Estimating Bridge Natural Frequencies Based on Modal Analysis of Vehicle-Bridge Synchronized Vibration Data.

This paper presents a method for accurately estimating the natural frequencies of bridges by simultaneously measuring the acceleration vibration data of vehicles and bridges and applying modal analysis theory. Vibration sensors synchronized with GPS timing were installed on both vehicles and bridges, achieving stable and high-precision time synchronization. This enabled the computation of the bridge's Frequency Response Functions (FRFs) for each mode, leading to a refined estimation of natural frequencies. The validity of the theory was confirmed through numerical simulations and experimental tests. The simulations confirmed its effectiveness, and similar trends were observed in actual bridge measurements. Consequently, this method significantly enhances the feasibility of bridge health monitoring systems. The proposed method is suitable for road bridges with spans ranging from short- to medium-span length, where the vehicle is capable of exciting the bridge.

Impact of subjective well-being on physical frailty in middle-aged and elderly Japanese with high social isolation.

Social isolation exacerbates physical frailty and is associated with subjective well-being. Even those with high levels of social isolation may have different health statuses depending on the type of isolation and their subjective well-being. However, the effect of subjective well-being on the relationship between social isolation and physical frailty remains unclear. This study examined whether the risk of physical frailty was the same for individuals with social isolation according to high and low subjective well-being. The study participants included 1,953 middle-aged Japanese adults aged 45 years and older. Physical frailty was assessed using a modified version of the Fried phenotype criteria. Probabilistic Latent Semantic Analysis was used to classify participants according to social isolation indicators. Subsequently, we focused on the groups with high social isolation and classified them according to whether their subjective well-being was high or low. Subjective well-being was evaluated using the Shiawase and Ikigai scales, which are concepts used in Japan. Finally, we used survival time analysis to examine the relationship between Shiawase or Ikigai and physical frailty in groups with high social isolation. The participants were classified into four groups based on their social isolation status. The physical frailty rate of the high social isolation class was 37.0%, which was significantly higher than that of the other classes. Survival time analysis revealed that among people with high social isolation, those with high Shiawase and Ikigai had a significantly lower risk of physical frailty than those with low Shiawase and Ikigai. All individuals with high social isolation are not at a high risk of physical frailty. The findings reveal that even those with high level of social isolation may have a lower risk of physical frailty if their subjective well-being is high. These results will contribute to promoting the prevention of frailty in middle-aged and older adults.

Data collaboration analysis in predicting diabetes from a small amount of health checkup data.

Recent studies showed that machine learning models such as gradient-boosting decision tree (GBDT) can predict diabetes with high accuracy from big data. In this study, we asked whether highly accurate prediction of diabetes is possible even from small data by expanding the amount of data through data collaboration (DC) analysis, a modern framework for integrating and analyzing data accumulated at multiple institutions while ensuring confidentiality. To this end, we focused on data from two institutions: health checkup data of 1502 citizens accumulated in Tsukuba City and health history data of 1399 patients collected at the University of Tsukuba Hospital. When using only the health checkup data, the ROC-AUC and Recall for logistic regression (LR) were 0.858 ± 0.014 and 0.970 ± 0.019, respectively, while those for GBDT were 0.856 ± 0.014 and 0.983 ± 0.016, respectively. When using also the health history data through DC analysis, these values for LR improved to 0.875 ± 0.013 and 0.993 ± 0.009, respectively, while those for GBDT deteriorated because of the low compatibility with a method used for confidential data sharing (although DC analysis brought improvements). Even in a situation where health checkup data of only 324 citizens are available, the ROC-AUC and Recall for LR were 0.767 ± 0.025 and 0.867 ± 0.04, respectively, thanks to DC analysis, indicating an 11% and 12% improvement. Thus, we concluded that the answer to the above question was "Yes" for LR but "No" for GBDT for the data set tested in this study.

Practical Application of Drive-By Monitoring Technology to Road Roughness Estimation Using Buses in Service.

The efficiency of vehicles and travel comfort are maintained by the effective management of road pavement conditions. Pavement conditions can be inspected at a low cost by drive-by monitoring technology. Drive-by monitoring technology is a method of collecting data from sensors installed on a running vehicle. This technique enables quick and low-cost inspections. However, most existing technologies assume that the vehicle runs at a constant speed. Therefore, this study devises a theoretical framework that estimates road unevenness without prior information about the vehicle's mechanical parameters even when the running speed changes. This paper also shows the required function of sensors for this scheme. The required ability is to collect the three-axis acceleration vibration and position data simultaneously. A field experiment was performed to examine the applicability of sensors with both functions to the proposed methods. Each sensor was installed on a bus in service in this field experiment. The vehicle's natural frequency estimated from the measured data ranges from 1 to 2 Hz, but the natural frequency estimated by the proposed method is 0.71 Hz. However, the estimated road unevenness does not change significantly with changes in the vehicle's estimated parameters. The results found that the accuracy of road unevenness estimation seems to be acceptable with the conventional method and the new method. Future work will include improving the algorithm and accuracy verification of the schemes.

