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On Ba Lang Beach in Nha Trang, Vietnam, the beach has been narrowed owing to land reclamation along the shoreline to construct a coastal road. The process of this artificial alteration was studied using satellite images, then the BG model (a model for predicting three-dimensional beach changes based on Bagnold’s concept) was used to investigate the feasibility of beach nourishment to recover the sandy beach. It was concluded that if we can procure the beach material of 6×104 m3, a sandy beach of 24 m width can be recovered at the central part of the beach nourishment area.

In developing countries including Vietnam with rapid economic growth, the beach erosion has become severe. Various artificial facilities for economic development have been rapidly constructed on coasts, and once erosion occurs, stop-gap measures against erosion have been widely taken, resulting in further downcoast erosion. In this study, beach erosion was investigated by comparing aerial photographs and actual field observations on October 23, 2016 with those on November 9, 2017, taking beach changes in Phan Thiet as an example. The erosion mechanism in this area was studied on the basis of these field data.

Background Conditions of the elderly like sarcopenia, locomotive syndrome, and frailty have been attracting attention recently. However, the relationship of these 3 conditions and the difference in the magnitude of influence each has on deterioration in health status remain unclear. The purpose of this study was to investigate the prevalence and relationship of sarcopenia, locomotive syndrome, and frailty, and to clarify their influence on the dropout from cohort study due to deterioration in health status. Methods The 1st survey of the Shiraniwa Elderly Cohort (Shiraniwa) study was conducted in 2016. We examined 409 participants (aged ≥ 65 years; 164 males, 245 females) and assessed sarcopenia, locomotive syndrome, and frailty. Those who could not attend the 2nd survey (2017) due to deterioration in health status were defined as the Dropout group. We investigated the predictors of Dropout using multiple logistic regression analysis. Results The prevalence of sarcopenia, locomotive syndrome stage 2, and frailty were 4.4%, 40.1%, and 14.2%, respectively; 89.7% of participants with frailty were also diagnosed with locomotive syndrome stage 2. From the results of the 2nd survey, 46 people were classified into the Dropout group. Independent predictors of the Dropout were locomotive syndrome stage 2 (adjusted odds ratio [OR]: 2.42, 95% confidence interval [CI]: 1.11–5.31) and frailty (adjusted OR: 3.37, 95%CI: 1.56–7.30). Conclusions Locomotive syndrome stage 2 was the most common condition in the elderly, and most people with frailty also had locomotive syndrome stage 2. Locomotive syndrome stage 2 and frailty independently influenced the dropout from cohort study due to deterioration in health status. These results suggest that screening for locomotive syndrome is useful for early detection of the elderly with a risk of deterioration in health status, and screening for frailty may contribute to detecting the elderly with higher risk of deterioration in health status.

In this paper, we try to predict the card prices of the trading card game using their information. The trading card game market is growing by the increasing popularity of the board game or the digital card game in the e-sports in recent years. The trading card game is a kind of card game which two or more people plays a card with some text or symbols those characteristics expresses a ruling or interaction to the other card. This interaction of cards may work effectively in the game, prices of those card pairs will be increased with the popularity of its combination. We have a hypothesis that card text is useful for prediction of card prices from the importance of card combinations. Therefore, in this research, we focus on not only the basic card information but also card text. Moreover, we use several machine learning method for prediction of card prices, and we analyze which machine learning method is an effect.

We propose a method for estimating new tags to enrich folksonomy on video sharing sites using various video information. Folksonomy is a process by which users tag videos to facilitate searches. One such website is Nico Nico Douga, although users of the site cannot post more than 12 tags to a video. Consequently, although some important tags will be posted, others might be missing. We present a method for acquiring some of these missing tags by choosing new tags. The method uses comments, tags, titles, descriptions, and thumbnails to estimate new tags. Using these data, we develop various algorithms, including neural networks, word embeddings, and K-means. Our method indicated high performance in experimental results.

