Miracle-dz/UniFAR-FTUs huggingface dataset:
KLK4T2 Is a Hormonally Regulated Transcript from the KLK4 Locus

The human kallikrein-related peptidase 4 (KLK4) and the transcribed pseudogene KLKP1 are reported to be highly expressed in the prostate. When trying to clone transcripts of KLKP1, we partly failed. Instead, we identified an androgen-regulated transcript, KLK4T2, which appeared to be a splice variant of KLK4 that also contained exons of KLKP1. Expression analysis of KLK4, KLK4T2, and KLKP1 transcripts in prostate cancer cell lines showed high levels of KLKP1 transcripts in the nucleus and in unfractionated cell extract, whereas it was almost completely absent in the cytoplasmatic fraction. This was in contrast to KLK4 and KLK4T2, which displayed high to moderate levels in the cytoplasm. In patient cohorts we found significantly higher expression of both KLK4T2 and KLK4 in benign prostatic hyperplasia compared to both primary prostate cancer and bone metastasis. Analysis of tissue panels demonstrated the highest expression of KLK4T2 in the prostate, but in contrast to the classical KLK4, relatively high levels were also found in placenta. So far, the function of KLK4T2 is still to be explored, but the structure of the translation product indicated that it generates a 17.4 kDa intracellular protein with possible regulatory function.
Dependence of wet etch rate on deposition, annealing conditions and etchants for PECVD silicon nitride film

The influence of deposition, annealing conditions, and etchants on the wet etch rate of plasma enhanced chemical vapor deposition (PECVD) silicon nitride thin film is studied. The deposition source gas flow rate and annealing temperature were varied to decrease the etch rate of SiNx:H by HF solution. A low etch rate was achieved by increasing the SiH4 gas flow rate or annealing temperature, or decreasing the NH3 and N2 gas flow rate. Concentrated, buffered, and dilute hydrofluoric acid were utilized as etchants for SiO2 and SiNx:H. A high etching selectivity of SiO2 over SiNx:H was obtained using highly concentrated buffered HF.
Reduction of Electromagnetic Field from Wireless Power Transfer Using a Series-Parallel Resonance Circuit Topology

In this paper, we implemented and analyzed a wireless power transfer (WPT) system with a CSPR topology. CSPR refers to constant current source, series resonance circuit topology of a transmitting coil, parallel resonance circuit topology of a receiving coil, and pure resistive loading. The transmitting coil is coupled by a magnetic field to the receiving coil without wire. Although the electromotive force (emf) is small (about 4.5V), the voltage on load resistor is 148V, because a parallel resonance scheme was adopted for the receiving coil. The implemented WPT system is designed to be able to transfer up to 1 ㎾ power and can operate a LED TV. Before the implementation, the EMF reduction mechanism based on the use of ferrite and a metal shield box was confirmed by an EM simulation and we found that the EMF can be suppressed dramatically by using this shield. The operating frequency of the implemented WPT system is 30.7㎑ and the air gap between two coils is 150㎜. The power transferred to the load resistor is 147W and the real power transfer efficiency is 66.4 %.
Cost analysis of urban water supply and waste water treatment processes to support decisions and policy making: application to a number of Swedish communities

An econometric model has been developed that represents the cost structure of water supply and waste water treatment in an urban area. This paper proposes a method to capture the financial characteristics of the underlying organisation and addresses the steps and the conceptualisation in order to create a cost structure for municipal water utilities. The estimation procedure is based on a multivariate regression approach and the cost structure is represented by a parametrical expression (cost function). This function has been used for the purpose of analysing the observed system in terms of efficiency, technology, capacity, financial state etc. In the mathematical formula the estimated parameters relate certain system input components to costs, which are important in order to understand the key drivers. An empirical analysis is undertaken for a number of utilities in Sweden.
OO Information Model for Construction Project Management

Recently, the writers developed a general and powerful mathematical model for scheduling construction projects. An optimization formulation was presented with the goal of minimizing the direct construction cost. The nonlinear optimization problem was solved by the recently patented neural dynamics model of Adeli and Park. In this paper an object-oriented (OO) information model is presented for construction scheduling, cost optimization, and change order management (CONSCOM) based on the new construction scheduling model. The goal is to lay the foundation for a new generation of flexible, powerful, maintainable, and reusable software system for the solution of construction scheduling problems. The model is presented as a domain-specific development framework using the Microsoft Foundation Class library and utilizing the software reuse feature of the framework. The framework reuse architecture is more flexible and powerful than other reuse techniques such as components and patterns. A companion paper presen.
SITAR: a scalable intrusion-tolerant architecture for distributed services

