Miracle-dz/UniFAR-FTUs huggingface dataset:
Nukleäre Rezeptoren beim hepatischen und intestinalen Medikamententransport

Die Bioverfügbarkeit von Pharmaka hängt vom Ausmaß der Resorption im Darm, der Biotransformation und dem Eliminationsweg ab. Die Resorption im Darm erfolgt über Transportproteine der Lamina epithelialis mucosae. Die Biotransformation beginnt bereits in intestinalen Epithelzellen und die aufgenommenen Xenobiotika werden über Effluxpumpen der basalen oder apikalen Membran in die Blutbahn bzw. zurück in das Darmlumen abgegeben [1]. Das Pfortaderblut erreicht die basolaterale (sinusoidale) Hepatozytenmembran, die ihrerseits mit multiplen Transportsystemen ausgestattet ist. Xenobiotika werden in unterschiedlichem Ausmaß von Hepatozyten aufgenommen und in Phase-I/II-Reaktionen biotransformiert. Die entstandenen polaren Medikamentenmetaboliten können über Effluxpumpen der basolateralen oder kanalikulären (apikalen) Hepatozytenmembran in das venöse Blut bzw. in die Galle ausgeschieden werden.
A New Method to Recognize Unfertilized Egg in Early Incubation Stage

In order to achieve higher recognition rate of unfertilized eggs, the paper proposes a new method based on the area feature of egg's vertical image and the classifier BP network. The eggs hatched 2-5 days are selected as the experiment objects in our study. Four kinds of feature, including the gray feature and the area feature extracted from the egg's vertical image and the egg's horizontal image, respectively, are sent to BP network to accomplish the recognition of unfertilized eggs. The experiment results indicate that the area feature of egg's vertical image contains more category information, and this kind of feature classified by BP network can reach 97.86% of recognition rate. Moreover, it is almost free from some external factors, such as light, camera, eggshell and the parameters of BP network. While the other features sent to BP network, the recognition rate can be reached to only 86.43%. This study provides an effective and useful method to recognize unfertilized egg in early incubation stage.
Robust Control for Ship Course-Keeping Based on Support Vector Machines: Particle Swarm Optimization and L2-Gain

To achieve a robust autopilot for ship course-keeping, a controller based on support vector machines (SVM) and L2-gain is proposed. A cascaded plant consists of a nonlinear ship response model and the rudder actuator dynamics. Uncertainties including modeling errors and external disturbances are taken into account in the response model. SVM is applied to identify the complicated nonlinear dynamics including the modeling errors, while L2-gain design is used to suppress the uncertain disturbances. To obtain the optimized structural parameters in SVM, particle swarm optimization (PSO) method is incorporated. Stability analysis and simulation results demonstrate the validity of the proposed control scheme.Copyright © 2013 by ASME
Intra-Cluster Multihop Routing in LEACH Based on Shortest Distance

In this paper we propose Intra Cluster Routing Shortest Distance-Low Energy Adaptive Clustering Hierarchy protocol (ICRSD-LEACH) that addresses inefficient energy distribution and dissipation in the Wireless Sensor Networks resulting in reduced network lifetime and communication efficiency. The proposed routing protocol performs intra-cluster multi hope routing to reduce communication cost. However, cluster formation, randomized rotation of cluster heads and data fusion in ICRSD-LEACH is similar to LEACH. Simulation results confirm that the proposed routing protocol reduces the communication cost which improves life time of network through intra cluster multi hoping and signified by prolonged lifetime of nodes which are far away from the base station.
When NEO meets the ORACLE: Predicting Collaboration and Movie Performance in IMDb

