Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Vascular Bifurcation in IVOCT Images Using Convolutional Neural Networks With Transfer Learning

Optical coherence tomography (OCT) technology enables experts to analyze coronary lesions from high-resolution intravascular images. Studies have shown a relationship between vascular bifurcation and a higher occurrence of wall thickening and lesions in these areas. Some level of automation could benefit experts since the visual analysis of pullback frames is a laborious and time-consuming task. Although convolutional neural networks (CNNs) have shown promising results in classifying medical images, in this paper, we found no studies using CNNs in IVOCT images to classify the vascular bifurcation. In this paper, we evaluated four different CNN architectures in the bifurcation classification task trained with the IVOCT images from nine pullbacks from nine different patients. We used data augmentation to balance the dataset, due to the small number of bifurcation-labeled frames, and also applied transfer learning methods to incorporate the knowledge from a lumen segmentation task into some of the evaluated networks. Our classification outperforms other works in this literature, presenting AUC = 99.72%, obtained by a CNN with transferred knowledge.
Comparative Sequential Pattern Mining of Human Trajectory Data Collected from a Campus-wide BLE Beacon System

Many social issues are expected to be addressed by collecting human trajectory data and analyzing them. As a demonstration study, we need a continuous and instant localization and trajectory collection system. We have developed a localization system using Bluetooth Low Energy (BLE) beacons and smartphones in our college campus. The system has been established to realize automated student roll call with 1, 600 BLE beacon emitters installed on our campus. We can estimate the location of a smartphone in our campus by analyzing received BLE beacons and their RSSIs (Received Signal Strength Indicators). In this paper, we demonstrate how we collect human trajectory data and how we can detect specific human behaviors from the collected data. We have obtained human trajectory data from 169 research participants comprised of 671 trips during the study held as a college festival event. Each research participant walked around with his/her smartphone. The smartphone continuously received BLE beacons during the event and periodically sent them to the server as a trajectory. We apply comparative sequential pattern mining to the obtained trajectory data and extract sequential patterns that are different between male trajectories and female trajectories. This study demonstrates the effectiveness of human trajectory data collection by a BLE beacon system and data analysis by comparative sequential pattern mining.
Clinical usefulness of measuring red blood cell distribution width on admission in patients with acute coronary syndromes

Abstract Background: Conventional cardiac markers used for the biochemical diagnosis of acute coronary syndromes (ACS) have a high specificity but low sensitivity within 2–4 h of symptoms onset. The red blood cell distribution width (RDW), reflecting the size variability of circulating red blood cells, has been shown to be independently associated with an increased risk of major cardiovascular events. We assessed whether there is an association between RDW at admission and cardiac troponin T (cTnT) elevation in patients with chest pain. Methods: We analyzed RDW values in 2304 adult patients, who were consecutively admitted over a 1-year period to the local emergency department for chest pain suggestive of ACS. In all patients, a baseline blood sample was collected for routine haematological testing, whereas cTnT was measured at baseline and after 4, 6, and 12 h. Results: A total of 456 patients (19.8% of total) had ACS. These patients, all having cTnT≥0.03 μg/L up to 12 h from admission other than ischaemic electrocardiographic changes, had higher RDW than non-ACS patients [median 15.1%, (5th–95th percentiles) 13.2%–19.0% vs. 13.5%, 12.9%–17.1%, p<0.001]. On admission, the sensitivity and specificity of cTnT were 94% (25 false negative results) and 100%, respectively. The diagnostic accuracy of RDW, as calculated by the receiver operating characteristic curve analysis, was 0.705 (p<0.001). At the cut-off value of 14%, the clinical sensitivity and specificity of RDW on admission were 79% and 50%, respectively. In 21 out of 25 patients classified as false negative for cTnT on admission, the RDW was >14%. Accordingly, the diagnostic sensitivity of the two combined measurements on admission was 99%. Conclusions: As RDW is widely available to clinicians as a part of the complete blood count, and therefore incurs no additional costs, it might be considered with other conventional cardiac markers for the risk stratification of ACS patients admitted to emergency departments. Clin Chem Lab Med 2009;47:353–7.
Evaluation of Advanced MOSFET Threshold Voltage Drift Measurement Techniques

