Miracle-dz/UniFAR-FTUs huggingface dataset:
Lynch Syndrome in Endometrial Carcinoma: A Sentinel Diagnosis

Abstract Lynch syndrome, also known as hereditary nonpolyposis colon cancer, is an autosomal dominant inherited cancer susceptibility syndrome characterized by germline mutations in mismatch repair genes such as MSH2, MSH6, PMS2, and MLH1. Although Lynch syndrome is most commonly associated with colon cancer, recent attention has shifted to its relationship to endometrial carcinoma. In women with Lynch syndrome, endometrial carcinoma is often the first clinical manifestation, alerting clinicians to the risk of subsequent Lynch syndrome–related cancers and the initiation of early screening and preventive strategies, which can significantly reduce cancer-related morbidity and mortality. Using traditional factors such as age and family history to decide which patients receive testing misses up to 70% of Lynch syndrome cases. The pathologist plays a vital role not only in identifying cases suggestive of Lynch syndrome, but also in interpreting screening tests. This review discusses the genetics and clinicopathologic features of Lynch syndrome–related endometrial carcinoma, as well as the screening protocols and preventive strategies used in the evaluation of patients who may be at risk for Lynch syndrome.
RCS Based Depolarizing Passive Tag with Improved Clutter Rejection for Potentiometric Gas Sensing

This paper presents a radar cross-section (RCS) based tag capable of detecting acidic/basic volatiles in the sensing environment. The sensor consists of two miniaturized annular slot antennas. One acts as the sensing element and the other as the reference. Both antennas are perturbed to provide a high cross-polarized scattering response. The cross-polarization-based interrogation technique provides robust detection against environmental scattering. A pH combination electrode coupled to a varactor diode provides the necessary transduction required for gas sensing. The concentration of the gas being monitored directly translates to the resonant frequency modulation of the sensing antenna.
Component Sizing of Single and Dual Drive Series Hybrid Electric Powertrain for Military Tracked Vehicles

Hybrid electric technology is becoming important in military vehicles due to its features and benefits such as onboard electric power, silent mobility, and improved performance. The desired mobility attributes of a military tracked vehicle were considered in this study to design a series hybrid electric powertrain for the same. This involved the power and torque analysis of vehicle performance using fundamental governing equations. From analysis of performance requirements, operating terrains and powertrain components characteristics, component sizing of a series hybrid electric powertrain for a military tracked vehicle was done with single drive and dual drive configurations.
SiO2/SiN membranes as MEMS Pirani gauges for wide pressure measurement range

Thanks to an original surface microfabrication process, large membranes suspended 1 micron above a substrate have been elaborated. A membrane with a wide heat exchange area and such a small gap allows the gauge to be sensitive in the high vacuum regime, and ensures a broader pressure range of measurement. By optimizing the membrane and beam sizes, this paper shows that one can combine different membranes to design a packaged sensor with a wide sensitive pressure range (10-2 to 105 Pa) and a very low power consumption (maximum 115 microwatt in this paper). These results allow the design of a fully integrated sensor, based on a unique technology, that can be integrated for in-situ pressure measurements in vacuum applications.
VeriAbs : Verification by Abstraction and Test Generation

Verification of programs continues to be a challenge and no single known technique succeeds on all programs. In this paper we present VeriAbs, a reachability verifier for C programs that incorporates a portfolio of techniques implemented as four strategies, where each strategy is a set of techniques applied in a specific sequence. It selects a strategy based on the kind of loops in the program. We analysed the effectiveness of the implemented strategies on the 3831 verification tasks from the ReachSafety category of the 8th International Competition on Software Verification (SV-COMP) 2019 and found that although classic techniques - explicit state model checking and bounded model checking, succeed on a majority of the programs, a wide range of further techniques are required to analyse the rest. A screencast of the tool is available at https://youtu.be/Hzh3PPiODwk.
Magnetic Couplers for Dynamic IPT Systems

This paper presents an analysis of magnetic couplers for dynamic IPT EV charging systems. Long and segmented pads configurations on the primary-side are analysed for dynamic IPT applications. Also pads with ferrite cores, or coreless pads with an intermediate coil are discussed. Ferrite designs allow higher power transfer due to the high permeability of ferrite cores but increase the system cost. Using coreless structures ensure lower costs, and the use of the intermediate coil will allow to compensate for the lack of ferrite cores. The studied designs are modelled and simulated in a 3D Finite Element Method (FEM) software.
SNSaPP: Unbiased Social Media Analysis Against Paid Posters

