Miracle-dz/UniFAR-FTUs huggingface dataset:
An individualized longitudinal approach to monitoring the dynamics of growth 2 and fitness development in adolescent athletes Monitoring the dynamics of growth and

This study evaluated the development of anthropometric and fitness 2 characteristics of three individual adolescent junior rugby league players, and 3 compared their characteristics with a cross-sectional population matched by age and 4 skill level. Cross-sectional anthropometric and fitness assessments were conducted on 5 1,172 players selected to the Rugby Football League’s (RFL’s) talent development 6 programme (i.e., the Player Performance Pathway) between 2005 and 2008. Three 7 players of differing relative age, maturational status and playing position were 8 measured and tracked once per year on three occasions (Under 13s, 14s, 15s age 9 categories) and compared against the cross-sectional population. Results demonstrated 10 that the later maturing players increased height (Player 1 = 9.2 %; Player 2 = 7.8 %) 11 and a number of fitness characteristics (e.g., 60m speed – Player 1 = -14.9 %; Player 2 12 = -9.9 %) more than the earlier maturing player (Player 3 – Height = 2.0 %, 60m 13 sprint = -0.7 %) over the two year period. The variation in the development of 14 anthropometric and fitness characteristics between the three players highlights the 15 importance of longitudinally monitoring individual characteristics during adolescence 16 to assess dynamic changes in growth, maturation and fitness. Findings showcase the 17 limitations of short-term performance assessments at one-off time points within 18 annual-age categories; instead advocating individual development and progression 19 tracking without de-selection. Coaches should consider using an individual approach, 20 comparing data with population averages, to assist in the prescription of appropriate 21 training and lifestyle interventions to aid the development of junior athletes.
Third doses of COVID-19 vaccines reduce infection and transmission of SARS-CoV-2 and 1 could prevent future surges in some populations: a modeling study

Background Vaccines have greatly reduced the impact of COVID-19, but vaccine protection against milder disease and infection have waned significantly, especially for the Delta variant 11 (B.1.617.2). A third booster dose of two-dose vaccines could restore protection but the benefit of 12 boosting immunity in younger healthy individuals and the resultant effects on transmission have 13 not been quantified. Methods We develop relationships between neutralizing antibody titers and vaccine protection 15 against both infection and transmission. We combine these relationships with data on waning and boosting of neutralizing antibody titers to examine the impact of third doses of Pfizer-BioNtech 17 and Moderna vaccines on infection and transmission and the impact on the pathogen effective 18 reproductive number R t . Findings Waning reduced protection of the Pfizer-BioNtech vaccine against all infections from 20 80.0% (95% CI: 77% to 83%) to 60.4% (95% CI: 53% to 67%), and for the Moderna vaccine 21 from 83.8 (95% CI: 80 to 87%) to 65.9% (95% CI: 61-71%). A third dose increased neutralizing 22 antibody titers 25.9-fold relative to waned levels for the Pfizer-BioNtech vaccine and 13-fold 23 relative to waned levels for the Moderna vaccine. This increased protection against infection to 24 87.2% (95% CI: 83% to 91%) and 86.3% (95% CI: 82% to 90%) for Pfizer and Moderna, 25 respectively. Increased protection against infection and transmission from third doses reduced R t 26 by 28% to 74% depending on vaccine coverage and previous infection and reduced R t below 1 27 when vaccination coverage was high or contact rates were well below pre-pandemic levels. 28 Interpretation A third vaccine dose could substantially reduce transmission of SARS-CoV-2 29 and prevent future surges, with the impact increasing with vaccine coverage and contact rates 30 among individuals. Reducing transmission would reduce infection in both unvaccinated 31 individuals and breakthrough infections in vaccinated individuals.
An Immersive Virtual Reality Platform Integrating Human An Immersive Virtual Reality Platform Integrating Human ECOG & sEEG: Implementation & Noise Analysis ECOG & sEEG: Implementation & Noise Analysis

