Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Application of Virtual Training System for Computer Hardware Assembly

Virtual reality technology is a research focus today, and has been applied to education, entertainment and many other fields. Computer hardware assembly is a course that teaches students how to recognize and assemble a computer. However, traditional teaching model has a series of problems, such as the slow update of computer training equipment, serious hardware waste and danger of assembly experiment process. In order to solve these problems, we designed and developed a virtual training system for computer hardware assembly (VTSCHA) based on the Unity3D platform. In the design stage, we fully considered the needs of the course and proposed a complete system architecture. Then through the study of Playmaker visual programming plug-in, animation and UI system, we respectively realized the parts display, computer assembly demonstration and computer simulation operation function, and finally completed the system. Practical results show that using VTSCHA can achieve a good teaching effect in the classroom. This system has good three-dimensional display and interactive functions. Learners can easily get started and operate in the virtual environment.
Discontinuous Functions as Limits of Compactly Supported Formulas

J. Marshall Ash (mash@depaul.edu, MR ID 27660, ORCID 0000-0003-3053-0988) is professor emeritus of mathematics at DePaul University. He received his Ph.D. in mathematics from the University of Chicago in 1966. He taught mathematics at DePaul University from 1969 until his retirement 45 years later. He continues to do collaborative mathematical research. He enjoys weekly 25 mile bicycle rides with friends in the Berkshire hills of western Massachusetts; reading some of the classics that were always put off for “later”; and viewing movies, plays and occasional Yankee games with his family.
Influence of Biochar on Soil Physicochemical Properties, Erosion Potential, and Maize (Zea mays L.) Grain Yield under Sandy Soil Condition

ABSTRACT Degraded soils in humid tropics are characterized by low fertility and high soil erosion potential. Hence, field experiments were conducted during 2018 and 2019 cropping seasons on an Alfisol at Owo in the forest–savanna transition zone of southwest Nigeria to evaluate the effects of the application of biochar (B) produced from waste wood of trees on physicochemical characteristics, erosion potential, and maize yield. Four treatments considered were control (no biochar application, 10 t ha−1 B, 20 t ha−1 B and 30 t ha−1 B). The treatments were laid out in a randomized complete block design with three replications. Results in both years indicated that B application significantly improved grain yield of maize and soil chemical properties, and reduced bulk density (BD) and penetration resistance (PR), and increased porosity (PO), moisture content (MC), and the mean weight diameter (MWD) of soil aggregates. Pooled over 2 years, B applied at 10, 20 and 30 t ha−1 increased grain yield of maize by 44.4%, 66.7%, and 88.9%, respectively, compared with the control. Averaged over 2 years, incorporating B into the soil significantly reduced soil loss (SL) by 32.3%, 56.9%, and 69.7% at 10, 20, and 30 t ha−1 application rates, respectively, compared with the control. The formation of macroaggregates in the B-amended soils is the critical factor to improve soil erosion potential. Therefore, the application rate of 30 t ha−1 B is considered as suitable for severely degraded soil because this application rate efficiently improves maize yield and soil properties and reduces SL.
Identification of a Stable Hydrogen-Driven Microbiome in a Highly Radioactive Storage Facility on the Sellafield Site

The use of nuclear power has been a significant part of the United Kingdom’s energy portfolio with the Sellafield site being used for power production and more recently reprocessing and decommissioning of spent nuclear fuel activities. Before being reprocessed, spent nuclear fuel is stored in water ponds with significant levels of background radioactivity and in high alkalinity (to minimize fuel corrosion). Despite these challenging conditions, the presence of microbial communities has been detected. To gain further insight into the microbial communities present in extreme environments, an indoor, hyper-alkaline, oligotrophic, and radioactive spent fuel storage pond (INP) located on the Sellafield site was analyzed. Water samples were collected from sample points within the INP complex, and also the purge water feeding tank (FT) that supplies water to the pond, and were screened for the presence of the 16S and 18S rRNA genes to inform sequencing requirements over a period of 30 months. Only 16S rRNA genes were successfully amplified for sequencing, suggesting that the microbial communities in the INP were dominated by prokaryotes. Quantitative Polymerase Chain Reaction (qPCR) analysis targeting 16S rRNA genes suggested that bacterial cells in the order of 104–106 mL–1 were present in the samples, with loadings rising with time. Next generation Illumina MiSeq sequencing was performed to identify the dominant microorganisms at eight sampling times. The 16S rRNA gene sequence analysis suggested that 70% and 91% from of the OTUs samples, from the FT and INP respectively, belonged to the phylum Proteobacteria, mainly from the alpha and beta subclasses. The remaining OTUs were assigned primarily to the phyla Acidobacteria, Bacteroidetes, and, Cyanobacteria. Overall the most abundant genera identified were Hydrogenophaga, Curvibacter, Porphyrobacter, Rhodoferax, Polaromonas, Sediminibacterium, Roseococcus, and Sphingomonas. The presence of organisms most closely related to Hydrogenophaga species in the INP areas, suggests the metabolism of hydrogen as an energy source, most likely linked to hydrolysis of water caused by the stored fuel. Isolation of axenic cultures using a range of minimal and rich media was also attempted, but only relatively minor components (from the phylum Bacteroidetes) of the pond water communities were obtained, emphasizing the importance of DNA-based, not culture-dependent techniques, for assessing the microbiome of nuclear facilities.
Larvicidal activity of Zinc oxide and titanium dioxide nanoparticles Synthesis using Cuscuta reflexa extract against malaria vector (Anopheles stephensi)

