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We present improved algorithms for the Steiner tree problem with the minimum number of Steiner points and bounded edge length. Given n terminal points in a 2D Euclidean plane and an edge length bound, the problem asks to construct a spanning tree of n terminal points with minimal Steiner points such that every edge length of the spanning tree is within the given bound. This problem is known to be NP-hard and has practical applications such as relay node placements in wireless networks, wavelength-division multiplexing(WDM) optimal network design, and VLSI design. The best-known deterministic approximation algorithm has O(n3) running time with an approximation ratio of 3. This paper proposes an efficient approximation algorithm using the Voronoi diagram that guarantees an approximation ratio of 3 in O(n log n) time. We also present the first exact algorithm to find an optimal Steiner tree for given three terminal points in constant time. Using this exact algorithm, we improve the 3-approximation algorithm with better performance regarding the number of required Steiner points in O(n log n) time. [ABSTRACT FROM AUTHOR]

Neurodiversity refers to the idea that all brains—no matter their differences—are valuable and should be accepted. Attitudes toward the neurodiversity perspective can have real-life impacts on the lives of neurodivergent people, from effects on daily interactions to how professionals deliver services for neurodivergent individuals. In order to identify negative attitudes toward neurodiversity and potentially intervene to improve them, we first need to measure these attitudes. This article describes the development and initial validation of the Neurodiversity Attitudes Questionnaire (NDAQ), including item revision based on expert review, cognitive interviews, systematic evaluation of participants’ response process, and analysis of the instrument’s internal factor structure using exploratory structural equation modeling. Pilot analysis with 351 individuals mostly living in the United States who were currently working in or intending to pursue helping professions indicates that the NDAQ has construct validity, is well understood by participants, and fits a five-factor structure. While the NDAQ represents the first instrument designed to specifically assess attitudes toward the neurodiversity perspective, further validation work is still needed.Neurodiversity refers to the idea that brain differences (including disabilities) are valuable and should be accepted. Attitudes toward neurodiversity can have real-life impacts on the lives of neurodivergent people (those whose brains do not fit society’s “standard”). These impacts can include effects on daily interactions, as well as how professionals such as teachers and doctors deliver services to neurodivergent people. In order to identify negative attitudes toward neurodiversity and potentially improve them, we first need to measure these attitudes. This article describes the development of the Neurodiversity Attitudes Questionnaire (NDAQ). NDAQ development included revision of questionnaire items based on feedback from experts and neurodivergent people, systematically evaluating the way participants responded to questionnaire items, and analysis of how the NDAQ items are grouped into different factors. A preliminary analysis with 351 individuals mostly living in the United States who were currently working or planning to work in a helping profession (e.g. doctors, teachers, therapists, and so on) indicates that the NDAQ measures attitudes toward neurodiversity, is well understood by participants, and fits a five-factor structure. While the NDAQ represents the first instrument designed to specifically assess attitudes toward the broad idea of neurodiversity, further work is still needed. [ABSTRACT FROM AUTHOR]

We consider the load balancing and coverage problem of femtocell networks in indoor environment. We propose a novel framework exploiting the Voronoi diagram with respect to the radio propagation distance. Our initial power assignment scheme achieves maximal indoor coverage with minimized maximum required transmit power, which results in reduced interference. Our approach can adopt any radio propagation model to achieve more accurate coverage for an indoor environment with various obstacles. Time varying data traffic may cause unbalanced data load of base stations producing traffic overload. Our dynamic power control algorithm redistributes the data load by automatically adjusting transmit power levels according to data traffic estimation while preserving coverage. Moreover, we present an algorithm to cope with the dynamic deletion and insertion of femto base stations. Simulations show that the proposed scheme achieves better coverage, reduced interference, and good load balance compared to previous algorithms. [ABSTRACT FROM AUTHOR]