This paper presents a intrusion tolerant architecture for distributed services, especially COTS servers. An intrusion tolerant system assumes that attacks will happen, and some will be successful. However, a wide range of mission critical applications need to provide continuous service despite active attacks or partial compromise. The proposed architecture emphasizes on continuity of operation. It strives to mitigate the effects of both known and unknown attack. We make use techniques of fault tolerant computing, specifically redundancy, diversity, acceptance test, textitvoting—, as well as adaptive reconfiguration. Our architecture consists of five functional components that work together to extend the fault tolerance capability of COTS servers. In addition, the architecture provides mechanisms to audit the COTS servers and internal components for signs of compromise. The auditing as well as adaptive reconfiguration components evaluate the environment threats, identify potential sources of compromise and adaptively generate new configurations for the system.
AI-Enabled Framework for Fog Computing Driven E-Healthcare Applications

Artificial Intelligence (AI) is the revolutionary paradigm to empower sixth generation (6G) edge computing based e-healthcare for everyone. Thus, this research aims to promote an AI-based cost-effective and efficient healthcare application. The cyber physical system (CPS) is a key player in the internet world where humans and their personal devices such as cell phones, laptops, wearables, etc., facilitate the healthcare environment. The data extracting, examining and monitoring strategies from sensors and actuators in the entire medical landscape are facilitated by cloud-enabled technologies for absorbing and accepting the entire emerging wave of revolution. The efficient and accurate examination of voluminous data from the sensor devices poses restrictions in terms of bandwidth, delay and energy. Due to the heterogeneous nature of the Internet of Medical Things (IoMT), the driven healthcare system must be smart, interoperable, convergent, and reliable to provide pervasive and cost-effective healthcare platforms. Unfortunately, because of higher power consumption and lesser packet delivery rate, achieving interoperable, convergent, and reliable transmission is challenging in connected healthcare. In such a scenario, this paper has fourfold major contributions. The first contribution is the development of a single chip wearable electrocardiogram (ECG) with the support of an analog front end (AFE) chip model (i.e., ADS1292R) for gathering the ECG data to examine the health status of elderly or chronic patients with the IoT-based cyber physical system (CPS). The second proposes a fuzzy-based sustainable, interoperable, and reliable algorithm (FSIRA), which is an intelligent and self-adaptive decision-making approach to prioritize emergency and critical patients in association with the selected parameters for improving healthcare quality at reasonable costs. The third is the proposal of a specific cloud-based architecture for mobile and connected healthcare. The fourth is the identification of the right balance between reliability, packet loss ratio, convergence, latency, interoperability, and throughput to support an adaptive IoMT driven connected healthcare. It is examined and observed that our proposed approaches outperform the conventional techniques by providing high reliability, high convergence, interoperability, and a better foundation to analyze and interpret the accuracy in systems from a medical health aspect. As for the IoMT, an enabled healthcare cloud is the key ingredient on which to focus, as it also faces the big hurdle of less bandwidth, more delay and energy drain. Thus, we propose the mathematical trade-offs between bandwidth, interoperability, reliability, delay, and energy dissipation for IoMT-oriented smart healthcare over a 6G platform.
Inter-Party Competition, Public Electoral Pressure, and Democratic Strength: Refining Political Explanations of Incarceration Trends in the U.S., 1980 – 2010

The purpose of this research is to advance the politics of mass imprisonment literature by testing and specifying the macro-explanations of the state-level incarceration change in the United States (U.S.) between 1980 and 2010. Specifically, I account for mechanisms of inter-party competition and public electoral pressure neglected in prior research. To accomplish this goal, I utilize random coefficient models designed to control for repeated annual measures of state-level data that overwhelm traditional analytic techniques. Findings suggest that violent crime, partisan affiliation of state legislators and governors, probation rates, citizen ideology, marijuana decriminalization, and recidivist-focused laws are associated with incarceration as hypothesized, as well as the African American presence net of crime and socioeconomic disadvantage. Contributing to the theoretical debates on democracy and punishment, this paper demonstrates that inter-party competition and public electoral pressure amplify incarceration in the context of Democratic Party dominance, where no liberalizing effects of competition were found. I conclude that legal and extralegal factors are associated with incarceration and suggest that the public did not oppose criminal justice expansion via democratic feedback mechanisms, so both penal populism (Pratt, 2008) and popular punitivism (Campbell et al., 2017) are valid interpretations of imprisonment politics during the analyzed period.
Form grinding of helical gears: effects of disk shaped tools plunging