The experimental characterization of the threshold voltage shift in metal–oxide–semiconductor field-effect transistors due to degradation mechanisms like bias temperature instability and hot-carrier degradation requires a careful consideration of various pitfalls. One of them concerns the comparability between the threshold voltage shifts obtained by different extraction methods. The focus of this paper is set on the comparison of two extraction methods used at recovery conditions, the constant current and the constant voltage method. Although considered equivalent, a thorough experimental analysis shows that the equivalence of both methods is limited by a low device parameter change during degradation, a measurement in the sub-threshold region, and the consideration of device-to-device variability.
Multi-Keyword Searchable and Data Verifiable Attribute-Based Encryption Scheme for Cloud Storage

In a data sharing system, it is a basic requirement for a user, who has an appropriate privilege to perform keyword retrieval for encrypted documents stored in the cloud. Although traditional searchable encryption technology can provide data protection and retrieval characteristic, there are some main issues should also be considered. First, most existing attribute-based searchable encryption schemes only support single-keyword search, which may return abundant irrelevant search results, resulting in a waste of computational and broadband resources. Second, the user often needs to seek some data related to some particular keywords but his attributes may be altered frequently. Third, the cloud server is not completely loyal which sometimes returns a fraction of erroneous search results. Focus on these issues, a practical multi-keyword searchable encryption scheme is proposed for data integrity verification and attribute revocation by combining the ciphertext policy attribute-based encryption (CP-ABE) and auditing ideas. The scheme on one hand supports multi-keyword search which avoids the cloud server yield ample irrelevant documents by narrowing the search scope, and the other hand can implement effectively attribute revocation by entrusting ciphertext updates to the powerful cloud server, thereby preventing access by illegal users. Furthermore, third-party audits use verification algorithms to ensure the correctness of search results and reduce the amount of computing by end users. The most critically, the scheme proved to be resistant to selective plaintext attacks and selective keyword attacks under the general group model. The extensive experimental results demonstrate that the scheme is more expressive, efficient, and feasible in the practical applications.
Facilitating Unmotivated Tasks Based on Affection for Virtual Pet

In our daily lives, some tasks are burdensome for people and are not willing to do them; however, people often do such tasks for their pets even though they are tired or busy due to affection for the pets. In this paper, we introduce a virtual pet to establish and maintain close relationship with the user to foster a similar feeling with real pets, and a platform for Android OS-based smartphone is developed. Particularly, we show an experiment to investigate the effect of reflective behavior of a virtual pet in increasing affection and accepting requests from the virtual pet, in which activity data collection for supervised-machine learning was chosen as an example of bothersome task. As a result, we confirmed that the reflective behavior significantly contributed to increase affection for the virtual pet, but acceptance rate of a task request did not increased, compared with a non-reflective one.
Positional Asynchronous Electric Drive with Vector Control and Non-Linear Correction

The urgency of the study is determined by the need to improve the control system of the positional electric drive, ensuring the execution of the specified movement by the executive mechanism with the maximum possible fast-action and the required indicators of the quality of the transient process. The aim of the paper is to increase the fast-action of a positional asynchronous electric drive with vector control. Nonlinear correction is realized on the basis of a microprocessor control system of an asynchronous electric drive. The algorithm of the non-linear correction program has two stages. At the first stage, the motion of the electric drive with the limiting acceleration is formed. To do this, a positive feedback proportional to the engine speed is applied, valid until the error (mismatch) in the speed loop exceeds the calculated switching value. At the second stage, the electric drive is effectively braked to produce a monotonic transient motion process. This is achieved by disabling positive and enabling negative speed feedback in the error function of mismatch. The time for working off a set position is reduced by almost 30% according to the mathematical modelin carried out in the Matlab (Simulink) software environment with respect to the movement of the balancing machine portal. The obtained result allows one to draw a conclusion about the advisability of using nonlinear correction in positional asynchronous electric drives with vector control and coordinate observer when external contours are built on the principle of subordinate regulation.
A multiple description CEO problem with log-loss distortion