—Virtual Reality (VR) offers a powerful new platform for experimental neuroscience that has become increasingly popular with non-invasive neural recording modalities like electroencephalography (EEG) and functional MRI. Despite this broad appeal, no analysis yet exists quantifying the impact of concurrent VR use on the fidelity of electrophysiological signal features acquired intracranially. In this work, we evaluate a VR platform for behavioral experimentation with in-patient human subjects undergoing invasive neural recording with electrocorticography (ECOG) and stereoelectroencephalography (sEEG). We present a noise analysis of data from two subjects, one child and one adult, both VR naïve prior to our experimental sessions. We demonstrate a line noise increase due to VR hardware that is effectively mitigated by common average rereferencing and no significant increase of the high-frequency noise floor between VR headset on and off conditions. We also discuss donning and removal of the VR headset with this patient population, as well as tips for addressing VR hesitancy and first immersion. This work demonstrates the feasibility of immersive VR experimentation with awake intracranial patients and is, to our knowledge, the first demonstration of its kind.
Security Mechanism for CSMA/CD Networks: A Survey

: In this paper we study about security against various malicious attacks. In this we also represent some known feasible attacks. We also get information about secured communication for different mechanism which provide a secrecy, security and authentication to most of security issues. In some logical section we learn about an active repeater in CSMA/CD for network comparison for data transmission between two addresses. If no match occurs, the logic section controls the transmitter so that the transmitter switches from transmitting the data packet to the clock signal. For bidirectional routing message received from wired network and send it to wireless network. At the end we get comparison result for transmitted message to the received message to find if a collision has occurred.
Murine Experimental Autoimmune Diseases Soluble Peptide: I-A Complexes Associated with Expression and Characterization of Recombinant

2 Structural and functional studies of murine MHC class II I-A molecules have been limited by the low yield and instability of soluble, recombinant heterodimers. In the murine autoimmune diseases experimental autoimmune encephalomyelitis and colla-gen-induced arthritis, MHC class II molecules I-A u and I-A q present peptides derived from myelin basic protein and type II collagen, respectively, to autoreactive T cells. To date, systems for the expression of these two I-A molecules in soluble form for use in structure-function relationship studies have not been reported. In the present study, we have expressed functional I-A u and I-A q molecules using a baculovirus insect cell system. The chain pairing and stability of the molecules were increased by covalently linking the antigenic peptides to b -chains and adding carboxyl-terminal leucine zippers. Peptide:I-A q complex quantitatively formed an SDS-stable dimer, whereas peptide:I-A u formed undetectable amounts. However, the two complexes did not show any signiﬁcant difference in their response to thermal denaturation as assessed by circular dichroism analyses. The autoantigen peptide:I-A complexes were highly active in stimulating cognate T cells to secrete IL-2 and inducing Ag-speciﬁc apoptosis of the T cells. Interestingly, the T cells were stimulated by these soluble molecules in the apparent absence of experimentally induced cross-linking of TCRs, indicating that they may have therapeutic potential in autoimmune disease models. The Journal of Immunology, 1998, 160: 5915–5921.
Vitamin D insufficiency in the first 6 months of infancy and subsequent challenge-proven IgE-mediated food allergy: a case-cohort study.

Background Ecological evidence suggests vitamin D insufficiency (VDI) due to lower ambient ultraviolet radiation (UVR) exposure may be a risk factor for IgE-mediated food allergy. However there are no studies relating directly measured VDI during early infancy to subsequent challenge-proven food allergy. Objective To prospectively investigate the association between VDI during infancy and subsequent challenge-proven food allergy. Methods In a birth cohort (n=1074), we used a case-cohort design to compare 25-hydroxy-vitamin-D 3 (25(OH)D 3 ) levels among infants with food allergy versus a random subcohort (n=274). The primary exposures were VDI (25(OH)D 3 <50 nmol/L) at birth and 6 months of age. Ambient UVR and time in the sun were combined to estimate UVR exposure dose. IgE-mediated food allergy status at 1 year of age was determined by formal challenge. Binomial regression was used to examine associations between VDI, UVR exposure dose and food allergy, and investigate potential confounding.
Hybrid Design Approach for Efficient Network Intrusion Detection using Data Mining and Network Performance Exploration