Around the Ogasawara Islands, only a few seismic stations in the area can be used to determine the hypocenters of regional earthquakes; thus, hypocenter location precision tends to be low. To more precisely determine hypocenter locations, we deployed a temporary seismic observation network of pop-up ocean bottom seismometers around the Ogasawara Islands from July to October 2015. We identified a double seismic zone in the 70–200 km depth range associated with the subducting Pacific slab. The slab-normal distance between the two planes of the double seismic zone is about 30–35 km, similar to such distances observed along the Japan and Mariana trenches. Furthermore, we found unusual seismicity in the mantle wedge at 20–50 km depth beneath the Ogasawara trough that might be related to structure formed at the onset of the oceanic slab subduction. The hypocenters determined from the ocean bottom seismometer observation were horizontally separated by a few tens of kilometers from hypocenters published by the Seismological Bulletin of Japan. USGS locations (Preliminary Determination of Epicenters) seem to be offset westward about 30 km compared with the locations determined in this study.

This paper shows the effect of the controlling file assignment on the file transfer time for a Web-based content categorization system. Our proposed algorithm estimates categories of contents based on the terms and the content categories already added. However, our algorithm uses a large table that consists of the scores that represent the relationship between a term and a category. To address the large table size and longer calculation time, we proposed a distributed Web system that uses multiple calculation machines. This Web system runs preprocessors on a Web browser and calculation machines. In this Web system, the file transfer time becomes a problem when a user sends larger files. In this paper, we propose a way to resolve the issue of longer file transfer time by controlling the file assignment. We assign the large files to the Web browser process, and we assign the smaller files to the calculation machines over the network.

On 17 July 1998, a tsunami caused serious damage on the northern coast of Papua New Guinea about 20 min after the mainshock of an Mw 7.0 earthquake. The tsunami has been attributed to a submarine landslide that occurred about 13 min after the mainshock because its arrival at the coast was too late and its height too great to be the direct result of the fault slip of the earthquake. Bathymetric data recorded after the tsunami revealed an amphitheater-like structure that was consistent with a recent submarine landslide. Most current tsunami warning systems are based on analysis of the early arrivals of seismic waves generated by an earthquake. In this study we investigated whether evidence of the landslide could be identified in the coda waves recorded after the mainshock. Based on previous studies of the tsunami source, we constructed synthetic seismograms to represent the submarine landslide and compared them to the observed coda waves of the preceding earthquake, with particular attention to the period around 13 min after the mainshock. We found phases possibly corresponding to the landslide event. However, they were easily covered with coda waves from the mainshock. We concluded that the 1998 landslide was too small to be evident in the coda waves following the magnitude 7 earthquake.

We developed a label-designing and restoration method for end-to-end automatic speech recognition based on connectionist temporal classification (CTC). With an end-to-end speech-recognition system including thousands of output labels such as words or characters, it is difficult to train a robust model because of data sparsity. With our proposed method, characters with less training data are estimated using the context of a language model rather than the acoustic features. Our method involves two steps. First, we train acoustic models using 70 class labels instead of thousands of low-frequency labels. Second, the class labels are restored to the original labels by using a weighted finite state transducer and n-gram language model. We applied the proposed method to a Japanese end-to-end automatic speech-recognition system including labels of over 3,000 characters. Experimental results indicate that the word error rate relatively improved with our method by a maximum of 15.5% compared with a conventional CTC-based method and is comparable to state-of-the-art hybrid DNN methods.

Trunk muscles play an important role in supporting the spinal column. A decline in trunk muscle mass, as measured by bioelectrical impedance analysis (TMM–BIA), is associated with low back pain and poor quality of life. The purpose of this study was to determine whether TMM–BIA correlates with quantitative and functional assessments traditionally used for the trunk muscles. We included 380 participants (aged ≥ 65 years, 152 males, 228 females) from the Shiraniwa Elderly Cohort (Shiraniwa) study, for whom the following data were available: TMM–BIA, lumbar magnetic resonance imaging (MRI), and back muscle strength (BMS). We measured the cross-sectional area (CSA) and fat-free CSA of the paravertebral muscles (PVM), including the erector spinae (ES), multifidus (MF), and psoas major (PM), on an axial lumbar MRI at L3/4. The correlation between TMM–BIA and the CSA of PVM, fat-free CSA of PVM, and BMS was investigated. TMM–BIA correlated with the CSA of total PVM and each individual PVM. A stronger correlation between TMM–BIA and fat-free CSA of PVM was observed. The TMM–BIA also strongly correlated with BMS. TMM–BIA is an easy and reliable way to evaluate the trunk muscle mass in a clinical setting.