Social media platforms have become a dominating role in our daily life, and it can also be a powerful tool for spreading information. The paid poster, for example, is a emerging job type, which aims to influence people's opinions on certain events or market trends. Impact of paid posters has recently attracted attention from both industry and academia: they are hired to campaign event and shape public's opinions, which may result in negative social impact. In this demo, we focus on one of the major sources of bias - paid posters, trying to provide a system that gives transparent and unbiased information to users. In this demo, we present our system SNSAPP, which consists of four core components: (1) crawler, which gathers information of potential paid posters from various social platforms; (2) paid posters management module that extracts the accurate paid poster information, including account ids, their post contents and their social media relationships; (3) event influence estimation module, which is to calculate the impact score of a particular social event; and (4) events ranking module, which provides an unbiased ranked list of social network celebrities after potential impact from paid posters. SNSAPP aims to provide an unbiased ranking and data analysis, when a burst event happens and there are lots of paid posters involved in. The system provides the functionality for users to monitoring true rankings and the evolving process of events, which helps people to make the right decisions.
Implementation of the Analytical Method for the Lightning Performance Assessment of Power Line with Line Lightning Protection Devices

This paper presents the implementation of the analytical formula method to assess the lightning performance of OHL with Line Lightning Protection Devices (LLPD). The method is based on the classical representation of OHL and poles as an equivalent circuit to calculate a critical lightning current for flashover of the line insulation or LLPD and uses IEEE Std. 1410. The algorithm of automatic placement of LLPDs has been made to help engineers to install protective devices on power line maximally effective. The method has been tested on the line in Colombia.
PIMD Signal Modeling Based on FTDNN

In this paper, modeling of the third-order passive intermodulation distortion (PIMD) caused by the downlink signal in the frequency division duplex (FDD) wireless communication system is developed with the Focused Time Delay Neural Network (FTDNN). PIMD is an interference signal generated due to the nonlinearity of a passive element in a wireless communication environment, and degrades the noise level of a receiver, resulting in a deterioration of communication quality. Offline learning and testing of the proposed approach are investigated with measured PIMD signals and transmitted downlink signals. As a result, it is confirmed that FTDNN structure is suitable for learning nonlinearity of the PIMD generation process.
Numerical Calculation Current Form of Led Lamp PWM Stabilizer

The requirements of electromagnetic compatibility (EMC) are applied to technical means at housing facilities, retail facilities, institutions, facilities for mass cultural entertainment, outdoor facilities, production and household facilities, etc. LED lamps in the typical sizes of filament lamps and, especially with filamentary light emitting elements (filament lamps), occupy a special place among the LED light sources that are also applicable to the EMC requirements. The peculiarity of the lamps with such a design is the limitations on the overall dimensions of the AC voltage to unidirectional current converter that are determined by the internal dimensions of a lamp base. The EMC assurance by adding filtering elements is not always possible under these conditions. Therefore, it is important to calculate the conductive interference voltage at the lamp design stage. Consequently, to develop the calculation algorithm is a crucial task. One can determine the interference value by means of the form of the output current of a PWM stabilizer flowing through a non-linear load consisting of LEDs. The time dependence of the current through the LED lamp load has been obtained by a method of successive intervals in the research. The obtained results have been compared with the data calculated by a piecewise linear representation of the non-linear load. The research results can be used to calculate the conductive interference voltage and assess the EMC of LED lamps and other electrical receivers with PWM converters.
Containerization in Scientific Calculations

The containerization is useful for reproducing computational experiments and for distributing software. However it is difficult to run distributed tasks in containers, since many of them use MPI for inter-process communication. In this paper we present and evaluate a solution – the mpiexec_docker tool, which allows to run containerized applications in similar way as non-containerized ones. It supports Docker and Podman as containerization software and OpenMPI, MVAPICH2 and Intel MPI as MPI implementations. It can work with Slurm and can use devices that popular in HPC like GPUs or InfiniBand adapters.
Case Study: Parameters Optimization Process for Flat Panel Display Manufacture

Taiwan’s flat panel display manufacturing is famous internationally. Its outstanding manufacturing capability can produce high quality panels in the shortest time. In the production process of flat panel displays, the process yield is the best indicator reflecting the good and bad of manufacturers. The yield is direct. The decision is to the company’s profit and reputation. Add to this, it is also the trust and acceptance of the company’s customers. When the products on the production line are abnormal in quality, the process and equipment engineers must immediately discuss the crux of the problem and improve it. For decomposition of analysis and process management to find out the method, it needs to carry out the problem in linear verification of confirmation whether the problem is a single problem or not. Furthermore, it will produce customer complaints, dissatisfaction with the company, causing the company’s losses. Therefore, using Knowledge Discovery from Data (KDD) to establish a process of big data analysis is core technology in our work. We proposed the improvement process that how to quickly find the variation factor and couple with machine learning. Hence the research is based on data pre-processing, modeling. The experiment shows that we find out the right parameters and optimze them. Finally, the yield improvement was increasing to 66%.
A Sequential Bayesian Updated Wiener Process Model for Remaining Useful Life Prediction

