Miracle-dz/UniFAR-FTUs huggingface dataset:
Long‐Term Behavior and Application Limits of Plasma‐Sprayed Zirconia Thermal Barrier Coatings

Investigations of changes in phase composition, mechanical properties, and microstructure of ZrO 2 -based plasma-sprayed thermal barrier coatings (TBCs) with 8 mol% CeO 2 , 19.5 mol% CeO 2 /1.5 mol% Y 2 O 3 , 35 mol% CeO 2 , and 4.5 mol% Y 2 O 3 after long-term heat treatments at typical operation temperatures (1000°-1400°C) are presented. Experimental studies include X-ray diffractometry, mechanical testing, and scanning electron microscopy. Thermal cycling experiments also have been performed. TBCs with 8 mol% CeO 2 contain mainly the tetragonal equilibrium phase and, therefore, show rapid failure because of the high amount of tetragonal → monoclinic phase transformation, even after relatively short heat treatments (1250°C/1h). In the case of the other systems that consist mainly of the tetragonal or cubic nonequilibrium phases, TBCs with 19.5 mol% CeO 2 /1.5 mol% Y 2 O 3 or 35 mol% CeO 2 reveal a smaller amount of monoclinic phase after long-term heat treatments (1250°C/1000h) compared with TBCs containing 4.5 mol% Y 2 O 3 . TBCs containing 35 mol% CeO 2 show a higher degree of sintering than the TBCs with 19.5 mol% CeO 2 /1.5 mol% Y 2 O 3 and, therefore, a greater increase of the elastic modulus. Among the systems investigated, TBCs containing 4.5 mol% Y 2 O 3 exhibit the highest resistance to failure in thermal-cycling experiments.
A Bayesian Approach for Interpolating Clear-Sky MODIS Land Surface Temperatures on Areas With Extensive Missing Data

The MODIS land surface temperature (LST) products contain large areas of missing data due to cloud contamination. Interpolating clear-sky equivalent LSTs on those areas is a first step in a stepwise approach toward fully recovering missing data. A previous study (viz. the Yu method) has implemented an effective clear-sky interpolation method, especially targeting large-area missing data. The Yu method postulates several global reference LST images that contain over 90% of valid pixels and that are assumed to have a close statistical relationship to the interpolated images. However, in practice, such reference images are rarely available throughout a one-year cycle, and the time gaps between the available reference images and the interpolated images are often huge, resulting in compromised interpolation accuracy. In this study, we intended to address those weaknesses and propose a novel clear-sky interpolation approach. The proposed approach uses multiple temporally proximate images as reference images, with which multiple initial estimates are made by an empirically orthogonal function method and then fused by a Bayesian approach to achieve a best estimate. The proposed approach was compared through two experiments to the Yu method and two other widely used methods, i.e., harmonic analysis of time series and co-kriging. Both experiments demonstrate the superiority of the proposed approach over those established methods, as evidenced by higher spatial correlation coefficients (0.90–0.94) and lower root-mean-square errors (1.19–3.64 °C) it achieved when measured against the original data that were intentionally removed.
Isolation and characterization of unrecorded yeasts species in the family Metschnikowiaceae and Bulleribasidiaceae in Korea