Following the example of aerospace transmissions producers, nowadays, more and more industrial fields are interested in reducing transmission noise and vibration and in increasing operating life. This requires a precise understanding of the real transmission behavior since the first steps of the design process. The usual approach is to apply theoretical meshing loads and to compute web, rim and supporting structures deflections by one of the several available methods (i.e. Finite Element Method), in order to predict stresses and deformations. But these calculations usually neglect that deformations modify gear meshing conditions, and therefore also load conditions can be very different from the theoretical ones. In order to realize models that simulate the contact between the actual tooth surfaces, taking into account the actual gear meshing conditions, we first need to know the gear tooth flank microgeometry. Also the experimental development phase of gear pairs could take advantage from a theoretical prediction of gear tooth flank micro-geometry, in order to minimize the necessary trials to set up the grinding machine. In this paper, a method and a software to compute the actual micro-geometry of ground tooth flank surfaces of helical gears is presented. In particular the grinding process by means of disk shaped tools has been studied. The effects of the choice of various parameters (especially the angle between the gear and the tool axis) have been investigated. The effects of tool plunging during its motion along the gear face have also been considered in order to appreciate the undesired modifications of tooth transverse and normal sections, caused by the particular shape of the instantaneous contact lines between the grinding wheel and the gear tooth flank being ground. The introduction of a new component of the tool relative velocity with respect to the gear, in fact, modifies the meshing conditions between the gear and the tool. The modification of the tool axis orientation, during the grinding operation, reduces this undesired effect. As a result of these calculations, the exact theoretical surface for more realistic meshing simulation is available, and, furthermore, the run of some simulations can give some helpful hints to set up the grinding machine and to design the grinding wheel. © 2003 ASME
Application of artificial neural network to discrimination of defect type in automatic radiographic testing of welds

The X-ray radiographic testing method is often used for detecting weld defects as a non-destructive testing method (NDT). Due to the difficulties in identifying small defects from the X-ray film, skilled laborers should be trained. However, recently it has been difficult to employ skilled laborers. Moreover, for the identification process, not only the laborers skill influence the testing result, but also it is difficult for skilled laborers to assess small flaws within a short time. In comparison, computer visual image processing system have some good characteristics, allowing objective assessment, high speed judgment, non-human's error etc. Therefore, an image processing system allows weld defects to detect using X-ray radiography in the presence of background noise. This paper deals with an image processing method for displaying defects by computer graphics. Furthermore an application of neural network to discriminate the type of defect was tried. As the result of the investigation, it was seen that the system constructed is effective to the detection and discrimination of small weld defects clearly.
Numerical Simulation of Autorotation in Forward Flight

Autorotation in forward flight is an important subject for gyroplanes or compound helicopters. By integrating the flapping and rotational equations of motion, we investigate in this work the steady-state autorotation of a three-bladed rotor for a given set of three independent variables: forward velocity, collective pitch angle, and shaft angle. Two-dimensional aerodynamic coefficients as functions of the angle of attack and the Reynolds number from the Navier-Stokes simulation and Pitt/Peters inflow model to determine induced flowfield are adopted to implement the simulation. Transient behavior of the solution from arbitrary initial conditions to a steady-state periodic solution is described. Variations of rotor speed and flapping angle of autorotation with the shaft angle and the collective pitch angle for a given forward velocity are presented and discussed in detail. Drastic changes in the region of autorotation near a specific shaft angle is found to exist, below which the range of collective pitch angle for stable autorotation becomes very limited and the flapping angle changes abruptly with the pitch angle.
Human Interaction With Multiple Remote Robots

In this chapter, I review research involving remote human supervision of multiple unmanned vehicles (UVs) using command complexity as an organizing construct. Multi-UV tasks range from foraging, requiring little coordination among UVs, to formation following, in which UVs must function as a cohesive unit. Command complexity, the degree to which operator effort increases with the number of supervised UVs, is used to categorize human interaction with multiple UVs. For systems in which each UV requires the same form of attention (O(n)), effort increases linearly with the number of UVs. For systems in which the control of one UV is dependent upon another (O(>n)), additional UVs impose greater than linear increases due to the expense of coordination. For other systems, an operator interacts with an autonomously coordinating group, and effort is unaffected by group size (O(1)). Studies of human/multi-UV interaction can be roughly grouped into O(n) supervision, involving one-to-one control of individual UVs, or .
The effect of body roll on hand speed and hand path in front crawl swimming - a simulation study