ABSTRACT In this present study, the Zinc oxide nanoparticles (ZnO NPs) and Titanium dioxide nanoparticles (TiO2 NPs) were synthesized using the aqueous stem extract of the Indian parasitic plant Cuscuta reflexa. Further, the synthesized nanoparticles were tested as larvicidal activity against the malaria vector, Anopheles stephensi larvae. The synthesized nanoparticles were characterized with UV-visible spectroscopy, X-rays powder diffraction (XRD), Transmission electron microscopy (TEM), scanning electron microscopy with Energy-dispersive X-ray spectroscopy (SEM-EDS). The mortality of larva was observed after 48 h by probit analysis. The synthesized ZnO NPs and TiO2 NPs were spherical in shape, and 40.86 nm and 85.58 nm in size, respectively. The TiO2 NPs were found highly effective against the larvae of An. stephensi (100% mortality in the first and fourth instar, 50–90% mortality in second instar, and 40–80% mortality in third instar larvae) than the ZnO NPs and aqueous stem extract. The present study reveals the first report of the synthesis of ZnO NPs and TiO2 NPs using the aqueous stem extract of C. reflexa which is a rapid, , and eco-safe approach. This could be a safe and useful technology for mosquito control.
Automated analysis with Apriori algorithm

B the supply of cybersecurity professionals could not keep up with growing demand, organizations have begun to focus on cybersecurity education. Although there has been prior research, not many practical methods have combined the curriculum with the workforce demand. The National Institute for Standards and Technology (NIST) has started an investigation regarding role profiles with the workforce framework. This research aims to propose a better method for automatically deriving curricular guidance. We analyzed the representative workforce framework with the Apriori algorithm and prioritized competencies. As a result, we developed a potent tool that automatically produced similar lists like NIST.
Revisiting Wi-Fi Performance under the Impact of Corrupted Channel State Information

Wi-Fi devices become increasingly susceptible to mutual interference in congested network scenarios. If a device starts to receive a new frame in the presence of concurrent interference signal, its preamble reception can be seriously damaged, which spoils the channel estimation process. The resulting corrupted channel state information (CSI) causes persistent decoding errors throughout the data payload. This paper presents a comprehensive study into the impact of corrupted CSI on Wi-Fi performance. Through experimental study and link-level analysis, we verify that actual receiver performance is highly dependent on CSI acquisition at the preamble, which has never been reflected by any physical layer abstraction models. We develop a realistic model that reflects the impact of corrupted CSI on overall frame reception. Applying our model to ns-3 simulator, we revisit network performance in interference-prone scenarios, to assess consistency with real-world Wi-Fi systems.
ARQ Algorithm Optimization of Radio Link Control Layer in 5G System

In the process of realizing the Radio Link Control layer of 5G system, ARQ mechanism is introduced to ensure the reliability of data retransmission, but at the same time, high delay and low throughput are also introduced in the retransmission. In addition, the traditional ARQ mechanism is inefficient and only applies to LTE systems. Therefore, an improved retransmission scheme based on wireless channel quality is proposed. The channel estimation is used to monitor the quality of the new channel in real time, and then compare the channel coefficient with the preset threshold value to adaptively select to receive feedback response. In addition, the sending and receiving scheme of the AM entity is designed in detail. The simulation result show that the ARQ mechanism proposed in this paper can achieve fast retransmission, significantly reduce the transmission delay, and increase the system throughput.
A study of charge and hydrodynamic effects in protein ultrafiltration