-The primary goal of an Intrusion Detection System (IDS) is to identify intruders and differentiate anomalous network activity from normal one. Intrusion detection has become a significant component of network security administration due to the enormous number of attacks persistently threaten our computer networks and systems. Traditional Network IDS are limited and do not provide a comprehensive solution for these serious problems which are causing the many types security breaches and IT service impacts. They search for potential malicious abnormal activities on the network traffics; they sometimes succeed to find true network attacks and anomalies (true positive). However, in many cases, systems fail to detect malicious network behaviors (false negative) or they fire alarms when nothing wrong in the network (false positive). In accumulation, they also require extensive and meticulous manual processing and interference. Hence applying Data Mining (DM) techniques on the network traffic data is a potential solution that helps in design and develop a better efficient intrusion detection systems. Data mining methods have been used build automatic intrusion detection systems. The central idea is to utilize auditing programs to extract set of features that describe each network connection or session, and apply data mining programs to learn that capture intrusive and non-intrusive behavior. In addition, Network Performance Analysis (NPA) is also an effective methodology to be applied for intrusion detection. In this research paper, we discuss DM and NPA Techniques for network intrusion detection and propose that an approach which will have the potential to detect intrusions in networks more effectively and help in increasing accuracy.
Dynamic analysis of functionally graded carbon nanotube (FGCNT) reinforced composite beam resting on viscoelastic foundation subjected to impulsive loading

In this study, dynamic analysis of functionally graded carbon nanotube reinforced composite (FGCNT) beam resting on viscoelastic foundation is investigated. Four different types of carbon nanotubes (CNTs) distribution including uniform (UD-CNT), and three types of functionally graded distribution of CNTs through the thickness of beam are considered. The Kelvin–Voigt viscoelastic model and higher-order shear deformation beam theory (HOBT) have been used. The rule of mixture is used to describe the effective material properties of the nanocomposite beams. The equations of motion are derived by using Lagrange’s equations, and solved by using finite element and Newmark methods. The effects of volume fraction and distribution of CNTs, stiffness and damping of viscoelastic foundation, slenderness ratio and different boundary conditions on transverse displacement and stresses of beam are investigated. The results show that by using viscoelastic foundation the amount of normal and shear stress have decreased considerably, and by increasing the stiffness coefficient of foundation, transverse displacement of beam reduces and the frequency of vibration increases as well, meanwhile by increasing the damping coefficient of foundation, amplitude of vibration decreases considerably. The model is verified and compared with previously published works and it shows good agreement.
The Predictive Five: A supervised learning approach to personality psychology

In the current study, we set out to examine the viability of a novel approach to modeling human personality. Current research in psychology suggests that people’s personalities can be effectively described using five broad dimensions (the Five-Factor Model; FFM); however, the FFM has been criticized for its relatively limited predictive ability. We propose a novel approach to modeling human personality that is based on the maximization of the model’s predictive accuracy. Unlike the FFM, which performs unsupervised dimensionality reduction, we utilized supervised machine learning techniques for dimensionality reduction of questionnaire data, using numerous psychologically meaningful outcomes as data labels (e.g., intelligence, well-being, sociability). The results showed that our five dimensional personality summary, which we term the Predictive Five (PF), provides predictive performance that is superior to the FFM in independent validation datasets, and on a new set of outcome variables selected by an independent group of psychologists. Furthermore, we examine the between-participants’ replicability of the PF representation and show that the PF has good test-retest reliability, and as such provides an important addition to the psychologists' toolbox. The approach described herein has the promise of providing an interpretable low-dimensional personality representation, which is also predictive of behaviour.
Kernel-based Identiﬁcation of Periodically Parameter-Varying Models of Power Kites

