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.

Improvement trend for individual health guidance intervention according to Japan clinical guidelines by public health nurses for type 2 diabetes mellitus who visited for medical checkups regularly: a case-control preliminary report.

We conducted a retrospective case-control study to assess the efficacy of personalized health guidance interventions on individuals with type 2 diabetes mellitus and obesity. A selection was made of individuals in regular visits to the Takagi Hospital for medical checkups between January 2017, and October 2021. Totally, 108 subjects (cases) with health guidance were divided into 2 groups: one group without pharmacotherapy for diabetes mellitus in medical institutions (n = 92) and another group with pharmacotherapy (n = 116). Cases were provided with personalized health guidance interventions by public health nurses for 30 min, in accordance with the Japanese clinical guidelines for the prevention of lifestyle-related diseases. Sex- and age-matched controls were chosen from individuals with diabetes mellitus without health guidance. The intervention without pharmacotherapy resulted in improvements in health indicators, including body weight, waist circumference, diastolic blood pressure, triglyceride levels, and γ-glutamyl trans-peptidase. These positive effects were not observed in the control group without health guidance. The therapeutic effects of health guidance were observed in cases where pharmacotherapy was administered. In conclusion, the implementation of individual health guidance interventions may prove to be effective for individuals with type 2 diabetes mellitus and obesity who regularly attend medical checkups.

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.

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.

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.

Optimal Water Level Management for Mitigating GHG Emissions through Water-Conserving Irrigation in An Giang Province, Vietnam.

Rational water and fertilizer management approaches and technologies could improve water use efficiency and fertilizer use efficiency in paddy rice cultivation. A promising water-conserving technology for paddy rice farming is the alternate wetting and drying irrigation system, established by the International Rice Research Institute. However, the strategy has still not been widely adopted, because water level measurement is challenging work and sometimes leads to a decrease in the rice yield. For the easy implementation of alternate wetting and drying among farmers, we analyzed a dataset obtained from a farmer's water management study carried out over a three-year period with three cropping seasons at six locations (n = 82) in An Giang Province, Southern Vietnam. We observed a significant relationship between specific water level management and the rice yield and greenhouse gas emissions during different growth periods. The average water level during the crop period was an important factor in increasing the rice yield and reducing greenhouse gas emissions. The average water level at 2 days after nitrogen fertilization also showed a potential to increase the rice yield. The greenhouse gas emissions were reduced when the number of days of non-flooded soil use was increased by 1 day during the crop period. The results offer insights demonstrating that farmers' implementation of multiple drainage during whole crop period and nitrogen fertilization period has the potential to contribute to both the rice yield increase and reduction in greenhouse gas emissions from rice cultivation.

Model Microbial Consortia as Tools for Understanding Complex Microbial Communities.

A major biological challenge in the postgenomic era has been untangling the composition and functions of microbes that inhabit complex communities or microbiomes. Multi-omics and modern bioinformatics have provided the tools to assay molecules across different cellular and community scales; however, mechanistic knowledge over microbial interactions often remains elusive. This is due to the immense diversity and the essentially undiminished volume of not-yet-cultured microbes. Simplified model communities hold some promise in enabling researchers to manage complexity so that they can mechanistically understand the emergent properties of microbial community interactions. In this review, we surveyed several approaches that have effectively used tractable model consortia to elucidate the complex behavior of microbial communities. We go further to provide some perspectives on the limitations and new opportunities with these approaches and highlight where these efforts are likely to lead as advances are made in molecular ecology and systems biology.

Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture.