Wiener processes have been extensively used to model the degradation processes exhibiting a linear trend for predicting the remaining useful life (RUL) of degrading components. To incorporate the real-time degradation monitoring information into degradation modeling, the Bayesian method has been frequently utilized to update the model parameter, particularly for the drift parameter in Wiener process. However, due to the inherent independent increment and Markov properties of Wiener process, the Bayesian updated drift parameter only utilizes the current degradation measurement and cannot incorporate the whole degradation measurements up to now. As such, once the updated degradation model in this way is used to predict the RUL, the obtained result may be dominated by partial degradation observations or lower the prognosis accuracy. In this paper, we propose a sequential Bayesian updated Wiener process model for RUL prediction. First, a Wiener process model with random drift efficient is used to model the degradation process with the linear trend. To estimate the model parameters, the historical degradation measurements are used to determine the initial model parameters based on the maximum likelihood estimation (MLE) method. Then, for the degrading component in service, a sequential Bayesian method is proposed to update the random drift parameter in Wiener process model. Differing from existing studies using the Bayesian method, the proposed sequential method uses the Bayesian estimate for random drift parameter in the last time as the prior of the next time. As such, the Bayesian estimate for random drift parameter in the current time is dependent on the whole degradation measurements up to current time, and thus the problem of depending only on the current degradation measurement is solved. Finally, we derive the analytical expressions of the RUL distribution based on the concept of the first passage time (FPT). Two case studies associated with the gyroscope drift data and lithium-ion battery data are provided to show the effectiveness and superiority of the proposed method. The results indicate that the proposed method can improve the RUL prediction accuracy.
Sequence Image Registration for Large Depth of Microscopic Focus Stacking

The large depth of images for microscopic measurement can be achieved by using focus stacking techniques with a small depth of field of objective lens. It is implemented by fusing the image sequences of short depth images. However, the non-linear movement of the objective imaging system or the measured object caused by the moving stage straightness error brings the misalignment of the image sequences, such as transversal translation, rotation, and tilting. All of these interferences, as well as the image brightness variation must be corrected by image registration before fusing the image sequences. In this paper, a fast-automatic registration method based on the scale invariant feature transform (SIFT) is proposed. It is achieved by firstly segmenting the focal regions of the image sequences through fast edge detection. Then the image features are extracted within the small segmented focal areas. It greatly reduces the computational cost of feature extraction and the following steps of image correction, and alignment. In the process, the random sampling consistency (RANSAC) algorithm is also used to remove the mistake features. The Laplacian pyramid method is adopted for the large depth of image fusion. The experimental results show that the proposed method is more efficient than the traditional SIFT algorithm. Its registration efficiency is improved by about 60%. This method facilitates the high-precision and real-time imaging of a monocular three-dimensional focus stacking.
A Scoring Model of Figural Goodness and Its Application to Contour Completion Problems

This paper models the concept of figural goodness of a shape and apply the model to solving the visual occlusion problem. Based on the observation that 'goodness' of figure is influenced by local and global shape contexts, we model simplicity and regularity of a shape, and define a figural goodness score by linearly combining these two. To evaluate the usefulness and limitation of the proposed scoring, we applying the model to solving a contour completion problem. In the application, various completion paths of occluded contours are generated by a computer using different kinds of completion algorithms. To the generated paths, the best one is selected as the contour completion result by comparing their figural goodness scores. Experimental results have shown that the scoring model of figural goodness works effectively for the contour completion problem.
Stacked Interdigital Filtering Antenna with Slant Polarization

The studies of the filtering antenna have performed many methods and type of resonators used in co-design between the filter and antenna. But none of them using the interdigital resonator with a via through hole. Interdigital resonator with a via through hole has a unique characteristic for it is short-circuited at one end and open circuited at the other. This condition is expected to have an effect to the electric field and the surface current direction. This paper performs a second order of the interdigital filter co-design with a proximity fed rectangular patch antenna. The simulation shows that the interdigital resonator with a via through hole affects the polarization of the antenna from a vertical polarization alter to a slant polarization. The design is fabricated and measured, both the simulation and measurement show a good agreement with a bandwidth of 330 Mhz at 4.65 GHz center frequency, maximum gain of 6.72 dBi and a −75° slant polarization.
End-User Programming of Low-and High-Level Actions for Robotic Task Planning