A new dynamic control scheme that uses the center of gravity is proposed to control the attitude of an underwater robot. Instead of using thrusters, ballast tanks are used for the static attitude control to avoid generating disturbances around the robot and to lower the power consumption. Five attitude ballast tanks are used to control the roll and pitch of the robot via the translocation of water. Using the dynamic center of gravity, the attitude can be maintained and controlled at a desired angle. The dynamics of the robot are derived using Lagrangian equations. By using the dynamic equations to find the optimal gains of the Proportional Derivative (PD) controller, this robot has been designed to have a fast attitude control capability with low power consumption. Through real experiments, it is demonstrated that the attitude control is efficient and accurate by adjusting the center of gravity. It is also verified that this system has outstanding efficiency in power consumption compared to conventional propeller systems. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Abstract: We propose a method to extract a kinematic skeleton from an articulated 3D model. Unlike the curve skeleton which concentrates on the abstract structure of given model, we aim to obtain the skeleton with accurate joint positions, which can be directly used for character rigging and animation. Restricting our focus on the articulated body, we construct its skeleton in a bottom-up manner starting from a set of automatically obtained feature points. Our method is a hybrid approach combining the advantages of topology-based and geometry-based methods using the Morse theory and the shape descriptor. It does not require manually-chosen feature points or markers, and is independent of both postures and the number of branches of the given model. Experiments show that our method can efficiently extract kinematic skeletons of various kinds of articulated bodies, and also that the results can be directly applied to the character rigging. [Copyright &y& Elsevier]

We consider the problem of guiding mobile agents to visit a subset of sensor nodes called event nodes in wireless sensor networks without location information, where the set of event nodes is not known in advance. As the set of event nodes changes over time, a path needs to be updated on-line. We propose a novel distributed algorithm to construct and update such a dynamic path to visit a set of event nodes. To the best of our knowledge, this is the first work to solve this problem using a distributed algorithm without any location information. Our approach is to maintain the Voronoi diagram of the dynamic set of event nodes implicitly in sensor networks. Doing so, we overcome the lack of location information and implement scalable distributed dynamic navigation. For computing an optimal path is NP-Hard, we prove that the ratio of the length of the constructed path by our algorithm to that of the optimal path is bounded by O(log k), where k is the number of event nodes, under a reasonable assumption. Our approach can be used to compute both an event visiting tour which requires to return to a starting point and an event visiting path which does not return to a starting point. We also extend our method to navigate multiple agents so that they collectively visit a set of event nodes. [ABSTRACT FROM AUTHOR]

Given n points, called terminals, in the plane ℝ and a positive integer k, the bottleneck Steiner tree problem is to find k Steiner points from ℝ and a spanning tree on the n+ k points that minimizes its longest edge length. Edge length is measured by an underlying distance function on ℝ, usually, the Euclidean or the L metric. This problem is known to be NP-hard. In this paper, we study this problem in the L metric for any 1≤ p≤∞, and aim to find an exact algorithm which is efficient for small fixed k. We present the first fixed-parameter tractable algorithm running in f( k)⋅ nlog n time for the L and the L metrics, and the first exact algorithm for the L metric for any fixed rational p with 1< p<∞ whose time complexity is f( k)⋅( n+ nlog n), where f( k) is a function dependent only on k. Note that prior to this paper there was no known exact algorithm even for the L metric. [ABSTRACT FROM AUTHOR]

The problem of computing a piecewise linear approximation to a surface from a set of sample points is important in solid modeling, computer graphics and computer vision. A recent algorithm using the Voronoi diagram of the sample points gave a guarantee on the distance of the output surface from the original sampled surface assuming that the sample was sufficiently dense. We give a similar algorithm, simplifying the computation and the proof of the geometric guarantee. In addition, we guarantee that our output surface is homeomorphic to the original surface; to our knowledge this is the first such topological guarantee for this problem. [ABSTRACT FROM AUTHOR]

This study examines whether households are encouraged to conserve electricity when their monthly utility statements indicate that their electricity usage is higher than that of their neighbours. A difference-in-differences analysis for 1161 Korean apartment households from 2016 to 2017 shows that the conservation effect appears only for those in medium-sized housing units. An eye-tracking experiment suggests a reason for this limited conservation effect: the average gazing time for the section of the statement that compares electricity usage across neighbouring households is lesser than the gazing time for other sections, indicating little interest in the information. We discuss this in the context of shared mental models that can guide people to consider social norms as context for their individual energy usage. • Difference-in-differences analysis finds conservation in medium-apartment households. • Eye-tracking experiment shows little interest in neighbour-comparison information. • Specifically, medium-apartment households are only interested in such information. • Most of households do not share social norm as context of individual energy usage. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to examine whether salience of neighbor comparison information attracts more attention from residents and consequently leads to significant energy conservation. An eye-tracking experiment on 54 residents in a local apartment complex in Korea found that the average time of attention to the neighbor comparison information increased to 277 ms when the size of the information was four times larger and the information was located to the far left. However, the interviews with the subjects suggest that salience of the information is seemingly unrelated to energy conservation, because most of them did not agree with the social consensus that individuals need to refrain from consuming energy when they know that they have consumed more than the neighbor's average. Utility data on 502 households in the apartments revealed that, of the households notified that they consumed more than their neighbors, only less than 50% reduced their energy consumption, which supports the interview results. Therefore, it was concluded that neighbor comparison information did not lead to significant energy conservation effects in the community, although salience of the information contributed to attracting more attention to the information. Unavailable household data remained as limitation to clarify the effect by households. [ABSTRACT FROM AUTHOR]

