Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of 3000-m Running Performance Using Classic Physiological Respiratory Responses

Introduction: Knowing which physiological variables predict running performance could help coaches to optimize training prescription to improve running performance. Objective: The present study investigated which physiological respiratory responses could predict 3000-m running performance. Methods: Seventeen amateur runners (29.82±7.1years; 173.12±9.0cm; 64.59±9.3kg) performed a maximal graded running test on a treadmill. The ventilatory threshold (VT), respiratory compensation point (RCP), and maximal oxygen consumption (VO2max) were assessed, as well as the respective velocities (vVT, vRCP, vVO2max). After 72 to 96 hours the runners performed the 3000-m running field test. The relationships between variables were performed using Pearson product momentum correlations. Thereafter, simple and multiple regression models were applied. The significance level adopted was 5% (p<0.05). Results: The majority of physiological responses were positive and well related to each other (r≥0.70; p<0.05). Despite vVT, vRCP, and vVO2max demonstrating a higher and inverse relationship with 3000-m time (r=-0.92; r =-0.96; r =-0.89; p<0.05), the multiple regression model indicated that vRCP and vVO2max are the best variables to predict 3000-m performance in experienced amateur road runners (R2=0.94). The equation proposed by the model was: 3000-m(s)=1399.21–[31.65*vRCP(km.h-1)]–[12.06*vVO2max (km.h-1)]. Conclusion: The vRCP and vVO2max may be used to predict 3000-m performance using only a maximal running test on a treadmill. In practical terms, coaches and physical conditioners can use performance in the 3000-m to select different exercise running intensities to prescribe exercise training intensities.
IMPACTING YOUTH LEADER SELF-EFFICACY

Leader self-efficacy (LSE) is associated with leader emergence and effectiveness, and is a strong predictor of both individual and group performance. While some research exists related to the connection between LSE and adult leadership, more studies are required to better understand the details surrounding LSE as it relates to adolescents. This mixed methods study examines the effects of a leadership development intervention on LSE in an eighth-grade student population. Results indicate strong support for the effectiveness of the intervention and its potential to increase youth LSE. This finding holds significant implications for educational practice, research, and the future of leadership development.
Optimal Scheduling of Cascade Reservoirs Based on an Integrated Multistrategy Particle Swarm Algorithm

The optimal scheduling of cascade reservoirs is an important water resource management and regulation method. In the actual operation process, its nonlinear, high-dimensional, and coupled characteristics become increasingly apparent under the influence of multiple constraints. In this study, an integrated multistrategy particle swarm optimization (IMPSO) algorithm is proposed to realize the optimal operation of mid- and long-term power generation in cascade reservoirs according to the solution problem in the scheduling process of cascade reservoirs. In IMPSO, a variety of effective improvement strategies are used, which are combined with the standard PSO algorithm in different steps, among which beta distribution initialization improves population diversity, parameter adaptive adjustment accelerates convergence speed, and the Lévy flight mechanism and adaptive variable spiral search strategy balance the global and local search capabilities of the algorithm. To handle complex constraints effectively, an explicit–implicit coupled constraint handling technique based on constraint normalization is designed to guide the update process into the feasible domain of the search space. The feasibility of the proposed method is verified in the mid- and long-term power generation optimization scheduling of the lower reaches of the Jinsha River–Three Gorges cascade hydropower reservoirs. The results show that the proposed method outperforms the other methods in terms of search accuracy and has the potential to improve hydropower resource utilization and power generation efficiency significantly.
Unicode ® Standard Annex # 29 UNICODE TEXT SEGMENTATION Version Unicode 15 . 1

A Unicode Standard Annex (UAX) forms an integral part of the Unicode Standard, but is published online as a separate document. The Unicode Standard may require conformance to normative content in a Unicode Standard Annex, if so specified in the Conformance chapter of that version of the Unicode Standard. The version number of a UAX document corresponds to the version of the Unicode Standard of which it forms a part.
A Very Simple Single Electron Lamb Shift Approximation

