Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Airline Network Pricing

Airfares vary across the booking horizon according to intertemporal price discrimination and adjustment of fares in response to stochastic demand shocks. Previous works studying these economic forces abstract away from the ramifications of pricing an itinerary has on revenue and consumer welfare in a larger network containing itineraries subjected to common interconnected capacity constraints. I estimate a dynamic structural model of airline network pricing with a novel high frequency data set on flight prices and seat availability while relaxing the assumption of optimality. By a method of simulated moments, I resolve the classic econometric issues of endogeneity, censoring, and truncation in order to recover the airline’s beliefs on its stochastic demand process. I perform several counterfactual experiments to compare revenue and consumer welfare under several different pricing strategies and network configurations to elucidate the channels through which pricing externalities are transmitted in the network. I show that when the airline strategically prices itineraries jointly in their network according to a network-perfect pricing policy, it can increase revenue by a lower bound of 2.3% relative to the existing industry standard of network-oblivious pricing policies that independently set seemingly optimal prices for individual itineraries, a significant gain given the industry.
Nomogram Predict Overall Survival of Patients with Thymic Epithelial Tumors After Surgery

Background: Hematological indicators and clinical characteristics play an important role in the evaluation of the progression and prognosis of thymic epithelial tumors. Therefore, we aimed to combine these potential indicators to establish a prognostic nomogram to determine the overall survival (OS) of patients with thymic epithelial tumors undergoing thymectomy. Methods: This retrospective study was conducted on 167 patients who underwent thymectomy between May 2004 and August 2015. Cox regression analysis were performed to determine the potential indicators related to prognosis and combine these indicators to create a nomogram for visual prediction. The prognostic predictive ability of the nomogram was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, and risk stratification. Decision curve analysis was used to evaluate the net benefits of the model. Results: Preoperative albumin levels, neutrophil-to-lymphocyte ratio (NLR), T stage, and underlying diseases (with hypertension and/or diabetes) were included in the nomogram. In the training cohort, the nomogram showed a stronger prognostic predictive ability than the T staging (C index: 0.886 vs 0.725). Calibration curves for the overall survival (OS) were in good agreement with the standard lines in cohorts. The net benefit of the nomogram was higher than that of the T staging model. Conclusions: The nomogram showed better performance in predicting the prognosis and survival of this patient population than the T staging prediction model. And it has potential to identify high-risk patients at an early stage. This is a relatively novel approach for the prediction of OS in this patient population.
Statistical Indoor Exclusion Zone Analysis by Investigating Electromagnetic Fields inside a Nuclear Power Plant

This article investigates a statistical indoor exclusion zone (EZ) that can be efficiently applied to a nuclear power plant (NPP) by examining electromagnetic fields inside the actual NPP. To obtain the statistical indoor EZ, the indoor environment of the Korea Institute of Nuclear Safety (KINS) simulator room is modeled using the Wireless InSite commercial electromagnetic simulation software. The indoor space around the transmitting antenna is classified as multiple observation regions, and the EZ boundaries of each region are independently defined within each separate observation region. The EZ boundaries are then obtained using a margined regression model, which makes it possible to determine a reasonable boundary of the statistical indoor EZ. To validate the statistical indoor EZ, the received power inside the KINS simulator room is then measured, which agrees well with the simulated results. The results demonstrate that the proposed statistical indoor EZ can be properly obtained not only from the simulation data but also from the measurement data.
Design of the LCC-SP Topology With a Current Doubler for 11-kW Wireless Charging System of Electric Vehicles

In this article, an 11-kW wireless charging system based on the LCC-serial–parallel (SP) topology utilizing the power control of a current doubler is established. The circuit characteristics of the LCC-SP topology are analyzed. Furthermore, the equivalent quality factor is introduced to analyze the harmonic problem of the system. Meanwhile, the equivalent impedance of the current doubler is derived by Fourier decomposition. Then, the LCC-SP compensation parameters are modified according to the derived equivalent impedance. Considering the above harmonic problem, the system loss, and the equivalent impedance correction of the current doubler, an LCC-SP parameter design scheme is proposed. To ensure a constant power output at different horizontal offsets, the closed-loop controller is investigated by establishing the small-signal model of the current doubler. Finally, an 11-kW wireless charging prototype with power regulation capability is constructed, which verifies that the system can maintain an 11.014-kW output power and a 91.286% system efficiency even at the maximum horizontal offset.
Fast Preparation of High-Performance Wood Materials Assisted by Ultrasonic and Vacuum Impregnation

