Miracle-dz/UniFAR-FTUs huggingface dataset:
Link Failure Detection and Alternate Path Tracing in OpenFlow Based Ethernet Networks

Software defined networking technology, centralizes and simplifies the control of network with centralized network provisioning and guaranteed content delivery. The conventional networks face link failure as its one of the major vulnerabilities that occurs within the networking topology. The paper proposes a technique to handle multiple link failure using Bidirectional Forwarding Detection(BFD). The one or more link failures occur due to slow convergence, pre-defined backup bandwidth, and loops resulting in degradation of the network performance. Widely, these failures cause paths that are not valid and reachable within wired networks. The length of every path containing an unsuccessful link is recorded and the total invalid routing time is computed. The out of reach paths record the overall range of paths that are unsuccessful during network partitioning. The multiple link failures are handled using multiple BFD sessions that are maintained by transmitting hello messages within the network. The corresponding neighbour nodes can have synchronized clock to detect failures at the same time.
Energy Storage as a Non-Wires Alternative for Deferring Distribution Capacity Investments

There is growing interest in Energy Storage Systems (ESS) and other distributed energy resources (DER) as non-wires alternatives to resolve distribution issues while also providing valuable services to the grid and to energy customers. One such use is to defer distribution capacity investments required due to load and/or DER growth. Selecting ESS power and energy ratings for capacity deferral requires time-series load profile data. This paper is a part of a longer-term objective of making it easy for utilities to consider energy storage systems within distribution planning. This paper proposes a practical planning-based approach to screen ESS (both power and energy ratings) to defer distribution capacity investments. More specifically, an approach is presented here that leverages linear power flow approximation to quickly perform many time-series ESS dispatch simulations enabling rapid ESS project screening for a large number of distribution feeders. This paper also illustrates intuitive ways to visualize optimal ESS power and energy ratings for different peak clipping objectives. The proposed ESS project screening approach is demonstrated on a real Hydro One distribution feeder.
Features of Invariant Extended Kalman Filter Applied to Unmanned Aerial Vehicle Navigation

This research used an invariant extended Kalman filter (IEKF) for the navigation of an unmanned aerial vehicle (UAV), and compared the properties and performance of this IEKF with those of an open-source navigation method based on an extended Kalman filter (EKF). The IEKF is a fairly new variant of the EKF, and its properties have been verified theoretically and through simulations and experiments. This study investigated its performance using a practical implementation and examined its distinctive features compared to the previous EKF-based approach. The test used two different types of UAVs: rotary wing and fixed wing. The method uses sensor measurements of the location and velocity from a GPS receiver; the acceleration, angular rate, and magnetic field from a microelectromechanical system-attitude heading reference system (MEMS-AHRS); and the altitude from a barometric sensor. Through flight tests, the estimated state variables and internal parameters such as the Kalman gain, state error covariance, and measurement innovation for the IEKF method and EKF-based method were compared. The estimated states and internal parameters showed that the IEKF method was more stable and convergent than the EKF-based method, although the estimated locations, velocities, and altitudes of the two methods were comparable.
An Ensemble SSL Algorithm for Efficient Chest X-Ray Image Classification

A critical component in the computer-aided medical diagnosis of digital chest X-rays is the automatic detection of lung abnormalities, since the effective identification at an initial stage constitutes a significant and crucial factor in patient’s treatment. The vigorous advances in computer and digital technologies have ultimately led to the development of large repositories of labeled and unlabeled images. Due to the effort and expense involved in labeling data, training datasets are of a limited size, while in contrast, electronic medical record systems contain a significant number of unlabeled images. Semi-supervised learning algorithms have become a hot topic of research as an alternative to traditional classification methods, exploiting the explicit classification information of labeled data with the knowledge hidden in the unlabeled data for building powerful and effective classifiers. In the present work, we evaluate the performance of an ensemble semi-supervised learning algorithm for the classification of chest X-rays of tuberculosis. The efficacy of the presented algorithm is demonstrated by several experiments and confirmed by the statistical nonparametric tests, illustrating that reliable and robust prediction models could be developed utilizing a few labeled and many unlabeled data.
Trends and Predictors of Palliative Care Referrals in Patients With Acute Heart Failure