Discussion on a Vehicle-Bridge Interaction System Identification in a Field Test.

For infrastructures to be sustainable, it is essential to improve maintenance and management efficiency. Vibration-based monitoring methods are being investigated to improve the efficiency of infrastructure maintenance and management. In this paper, signals from acceleration sensors attached to vehicles traveling on bridges are processed. Methods have been proposed to individually estimate the modal parameters of bridges and road unevenness from vehicle vibrations. This study proposes a method to simultaneously estimate the mechanical parameters of the vehicle, bridge, and road unevenness with only a few constraints. Numerical validation examined the effect of introducing the Kalman filter on the accuracy of estimating the mechanical parameters of vehicles and bridges. In field tests, vehicle vibration, bridge vibration, and road unevenness were measured and verified, respectively. The road surface irregularities estimated by the proposed method were compared with the measured values, which were somewhat smaller than the measured values. Future studies are needed to improve the efficiency of vehicle vibration preprocessing and optimization methods and to establish a methodology for evaluating accuracy.

A two-phase model of collective memory decay with a dynamical switching point.

Public memories of significant events shared within societies and groups have been conceptualized and studied as collective memory since the 1920s. Thanks to the recent advancement in digitization of public-domain knowledge and online user behaviors, collective memory has now become a subject of rigorous quantitative investigation using large-scale empirical data. Earlier studies, however, typically considered only one dynamical process applied to data obtained in just one specific event category. Here we propose a two-phase mathematical model of collective memory decay that combines exponential and power-law phases, which represent fast (linear) and slow (nonlinear) decay dynamics, respectively. We applied the proposed model to the Wikipedia page view data for articles on significant events in five categories: earthquakes, deaths of notable persons, aviation accidents, mass murder incidents, and terrorist attacks. Results showed that the proposed two-phase model compared favorably with other existing models of collective memory decay in most of the event categories. The estimated model parameters were found to be similar across all the event categories. The proposed model also allowed for detection of a dynamical switching point when the dominant decay dynamics exhibit a phase shift from exponential to power-law. Such decay phase shifts typically occurred about 10 to 11 days after the peak in all of the five event categories.

Application of C-LSTM Networks to Automatic Labeling of Vehicle Dynamic Response Data for Bridges.

Maintaining bridges that support road infrastructure is critical to the economy and human life. Structural health monitoring of bridges using vibration includes direct monitoring and drive-by monitoring. Drive-by monitoring uses a vehicle equipped with accelerometers to drive over bridges and estimates the bridge's health from the vehicle vibration obtained. In this study, we attempt to identify the driving segments on bridges in the vehicle vibration data for the practical application of drive-by monitoring. We developed an in-vehicle sensor system that can measure three-dimensional behavior, and we propose a new problem of identifying the driving segment of vehicle vibration on a bridge from data measured in a field experiment. The "on a bridge" label was assigned based on the peaks in the vehicle vibration when running at joints. A supervised binary classification model using C-LSTM (Convolution-Long-Term Short Memory) networks was constructed and applied to data measured, and the model was successfully constructed with high accuracy. The challenge is to build a model that can be applied to bridges where joints do not exist. Therefore, future work is needed to propose a running label on bridges based on bridge vibration and extend the model to a multi-class model.

Sensing Framework for the Internet of Actors in the Value Co-Creation Process with a Beacon-Attachable Indoor Positioning System.

To evaluate and improve the value of a service, it is important to measure not only the outcomes, but also the process of the service. Value co-creation (VCC) is not limited to outcomes, especially in interpersonal services based on interactions between actors. In this paper, a sensing framework for a VCC process in retail stores is proposed by improving an environment recognition based indoor positioning system with high positioning performance in a metal shelf environment. The conventional indoor positioning systems use radio waves; therefore, errors are caused by reflection, absorption, and interference from metal shelves. An improvement in positioning performance was achieved in the proposed method by using an IR (infrared) slit and IR light, which avoids such errors. The system was designed to recognize many and unspecified people based on the environment recognition method that the receivers had installed, in the service environment. In addition, sensor networking was also conducted by adding a function to transmit payload and identification simultaneously to the beacons that were attached to positioning objects. The effectiveness of the proposed method was verified by installing it not only in an experimental environment with ideal conditions, but posteriorly, the system was tested in real conditions, in a retail store. In our experimental setup, in a comparison with equal element numbers, positioning identification was possible within an error of 96.2 mm in a static environment in contrast to the radio wave based method where an average positioning error of approximately 648 mm was measured using the radio wave based method (Bluetooth low-energy fingerprinting technique). Moreover, when multiple beacons were used simultaneously in our system within the measurement range of one receiver, the appropriate setting of the pulse interval and jitter rate was implemented by simulation. Additionally, it was confirmed that, in a real scenario, it is possible to measure the changes in movement and positional relationships between people. This result shows the feasibility of measuring and evaluating the VCC process in retail stores, although it was difficult to measure the interaction between actors.

