Miracle-dz/UniFAR-FTUs huggingface dataset:
Contextual Factors Influencing Physical Activity and Technical Performance in Australian Football League Women's Competition Match-Play

Abstract Leabeater, A, Clarke, A, and Sullivan, C. Contextual factors influencing physical activity and technical performance in AFLW competition match-play. J Strength Cond Res 37(1): 194–199, 2023—The purpose of this study was to examine the influence of contextual factors on physical activity and technical match performance during Australian Football League Women's (AFLW) competition match-play. The study was of a retrospective longitudinal design and used physical activity and technical data collected from female Australian Football players (n = 49) from 1 team during 23 AFLW competition games over 3 seasons. A three-level linear mixed model was constructed to investigate the influence of different contextual factors (match-related variables) on relative total distance (TD), relative high-speed running (HSR) distance, and ranking points during AFLW match-play. The results showed that from season 1 to season 3, relative TD increased by 2.0 m·min−1 (ES: 0.06 [−0.04 to 0.16], p < 0.05) and relative HSR increased by 4.1 m·min−1 (ES: 0.22 [0.14–0.31], p < 0.001). Interstate matches were associated with a reduction of 5.1 m·min−1 per match in TD (ES: −0.21 [−0.30 to −0.12], p < 0.001) and 2.5 m·min−1 in HSR distance (ES: −0.22 [−0.31 to −0.13], p < 0.001). Total disposals were associated with a 0.23 m·minute−1 reduction in HSR for that player (ES: −0.13 [−0.22 to 0.04], p < 0.01). Match margin was the only contextual factor to influence ranking points/min (0.007 AU·min−1, ES: 0.30 [0.21–0.38], p < 0.001). In conclusion, this study shows that player physical activity may be reduced during interstate AFLW matches; the average HSR has increased since the start of the AFLW competition and may reflect increasing match activity profiles, and players have a greater rate of accumulation of ranking points when the score difference is greater.
A Privacy Preserving of Composite Private/Public Key in Cloud Servers

Security is a term used to provide secrecy of data from the illegal entries. It is used to prevent a user that he/she should not have access to. It is a two step process. The security system in the first step identifies who the user is by requiring the user to submit some sort of identification. This is called authentication, and it means that the system is trying to find out who you are. Once the system identifies who you are, in the next step the system has to determine that you should permitted to access the recourse. This part of the process is called authorization, and it means that the system is checking to see if you have privileges to perform a certain action. OAuth and OpenID are the authentication schemes are used for authentication but they also have privacy protection problems. Here we are proposing composite private key over cloud system which is protected by splitting key into different servers which combines to form a single composite key. In this approach we are having third party key servers used public key cryptography to save public/private keys of their clients. We are using ring signatures by forming the network into ring and public keys are shared from that ring structures. We are proposing this composite private/public key pairs for privacy preserving in the facebook and other social network. We also propose homomorphic algorithm to prevent the compromised key server problem with the attacker.
Reliability investigations on conductive adhesive joints with emphasis on the mechanics of the conduction mechanism

The isotropic conductive adhesive (ICA) mounting technology is of growing interest, but reliability concerns are still preventing its broad application. Reports on environmental testing results are related to both high temperature storage and thermal cycling. Additionally, the influence of moisture has been investigated for both pressure cooker test and humidity storage with exposure times up to several weeks. In an ICA, the conductive particles are embedded in a polymeric matrix material, where they can form conductive paths. This mechanical part of the conductive mechanism was studied in more detail using a finite element (FE-) model, because only a little information is available on this subject. A joint of a chip resistor on an organic board was selected for the model. The conductive adhesive is not treated as a homogeneous material, but split into the polymeric matrix material and idealized conductive particles. A temperature dependent viscoelastic constitutive description has been used to model the epoxy behavior. Additionally, moisture diffusion analyzes of the adhesive joints were conducted. The contacting pressure of the particles is shown to depend on cure shrinkage, temperature changes, and moisture swelling effects.
A novel dual-radar fusion method for improving the cross-range resolution of ISAR imagery