In the absence of high-quality hardwood timber resources, we have gradually turned our attention from natural forests to planted fast-growing forests. However, fast-growing tree timber in general has defects such as low wood density, loose texture, and poor mechanical properties. Therefore, improving the performance of wood through efficient and rapid technological processes and increasing the utilization of inferior wood is a good way to extend the use of wood. Densification of wood increases the strength of low-density wood and extends the range of applications for wood and wood-derived products. In this paper, the effects of ultrasonic and vacuum pretreatment on the properties of high-performance wood were explored by combining sonication, vacuum impregnation, chemical softening, and thermomechanical treatments to densify the wood; then, the changes in the chemical composition, microstructure, and mechanical properties of poplar wood before and after treatment were analyzed comparatively by FT-IR, XRD, SEM, and mechanical tests. The results showed that with ultrasonic pretreatment and vacuum impregnation, the compression ratio of high-performance wood reached its highest level and the MOR and MOE reached their maximums. With the help of this method, fast-growing softwoods can be easily prepared into dense wood materials, and it is hoped that this new material can be applied in the fields of construction, aviation, and automobile manufacturing.
CARBON-SULFUR NANOCOMPOSITES FOR LITHIUM-SULFUR BATTERIES

Title of Document: CARBON-SULFUR NANOCOMPOSITES FOR LITHIUM-SULFUR BATTERIES Jeremy Taylor Ticey, Doctor of Philosophy, 2015 Directed By: Professor John Cumings, Department of Materials Science and Engineering The increasing reliance on energy storage systems is constantly pushing research efforts to find better performing, low cost electrochemical batteries. The lithium-sulfur battery has been deemed one of the most viable candidates due to its high energy density and non-toxic, inexpensive components. In order to reach its full potential, sulfur should be incorporated into a conductive carbon host structure to ensure its electrical conductivity and cycling performance. In addition, rapid capacity fading resulting from the polysulfide shuttle mechanism should be addressed. The goal of this dissertation is to employ transmission electron microscopy (TEM) to study various nanostructured carbon materials that can serve as a cathode component in a lithium-sulfur battery. The dissertation is divided into three topics. The first topic describes the creation of graphene/sulfur composites suitable for in-situ TEM. TEM studies on sulfur are limited due to sulfur’s ability to sublimate at the operating conditions of most conventional TEMs. Therefore, we develop a layered structure in which sulfur is enveloped between two graphene sheets to stabilize the sulfur. We report the fabrication methods and TEM analysis of these structures. The second topic is the study of sulfur which is incorporated into single-walled carbon nanotubes (SWCNTs). The inner cavity of a SWCNT provides a large electrochemical interface, good mechanical stability and the potential to retain polysulfides formed during cycling. We utilize a two-step procedure consisting of thermal oxidation and hightemperature filling to produce sulfur-filled SWCNTs. Our electrochemical testing shows a clear dependence on the cell’s performance with the thermal oxidation temperature. We conclude that 475 °C is the optimal oxidation temperature for sulfur filling and results in the most stable cycling performance. The last topic is in-situ TEM studies of multi-walled carbon nanotube-sulfur composites utilizing various solid electrolytes. We examine the implications of employing a Li2S-P2S5 solid electrolyte and compare with a Li2O solid electrolyte during in-situ TEM studies. When using a Li2S-P2S5 solid electrolyte, we are able to show the formation of a lithium-sulfide phase on the surface of MWCNT-sulfur composites and show evidence of lithium dendrite growth suppression. CARBON-SULFUR NANOCOMPOSITES FOR LITHIUM-SULFUR BATTERIES
Surgical feeding tube insertion, the literature review and the actual procedure

Nutritional support through feeding tubes for patients who are unable to take oral feed has many advantages over parenteral nutrition. The feeding tubes can also be used for decompression in patients with bowel obstruction or gastroparesis and those requiring peri-operative nutritional support when oral intake is contraindicated or limited. Therefore, insertion of the feeding tube is currently one of the most commonly performed procedures. With the advances in intervention, most of the feeding tubes are inserted under endoscopic or fluoroscopic guidance. However, in some cases only the insertion of a surgical feeding tube is possible. This paper introduces the indications for inserting a surgical feeding tube formation. It also de- scribes the surgical management of dislodgement and clogging of the tube, and enterocutaneous fistula among the possible complications.
Three Women in Time: Beatrice Edgell, Josephine Nash Curtis, and Mary Sturt

This article discusses research on time perception published by three women (Beatrice Edgell, Josephine Nash Curtis, and Mary Sturt) active in the early years of the 20th. Century. Edgell (On time judgment, Am. J. Psychol., 1903) was involved in psychophysical studies on the perception of brief durations, in the tradition of Vierordt and other mostly German authors. Curtis (Duration and the temporal judgment, Am. J. Psychol., 1916) provided detailed reports of introspections from participants performing timing tasks, in the manner of her supervisor, Titchener. Sturt (via the article by Oakden & Sturt, The development of the knowledge of time in children, Br. J. Psychol., 1922, an article by Sturt herself, Experiments on the estimate of duration, Br. J. Psychol. 1923, and her book The Psychology of Time, 1925) was involved in extensive developmental studies on the understanding of everyday time concepts, such as years, months, and dates, as well as other work involving variations in time judgements as a function of different conditions, such as when receiving painful stimulation.
Strategies for colorectal cancer screening and post-polypectomy surveillance for young adults under age 50