Progressive compression is one of the most effective multi-resolution schemes for sending large 3D meshes in a network environment. However, if we change the 3D meshes, i.e., adding watermarks or changing the pose of models, the deformed 3D mesh model should be compressed again from scratch and it may take too much time especially for large mesh models. In this paper, we greatly reduce the compression time for deformed models, which we call recompression , when connectivity-preserving deformation is applied to mesh models. We first compress a large mesh progressively using a wavelet-based method, and then extract vertices and wavelet coefficients affected by deformed area using our propagation algorithm. Direct modification acts on the required elements using original matrix filters without additional postprocessing, boosting compression performance. Our method increases the recompression speed up to 17 fold compared with the original speed, even if the entire mesh is deformed. We also show that the speedup increases up to 33 fold when local deformation acts on the local regions comprising 5% of mesh. • Practical way for progressive compression after connectivity-preserving deformation. • Wavelet-based propagation algorithm utilizing previously compressed mesh. • High recompression speedup about large mesh up to 5 million vertices. [ABSTRACT FROM AUTHOR]

This study addresses a view-path-planning problem during 3-D scanning of a large-scale structure based on multiview stereo (MVS) for unmanned aerial platforms. Recently, most studies have adopted an explore-then-exploit strategy for 3-D scanning. The strategy first generates a coarse model from a simple overhead scanning and then plans an inspection path to cover the entire surface of the coarse model. However, even though the inspection path may be optimal, it is difficult to guarantee a complete and accurate reconstruction result due to defective factors of MVS such as occlusions, textureless surfaces, and insufficient parallaxes. Furthermore, the entire procedure of this strategy is inefficiently slow because of path redundancies and long MVS processing time. Therefore, we propose a novel view-path-planning method for 3-D scanning based on an online MVS reconstruction algorithm. The suggested method incrementally reconstructs the target model online and iteratively plans view paths by analyzing the current partial reconstructions. The method continuously analyzes the quality of the model and detects inaccurately reconstructed surfaces. It then plans an inspection path that provides a complete coverage of the detected surfaces while maximizing the performance of MVS. This method can construct a complete 3-D model in a single scanning trial without the need for rescanning. Extensive experiments show that our method outperforms the other state-of-the-art methods, especially in terms of the model completeness of complex structures. [ABSTRACT FROM AUTHOR]

Osteoporosis is a degenerative disease characterized by reduced bone mass, in which deregulated bone remodeling by osteoclasts and osteoblasts is a main pathogenesis. Although recently tussilagone, a major active component of flower buds of Tussilago farfara , has been shown to inhibit osteoclastogenesis, its effect on estrogen deficiency-induced osteoporosis remains unknown. This study examined the effect of tussilagone on bone loss in ovariectomized mice and further explored its impact on osteoclast apoptosis and osteoblast formation in addition to osteoclastogenesis. Tussilagone suppression of osteoclastogenesis was confirmed in bone marrow derived macrophages, which was observed with the 1/10 concentration of that of the previous study. As demonstrated by ApoPercentage dye staining and Western blotting, tussilagone enhanced apoptosis in differentiated osteoclasts by increasing estrogen receptor α and Fas ligand expression. On the contrary, either osteoblast differentiation or mineralization was not affected by tussilagone. Lastly, administering tussilagone to mice for 6 weeks prevented trabecular microarchitecture impairment in ovariectomized mice compared to vehicle control groups. These findings suggest that tussilagone or Tussilago farfara prevents osteoporotic bone loss by suppressing osteoclast differentiation and inducing osteoclast apoptosis, and that it may therefore offer a possible remedy against resorptive bone diseases. Image 1 • Tussilagone inhibits differentiation of BMMs into osteoclasts. • Tussilagone induces apoptosis in osteoclasts. • Tussilagone decreases estrogen deficiency-induced bone loss in mice. [ABSTRACT FROM AUTHOR]