In 2019, we isolated unrecorded yeasts from soil collected in Pocheon city, Korea. The identified yeasts belong to the family Metschnikowiaceae and Bulleribasidiaceae. This study focusses on the isolation and description of unrecorded species in the genera Kodamaea and Hannaella. The genus Kodamaea contains ascomycetous yeast in the family Metschnikowiaceae, the order Saccharomycetales, the subphylum Saccharomycotina, the phylum Ascomycota. The Kodamaea clade consists of 23 recognized species and has K. ohmeri as the type species. The Kodamaea clade is closely related to the genera Clavispora and Metschnikowia (Lachance and Kurtzman, 2011). Species in the clade Kodamaea have been isolated from various sources such as mushrooms, ephemeral flowers, insects (Freitas et al., 2013) and rotting wood (Gao et al., 2017). The members of genus Kodamaea are fermentative and form coenzyme Q-9 and hyphae. The genus Hannaella contains basidiomycetous yeast in the family Bulleribasidiaceae, the order Tremellales, the subphylum Agaricomycotina, the phylum Basidiomycota. The genus Hannaella consists of 11 recognized species and has H. sinensis as the type species. The genus Hannaella is closely related to the genera Dioszegia and Derxomyces and was proposed to accommodate seven species that were transferred from the Bullera sinensis clade: H. coprosmaensis, H. kunmingensis, H. luteola, H. oryzae, H. sinensis, H. surugaensis and H. zeae (Wang & Bai, 2008). Species in the genus Hannaella have been isolated from various sources such as soil (Landell et al., 2014), plants (Surussawadee et al., 2015; Kaewwichian et al., 2015) and water (Han et al., 2017). The members of the genus Hannaella are not fermentative and form coenzyme Q-10 and hyphae. This study focuses on the description of four yeast species belonging to genera Kodamaea and Hannaella that have not officially been reported in Korea.
Proposal for a Maturity Model in Sustainability in the Supply Chain

Sustainability has become a relevant element for organizations due to several motivators: companies adopt sustainability practices in need for regulatory compliance, anticipation of regulatory changes, understanding of limited natural resources, and a desire to limit expenditure associated with resource consumption and waste disposal. Thus, this article aims to identify the gaps present in maturity models, present an integrator theoretical model that considers the characteristic elements of the models present in the literature and affects the level of maturity in sustainability. The construction of the integrator theoretical model was based on the following stages: research questions; theoretical framework on Supply Chain Management; sustainability and concept of maturity model; maturity models and performance measurement systems; interpretation/analysis of research; and construction of the integrator theoretical model. The literature review was carried out in the Scopus and Web of Science databases. The main conclusions: maturity models focus on only one aspect or are excessively broad and do not include in detail the elements necessary to measure the level of maturity in sustainability. The proposed model aims to mitigate these gaps with the addition of the cross-sectional dimension, which offers an integrated and holistic view in relation to the other dimensions.
Knowledge Representation Using Decision Trees Constructed Based on Binary Splits

It is tremendously important to construct decision trees to use as a tool for knowledge representation from a given decision table. However, the usual algorithms may split the decision table based on each value, which is not efficient for numerical attributes. The methodology of this paper is to split the given decision table into binary groups as like the CART algorithm, that uses binary split to work for both categorical and numerical attributes. The difference is that it uses split for each attribute established by the directed acyclic graph in a dynamic programming fashion whereas, the CART uses binary split among all considered attributes in a greedy fashion. The aim of this paper is to study the effect of binary splits in comparison with each value splits when building the decision trees. Such effect can be studied by comparing the number of nodes, local and global misclassification rate among the constructed decision trees based on three proposed algorithms.
A study to assess the socio demographic profile of anganwadi children in Trivandram district, Kerala, India

Aim: To assess the socio demographic profile of anganwadi children in Trivandrum district, Kerala, India. Sample: Ninety children attending the anganwadi centers in the age group of two to six years were studied. Study Design: A random study was done to assess the socio demographic profile of children (2-6 years) attending anganwadi centers in the Urban 2 project areas of Trivandrum district, Kerala. Children were selected randomly from sector 1 and sector 4. Data collected were compared with the standard values to find the disparities. Locale of study: Sectors I and IV in the Urban II project areas of Trivandrum district in Kerala was randomly selected for study. Methodology: In order to achieve the objectives, socio demographic variables of the respondents namely age, religion, caste, ordinal position, education and occupation of parents, monthly incomes, house condition etc. were collected using pretested questionnaire. Results: A sizeable portion of male child (35.00%) were under the age category of 24-36 months and female child in age group of both 37-48 months and 49-60 months (34.00%). Birth weight of children were collected from their mothers and found that 11.6% of male children and 13% of female children in the study population were having a lower birth weight i.e. less than 2500gm. Majority of children (48.88%) were from the families having a monthly income of less than or equal to 20,000. Conclusion: Children with their birth weight less than 2500gram need to be cared and should carefully note there anthropometric measurements. Since they are more prone to malnutrition, illness etc. throughout their life cycle. More than half (58.90%) of the mothers of the children were graduate and a large percent of mothers were not working. Children from low income group need special attention since they may be deprived from nutrient rich foods.
The updated DESGW processing pipeline for the third LIGO/VIRGO observing run

