Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Growth and Differentiation of Human Fetal Osteoblasts (hFOB) Cells on Demineralized Bone Matrix (DBM)

ABSTRACT Cells with osteogenic potential are believed to be an ideal source for bone tissue bioengineering. Large bone defects require temporary substitution of the damaged parts. In this respect, the transplantation of bone cells cultured on osteogenic substrates has been investigated. To use the natural bone matrix, one approach is the so-called demineralized bone matrix (DBM). In this study, we evaluated the interaction of human fetal osteoblasts (hFOB 1.19 cells, a human fetal osteoblastic cell line) with DBM fragments. No additional bone differentiation inducer was used other than the DBM itself. The samples were processed, had adhesion pattern evaluated and analyzed by light microscopy (cytochemical and immunocytochemical analysis) and electron microscopy (scanning and transmission). The adhesion pattern of hFOB cells on DBM was similar to what was observed on the cell culture plate. Morphological analysis showed that the hFOB cells had emitted filopodia and cellular projections on both controls and DBM. On DBM, the adhered cells emitted prolongations and migrated into the matrix. The monolayer growth pattern was observed as well as the accumulation of filamentous and reticulate extracellular materials when hFOB cells were cultured on the DBM surface. EDS analysis revealed the deposition of calcium on DBM. Immunocytochemical data showed that the hFOB cells were able to secrete extracellular matrix molecules such as fibronectin and laminin on DBM. Our data indicate that DBM successfully stimulates the osteoblastic phenotype of osteoblast-like cells and corroborate with the fact that DBM is a considerable natural matrix that promotes fractured-bone healing.
Voltage transformer ferroresonance in 275 kV substation

The ferroresonant behaviour of a 275 kV electromagnetic voltage transformers, fed from a sinusoidal supply via circuit breaker grading capacitance, in a National Grid substation in analysed using nonlinear bifurcation diagrams representing system behaviour have been presented showing two possible types of operation, normal response and fundamental frequency ferroresonance, in line with practical site experience.
Exploring the Effect of High-frequency Components in GANs Training

Generative Adversarial Networks (GANs) have the ability to generate images that are visually indistinguishable from real images. However, recent studies have revealed that generated and real images share significant differences in the frequency domain. In this article, we argue that the frequency gap is caused by the high-frequency sensitivity of the discriminator. According to our observation, during the training of most GANs, severe high-frequency differences make the discriminator focus on high-frequency components excessively, which hinders the generator from fitting the low-frequency components that are important for learning images’ content. Then, we propose two simple yet effective image pre-processing operations in the frequency domain for eliminating the side effects caused by high-frequency differences in GANs training: High-frequency Confusion (HFC) and High-frequency Filter (HFF). The proposed operations are general and can be applied to most existing GANs at a fraction of the cost. The advanced performance of the proposed operations is verified on multiple loss functions, network architectures, and datasets. Specifically, the proposed HFF achieves significant improvements of 42.5% FID on CelebA (128*128) unconditional generation based on SNGAN, 30.2% FID on CelebA unconditional generation based on SSGAN, and 69.3% FID on CelebA unconditional generation based on InfoMAXGAN. Furthermore, we also adopt HFF as the first attempt at data augmentation in the frequency domain for contrastive learning, achieving state-of-the-art performance on unconditional generation. Code is available at https://github.com/iceli1007/HFC-and-HFF.
Convergence rates in the functional CLT for alpha-mixing triangular arrays