Programming robots for general purpose applications is extremely challenging due to the great diversity of end-user tasks ranging from manufacturing environments to personal homes. Recent work has focused on enabling end-users to program robots using Programming by Demonstration. However, teaching robots new actions from scratch that can be reused for unseen tasks remains a difficult challenge and is generally left up to robotic experts. We propose iRoPro, an interactive Robot Programming framework that allows end-users to teach robots new actions from scratch and reuse them with a task planner. In this work we provide a system implementation on a two-armed Baxter robot that (i) allows simultaneous teaching of low-and high-level actions by demonstration, (ii) includes a user interface for action creation with condition inference and modification, and (iii) allows creating and solving previously unseen problems using a task planner for the robot to execute in real-time. We evaluate the generalisation power of the system on six benchmark tasks and show how taught actions can be easily reused for complex tasks. We further demonstrate its usability with a user study (N=21), where users completed eight tasks to teach the robot new actions that are reused with a task planner. The study demonstrates that users with any programming level and educational background can easily learn and use the system.
highlighted topics Plasticity in Respiratory Motor Control Invited Review: The crossed phrenic phenomenon: a model for plasticity in the respiratory pathways following spinal cord injury

Invited Review: The crossed phrenic phenom- enon: a model for plasticity in the respiratory pathways following spinal cord injury. J Appl Physiol 94: 795–810, 2003; 10.1152/japplphysiol. 00847.2002. —Hemisection of the cervical spinal cord rostral to the level of the phrenic nucleus interrupts descending bulbospinal respiratory path- ways, which results in a paralysis of the ipsilateral hemidiaphragm. In several mammalian species, functional recovery of the paretic hemidia- phragm can be achieved by transecting the contralateral phrenic nerve. The recovery of the paralyzed hemidiaphragm has been termed the “crossed phrenic phenomenon. ” The physiological basis for the crossed phrenic phenomenon is as follows: asphyxia induced by spinal hemisection and con- tralateral phrenicotomy increases central respiratory drive, which activates a latent crossed respiratory pathway. The uninjured, initially latent path- way mediates the hemidiaphragm recovery by descending into the spinal cord contralateral to the hemisection and then crossing the midline of the spinal cord before terminating on phrenic motoneurons ipsilateral and caudal to the hemisection. The purpose of this study is to review work conducted on the crossed phrenic phenomenon and to review closely related studies focusing particularly on the plasticity associated with the response. Because the review deals with recovery of respiratory muscles paralyzed by spinal cord injury, the clinical relevance of the reviewed studies is high- lighted.
A 28 μW timing circuit for a 60 μm2 HV-CMOS pixel

High Voltage-CMOS (HV-CMOS) sensors are the sensor technology of choice for the pixel tracker in the Mu3e experiment at PSI in Switzerland. These particular sensors allow the integration of the readout electronics with the sensor, having potentially 100% fill-factor. In this contribution, design details and simulation results of sampling circuits integrated with the sensor to enable low power 4D tracking will be presented. Particular attention was considered to minimize the timing errors due to amplitude variations (time walk) and enhance the time resolution.
Estimation of Technical and Allocative Inefficiency in a Translog Cost System:

Estimation and decomposition of overall (economic) efficiency into technical and allocative components goes back to Farrell (1957). However, in a cross-sectional framework joint econometric estimation of efficiency components has been mostly confined to restrictive production function models (such as the Cobb-Douglas). In this paper we implement a maximum likelihood (ML) procedure to estimate technical and allocative inefficiency using the dual cost system (cost function and the derivative conditions) in the presence of cross-sectional data. Specifically, the ML procedure is used to estimate simultaneously the translog cost system and cost increase due to both technical and allocative inefficiency. This solves the so-called ‘Greene problem’ in the efficiency literature. The proposed technique is applied to the Christensen and Greene (1976) data on U.S. electric utilities, and a cross-section of the Brynjolfsson and Hitt (2003) data on large U.S. firms. JEL classification: C 31
Adaptive Output Voltage Tracking Control for a Fuel Cell-Boost Converter Power Supply

A DC/DC boost converter is an essential subassembly for power/energy transfer from a power source to electrical facilities. Polymer electrolyte membrane fuel cell (PEMFC) is currently drawing great attention as the power source for electric vehicles. With the coordination of a boost converter tackling with widely changing external load, an electric vehicle can obtain the required voltage supply for its powertrain system. This paper focuses on PEMFC power system voltage control in face of varied tracking references and disturbance injections. An equivalent electrical circuit model for the PEMFC and the boost converter averaging state model are employed to describe the entire power system. Then, a sliding mode control integrated with backstepping method is used to provide the control signal in the form of the PWM duty ratio, wherein the control stability is ensured via suitable configuration of Lyapunov functions. Moreover, an adaptive law for dealing with the parameter uncertainties is also adopted. Finally, simulation and experimental tests are carried out to verify the voltage tracking effectiveness of the proposed control method, with external load variation and parametric uncertainties considered in the operation conditions.