A model for predicting 3-D beach changes in an extensive area including beach and backshore areas was developed, taking the effects due to both waves and windblown sand into account. In the calculation of beach changes, the BG model (a model for predicting beach changes based on Bagnold's concept) was employed, and a cellular automaton method was used to calculate the backshore changes due to the effect of windblown sand. To validate the model applicability, a reproduction calculation was carried out for the beach formed at the corner of Futtsu new port. The calculation results were in good agreement with the measurement results.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/905aRlNAOjA

Long-term shoreline changes of a cuspate foreland behind Okinoshima Island located in Tateyama Bay were investigated, and a beach survey was carried out using an RTK-GPS on May 2, 2018. Then, numerical simulation of the formation and deformation of a cuspate foreland between 1941 and 2012 was carried out using the BG model (a model for predicting 3-D beach changes based on Bagnold's concept). It was found that sand, which was deposited on the shallow sea associated with the increase in ground level during the Kanto Great Earthquake that occurred in 1923, accumulated to form a cuspate foreland.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/4SDfN9xp9hE

Off the east coast of the Izu Peninsula in Japan, there is a submarine volcanic region where earthquake swarms occur caused by magma intrusions. We investigated the background seismicity rates of the swarm activity by removing the triggering effect of aftershocks. We found that such background rate changes coincide with the changes of exponentially weighted averages of volumetric strain increments at the Higashi-Izu station. We further found that such a relationship consistently depends on the distance between the strainmeter station and the location of the swarm onset. The quantitative relationships revealed here may be used to monitor magma intrusions that drive the stress changes.

The aim of the present study was to investigate the preferred orientation of biological apatite (BAp) as a new index of the quality of subchondral bone (SB) in knee joint osteoarthritis (OA). Ten OA and five normal knee joints were obtained. Thickness, quantity and bone mineral density (BMD) of SB were analyzed at the medial condyle of the femur in dry conditions by peripheral quantitative computed tomography. In addition, the preferred crystallographic orientation of the c-axis of BAp was evaluated as bone quality parameter using a microbeam X-ray diffractometer technique. BMD and thickness of SB were significantly increased in OA specimens compared to normal knee specimens (P

The proximal tubule has a remarkable capacity for repair after acute injury, but the cellular lineage and molecular mechanisms underlying this repair response are incompletely understood. Here, we developed a Kim1-GFPCreERt2 knockin mouse line (Kim1-GCE) in order to perform genetic lineage tracing of dedifferentiated cells while measuring the cellular transcriptome of proximal tubule during repair. Acutely injured genetically labeled clones coexpressed KIM1, VIMENTIN, SOX9, and KI67, indicating a dedifferentiated and proliferative state. Clonal analysis revealed clonal expansion of Kim1+ cells, indicating that acutely injured, dedifferentiated proximal tubule cells, rather than fixed tubular progenitor cells, account for repair. Translational profiling during injury and repair revealed signatures of both successful and unsuccessful maladaptive repair. The transcription factor Foxm1 was induced early in injury, was required for epithelial proliferation in vitro, and was dependent on epidermal growth factor receptor (EGFR) stimulation. In conclusion, dedifferentiated proximal tubule cells effect proximal tubule repair, and we reveal an EGFR/FOXM1-dependent signaling pathway that drives proliferative repair after injury.

The proximal tubule has a remarkable capacity for repair after acute injury but the cellular lineage and molecular mechanisms underlying this repair response have been poorly characterized. Here, we developed a Kim-1-GFPCreERt2knockin mouse line (Kim-1-GCE), performed genetic lineage analysis after injury and measured the cellular transcriptome of proximal tubule during repair. Acutely injured genetically labeled clones co-expressed Kim-1, Vimentin, Sox9 and Ki67, indicating a dedifferentiated and proliferative state. Clonal analysis revealed clonal expansion of Kim-1+ cells, indicating that acutely injured, dedifferentiated proximal tubule cells account for repair rather than a fixed tubular progenitor. Translational profiling during injury and repair revealed signatures of both successful and unsuccessful maladaptive repair. The transcription factor FoxM1 was induced early in injury, was required for epithelial proliferation, and was dependent on epidermal growth factor receptor (EGFR) stimulation. In conclusion, dedifferentiated proximal tubule cells effect proximal tubule repair and we reveal a novel EGFR-FoxM1-dependent signaling pathway that drives proliferative repair after injury.