The DESGW group seeks to identify electromagnetic counterparts of gravitational wave events seen by the LIGO-VIRGO network, such as those expected from binary neutron star mergers or neutron star-black hole mergers. DESGW was active throughout the first two LIGO observing seasons, following up several binary black hole mergers and the first binary neutron star merger, GW170817. This work describes the modifications to the observing strategy generation and image processing pipeline between the second (ending in August 2017) and third (beginning in April 2019) LIGO observing seasons. The modifications include a more robust observing strategy generator, further parallelization of the image reduction software and difference imaging processing pipeline, data transfer streamlining, and a web page listing identified counterpart candidates that updates in real time. Taken together, the additional parallelization steps enable the identification of potential electromagnetic counterparts within fully calibrated search images in less than one hour, compared to the 3-5 hours it would typically take during the first two seasons. These performance improvements are critical to the entire EM follow-up community, as rapid identification (or rejection) of candidates enables detailed and rapid spectroscopic follow-up by multiple instruments, leading to more information about the environment immediately following such gravitational wave events.
Distributed Conditions for Small-Signal Stability of Power Grids and Local Control Design

Operating modern power grids with stability guarantees is markedly important. Typical methods for analyzing and certifying power grid stability are largely centralized relying on the ability of the system operator to gather network-wide information and accurately compute the system's eigenvalues. These methods are oftentimes not privacy-preserving and computationally burdensome. They are therefore, not well-suited to modern power grids where small-signal stability has to be evaluated timely, efficiently and in a privacy-preserving fashion. In this paper, we introduce a distributed methodology for certifying small-signal stability of power grids and designing the local controllers. First, we analytically derive distributed conditions for network-wide stability that bus agents can inspect using local information. By leveraging these conditions, we then introduce a distributed control design algorithm (DCDA) that can guide the local control design so that stability of the interconnected system is guaranteed. The agents that adopt the proposed distributed algorithm are responsible for tuning their local controllers, producing their local control commands and ensuring that their local stability condition is met. The system operator is only responsible for verifying network-wide stability upon receiving affirmative responses from all agents and, announcing, that the overall system is stable. The proposed DCDA algorithm is numerically validated via simulations using the IEEE 39-bus system.
Endpoints and Interdependencies in Internet of Things Residual Artifacts: Measurements, Analyses, and Insights into Defenses

The usage of Internet of Things (IoT) devices is growing fast. Moreover, the lack of security measures among the IoT devices and their persistent online connection give adversaries an opportunity to exploit them for multiple types of attacks, such as distributed denial-of-service (DDoS). To understand the risks of IoT devices, we analyze IoT malware from an endpoint standpoint. We investigate the relationship between endpoints infected and attacked by IoT malware, and gain insights into the underlying dynamics in the malware ecosystem. We observe the affinities and different patterns among endpoints. Towards this, we reverse-engineer 2,423 IoT malware samples and extract IP addresses from them. We further gather information about these endpoints from Internet-wide scans. For masked IP addresses, we examine their network distribution, with networks accumulating more than 100 million endpoints. Moreover, we conduct a network penetration analysis, leveraging information such as active ports, vulnerabilities, and organizations. We discover the possibility of ports being an entry point of attack and observe the low presence of vulnerable services in dropzones. Our analysis shows the tolerance of organizations towards endpoints with malicious intent. To understand the dependencies among malware, we highlight dropzone characteristics including spatial, network, and organizational affinities. Towards the analysis of dropzones’ interdependencies and dynamics, we identify dropzones chains. In particular, we identify 56 unique chains, which unveil coordination among different malware families. Our further analysis of chains suggests a centrality-based defense and monitoring mechanism to limit malware propagation. Finally, we propose a defense based on the observed measures, such as the blocked/blacklisted IP addresses or ports. In particular, we investigate network-level and countrylevel defenses, by blocking a list of ports that are not commonly used by benign applications, and study the underlying issues and possible solutions of such a defense.
Cathodic stripping voltammetric determination of ceftazidime in urine at a hanging mercury drop electrode

