Machine learning for the diagnosis of early stage diabetes using temporal glucose profiles

Machine learning shows remarkable success for recognizing patterns in data. Here we apply the machine learning (ML) for the diagnosis of early stage diabetes, which is known as a challenging task in medicine. Blood glucose levels are tightly regulated by two counter-regulatory hormones, insulin and glucagon, and the failure of the glucose homeostasis leads to the common metabolic disease, diabetes mellitus. It is a chronic disease that has a long latent period the complicates detection of the disease at an early stage. The vast majority of diabetics result from that diminished effectiveness of insulin action. The insulin resistance must modify the temporal profile of blood glucose. Thus we propose to use ML to detect the subtle change in the temporal pattern of glucose concentration. Time series data of blood glucose with sufficient resolution is currently unavailable, so we confirm the proposal using synthetic data of glucose profiles produced by a biophysical model that considers the glucose regulation and hormone action. Multi-layered perceptrons, convolutional neural networks, and recurrent neural networks all identified the degree of insulin resistance with high accuracy above $85\%$.Comment: 4 pages, 2 figur

Chronic rhinosinusitis with nasal polyps in older adults : clinical presentation, pathophysiology, and comorbidity

Purpose of Review Chronic rhinosinusitis and nasal polyps (CRSwNP) is a common condition that significantly affects patients' life. This work aims to provide an up-to-date overview of CRSwNP in older adults, focusing on its aging-related clinical presentations, pathophysiology, and comorbidity associations including asthma. Recent Findings Recent large population-based studies using nasal endoscopy have shown that CRSwNP is a mostly late-onset disease. Age-related changes in physiologic functions, including nasal epithelial barrier dysfunction, may underlie the incidence and different clinical presentations of CRSwNP in older adults. However, there is still a paucity of evidence on the effect of aging on phenotypes and endotypes of CRSwNP. Meanwhile, late-onset asthma is a major comorbid condition in patients with CRSwNP; they frequently present with type 2 inflammatory signatures that are refractory to conventional treatments when they are comorbid. However, as they are more commonly non-atopic, causative factors other than classical atopic sensitization, such as Staphylococcus aureus specific IgE sensitization, are suggested to drive the type 2 inflammation. There are additional comorbidity associations in older patients with CRSwNP, including those with chronic otitis media and head and neck malignancy. Age is a major determinant for the incidence and clinical presentations of CRSwNP. Given the heterogeneity in phenotypes and endotypes, longitudinal investigations are warranted to elucidate the effects of aging on CRSwNP

Micromechanical characterization of single-crystalline niobium at low temperature

Due to the significant interests in application of micro-electro-mechanical system to devices used in harsh environments, small-scale mechanical behaviors in different thermal environments have been extensively studied recently. Particularly, the study on mechanical behavior of body-centered-cubic (bcc) metals has received a strong attention because of the significant temperature dependence of screw dislocation mobility and its cross-slip probability. So far, most studies have been done in either room temperature or elevated temperature, but a low temperature study is relatively scarce. In this work, we present our recent development of in-situ cryogenic micromechanical testing system and the results of cryogenic micro-tensile tests on a [0 0 1] bcc niobium single crystal. The dog-bone shaped tensile samples were fabricated via focused-ion beam milling and were tested at room temperature, 100K and 56K. The decrease in temperature increased the flow strengths. In addition, stress-strain curves at room temperature were smooth, but those at 56 and 100K showed a few distinctively large strain bursts. Post-mortem scanning electron microscopy revealed that necking region of samples tested at room temperature underwent uniform and homogeneous plastic deformation, but that at low temperature underwent highly localized plastic deformation followed by brittle fracture with limited ductility. Thus, micro-tensile tests of niobium single crystal show the ductile-to-brittle transition. All the results will be discussed in terms of the temperature dependence of cross-slip and intrinsic lattice resistance of screw dislocation. Our results will enable a deeper understanding of the combined effects of sample dimension and temperature on plasticity and fracture processes in bcc metals

A Design of MAC Model Based on the Separation of Duties and Data Coloring: DSDC-MAC

Among the access control methods for database security, there is Mandatory Access Control (MAC) model in which the security level is set to both the subject and the object to enhance the security control. Legacy MAC models have focused only on one thing, either confidentiality or integrity. Thus, it can cause collisions between security policies in supporting confidentiality and integrity simultaneously. In addition, they do not provide a granular security class policy of subjects and objects in terms of subjects\u27 roles or tasks. In this paper, we present the security policy of Bell_LaPadula Model (BLP) model and Biba model as one complemented policy. In addition, Duties Separation and Data Coloring (DSDC)-MAC model applying new data coloring security method is proposed to enable granular access control from the viewpoint of Segregation of Duty (SoD). The case study demonstrated that the proposed modeling work maintains the practicality through the design of Human Resources management System. The proposed model in this study is suitable for organizations like military forces or intelligence agencies where confidential information should be carefully handled. Furthermore, this model is expected to protect systems against malicious insiders and improve the confidentiality and integrity of data

Economic Possibilities of Shipping though Northern Sea Route1

AbstractGlobal warming and climate change haves brought a new issue in the Arctic sea. Therefore, we can now explore new shipping routes through the Arctic Ocean instead of the existing commercial route. In particular, the Northern Sea Route (NSR) is one of the feasible shipping routes and, has provided tremendous shipping benefits. If the NSR becomes commercialized, we will be able to save about 5,000 nautical miles in distance and sailing time. In this study, we will emphasize some of the important results on the possibility of commercializing the shipping route in the Arctic. The NSR may bring positive economic effects in terms of shipping distance and time. For example, when utilizing the NSR, the maximum cargo traffic between Asia and Europe is expected to be around 46 million TEU. However, we also need to consider an expensive passage fee that is currently imposed by Russia. In conclusion, we maintain our efforts to protect the environment in the Arctic, in terms of logistics, and we need to explore every possible avenue to bring possible economic benefits to the North Pacific countries