Unmanned aerial vehicles (UAVs or drones) are a very promising branch of technology, and they have been utilized in agriculture-in cooperation with image processing technologies-for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of plants in the limited time available, but this reduces the spatial resolution of the captured images. In this study, we applied a super-resolution method to the low-resolution images of tomato diseases to recover detailed appearances, such as lesions on plant organs. We also conducted disease classification using high-resolution, low-resolution, and super-resolution images to evaluate the effectiveness of super-resolution methods in disease classification. Our results indicated that the super-resolution method outperformed conventional image scaling methods in spatial resolution enhancement of tomato disease images. The results of disease classification showed that the accuracy attained was also better by a large margin with super-resolution images than with low-resolution images. These results indicated that our approach not only recovered the information lost in low-resolution images, but also exerted a beneficial influence on further image analysis. The proposed approach will accelerate image-based phenotyping and vigor diagnosis in the field, because it not only saves time to capture images of a crop in a cultivation field but also secures the accuracy of these images for further analysis.

Machine Learning-Based Calibration of Low-Cost Air Temperature Sensors Using Environmental Data.

The measurement of air temperature is strongly influenced by environmental factors such as solar radiation, humidity, wind speed and rainfall. This is problematic in low-cost air temperature sensors, which lack a radiation shield or a forced aspiration system, exposing them to direct sunlight and condensation. In this study, we developed a machine learning-based calibration method for air temperature measurement by a low-cost sensor. An artificial neural network (ANN) was used to balance the effect of multiple environmental factors on the measurements. Data were collected over 305 days, at three different locations in Japan, and used to evaluate the performance of the approach. Data collected at the same location and at different locations were used for training and testing, and the former was also used for k-fold cross-validation, demonstrating an average improvement in mean absolute error (MAE) from 1.62 to 0.67 by applying our method. Some calibration failures were noted, due to abrupt changes in environmental conditions such as solar radiation or rainfall. The MAE was shown to decrease even when the data collected in different nearby locations were used for training and testing. However, the results also showed that negative effects arose when data obtained from widely-separated locations were used, because of the significant environmental differences between them.

Node Detection and Internode Length Estimation of Tomato Seedlings Based on Image Analysis and Machine Learning.

Seedling vigor in tomatoes determines the quality and growth of fruits and total plant productivity. It is well known that the salient effects of environmental stresses appear on the internode length; the length between adjoining main stem node (henceforth called node). In this study, we develop a method for internode length estimation using image processing technology. The proposed method consists of three steps: node detection, node order estimation, and internode length estimation. This method has two main advantages: (i) as it uses machine learning approaches for node detection, it does not require adjustment of threshold values even though seedlings are imaged under varying timings and lighting conditions with complex backgrounds; and (ii) as it uses affinity propagation for node order estimation, it can be applied to seedlings with different numbers of nodes without prior provision of the node number as a parameter. Our node detection results show that the proposed method can detect 72% of the 358 nodes in time-series imaging of three seedlings (recall = 0.72, precision = 0.78). In particular, the application of a general object recognition approach, Bag of Visual Words (BoVWs), enabled the elimination of many false positives on leaves occurring in the image segmentation based on pixel color, significantly improving the precision. The internode length estimation results had a relative error of below 15.4%. These results demonstrate that our method has the ability to evaluate the vigor of tomato seedlings quickly and accurately.

A hidden pitfall in the preparation of agar media undermines microorganism cultivability.

Microbiologists have been using agar growth medium for over 120 years. It revolutionized microbiology in the 1890s when microbiologists were seeking effective methods to isolate microorganisms, which led to the successful cultivation of microorganisms as single clones. But there has been a disparity between total cell counts and cultivable cell counts on plates, often referred to as the "great plate count anomaly," that has long been a phenomenon that still remains unsolved. Here, we report that a common practice microbiologists have employed to prepare agar medium has a hidden pitfall: when phosphate was autoclaved together with agar to prepare solid growth media (PT medium), total colony counts were remarkably lower than those grown on agar plates in which phosphate and agar were separately autoclaved and mixed right before solidification (PS medium). We used a pure culture of Gemmatimonas aurantiaca T-27(T) and three representative sources of environmental samples, soil, sediment, and water, as inocula and compared colony counts between PT and PS agar plates. There were higher numbers of CFU on PS medium than on PT medium using G. aurantiaca or any of the environmental samples. Chemical analysis of PT agar plates suggested that hydrogen peroxide was contributing to growth inhibition. Comparison of 454 pyrosequences of the environmental samples to the isolates revealed that taxa grown on PS medium were more reflective of the original community structure than those grown on PT medium. Moreover, more hitherto-uncultivated microbes grew on PS than on PT medium.