Objective: To determine the rate and predictors of palliative care referral (PCR) in hospitalized patients with acute heart failure (AHF). Introduction: The PCR is commonly utilized in terminal conditions such as metastatic cancers. There is no data on trends and predictors from large-scale registry of general population regarding PCR in patients with AHF. Methods: For this retrospective study, data were obtained from National Inpatient Sample Database from 2010 to 2014. We used International Classification of Diseases, Ninth Revision diagnosis codes to identify cases with a principle diagnosis of AHF. These patients were divided into 2 groups: (1) PCR, (2) no PCR groups. We performed multivariate analysis to identify predictors of PCRs, as well as reported PCR trends from 2010 to 2014. Results: From the database, out of 37 312 324 hospitalizations, 621 947 unweighted cases with primary diagnosis of AHF were selected for further analysis. About 2.8% received PCR. From 2010 to 2014, there was an uptrend from 2.0% to 3.6% for PCR. Metastatic cancer, ventilator-dependent respiratory failure, and cardiogenic shock were strongly associated with PCR. Those who underwent percutaneous coronary intervention and African American or other races were negative predictors for PCR. In the PCR group, 31.4% of patients died during hospitalization. Conclusion: Palliative care referrals were made in a very small proportion of patients with AHF. We observed steady rise in the PCR utilization. Chronic conditions, advancing age, and high-risk patients were major predictors of PCR.
Analytical and Experimental Analysis for Position Optimization of a Grasp Assistance Supernumerary Robotic Hand

The reduction of muscular strength in elderly people and patients with neurological movement disorders drastically reduces the hand autonomy for performing several daily activities. This letter presents preliminary results towards a novel supernumerary hand system, i.e., the SoftHand X, that aims to augment the grasping capabilities of people with reduced hand functionalities. The system consists of an active soft robotic hand and a passive gravity compensation mechanism. A primary issue in the design of this supernumerary limb is its placement with respect to the user's arm, due to its profound effects in terms of expected kinematics and dynamics. This letter addresses this problem with a detailed analysis based on theoretical performance indexes and experimental proofs. Starting from 16 different positions, 2 optimal positions are found with multivariate optimization and then they are experimentally evaluated by 11 healthy subjects performing standard clinical tests. Both analytical and experimental results identify these two positions as the closest to those of the human hand, assumed as the optimum. Finally, a questionnaire and subjects’ suggestion reveal one of them strongly favorite.
Phase-Shifterless Power Controlled Combining Based on 20-kW S-Band Magnetrons With an Asymmetric Injection

A real-time phase-shifterless power controlled combining based on 20-kW S-band continuous-wave magnetrons with an asymmetric injection was proposed in this letter. A high-power-capacity combiner was designed, and the behaviors of the asymmetric injection magnetrons were qualitatively characterized. The system showed a nearly 3-MHz injection-locked bandwidth and an output power control range over 3 dB at an injection ratio of 0.07. An excellent spur suppression ratio of −65.0 dBc at 500 kHz, an output amplitude stability of 0.02 dB (peak to peak), and a phase stability of ±0.9° (peak to peak) were also demonstrated. To the best of our knowledge, the power output of 34.0 kW with a total combining efficiency of 86.7% sets a new performance record for an S-band continuous wave magnetron power combining system, which is one of the best spur suppressions among all reported S-band injection locked magnetrons with an output power of over 15 kW.
Knowledge translation and process improvement interventions increased pain assessment documentation in a large quaternary paediatric post-anaesthesia care unit

Background Due to inadequate pain assessment documentation in our paediatric post-anaesthetic care unit (PACU), we were unable to monitor pain intensity, and target factors contributing to moderate and severe postoperative pain in children. The purpose of this study was to improve pain assessment documentation in PACU through a process improvement intervention and knowledge translation (KT) strategy. The study was set in a PACU within a large university affiliated paediatric hospital. Participants included PACU and Acute Pain Service nursing staff, administrative staff and anaesthesiologists. Methods The Plan–Do–Study-Act method of quality improvement was used. Benchmark data were obtained by chart review of 99 patient medical records prior to interventions. Data included pain assessment documentation (pain intensity score, use of validated pain intensity measure) during PACU stay. Repeat chart audit took place at 4, 5 and 6 months after the intervention. Intervention Key informant interviews were conducted to identify barriers to pain assessment documentation. A process improvement was implemented whereby the PACU flowsheets were modified to facilitate pain assessment documentation. KT strategy was implemented to increase awareness of pain assessment documentation and to provide the knowledge, skill and judgement to support this practice. The KT strategy was directed at PACU nursing staff and comprised education outreach (educational meetings for PACU nurses, discussions at daily huddles), reminders (screensavers, bedside posters, email reminders) and feedback of audit results. Results The proportion of charts that included at least one documented pain assessment was 69%. After intervention, pain assessment documentation increased to >90% at 4 and 5 months, respectively, and to 100% after 6 months. Conclusion After implementing process improvement and KT interventions, pain assessment documentation improved. Additional work is needed in several key areas, specifically monitoring moderate to severe pain, in order to target factors contributing to significant postoperative pain in children.
Characterization and proteomic profiling of pancreatic cancer‐derived serum exosomes