Putative cell adhesion membrane protein Vstm5 regulates neuronal morphology and migration in the central nervous system

During brain development, dynamic changes in neuronal membranes perform critical roles in neuronal morphogenesis and migration to create functional neural circuits. Among the proteins that induce membrane dynamics, cell adhesion molecules are important in neuronal membrane plasticity. Here, we report that V-set and transmembrane domain-containing protein 5 (Vstm5), a cell-adhesion-like molecule belonging to the Ig superfamily, was found in mouse brain. Knock-down of Vstm5 in cultured hippocampal neurons markedly reduced the complexity of dendritic structures, as well as the number of dendritic filopodia. Vstm5 also regulates neuronal morphology by promoting dendritic protrusions that later develop into dendritic spines. Using electroporationin utero, we found that Vstm5 overexpression delayed neuronal migration and induced multiple branches in leading processes during corticogenesis. These results indicate that Vstm5 is a new cell-adhesion-like molecule and is critically involved in synaptogenesis and corticogenesis by promoting neuronal membrane dynamics.SIGNIFICANCE STATEMENTNeuronal migration and morphogenesis play critical roles in brain development and function. In this study, we demonstrate for the first time that V-set and transmembrane domain-containing protein 5 (Vstm5), a putative cell adhesion membrane protein, modulates both the position and complexity of central neurons by altering their membrane morphology and dynamics. Vstm5 is also one of the target genes responsible for variations in patient responses to treatments for major depressive disorder. Our results provide the first evidence that Vstm5 is a novel factor involved in the modulation of the neuronal membrane and a critical element in normal neural circuit formation during mammalian brain development.</jats:p

Query-Efficient Black-Box Red Teaming via Bayesian Optimization

The deployment of large-scale generative models is often restricted by their potential risk of causing harm to users in unpredictable ways. We focus on the problem of black-box red teaming, where a red team generates test cases and interacts with the victim model to discover a diverse set of failures with limited query access. Existing red teaming methods construct test cases based on human supervision or language model (LM) and query all test cases in a brute-force manner without incorporating any information from past evaluations, resulting in a prohibitively large number of queries. To this end, we propose Bayesian red teaming (BRT), novel query-efficient black-box red teaming methods based on Bayesian optimization, which iteratively identify diverse positive test cases leading to model failures by utilizing the pre-defined user input pool and the past evaluations. Experimental results on various user input pools demonstrate that our method consistently finds a significantly larger number of diverse positive test cases under the limited query budget than the baseline methods. The source code is available at https://github.com/snu-mllab/Bayesian-Red-Teaming.Comment: ACL 2023 Long Paper - Main Conferenc

Data-Reserved Periodic Diffusion LMS With Low Communication Cost Over Networks

In this paper, we analyze diffusion strategies in which all nodes attempt to estimate a common vector parameter for achieving distributed estimation in adaptive networks. Under diffusion strategies, each node essentially needs to share processed data with predefined neighbors. Although the use of internode communication has contributed significantly to improving convergence performance based on diffusion, such communications consume a huge quantity of power in data transmission. In developing low-power consumption diffusion strategies, it is very important to reduce the communication cost without significant degradation of convergence performance. For that purpose, we propose a data-reserved periodic diffusion least-mean-squares (LMS) algorithm in which each node updates and transmits an estimate periodically while reserving its measurement data even during non-update time. By applying these reserved data in an adaptation step at update time, the proposed algorithm mitigates the decline in convergence speed incurred by most conventional periodic schemes. For a period p, the total cost of communication is reduced to a factor of 1/p relative to the conventional adapt-then-combine (ATC) diffusion LMS algorithm. The loss of combination steps in this process leads naturally to a slight increase in the steady-state error as the period p increases, as is theoretically confirmed through mathematical analysis. We also prove an interesting property of the proposed algorithm, namely, that it suffers less degradation of the steady-state error than the conventional diffusion in a noisy communication environment. Experimental results show that the proposed algorithm outperforms related conventional algorithms and, in particular, outperforms ATC diffusion LMS over a network with noisy links.11Ysciescopu

Improving the Vertical Accuracy of Indoor Positioning for Emergency Communication

The emergency communication systems are undergoing a transition from the PSTN-based legacy system to an IP-based next generation system. In the next generation system, GPS accurately provides a user's location when the user makes an emergency call outdoors using a mobile phone. Indoor positioning, however, presents a challenge because GPS does not generally work indoors. Moreover, unlike outdoors, vertical accuracy is critical indoors because an error of few meters will send emergency responders to a different floor in a building. This paper presents an indoor positioning system which focuses on improving the accuracy of vertical location. We aim to provide floor-level accuracy with minimal infrastructure support. Our approach is to use multiple sensors available in today's smartphones to trace users' vertical movements inside buildings. We make three contributions. First, we present the elevator module for tracking a user's movement in elevators. The elevator module addresses three core challenges that make it difficult to accurately derive displacement from acceleration. Second, we present the stairway module which determines the number of floors a user has traveled on foot. Unlike previous systems that track users' foot steps, our stairway module uses a novel landing counting technique. Third, we present a hybrid architecture that combines the sensor-based components with minimal and practical infrastructure. The infrastructure provides initial anchor and periodic corrections of a user's vertical location indoors. The architecture strikes the right balance between the accuracy of location and the feasibility of deployment for the purpose of emergency communication