Occlusal status of implant superstructures at mandibular first molar immediately after setting.

BACKGROUND: Occlusal contact on the implant superstructures is important for successful treatment. The purpose of this study was to investigate the occlusal contact of single implant superstructures at the mandibular first molar immediately after seating from weak to strong clenching. METHODS: Subjects were nine patients who had just been fitted with an implant prosthesis in the mandibular first molar region, with no missing teeth other than in the implant region. First, while masseter muscle activity was monitored, maximum clenching strength (100 % maximum voluntary contraction (MVC)) was determined with an electromyogram. Next, occlusal load and occlusal contact area were measured three times at clenching intensities of 40, 60, 80, and 100 % MVC by the use of pressure-sensitive film for occlusal force diagnostic and Occluzer for occlusal force measurement. Finally, the occlusal contact area was measured once each at 20, 40, and 60 % MVC using a silicone testing material and BiteEye for occlusal contact measurement. A two-way analysis of variance (ANOVA) was used to determine occlusal loading and occlusal area as dependent variables, and clenching strength and presence or absence of implant as between-subject factors. A multiple comparison test was performed using the Bonferroni method. RESULTS: The occlusal contact area and occlusal load of the implant prosthesis increased with clenching strength, and the increases in occlusal contact area and occlusal load of the implant prosthesis were less than those of the contralateral tooth at high clenching strength. However, significant difference was not observed when compared with both sides of the molar region regardless of clenching strength. CONCLUSIONS: The occlusal contact area of the implant had a tendency to be adjusted smaller than the natural tooth by a dental technician and a dentist. On the other hand, despite the small tissue displaceability of the implant, occlusal load on the implant prosthesis was smaller than on the natural tooth at high clenching strength.

Influence of occlusal loading force on occlusal contacts in natural dentition.

PURPOSE: Proper occlusal contact is important for the long-term success of prosthodontic therapy. We clarified the effects of occlusal loading force on occlusal contact in natural dentition by comparing measured values for occlusal loading and occlusal contact area. METHODS: Masseter muscle activity was measured in 10 subjects (2 male, 8 female; mean age, 27 years) with natural dentition using electromyography, with clenching at full strength with nothing interposed between the upper and lower teeth defined as 100% maximum voluntary contraction (MVC). Pressure-sensitive film (Occluzer) was used to examine occlusal contact points at 20, 40, 60, 80, 100 and 120% MVC. A material for checking accuracy of fit (BiteEye) was used to examine occlusal contact points at 20, 40, 60 and 80% MVC. ANOVA and the Bonferroni method were used to assess the results, with the level of significance set at 5%. Coefficients of variation (CV) were also calculated by dividing the standard deviation by the mean. RESULTS: Occlusal loading and occlusal contact area increased with clenching strength; however, CV showed differences between the methods at low and high MVC. CONCLUSIONS: With Occluzer, testing should be carried out at clenching strength ≥ 60% MVC. With BiteEye, testing should be carried out from light clenching strength at 20% MVC to moderate clenching strengths at 40-60% MVC. Occluzer and BiteEye (10 µm) gave similar occlusal contact areas at 60-80% MVC. These results suggest that combined use of Occluzer and BiteEye gives an accurate picture of occlusion from weak to strong clenching strength.

Low level laser therapy (LLLT) for patients with sacroiliac joint pain.

BACKGROUND AND AIMS: Sacroiliac joint pain not associated with a major etiological factor is a common problem seen in the orthopedic clinical setting, but diagnosis is difficult because of the anatomical area and thus it is sometimes difficult to effect a complete cure. Low level laser therapy (LLLT) has been well-reported as having efficacy in difficult pain types, so the following preliminary study was designed to assess the efficacy of LLLT for sacroiliac pain. MATERIALS AND METHODS: Nine patients participated, 4 males and 5 females, average age of 50.4 yrs, who attended the outpatient department with sacroiliac pain. The usual major disorders were ruled out. Pain was assessed subjectively pre-and post-LLLT on a visual analog scale, and trunk range of motion was examined with the flexion test to obtain the pre- and post-treatment finger to floor distance (FFD). The LLLT system used was an 830 nm CW diode laser, 1000 mW, 30 sec/point (20 J/cm(2)) applied on the bilateral tender points twice/week for 5 weeks. Baseline and final assessment values (after the final treatment session) were compared with the Wilcoxon signed rank test (nonparametric score). RESULTS: All patients completed the study. Eight of the 9 patients showed significant pain improvement and 6 demonstrated significantly increased trunk mobility (P <0.05 for both). CONCLUSIONS: LLLT was effective for sacroiliac pain, and this may be due to improvement of the blood circulation of the strong ligaments which support the sacroiliac joint, activation of the descending inhibitory pathway, and the additional removal of irregularities of the sacroiliac joint articular surfaces. Further larger-scale studies are warranted.