ABSTRACT For the intelligent crossroad with millimetre wave radar, two radars are placed perpendicular to each other to complete the monitoring and identification of vehicles which means the cross-radar can obtain inverse synthetic aperture radar (ISAR) image while the radial radar can not obtain, but the cross-range of a scattering point in ISAR image is equivalent to the radial range of the same point in another radar’s view. Thus, the special placement of radar is utilized to improve cross-range resolution in ISAR image. In this letter, a novel dual-radar fusion method for improving ISAR image cross-range resolution for isolated scattering points on target is proposed. First, the range information of scatters is gathered from radial radar based on multiple signal characterization (MUSIC) algorithm. Then, data interpolation and construction of the modulation function will be completed. Finally, the ISAR image cross-range resolution can be improved by fusing the ISAR image obtained from cross-radar and the modulation function. The effectiveness of the proposed method is validated by simulation and experimental results.
Humaria Laevispora, a New Cryptic Species of Pezizales (Pyronemataceae, Ascomycetes) Based On Morphoanatomical and Phylogenetic Analysis From Pakistan

In order to explore the biodiversity of mushrooms from Pakistan, authors come across a new Humaria sp. associated with Pinus wallichiana from Pakistan’s part of Himalayan moist temperate forests. Morpho-anatomical and phylogenetic characterization were used to elucidate their taxonomic affinities. Morphological and phylogenetic analysis confirms that it is a new species of Humaria. Humaria laevispora is subsequently described in detail and compared to closely related taxa Humaria hemisphaerica. The analysis also reveals that epigeous Humaria sp. is sister to hypogeous Genea spp. reflecting epigeous habit in Humaria a derived condition. Bangladesh J. Plant Taxon. 28(2): 379-384, 2021 (December)
REVEALING THE RELATION BETWEEN INDEPENDENT VARIABLES AND DRYING TIME IMPLEMENTED IN TORKSIM BY MEANS OF ARTIFICIAL NEURAL NETWORKS: A PRELIMINARY STUDY

The purpose of this study was to reveal by means of artificial neural networks (ANN) the relation that is inside Torksim software between the independent variables (wood species, density, temperature, green moisture content, air velocity and drying schedule) and drying time in order to be incorporated in spreadsheet programs, which are used in sawmills for production planning. Different configurations of the ANN model were tested to find out the optimal structure. The optimal structure of the ANN model was 6-6-1 and was figured out based on both, the mean relative error (MRE= 1.30%) and coefficient of determination (R 2 =0.998). The ANN model presented in this paper is capable to discover the valuable relation between independent variables and drying time in TORKSIM software. Consequently, it can be easily and fast integrated in spreadsheet programs that are used for production planning.
Domains in the Encyclopedic Semantics of some English and Arabic Equivalent Culture-Specific Words

The present study aims at finding interpretations for some inquiries in the field of encyclopedic semantics. It is an academic reflection of language exchange between English and Arabic which is one of the most prevalent interests of the recent cognitive linguistic researches. Particularly, it analyzes the way culture-specific words of two different languages can comparatively be understood. The single-method is adopted for the methodological approach of the study. The data collection is conducted according to a content analysis by extracting some CSWs that are referred to in some comparative culture-specific studies of English and Arabic. It is found that (1) there can be more than one domain matrix for equivalent CSWs; (2) the exact comparison between CSWs lies in the profile-base organization (3) the two or multi-dimensional domains are configurational; (4) the culture-specific standards locate the diversity between the domain matrixes of equivalent CSWs. Some key conclusions to draw is that (1) the domain matrix of a CSW depends on to the culture-specific norms; (2) the distinctive point of the tripartite (profile, base and concept) is the profile rather than the base; (3) image-schematic domains indicate the object material domains; (4) culture-specific norms are affected by religious and historical factors which control the inventory knowledge for the CSWs.
Exploring Deep Neural Network Capability for Intrusion Detection Using Different Mobile Phones Platforms