The Lamb shift was discovered by Willis Lamb and measured for the first time in 1947 by Lamb and Rutherford [1, 2, 3] on the hydrogen microwave spectrum. We suggest that the Lamb shift can be approximated by a very simple function that seems accurate enough for most experimenters working with elements where relativistic effects of the electron are minimal, that is up to element 80 or so. Even if our new approximation does not show anything new in physics, we think it can be useful for experimenters and students of quantum physics and chemistry; now everyone can calculate the Lamb shift on the back of an envelope.
Existence and influence of mixed states in a model of vegetation patterns

Abstract. The Rietkerk vegetation model is a system of partial differential equations, which has been used to understand the formation and dynamics of spatial patterns in vegetation ecosystems, including desertification and biodiversity loss. Here, we provide an in-depth bifurcation analysis of the vegetation patterns produced by Rietkerk's model, based on a linear stability analysis of the homogeneous equilibrium of the system. Specifically, using a continuation method based on the Newton–Raphson algorithm, we obtain all the main heterogeneous equilibria for a given size of the domain. We confirm that inhomogeneous vegetated states can exist and be stable, even for a value of rainfall for which no vegetation exists in the non-spatialized system. In addition, we evidence the existence of a new type of equilibrium, which we call “mixed state”, in which the equilibria are always unstable and take the form of a mix of two equilibria from the main branches. Although these equilibria are unstable, they influence the dynamics of the transitions between distinct stable states by slowing down the evolution of the system when it passes close to it. Our approach proves to be a helpful way to assess the existence of tipping points in spatially extended systems and disentangle the fate of the system in the Busse balloon. Overall, our findings represent a significant step forward in understanding the behaviour of the Rietkerk model and the broader dynamics of vegetation patterns.
Electrical conductivity in the mantle transition zone beneath Mongol-1 Okhotsk suture: revealed by the geomagnetic signals of ground 2 observatories

： The closure of the Mongo-Okhotsk ocean has a strong influence on the 9 tectonic evolution of Northeast China. However, the dynamic mechanism in the 10 Mongol-Okhotsk suture area is controversial. This paper intends to obtain the deep 11 structure of beneath Northeast China based on geomagnetic depth sounding, and 12 constrain the subduction of Mongol-Okhotsk Ocean from the perspective of electrical 13 properties. This paper collects and processes the data of geomagnetic stations in China 14 and adjacent areas, and obtains stable C -response data. The staggered grid finite 15 difference method is used for forward modeling, and the finite memory quasi Newton 16 method based on L 1 -norm is used for inversion. The three-dimensional inversion of 17 geomagnetic data is carried out in spherical coordinates. The intensive model testing 18 stations can obtain high-resolution underground electrical structures. The measured 19 data show that there are obvious high conductivity anomalies in the mantle transition 20 zone in Northeast China, especially in the west of the Great Xing’an Range, showing 21 an area of high conductivity anomalies. Combined with the regional tectonic 22 background of the region, we speculate that the high conductivity anomaly body is 23 related to the southward subduction of the Mongol-Okhotsk Ocean. The Mongol-24 Okhotsk Ocean subducted under the Eurasian plate at a small angle in the southward 25 direction. With the closing of the Okhotsk Ocean and the extension environment after 26 the termination of subduction, the subducted oceanic crust plate has been faulted and 27 depressed and partially stopped in the mantle transition zone.
Non-destructive multi-sensor core logging allows rapid imaging, measurement of bulk density and estimation of ice content in permafrost cores