Hollywood is a billion dollar industry and a main source of recreat ion for millions throughout the world. It is also the source of income for many who are related to the industry in one way or the other. Both these set of people wants the movie watcher to enjoy the movie being watched. An enjoyable movie is what the movie goer wants as a value for money. The benefit for the production crew with well-made movie is not just the profit, but also the fame that they get when movie goers appreciate the movie. But what is it that makes a movie enjoyable, at the same time successful at the box office and an award winner? Does the nodal closeness to highly acclaimed directors or actors make the movie a success? What if the acclaimed actor who would fit in a particular role is not available. Can a system help the producer/ director in finding a new replacement for the cast? We try to answer all these questions with a bunch of experiments we conducted on a dataset from IMDb. We model each movie as a s mall network of production crew consisting of actors, directors, producers etc., and apply theories of Lin k Prediction and Node Centrality. We co mpare various lin k predictor metrics to find the best performing predictor on training and test IMDb dataset. Link Prediction serves as a technique to find suitable replacements for production crew. We also compare various metrics to determine if s mall geodesic distance of the cast in a mov ie to acco mplished actors increases the probability of the movie winning an award. We also determine if the performance of a proposed movie can be predicted by how close by their centrality measures are to highly acclaimed production crew nodes. Author Keywords Movie rating prediction, similarity score, node centrality, link prediction
Integer programming models and analysis for a multilevel passenger screening problem

Designing effective aviation security systems has become a problem of national interest and concern. Passenger prescreening is an important component of aviation security. Effectively using passenger prescreening information to develop screening strategies can be quite challenging. Moreover, it can be difficult to measure the effectiveness of such systems after they are in place. To address these issues, this paper introduces the Multilevel Passenger Screening Problem (MPSP). In MPSP, a set of classes are available for screening passengers, each of which corresponds to several device types for passenger screening, where each device type has an associated capacity and passengers are differentiated by their perceived risk levels. The objective of MPSP is to use prescreening information to determine the passenger assignments that maximize the total security subject to capacity and assignment constraints. MPSP is illustrated with examples that incorporate flight schedule and passenger volume data extracted from the Official Airline Guide.
ARM Core Unit Design of a Remote Video Monitoring System

In this study, we have a analysis of the ARM core unit design of a remote video monitoring system. An important aspect of a remote video monitoring system is that the image information stored in the monitoring system is transmitted to a remote PC through the GSM/GPRS network. There into the application of the ARM core unit is one part of the design of the entire remote video monitoring system. An ARM core unit is designed based on ARM architecture and ARM chips. It includes hardware and software design. Practice shows high stability and reliability of the design.
Multi-layered Urban Strategies to Foster the Smart Cities Development

In the last decade, the Smart City model has emerged as a reference concept in shaping the city of the future, mainly by strengthening the connections between grids, Information and Communications Technologies (ICT), governance and people. In this framework, architecture and the building scale seem to be left in the background, as a residual aspect compared to the role that grids and ICT are expected to play. However, the integrated design at building and district scale is an ineluctable backbone of the implementation process, allowing further actions to achieve effective and innovative paths toward a smarter city. The paper aims to point out the interrelations between the Smart City concept and the key parameters needed to manage complex urban environment in real conditions. An on-going research activity lead in the city of Bologna is summarized, in which the cooperation between the Municipality, the Department of Architecture, local stakeholders and companies is aimed at combining hardware and software more effectively. The goal is to bridge the gap between physical and virtual components, by setting methods and tools to couple technical aspects with socio-economic issues that usually feed the renovation processes. It means creating a tool able to provide and manage information concerning the interactions between the buildings within the district and the urban fabric at city level. The tool must perform the integration between ICT and conventional building components, by collecting data, mapping relations and identifying both conflicts and synergies. A layered structure is defined in order to cover the most influencing parameters as well as key crosscutting issue that may influence the smart city development and effectiveness. The expected benefits mainly concern public administration and policy makers, to which the tool may provide a support in maximizing the impacts and the exploitation potential of the innovations at city level.
Noncontact heart rate monitoring using Doppler radar and continuous wavelet transform