This paper introduces a method to generate a three-dimensional (3D) virtual model of an imaginary city from a single street-view image to represent the appearance of the city in a given input photograph. The proposed approach differs from reconstruction approaches, which generate a city model by guessing the city name from the input photograph. In contrast, we use machine learning to identify where to generate the city, what to allocate in the city, and how to arrange the components. We employ generative adversarial networks and convolutional neural networks to create a terrain map and identify the components and styles that represent the virtual city appearance. We demonstrate that our system creates 3D virtual cities that are visually similar in terms of plausibility and naturalness to actual cities corresponding to input photographs from around the world. To the best of our knowledge, this is the first work to generate a city model including all general city components, including streets, buildings, and vegetation, to match the style of a single input image. [ABSTRACT FROM AUTHOR]

In this paper, we propose a resampling detection method for stereoscopic images. Although previous resampling techniques can be applied to stereoscopic images, performance improvement is hard to be expected with the two separated results. In this research, we found a strong relationship between the left and right images derived from the characteristics of the stereoscopic images. The proposed technique exploits that relationship of the stereoscopic images as additional information for reliable detection performance. Furthermore, the proposed method includes a preprocessing step to acquire the independent performance from the image's own characteristics. The experimental results exhibit superior performance compared with the existing works. [ABSTRACT FROM AUTHOR]

Forkhead Box M1 (FOXM1) is known to regulate cell proliferation, apoptosis and tumorigenesis. The lignan, (−)-(2R,3R)-1,4-O-diferuloylsecoisolariciresinol (DFS), from Alnus japonica has shown anti-cancer effects against colon cancer cells by suppressing FOXM1. The present study hypothesized that DFS can have anti-cancer effects against glioblastoma (GBM) tumorspheres (TSs). Immunoprecipitation and luciferase reporter assays were performed to evaluate the ability of DFS to suppress nuclear translocation of β-catenin through β-catenin/FOXM1 binding. DFS-pretreated GBM TSs were evaluated to assess the ability of DFS to inhibit GBM TSs and their transcriptional profiles. The in vivo efficacy was examined in orthotopic xenograft models of GBM. Expression of FOXM1 was higher in GBM than in normal tissues. DFS-induced FOXM1 protein degradation blocked β-catenin translocation into the nucleus and consequently suppressed downstream target genes of FOXM1 pathways. DFS inhibited cell viability and ATP levels, while increasing apoptosis, and it reduced tumorsphere formation and the invasiveness of GBM TSs. And DFS reduced the activities of transcription factors related to tumorigenesis, stemness, and invasiveness. DFS significantly inhibited tumor growth and prolonged the survival rate of mice in orthotopic xenograft models of GBM. It suggests that DFS inhibits the proliferation of GBM TSs by suppressing FOXM1. DFS may be a potential therapeutic agent to treat GBM. [ABSTRACT FROM AUTHOR]

Abstract: Given a virtual garment model on a reference human model, we propose an automated 3D garment fitting system that fits the garment model to a target human model. The proposed method can transfer garment models between human models without any user guidance even when the reference and target human models have different poses. Our goal is not to resize or deform the original garment model according to the target human model but to yield realistic fitting results of the given garment on the target human models. Using pose-independent segmentation and cloth simulation, we achieve realistic and automatic fitting results in reasonable running time. Our method can replace the time-consuming manual fitting process that is necessary for many applications that use virtual garments, such as games, animations, CAD tools and online clothing stores. [Copyright &y& Elsevier]

We present a novel method to approximate medial axis points given a set of points sampled from a surface and the normal vectors to the surface at those points. For each sample point, we find its maximal tangent ball containing no other sample points, by iteratively reducing its radius using nearest neighbor queries. We prove that the center of the ball constructed by our algorithm converges to a true medial axis point as the sampling density increases to infinity. We also propose a simple heuristic to handle noisy samples. By simple extensions, our method is applied to medial axis point simplification, local feature size estimation and feature-sensitive point decimation. Our algorithm is simple, easy to implement, and suitable for parallel computation using GPU because the iteration process for each sample point runs independently. Experimental results show that our method is efficient both in time and in space. [ABSTRACT FROM AUTHOR]