On plant detection of intact tomato fruits using image analysis and machine learning methods.

Fully automated yield estimation of intact fruits prior to harvesting provides various benefits to farmers. Until now, several studies have been conducted to estimate fruit yield using image-processing technologies. However, most of these techniques require thresholds for features such as color, shape and size. In addition, their performance strongly depends on the thresholds used, although optimal thresholds tend to vary with images. Furthermore, most of these techniques have attempted to detect only mature and immature fruits, although the number of young fruits is more important for the prediction of long-term fluctuations in yield. In this study, we aimed to develop a method to accurately detect individual intact tomato fruits including mature, immature and young fruits on a plant using a conventional RGB digital camera in conjunction with machine learning approaches. The developed method did not require an adjustment of threshold values for fruit detection from each image because image segmentation was conducted based on classification models generated in accordance with the color, shape, texture and size of the images. The results of fruit detection in the test images showed that the developed method achieved a recall of 0.80, while the precision was 0.88. The recall values of mature, immature and young fruits were 1.00, 0.80 and 0.78, respectively.

Complete genome sequence of Opitutales bacterium strain ASA1, isolated from soil.

We present the complete genome of Opitutales bacterium ASA1, isolated from soil. The genome is 5,821,695 bp with 4,638 protein-coding sequences. The genome data suggest that this strain belongs to the class Opitutae of the phylum Verrucomicrobiota, and its genome has six unique biosynthetic gene clusters associated with secondary metabolites.

Microscopic and metatranscriptomic analyses revealed unique cross-domain parasitism between phylum Candidatus Patescibacteria/candidate phyla radiation and methanogenic archaea in anaerobic ecosystems.

To verify whether members of the phylum Candidatus Patescibacteria parasitize archaea, we applied cultivation, microscopy, metatranscriptomic, and protein structure prediction analyses on the Patescibacteria-enriched cultures derived from a methanogenic bioreactor. Amendment of cultures with exogenous methanogenic archaea, acetate, amino acids, and nucleoside monophosphates increased the relative abundance of Ca. Patescibacteria. The predominant Ca. Patescibacteria were families Ca. Yanofskyibacteriaceae and Ca. Minisyncoccaceae, and the former showed positive linear relationships (r2 ≥ 0.70) Methanothrix in their relative abundances, suggesting related growth patterns. Methanothrix and Methanospirillum cells with attached Ca. Yanofskyibacteriaceae and Ca. Minisyncoccaceae, respectively, had significantly lower cellular activity than those of the methanogens without Ca. Patescibacteria, as extrapolated from fluorescence in situ hybridization-based fluorescence. We also observed that parasitized methanogens often had cell surface deformations. Some Methanothrix-like filamentous cells were dented where the submicron cells were attached. Ca. Yanofskyibacteriaceae and Ca. Minisyncoccaceae highly expressed extracellular enzymes, and based on structural predictions, some contained peptidoglycan-binding domains with potential involvement in host cell attachment. Collectively, we propose that the interactions of Ca. Yanofskyibacteriaceae and Ca. Minisyncoccaceae with methanogenic archaea are parasitisms.IMPORTANCECulture-independent DNA sequencing approaches have explored diverse yet-to-be-cultured microorganisms and have significantly expanded the tree of life in recent years. One major lineage of the domain Bacteria, Ca. Patescibacteria (also known as candidate phyla radiation), is widely distributed in natural and engineered ecosystems and has been thought to be dependent on host bacteria due to the lack of several biosynthetic pathways and small cell/genome size. Although bacteria-parasitizing or bacteria-preying Ca. Patescibacteria have been described, our recent studies revealed that some lineages can specifically interact with archaea. In this study, we provide strong evidence that the relationship is parasitic, shedding light on overlooked roles of Ca. Patescibacteria in anaerobic habitats.