: Network intrusion activities started since the network typologies become available for public, the target devices were computers, servers, switches, routers and so on, but with the fever of smartphones spreading among the public, these smartphones have become a target for hacker attacks. Network Intrusion Detection System (IDS) is a device, software or both used by network administrator to monitor the network security and recognize any malicious activity or organization’s network policy violation. Deep neural network is the famous technology in deep learning where it is an artificial neural network with multiple hidden layers, and it simulates the human brain and it’s the central nervous system in thinking and detecting pattern. Mobile phones are widely used today, with different platforms which known now as smartphones, these smartphones belong to many manufacturing and require operating system. This research explores deep neural networks capability for intrusion detection using different mobile phones platforms, the research experiments five deep neural networks approaches, Fully Connected Deep Neural Networks (FCDNN), Convolutional Neural Networks (CNN), Convolutional Neural Networks followed by Fully Connected Neural Networks (CNN&FCDNN), Convolutional Neural Networks followed by Fully Connected Neural Networks and then followed by Convolution Neural Network (CNN&FCDNN&CNN), and finally Fully Connected Deep Neural Networks followed by Convolution Neural Networks (FCDNN&CNN). Two data sets have been used for testing the approaches, Android data set and NSL-KDD data set. The proposed approaches have been compared with each other’s and also compared with traditional Machine Learning (ML) approaches. The results show that CNN&FCDNN&CNN is the best deep learning approach where it achieved accuracy of 0.863 and 0.997 for the two data sets Android and NSL-KDD respectively. The accuracy results also show that the best approach is the random forest where it achieved 0.88 and 0.998 for Android and NSL-KDD data sets respectively. Deep neural networks show that they are good machine learning candidates for problems similar to mobile phones intrusion detection systems.
Board-to-board optical interconnection system using optical slots

A practical optical backplane system was prepared with transmitter-receiver processing boards and an optical backplane made of polymeric-waveguide-embedded optical printed-circuit boards. As connection components between the transmitter-receiver processing boards and backplane board, optical slots were used to enable easy and repeatable insertion and extraction of the boards with micrometer precision. We report an 8-Gb/s data transmission between transmitter processing board and optical backplane.
Metabolic Characterization of Plant Dehydration Tolerance in Seeds and Seedlings of Model plant Arabidopsis Thaliana and Desert Plant Schismus arabicus

Seeds in the seed-bank experience different natural regime such as diurnal cycles of imbibition followed by complete dehydration and the annual seasonal changes. These conditions pose a challenge to the regulation of germination and seedling survival. The effect of recurring hydration-dehydration (Hy-Dh) cycles and annual periodicity were tested on seeds from four Arabidopsis thaliana accessions [Col-0, Cvi, C24 and Ler] and Schismus arabicus Nees caryopses respectively. Diurnal Hy-Dh cycles had a detrimental effect on germination rate and on the final percentage of germination in Col-0, Cvi and C24 ecotypes, but not in Ler ecotype, whose seeds showed improved vigor following the treatments. Membrane permeability measured by ion conductivity was generally increased following each Hy-Dh cycle and was correlated with changes in the Redox status represented by the GSSG/GSH ratio. Among the ecotypes Col-0 seeds displayed highest membrane permeability, whilst Ler was characterized by the greatest increase in electrical conductivity following Hy-Dh cycles. Following Dh 2 and Dh 3, the respiratory activity of Ler seeds significantly increased in contrast to the other ii Abstract ecotypes, indicative of a dramatic shift in metabolism. These differences were associated with accession-specific content and patterns of change of (i) cell wall related laminaribiose and mannose, (ii) fatty acid composition –specifically of the monounsaturated oleic acid and of the more unsaturated α-linoleic acid–, (iii) Asn, ornithine and related polyamine putrescine. Furthermore, in Ler ecotype the content of TCA cycle intermediate fumarate, succinate and malate increased in response to dehydration, as opposed to a decrease in the other three ecotypes. These findings provide a link between seed respiration, energy metabolism, fatty acid -oxidation, Nmobilization and membrane permeability and the improved germination of Ler seeds following Hy-Dh cycles. Shismus arabicus,a common annual desert plant exhibited unique adaptations and survival strategies that enable it to germinate and develop in deserts. Germination of Schismus arabicus Nees caryopses is relatively constant across the year. In contrast,its tolerance to desiccation changes seasonally, with high rate of survival after dehydration of seedlings in winter but low in summer. Metabolic profiling presented a metabolic shift in germinated and dehydrated seedlings across the year. The data suggest the coordination of central metabolism and phenylpropanoid pathway in adapting plants to the annual seasonal changes which affect plants survival ability.
Augmented Reality for Human-Robot Collaboration