An algorithm based on wavelet transform is utilized in detecting and examining the heartbeat signal obtained from a Doppler radar.Time–frequency localization properties of wavelet transform were used to examine the signal and provided detail of swift and slow changes in heart rate over very small periods resulting in better determination of the accuracy of the Doppler radar. Till 1 m, a very accurate and robust performance was observed for the Doppler radar. Even at 2‐m heart rate was detectable but not with reasonable accuracy. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26092
CAN MUSCLE ACTIVATION BE INCREASED WHEN MODIFYING THE DUMBBELL CHEST PRESS? AN ELECTROMYOGRAPHIC COMPARISON

The development of core stability is an important part of the athlete strength and conditioning process. Research has shown that when traditional resistance exercise is performed on a stability ball, core muscle surface electromyography (sEMG) is increased (Anderson & Behm, 2005). However, investigators have also demonstrated this can lead to a considerable reduction in agonist muscle sEMG (Behm & Anderson, 2006). It has been suggested that by replacing traditional bilateral resistance exercises with unilateral variations the reduction in agonist muscle sEMG associated with stability ball resistance exercise can be avoided (Behm & Anderson, 2006). However, this theory has not been tested on the chest press. Therefore, the aim of this study was to compare core and agonist sEMG during chest press performance to establish whether unilateral chest press exercise would increase core sEMG without compromising agonist sEMG.
Wpływ pandemii COVID-19 na codzienną mobilność mieszkańców Warszawy

The main purpose of this article is to discuss the impact of COVID-19 pandemic on daily mobility of Warsaw residents. Another issue concerns how city residents perceive traffic congestion. The source basis are the results of studies, which were conducted on a purposively selected sample of 300 inhabitants of Warsaw, as well as the statistics data collected by Warsaw Roads Administration, Public Transport Authority and Statistical Office in Warsaw. The conducted study confirms and develops previous research and proves that urban mobility has been strongly impacted by the COVID-19 pandemic. The Warsaw road network is characterized by a high level of congestion and the most common reasons are: too many passenger cars and too low road network capacity to handle the flow.
IBM in the 21st Century: The Coming of the Globally Integrated Enterprise

In April 2008, members of IBM's fifth Integration and Values Team (IVT5), were close to finishing their deliberations. This high-powered group of high-level executives included country general managers from India and Brazil as well as vice presidents from businesses and functions, chosen from a group of about 300 leaders convened Chairman and CEO Sam Palmisano to view IBM holistically. Senior VP of Corporate Communications and Marketing, Jon Iwata, and the new head of Research, John E. Kelly III, were the executive sponsors, IVT5's focus was on "the global IBMer" defining and developing leaders for the global economy; making the "globally-integrated enterprise" relevant to all employees through global citizenship and the IBM values and culture; and ensuring market access in the form of a level playing field for IBM to compete globally. The scope was all 170 countries in which IBM operated. As leaders who had risen to their positions because they were globally-oriented systems thinkers who reflected IBM's emphasis on innovation, they knew that it was necessary to stand back to look at the big picture - to see how IBM worked now, to view IBM at its best, but also to understand the gaps, dilemmas and opportunities.
Model of metameric locomotion in smooth active directional filaments with curvature fluctuations

Locomotion in segmented animals, such as annelids and myriapods (centipedes and millipedes), is generated by a coordinated movement known as metameric locomotion, which can be also implemented in robots designed to perform specific tasks. We introduce a theoretical model, based on an active directional motion of the head segment and a passive trailing of the rest of the body segments, in order to formalize and study the metameric locomotion. The model is specifically formulated as a steered Ornstein-Uhlenbeck curvature process, preserving the continuity of the curvature along the whole body filament, and thus supersedes the simple active Brownian model, which would be inapplicable in this case. We obtain the probability density by analytically solving the Fokker-Planck equation pertinent to the model. We also calculate explicitly the correlators, such as the mean-square orientational fluctuations, the orientational correlation function and the mean-square separation between the head and tail segments, both analytically either via the Fokker-Planck equation or directly by either solving analytically or implementing it numerically from the Langevin equations. The analytical and numerical results coincide. Our theoretical model can help understand the locomotion of metameric animals and instruct the design of metameric robots.
Monopolar square patch antennas with wideband operation

