Miracle-dz/UniFAR-FTUs huggingface dataset:
Eliciting gastric cancer survivors’ preferences for follow-up services: a discrete choice experiment protocol

Introduction Follow-up care is important for gastric cancer survivors, but follow-up strategies for gastric cancer survivors remain inconsistent, and compliance of gastric cancer survivors with follow-up care is very low. Understanding the needs and preferences of gastric cancer survivors is conducive to developing appropriate and acceptable follow-up strategies, thereby improving patient compliance. Discrete choice experiments can quantify individual needs and preferences. However, to date, there is no discrete choice experiment on the preferences of gastric cancer survivors, and no studies have examined how gastric cancer survivors make choices based on different characteristics of follow-up. This paper outlines an ongoing discrete choice experiment that aims to (1) explore follow-up service-related characteristics that may affect gastric cancer survivors’ choices about their follow-up, (2) elicit how gastric cancer survivors consider the trade-offs among different follow-up service options using discrete choice experiment, (3) determine whether gastric cancer survivors’ needs and preferences for follow-up vary due to the economy, politics, technology and culture in different regions. Methods and analysis Six attributes were developed through a literature review, semistructured interviews and experts and focus group discussions. A fractional factorial design was used to evaluate the interaction between attributes. A multiple logit model will be used to understand the trade-off between the follow-up characteristics of gastric cancer survivors. A mixed logit model will be used to explore the willingness to pay and uptake rate of gastric cancer survivors for follow-up attributes and further explore the preferences of different groups. Ethics and dissemination This study was approved by the ethics committee of the School of Nursing, Jilin University. The results of this study will be shared through online blogs, policy briefs, seminars and peer-reviewed journal articles and will be used to modify the current strategy of gastric cancer survivors’ follow-up services according to economic development and regional culture.
Cancer and mortality in coal mine workers: a systematic review and meta-analysis

Coal mine workers are exposed to a number of workplace hazards which may increase the risk of cancer and mortality. We conducted a systematic review and meta-analysis to investigate cancer and mortality in coal mine workers We searched in Ovid Medline, PubMed, Embase and Web of Science databases using keywords and text words related to coal mines, cancer and mortality and identified 36 full-text articles using predefined inclusion criteria. Each study’s quality was assessed using the Newcastle-Ottawa Scale. We performed random-effect meta-analyses including 21 of the identified articles evaluating cancer and/or mortality of coal mine workers. The meta-analysis showed an increased risk of all-cause mortality (SMR 1.14, 95% CI 1.00 to 1.30) and mortality from non-malignant respiratory disease (NMRD) (3.59, 95% CI 3.00 to 4.30) in cohorts with coal workers’ pneumoconiosis (CWP). We found a somewhat increased risk of stomach cancer (1.11, 95% CI 0.97 to 1.35) and of mortality from NMRD (1.26, 95% CI 0.99 to 1.61) in the cohorts of coal miners with unknown CWP status. The meta-analysis also showed a decreased risk of prostate cancer and cardiovascular and cerebrovascular mortality among coal miners. This may be a result of the healthy worker effect and possible lower smoking rates, and perhaps also reflect the physically active nature of many jobs in coal mines. The meta-analysis for lung cancer did not show increased risk in coal miners with CWP (1.49, 95% CI 0.70 to 3.18) or for coal miners of unknown CWP status (1.03, 95% CI 0.91 to 1.18). Lower smoking rates in coal mine workers could explain why case–control studies where smoking was controlled for showed higher risks for lung cancer than were seen in cohort studies. Coal mine workers are at increased risk of mortality from NMRD but decreased risk of prostate cancer and cardiovascular and cerebrovascular mortality. Studies of coal mine workers need long-term follow-up to identify increased mortality and cancer incidence.
Maneuver tracking algorithms for AEW target tracking applications

In a previous paper, we described AEW advanced tracking algorithm development and showed performance results for straight line targets. In this paper we show modifications of the tracking and association algorithms necessary to track the remaining 100 maneuvering targets of the 120 targets scenario. As part of ongoing AEW advanced tracking algorithm development activities, a novel approach has been developed that utilizes the Unbiased Coordinate Conversion Filter developed by Bar-Shalom et al for range and azimuth angle processing from the radar with a standard EKF for rdot and angular measurements from other sensors identified as a combined Kalman filter. We also incorporated fading memory into the filter to make it responsive to target maneuvers.
Who Owns the Project Name?