Pancreatic cancer (PC) is one of the most lethal cancers known worldwide, and its prognosis is poor in most patients. Exosomes are nanosized extracellular vesicles, which are released from various cell types. They are involved in cellular communication. The diagnosis and treatment of PC were improved substantially with exosomes. In this study, we isolated PC‐derived exosomes and investigated their proteomic profile. Then, we conducted bioinformatic analysis on proteomic data. Differential ultracentrifugation was performed to isolate exosomes from human serum samples and four PC cell lines. Transmission electron microscopy and Western blot analysis were used to characterize the isolated exosomes. Liquid chromatography coupled with tandem mass spectrometry was conducted to identify the proteome of serum exosomes. Proteomic analysis demonstrated that all the serum exosomes were derived from three cohorts of human subjects; these serum exosomes contained a total of 655 proteins, out of which 315 proteins overlapped with ExoCarta database. Gene oncology and kyoto encyclopedia of genes and genomes analyses provided the functional annotation of the proteome. Interestingly, 18 or 14 proteins were upregulated and 11 or 14 proteins were downregulated in serum exosomes derived from patients with PC as compared with in serum exosomes derived from healthy volunteers or from pancreatitis patients respectively. Annexin A11, a calcium‐dependent phospholipid‐binding protein, was expressed in a PC cell line (CFPAC‐1)‐derived exosomes and in tumor tissues of patients with PC, respectively. Our data provided a basic foundation for further studies on the protein composition of PC‐derived exosomes and its involvement in PC biology.
Separation and determination of alpha‐synuclein monomeric and oligomeric species using two electrophoretic approaches

Parkinson's disease (PD) is a frequent degenerative disorder that is diagnosed based on clinical symptoms. When the first symptoms appear, more than 70% of the dopaminergic cells are already lost. Therefore, it is of utmost importance to have reliable biomarkers to diagnose much earlier PD. In this context, alpha‐synuclein (aSyn) is a protein of high interest because of its tendency to form oligomers and amyloid fibrils. The oligomeric forms seem to play a critical pathological role in PD. To date, most of studies aiming at detecting and quantifying aSyn oligomers were performed by immunoassays, mainly by ELISA using specific antibodies. In this study a capillary gel electrophoresis (CGE) coupled with fluorescence detection method was developed to detect and quantify the oligomeric forms of aSyn formed in vitro. All the results obtained were supported by SDS–PAGE analysis, a widely used and well‐known technique but exhibiting a main drawback since it is not an automated technique. The repeatability and the intermediate precision of the method were evaluated, as well as the stability of the labeled and non‐labeled aSyn samples. After careful screening and optimization of various labeling reagents, 4‐fluoro‐7‐nitrobenzofurazan (NBD‐F) was selected and used to establish a calibration curve with monomeric fluorescently‐labeled aSyn. Finally, the method was used to study the effect of doxycycline on the oligomerization process. Altogether, our results show that CGE is a very promising automated technique to analyze aSyn monomers, as well as small oligomers.
Wearable Microstrip Patch Ultra Wide Band Antenna for Breast Cancer Detection

This paper illustrates a novel design for a wearable microstrip patch ultra-wide band (UWB) antenna with improved bandwidth design to be used in breast cancer detection. The operating frequency of the proposed antenna ranges from 1.6 GHz to 11.2 GHz. The antenna consists of a rectangular radiating patch fed by a rectangular feed line. This antenna design will be part of a wearable device for women to detect breast cancer early. To support wearable property, 100% cotton has been utilized as the substrate with dielectric constant 1.6, while the transmitting component patch and ground planes are composed of copper as the conductive material. The analysis of the antenna and breast models was carried out using CST Microwave Studio. Simulated results in terms of return loss, bandwidth, radiation pattern, and gain and efficiency are presented to validate the usefulness of the proposed design, and different bending conditions are presented.
Soft-WSN: Software-Defined WSN Management System for IoT Applications

In this paper, we propose a software-defined wireless sensor network architecture (Soft-WSN )—an effort to support application-aware service provisioning in Internet of Things (IoT). Detailed architecture of the proposed system is presented involving the application, control, and infrastructure layers to enable software-defined networking (SDN) in IoT. We design a software-defined controller, which includes two management policies—device management and network management. Device management facilitates users to control their devices in the network. To enable device control mechanisms, we investigate three scheduling issues in a sensor node—sensing task, sensing delay, and active sleep. On the other hand, the topology of the network is controlled by the network management policies, which can be modified in run time to deal with dynamic requirements of IoT. Furthermore, the proposed scheme is implemented in a real hardware platform without changing the underlying sensor networking concepts, so that existing sensor devices can be seamlessly integrated. Therefore, in contrast to the existing SDN solutions for WSNs, the proposed system, Soft-WSN, focuses on both device management and topology management to meet run-time application-specific requirements of IoT, while enhancing flexibility and simplicity of WSN management. Experimental results on a real hardware-based test bed indicate that the proposed scheme is beneficial to meet real-time application-specific requirements of IoT, while ensuring significant improvements on network performance over the traditional approaches.
Planetary Gear Fault Detection Based on Mechanical Torque and Stator Current Signatures of a Wound Rotor Induction Generator