The design of a wideband patch antenna with monopole-like conical radiation patterns is presented. The antenna has a square patch that is shorted to the ground plane through two shorting walls and is excited by a top-loaded coaxial feed centred below the square patch. Several prototypes with various antenna heights are implemented and measured. A prototype with impedance bandwidth of about 50% is achieved when its height is less than 0.09 free-space wavelengths.
Construction of a new class of generating functions of binary products of some special numbers and polynomials

In this paper, we derive some new symmetric properties of k-Fibonacci numbers by making use of symmetrizing operator. We also give some new generating functions for the products of some special numbers such as k-Fibonacci numbers, k-Pell numbers, Jacobsthal numbers, Fibonacci polynomials and Chebyshev polynomials.
General Inverse Design of Layered Thin-Film Materials with Convolutional Neural Networks

: The design of metamaterials which support unique optical responses is the basis for most thin-ﬁ lm nanophotonic applications. In practice, this inverse design (ID) problem can be di ﬃ cult to solve systematically due to the large design parameter space associated with general multilayered systems. We apply convolutional neural networks, a subset of deep machine learning, as a tool to solve this ID problem for metamaterials composed of stacks of thin ﬁ lms. We demonstrate the remarkable ability of neural networks to probe the large global design space (up to 10 12 possible parameter combinations) and resolve all relationships between the metamaterial structure and corresponding ellipsometric and re ﬂ ectance/transmittance spectra. The applicability of the approach is further expanded to include the ID of synthetic engineered spectra in general design scenarios. Furthermore, this approach is compared with traditional optimization methods. We ﬁ nd an increase in the relative optimization e ﬃ ciency of the networks with the increase in the total layer number, revealing the advantage of the machine learning approach in many-layered systems where traditional methods become impractical.
Enhanced Bayesian Factorization With Variant Scale Partitioning for Multivariate Time Series Analysis

Multivariate time series data (Mv-TSD) portray the evolving processes of the system(s) under examination in a “multi-view” manner. Factorization methods are salient for Mv-TSD analysis with the potentials of structural feature construction correlating various data attributes. However, research challenges remain in the derivation of factors due to highly scattered data distribution of Mv-TSD and intensive interferences/outliers embedded in the source data. The proposed Enhanced Bayesian Factorization approach (<italic>Enhanced-BF</italic>) addresses the challenges in three phases: (1) variant scale partitioning applies to Mv-TSD according to degree of amplitude and obtains the blocks of variant scales; (2) hierarchical Bayesian model for tensor factorization automatically derives the factors of each block with interferences suppressed; (3) Bayesian unification model merges those block factors to construct the final structural features. <italic>Enhanced-BF</italic> has been evaluated using a case study of brain data engineering with multivariate electroencephalogram (EEG). Experimental results indicate that the proposed method manifests robustness to the interferences and outperforms the counterparts in terms of operation efficiency and error when factorizing EEG tensor. Besides, <italic>Enhanced-BF</italic> excels in factorization-based analysis of ongoing autism spectrum disorder (ASD) EEG: 3 times speed-up in factorization and <inline-formula><tex-math notation="LaTeX">$87.35\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>87</mml:mn><mml:mo>. </mml:mo><mml:mn>35</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="chen-ieq1-3128770.gif"/></alternatives></inline-formula> accuracy in ASD discrimination. The latent factors (“biomarkers”) can distinctly interpret the typical EEG characteristics of ASD subjects.
Performance Analysis of Two-Stage Optimal Feature-Selection Techniques for Finger Knuckle Recognition