The aim of this study was to predict the effect of body roll on hand speed and hand path during the pull phase in front crawl swimming. An earlier three-segment model (Hay, Liu, & Andrews, 1993) was developed to enable the hand to move out of the plane through the shoulder parallel to the sagittal plane of the rotating trunk. Elbow flexion, shoulder abduction, and body roll angular velocities were modeled as sine or cosine functions. For a given elbow flexion, an increase in maximum body roll from 45° to 60° produced a marked increase in medial hand motion. For a given body roll, an increase in maximum elbow flexion from 60° to 90° increased medial hand motion and reduced downward hand motion. An increase in body roll increased hand speed in the plane perpendicular to the swimming direction, thus increasing the potential of the hand to develop propulsive lift forces.
Low-order network equivalents for electromagnetic transients studies

Network equivalents can be used to represent parts of a power system to reduce the complexity and the computation time during the simulation of electromagnetic transients. The goal is to simplify the representation while preserving the accuracy of transients in the remainder. First, equations for the subnetwork of interest are stated in the frequency domain using network admittance functions. For cases of practical interest, it is shown that these can be approximated by low-order rational functions using an existing, proven optimization technique of control system engineering. Finally, the Electromagnetic Transients Program (EMTP) has been modified to permit the direct representation of such equivalents, which can be efficiently used for switching surge and fault studies. A detailed numerical example illustrates accuracy and efficiency of the new procedure.
Exploring Data Mining and Aided Diagnosis System of Hepatopathy

Chronic viral hepatitis, especially viral hepatitis B (HBV), has become a widespread infectious disease in the world. China is a big power of country in HBV, and people infected in China are the largest repository of HBV, which provides extensive research resources. The Data Mining and Aided Diagnosis System of Hepatopathy (DMADSH) embarks from the clinical situations and actual needs, combines the medical knowledge with computer data comprehensive analysis and mining technology, and through the knowledge extraction of the vast amounts of patient clinical data, image characteristics, location and shape of lesion, it gets the classification of hepatitis lesions and diagnosis automatically, so as to diagnose early to liver cancer and liver cirrhosis, and support for long-term dynamic monitoring in patients of hepatopathy and other health purposes.
Receivers with improved performance in the presence of co-channel interference based on the wavelet transform

We present the co-channel interference mitigation in the time-scale domain (CIMTS) algorithm which estimates the signal of interest (SOI) and the interfering signal from their superposition in the presence of additive noise. This method is inspired by the reconstruction of the interference from the null space of the SOI in the time-scale domain. Once the null space of the SOI is determined, the interfering signal is reconstructed via a set of linear operations. Then, the SOI is estimated by a simple subtraction of the estimated interference from the observations. <<ETX>>
Characterisation of optical properties of solar nanofluids by an inverse problem based on a numerical model

Some nanoparticles (NPs) possess an outstanding photothermal conversion under optical illumination. For this reason, these NPs are under research in a wide variety of light-induced heating applications such as solar nanofluids, which could be used for direct light absorption in solar collectors. Experimental characterisation of solar nanofluids for their application to light-to-heat conversion processes requires a considerable amount of resources to determine the properties of this mixture, at the nanoscale level. On this ground, an inverse problem based on a high-frequency and light-to-heat finite element model is proposed in the present work to numerically predict the optical properties of these nanofluids. In particular, a cost function based on a L2 norm is formulated to compare experimental measurements and numerical predictions. Then, this function is minimised by means of heuristic techniques –specifically, genetic algorithms- and the desired properties can be determined. In conclusion, the current work presents a numerical tool that could help in the characterisation of properties of solar nanofluids and contribute to reduce the number of experiments to be conducted for this purpose.
Disentangling factors in the placement of manner adverbials in German: The effect of distributional similarity

Processing differences between obligatory constituents like verbal complements and facultative ones like adjuncts are widely discussed in psycholinguistics. But the relative positional and semantic variability of adjuncts makes analyzing these differences a daunting challenge. Focusing on the intricate problem of the default position of manner adverbials in German, we present a re-analysis of a recent psycholinguistic study on their ordering preferences in which we explore the extent to which similarities between word embeddings can be used as stand-ins for shared semantic memory, representing the probability of seamless conceptual combination. In re-analyzing six experiments across different paradigms, the addition of the new predictors yields substantially better models which show that these factors considerably interact with established lexical and grammatical predictors.
ESCALA DE MIEDO AL COVID-19 (FCV-19S): PROPIEDADES PSICOMÉTRICAS E INVARIABILIDAD DE LA MEDIDA EN LA VERSIÓN ESPAÑOLA

Introduction. The emergence of COVID-19 worldwide has had serious consequences for physical and psychological health. Spain is one of the countries that has been most-seriously affected by the pandemic. This study aims to evaluate the psychometric properties of the Spanish version of the COVID-19 fear scale (FCV-19S), assessing its structural validity, differential item functioning, and measurement invariance by gender and age.