This paper investigates the Multiple Description (MD) Chief Executive Officer (CEO) problem under logarithmic-loss distortion. The setup extends previous work of Courtade and Weissman (2014) by requiring the CEO to obtain a useful reconstruction also from a reduced set of descriptions. A single-letter characterization of the achievable region is derived under a suitable conditional independence assumption. Surprisingly, the resulting rate requirement is in general less than that required to ensure successful typicality decoding of the corresponding description.
Compact Meta-Surface Antenna Array Decoupling (MAAD) Design for Tightly Coupled Antennas

This paper introduces a series of antenna array decoupling method named Meta-surface Antenna Array Decoupling (MAAD) Method. It has two forms: meta-cover and meta-ground, which place sub-wavelength resonators above and below an antenna array, respectively. By properly adjusting the working frequency of the sub-wavelength resonators, the distance between the antenna array and the meta-surface as well as the self-matching of each antenna array elements, the method can significantly reduce the mutual coupling between the element in an array, while maintain or even increase its matching bandwidth. Thanks to the periodic nature of the meta-surface, the method can directly extended to antenna arrays with more than two elements. It can find good application scenarios in both mobile terminals and Massive MIMO base stations of 5G wireless communication systems.
Novel Integrated Design of a Dual-Band Dual-Polarization 5G mm-Wave Antenna Array Fed by FPCs with a U-Slotted Full-Metal Case for a Cellular Phone

A novel design of a dual-band dual-polarization millimeter-wave (mm-Wave) antenna array fed by a flexible printed circuit (FPC) integrated into a full-metal casing with U-shaped slots of a cellular phone for the fifth generation mobile communications (5G) is proposed. This integrated and conformal design is also promising to the future potential attractive antenna solution of mm-Wave antennas in non-mm-Wave antennas (AiA) especially when a metal frame or a metal casing is applied to the exterior of a cellular phone. The novel mm-Wave antenna array is based on 5 dual-band dual-polarization stacked patch antennas embedded in the metal exterior and the antenna array is fed by one FPC with 10 traces for dual polarizations of each antenna element. Owing to the ground shading of the recessed metal cells for the stacked patch antennas, the performance of the antenna array will be not so susceptible to the components or structures behind the integrated metal structures. Bases on simulations, in terms of the input reflection coefficients| Snn| ≤ -10 dB, the bandwidths of the ports (V-ports) in the mm-Wave antenna array for the vertical polarization (V-pol.) range from 27.43 GHz to 28.49 GHz and from 36.29 GHz to 40.05 GHz, respectively; similarly, the bandwidths of the ports (H-ports) in the mm-Wave antenna array for the horizontal polarization (H-pol.) range from 27.36 GHz to 28.46 GHz and from 36.64 GHz to 41.71 GHz, respectively. In other words, the two popular 5G mm-Wave bands of n261 (27.5-28.35 GHz) and n260 (37.0-40.0 GHz) in the third generation partnership project (3GPP) therefore can be accommodated. The maximum (max.) V-pol. peak realized gains in the low band (band n261) and high band (band n260) are 10.10 dBi and 11.21 dBi, and the max. scanning angles are both 45°. Similarly, the max. H-pol. peak realized gains in the low band and high band are 10.26 dBi and 10.57 dBi, and the max. scanning angles are 60° and 30°, respectively. The antenna array also can achieve right-hand and left-hand circular polarizations.
Large-scale implementation of standardized quantitative real-time PCR fecal source identification procedures in the Tillamook Bay Watershed