Structural recognition by recombinant human heparanase that plays critical roles in tumor metastasis. Hierarchical sulfate groups with different effects and the essential target disulfated trisaccharide sequence.

Human heparanase is an endo-beta-d-glucuronidase that degrades heparan sulfate/heparin and has been implicated in a variety of biological processes, such as inflammation, tumor angiogenesis, and metastasis. Although the cloned enzyme has been demonstrated to have a critical role in tumor metastasis, the substrate specificity has been poorly understood. In the present study, the specificity of the purified recombinant human heparanase was investigated for the first time using a series of structurally defined oligosaccharides isolated from heparin/heparan sulfate. The best substrates were deltaHexUA(+/-2S)-GlcN(NS,6S)-GlcUA-GlcN(NS,6S)-GlcUA-GlcN(NS,6S) and deltaHexUA(2S)-GlcN(NS,6S)-GlcUA-GlcN(NS,6S) (where deltaHexUA, GlcN, GlcUA, NS, 2S, and 6S represent unsaturated hexuronic acid, d-glucosamine, d-glucuronic acid, 2-N-sulfate, 2-O-sulfate, and 6-O-disulfate, respectively). Based on the percentage conversion of the substrates to products under identical assay conditions, several aspects of the recognition structures were revealed. 1) The minimum recognition backbone is the trisaccharide GlcN-GlcUA-GlcN. 2) The target GlcUA residues are in the sulfated region. 3) The -GlcN(6S)-GlcUA-GlcN(NS)- sequence is essential but not sufficient as the cleavage site. 4) The IdoUA(2S) residue, located two saccharides away from the target GlcUA residue, claimed previously to be essential, is not indispensable. 5) The 3-O-sulfate group on the GlcN is dispensable and even has an inhibitory effect when located in a highly sulfated region. 6) Based on these and previous results, HexUA(2S)-GlcN(NS,6S)-IdoUA-GlcNAc(6S)-GlcUA-GlcN(NS,+/-6S)-IdoUA(2S)-GlcN(NS,6S) (where HexUA represents hexuronic acid) has been proposed as a probable physiological target octasaccharide sequence. These findings will aid establishing a quantitative assay method using the above tetrasaccharide and designing heparan sulfate-based specific inhibitors of the heparanase for new therapeutic strategies.

Determination of the glycosaminoglycan-protein linkage region oligosaccharide structures of proteoglycans from Drosophila melanogaster and Caenorhabditis elegans.

Caenorhabditis elegans and Drosophila melanogaster are relevant models for studying the roles of glycosaminoglycans (GAG) during the development of multicellular organisms. The genome projects of these organisms have revealed the existence of multiple genes related to GAG-synthesizing enzymes. Although the putative genes encoding the enzymes that synthesize the GAG-protein linkage region have also been identified, there is no direct evidence that the GAG chains bind covalently to core proteins. This study aimed to clarify whether GAG chains in these organisms are linked to core proteins through the conventional linkage region tetrasaccharide sequence found in vertebrates and whether modifications by phosphorylation and sulfation reported for vertebrates are present also in invertebrates. The linkage region oligosaccharides were isolated from C. elegans chondroitin in addition to D. melanogaster heparan and chondroitin sulfate after digestion with the respective bacterial eliminases and were then derivatized with a fluorophore 2-aminobenzamide. Their structures were characterized by gel filtration and anion-exchange high performance liquid chromatography in conjunction with enzymatic digestion and matrix-assisted laser desorption ionization time-of-flight spectrometry, which demonstrated a uniform linkage tetrasaccharide structure of -GlcUA-Gal-Gal-Xyl- or -GlcUA-Gal-Gal-Xyl(2-O-phosphate)- for C. elegans chondroitin and D. melanogaster CS, respectively. In contrast, the unmodified and phosphorylated counterparts were demonstrated in heparan sulfate of adult flies at a molar ratio of 73:27, and in that of the immortalized D. melanogaster S2 cell line at a molar ratio of 7:93, which suggests that the linkage region in the fruit fly first becomes phosphorylated uniformly on the Xyl residue and then dephosphorylated. It has been established here that GAG chains in both C. elegans and D. melanogaster are synthesized on the core protein through the ubiquitous linkage region tetrasaccharide sequence, suggesting that indispensable functions of the linkage region in the GAG synthesis have been well conserved during evolution.