Automated biometric authentication attracts the attention of researchers to work on hand-based images to develop applications in forensics science. Finger Knuckle Print (FKP) is one of the hand-based biometrics used in the recognition of an individual. FKP is rich in texture, less in contact and known for its unique features. The dimensionality of the features, extracted from the image, is one of the main problems in pattern recognition. Since selecting the relevant features is an important but challenging task, the feature subset selection is an optimization problem. A reduced number of features results in enhanced classification accuracy. The proposed FKP system presents a mulitalgorithm fusion based on subspace algorithms at feature level fusion technique. In this paper, a new feature-selection algorithm, which is a Modified Magnetotatic bacterium Optimization Algorithm (MMBOA), is proposed for finger knuckle recognition to select relevant and useful features that increase the classification accuracy. The distinct characteristic of this bacterium influences the design of a new optimization technique. The hybrid features such as Eigen and Fisher (EiFi) are extracted from the finger knuckle. The fusion of this feature vector is optimized using newly proposed MMBOA_mr optimization algorithm. The results demonstrate a significant improvement compared with unimodal identifiers, and the proposed approach significantly outperforms with a recognition accuracy of 99.7% with 22 features with the reduction rate of 72%. Additionally, the proposed approach is compared with the state-of-the-art methods.
Modeling and control of a kite on a variable length flexible inelastic tether

This paper deals with the modeling of a tethered kite system. Such systems have the potential to generate power by driving a ground generator from winds at high altitude. To test the validity of controllers developed for the system, it is necessary to employ models of various sophistication. In this paper, the tether is modeled as a collection of point masses connected by inelastic rods. A simple procedure for efficiently determining the tension constraint forces is developed. The procedure used for deploying and retrieving the cable in the model is also presented. This entails the addition and subtraction of elements in the model. A simple feedback controller is derived to maneuver the kite in the cross-wind direction and for maintaining the tether tension at the desired level. The tether length is controlled to maintain the desired altitude of the kite. Numerical results demonstrate the effectiveness of the controller and efficiency of the tether model.
Effects of Drying Process on the Volatile and Non-Volatile Flavor Compounds of Lentinula edodes

In this study, fresh Lentinula edodes was dehydrated using freeze-drying (FD), hot-air drying (HAD), and natural drying (ND), and the volatile and non-volatile flavor compounds were analyzed. The drying process changed the contents of eight-carbon compounds and resulted in a weaker “mushroom flavor” for dried L. edodes. HAD mushrooms had higher levels of cyclic sulfur compounds (56.55 μg/g) and showed a stronger typical shiitake mushroom aroma than those of fresh (7.24 μg/g), ND (0.04 μg/g), and FD mushrooms (3.90 μg/g). The levels of 5′-nucleotide increased, whereas the levels of organic acids and free amino acids decreased after the drying process. The dried L. edodes treated with FD had the lowest levels of total free amino acids (29.13 mg/g). However, it had the highest levels of umami taste amino acids (3.97 mg/g), bitter taste amino acids (6.28 mg/g) and equivalent umami concentration (EUC) value (29.88 g monosodium glutamate (MSG) per 100 g). The results indicated that FD was an effective drying method to produce umami flavor in dried mushrooms. Meanwhile, HAD can be used to produce a typical shiitake mushroom aroma. Our results provide a theoretical basis to manufacture L. edodes products with a desirable flavor for daily cuisine or in a processed form.
Influences of the Temperature on the Electrical Properties of HfO2-Based Resistive Switching Devices

In the attempt to understand the behavior of HfO2-based resistive switching devices at low temperatures, TiN/Ti/HfO2/W metal–insulator–metal devices were fabricated; the atomic layer deposition technique was used to grow the high-k layer. After performing an electroforming process at room temperature, the device was cooled in a cryostat to carry out 100 current–voltage cycles at several temperatures ranging from the “liquid nitrogen temperature” to 350 K. The measurements showed a semiconducting behavior in high and low resistance states. In the low resistance state, a hopping conduction mechanism was obtained. The set and reset voltages increased when temperature decreased because the thermal energies for oxygen vacancies and ions were reduced. However, the temperature did not influence the power absorbed in the reset transition, indicating the local temperature in the filament controls the transition. The set transition turned from gradual to abrupt when decreasing the temperature, due to a positive feedback between the current increase and the Joule heating at low temperatures.