Background: Obesity is an important risk factor for polyneuropathy (PN) in subjects with DM. However, PN can be detected in subjects without overt DM but with risk factors for DM such as metabolic syndrome. Therefore, it is worthy to investigate the prevalence of PN in obese subjects and to discover the underlying mechanisms of the association between obesity and PN. Methods: We analyzed the data of 184 subjects who underwent bariatric/metabolic surgery. PN was diagnosed when a Michigan Neuropathy Screening Instrument score was ≥ 2.5. Total body fat mass and percentage were measured by bioimpedance analysis, and visceral fat area (VFA) was quantified by computed tomography. According to DM status, obesity-related parameters were compared between subjects with PN and those without PN. The association between obesity-related parameters and PN was analyzed using logistic regression models. Results: Of 184 subjects (mean age, 39.1 years; mean BMI, 38.6 kg/m2), 39.7% were diagnosed with DM. The prevalence of PN was 9.0% in non-DM group and 21.9% in DM group. In non-DM group, subjects with PN showed higher HOMA-IR, fat mass, and VFA compared with those without PN. HOMA-IR (OR, 1.492; 95% CI, 1.110-2.005), fat mass (OR, 1.087; 95% CI, 1.008-1.171), and VFA (OR 1.013; 95% 1.001-1.024) were significantly associated with PN even after adjustment of known risk factors of PN. In DM group, subjects with PN showed higher body weight, BMI, waist circumference, and VFA compared with those without PN. However, after adjustment of known risk factors of PN, these obesity related parameters were not significantly associated with PN. Conclusion: Fat mass and insulin resistance might be independent risk factors in development of PN for obese subjects without DM. PN evaluation might be necessary in subjects with morbid obesity even before development of overt DM, and we need to investigate whether weight loss intervention can prevent or delay PN in obese subjects. Disclosure: K. Kim: None. T. Oh: None. S. Choi: None. H. Jang: None. [ABSTRACT FROM AUTHOR]

The calcium Sensing Receptor (CaSR) is a cell surface receptor belonging to the family of G-protein coupled receptors. CaSR is mainly expressed by parathyroid glands, kidneys, bone, skin, adipose tissue, the gut, the nervous system, and the cardiovascular system. The receptor, as its name implies is involved in sensing calcium fluctuations in the extracellular matrix of cells, thereby having a major impact on the mineral homeostasis in humans. Besides calcium ions, the receptor is also activated by other di- and tri-valent cations, polypeptides, polyamines, antibiotics, calcilytics and calcimimetics, which upon binding induce intracellular signaling pathways. Recent studies have demonstrated that CaSR influences a wide variety of cells and processes that are involved in inflammation, the cardiovascular system, such as vascular calcification, atherosclerosis, myocardial infarction, hypertension, and obesity. Therefore, in this review, the current understanding of the role that CaSR plays in inflammation and its consequences on the cardiovascular system will be highlighted. [ABSTRACT FROM AUTHOR]

This paper presents a computational framework for providing affective labels to real-life situations, called A-Situ. We first define an affective situation, as a specific arrangement of affective entities relevant to emotion elicitation in a situation. Then, the affective situation is represented as a set of labels in the valence-arousal emotion space. Based on psychological behaviors in response to a situation, the proposed framework quantifies the expected emotion evoked by the interaction with a stimulus event. The accumulated result in a spatiotemporal situation is represented as a polynomial curve called the affective curve, which bridges the semantic gap between cognitive and affective perception in real-world situations. We show the efficacy of the curve for reliable emotion labeling in real-world experiments, respectively concerning (1) a comparison between the results from our system and existing explicit assessments for measuring emotion, (2) physiological distinctiveness in emotional states, and (3) physiological characteristics correlated to continuous labels. The efficiency of affective curves to discriminate emotional states is evaluated through subject-dependent classification performance using bicoherence features to represent discrete affective states in the valence-arousal space. Furthermore, electroencephalography-based statistical analysis revealed the physiological correlates of the affective curves. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study is to evaluate if low muscle mass increases risk of T2D in women with previous gestational diabetes mellitus (pGDM). Methods: A total of 378 women with pGDM (mean age: 35.6 ± 3.9 years) was prospectively evaluated for incidence of T2D. GDM was diagnosed with 75g or 100g oral glucose tolerance test (OGTT) during 24-28 week gestational age. Reclassification of glycemic status was performed with 75g OGTT at 2 months after delivery and lean body mass (LBM) was assessed with bioelectrical impedance analysis (Inbody720, Seoul, Korea). LBM was divided by BMI and this index was divided into 3 tertiles: lowest ≤0.88 (N=107), middle 0.89-0.97 (N=111), highest ≥0.98 group (N=99). The primary outcome was incidence of T2D up to 1 year follow up. Results: The lowest muscle group developed T2D (p=0.007) more than higher muscle groups. The trend for risk developing prediabetes and T2D was significantly increased according to LBM/BMI tertiles (p for trend=0.002). After adjusting family history of T2D, extent of gestational hyperglycemia and waist circumference, lowest group demonstrated HR for developing T2D 6.6 [CI 1.36 to 32.25], p=0.01, compared to the highest group. Conclusion: Lower muscle mass is an independent risk factor for T2D in pGDM. Therefore, it is important to examine muscle mass during risk assessment for T2D in Korean non-obese women with pGDM. Disclosure: Y. Shin: None. T. Oh: None. S. Choi: None. H. Jang: Speaker's Bureau; Self; Daiichi Sankyo, Handok, Pfizer Inc., Takeda Pharmaceutical Company Limited. [ABSTRACT FROM AUTHOR]