Background: The periarticular multimodal cocktail injection is currently commonly used to treat postoperative pain after total hip arthroplasty (THA). Despite its analgesic effect, it is frequently reported to cause nausea and vomiting, which are adverse effects of opioids. This study aimed to assess the efficacy of morphine as a component of a multimodal cocktail injection for providing postoperative analgesia and alleviating swelling in patients who underwent THA. Materials and methods: This was a prospective, single-centre, randomised controlled trial involving 100 patients scheduled for unilateral THA. A mixture of steroids, local anaesthetics, NSAIDs, and epinephrine with or without morphine (0.1 mg/kg), was injected into randomly assigned patients. Postoperative assessment was performed with all attending personnel and patients blind to group assignment. Visual analogue scale (VAS) of pain, range of motion (ROM), nausea numerical rating scale (NRS), the total dose of antiemetic drugs used and thigh swelling were compared between groups on postoperative days. Results: Pain VAS scores both at rest and on motion did not differ between the 2 groups at any postoperative time-point. The nausea NRS scores during the postoperative period from 0 minutes to 1 hour and the total dose of antiemetic drugs administered were significantly higher in the morphine group. The thigh girth showed no difference between groups on any of the postoperative days. Conclusions: The results of this study suggested that addition of morphine to the multimodal cocktail injection after THA is not effective for relieving postoperative pain, alleviating swelling, or improving ROM, and results in nausea and vomiting. Randomised controlled trial registration number UMIN000022668.

Valproic acid (VPA) is known to induce hepatic steatosis due to mitochondrial toxicity in rodents and humans. In the present study, we administered VPA to SD rats for 3 or 14 days at 250 and 500 mg/kg and then performed lipidomics analysis to reveal VPA-induced alteration of the hepatic lipid profile and its association with the plasma lipid profile. VPA induced hepatic steatosis at the high dose level without any degenerative changes in the liver on day 4 (after 3 days dosing) and at the low dose level on day 15 (after 14 days dosing). We compared the plasma and hepatic lipid profiles obtained on day 4 between the VPA-treated and control rats using a multivariate analysis to determine differences between the two groups. In total, 36 species of plasma lipids and 24 species of hepatic lipids were identified as altered in the VPA-treated group. Of these lipid species, ether-phosphatidylcholines (ePCs), including PC(16:0e/22:4) and PC(16:0e/22:6), were decreased in both the plasma and liver from the low dose level on day 4, however, neither an increase in hepatic TG level nor histopathological hepatic steatosis was observed at either dose level on day 4. Hepatic mRNA levels of glycerone-phosphate O-acyltransferase (Gnpat), which is a key enzyme for biosynthesis of ePC, was also decreased by treatment with VPA along with the decrease in ePCs. In conclusion, the changes in ePCs, (PC[16:0e/22:4] and PC[16:0e/22:6]), have potential utility as predictive biomarkers for VPA-induced hepatic steatosis.

This paper proposes a scheme for parallel calculation on a Web browser for contents categorization. When we provide a contents categorization with distributed calculation, the file transfer time becomes a major problem. However, if a browser can perform a part of the calculation, we can reduce the transfer time. In this paper, we use Web Workers that allows us to parallel computing. In our system, a Web browser uses the Web Workers and performs a part of the calculation.