Abstract A method was developed for the differential-pulse cathodic stripping voltammetric determination of ceftazidime with a hanging mercury drop electrode using its reduction peak at −0.43 V in Britton–Robinson buffer pH 4.0. The optimum accumulation potential and time were −0.15 V and up to 60 s, respectively. Linear calibration graphs were obtained from 1 × 10 −8 M and 1.5 × 10 −7 M. The limit of determination was calculated to be 5 × 10 −9 M. The coefficient of variation was 4% ( n = 7) at 1 × 10 −7 M ceftazidime. The effect of various components of urine on the voltammetric response was studied, and creatinine, uric acid, urea, and glucose were shown to interfere in the method. Ceftazidime bound to human albumin gives a unique stripping peak at −0.48 V. Recoveries of 87% ± 2% of the ceftazidime ( n = 5) were obtained from urine spiked with 1.27 μg ml −1 using C-18 solid phase extraction cartridges.
A simple repair method of fatigue cracks using stop-holes reinforced with wedge members

ABSTRACT A simple method of repairing fatigue cracks using stop-holes reinforced with wedge members has been newly proposed. By using this method, the stress range at the stop-hole edge is expected to be drastically reduced by the wedge load effect of the wedge member. The chief advantages of this method are that the repair work can be easily performed from only one side of a cracked structure and that the wedge member can be set so adaptive as to maintain the wedge load automatically and effectively even after the structure around the stop-hole is subjected to some excessive tensile loads and the stop-hole is plastically deformed. Speciﬁcally, slope-type wedge members have been newly designed and optimized, and an adaptive mechanism of the wedge member has been devised using a pulley, a string and a weight. Static loading tests and fatigue tests were performed on a steel plate specimen with a slit and a drill hole, and validity of the above repair method was experimentally examined using both of simple and adaptive wedge members. FE analyses using contact elements were also carried out for a comparative study. As a result, it was found that the stress range at the stop-hole edge is reduced by more than 60 % and the fatigue life is prolonged more than 20-fold by application of the adaptive wedge member as compared with those in the case of the conventional stop-hole. It was also shown that application of the simple wedge member is limitedly effective when the wedge part is held on the specimen and the applied load range is lower than a certain level.
THE ECG SIGNAL CLASSIFICATION BASED ON ENSEMBLE LEARNING OF PSO-ELM ALGORITHM

: ECG anomaly detection plays an important role in clinical medicine. So far, a number of ECG recognition technologies have emerged in this ﬁeld, but most often suﬀer from slow training and instability. Considering that the Extreme Learning Machine (ELM) and Particle Swarm Optimization (PSO) algorithm have the advantages of fast learning speed and strong generalization ability, this paper integrates multiple independent PSO-ELM model and proposes a novel ensemble learning framework termed as E-PSO-ELM to realize ECG signals recognition. More speciﬁcally, the individual PSO-ELM adopts the input weight and hidden layer deviation of ELM as the particles in the PSO algorithm, and takes the root mean square error of ELM training sample as the adaptive value of the particles, so as to enhance the stability of the network and realize high ECG recognition rate. The simulation results on MIT-BIH Arrhythmia Database show that E-PSO-ELM has a high classiﬁcation accuracy rate of 98.23 %. In addition, compared with other algorithms, the stability of E-PSO-ELM is more prominent, which can reduce the probability of operating errors. Therefore, E-PSO-ELM has a high practical value.
Network Slicing for 5G with UE State Based Allocation and Blockchain Approach