Objective: Diabetes has been suggested to be one of the risk factors of physical disability in older adults. The aim of this study is to examine the prevalence of sarcopenia in Korean older adults with diabetes compared to nondiabetic adults. Methods: We analyzed 1,241 adults aged 70-84 years, who were enrolled in the Korean Frailty and Aging Cohort Study (KFACS). The skeletal muscle mass was assessed by dual-energy X-ray absorptiometry, and muscle strength was assessed by hand grip strength (HGS). Physical performance was assessed by the Short Physical Performance Battery (SPPB), and the Timed Up and Go (TUG) test. Sarcopenia was defined using the criteria of Asian Working Group for Sarcopenia (AWGS) and the Foundation for the National Institutes of Health (FNIH). Results: The mean age of the subjects was 76.2 ± 9.3 years, and 46.8% were men. Prevalence of diabetes was 31.1% in men and 23.8% in women. Subjects with diabetes had higher levels of fasting glucose, insulin, HbA1c, and HOMA-IR, compared to the nondiabetic group. In men, the prevalence of sarcopenia and muscle mass index was not different between diabetic and nondiabetic groups, but the diabetic subjects had lower HGS and gait speed, and they took longer time on TUG test compared to the nondiabetic group. In women, the prevalence of sarcopenia defined by AWGS was higher in the diabetic group compared to the nondiabetic group. Women with diabetes had lower gait speed and SPPB score, and took longer time on TUG test compared to the nondiabetic group, although HGS and muscle mass index were not different between the two group. Conclusion: Prevalence of sarcopenia was higher in older women with diabetes compared to nondiabetic group, but those are not different in men. In older adults with diabetes, physical performance and muscle strength were reduced, whereas muscle mass was relatively preserved compared to the nondiabetic group. Thus, in older adults, diabetes might be associated with developing sarcopenia, especially in a form of decreased muscle quality. Disclosure: S. Kang: None. T. Oh: None. S. Choi: None. K. Park: None. H. Jang: None. [ABSTRACT FROM AUTHOR]

Self-awareness of diabetes is the first step to prevent this non-curable disease. Therefore, it is important to develop diabetes risk scores which can be easily calculated by general people. We developed self-assessable diabetes risk score using the data of Korean Genome and Epidemiology Study (KoGES). A total of 8,740 subjects without diabetes at baseline were followed-up biannually over 10 years. We assessed the significantly different clinical and non-laboratory variables at baseline between subjects developed diabetes mellitus and those free from diabetes at 10-year follow-up. Each of variables generated a maximum score of 100 in each gender group. Next, the 10-year probability of incident diabetes in each score was calculated. During a median follow-up of 9.7 years, 22.7% of subjects progressed to diabetes. The self-assessable diabetes risk scores included age, living location, smoking history, hypertension, family history of diabetes and waist circumference. The developed risk score yielded acceptable discrimination for incident diabetes in both male (AUC 0.661) and female (AUC 0.691). If the subject had a score more than 50, the probability of 10-year incident diabetes would be 43.4% and 36.1% in male and female, respectively. In conclusion, our newly developed self-assessable diabetes risk score is easily applicable to people without diabetes to predict their future risk of diabetes by themselves without laboratory tests. This model would be helpful to make a diabetes prevention program and to identify high risk subjects who should undergo laboratory tests more frequently. Further studies will be needed to validate the model and to test its feasibility in real clinical settings. Disclosure: T. Oh: None. J. Moon: None. S. Choi: None. S. Lim: None. Y. Cho: Consultant; Self; Hanmi Pharm. Co., Ltd. Research Support; Self; AstraZeneca, Sanofi-Aventis. K. Park: None. N.H. Cho: None. H. Jang: None. Funding: Korea Centers for Disease Control & Prevention [ABSTRACT FROM AUTHOR]