Although robotics is well established as a research field, there has been relatively little work on human-robot collaboration. This type of collaboration is going to become an increasingly important issue as robots work ever more closely with humans. For example, in space exploration, recent research has pointed out that to reduce human workload, costs, fatigue driven error and risk, intelligent robotic systems will need to be a significant part of mission design (Fong and Nourbakhsh 2005). Fong and Nourbakhsh also observe that scant attention has been paid to joint human-robot teams, and that making human-robot collaboration natural and efficient is crucial to future space exploration. NASA’s vision for space exploration stresses the cultivation of human-robotic systems (NASA 2004). In addition, companies such as Honda (Honda 2007), Toyota (Toyota 2007) and Sony (Sony 2007) are interested in developing consumer robots that interact with humans in the home and workplace. Finally, the Cogniron project (COGNIRON 2007), MIT Media lab (Hoffmann and Breazeal 2004) and the Mitsubishi Electric Research Laboratories (Sidner and Lee 2005), among others, are currently conducting research in human-robot interaction (HRI). HRI has become a research field in its own right, as shown by the 2006 inaugural conference for HRI with the theme Toward Human-Robot Collaboration (HRI2006 2006). Research into human-human communication can be used as a starting point in developing a robust human-robot collaboration system. Previous research with humans has shown that grounding, situational awareness, a common frame of reference and spatial referencing are vital in effective communication. Clearly, there is a growing need for research on humanrobot collaboration and models of communication between humans and robotic systems. Augmented Reality (AR) is a technology for overlaying three-dimensional virtual graphics onto the users view of the real world. It also allows for real time interaction with these virtual graphics, enabling a user to reach into the augmented world and manipulate it directly. Augmented Reality could be used to overlay virtual imagery on a real robot and so display the internal state and intentions of the robot. Thus AR can bridge the divide between human and robotic systems and could enable effective human-robot collaboration. In this chapter an overview of models of human-human collaboration is provided and how these models could be used to develop a model for human-robot collaboration is investigated. The field of human-robot interaction is reviewed and how it fits into a model
Artificial loading of the induction motors using a matrix converter

The paper discuses the use of a frequency converter for artificial loading of an induction motor. The characteristic of the artificial loading requires a cyclic circulation of energy between the converter and motor in order to increase the motor current and torque to the rated values without any load on the motor shaft. It is known that standard converters have serious limitations regarding the circulating energy, and if the incoming energy exceeds the storage capacity of the DC-link capacitors, an overvoltage fault may occur in the converter. This limitation can be overridden by using a unidirectional power flow converter with high energy-storage capability in the DC-link or by using a bidirectional power flow converter with reduced energy storage. Two possible bi-directional power flow converter topologies are investigated: the back-to-back voltage source inverter (VSI) and the matrix converter. A comparative analysis of two bi-directional power flow converters shows that the energy stored in the reactive components of a matrix converter is minimized. It is proven that the matrix converter may be successfully used in artificial loading of the induction motors.
Numerical simulation on pulsed operation of an all-semiconductor optical amplifier nonlinear loop device