We obtain convergence rates (in the Levi-Prokhorove metric) in the functional central limit theorem (CLT) for partial sums S n = P nj =1 ξ j,n of triangular arrays { ξ 1 ,n ,ξ 2 ,n ,. ,ξ n,n } sat- isfying some mixing and moment conditions (which are not necessarily uniform in n ). For certain classes of additive functionals of triangular arrays of contracting Markov chains (in the sense of Do- brushin) we obtain rates which are close to the best rates obtained for independent random variables. In addition, we obtain close to optimal rates in the usual CLT and a moderate deviations principle and some Rosenthal type inequalities. We will also discuss applications to some classes of local statistics (e.g. covariance estimators), as well as expanding non-stationary dynamical systems, which can be reduced to non-uniformly mixing triangular arrays by an approximation argument. The main novelty here is that our results are obtained without any assumptions about the growth rate of the variance of S n . The result are obtained using a certain type of block decomposition, which, in a sense, reduces the problem to the case when the variance of S n is “not negligible” in comparison with the (new) number of summands.
Direct assessment of parameter sensitivity in multivariable closed-loop control systems

A signal convolution method of calculating parameter sensitivity functions is being developed as the basis for a controller optimisation scheme for multivariable control systems. The signals to be convolved in this direct assessment method of parameter sensitivity analysis are obtained directly from the system. This paper details the theory of the signal convolution method in the multivariable case and the results which have been obtained in simulation studies for a helicopter flight control system. These studies have led to conclusions concerning the suitability of the method for use in controller optimization, particularly in the context of system commissioning tests.
Crossroads between membrane trafficking machinery and copper homeostasis in the nerve system

Imbalanced copper homeostasis and perturbation of membrane trafficking are two common symptoms that have been associated with the pathogenesis of neurodegenerative and neurodevelopmental diseases. Accumulating evidence from biophysical, cellular and in vivo studies suggest that membrane trafficking orchestrates both copper homeostasis and neural functions—however, a systematic review of how copper homeostasis and membrane trafficking interplays in neurons remains lacking. Here, we summarize current knowledge of the general trafficking itineraries for copper transporters and highlight several critical membrane trafficking regulators in maintaining copper homeostasis. We discuss how membrane trafficking regulators may alter copper transporter distribution in different membrane compartments to regulate intracellular copper homeostasis. Using Parkinson's disease and MEDNIK as examples, we further elaborate how misregulated trafficking regulators may interplay parallelly or synergistically with copper dyshomeostasis in devastating pathogenesis in neurodegenerative diseases. Finally, we explore multiple unsolved questions and highlight the existing challenges to understand how copper homeostasis is modulated through membrane trafficking.
Preparing for Class: Actions and Resources of Introductory Biology Students

Instructors want students to be prepared for class. There are several different resources and activities available to help students prepare for class, but very little is known about how students choose to prepare for class in the context of undergraduate biology. ABSTRACT Instructors want students to be prepared for class. There are several different resources and activities available to help students prepare for class, but very little is known about how students choose to prepare for class in the context of undergraduate biology. In this study, we used content analysis to investigate what students do to prepare for an introductory biology course and if and how that preparation differed under two different conditions. Students were either directed to search out and choose their resources to prepare for class (choice treatment) or assigned specific pages from a textbook (text treatment). Students in the choice treatment reported preparing for class slightly more often than students in the text treatment, with both groups reporting that they prepared for over three-quarters of classes. However, students assigned specific textbook passages engaged more while preparing than students who had to find their resources. The textbook was a popular resource but second to websites for students who got to choose. Students in both groups performed similarly in the course. This work helps instructors understand what their students may be doing to prepare for class. We provide recommendations to guide instructors on how to help their students prepare for class.
A Novel Method of Ship Detection from Spaceborne Optical Image Based on Spatial Pyramid Matching

In this paper we propose an automatic ship detection method in High Resolution optical satellite images based on neighbor context information. First, a pre-detection of targets gives us candidates. For each candidate, we choose an extended region called candidate with neighborhood which comprises candidate and its neighbor area. Second, the patches of candidate with neighborhood are got by a regular grid, and their SIFT(Scale Invariant Feature Transform) features are extracted. Then the SIFT features of training images are clustered with the K-means algorithm to form a codebook of the patches. We quantize the patches of candidate with neighborhood according to this codebook and get the visual word representation. Finally by applying spatial pyramid matching, the candidates are classified with SVM (support vector machine). Experiment results are given for a set of images show that our method has got predominant performance.
DC induction heating of aluminum billets using superconducting magnets