The incidence of colorectal cancer in young adults aged <50 years is increasing. In line with these recent trends, it is necessary to pay attention to young-onset colorectal adenoma, a precursor of colorectal cancer. Recent studies have reported that the prevalence of colorectal adenomas in young adults aged <50 years is not low. Moreover, it has been reported that the prevalence of advanced colorectal neoplasia (advanced adenoma or colorectal cancer) in young persons aged <50 years with clinical risk factors or a positive fecal immunochemical test result is not lower than that in average-risk older persons. In this review, I examined and summarized the prevalence and risk factors of colorectal neoplasia (colorectal adenoma or colorectal cancer) in young adults aged <50 years. Considering the results of previous studies, I proposed effective strategies for colorectal cancer screening using clinical risk factors and the fecal immunochemical test, and discussed post-polypectomy surveillance for this age group.
Effects on relevant factors of Penicillium citreoviridin toxin production

Objective To observe the effect of temperature,pH and time on Penicillium citreoviridin′s(PCV) production of toxin in laboratory.Methods PCV was cultured in Charles culture medium in different conditions,Citreoviridin(CIT) was extracted and quantitated by HPLC.Results Quantities of CIT produced by PCV were uniform at the temperature of 30? ℃ and 8? ℃(222.36～231.02? μg/g medium);PCV produced more CIT in alterant temperature(532.16? μg/g medium;PCV produced less CIT in acid culture medium(161.86? μg/g medium);PCV produced the most CIT after had cultured for 10 days.Conclusion PCV′s production of toxin was promoted in alterant temperature.PCV′s production of toxin was restrained in acid culture medium.PCVproduced maximum CIT after 10 days culture.
External Calibration Results of the SAOCOM-1A Commissioning Phase

SAOCOM is a scientific and commercial mission developed by CONAE, the National Space Commission of Argentina. It is composed of two identical satellites, each one carrying a fully polarimetric L-band synthetic aperture radar (SAR). The main driver of the mission is the retrieval of soil moisture, an application that demands high radiometric and polarimetric accuracy. In this article, we summarize the main external calibration results obtained during the commissioning phase of the SAOCOM-1A satellite. In addition, the general calibration strategy as well as the devices and facilities that were involved in the external calibration process are described.
Federated-Learning-Based Anomaly Detection for IoT Security Attacks

The Internet of Things (IoT) is made up of billions of physical devices connected to the Internet via networks that perform tasks independently with less human intervention. Such brilliant automation of mundane tasks requires a considerable amount of user data in digital format, which, in turn, makes IoT networks an open source of personally identifiable information data for malicious attackers to steal, manipulate, and perform nefarious activities. A huge interest has been developed over the past years in applying machine learning (ML)-assisted approaches in the IoT security space. However, the assumption in many current works is that big training data are widely available and transferable to the main server because data are born at the edge and are generated continuously by IoT devices. This is to say that classic ML works on the legacy set of entire data located on a central server, which makes it the least preferred option for domains with privacy concerns on user data. To address this issue, we propose the federated-learning (FL)-based anomaly detection approach to proactively recognize intrusion in IoT networks using decentralized on-device data. Our approach uses federated training rounds on gated recurrent units (GRUs) models and keeps the data intact on local IoT devices by sharing only the learned weights with the central server of FL. Also, the approach’s ensembler part aggregates the updates from multiple sources to optimize the global ML model’s accuracy. Our experimental results demonstrate that our approach outperforms the classic/centralized machine learning (non-FL) versions in securing the privacy of user data and provides an optimal accuracy rate in attack detection.
Detecting Insider Threat via a Cyber-Security Culture Framework

ABSTRACT Insider threat has been recognized by both scientific community and security professionals as one of the gravest security hazards for private companies, institutions, and governmental organizations. Extended research on the types, associated internal and external factors, detection approaches and mitigation strategies has been conducted over the last decades. Various frameworks have been introduced in an attempt to understand and reflect the danger posed by this threat, whereas multiple identified cases have been classified in private or public databases. This paper aims to present how a cyber-security culture framework with a clear focus on the human factor can assist in detecting possible threats of both malicious and unintentional insiders. We link current insider threat categories with specific security domains of the framework and introduce an assessment methodology of the core contributing parameters. Specific approach takes into consideration technical, behavioral, cultural, and personal indicators and assists in identifying possible security perils deriving from privileged individuals.
Modeling Study on the Impact of Mold Thickness on Strip Warpage of a Molded Leadframe Package