Acyl CoA: diacylglycerol acyltransferase (DGAT) 1 is an enzyme that catalyzes the re-synthesis of triglycerides (TG) from free fatty acids and diacylglycerol. JTT-553 is a DGAT1 inhibitor and exhibits its pharmacological action (inhibition of re-synthesis of TG) in the enterocytes of the small intestine leading to suppression of a postprandial elevation of plasma lipids. After repeated oral dosing JTT-553 in rats and monkeys, plasma transaminase levels were increased but there were neither changes in other hepatic function parameters nor histopathological findings suggestive of hepatotoxicity. Based on the results of exploratory studies for investigation of the mechanism of the increase in transaminase levels, plasma transaminase levels were increased after dosing JTT-553 only when animals were fed after dosing and a main factor in the diet contributing to the increase in plasma transaminase levels was lipids. After dosing JTT-553, transaminase levels were increased in the small intestine but not in the liver, indicating that the origin of transaminase increased in the plasma was not the liver but the small intestine where JTT-553 exhibits its pharmacological action. The increase in small intestinal transaminase levels was due to increased enzyme protein synthesis and was suppressed by inhibiting fatty acid-transport to the enterocytes. In conclusion, the JTT-553-related increase in plasma transaminase levels is considered not to be due to release of the enzymes from injured cells into the circulation but to be phenomena resulting from enhancement of enzyme protein synthesis in the small intestine due to the pharmacological action of JTT-553 in this organ.

Diabetic nephropathy (DN) is one of the complications of diabetes and is now the most common cause of end-stage renal disease. Fructose is a simple carbohydrate that is present in fruits and honey and is used as a sweetener because of its sweet taste. Fructose has been reported to have the potential to progress diabetes and DN in humans even though fructose itself does not increase postprandial plasma glucose levels. In this study, we investigated the effects of high fructose intake on the kidney of the Spontaneously Diabetic Torii (SDT) rats which have renal lesions similar to those in DN patients and compared these with the effects in normal SD rats. This study revealed that a 4-week feeding of the high fructose diet increased urinary excretion of kidney injury makers for tubular injury and accelerated mainly renal tubular and interstitial lesions in the SDT rats but not in normal rats. The progression of the nephropathy in the SDT rats was considered to be related to increased internal uric acid and blood glucose levels due to the high fructose intake. In conclusion, high fructose intake exaggerated the renal lesions in the SDT rats probably due to effects on the tubules and interstitium through metabolic implications for uric acid and glucose.

This paper describes a novel training method for acoustic models using connectionist temporal classification (CTC) for Japanese end-to-end automatic speech recognition (ASR). End-to-end ASR can estimate characters directly without using a pronunciation dictionary; however, this approach was conducted mostly in the English research area. When dealing with languages such as Japanese, we confront difficulties with robust acoustic modeling. One of the issues is caused by a large number of characters, including Japanese kanji, which leads to an increase in the number of model parameters. Additionally, multiple pronunciations of kanji increase the variance of acoustic features for corresponding characters. Therefore, we propose end-to-end ASR based on bi-directional long short-term memory (BLSTM) networks to solve these problems. Our proposal involves two approaches: reducing the number of dimensions of BLSTM and adding character strings to output layer labels. Dimensional compression decreases the number of parameters, while output label expansion reduces the variance of acoustic features. Consequently, we could obtain a robust model with a small number of parameters. Our experimental results with Japanese broadcast programs show the combined method of these two approaches improved the word error rate significantly compared with the conventional character-based end-to-end approach.

Type 2 diabetes mellitus (T2DM) arises primarily due to lifestyle factors and genetics. A number of lifestyle factors are known to be important in the development of T2DM, including obesity. JTT-553, a novel Acyl CoA:diacylglycerol acyltransferase 1 inhibitor, reduced body weight depending on dietary fat in diet-induced obesity (DIO) rats in our previous study. Here, the effect of JTT-553 on glucose metabolism was evaluated using body weight reduction in T2DM mice. JTT-553 was repeatedly administered to DIO and KK-A(y) mice. JTT-553 reduced body weight gain and fat weight in both mouse models. In DIO mice, JTT-553 decreased insulin, non-esterified fatty acid (NEFA), total cholesterol (TC), and liver triglyceride (TG) plasma concentrations in non-fasting conditions. JTT-553 also improved insulin-dependent glucose uptake in adipose tissues and glucose intolerance in DIO mice. In KK-A(y) mice, JTT-553 decreased glucose, NEFA, TC and liver TG plasma concentrations in non-fasting conditions. JTT-553 also decreased glucose, insulin, and TC plasma concentrations in fasting conditions. In addition, JTT-553 decreased TNF-α mRNA levels and increased GLUT4 mRNA levels in adipose tissues in KK-A(y) mice. These results suggest that JTT-553 improves insulin resistance in adipose tissues and systemic glucose metabolism through reductions in body weight.