Purpose – To analyse the heating process of an aluminum billet rotating in a static magnetic field produced by superconducting coils.Design/methodology/approach – The idea is to force the billet to rotate in a static magnetic field produced by a DC superconducting magnet. Since, a static superconducting magnet has no losses, the efficiency of the system is the efficiency of the motor used. In order to evaluate the temperature distribution arising from the field profile produced by a given coil configuration, a numerical model, based on an equivalent electric network with temperature‐dependent parameters, is used.Findings – The main heating parameters, i.e. heating time, total power injected and temperature difference, are evaluated for different values of angular velocity and magnetic field. The field profile suitable to meet the specifics of an industrial heating process in terms of temperature homogeneity and heating time is determined. Starting form this profile the layout of the magnet is arrived at a.
A comparison between different PMD compensation techniques

We quantify the benefits of using different techniques for compensation of polarization mode dispersion (PMD) in fiber-optic communication systems by means of numerical simulations. This is done both with respect to PMD-induced pulse broadening and in terms of system outage probability for different data formats [nonreturn-to-zero (NRZ) and return-to-zero (RZ)]. Attention is focused on simple and relevant single- and double-stage post-transmission compensators with a few degrees of freedom (DOF). It is generally believed that a PMD compensator with a polarization controller and a variable delay line can only compensate the PMD to the first order. We show, from analytical results, the counterintuitive fact that this scheme can also partially compensate for higher order PMD. We also investigate the benefit of using a polarizer as compensation element where the optical average power can be used as a feedback signal.
Adopting Importance Performance Analysis to Explore the Relationship between Service Quality and Customer Satisfaction in Dried Pork Market

Building on prior research, service quality is typically deemed that customers’ perception of purchasing importance would possibly influence on their satisfaction. However, very little research has been measured the difference between the customer importance and satisfaction. This study was to provide a picture of how service quality influences on customer satisfaction through dried pork market in central Taiwan. This study consists of four parts in questionnaires including customer information, customer importance, and customer satisfaction. Findings demonstrated that the differences between customer importance and customer satisfaction of service quality. This study predicts by considering implications for the management of the service quality process and identifying future research directions.
HapticPanel: An Open System to Render Haptic Interfaces in Virtual Reality for Manufacturing Industry

Virtual Reality (VR) allows simulation of machine control panels without physical access to the machine, enabling easier and faster initial exploration, testing, and validation of machine panel designs. However, haptic feedback is indispensable if we want to interact with these simulated panels in a realistic manner. We present HapticPanel, an encountered-type haptic system that provides realistic haptic feedback for machine control panels in VR. To ensure a realistic manipulation of input elements, the user’s hand is continuously tracked during interaction with the virtual interface. Based on which virtual element the user intends to manipulate, a motorized panel with stepper motors moves a corresponding physical input element in front of the user’s hand, enabling realistic physical interaction.
Analysis of Detection Thresholds for Hand Redirection during Mid-Air Interactions in Virtual Reality

Avatars in virtual reality (VR) with fully articulated hands enable users to naturally interact with the virtual environment (VE). Interactions are often performed in a one-to-one mapping between the movements of the user’s real body, for instance, the hands, and the displayed body of the avatar. However, VR also allows manipulating this mapping to introduce non-isomorphic techniques. In this context, research on manipulations of virtual hand movements typically focuses on increasing the user’s interaction space to improve the overall efficiency of hand-based interactions. In this paper, we investigate a hand retargeting method for decelerated hand movements. With this technique, users need to perform larger movements to reach for an object in the VE, which can be utilized, for example, in therapeutic applications. If these gain-based redirections of virtual hand movements are small enough, users become unable to reliably detect them due to the dominance of the visual sense. In a psychophysical experiment, we analyzed detection thresholds for six different motion paths in mid-air for both hands. We found significantly different detection thresholds between movement directions on each spatial axis. To verify our findings, we applied the identified gains in a playful application in a confirmatory study.
Fusing Semantic Segmentation and Object Detection for Visual SLAM in Dynamic Scenes