Permafrost cores provide physical samples that can be used to measure the characteristics of frozen ground. 10 Measurement of core physical properties, however, are typically destructive and time intensive. In this study, multi-sensor core logging (MSCL) is used to provide a rapid, high-resolution, non-destructive method to image and collect the physical properties of permafrost cores, allowing the visualization of cryostructures, measurement of bulk density and magnetic susceptibility, and estimation of volumetric ice content. Six permafrost cores with differing properties were analyzed using MSCL and compared with established destructive analyses to assess the potential of this instrument both in terms of 15 accuracy and relative rate of data acquisition. A calibration procedure is presented for gamma ray attenuation from a 137 Cs source that is specific to frozen core materials. This accurately measures bulk density over the wide range of material densities found in permafrost. MSCL bulk density data show strong agreement with destructive analyses based on discrete sample measurements. Bulk density data from the gamma attenuation, along with soil density measurements for different sediment types, are used to estimate volumetric ice content. The results show strong agreement with destructive analyses, 20 illustrating that MSCL can provide accurate non-destructive estimates of ice contents and provide a digital archive of permafrost cores for future applications.
Modeling of a bimetallic eccentric cylindrical plasma waveguide based on a transmission line for TEM-mode

Abstract In this paper, a plasma waveguide made of two eccentric cylindrical metallic walls have been studied according to the theory of transmission lines. The inductance per unit length L, the capacitance per unit length C, the resistance per unit length R and the shunt conductance per unit length G are obtained. The graphs of variations of the mentioned parameters vs. geometrical dimensions of waveguide are investigated. This investigations have been done for two different types of plasma waveguide. At first stage, plasma region will be considered in cold and collisional approximation and in second stage, a drift plasma in cold collisionless approximation will be considered. Also, graphs of phase velocity variation vs. the main parameters of the waveguide are presented.
The effect of body composition on match physical performance in highly trained male football players

The aim of this study was to estimate the effect of body composition on match physical performance in highly trained male football players. For this purpose, body composition and match physical performance were collected over a five-month period from a Norwegian men´s team playing in the top division during the 2021 season. Dual energy X-ray absorptiometry (DXA) was used to collect information regarding the players´ body fat percentage [BF%] and lean muscle mass [LMM], while ZXY Sport Tracking system was used to collect match physical performance as total distance [TD], high intensity running [HIR], sprint distance [SpD], max speed and acceleration [ACC]. 15 players with mean (standard deviation) age, weight, and height of 24.8 (2.9) years, 77.4 (8.0) kg, and 181.7 (7.2) cm, constituted the sample. Due to missing observations, analysis was done both for complete and imputed cases, with the full dataset containing 62 observations. Linear-mixed modeling was used to estimate the effect of LMM and BF%, adjusted for playing position, on match physical performance. The largest associations were found between BF% and TD and between LMM and max speed, respectively. A one standard deviation increase in BF% decreased the relative total distance covered during match-play by ~0.3 standard deviations, while a one standard deviation increase in LMM increased max speed by ~0.3 standard deviations. However, the confidence intervals for all examined associations were wide, and no significant findings were found. Based on the results from this study, the effect of body composition on match physical performance is likely trivial compared to playing position.
FedTIU: Securing Virtualized PLCs Against DDoS Attacks Using a Federated Learning Enabled Threat Intelligence Unit

Conventional Programmable Logic Controller (PLC) systems are becoming increasingly challenging to manage due to hardware and software dependencies. Moreover, the number and size of conventional PLCs on factory floors continue to increase, and virtualized PLC (vPLC) offers a solution to address these challenges. The utilization of vPLC offers the advantages of streamlining communication between high-level applications and low-level machine operations, enhancing programming ability in process control systems by abstracting control functions from I/O modules, and increasing automation in industrial control networks. Nevertheless, the connection of vPLC to the internet and cloud services presents a considerable cybersecurity risk, and the crucial aspect of information security for vPLCs is ensuring their availability. Distributed Denial of Service (DDoS) attacks can be particularly devastating for vPLCs, as they rely on internet connectivity to function. DDoS attacks on vPLC overwhelm it and causing it to become unavailable. vPLCs manages control systems and if targeted by a DDoS attack, these systems could become unresponsive, leading to significant disruption to industrial processes. Thus, implementing effective DDoS protection measures is crucial for ensuring the availability and reliability of vPLCs in industrial settings. Therefore, this work proposes a Federated learning enabled Threat Intelligence Unit (FedTIU) for detecting DDoS attacks on vPLCs on an Edge Compute Stack near to vPLC. The proposed approach involves collaborative model training using federated learning techniques to gain knowledge of new attack patterns from other industrial sites while maintaining data privacy.
Emotion Identification in Speech Using Convolutional Neural Network and Long Short-Term Memory in Deep Learning