This thesis is concerned with the study of different effects in protein ultrafiltration including device configuration, solution chemistry and membrane charge In the recent and more established literature membrane fouling remains a challenging problem that limits the wider application of ultrafiltration. Thus, investigations which can aid understanding and potentially reduce membrane fouling are of particular interest and in this study the problem has been addressed from several different angles Polyethersulfone membranes were studied at varying pH and two ionic strengths using bovine serum albumm and lysozyme as the model proteins. The study was conducted both in a stirred cell and a crossflow configuration in order to evaluate the influence of different system hydrodynamics on filtration This work was further substantiated through the application of filtration models An attempt was also made to modify the membrane surface by low temperature plasma modification with the intention to preferentially alter the characteristics of the membrane surface Both unmodified and plasma-modified polyethersulfone membranes were characterised using a range of analytical methods including flux data, streaming potential, contact angle and MWCO measurements to aid results interpretation. The research showed that MWCO data quoted by manufacturers is mostly greater than that obtained during laboratory studies The MWCO technique was also used to highlight differences between the unmodified and plasma-modified membranes demonstrating that the modification resulted in a membrane with tighter pores in the lower molecular weight region. Concentration polarisation effects were found to be reduced as a result of the plasmamodification The study of protein filtration at different pH and ionic strengths demonstrated that ionic strength effects were more pronounced than pH effects It was also shown that changes m the ionic strength can be used to alter the degree of protein rejection for the given system concentration polarisation was found to be higher during crossflow filtration compared to stirred cell filtration The thesis adds to existing knowledge in the area of ultrafiltration emphasizing the importance of device configuration, solution chemistry as well as the potential of charged membranes
Characterisation of Morphology in Musculus Semitendinosus Tendon Used for Anterior Cruciate Ligament Reconstruction: A Pilot Study

Summary Introduction Anterior cruciate ligament (ACL) rupture is very common in athletes. In the general population, incidence is approximately 33 per 100 000 people. Aim of the study The aim of the study was the evaluation of morphological changes in the musculus semitendinosus tendon used for the reconstruction of ACL to understand the quality of most common for surgery used material. Material and methods The materials were obtained from four ACL autologous hamstring reconstruction surgeries. The tissue was stained with hematoxyllin and eosin and with immunohistochemical (IMH) staining of PGP9.5, VEGF, collagen I and collagen III. The material was evaluated with semiquantitative method. Results Routine staining showed practically unchanged tendon structure, with one exception when sclerotic blood vessels were observed in endotenon. Collagen III IMH demonstrated moderate to numerous positive collagen fibres in two cases, but in other two there were only few positive structures seen. Collagen I IMH showed few to moderate number of positive collagen fibres in all cases. In two cases, moderate number of PGP9.5 positive nerve fibres was observed and in two other cases occasional to few number of positive structures was detected. PGP 9.5 marked higher number of nerve fibres in peritenon than in endotenon. Numerous VEGF positive endotheliocytes were observed in two cases, but in two other cases VEGF positive endotheliocytes were occasional. Conclusions Tendon of musculus semitendinosus displays two patterns of distribution of tissue ischemia, neuropeptide containing innervation and collagen I and III. Collagen III is thought to be evaluated as a response of tendon to the ischemia and intensive innervation, while increase of collagen I probably is related to the relatively unchanged vascularity and innervation. The pattern of musculus semitendinosus tendon structural changes seems to be connected to the individual homeostasis in patients persisting before the usage of tendon for the reconstruction.
K-water’s Integrated Water Resources Management system (K-HIT, K-water Hydro Intelligent Toolkit)

ABSTRACT This study details the Hydro Intelligent Toolkit (K-HIT) developed in 2002 by K-water, the Korean water agency, to cope with extreme events such as floods and droughts. It is structured to outline the challenges to water management in Korea, the development and components of K-HIT, its effectiveness in practice, and lessons learned.
The Reserve Price Optimization for Publishers on Real-Time Bidding on-Line Marketplaces with Time-Series Forecasting

Abstract Today's Internet marketing ecosystems are very complex, with many competing players, transactions concluded within milliseconds, and hundreds of different parameters to be analyzed in the decision-making process. In addition, both sellers and buyers operate under uncertainty, without full information about auction results, purchasing preferences, and strategies of their competitors or suppliers. As a result, most market participants strive to optimize their trading strategies using advanced machine learning algorithms. In this publication, we propose a new approach to determining reserve-price strategies for publishers, focusing not only on the profits from individual ad impressions, but also on maximum coverage of advertising space. This strategy combines the heuristics developed by experienced RTB consultants with machine learning forecasting algorithms like ARIMA, SARIMA, Exponential Smoothing, and Facebook Prophet. The paper analyses the effectiveness of these algorithms, recommends the best one, and presents its implementation in real environment. As such, its results may form a basis for a competitive advantage for publishers on very demanding online advertising markets.
A Mixture Density Channel Model for Deep Learning-Based Wireless Physical Layer Design