Fecal pollution management remains one of the biggest challenges for water quality authorities worldwide. Advanced fecal pollution source identification technologies are now available that can provide quantitative information from many animal groups. As public interest in these methodologies grows, it is vital to use standardized procedures with clearly defined data acceptance metrics and conduct field studies demonstrating the use of these techniques to help resolve real-world water quality challenges. Here we apply recently standardized human-associated qPCR methods with custom data acceptance metrics (HF183/BacR287 and HumM2), along with established procedures for ruminant (Rum2Bac), cattle (CowM2 and CowM3), canine (DG3 and DG37), and avian (GFD) fecal pollution sources to (i) demonstrate the feasibility of implementing standardized qPCR procedures in a large-scale field study, and (ii) characterize trends in fecal pollution sources in the research area. A total of 602 water samples were collected over a one-year period at 29 sites along the Trask, Kilchis, and Tillamook rivers and tributaries in the Tillamook Bay Watershed (OR, USA). Host-associated qPCR results were combined with high-resolution geographic information system (GIS) land use and general indicator bacteria (E. coli) measurements to elucidate water quality fecal pollution trends. Results demonstrate the feasibility of implementing standardized fecal source identification qPCR methods with established data acceptance metrics in a large-scale field study leading to new investigative leads suggesting that elevated E. coli levels may be linked to specific pollution sources and land use activities in the Tillamook Bay Watershed.
The clinical outcomes for chordomas in the cranial base and spine

Abstract Owing to the special growth pattern of chordomas and the limited treatment options currently available, the treatment of chordoma still remains difficult. In this study, we hope to further clarify the relationship between surgical treatment and radiotherapy of chordoma and disease progression. All patients with a primary histopathological diagnosis of clival or spinal chordomas recorded in our institution between 1976 and 2017 were examined. A total of 60 patients (location: skull base/clival, n = 24; vertebral column, n = 5; sacrum, n = 31) had a mean follow-up time of 7.7 years (range 12 months–35 years). Compared with patients who received subtotal resection (n = 5, 5-year and 10-year survival = 61% and 39%, respectively), the annual survival rate of patients who received total resection (n = 55, 5-year and 10-year survival = 67%, respectively) was significantly higher. The overall 10-year survival rate (58%) of patients treated with surgery alone was significantly different from those treated with a combination of surgery and radiation (73%). The long-term prognosis of sacral chordoma was the worst (10-year survival rate = 48%). The best treatment strategy for improved long-term survival in chordoma was a combination of surgical resection and radiation therapy. Adjuvant radiotherapy for chordoma significantly improves disease-free survival, although the long-term survival benefit remains to be determined. A worse prognosis and poor long-term survival are seen in sacral chordomas.
Superdirective and Broadband Compact Antenna Array Using Non-Foster Elements

Performance characteristics of passive electrically small antennas are limited by fundamental physics. Using active elements into antenna structures appears like an opportunity to overshoot those limits. Non-Foster elements are classically used in matching networks for electrically small antennas in order to increase their impedance matching bandwidth. In this paper, Non-Foster elements are proposed as innovative method to achieve a broadband high directive and compact two-dipole array at 1.2 GHz. This implementation achieves a high directivity within 20% bandwidth.
Design of a Compact Monopole On-Chip Antenna for 24 GHz Automotive Radar Application

This article demonstrates the design of a miniaturized, ultra-wideband monopole on-chip antenna for automotive radar application. The proposed antenna achieves significant impedance bandwidth of 28.4 GHz (S11< -10 dB from 8.3 GHz to 36.7 GHz) with centre frequency of 24 GHz. It achieves minimum return loss of around -32 dB at 24 GHz that clearly indicates good impedance matching of the antenna with the source. The proposed antenna offers peak gain of -3 dBi at 28 GHz. Compactness (size of 3.8 mm × 4 mm × 0.676 mm) and simple design layout is the main attractiveness of this research work. The 3D antenna structure has been analyzed using ANSYS HFSS v17. Silicon wafer with thickness of 675 µm is used as a substrate of the proposed antenna.
LTE Cell Traffic Grow and Congestion Forecasting