Objective We generated knock-in mice that express a tamoxifen-inducible Cre recombinase from the Prg4 locus (Prg4GFPCreERt2), and used these animals to fate-map the progeny of Prg4-positive articular cartilage cells at various ages.

The impact of the removal of a river mouth bar as a measure against river mouth closure to the surrounding coasts was investigated, taking the Hota coast as an example. Also, on this coast, landfilling was extensively carried out to build a coastal road along the coastline, resulting in the narrowing of the natural sandy beach. These anthropogenic factors affected the overall shoreline on a pocket beach, devastating the natural coastal environment. We investigated the effects of these impacts using aerial photographs and field observations.

In cooperation with Ho Chi Minh City University of Vietnam, beach changes on the coasts of Phan Rang City 270 km east of Ho Chi Minh City were investigated. Beach changes associated with the elongation of a sand spit and sand accumulation owing to the blockage of longshore sand transport by a jetty were investigated using satellite images together with site observation. This method combined satellite image analysis and site observation is useful for investigating beach changes in developing countries, where field data necessary for the analysis are often lacking. Preventive or mitigation measures were considered in view of Integrated Coastal Zone Management in place of the local optimization.

On a sand dune, a blowout is often formed owing to wind effect. The formation of a blowout was observed on November 25, 2016 at the Node coast facing the Pacific Ocean, where a blowout has been formed to leave a concave topography. Then, a model for predicting the formation of a blowout was developed using a cellular automaton method, in which two important factors of saltation and avalanche were taken into account. The results of the numerical simulation were compared with the measured results on the Node coast, and the predicted and measured shapes of the blowout were in good agreement. Also, it was found that the direction of the beach access must be extended in the direction normal to the direction of prevailing wind to prevent blowout formation.

A folksonomy is a system to classify an online item/concept by a short text label as a tag that is applied by users. Many folksonomies include many tags that consist words of long-tail contents. To explain these tags, A wiki-like system provided by some folksonomy services for user understanding. These systems provide a function that creates a link to another article automatically that described in an article for enriching the articles. The cause of the automatic link construction function, those wiki-like systems includes many incorrect links. By these incorrect links, it is hard to use the systems for applications that use Wikipedia internal links. Therefore, we propose a method for extracting correct links from all of the automatically created links.

This paper shows a topic trend on a P2P based Social Network Service. There is a text-based Social Network Service (SNS) named Mastodon. Mastodon is a peer-to-peer and open-source SNS. Many persons and companies run Mastodon instances. We consider that there is a topic trend for each node. In this paper, we collect text messages and infer topic trend on a Mastodon instance using Latent Dirichlet Allocation(LDA). The understanding a topic trend helps to choice an instance that a user should participate.

Recent years have witnessed web services drastically becoming popular in our daily lives, and many consumers take user reviews of products into account when planning purchases. The number of cosmetic review sites, users, and products posted have been increasing year by year. For example, when a user searches for skin lotions using the @cosme website, she consults with reviews of users with similar attributes to her own (age, skin quality, etc.) and searches for items that are compatible with the skin lotion that she uses on a daily basis. However, since different basic cosmetics may have different effects, it is difficult to find products that are compatible with a user, even using the review information from @cosme. In this study, we assume that the compatibility between a user and a basic cosmetic product depends on its cosmetic ingredients. Combining review information from Bihada-Mania website with that from @cosme, we extracted the effective cosmetic ingredients for each user attribute and developed a recommender system of basic cosmetics based on ingredients. We applied the IF-IPF method which applied the concept of TF-IDF method to extraction of effective ingredients of cosmetics. We have defined the scale “invalidated product number” to evaluate the effectiveness of our recommendation service. From the results of the two experiments, the invalidated product number is less than 5% for all user attributes. This indicates that our recommender system has certain reliability.

This paper describes a distributed calculation scheme for scoring relationship among documents. This scheme categorizes documents by using an algorithm which calculates a score value for the relationship between a category and a word in a document. The longer calculation time becomes when increasing the number of documents. Therefore, our scheme uses multiple machines. A master node divides a document set into several subsets, and it distributes them to each calculation nodes. Using this distributed calculation makes the calculation time short, and also makes the memory usage low.