Strip warpage is a common problem in molded leadframe packages. When warpage becomes excessive, the strip could not be processed as it would result in the strip being stuck or damaged during loading to the handling machine loader. This study focuses on the impact of mold cap thickness on strip warpage of a molded Quad Flat No Lead (QFN) package to provide guidance in reducing the strip warpage to an acceptable level. Different mold thickness values were considered in the modeling using finite element analysis (FEA). Results showed that there is an optimum mold thickness, which is around 1.0 mm for 0.20 mm leadframe thickness and 0.65 mm for 0.125 mm leadframe thickness, that gives the lowest warpage in the case considered. The optimum mold cap thickness is lower for thinner leadframe. At mold thickness lower than the optimum value, warpage is in “frowning” mode and increases as the package gets thinner and this agrees with actual observations. This study shows that mold cap thickness has significant impact on molded strip warpage and could be assessed using FEA. Therefore, controlling the mold cap thickness could now be considered an option to reduce strip warpage in molded semiconductor packages as supported by modeling.
Transformations of Carbon and Sulfur Wastewater Components Under Aerobic–Anaerobic Transient Conditions in Sewer Systems

Wastewater quality changes in the carbon and sulfur cycles in pressure sewers and in a gravity sewer that followed a pressure sewer were studied. The primary focus was on changes in chemical oxygen demand (COD) components during transport, which were investigated using oxygen uptake rate measurements and volatile fatty acid analyses. Sulfide formation in the pressure sewers and sulfide oxidation in the gravity sewer were also studied. Anaerobic hydrolysis, which resulted in a net production of readily biodegradable substrate in the pressure sewers, was quantified. A process model description, which included the main aerobic and anaerobic processes in the water phase and in the biofilm, was presented; model parameters were determined based on calibration. This simulation procedure made it possible to consider integrated aspects of hydrogen sulfide and variations in COD components in sewers such as odor and sewer corrosion by hydrogen sulfide and the inadequacy of advanced wastewater treatment because of the input of low‐quality wastewater. It is possible to include wastewater quality changes and, thereby, process aspects for sewer design and operation.
Relocation of Seismicity in the Guadalentín Tectonic Valley, Eastern Betics Shear Zone (Southeast Iberia)

The eastern Betics shear zone comprises one of the most seismically active areas in Iberia, due to the presence of large active faults loaded by the oblique convergence between Eurasia and Africa plates. We focus our study on the sector of the eastern Betic Cordillera affected by the Alhama de Murcia fault (AMF) and other nearby faults that are the source of large paleoseismic events and some damaging historical earthquakes. This study aims to give more accurate locations to the hypocenters in the region around these faults, using a model that accounts for lateral variations of P-wave velocity. This task was accomplished, developing a new 3D velocity crustal model of the region, by combining recent regional and local geological and geophysical data, such as geological mapping, gravimetry, seismic-wave tomography, and seismic exploration surveys. Afterward, as a preliminary test of performance, we compared the hypocenters obtained with this model against the ones computed with other 1D velocity models, using NonLinLoc with a seismic dataset of the highest possible quality (i.e., filtered by a minimum magnitude) in this area within the period January 2015–December 2018. Then, for comparing the reliability of the new 3D local model against a larger 3D regional model, we carried out a final relocation with all the earthquakes of the Spanish Seismic Catalog in the study area for the period April 2011–October 2019. New locations obtained with the local model, which show better clustering near active structures and lower epicentral uncertainty in comparison with the regional model, allow us to observe possible genetic relation between seismicity and specific faults after the inversion, in particular, the AMF.
A comprehensive data‐level investigation of cancer diagnosis on imbalanced data

Cancer is one of the leading causes of death in the world. Cancer research is vital as the prognosis of cancer enables clinical applications for patients. In this study, we have proposed the Stacked Ensemble Model (Stacking of bagged and boosted learners) for the automatic disease diagnosis. The experimental results prove the superiority of the proposed method to conventional machine learning techniques. In the empirical study, the performance of eight data handling methods and 14 classification methods is compared to obtain prediction results. The performance of the model has been evaluated on five benchmark datasets. The appreciable Area under the Curve scores achieved by the proposed methodology on Cervical Cancer (0.98), Mesothelioma (0.93), Breast Cancer (0.99), Prostate Cancer (0.97), and Hepatitis‐C Virus (0.998) datasets make this work more significant than the previously published works. The experimental results show that our proposed method is superior to conventional machine learning techniques and the proposed model contributes in the form of an efficient computational model.