Recent popularity grow of predictive analysis is growing in many fields. Importance to forecast mobile traffic for each LTE cell can bring mobile network planning advantages for the operator. It can help operators to spend minimum investing for new sites and cells but be able to guarantee excellent service experience for mobile broadband users. In this paper study of mobile traffic forecasting feasibility using fbProphet algorithm developed by Facebook is presented. Target is to have short term forecasting from which the operator can proactively consider network expansion if the load is too high to satisfy user throughput demands. Five months of daily traffic data used to train model and one month used for forecasting and model testing. Also, 30 days of hourly data were used for busy hour traffic forecasting. In the last part relation between data traffic carried in the LTE cell to cell load explained.
Adaptive Influence Blocking: Minimizing the Negative Spread by Observation-Based Policies

Spread of negative influence (N-Inf) in a networked system seems to be inevitable, e.g., epidemic spread in human networks, rumors in an online social network and computer virus plaguing the Internet etc. The widespread of N-Inf might cause severe damage and hence the Influence Blocking (IB) problem is attracting ample research interest. The IB problem aims at minimizing the N-Inf spread by immunization, i.e. selecting k (budget size) immunization nodes (Imm-nodes) to prevent the N-Inf from spreading. However, existing works for IB problem are all formulated as a one-shot task: selecting all the k Imm-nodes at the very beginning of N-Inf spread. In real world, unforeseen events might occur and one-shot policies will lack reserved measures to handle these situations. A more reasonable policy is to adaptively invest the budget based on the observation of N-Inf spread along as the time goes by. With the adaptive policy, we can both reserve resources for handling unforeseen events and save unnecessary costs if the spread of N-Inf dies out quickly. Motivated by the above considerations, we propose a novel Adaptive Influence Blocking (AIB) problem. Given the intermediate observations of N-Inf spread, the AIB problem aims at selecting Imm-nodes adaptively. We design a k-R (k-nodes-per-Round) policy which selects k Imm-nodes for each round until the budget is exhausted, and an α-T (α-Tolerance) policy which selects a new Imm-node if the expected N-Inf spread exceeds a threshold α. Scalable algorithms with provable approximation guarantees and error bounds are implemented for these policies and significant improvements on time complexity are achieved. Experimental results on real-world datasets demonstrate the effectiveness and scalability of the proposed methods.
A Compact Dual-Frequency Base-Station Dipole Array with AMC Reflector

A compact dual-frequency dipole array is presented for use in base stations operating in the Digital Cellular System (DCS) and Wideband Code Division Multiple Access (WCDMA) bands. The size-miniaturization is realized by utilizing band notch dipole (BND) as array element and artificial magnetic conductor (AMC) as array reflector for reductions in array width and profile height, respectively. Simulation results show that good impedance matching, high antenna isolation, and good radiation performances are achieved simultaneously.
Testing Android Incoming Calls

Mobile applications are increasingly present in our daily lives. Being increasingly dependent on apps, we all want to make sure apps work as expected. One way to increase confidence and quality of software is through testing. However, the existing approaches and tools still do not provide sufficient solutions for testing mobile apps with features different from the ones found in desktop or web applications. In particular, there are guidelines that mobile developers should follow and that may be tested automatically but, as far as we know, there are no tools that are able do it. The iMPAcT tool combines exploration, reverse engineering and testing to check if mobile apps follow best practices to implement specific behavior called UI Patterns. Examples of UI Patterns within this catalog are: orientation, background-foreground, side drawer, tab-scroll, among others. For each of these behaviors (UI Patterns), the iMPAcT tool has a corresponding Test Pattern that checks if the UI Pattern implementation follows the guidelines. This paper presents an extension to iMPAcT tool. It enables to test if Android apps work properly after receiving an incoming call, i.e., if the state of the screen after the call is the same as before getting the call. It formalizes the problem, describes the overall approach, describes the architecture of the tool and reports an experiment performed over 61 public mobile apps.