Diabetic neuropathy is one of microvascular complications of diabetes. Among many types of diabetic neuropathy small-fiber neuropathy is believed to be the earliest sign of nerve dysfunction. Albuminuria, the other microvascular complication, is common and precedes renal dysfunction in diabetes and the early detection of these two complications is important. In this study, we investigated whether the small-fiber nerve dysfunction would be prevalent in subjects with diabetes and albuminuria. If so, we could discover a common etiology of these two conditions. We enrolled adult type 2 diabetes (n = 311) and measured their feet electrochemical skin conductance (ESC) by SUDOSCAN, and albumin to creatinine ratio (ACR) using random urine samples. The subjects were categorized according to their albuminuria status: no albuminuria, newly detected albuminuria, and persistent albuminuria. We defined small-fiber neuropathy if the feet ESC levels were less than 60 uS. Mean ages of subjects were 57.9 years and 58.8% were male. Among them, 13.5% and 20.6% of subjects had newly detected and persistent albuminuria, respectively. Mean ESC levels were decreased in subjects with albuminuria than those without albuminuria. In addition, more subjects had small-fiber neuropathy in albuminuria groups than normal counterpart (47.6% vs. 56.3% vs. 26.8% in newly detected albuminuria, persistent albuminuria, and no albuminuria groups, respectively, P <0.001). Feet ESC levels were negatively correlated with ACR and it can detect the presence of albuminuria with 58.5% of sensitivity and 70.2% of specificity. The feet ESC levels were independently associated with albuminuria after adjusting for diabetes duration, HbA1c, systolic blood pressure, triglyceride, and LDL-cholesterol. In conclusion, small-fiber neuropathy was more prevalent in diabetes with albuminuria compared to diabetes without albuminuria. The small-fiber neuropathy might be an independent risk factor for diabetic nephropathy. Disclosure: T. Oh: None. S. Kang: None. S. Choi: None. H. Jang: None. [ABSTRACT FROM AUTHOR]

Finding k nearest neighbor objects in spatial databases is a fundamental problem in many geospatial systems and the direction is one of the key features of a spatial object. Moreover, the recent tremendous growth of sensor technologies in mobile devices produces an enormous amount of spatio-directional (i.e., spatially and directionally encoded) objects such as photos. Therefore, an efficient and proper utilization of the direction feature is a new challenge. Inspired by this issue and the traditional k nearest neighbor search problem, we devise a new type of query, called the direction-constrained k nearest neighbor (DC kNN) query. The DC kNN query finds k nearest neighbors from the location of the query such that the direction of each neighbor is in a certain range from the direction of the query. We develop a new index structure called MULTI, to efficiently answer the DC kNN query with two novel index access algorithms based on the cost analysis. Furthermore, our problem and solution can be generalized to deal with spatio-circulant dimensional (such as a direction and circulant periods of time such as an hour, a day, and a week) objects. Experimental results show that our proposed index structure and access algorithms outperform two adapted algorithms from existing kNN algorithms. [ABSTRACT FROM AUTHOR]

Abstract: We study the problems of computing two non-convex enclosing shapes with the minimum area; the L-shape and the rectilinear convex hull. Given a set of n points in the plane, we find an L-shape enclosing the points or a rectilinear convex hull of the point set with minimum area over all orientations. We show that the minimum enclosing shapes for fixed orientations change combinatorially at most times while rotating the coordinate system. Based on this, we propose efficient algorithms that compute both shapes with the minimum area over all orientations. The algorithms provide an efficient way of maintaining the set of extremal points, or the staircase, while rotating the coordinate system, and compute both minimum enclosing shapes in time and space. We also show that the time complexity of maintaining the staircase can be improved if we use more space. [Copyright &y& Elsevier]