Orally and topically administered Sparassis crispa (Hanabiratake) improved healing of skin wounds in mice with streptozotocin-induced diabetes.

Sparassis crispa (SC) contains significant concentrations of ß-glucan, which can accelerate wound healing, but the dose dependence for oral administration and the effects of topical administration are unknown. In streptozotocin-induced diabetic mice, dietary SC promoted dose-dependent effective wound healing. Similar wound healing activity was observed when purified SC ß-glucan was topically applied to wounds of diabetic mice.

Effect of vitamin K2 on the recurrence of hepatocellular carcinoma.

UNLABELLED: Hepatocellular carcinoma (HCC) is characterized by frequent recurrence, even after curative treatment. Vitamin K2, which has been reported to reduce HCC development, may be effective in preventing HCC recurrence. Patients who underwent curative ablation or resection of HCC were randomly assigned to receive placebo, 45 mg/day, or 90 mg/day vitamin K2 in double-blind fashion. HCC recurrence was surveyed every 12 weeks with dynamic computed tomography/magnetic resonance imaging, with HCC-specific tumor markers monitored every 4 weeks. The primary aim was to confirm the superiority of active drug to placebo concerning disease-free survival (DFS), and the secondary aim was to evaluate dose-response relationship. Disease occurrence and death from any cause were treated as events. Hazard ratios (HRs) for disease occurrence and death were calculated using a Cox proportional hazards model. Enrollment was commenced in March 2004. DFS was assessed in 548 patients, including 181 in the placebo group, 182 in the 45-mg/day group, and 185 in the 90-mg/day group. Disease occurrence or death was diagnosed in 58, 52, and 76 patients in the respective groups. The second interim analysis indicated that vitamin K2 did not prevent disease occurrence or death, with an HR of 1.150 (95% confidence interval: 0.843-1.570, one-sided; P=0.811) between the placebo and combined active-drug groups, and the study was discontinued in March 2007. CONCLUSION: Efficacy of vitamin K2 in suppressing HCC recurrence was not confirmed in this double-blind, randomized, placebo-controlled study.

Scaffold size-dependent effect on the enhanced uptake of antibiotics and other compounds by Escherichia coli and Pseudomonas aeruginosa.

The outer membrane of Gram-negative bacteria functions as an impermeable barrier to foreign compounds. Thus, modulating membrane transport can contribute to improving susceptibility to antibiotics and efficiency of bioproduction reactions. In this study, the cellular uptake of hydrophobic and large-scaffold antibiotics and other compounds in Gram-negative bacteria was investigated by modulating the homolog expression of bamB encoding an outer membrane lipoprotein and tolC encoding an outer membrane efflux protein via gene deletion and gene silencing. The potential of deletion mutants for biotechnological applications, such as drug screening and bioproduction, was also demonstrated. Instead of being subjected to gene deletion, wild-type bacterial cells were treated with cell-penetrating peptide conjugates of a peptide nucleic acid (CPP-PNA) against bamB and tolC homologs as antisense agents. Results revealed that the single deletion of bamB and tolC in Escherichia coli increased the uptake of large- and small-scaffold hydrophobic compounds, respectively. A bamB-and-tolC double deletion mutant had a higher uptake efficiency for certain antibiotics and other compounds with high hydrophobicity than each single deletion mutant. The CPP-PNA treated E. coli and Pseudomonas aeruginosa cells showed high sensitivity to various antibiotics. Therefore, these gene deletion and silencing approaches can be utilized in therapeutic and biotechnological fields.