The assumption of static scenes limits the performance of traditional visual SLAM. Many existing solutions adopt deep learning methods or geometric constraints to solve the problem of dynamic scenes, but these schemes are either low efficiency or lack of robustness to a certain extent. In this paper, we propose a solution combining object detection and semantic segmentation to obtain the prior contours of potential dynamic objects. With this prior information, geometric constraints techniques are utilized to assist with removing dynamic feature points. Finally, the evaluation with the public datasets demonstrates that our proposed method can improve the accuracy of pose estimation and robustness of visual SLAM with no efficiency loss in high dynamic scenarios.
The Impact of Increase of Cigarette Expension on Net Income in Income Statements

The Indonesian government decided to increase the excise tax on tobacco products by 23% starting January 1, 2020. The performance of cigarette manufacturers was affected by government policies that increased cigarette excise or tobacco product excise which had an impact on the growth of cigarette issuers' income. This study aims to analyze the impact of the increase in cigarette excise on net income at PT. Gudang Garam Tbk. This type of research in this research is descriptive with a qualitative approach. The results of this research show that the increase in cigarette excise has an effect on net income at PT. Gudang Garam Tbk. PT Gudang Garam Tbk's Profit and Loss Report shows an increase in all aspects, both sales, gross profit and net income even though the government policy regarding the increase in cigarette excise rates has been implemented as of January 1, 2020. This reflects that PT Gudang Garam has implemented a good strategy in maintaining profitability of the company. Business of PT. Gudang Garam Tbk, is still supported by sales of the machine-made kretek cigarette (SKM) segment, which contributed 91.25 percent to the company's revenue.
Rethinking Protein Drug Design with Highly Accurate Structure Prediction of Anti-CRISPR Proteins

Protein therapeutics play an important role in controlling the functions and activities of disease-causing proteins in modern medicine. Despite protein therapeutics having several advantages over traditional small-molecule therapeutics, further development has been hindered by drug complexity and delivery issues. However, recent progress in deep learning-based protein structure prediction approaches such as AlphaFold opens new opportunities to exploit the complexity of these macro-biomolecules for highly-specialised design to inhibit, regulate or even manipulate specific disease-causing proteins. Anti-CRISPR proteins are small proteins (<100 amino acids) from bacteriophages that counter-defend against the prokaryotic adaptive immunity of CRISPR-Cas systems. They are unique examples of natural protein therapeutics that have been optimized by the host-parasite evolutionary arms race to inhibit a wide variety of host proteins. Here, we show that these Anti-CRISPR proteins display diverse inhibition mechanisms through accurate structural prediction and functional analysis. We find that these phage-derived proteins are extremely distinct in structure, some of which have no homologues in the current protein structure domain. Furthermore, we find a novel family of Anti-CRISPR proteins which are structurally homologous to the recently-discovered mechanism of manipulating host proteins through enzymatic activity, rather than through direct inference. Using highly accurate structure prediction, we present a wide variety of protein-manipulating strategies of anti-CRISPR proteins for future protein drug design.
Value Strategies in Trading Derivatives: Theories and Practice in Forwards, Futures and Options

Investors can use different kinds of investment strategies when making derivative investments. Although China has a large number of investors, Chinese derivatives market is still a developing market, there are many different kinds of trading strategies that are worth considering whether they can fit in this developing market. Based on value investment style, this paper applies different kinds of strategies to currencies, commodities and options respectively, and for each asset, this paper did research on their discretionary trading models, systematic trading models and advanced models respectively. Through measuring the return from the back test of each investment strategy, this paper made investment conclusion and gave recommendations on Chinese derivatives market. CCS Concepts: Social and professional topics-Professional topics-Computing and business-Economic impact
Mathematical Model for the Optimization of the Airport Self-Service Kiosks System