In airborne wind energy (AWE) systems, control design is usually conducted with linearized or simpliﬁed kine-matic models. The model mismatch in model-based control design may lead to severe performance deterioration in practice. Therefore, it is desired to assess the closed-loop performance from experimental trajectory data with a model of the AWE system in closed loop with the designed controller. Such a model would make it possible to simulate and analyze the performance of existing ﬂight systems analytically. Furthermore, additional control loops can be designed to reﬁne the performance based on the identiﬁed closed-loop model.
Analysis of deep sky sources found by the infrared astronomy satellite

Abstract : This program was aimed at understanding the number and types of sources found in the fields observed with greatest sensitivity by the IRAS satellite. The initial phase of the study emphasized observation and analysis of sources found in the less sensitive all sky survey carried out with Infrared Astronomy Satellite. Significant differences between the bright and faint 12 um sources were found, which constrain their relative spatial distributions and luminosities. A study focussed one one, large population of infrared-bright stars -- those whose atmospheres are rich in carbon - yielded measurements of their space distribution range of mass loss rates, and lifetimes. An analysis of 60 um sources from the IRAS survey showed that eighty-five percent of those located more than thirty degrees above the plane of the Galaxy are extragalactic objects, provided a measure of the space density of galaxies of different infrared luminosities, and showed that there are significant differences in the environment and infrared properties of the most luminous and least luminous galaxies. Studies of galaxies with particularly strong mid-infrared emission resulted in the discovery of ultraluminous objects. Initial studies of results from the IRAS pointed observations show effects of contamination by low-surface-brightness intestellar clouds.
Study the molecular docking for established phytochemicals of Cissus quadrangularis against tumor necrosis factor alpha (TNF-α) for the prevention of inflammation of arthritis as a major risk of urinary incontinence

Cissus quadrangularis is a medicinal plant. It has been used for the treatment of inflammation related diseases. The local name of Cissus quadrangularis is harbhanga. This plant are used in all over the countries medicinally due to their potent anti-inflammatory and free radical scavenging properties. Tumor necrosis factor or TNF-α is a pro inflammatory cytokine protein, which increases during inflammation and causes pain related diseases. Different non-steroidal anti-inflammatory drugs that has been used for pain relief but this drugs have adverse side effects. For this reason researchers are showing interest for medicinal plants or Phytomedicine without any adverse side effects. The main aim of this work was to know the inhibitory activity by observing binding affinity and energy value of TNF-α towards different phytochemicals present in Cissus quadrangularis through the molecular docking study.
I Know What Your Layers Did: Layer-wise Explainability of Deep Learning Side-channel Analysis

Masked cryptographic implementations can be vulnerable to higher-order attacks. For instance, deep neural networks have proven eﬀective for second-order proﬁling side-channel attacks even in a black-box setting (no prior knowledge of masks and implementation details). While such attacks have been successful, no explanations were provided for understanding why a variety of deep neural networks can (or cannot) learn high-order leakages and what the limitations are. In other words, we lack the explainability on neural network layers combining (or not) unknown and random secret shares, which is a necessary step to defeat, e.g., Boolean masking countermeasures. In this paper, we use information-theoretic metrics to explain the internal activities of deep neural network layers. We propose a novel methodology for the explainability of deep learning-based proﬁling side-channel analysis (denoted ExDL-SCA) to understand the processing of secret masks. Inspired by the Information Bottleneck theory, our explainability methodology uses perceived information to explain and detect the diﬀerent phenomena that occur in deep neural networks, such as ﬁtting, compression, and generalization. We provide experimental results on masked AES datasets showing where, what, and why deep neural networks learn relevant features from input trace sets while compressing irrelevant ones, including noise. This paper opens new perspectives for understanding the role of diﬀerent neural network layers in proﬁling side-channel attacks.
Weight two masking of the reed-solomon structure in conjunction with list decoding