Machine learning is a highly promising tool to design the physical layer of wireless communication systems, but it usually requires that a channel model is known. As data rates increase and wireless transceivers become more complex, the wireless channel, hardware imperfections, and their interactions become more difficult to model and compensate explicitly. New machine learning schemes for the physical layer do not require an explicit model but implicitly learn the end-to-end link including channel characteristics and non-linearities of the system directly from the training data. In this paper, we present a novel neural network architecture that provides an explicit stochastic channel model, by learning the parameters of a Gaussian mixture distribution from real channel samples. We use this channel model in conjunction with an autoencoder for physical layer design to learn a suitable modulation scheme. Since our system learns an explicit model for the channel, we can use transfer learning to adapt more quickly to changes in the environment. We apply our model to millimeter wave communications with its challenges of phased arrays with a large number of antennas, high carrier frequencies, wide bandwidth and complex channel characteristics. We experimentally validate the system using a 60 GHz FPGA-based testbed and show that it is able to reproduce the channel characteristics with good accuracy.
UNet-NILM: A Deep Neural Network for Multi-tasks Appliances State Detection and Power Estimation in NILM

Over the years, an enormous amount of research has been exploring Deep Neural Networks (DNN), particularly Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) for estimating the energy consumption of appliances from a single point source such as smart meters - Non-Intrusive Load Monitoring (NILM). However, most of the existing DNNs models for NILM use a single-task learning approach in which a neural network is trained exclusively for each appliance. This strategy is computationally expensive and ignores the fact that multiple appliances can be active simultaneously and dependencies between them. In this work, we propose UNet-NILM for multi-task appliances' state detection and power estimation, applying a multi-label learning strategy and multi-target quantile regression. The UNet-NILM is a one-dimensional CNN based on the U-Net architecture initially proposed for image segmentation. Empirical evaluation on the UK-DALE dataset suggests promising performance against traditional single-task learning.
Aiding a Disaster Spot via an UAV-Based Mobile AF Relay: Joint Trajectory and Power Optimization

Followed by the destruction of existing infrastructure or the emergence of the necessity for a new infrastructure, disaster events (e.g., earthquakes and pandemic) may require inspection of certain area and passing information to a dedicated help unit. Unmanned Aerial Vehicle (UAV)-aided mobile relaying technology is one of the effective means of provisioning service in such situations. In this paper, as the part of the rescuing operation in a certain disaster spot, we consider a mobile relaying technique, where an UAV acts as a relay node to ferry data between two disconnected floating or fixed nodes. For the sake of simplicity and low cost, amplify-and-forward relaying capability is adopted for the UAV. We consider the maximization of end-to-end throughput of such a system by optimizing the source/UAV power allocation as well as the trajectory of the UAV while considering practical mobility constraints (on the speed and initial/final locations of the UAV) as well as signal causality constraints. The formulated optimization problem is non-convex, and hence intractable to solve. Therefore, similar to the existing solution approach, we solve the problem via an iteration-based solution strategy, however we solve the source/UAV power allocation and the UAV trajectory design problems per iteration in a different manner. For the source/UAV power allocation problem, we provide heuristic solutions while considering both the availability and absence of a buffer at the UAV node. On the other hand, for the given power assignment, we adopt the geometric programming (GP)-based approach upon the transformation of variables and constraints. Furthermore, under the free initial and final UAV locations, jointly optimal power allocation and UAV trajectory are derived. Through extensive simulation, we verify the effectiveness of the proposed scheme while comparing with one existing work.
Changes in the Start Reaction Times in the 200 m Run at the World Championships After the Tightening of False Start Rule

Summary Reaction time is an important component of the structure of sports performance in sprint disciplines. In our observation, we focused on the men’s and women’s 200 metres discipline at the World Championships (WCH) in two periods. The first in 1999-2009 and the second in 2011-2019. This division was conditioned by the change in the false start rule, which states that any competitor who makes a false start, except in multicontest, will be disqualified (valid since 1st January 2010). This change affected the speed of the sprinter’s reaction. The monitored group were finalists of the 200 m runs at the WCH, a total of 11 events. We used basic mathematical-statistical characteristics and assessed changes in reaction times using parametric paired and parametric unpaired t-test and Wilcoxon test. We compared reaction time in the heats and the finals. We found that at some WCH, worse reaction times were achieved in the finals of both categories compared with the heats. By comparing the reaction speed in the heats with the reaction speed in the men‘s finals, we recorded this statistically significant difference in the first period (p < 0.01) and after tightening the rule at the level of p < 0.10. In the women’s group, this difference was not statistically significant in any period. The percentage of the reaction speed in the final time of the 200 m run was 0.76 – 0.86 % in the men’s group and 0.74 – 0.78 % in the women’s group. The analysis of the results from the WCH in athletics confirmed the importance of reaction speed in the 200 m run.