This paper studied the effectiveness of airports self-service kiosks by using the data analysis. The queuing systems taking place in various service situations in our daily life. Reasonable use of queuing theory can significantly improve the efficiency of the queuing system and system performance. The service system, queuing system and queuing model is suggested. The queuing theory in the area of service science, the corresponding mathematical model of the airport self-check-in system is established. After analyzing the collected data, it is conclude that the overall proportion of time that the kiosk is idle is quite high at the Vienna airport, especially during the weekdays. Furthermore, the suggestions for the airport selfservice system are offered.
A square-diaphragm piezoresistive pressure sensor with a rectangular central boss for low-pressure ranges

Describes the theory and experimental data for a piezoresistive low-pressure sensor featuring a variety of advantages. The objective of this development was a sensor with high sensitivity, high overload range, and good linearity. In comparison to familiar sensor types, the sensor developed for the pressure range of 10 kPa exhibits an excellent sensitivity of 35 mV/V FSO (full scale output) and nonlinearity >
Growth and carcass characteristics of lambs sired by Texel, Oxford Down and Suffolk rams

Three hundred and twelve lambs (160 ram, 152 ewe) sired by Texel (n = 118), Oxford Down (n = 94) and Suffolk (n = 100) rams and out of Romney ewes were grazed at Poukawa Research Station, Hastings, to evaluate comparative growth characteristics and carcass composition. Lambs were sourced from a range of commercial properties and sires. Representative samples from each breed and sex were slaughtered after 84, 112 and 145 days on trial. Fasted liveweight gain were significantly (P<0.001) higher for Suffolk-cross (107 g/d) and Oxford Down-cross (101 g/d) lambs than for Texel-cross lambs (84 g/d). At a constant hot carcass weight (HCW) of 19.2 kg, Texel-cross lambs had a significantly (P<0.01) lower GR (mean 12.0 mm) than Suffolk-cross (14.1 mm) and Oxford Down-cross (13.3 mm) lambs. Carcasses were boned to a commercial specification which maximised the removal of bone and fat. At a carcass weight (CW) of 19.2 kg Texel-cross lambs had a significantly (P<0.001) higher saleable meat yield (SMY; 647 g/kg CW) than Suffolk-cross (634 g / kg) and Oxford Down-cross (629 g/kg) lambs. Texel-cross and Oxford Down-cross lambs had a higher proportion of the SMY in high value cuts (HVC) than Suffolk-cross lambs. At a CW of 19.2 kg Suffolk-cross lambs (395 g HVC/kg SMY) had a lower yield than Tex elcross (402 g/kg; P<0.001) and Oxford Down-cross (400 g/kg; P<0.05) lambs. There was no breed by sex interaction, but ewe lambs yielded a significantly higher proportion of HVC in their SMY (402 v 396 g/kg for ewe and ram lambs respectively, P<0.001). At a CW of 19.2 kg eye muscle area was significantly higher (P<0.001) for Texel-cross lambs (13.5 cm 2 ) than for Suffolk-cross and Oxford Down-cross (both 12.7 cm 2 ) lambs, with no sex differences.
All optical add‐drop multiplexer by utilizing a single semiconductor optical amplifier

A simple all‐optical add‐drop multiplexer scheme is presented by utilizing cross gain modulation (XGM) and four‐wave mixing (FWM) effects in a single semiconductor optical amplifier (SOA). When the synchronized data stream and control signal is launched into a SOA, FWM generates the dropped channel, while XGM is used to clean the corresponding bit slots for adding new data. This function is demonstrated at 10 Gbit/s by simulation and experiment. Both of them show good performance. © 2010 Wiley Periodicals, Inc. Microwave Opt Technol Lett 52: 1977–1980, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.25382