In the United States, ownership of trade marks can be bedevilling. A trade mark registration is not a grant of rights, only recognition of already-existing rights. Instead, a trade mark is owned by the first to use it and may only be registered by the owner. But, there is no consistent rule or standard that courts apply when deciding disputes over ownership. Moreover, U.S. trade mark law eschews the concept of joint ownership, considering it inconsistent with a trade mark's role as a sole source identifier or assurer of quality. Thus, courts are in the position of having to identify a single owner of a trade mark using poorly defined law. This article will review the various ways that courts have decided who owns a trade mark when there are two claimants. It will also provide guidance to free and open source software projects about how to best manage their project names so that the project has a clear claim of ownership and its project name is fully enforceable as a trade mark.
Design and Realization of the Small Power Two-Way DC Power Supply Based on UCC2800

To provide DC power to auxiliary equipment for a certain type of aircraft, according to the actual need, small power two-way dc power supply is designed using current mode pulse width modulator UCC2800. This paper introduces the basic principle of UCC2800, and also introduces the design and realization process of the low-power dc power supply based on UCC2800.
Characterization and modeling of ultrasonic structural noise in the multiple scattering regime

Multiple scattering can occur when performing ultrasonic measurements on highly scattering materials such as coarse grain steel or concrete. It constitutes in general a limiting factor for NDE techniques. In this communication, a method to simulate the structural noise due to multiple scattering is described. It requires three parameters: the diffusion constant, the elastic mean free path and the correlation distance. A method to obtain these parameters based on a single measurement procedure is presented. This approach has been applied to samples of coarse grain steel. The backscattered noise has been calculated for different probes and compared to experimental signals.
An improved two-switch flyback converter with regenerative clamping

A novel soft-switching two-switch flyback converter is proposed in this article. This converter is composed of two active power switches, a flyback transformer and two passive regenerative clamping circuits. The proposed converter has the advantages of a low-cost circuit configuration, a simple control scheme, high efficiency, and a wide operating range. The circuit topology, analysis, design considerations and experimental results of the new flyback converter are presented.
The effect of discretion, outcome feedback, and process feedback on employee job satisfaction

A recent article reported that employees′ performance increased when they were allowed to chose the production method and were provided with the outcome feedback on their performance. Extends that study by analysing the effect of discretion, outcome feedback, and process feedback on employee satisfaction. The results of the experiments indicate that, although providing discretion and outcome feedback improved employee satisfaction, the improvement was statistically insignificant. The more interesting result indicates that satisfaction was significantly improved when employees were provided with process feedback in addition to discretion and outcome feedback.
Thermomigration in Pb–Sn solder joints under joule heating during electric current stressing

Electromigration of solder joint under high dc current density is known as a reliability concern for the future high-density flip chip packaging and power packaging. Biased mass diffusion within solder joint from cathode to anode under high dc current density is observed in these experiments. In this letter, the experiments on flip chip solder joints under dc current stressing are conducted and thermomigration due to the thermal gradient in the solder joint caused by joule heating is reported. A three-dimensional coupled electric thermal finite-element (FE) simulation of a realistic flip chip module shows the existence of thermal gradient in the solder joint which is high enough to trigger thermomigration.
Effects of parity on the reproductive performance of Nigerian indigenous sows and progeny survivability rates in Enugu State, South East Nigeria

The effects of parity on the reproductive performance of Nigerian indigenous sow breed, progeny survivability and mortality in a commercial breeding farm in Enugu State Nigeria were investigated in this study. One hundred apparently healthy third trimester pregnant sows were randomly assigned to four treatment groups of twenty five sows per group in a completely randomized design (CRD) according to their reproductive parities as groups I, II, III and IV representing the first (P1), second (P2), third (P3) and fourth (P4) parities respectively. This study lasted for two years. The mean number of piglets born alive (NBA) of P1 (6.00±0.71 Head) and P2 (6.00±0.71 Head) were significantly decreased when compared to P4 (8.50±0.65 Head) but showed no significant difference when compared to P3 (7.50±0.50 Head). Second parity sows recorded the highest number of piglets’ deaths after birth while P1 and P3 litters recorded the lowest deaths after birth. Mean pre-weaning survival of progenies was highest in P3 (91.43±5.09 %) and lowest in P2 (84.38±11.83 %) while mean piglet mortality was highest in P2 (15.63±11.83 %) but lowest in P3 (8.57±5.09 %). It can be concluded from this research work that PIII sows provided adequate requirements necessary for their litter nourishment, growth and survival more than the other parities. Therefore progeny growth performance was best at third parity of reproduction.
Usecase of Blockchain in Disaster Management-A Conceptual View

Blockchain is a distributed database technology where data can be secured with cryptographic function and provide transparency to the system. It has been extensively used in different use cases like financial instruments, egovernance, supply chain and many more. This paper focuses on how blockchain can be used as an application during emergencies. Because, there is no such integrated information system so far developed for disaster management and control for effective decision making. Conceptual model has been developed by reviewing various literature papers from disaster and blockchain streams. This paper tries to address collaborating the stakeholders to one single platform where the information sharing and storing are reliable and consistent. This paper provide a system model for various user scenario in pre, during and post disaster situations. The model claim a holistic view and provide a solution to the disaster events.
Visualization research at the Software Engineering and Information Systems Laboratory (SEIS)