: We present a code-based cryptosystem, in which we use Reed-Solomon codes as secret codes and a weight two matrix for masking, to make the system secure against attacks based on the Schur product. We combine this with the Guruswami-Sudan list decoding for decryption to get lower key sizes. As a consequence, we obtain a key size reduction of 21:8% compared to the standard McEliece cryptosystem proposed by Bernstein et al.
The direct effect of a sustained inflation in preterm infants at birth

Background : A sustained inflation (SI) at birth enhances lung aeration, increases functional residual capacity (FRC) and reduces need for mechanical ventilation in preterm infants. However, face mask ventilation of preterm infants is difficult, therefore clinical effect of the SI is unclear. Methods : In this observational study inflation pressures and tidal volumes were recorded using respiratory function monitoring of preterm infants <32 weeks gestation receiving a SI. Inspiratory- (Vti) and expiratory tidal volumes (Vte) of the SI and cumulative Vti and Vte of breaths (Vti br , Vte br ) during the SI were determined. Heart rate (HR) and oxygen saturation (SpO 2 ) were determined before and after the SI. Results : 70 infants were included (median (IQR) GA 29 (27-30) weeks). Mean (SD) SI duration was 10.5 (2.9) s using PIP 24.2 (2.3) cmH 2 O and PEEP 6.0 (1.8) cmH 2 O. In 20/70 infants, no volumes were delivered during the SI due to mask leak. No leak occurred in 50/70 infants of which 36/50 breathed during the SI. In 14/50 infants who did not breathe, Vti and Vte were 0.9 (0.4-2.7) mL/kg and 0.6 (0.1-2.0) mL/kg with FRC gain of 0.0 (-0.5-0.6) mL/kg. In 36/50 infants who breathed during the SI, Vti was 2.9 (0.9-9.2) mL/kg and Vte 3.8 (1.0-5.9) mL/kg, whereas Vti br was 16.4 (6.8-23.3) mL/kg, and Vte br 5.8 (1.2-16.8) mL/ kg with FRC gain of 7.1 (1.7-15.9) mL/kg. HR and SpO 2 did not increase immediately after the SI. Conclusions : A SI of 10 s and 25 cmH 2 O in preterm infants at birth was not effective
Institutional Knowledge at Singapore Management University Institutional Knowledge at Singapore Management University

Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.
distance measured by real-time ultrasound in overhead athletes with shoulder impingement syndrome

Introduction: Shoulder impingement syndrome (SIS), characterized by decreased acromiohumeral distance (AHD), is a promising objective outcome measure with both clinical and research utility. The purpose of this study was to evaluate and compare the effectiveness of combining exercise therapy and manual therapy with motor control exercise on AHD in overhead athletes with SIS. Material and methods: Ten overhead athletes with clinically diagnosed SIS were randomly assigned to two groups. The ET plus MT group received the exercise therapy plus manual therapy regime, and the MCE group followed the motor control exercise protocol. Both groups underwent eight weeks of intervention, and AHD was evaluated at three levels of abduction (0°, 45°, 60°) with real-time ultrasound (RTUS). The AHD evaluation was performed at baseline and at end of intervention (week 8). Results: AHD improvement was noted at all three levels only in the ET plus MT group and the mean difference was found to be 2.62 ± 0.18mm (0°), 3.28 ± 0.40mm (45°) and 3.77 ± 0.30mm (60°). Statistical analysis performed with two-way repeated measures ANOVA (3x2) revealed significant group effects for AHD (0°: F(2,1.10) = 0.76, p < 0.001; 45°: F(2,0.98) = 0.80, p < 0.001; 60°: F(2,0.95) = 0.84, p < 0.001). Time effect and interaction effects were also found to be significant. Conclusions: plus effective than MCE at 0°,45°, 60° in overhead athletes with SIS.