— The role of emotions in human mental health is extremely important. Since spontaneous emotions in real scenarios are more challenging to detect than other emotions, emotion recognition in real scenarios has attracted a lot of attention in affective computing recently. Motivated by the aid of using the numerous outcomes of various lengths of audio spectrograms on emotion identification, this paper proposes a Long Short-Term Memory (LSTM) model for speech emotion recognition. Initially, a deep convolutional neural network (CNN) version is used to research deep segment-stage capabilities at the foundation of the created image-like 3 channels of spectrograms. Then, a deep LSTM version is followed on the idea of the found-out segment-stage CNN capabilities to seize the temporal dependency amongst all divided segments in an utterance for utterance-stage emotion recognition. Finally, special emotion recognition results, received with the aid of using combining CNN with LSTM at more than one length of segment-stage spectrograms, are included with the aid of using the use of a score-stage fusion strategy.
An Analysis of Primary and Secondary School Enrolment and Inclusive Growth in Nigeria

Education is a key driver to the growth and development process of any economy. However, the development of the education sector has been a major constraint to many developing countries including Nigeria. Over time, economic activities in Nigeria have not been appreciable inclusive and this has affected the growth and development process of the country. In response to this challenge, this paper seeks to examine the impact of primary and secondary enrolments on inclusive economic growth in Nigeria. The time series data on school enrolment spanning the period of 1980 to 2016 were captured using the OLS econometric technique. The results of the analysis revealed that primary school enrolment is positive but statistically insignificant to economic growth, whilst secondary school enrolment is both positive and statistically significant to economic growth in Nigeria. The study recommends that education should be adequately and consistently funded at all levels. There should be concerted effort of every stakeholder towards getting every child of school age into school to give them education necessary for their effective participation in economic activities to make economic growth in Nigeria inclusive.
A controversial study on Random Forest Accuracy for Attack Detection

Machine learning based anomaly and attack detection is a topic under the spotlights for more than one decade. It is raising a signiﬁcant research eﬀort worldwide. The reasons of this interest lie in the ability of machine learning to introduce a large part of autonomy in the attacks detection process compared to the classical signature based approach, and then reduces the management cost of networks for NetOps, provides rapid and eﬃcient results, and is prone to detect 0d attacks. This paper conﬁrms this eﬃciency showing that using the simple Random Forest (RF) algorithms together with features selection allows detection ratio greater than 99%. However, despite a large set of attempts on the training stage for improving this detection ratio, RF never detects 100% of attacks. It especially always misses some attacks in the traﬃc, especially under-represented ones in the training dataset. False Negatives are certainly the most dramatic events for network security. In addition, it makes adversarial learning very easy to perform. This paper then presents a controversial study on machine learning based attack detection (using the signiﬁcantly illustrative RF example), and its trust-worthiness limits. This paper is then trying to break the current dogma that machine learning is THE solution for future cyber-security systems.
CARBON DIOXIDE EMISSION, INSTITUTIONAL QUALITY, AND ECONOMIC GROWTH: EMPIRICAL EVIDENCE FROM MALSYSIA