—This paper summarizes twelve years of visualization research at the Software Engineering and Information Systems Laboratory (SEIS), located at the University of Campinas. This research comprises theoretical and applied research in visualization and embraces themes such as the development of matrix reordering algorithms, the creation of heuristics for visualization, and the application of visualization techniques to areas such as oil engineering and educational data mining.
Evaluation of three multiple-choice assessment methods in a human factors engineering course

This study investigated students’ objective performance and subjective preference for the conventional, liberal, and confidence marking multiple-choice methods. Eighty-one university students answered multiple-choice quiz questions on human factors engineering using each of the three methods and then provided feedback on each method. Relative to the conventional method, the liberal and confidence marking methods were useful for extracting information about partial knowledge and increased the variance of performance scores. The different multiple-choice methods could cause students to change their response criterion in performing the assessment, whereas the ability to discriminate correct answers from distracters did not vary across the multiple-choice methods. Regarding subjective preferences, the conventional method was the most preferred followed by the liberal method and then the confidence marking method. The findings of this study would be useful for the selection of effective multiple-choice methods for academic assessments.
Evaluation of the survival and growth of the ornamental "Colombian shark catfish" Ariopsis seemanni in water of different salinities

Ariopsis seemanni is one of the few marine catfish in the ornamental fish trade. In Colombia, its country of origin, this catfish is being overfished. The most immediate threat to their populations occurs during their collection and commercialization, in which they are treated as a freshwater fish. The fish are collected in water of varying salinities then immediately placed in freshwater that compromises their health and typically causes mass mortalities. In this study, we evaluated the growth and survival of small juveniles of this catfish raised in water of different salinities (0, 10, 20 ppt), over a period of 60 days. The average weight and length of the catfish at the beginning of the experiment were 2.6±0.1 g and 60.9±2.7 mm, respectively. At the end of the experiment, the catfish reared in salt water (10 and 20 ppt) grew significantly (p < 0.05) from their initial values and were significantly larger (e.g., 6.0±1.3 g and 82±7.4 mm; p < 0.05) than those maintained in freshwater; which did not gain significant weight (e.g., 2.6±0.5 g, p > 0.05). The average size of fish was similar (p > 0.5), within the two salinity treatments. We recommend that immediately after collection this catfish be placed in water with a salt concentration of about 10 ppt that would greatly improve survival and decrease morbidity.
Predicting ratings in multi-criteria recommender systems via a collective factor model

In a multi-criteria recommender system, users are allowed to give an overall rating to an item and provide a score on each of its attribute. Finding an effective method to exploit a user’s multi-criteria ratings to predict the overall rating becomes one of the most important challenges. Among traditional solutions, most of the architectures are not designed in an end-to-end manner. These approaches initially estimate a user’s multi-criteria scores, and train a separate model to predict the user’s overall rating. This introduces extra training overhead, and the overall prediction accuracy is usually sensitive to its multi-criteria ratings models. In this paper, we propose a collective model to predict user’s overall rating by automatically weighting each of the predicted multi-criteria sub-scores. The proposed architecture integrates the multi-criteria ratings and the overall rating models in a unified system, which allows to train and perform multi-criteria recommendation in an end-to-end manner. Experiments on 3 real datasets show that our proposed architectures achieve up to 13.14% lower prediction error over baseline approaches.
Preparation and Application Study of Nano-Sized Organic Bentonite Used for Composite Flame Retardant

Nono-sized organic bentonite (OMMT) was synthesized through intercalation modification process with organic phosphorus flame retardant (Cyagard RF-1) and quaternary ammonium salt (CTAB). Composite materials of polybutylene terephthalate (PBT)/OMMT, Polyamide-6 (PA6)/OMMT was prepared by a double screw extrusion. The flame retardancy and mechanical properties of these materials were characterized. Nano-sized OMMT has large interlayer spacings and good dispersion after modification. In compared with PBT and PA6, composite materials of PBT/OMMT and PA6/OMMT had high tensile strength, bending strength and notched impact strength, while their elongation decreased after addition of nano-sized OMMT, the limiting oxygen index ( LOI ) and UL94 vertical combustion of OBT/OMMT and PA6/OMMT composite materials with dosage of 3 wt% OMMT decreased slightly, in comparison with these composite metarials containing constant amounts of flame retardant.
Robust ToA-Estimation using Convolutional Neural Networks on Randomized Channel Models