Introduction: Previous studies demonstrated that older adults with diabetes had lower skeletal muscle mass, strength, and physical function compared with those without diabetes. The aim of this study is to evaluate the effect of hyperglycemia and insulin resistance in the progression of sarcopenia in older adults with diabetes. Methods: The Korean Frailty and Aging Cohort Study is a multicenter prospective study with a baseline examination measured in 2016-2017. Longitudinal analysis was conducted with the 2018 follow up data. The difference of muscle related variables over the two years was evaluated for both genders and stratified by the presence of diabetes and insulin resistance. Results: Among the 1,515 participants with baseline and two-year follow-up examination on skeletal muscle mass, strength, and function, 327 (21.6%) had diabetes mellitus at baseline. Participants showed decline in ASM, ASM/height2, ASM/body mass index (BMI), gait speed, and Timed Up and Go (TUG) test regardless of diabetes status over the two years (all p<0.001). In men with higher HOMA-IR (≥1.11), the decline of muscle mass indices (p<0.001), and TUG test (p=0.002) was significantly greater than men with lower HOMA-IR (<1.11). Women with higher HOMA-IR also showed greater decline in hand grip strength (p=0.040) gait speed (p=0.035), muscle mass indices (p<0.005), and TUG test (p=0.010) than women with lower HOMA-IR. None of the variables were significantly different when compared according to the baseline HbA1c level. In subjects without diabetes, the decline of muscle mass indices was significantly greater in subjects with higher HOMA-IR compared to those with lower HOMA-IR, but muscle strength and function were not affected by insulin resistance. Conclusion: Insulin resistance shows preponderating influence over hyperglycemia in progression of sarcopenia in Korean older adults. This result suggests that insulin sensitizer might be beneficial in prevention of sarcopenia in older adults with diabetes. Disclosure: H. Choe: None. K. Kim: None. T. Oh: None. S. Choi: None. K. Park: None. H. Jang: Speaker's Bureau; Self; Daiichi Sankyo, Handok, Pfizer Inc., Takeda Pharmaceutical Company Limited. [ABSTRACT FROM AUTHOR]

Background: Screening for diabetic peripheral neuropathy (DPN) is easily omitted in the busy clinical setting. SUDOSCAN is a non-invasive and convenient tool for evaluating small-fiber neuropathy, but its clinical effectiveness for screening of DPN is lacking. We investigated whether SUDOSCAN combined with a neuropathy questionnaire could be an effective tool for screening for DPN in people with type 2 diabetes. Methods: We analysed the data for 197 people with type 2 diabetes without renal dysfunction or changes in their use of anti-hyperglycaemic medications during the past 3 months. The presence of DPN was evaluated using the Michigan Neuropathy Screening Instrument Physical Examination (MNSI-PE). Electrochemical skin conductance (ESC) of the feet was assessed using SUDOSCAN, and the MNSI Questionnaire (MNSI-Q) and 10-gram monofilament tests were conducted. We developed a scoring model including various combinations of clinical parameters and neuropathy examination results. Results: The prevalence of DPN was 42.6%. Participants with DPN were older (59.9 ± 9.5 vs. 56.7 ± 8.8 years) and had a longer duration of diabetes than those without DPN. Feet ESC distinguished the presence of DPN, and the optimal cut-off value was 69.5 uS. The OR for the association between an abnormal feet ESC (<70 uS) and the presence of DPN was 3.23 (95% CI 1.67, 6.42, p = 0.001). We made the DPN screening scores using the corresponding ORs for age, diabetes duration, and neuropathy evaluation. The MNSI-Q plus SUDOSCAN model (AUC 0.689), but not the MNSI-Q plus 10-gram monofilament model (AUC 0.668) showed better discrimination power than the MNSI-Q-only model (AUC 0.639). Conclusions: The screening model for DPN that includes SUDOSCAN and the MNSI-Q can detect DPN with acceptable discrimination power and is more convenient than neurophysiological studies. This strategy may be useful in the busy outpatient clinical setting. Disclosure: T. Oh: None. K. Kim: None. Y. Shin: None. H. Jang: Speaker's Bureau; Self; Daiichi Sankyo, Handok, Pfizer Inc., Takeda Pharmaceutical Company Limited. S. Choi: None. Funding: Korean Diabetes Association (2016F-5) [ABSTRACT FROM AUTHOR]