Pulsed-signal self- and cross-switching operations in an all-semiconductor-optical-amplifier (SOA) nonlinear optical loop device are numerically investigated. The device consists of a loop amplifier, a multimode-interference waveguide amplifier (MMIWA), an input leg, and an output leg. With the combined mechanisms, including nonlinear coupling in the MMIWA, lateral field redistribution and amplification by the loop, and asymmetric gain-phase modulation between two counterpropagating signals in the loop, the device operates with efficient power-dependent switching. Simulations were conducted using a modified time-domain traveling-wave method for the interplay between the two counterpropagating signals in MMIWA and loop. Typical parameter values of GaAs-AlGaAs multiple quantum-well (MQW) optical amplifiers were adopted for simulating separately published experimental conditions. Numerical results of simulation agreed well in physical trend with the reported experimental data.
Option-Based Credit Spreads

We present a novel empirical benchmark for analyzing credit risk using “pseudo firms” that purchase traded assets financed with equity and zero-coupon bonds. By no-arbitrage, the bonds are equivalent to Treasuries minus put options on pseudo-firm assets. Empirically, like corporate spreads, pseudo-bond spreads are large, countercyclical, and predict lower economic growth. Using this framework, we find that bond market illiquidity, investors’ over-estimation of default risks, corporate frictions, and constraints on aggregate credit supply do not seem to explain excessive observed credit spreads, but, instead, a risk premium for tail and idiosyncratic asset risks is the primary determinant of corporate spreads. For their comments, we thank Pierluigi Balduzzi, Jack Bao, Hui Chen, Alexander David, Darrell Duffie, Peter Feldḧutter, Stefano Giglio, Zhiguo He, John Heaton, J.B. Heaton, Steven Heston, Erica Li, Francis Longstaff, Monika Piazzesi, Juliana Salomao, Steve Schaefer, Yang Song, Suresh Sundaresan, Andrea Vedolin, and seminar participants at Bocconi University, Stockholm School of Economics, Bank of Canada, Federal Reserve Board, Federal Reserve Bank of Chicago, University of Maryland, University of Chicago Booth School of Business, the Einaudi Institute for Economics and Finance, AQR, CICF, the 2014 NBER Asset Pricing meeting, the 2015 European Summer Symposium in Financial Markets, the 2016 European Finance Association, London Business School, Boston College, Oxford University, and Copenhagen Business School. We thank Bryan Kelly for helping with CME data. The views expressed herein are the authors’ and do not necessarily reflect those of the Board of Governors of the Federal Reserve System, nor any institutions with which any of the authors are affiliated. A previous version of this paper was briefly circulated with the title “The Empirical Merton Model. ” Veronesi acknowledges financial support from the Fama-Miller Center for Research in Finance and by the Center for Research in Security Prices at the University of Chicago Booth School of Business. Contact information: Christopher L. Culp: christopher.culp@jhu.edu; Yoshio Nozawa: yoshio.nozawa@frb.gov; and Pietro Veronesi: pietro.veronesi@chicagobooth.edu.
A comparison of cross-training policies in different job shops

This research compares a set of cross-training policies represented by different numbers of cross-trained workers, additional skills per cross-trained worker, and additional machines. The policies are evaluated in job shops, represented by different efficiency losses, labour utilization, variability in processing times, and worker absenteeism. Our results show that adding one machine in each department and cross-training one or two workers from each department with one additional skill is generally sufficient to realize most of the benefits of cross-training. Cross-training is thus beneficial in most job shops, unless the cost of the minimal training and spare machines is high. Our results also show that the value of cross-training and adding machines depends very much on the environment, and it is better to spread cross-training over more workers than to train a few workers with more skills.