Many radio-based positioning systems use time-of-arrival (ToA). We obtain it from the first and direct path of arrival (FDPoA) in a corresponding set of multipath components (MPC) of the underlying channel state information (CSI). While detection of the FDPoA under Line-of-Sight (LoS) is simple, it is prone to errors in environments with specular and diffuse reflections, as well as nonlinear diffraction, absorption, and transmission of a signal. Such Obstructed- or Non-Line-of-Sight (OLoS, NLoS) situations lead to incorrect FDPoA and consequently to incorrect ToA estimates and inaccurate positions. State-of-the-art estimators are computationally expensive and usually fail with O/NLoS at low signal-to-noise ratios (SNRs). We propose a deep learning (DL) approach to identify optimal FDPoAs as ToA directly from the raw CSI. Our 1D Convolutional Neural Network (CNN) learns the spatial distribution of MPCs of the CSI to predict correct estimates of the ToA. To train our DL model, we use QuaDRiGa to generate datasets with CIRs and ground truth ToAs for realistic 5G channel models. We found that Delay Spread (DS), k-Factor (kF), and SNR are appropriate metrics to cover most LoS-NLoS constellations in realistic datasets. We compare our DL model with state-of-the-art estimators such as threshold (PEAK), inflection point (IFP), and MUSIC and show that we consistently outperform them by about 17% for SNRs below -10 dB.
Method for determining the junction temperature of alternating current light-emitting diodes

A numerical simulation was used to simulate the temperature distribution during AC and DC operations of an alternating current light-emitting diode (AC LED). The relationship between the junction temperature and the temperature at the centre of the bottom surface of the submount of an AC LED was measured under DC operation. This relationship was confirmed by numerical simulation. The numerical results were consistent with the experimental observations in that the temperature at the centre of the bottom surface of the submount was insensitive to the current variations that occur in an AC LED, probably because of the large mass of the submount. However, it was difficult to measure the temperature oscillation at the junctions in an AC LED, although this oscillation can be clearly seen in the numerical results. Thus, the authors propose a formula for predicting the range of the oscillating junction temperature for an AC LED.
Automated Inference of Linked Transit Journeys in London Using Fare-Transaction and Vehicle Location Data

Urban public transit providers historically have planned and managed their networks and services with little knowledge of their customers’ travel patterns. Although ticket gates and bus fareboxes yield counts of passenger activity in specific stations or vehicles, the relationships between these transactions—the origins, transfers, and destinations of individual passengers—typically have been acquired only through small, costly, and infrequent rider surveys. New methods for inferring the journeys of all riders on a large public transit network have been built on recent work into the use of automated fare collection and vehicle location systems for analysis of passenger behavior. Complete daily sets of data from London's Oyster farecard and the iBus vehicle location system were used to infer boarding and alighting times and locations for individual bus passengers and to infer transfers between passenger trips of various public modes, and origin–destination matrices of linked intermodal transit journeys that include the estimated flows of passengers not using farecards were constructed. The outputs were validated against surveys and traditional origin–destination matrices. The software implementation demonstrated that the procedure is efficient enough to be performed daily, allowing transit providers to observe travel behavior on all services at all times.
Reflow Soldering Process Virtual Test Based on BPNN-GA and ANSYS

Experiment plays the prime method in soldering reflow profile forecasting. While its high cost and low efficiency makes the company hard to develop. According to the nonlinear relationship between the multi input and output, reflow profile input parameters setting method based on BP neural network and genetic algorithm(BPNN-GA) is proposed in the paper. Establish the finite element model of the PCB products with ANSYS software, and simulate the reflow profile. Temperature field in the PCBAs heat process is analyzed to help adjust to provide guidance for parameter settings partially. The result shows that the process of parameters set methods with BPNN-GA and simulating analysis with ANSYS is effective in establish the virtual test system. The obtained characteristic value meets product quality requirements well.
Vibration energy harvesting from heavy haul railcar vibrations using a two-degree-of-freedom coupled oscillating system

This paper investigates the design and fabrication of an energy-harvesting device for converting the kinetic energy of heavy haul railcar vibrations into electrical energy. The inertial-based electromagnetic generator is a two-degree-of-freedom (2-DoF) coupled oscillating system that can efficiently operate at the two dominant frequencies corresponding to unloaded and loaded railcar conditions. Vibration measurements from the field indicate the dominant frequency of the railcar at a sprung location shifts between 14.6 and 5.8 Hz for the unloaded and loaded conditions, respectively. Design and optimization was investigated using multi-physics finite element analysis (COMSOL) with sinusoidal vibration input. A prototype was developed to demonstrate that a practical amount of power can be generated using the 2-DoF coupled system. Experimental results favourably agree with model predictions, and show that more than 200 mW of output power can be generated at each dominant frequency from a 0.4 g peak sinusoidal host acceleration (where g = 9.8 m/s2). In addition measured railcar vibration was replicated using a power spectral density approach, allowing prediction to be made about the performance of the generator in the field.