Symbiosis between Candidatus Patescibacteria and Archaea Discovered in Wastewater-Treating Bioreactors.

Each prokaryotic domain, Bacteria and Archaea, contains a large and diverse group of organisms characterized by their ultrasmall cell size and symbiotic lifestyles (potentially commensal, mutualistic, and parasitic relationships), namely, Candidatus Patescibacteria (also known as the Candidate Phyla Radiation/CPR superphylum) and DPANN archaea, respectively. Cultivation-based approaches have revealed that Ca. Patescibacteria and DPANN symbiotically interact with bacterial and archaeal partners and hosts, respectively, but that cross-domain symbiosis and parasitism have never been observed. By amending wastewater treatment sludge samples with methanogenic archaea, we observed increased abundances of Ca. Patescibacteria (Ca. Yanofskybacteria/UBA5738) and, using fluorescence in situ hybridization (FISH), discovered that nearly all of the Ca. Yanofskybacteria/UBA5738 cells were attached to Methanothrix (95.7 ± 2.1%) and that none of the cells were attached to other lineages, implying high host dependency and specificity. Methanothrix filaments (multicellular) with Ca. Yanofskybacteria/UBA5738 attached had significantly more cells with no or low detectable ribosomal activity (based on FISH fluorescence) and often showed deformations at the sites of attachment (based on transmission electron microscopy), suggesting that the interaction is parasitic. Metagenome-assisted metabolic reconstruction showed that Ca. Yanofskybacteria/UBA5738 lacks most of the biosynthetic pathways necessary for cell growth and universally conserves three unique gene arrays that contain multiple genes with signal peptides in the metagenome-assembled genomes of the Ca. Yanofskybacteria/UBA5738 lineage. The results shed light on a novel cross-domain symbiosis and inspire potential strategies for culturing CPR and DPANN. IMPORTANCE One highly diverse phylogenetic group of Bacteria, Ca. Patescibacteria, remains poorly understood, but, from the few cultured representatives and metagenomic investigations, they are thought to live symbiotically or parasitically with other bacteria or even with eukarya. We explored the possibility of symbiotic interactions with Archaea by amending wastewater treatment sludge samples that were rich in Ca. Patescibacteria and Archaea with an isolate archaeon that is closely related to a methanogen population abundant in situ (Methanothrix). This strategic cultivation successfully established enrichment cultures that were mainly comprised of Ca. Patescibacteria (family level lineage Ca. Yanofskybacteria/UBA5738) and Methanothrix, in which we found highly specific physical interactions between the two organisms. Microscopic observations based on transmission electron microscopy, target-specific fluorescence in situ hybridization, and metagenomic analyses showed evidence that the interaction is likely parasitic. The results show a novel cross-domain parasitism between Bacteria and Archaea and suggest that the amendment of host Archaea may be an effective approach in culturing novel Ca. Patescibacteria.

Novel Cross-domain Symbiosis between Candidatus Patescibacteria and Hydrogenotrophic Methanogenic Archaea Methanospirillum Discovered in a Methanogenic Ecosystem.

To identify novel cross-domain symbiosis between Candidatus Patescibacteria and Archaea, we performed fluorescence in situ hybridization (FISH) on enrichment cultures derived from methanogenic bioreactor sludge with the newly designed 32-520-1066 probe targeting the family-level uncultured clade 32-520/UBA5633 lineage in the class Ca. Paceibacteria. All FISH-detectable 32-520/UBA5633 cells were attached to Methanospirillum, indicating high host specificity. Transmission electron microscopy observations revealed 32-520/UBA5633-like cells that were specifically adherent to the plug structure of Methanospirillum-like rod-shaped cells. The metagenome-assembled genomes of 32-520/UBA5633 encoded unique gene clusters comprising pilin signal peptides and type IV pilins. These results provide novel insights into unseen symbiosis between Ca. Patescibacteria and Archaea.