In this paper, an approach for tooth localized fault detection in the sun gear of a planetary gear, using the measured mechanical torque and the stator current of a wound rotor induction generator (WRIG), is proposed. A theoretical background is developed to demonstrate that the faulty sun gear produces periodic fault signatures in the mechanical torque and consequently fault-related frequencies in the stator current of the WRIG. The employed technique needs knowledge of mechanical system torsional natural frequencies, which aid in identifying the most sensitive fault characteristic harmonics in both mechanical torque and stator current spectra. It is illustrated by simulation and experimental results that the amplitude of these harmonics can be used as a fault index for diagnosis of tooth localized defect in planetary gears. A test rig based on a 5.5 kW WRIG, shaft connected to the sun gear of a planetary gear through a high-speed shaft and couplings, was utilized for validation of the proposed technique.
Energy Management for an Islanded Microgrid Based on Harmony Search Algorithm

Microgrids are the latest solution used for increasing the self-sustainability and reliability of future electrical distribution grids. This paper presents an overview of an islanded microgrid that features three renewable energy resources, an energy storage system and loads. Ensuring an appropriate energy management for the microgrids is a challenging issue. Different approaches exist, but this paper solves the day-ahead scheduling problem using the Harmony Search Optimization Algorithm. The optimal operation of the solar, geothermal and biomass units are calculated considering the minimum functional cost of the system. The results are presented through a Graphical User Interface (GUI). A comparison between energy management solutions, proposed by the Harmony Search (HS) Optimization Algorithm and the Mixed Integer Linear Programming (MILP) method, is also available. The presented results can be valuable for other researchers in this field.
A review of the complexity adjustment in the Korean Diagnosis-Related Group (KDRG)

Background: The Korean Diagnosis-Related Groups (KDRG) was revised in 2003, modifying the complexity adjustment mechanism of the Australian Refined Diagnosis-Related Groups (AR-DRGs). In 2014, the Complication and Comorbidity Level (CCL) of the existing AR-DRG system was found to have very little correlation with cost. Objective: Based on the Australian experience, the CCL for KDRG version 3.4 was reviewed. Method: Inpatient claim data for 2011 were used in this study. About 5,731,551 episodes, which had one or no complication and comorbidity (CC) and met the inclusion criteria, were selected. The differences of average hospital charges by the CCL were analysed in each Adjacent Diagnosis-Related Group (ADRG) using analysis of variance followed by Duncan’s test. The patterns of differences were presented with R 2 in three patterns: The CCL reflected the complexity well (VALID); the average charge of CCL 2, 3, 4 was greater than CCL 0 (PARTIALLY VALID); the CCL did not reflect the complexity (NOT VALID). Results: A total of 114 (19.03%), 190 (31.72%) and 295 (49.25%) ADRGs were included in VALID, PARTIALLY VALID and NOT VALID, respectively. The average R 2 for hospital charge of CCL was 4.94%. The average R 2 in VALID, PARTIALLY VALID and NOT VALID was 4.54%, 5.21%, and 4.93%, respectively. Conclusion: The CCL, the first step of complexity adjustment using secondary diagnoses, exhibited low performance. If highly accurate coding data and cost data become available, the performance of secondary diagnosis as a variable to reflect the case complexity should be re-evaluated. Implications: Lack of reviewing the complexity adjustment mechanism of the KDRG since 2003 has resulted in outdated CC lists and levels that no longer reflect the current Korean healthcare system. Reliable cost data (vs. charge) and accurate coding are essential for accuracy of reimbursement.
Performance Enhancement of SPR Biosensor Based on Phosphorene and Transition Metal Dichalcogenides for Sensing DNA Hybridization

Two-dimensional (2-D) materials have attracted a lot of attention for using in surface plasmon resonance (SPR) biosensors. High sensitivity and figure of merit are two desirable parameters in sensor performance analysis. Using heterostructures of phosphorene, graphene, and transition metal dichalcogenides is proposed to enhance the sensitivity of biosensor. Although the proposed biosensor can be used for detection of different analytes with a wide refractive index range, DNA hybridization is the sensing target in this paper. Sensing parameters of different biosensor configurations based on a few-layer black phosphorus (BP) and other 2-D materials are compared with the conventional Au-based SPR sensor and the highest sensitivity of 187°/RIU for the structure consists of 10-layer BP and monolayer WS2 is obtained. The suggested sensor structure provides the sensitivity more than two times of the conventional biosensor. This high sensor performance may have potential applications in medical diagnosis and biochemical detection.