In view of Malaysia’s status as a fast-growing economy with accelerating carbon dioxide emissions, a better understanding of the relationship between economic growth and pollution is vital to the policy makers. This paper, therefore, attempts to investigate the existence of long run relationship among carbon dioxide emission, institutional quality, exports, and economic growth and further examines the causal relationship among these variables in Malaysia for the period 1984-2008. For the purpose of this study, both autoregressive distributed lag (ARDL) bound testing approach and Granger causality tests are employed. From the bounds test, it is found that a long run relationship does exist among the variables, even using different conditioning information sets. A positive and significant interaction term between carbon dioxide emission and institutional quality indicator (i.e. law and order) implies that good institutional quality is important in controlling carbon dioxide emission in the process of economic development. The results for Granger causality tests further confirm the importance of institutional frameworks in reducing carbon dioxide emissions since institutional quality is found not only affects economic growth directly, but also indirectly via carbon dioxide emissions. This indicates that sound institutional frameworks are essential for Malaysia to achieve high economic growth without sacrificing its environment.
A Three-Dimensional Variational Nodal Method for Pin-Resolved Neutron Transport Analysis of Pressurized Water Reactors

Abstract A three-dimensional variational nodal method (VNM) is presented for pressurized water reactor core calculations without fuel-moderator homogenization. The nodal functional is presented and discretized to obtain response matrix equations. Within the nodes, finite elements in the x-y plane and orthogonal polynomials in z are used to approximate the spatial flux distribution. On the lateral interfaces, orthogonal polynomials are employed. On the axial interfaces, the finite elements facilitate a spatially accurate current representation that has proven to be a challenge for the method of characteristics–based two-dimensional/one-dimensional approximations which typically rely on spatial homogenization. The angular discretization utilizes an even-parity integral method within the nodes, with the integrals evaluated using high-order Chebyshev-Legendre cubature. On the lateral and axial interfaces, low-order spherical harmonics (Pn) are augmented by high-order Pn expansions to which quasi-reflected conditions are applied. With quasi-reflected conditions, the solution converges to the high-order Pn solution for an infinite lattice of identical cells with no gradient, while the low-order Pn expansions handle global gradients in both the radial and axial directions. The method is implemented in the PANX code and applied first to a number of model problems to study convergence of the space-angle approximations and then to the C5G7 benchmark problems. Multigroup Monte Carlo solutions provide reference values for eigenvalues and pin-power distributions.
Organotin(IV) Complexes as Promising Potential Drug Candidates in the Field of Cancer Chemotherapy: A Narrative Review

Organotin(IV) complexes have a wide range of different applications. They are highly involved in pharmaceutical applications and have shown anticancer activity against various cancer cell lines. They act as antioxidants and can scavenge free radical species. The biological activity of organotin complexes depends on the organic moiety, type of substituents, number, type, and content of heteroatoms, and their geometry. The current review aimed to discuss using organotin complexes against different cancer cells.
A study of student spectator behavior at collegiate sporting events: the role of spectator attachment and interaction

ABSTRACT Understanding the behavior of student spectators is crucial for effectively promoting college sports events, as it is an emerging sector of the sports tourism industry. This study examined how student spectators evaluate their experience during college sports events across multidimensional behavior stages: spectator attachment, interaction and emotion, and satisfaction. A total of 229 college students in the United States completed an online survey. Results showed that spectator attachment positively influenced spectator interaction and emotion, which in turn had a positive impact on satisfaction. Spectator interaction and emotion also mediated the relationship between spectator attachment and satisfaction. The findings provide insights into the importance of student spectator attachment and interaction in generating positive emotions and satisfaction, with implications for sports tourism and marketing.
The Yang-Mills Gradient Flow and Loop Groups

We study the Yang-Mills gradient flow as a Morse function on the space A(P) of connection 1-forms on a principal G-bundle P over the sphere S 2 . The resulting Morse homology is compared to that of the loop group G. Via a hybrid moduli space approach we obtain an isomorphism between both Morse homologies, thereby confirming a conjecture due to Atiyah.