carcinoma tissues. The cellularity showed significant correlation with tumor size and vascular invasion, but not with other clinicopathological factors (menopausal status, operation method, ER status, histological grade or type, lymph node stage) and prognosis. The total cancer cell number revealed a positive relationship with survival (overall survival) and disease-free interval (DFI) by univariate analysis, even though it did not show any positive correlation with other clinicopathological factors in this study. Moreover, it was not found to have any stronger impact than other previously reported prognostic factors such as tumor size, lymph node stage or tumor grade by multivariate analysis. From these evidences, we speculate that the cellularity correlates with expansion or invasion of tumor cells and the total number of cancer cells reflects the prognosis of the tumor-bearing host, although it does not play a major role in prediction.

It is fundamental problem for mobile robots to detect 2D free regions where they can move by local sensing. In many indoor environments, there may be lots of objects, such as chairs, desks, etc., and much portion of the free region can not be directly detected. To resolve this problem, we have developed a method for detecting free regions in which a robot visually tracks walking human, and regards 2D regions swept by the human as free regions. Based on this idea, we propose a method for building a map of obstacles and free regions, and navigation with an distance transform based path planning algorithm. The free regions were obtained reliably by combining stereo vision and visual tracking techniques.