5G communications technologies are the backbone of future communications systems in satisfying different heterogeneous requirements of the industry and consumer applications. These systems rely on standardized protocols and heterogeneous architectures to engineer massive scaling of communication devices. Network Slicing (NS) can be incorporated into 5G to cater to the ever increasing needs of smart communications, ranging from Enhanced Mobile Broadband (eMBB) to Ultra-Reliable Low Latency Communications (URLLC). In this article, we present the performance analysis of such a network using real-world deployment and testing scenarios with state based network slice allocation. To account for transparency and security, a Blockchain-based model is integrated within the network operations. In particular, we carefully account for the latency aware operations of Network Slicing along with its UE state based allocation by telecom providers using Blockchain. Furthermore, provisioning the Blockchain in the Network Slice allocations increases the transparency and efficiency of resource handling operations within the network.
Comparison and association of acute physiological and posturographic effects in four exercises on stable and unstable surfaces with or without partial blood flow restriction

Purpose. Prior research has shown that running squats on unstable surfaces may be useful in increasing antagonist muscle and body centre activity; nonetheless, the evidence for improved muscle strength-power is contradictory. In parallel, low-intensity strength training with partial blood flow restriction is effective in developing strength, hypertrophy, and muscular endurance. Combining both modalities could complement the benefits of exercising on unstable surface. Our objective was to compare the acute effects of 4 exercise types with or without partial blood flow restriction under stable and unstable conditions. Methods. Seven volunteers performed 4 protocols: exercises with high-intensity overload and stable conditions, low-intensity overload with blood flow restriction and stable conditions, unstable conditions without blood flow restriction, and unstable conditions with blood flow restriction. At the beginning, end, and recovery of each protocol, physiological variables were measured: heart rate, subjective perception of effort, blood lactate, and posturographic variables (total distance with eyes open and closed). Results. Exercises with stable surfaces generated greater physiological stress than both exercises on unstable surfaces. Furthermore, incorporating blood flow restriction into unstable exercise allowed an increase in the physiological demand without altering postural balance. There were only significant changes in postural balance in the high-intensity protocol with stable conditions. Conclusions. Exercises combining partial blood flow restriction on stable and unstable surfaces increase the physiological demands without altering postural balance compared with high-intensity exercise on a stable surface.
Can mirabegron facilitate ureteral access sheath placement during flexible ureterorenoscopy?

DOI: 10.4328/ACAM.20214 Received: 2020-06-02 Accepted: 2020-07-07 Published Online: 2020-07-18 Printed: 2020-11-01 Ann Clin Anal Med 2020;11(6):553-556 Corresponding Author: Murat Keske, Kayseri City Hospital, Department of Urology, Kocasinan, 38080 Kayseri, Turkey. E-mail: muratkeske@yahoo.co.uk P: +90 5426620882 Corresponding Author ORCID ID: https://orcid.org/0000-0001-6591-4506 Abstract Aim: In this study, we aimed to demonstrate the effect of mirabegron on ureteral access sheath (UAS) placement during flexible ureterorenoscopy (f-URS). Material and Methods: The study enrolled 96 patients with renal stones who underwent f-URS between October 2019 and March 2020. The patients were divided into 2 groups. Mirabegron treatment was administered 2 weeks before f-URS in Group 1 (n = 41), and no mirabegron treatment was given in Group 2 (n = 55). All operations were performed by a single surgeon (MK). Demographic characteristics were recorded for each patient, including age, body weight, height, body mass index (BMI), stone characteristics, and perioperative data, including operation-fluoroscopy durations, stone-free rates, complications, and surgery success rates. Group data were compared, and p-values less than 0.05 were considered statistically significant. Results: No significant difference was detected between the groups in terms of age, sex, body mass index, number and size of stones, side of stones, density of stones, and renal hydronephrosis level. UAS placement in Group 1 was found to be statistically significant at the first attempt (without using a semi-rigid ureteroscope or balloon dilatation) compared with Group 2 (p=0.001) Discussion: The use of mirabegron may facilitate UAS placement during f-URS with less operation time and fewer complications.